Skin Cancer Classification for Detecting Melanoma
Using
Transfer Learning and Ensemble Modeling

J-Component - Soft Computing

Made under the guidance of Dr. Agilandeeswari L

By:
Aashish Bansal 19BIT0346
Keerthi Yasasvi 19BIT03
Perumalla Sasank 19BIT03

The project is a Transfer Learning and CNN trained model which can predict whether the patient has a suffering from Cancer or not by checking the images of the infected areas on the body. The model has been trained on a variety of images through which it predicts the required. In this project, the image file of the patient is upload into a software, which is GUI-based interface, developed with the help of Tkinter, and it consists of the model saved as a file and the software uses that to analyze the image and give the prediction which can help doctors to start with the medication way faster instead of waiting for the laboratory reports for the confirmation. So basically,

• Skin cancer is an abnormal growth of skin cells. Most skin cancers are caused by exposure to ultraviolet (UV) light. When the skin is not protected, UV rays from sunlight or tanning beds can damage and alter skin's DNA that leads to the cancer.
• Deep learning model has been built to classify and identify the binary diagnostic group of melanocytic images obtained through dermoscopy.
• Based on the model, disease detection through dermal cell images has been investigated, and classifications on dermal cell images have been performed.

Ensembles are predictive models that combine predictions from two or more other models. Ensemble learning methods are popular and the goto technique when the best performance on a predictive modeling project is the most important outcome. Nevertheless, they are not always the most appropriate technique to use and beginners the field of applied machine learning have the expectation that ensembles or a specific ensemble method are always the best method to use. Ensembles offer two specific benefits on a predictive modeling project, and it is important to know what these benefits are and how to measure them to ensure that using an ensemble is the right decision on your project. In this tutorial, you will discover the benefits of using ensemble methods for machine learning. After reading this tutorial, you will know:

• A minimum benefit of using ensembles is to reduce the spread in the average skill of a predictive model.
• A key benefit of using ensembles is to improve the average prediction performance over any contributing member in the ensemble.
• The mechanism for improved performance with ensembles is often the reduction in the variance component of prediction errors made by the contributing models.

NOTE: IF YOU HAVE RUN THIS MODEL BEFORE, THEN TO RE-TRAIN THE MODEL FROM THE BEGINNING, YOU NEED TO DELETE THE LOGS CREATED IN THE TRAINING, VALIDATION AND TESTING DATA FROM THE LOCATION WHERE THE DATASET IS STORED.

1. Preprocessing

Flowchart:

1.1. Loading Libraries

All the Libraries being used in the model have been imported in the beginning of the model all together.

import numpy as np
from numpy import *
from numpy import average
from numpy import array

import pandas as pd
import os
import cv2
import csv
import scipy

import matplotlib.pyplot as plt
# import matplotlib.pylab as plt
%matplotlib inline

from sklearn.datasets import load_files
from sklearn.metrics import roc_curve, auc

import keras
from keras.preprocessing import image
from keras.preprocessing.image import img_to_array
from keras.preprocessing.image import load_img

from keras.utils import np_utils

from keras.models import Sequential
from keras.models import load_model
from keras.models import clone_model
from keras.models import Model
from keras.models import model_from_json

from keras.layers import Dense, GlobalAveragePooling2D, Flatten, BatchNormalization, Activation, Dropout
from keras.layers import Input
from keras.layers import Dense

from keras.callbacks import ModelCheckpoint, TensorBoard

from keras.applications.mobilenet import preprocess_input

from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
from tensorflow.python.keras.layers import Dense,Conv2D,Flatten,MaxPooling2D,GlobalAveragePooling2D,Activation,BatchNormalization,Dropout
from tensorflow.python.keras import Sequential,backend,optimizers


from tkinter import *

from PIL import ImageTk
from PIL import ImageFile
from PIL import Image

from tqdm import tqdm
import tqdm

from glob import glob

import seaborn as sns

ImageFile.LOAD_TRUNCATED_IMAGES = True

1.2. Loading Data

1.2.1. Mounting Google Drive

Please click on the Link generated and then choose the Google account, which contains the dataset, which is being authorised by you to access the dataset.

from google.colab import drive
drive.mount('/content/drive')

Mounted at /content/drive

1.2.2. Training Data

First the training data is being imported into the model via the Google Drive. The training data consists of 2000 images.

1.2.2.1. Importing Training Data

# Load text files with categories as subfolder names.
path_training_data = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Part3_GroundTruth.csv"
training_data = pd.read_csv(path_training_data)

1.2.2.2 Display the Training Data of the CSV File

training_data

	image_id	melanoma	seborrheic_keratosis
0	ISIC_0000000	0.0	0.0
1	ISIC_0000001	0.0	0.0
2	ISIC_0000002	1.0	0.0
3	ISIC_0000003	0.0	0.0
4	ISIC_0000004	1.0	0.0
...	...	...	...
1995	ISIC_0015220	0.0	1.0
1996	ISIC_0015233	0.0	1.0
1997	ISIC_0015260	0.0	1.0
1998	ISIC_0015284	1.0	0.0
1999	ISIC_0015295	0.0	1.0

2000 rows × 3 columns

print("Filename: \n", training_data['image_id'][:5])

Filename: 
 0    ISIC_0000000
1    ISIC_0000001
2    ISIC_0000002
3    ISIC_0000003
4    ISIC_0000004
Name: image_id, dtype: object

print("Targets: \n", training_data['melanoma'][:5])

Targets: 
 0    0.0
1    0.0
2    1.0
3    0.0
4    1.0
Name: melanoma, dtype: float64

1.2.2.3 Obtaining the Labels of all the Images as One-Hot Encoding

# Getting the labels
target = np_utils.to_categorical(np.array(training_data['melanoma']), 2)
target

array([[1., 0.],
       [1., 0.],
       [0., 1.],
       ...,
       [1., 0.],
       [0., 1.],
       [1., 0.]], dtype=float32)

1.2.2.4 Checking the Number of Training Images

len(training_data['image_id'])

2000

1.2.2.5 Loading the Image Filenames

# Splitting the data into the training and validation set
#load_dataset('/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/')
train_files, train_targets = training_data['image_id'][:2000], target[:2000]

train_files

0       ISIC_0000000
1       ISIC_0000001
2       ISIC_0000002
3       ISIC_0000003
4       ISIC_0000004
            ...     
1995    ISIC_0015220
1996    ISIC_0015233
1997    ISIC_0015260
1998    ISIC_0015284
1999    ISIC_0015295
Name: image_id, Length: 2000, dtype: object

train_targets

array([[1., 0.],
       [1., 0.],
       [0., 1.],
       ...,
       [1., 0.],
       [0., 1.],
       [1., 0.]], dtype=float32)

1.2.3 Validation Data

Now, we will be importing the Validation data into the model via the Google Drive. The training data consists of 150 images.

1.2.3.1. Importing Validation Dataset

# Load text files with categories as subfolder names.
path_validation_data = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Part3_GroundTruth.csv"
validation_data = pd.read_csv(path_validation_data)

1.2.3.2 Display the Validation Data of the CSV File

validation_data

	image_id	melanoma	seborrheic_keratosis
0	ISIC_0001769	0.0	0.0
1	ISIC_0001852	0.0	0.0
2	ISIC_0001871	0.0	0.0
3	ISIC_0003462	0.0	0.0
4	ISIC_0003539	0.0	0.0
...	...	...	...
145	ISIC_0015443	0.0	0.0
146	ISIC_0015445	0.0	0.0
147	ISIC_0015483	0.0	0.0
148	ISIC_0015496	0.0	0.0
149	ISIC_0015627	0.0	0.0

150 rows × 3 columns

print("Filename: \n", validation_data['image_id'][:5])

Filename: 
 0    ISIC_0001769
1    ISIC_0001852
2    ISIC_0001871
3    ISIC_0003462
4    ISIC_0003539
Name: image_id, dtype: object

print("Targets: \n", validation_data['melanoma'][:5])

Targets: 
 0    0.0
1    0.0
2    0.0
3    0.0
4    0.0
Name: melanoma, dtype: float64

1.2.3.3 Obtaining the Labels of all the Images as One-Hot Encoding

# Getting the labels
target = np_utils.to_categorical(np.array(validation_data['melanoma']), 2)
target

array([[1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.]], dtype=float32)

1.2.3.4. Checking the Number of Validation Images

len(validation_data['image_id'])

150

1.2.3.5 Loading the Images Filenames of the Validation Data

# train_files, train_targets = training_data['image_id'][:2000], target[:2000]
valid_files, valid_targets = validation_data['image_id'][:150], target[:150]

valid_files

0      ISIC_0001769
1      ISIC_0001852
2      ISIC_0001871
3      ISIC_0003462
4      ISIC_0003539
           ...     
145    ISIC_0015443
146    ISIC_0015445
147    ISIC_0015483
148    ISIC_0015496
149    ISIC_0015627
Name: image_id, Length: 150, dtype: object

valid_targets

array([[1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [0., 1.],
       [0., 1.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.],
       [1., 0.]], dtype=float32)

1.2.4. Testing Data

Now, we will be importing the Testing data into the model via the Google Drive. The Testing data consists of 600 images.

1.2.4.1. Importing Testing Dataset

# Load text files with categories as subfolder names.
path_testing_data = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Part3_GroundTruth.csv"
testing_data = pd.read_csv(path_testing_data)

1.2.4.2. Display the Testing Data of the CSV File

testing_data

	image_id	melanoma	seborrheic_keratosis
0	ISIC_0012086	0.0	1.0
1	ISIC_0012092	0.0	0.0
2	ISIC_0012095	0.0	0.0
3	ISIC_0012134	0.0	1.0
4	ISIC_0012136	0.0	1.0
...	...	...	...
595	ISIC_0016068	0.0	0.0
596	ISIC_0016069	0.0	0.0
597	ISIC_0016070	0.0	0.0
598	ISIC_0016071	0.0	0.0
599	ISIC_0016072	0.0	0.0

600 rows × 3 columns

print("Filename: \n", testing_data['image_id'][:5])

Filename: 
 0    ISIC_0012086
1    ISIC_0012092
2    ISIC_0012095
3    ISIC_0012134
4    ISIC_0012136
Name: image_id, dtype: object

print("Targets: \n", testing_data['melanoma'][:5])

Targets: 
 0    0.0
1    0.0
2    0.0
3    0.0
4    0.0
Name: melanoma, dtype: float64

1.2.4.3. Obtaining the Labels of all the Images as One-Hot Encoding

# Getting the labels
test_target = np_utils.to_categorical(np.array(testing_data['melanoma']), 2)
test_target

array([[1., 0.],
       [1., 0.],
       [1., 0.],
       ...,
       [1., 0.],
       [1., 0.],
       [1., 0.]], dtype=float32)

1.2.4.4. Checking the Number of Testing Images

len(testing_data['image_id'])

600

1.2.4.5. Loading the Images Filenames of the Testing Data

# train_files, train_targets = training_data['image_id'][:2000], target[:2000]
test_files, test_targets = testing_data['image_id'][:600], test_target[:600]

test_files

0      ISIC_0012086
1      ISIC_0012092
2      ISIC_0012095
3      ISIC_0012134
4      ISIC_0012136
           ...     
595    ISIC_0016068
596    ISIC_0016069
597    ISIC_0016070
598    ISIC_0016071
599    ISIC_0016072
Name: image_id, Length: 600, dtype: object

len(test_targets)

600

test_targets

array([[1., 0.],
       [1., 0.],
       [1., 0.],
       ...,
       [1., 0.],
       [1., 0.],
       [1., 0.]], dtype=float32)

1.3. Image preprocessing

# Importing the libraries
import keras
from keras.preprocessing import image                  
from tqdm import tqdm
from PIL import ImageFile                            
ImageFile.LOAD_TRUNCATED_IMAGES = True

def path_to_tensor(img_path):
    """
    Getting a tensor from a given path.
    """
    # Loading the image
    img = image.load_img(img_path, target_size=(512, 512))
    # Converting the image to numpy array
    x = image.img_to_array(img)
    # convert 3D tensor to 4D tensor with shape (1, 512, 512, 3)
    return np.expand_dims(x, axis=0)

def paths_to_tensor(img_paths):
    """
    # Getting a list of tensors from a given path directory.
    """
    list_of_tensors = [path_to_tensor(img_path) for img_path in tqdm(img_paths)]
    return np.vstack(list_of_tensors)

1.3.1 Training Data

1.3.1.1. Display the Filenames of Training Data

train_files

0       ISIC_0000000
1       ISIC_0000001
2       ISIC_0000002
3       ISIC_0000003
4       ISIC_0000004
            ...     
1995    ISIC_0015220
1996    ISIC_0015233
1997    ISIC_0015260
1998    ISIC_0015284
1999    ISIC_0015295
Name: image_id, Length: 2000, dtype: object

1.3.1.2. DIsplay all the Filenames present in the Dataset Directory

import os
os.chdir("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/")
!ls

ISIC_0000000.jpg  ISIC_0002885.jpg  ISIC_0011227.jpg  ISIC_0013474.jpg
ISIC_0000001.jpg  ISIC_0002948.jpg  ISIC_0011229.jpg  ISIC_0013480.jpg
ISIC_0000002.jpg  ISIC_0002975.jpg  ISIC_0011230.jpg  ISIC_0013486.jpg
ISIC_0000003.jpg  ISIC_0002976.jpg  ISIC_0011292.jpg  ISIC_0013487.jpg
ISIC_0000004.jpg  ISIC_0003005.jpg  ISIC_0011294.jpg  ISIC_0013488.jpg
ISIC_0000006.jpg  ISIC_0003051.jpg  ISIC_0011296.jpg  ISIC_0013489.jpg
ISIC_0000007.jpg  ISIC_0003056.jpg  ISIC_0011297.jpg  ISIC_0013490.jpg
ISIC_0000008.jpg  ISIC_0003174.jpg  ISIC_0011298.jpg  ISIC_0013492.jpg
ISIC_0000009.jpg  ISIC_0003308.jpg  ISIC_0011300.jpg  ISIC_0013493.jpg
ISIC_0000010.jpg  ISIC_0003346.jpg  ISIC_0011303.jpg  ISIC_0013494.jpg
ISIC_0000011.jpg  ISIC_0003728.jpg  ISIC_0011304.jpg  ISIC_0013495.jpg
ISIC_0000012.jpg  ISIC_0004110.jpg  ISIC_0011305.jpg  ISIC_0013497.jpg
ISIC_0000013.jpg  ISIC_0004115.jpg  ISIC_0011306.jpg  ISIC_0013498.jpg
ISIC_0000014.jpg  ISIC_0004166.jpg  ISIC_0011310.jpg  ISIC_0013499.jpg
ISIC_0000015.jpg  ISIC_0004168.jpg  ISIC_0011315.jpg  ISIC_0013500.jpg
ISIC_0000016.jpg  ISIC_0004309.jpg  ISIC_0011317.jpg  ISIC_0013516.jpg
ISIC_0000017.jpg  ISIC_0004346.jpg  ISIC_0011321.jpg  ISIC_0013517.jpg
ISIC_0000018.jpg  ISIC_0004715.jpg  ISIC_0011322.jpg  ISIC_0013523.jpg
ISIC_0000019.jpg  ISIC_0004985.jpg  ISIC_0011324.jpg  ISIC_0013525.jpg
ISIC_0000020.jpg  ISIC_0005000.jpg  ISIC_0011326.jpg  ISIC_0013526.jpg
ISIC_0000021.jpg  ISIC_0005187.jpg  ISIC_0011327.jpg  ISIC_0013530.jpg
ISIC_0000022.jpg  ISIC_0005548.jpg  ISIC_0011328.jpg  ISIC_0013552.jpg
ISIC_0000023.jpg  ISIC_0005555.jpg  ISIC_0011330.jpg  ISIC_0013553.jpg
ISIC_0000024.jpg  ISIC_0005620.jpg  ISIC_0011333.jpg  ISIC_0013554.jpg
ISIC_0000025.jpg  ISIC_0005639.jpg  ISIC_0011336.jpg  ISIC_0013558.jpg
ISIC_0000026.jpg  ISIC_0005666.jpg  ISIC_0011338.jpg  ISIC_0013559.jpg
ISIC_0000027.jpg  ISIC_0005787.jpg  ISIC_0011339.jpg  ISIC_0013567.jpg
ISIC_0000028.jpg  ISIC_0006021.jpg  ISIC_0011343.jpg  ISIC_0013568.jpg
ISIC_0000029.jpg  ISIC_0006114.jpg  ISIC_0011344.jpg  ISIC_0013572.jpg
ISIC_0000030.jpg  ISIC_0006193.jpg  ISIC_0011345.jpg  ISIC_0013573.jpg
ISIC_0000031.jpg  ISIC_0006326.jpg  ISIC_0011347.jpg  ISIC_0013578.jpg
ISIC_0000032.jpg  ISIC_0006350.jpg  ISIC_0011348.jpg  ISIC_0013579.jpg
ISIC_0000034.jpg  ISIC_0006612.jpg  ISIC_0011349.jpg  ISIC_0013580.jpg
ISIC_0000035.jpg  ISIC_0006711.jpg  ISIC_0011352.jpg  ISIC_0013581.jpg
ISIC_0000036.jpg  ISIC_0006776.jpg  ISIC_0011353.jpg  ISIC_0013584.jpg
ISIC_0000037.jpg  ISIC_0006795.jpg  ISIC_0011358.jpg  ISIC_0013585.jpg
ISIC_0000038.jpg  ISIC_0006800.jpg  ISIC_0011359.jpg  ISIC_0013592.jpg
ISIC_0000039.jpg  ISIC_0006940.jpg  ISIC_0011361.jpg  ISIC_0013594.jpg
ISIC_0000040.jpg  ISIC_0006982.jpg  ISIC_0011362.jpg  ISIC_0013595.jpg
ISIC_0000041.jpg  ISIC_0007038.jpg  ISIC_0011363.jpg  ISIC_0013596.jpg
ISIC_0000042.jpg  ISIC_0007087.jpg  ISIC_0011366.jpg  ISIC_0013597.jpg
ISIC_0000043.jpg  ISIC_0007322.jpg  ISIC_0011367.jpg  ISIC_0013599.jpg
ISIC_0000044.jpg  ISIC_0007475.jpg  ISIC_0011372.jpg  ISIC_0013601.jpg
ISIC_0000045.jpg  ISIC_0007557.jpg  ISIC_0011382.jpg  ISIC_0013603.jpg
ISIC_0000046.jpg  ISIC_0007693.jpg  ISIC_0011384.jpg  ISIC_0013606.jpg
ISIC_0000047.jpg  ISIC_0007760.jpg  ISIC_0011386.jpg  ISIC_0013610.jpg
ISIC_0000048.jpg  ISIC_0008029.jpg  ISIC_0011387.jpg  ISIC_0013618.jpg
ISIC_0000049.jpg  ISIC_0008116.jpg  ISIC_0011393.jpg  ISIC_0013621.jpg
ISIC_0000050.jpg  ISIC_0008145.jpg  ISIC_0011397.jpg  ISIC_0013625.jpg
ISIC_0000051.jpg  ISIC_0008207.jpg  ISIC_0011398.jpg  ISIC_0013626.jpg
ISIC_0000052.jpg  ISIC_0008236.jpg  ISIC_0011402.jpg  ISIC_0013634.jpg
ISIC_0000053.jpg  ISIC_0008256.jpg  ISIC_0012089.jpg  ISIC_0013635.jpg
ISIC_0000054.jpg  ISIC_0008280.jpg  ISIC_0012090.jpg  ISIC_0013639.jpg
ISIC_0000055.jpg  ISIC_0008294.jpg  ISIC_0012094.jpg  ISIC_0013643.jpg
ISIC_0000056.jpg  ISIC_0008347.jpg  ISIC_0012097.jpg  ISIC_0013652.jpg
ISIC_0000057.jpg  ISIC_0008396.jpg  ISIC_0012102.jpg  ISIC_0013656.jpg
ISIC_0000059.jpg  ISIC_0008403.jpg  ISIC_0012103.jpg  ISIC_0013664.jpg
ISIC_0000061.jpg  ISIC_0008406.jpg  ISIC_0012105.jpg  ISIC_0013667.jpg
ISIC_0000062.jpg  ISIC_0008507.jpg  ISIC_0012107.jpg  ISIC_0013670.jpg
ISIC_0000063.jpg  ISIC_0008528.jpg  ISIC_0012108.jpg  ISIC_0013671.jpg
ISIC_0000064.jpg  ISIC_0008541.jpg  ISIC_0012116.jpg  ISIC_0013672.jpg
ISIC_0000065.jpg  ISIC_0008552.jpg  ISIC_0012117.jpg  ISIC_0013674.jpg
ISIC_0000066.jpg  ISIC_0008600.jpg  ISIC_0012118.jpg  ISIC_0013675.jpg
ISIC_0000067.jpg  ISIC_0008626.jpg  ISIC_0012135.jpg  ISIC_0013676.jpg
ISIC_0000068.jpg  ISIC_0008659.jpg  ISIC_0012137.jpg  ISIC_0013680.jpg
ISIC_0000069.jpg  ISIC_0008785.jpg  ISIC_0012141.jpg  ISIC_0013682.jpg
ISIC_0000071.jpg  ISIC_0008807.jpg  ISIC_0012148.jpg  ISIC_0013684.jpg
ISIC_0000072.jpg  ISIC_0008879.jpg  ISIC_0012150.jpg  ISIC_0013685.jpg
ISIC_0000073.jpg  ISIC_0008992.jpg  ISIC_0012155.jpg  ISIC_0013687.jpg
ISIC_0000074.jpg  ISIC_0008993.jpg  ISIC_0012156.jpg  ISIC_0013688.jpg
ISIC_0000075.jpg  ISIC_0008998.jpg  ISIC_0012164.jpg  ISIC_0013689.jpg
ISIC_0000077.jpg  ISIC_0009035.jpg  ISIC_0012167.jpg  ISIC_0013690.jpg
ISIC_0000078.jpg  ISIC_0009078.jpg  ISIC_0012170.jpg  ISIC_0013691.jpg
ISIC_0000079.jpg  ISIC_0009083.jpg  ISIC_0012172.jpg  ISIC_0013695.jpg
ISIC_0000080.jpg  ISIC_0009160.jpg  ISIC_0012173.jpg  ISIC_0013706.jpg
ISIC_0000081.jpg  ISIC_0009165.jpg  ISIC_0012175.jpg  ISIC_0013707.jpg
ISIC_0000082.jpg  ISIC_0009188.jpg  ISIC_0012177.jpg  ISIC_0013709.jpg
ISIC_0000085.jpg  ISIC_0009252.jpg  ISIC_0012179.jpg  ISIC_0013712.jpg
ISIC_0000086.jpg  ISIC_0009297.jpg  ISIC_0012182.jpg  ISIC_0013713.jpg
ISIC_0000087.jpg  ISIC_0009298.jpg  ISIC_0012183.jpg  ISIC_0013719.jpg
ISIC_0000088.jpg  ISIC_0009344.jpg  ISIC_0012187.jpg  ISIC_0013721.jpg
ISIC_0000089.jpg  ISIC_0009430.jpg  ISIC_0012203.jpg  ISIC_0013725.jpg
ISIC_0000091.jpg  ISIC_0009504.jpg  ISIC_0012205.jpg  ISIC_0013731.jpg
ISIC_0000092.jpg  ISIC_0009533.jpg  ISIC_0012208.jpg  ISIC_0013737.jpg
ISIC_0000093.jpg  ISIC_0009564.jpg  ISIC_0012209.jpg  ISIC_0013740.jpg
ISIC_0000094.jpg  ISIC_0009583.jpg  ISIC_0012211.jpg  ISIC_0013742.jpg
ISIC_0000095.jpg  ISIC_0009599.jpg  ISIC_0012212.jpg  ISIC_0013747.jpg
ISIC_0000096.jpg  ISIC_0009758.jpg  ISIC_0012213.jpg  ISIC_0013748.jpg
ISIC_0000097.jpg  ISIC_0009860.jpg  ISIC_0012214.jpg  ISIC_0013749.jpg
ISIC_0000098.jpg  ISIC_0009868.jpg  ISIC_0012217.jpg  ISIC_0013758.jpg
ISIC_0000099.jpg  ISIC_0009869.jpg  ISIC_0012224.jpg  ISIC_0013762.jpg
ISIC_0000100.jpg  ISIC_0009870.jpg  ISIC_0012227.jpg  ISIC_0013765.jpg
ISIC_0000101.jpg  ISIC_0009871.jpg  ISIC_0012228.jpg  ISIC_0013772.jpg
ISIC_0000102.jpg  ISIC_0009872.jpg  ISIC_0012230.jpg  ISIC_0013775.jpg
ISIC_0000103.jpg  ISIC_0009873.jpg  ISIC_0012232.jpg  ISIC_0013777.jpg
ISIC_0000104.jpg  ISIC_0009874.jpg  ISIC_0012233.jpg  ISIC_0013778.jpg
ISIC_0000105.jpg  ISIC_0009875.jpg  ISIC_0012235.jpg  ISIC_0013782.jpg
ISIC_0000107.jpg  ISIC_0009877.jpg  ISIC_0012237.jpg  ISIC_0013783.jpg
ISIC_0000108.jpg  ISIC_0009879.jpg  ISIC_0012238.jpg  ISIC_0013789.jpg
ISIC_0000109.jpg  ISIC_0009880.jpg  ISIC_0012245.jpg  ISIC_0013792.jpg
ISIC_0000110.jpg  ISIC_0009881.jpg  ISIC_0012246.jpg  ISIC_0013795.jpg
ISIC_0000111.jpg  ISIC_0009882.jpg  ISIC_0012250.jpg  ISIC_0013796.jpg
ISIC_0000112.jpg  ISIC_0009883.jpg  ISIC_0012253.jpg  ISIC_0013797.jpg
ISIC_0000113.jpg  ISIC_0009884.jpg  ISIC_0012257.jpg  ISIC_0013798.jpg
ISIC_0000116.jpg  ISIC_0009885.jpg  ISIC_0012259.jpg  ISIC_0013799.jpg
ISIC_0000118.jpg  ISIC_0009888.jpg  ISIC_0012260.jpg  ISIC_0013800.jpg
ISIC_0000119.jpg  ISIC_0009889.jpg  ISIC_0012261.jpg  ISIC_0013801.jpg
ISIC_0000120.jpg  ISIC_0009891.jpg  ISIC_0012263.jpg  ISIC_0013802.jpg
ISIC_0000121.jpg  ISIC_0009895.jpg  ISIC_0012268.jpg  ISIC_0013803.jpg
ISIC_0000122.jpg  ISIC_0009896.jpg  ISIC_0012271.jpg  ISIC_0013804.jpg
ISIC_0000123.jpg  ISIC_0009897.jpg  ISIC_0012274.jpg  ISIC_0013805.jpg
ISIC_0000124.jpg  ISIC_0009898.jpg  ISIC_0012278.jpg  ISIC_0013806.jpg
ISIC_0000125.jpg  ISIC_0009899.jpg  ISIC_0012281.jpg  ISIC_0013807.jpg
ISIC_0000126.jpg  ISIC_0009901.jpg  ISIC_0012282.jpg  ISIC_0013808.jpg
ISIC_0000127.jpg  ISIC_0009902.jpg  ISIC_0012284.jpg  ISIC_0013815.jpg
ISIC_0000128.jpg  ISIC_0009905.jpg  ISIC_0012285.jpg  ISIC_0013816.jpg
ISIC_0000129.jpg  ISIC_0009906.jpg  ISIC_0012290.jpg  ISIC_0013817.jpg
ISIC_0000130.jpg  ISIC_0009909.jpg  ISIC_0012291.jpg  ISIC_0013819.jpg
ISIC_0000131.jpg  ISIC_0009910.jpg  ISIC_0012294.jpg  ISIC_0013830.jpg
ISIC_0000132.jpg  ISIC_0009911.jpg  ISIC_0012298.jpg  ISIC_0013831.jpg
ISIC_0000133.jpg  ISIC_0009912.jpg  ISIC_0012299.jpg  ISIC_0013832.jpg
ISIC_0000134.jpg  ISIC_0009914.jpg  ISIC_0012303.jpg  ISIC_0013835.jpg
ISIC_0000135.jpg  ISIC_0009915.jpg  ISIC_0012309.jpg  ISIC_0013836.jpg
ISIC_0000136.jpg  ISIC_0009917.jpg  ISIC_0012311.jpg  ISIC_0013837.jpg
ISIC_0000137.jpg  ISIC_0009918.jpg  ISIC_0012318.jpg  ISIC_0013839.jpg
ISIC_0000138.jpg  ISIC_0009919.jpg  ISIC_0012320.jpg  ISIC_0013840.jpg
ISIC_0000139.jpg  ISIC_0009920.jpg  ISIC_0012322.jpg  ISIC_0013841.jpg
ISIC_0000140.jpg  ISIC_0009921.jpg  ISIC_0012324.jpg  ISIC_0013843.jpg
ISIC_0000141.jpg  ISIC_0009923.jpg  ISIC_0012325.jpg  ISIC_0013844.jpg
ISIC_0000142.jpg  ISIC_0009925.jpg  ISIC_0012329.jpg  ISIC_0013845.jpg
ISIC_0000143.jpg  ISIC_0009929.jpg  ISIC_0012332.jpg  ISIC_0013861.jpg
ISIC_0000145.jpg  ISIC_0009930.jpg  ISIC_0012333.jpg  ISIC_0013862.jpg
ISIC_0000146.jpg  ISIC_0009931.jpg  ISIC_0012334.jpg  ISIC_0013864.jpg
ISIC_0000147.jpg  ISIC_0009932.jpg  ISIC_0012338.jpg  ISIC_0013865.jpg
ISIC_0000148.jpg  ISIC_0009933.jpg  ISIC_0012339.jpg  ISIC_0013874.jpg
ISIC_0000149.jpg  ISIC_0009935.jpg  ISIC_0012342.jpg  ISIC_0013876.jpg
ISIC_0000150.jpg  ISIC_0009936.jpg  ISIC_0012348.jpg  ISIC_0013879.jpg
ISIC_0000151.jpg  ISIC_0009937.jpg  ISIC_0012351.jpg  ISIC_0013886.jpg
ISIC_0000152.jpg  ISIC_0009938.jpg  ISIC_0012359.jpg  ISIC_0013888.jpg
ISIC_0000153.jpg  ISIC_0009939.jpg  ISIC_0012360.jpg  ISIC_0013890.jpg
ISIC_0000154.jpg  ISIC_0009940.jpg  ISIC_0012363.jpg  ISIC_0013896.jpg
ISIC_0000155.jpg  ISIC_0009941.jpg  ISIC_0012374.jpg  ISIC_0013910.jpg
ISIC_0000156.jpg  ISIC_0009942.jpg  ISIC_0012376.jpg  ISIC_0013918.jpg
ISIC_0000157.jpg  ISIC_0009943.jpg  ISIC_0012377.jpg  ISIC_0013921.jpg
ISIC_0000159.jpg  ISIC_0009945.jpg  ISIC_0012378.jpg  ISIC_0013922.jpg
ISIC_0000160.jpg  ISIC_0009946.jpg  ISIC_0012379.jpg  ISIC_0013927.jpg
ISIC_0000161.jpg  ISIC_0009947.jpg  ISIC_0012381.jpg  ISIC_0013929.jpg
ISIC_0000162.jpg  ISIC_0009949.jpg  ISIC_0012382.jpg  ISIC_0013933.jpg
ISIC_0000163.jpg  ISIC_0009950.jpg  ISIC_0012384.jpg  ISIC_0013935.jpg
ISIC_0000164.jpg  ISIC_0009951.jpg  ISIC_0012386.jpg  ISIC_0013936.jpg
ISIC_0000165.jpg  ISIC_0009953.jpg  ISIC_0012390.jpg  ISIC_0013942.jpg
ISIC_0000166.jpg  ISIC_0009954.jpg  ISIC_0012391.jpg  ISIC_0013946.jpg
ISIC_0000167.jpg  ISIC_0009955.jpg  ISIC_0012397.jpg  ISIC_0013958.jpg
ISIC_0000169.jpg  ISIC_0009956.jpg  ISIC_0012406.jpg  ISIC_0013961.jpg
ISIC_0000171.jpg  ISIC_0009958.jpg  ISIC_0012413.jpg  ISIC_0013962.jpg
ISIC_0000172.jpg  ISIC_0009960.jpg  ISIC_0012415.jpg  ISIC_0013965.jpg
ISIC_0000174.jpg  ISIC_0009961.jpg  ISIC_0012416.jpg  ISIC_0013967.jpg
ISIC_0000176.jpg  ISIC_0009962.jpg  ISIC_0012433.jpg  ISIC_0013969.jpg
ISIC_0000177.jpg  ISIC_0009963.jpg  ISIC_0012435.jpg  ISIC_0013970.jpg
ISIC_0000179.jpg  ISIC_0009964.jpg  ISIC_0012442.jpg  ISIC_0013971.jpg
ISIC_0000181.jpg  ISIC_0009965.jpg  ISIC_0012445.jpg  ISIC_0013972.jpg
ISIC_0000182.jpg  ISIC_0009966.jpg  ISIC_0012450.jpg  ISIC_0013975.jpg
ISIC_0000184.jpg  ISIC_0009967.jpg  ISIC_0012452.jpg  ISIC_0013980.jpg
ISIC_0000185.jpg  ISIC_0009968.jpg  ISIC_0012453.jpg  ISIC_0013981.jpg
ISIC_0000186.jpg  ISIC_0009969.jpg  ISIC_0012455.jpg  ISIC_0013982.jpg
ISIC_0000188.jpg  ISIC_0009971.jpg  ISIC_0012459.jpg  ISIC_0013983.jpg
ISIC_0000189.jpg  ISIC_0009972.jpg  ISIC_0012460.jpg  ISIC_0013984.jpg
ISIC_0000190.jpg  ISIC_0009973.jpg  ISIC_0012464.jpg  ISIC_0013986.jpg
ISIC_0000191.jpg  ISIC_0009974.jpg  ISIC_0012469.jpg  ISIC_0013995.jpg
ISIC_0000192.jpg  ISIC_0009975.jpg  ISIC_0012473.jpg  ISIC_0013996.jpg
ISIC_0000193.jpg  ISIC_0009976.jpg  ISIC_0012475.jpg  ISIC_0013997.jpg
ISIC_0000196.jpg  ISIC_0009977.jpg  ISIC_0012478.jpg  ISIC_0014001.jpg
ISIC_0000197.jpg  ISIC_0009979.jpg  ISIC_0012481.jpg  ISIC_0014004.jpg
ISIC_0000198.jpg  ISIC_0009981.jpg  ISIC_0012487.jpg  ISIC_0014013.jpg
ISIC_0000199.jpg  ISIC_0009982.jpg  ISIC_0012489.jpg  ISIC_0014026.jpg
ISIC_0000201.jpg  ISIC_0009987.jpg  ISIC_0012494.jpg  ISIC_0014028.jpg
ISIC_0000202.jpg  ISIC_0009991.jpg  ISIC_0012495.jpg  ISIC_0014029.jpg
ISIC_0000203.jpg  ISIC_0009993.jpg  ISIC_0012496.jpg  ISIC_0014031.jpg
ISIC_0000204.jpg  ISIC_0009994.jpg  ISIC_0012501.jpg  ISIC_0014032.jpg
ISIC_0000205.jpg  ISIC_0009998.jpg  ISIC_0012503.jpg  ISIC_0014044.jpg
ISIC_0000206.jpg  ISIC_0010000.jpg  ISIC_0012506.jpg  ISIC_0014045.jpg
ISIC_0000207.jpg  ISIC_0010002.jpg  ISIC_0012508.jpg  ISIC_0014046.jpg
ISIC_0000208.jpg  ISIC_0010003.jpg  ISIC_0012511.jpg  ISIC_0014049.jpg
ISIC_0000209.jpg  ISIC_0010005.jpg  ISIC_0012512.jpg  ISIC_0014061.jpg
ISIC_0000211.jpg  ISIC_0010006.jpg  ISIC_0012516.jpg  ISIC_0014062.jpg
ISIC_0000212.jpg  ISIC_0010011.jpg  ISIC_0012517.jpg  ISIC_0014066.jpg
ISIC_0000213.jpg  ISIC_0010013.jpg  ISIC_0012518.jpg  ISIC_0014069.jpg
ISIC_0000214.jpg  ISIC_0010014.jpg  ISIC_0012520.jpg  ISIC_0014072.jpg
ISIC_0000215.jpg  ISIC_0010015.jpg  ISIC_0012521.jpg  ISIC_0014073.jpg
ISIC_0000216.jpg  ISIC_0010016.jpg  ISIC_0012523.jpg  ISIC_0014074.jpg
ISIC_0000217.jpg  ISIC_0010017.jpg  ISIC_0012526.jpg  ISIC_0014076.jpg
ISIC_0000218.jpg  ISIC_0010018.jpg  ISIC_0012527.jpg  ISIC_0014079.jpg
ISIC_0000219.jpg  ISIC_0010019.jpg  ISIC_0012529.jpg  ISIC_0014080.jpg
ISIC_0000220.jpg  ISIC_0010020.jpg  ISIC_0012539.jpg  ISIC_0014081.jpg
ISIC_0000221.jpg  ISIC_0010021.jpg  ISIC_0012543.jpg  ISIC_0014082.jpg
ISIC_0000222.jpg  ISIC_0010022.jpg  ISIC_0012544.jpg  ISIC_0014083.jpg
ISIC_0000223.jpg  ISIC_0010024.jpg  ISIC_0012549.jpg  ISIC_0014088.jpg
ISIC_0000224.jpg  ISIC_0010025.jpg  ISIC_0012550.jpg  ISIC_0014089.jpg
ISIC_0000225.jpg  ISIC_0010028.jpg  ISIC_0012653.jpg  ISIC_0014092.jpg
ISIC_0000226.jpg  ISIC_0010029.jpg  ISIC_0012655.jpg  ISIC_0014093.jpg
ISIC_0000227.jpg  ISIC_0010032.jpg  ISIC_0012657.jpg  ISIC_0014094.jpg
ISIC_0000229.jpg  ISIC_0010034.jpg  ISIC_0012658.jpg  ISIC_0014099.jpg
ISIC_0000231.jpg  ISIC_0010036.jpg  ISIC_0012659.jpg  ISIC_0014108.jpg
ISIC_0000232.jpg  ISIC_0010040.jpg  ISIC_0012661.jpg  ISIC_0014114.jpg
ISIC_0000233.jpg  ISIC_0010042.jpg  ISIC_0012662.jpg  ISIC_0014120.jpg
ISIC_0000234.jpg  ISIC_0010043.jpg  ISIC_0012663.jpg  ISIC_0014127.jpg
ISIC_0000235.jpg  ISIC_0010044.jpg  ISIC_0012664.jpg  ISIC_0014131.jpg
ISIC_0000236.jpg  ISIC_0010046.jpg  ISIC_0012665.jpg  ISIC_0014132.jpg
ISIC_0000237.jpg  ISIC_0010047.jpg  ISIC_0012666.jpg  ISIC_0014133.jpg
ISIC_0000239.jpg  ISIC_0010051.jpg  ISIC_0012669.jpg  ISIC_0014136.jpg
ISIC_0000240.jpg  ISIC_0010053.jpg  ISIC_0012670.jpg  ISIC_0014144.jpg
ISIC_0000242.jpg  ISIC_0010054.jpg  ISIC_0012671.jpg  ISIC_0014149.jpg
ISIC_0000243.jpg  ISIC_0010055.jpg  ISIC_0012672.jpg  ISIC_0014150.jpg
ISIC_0000244.jpg  ISIC_0010057.jpg  ISIC_0012673.jpg  ISIC_0014151.jpg
ISIC_0000245.jpg  ISIC_0010058.jpg  ISIC_0012674.jpg  ISIC_0014156.jpg
ISIC_0000246.jpg  ISIC_0010059.jpg  ISIC_0012675.jpg  ISIC_0014157.jpg
ISIC_0000247.jpg  ISIC_0010060.jpg  ISIC_0012676.jpg  ISIC_0014158.jpg
ISIC_0000250.jpg  ISIC_0010061.jpg  ISIC_0012677.jpg  ISIC_0014163.jpg
ISIC_0000251.jpg  ISIC_0010062.jpg  ISIC_0012678.jpg  ISIC_0014164.jpg
ISIC_0000252.jpg  ISIC_0010063.jpg  ISIC_0012679.jpg  ISIC_0014166.jpg
ISIC_0000253.jpg  ISIC_0010064.jpg  ISIC_0012680.jpg  ISIC_0014169.jpg
ISIC_0000254.jpg  ISIC_0010066.jpg  ISIC_0012681.jpg  ISIC_0014171.jpg
ISIC_0000255.jpg  ISIC_0010067.jpg  ISIC_0012682.jpg  ISIC_0014173.jpg
ISIC_0000256.jpg  ISIC_0010069.jpg  ISIC_0012683.jpg  ISIC_0014174.jpg
ISIC_0000258.jpg  ISIC_0010070.jpg  ISIC_0012685.jpg  ISIC_0014179.jpg
ISIC_0000259.jpg  ISIC_0010074.jpg  ISIC_0012690.jpg  ISIC_0014183.jpg
ISIC_0000260.jpg  ISIC_0010075.jpg  ISIC_0012692.jpg  ISIC_0014185.jpg
ISIC_0000261.jpg  ISIC_0010077.jpg  ISIC_0012693.jpg  ISIC_0014187.jpg
ISIC_0000262.jpg  ISIC_0010078.jpg  ISIC_0012696.jpg  ISIC_0014189.jpg
ISIC_0000263.jpg  ISIC_0010080.jpg  ISIC_0012697.jpg  ISIC_0014190.jpg
ISIC_0000264.jpg  ISIC_0010081.jpg  ISIC_0012699.jpg  ISIC_0014191.jpg
ISIC_0000265.jpg  ISIC_0010086.jpg  ISIC_0012700.jpg  ISIC_0014195.jpg
ISIC_0000268.jpg  ISIC_0010087.jpg  ISIC_0012701.jpg  ISIC_0014197.jpg
ISIC_0000269.jpg  ISIC_0010088.jpg  ISIC_0012702.jpg  ISIC_0014216.jpg
ISIC_0000274.jpg  ISIC_0010089.jpg  ISIC_0012704.jpg  ISIC_0014222.jpg
ISIC_0000275.jpg  ISIC_0010090.jpg  ISIC_0012706.jpg  ISIC_0014225.jpg
ISIC_0000276.jpg  ISIC_0010092.jpg  ISIC_0012709.jpg  ISIC_0014229.jpg
ISIC_0000277.jpg  ISIC_0010093.jpg  ISIC_0012710.jpg  ISIC_0014238.jpg
ISIC_0000278.jpg  ISIC_0010094.jpg  ISIC_0012711.jpg  ISIC_0014248.jpg
ISIC_0000281.jpg  ISIC_0010100.jpg  ISIC_0012713.jpg  ISIC_0014249.jpg
ISIC_0000282.jpg  ISIC_0010102.jpg  ISIC_0012715.jpg  ISIC_0014253.jpg
ISIC_0000283.jpg  ISIC_0010104.jpg  ISIC_0012719.jpg  ISIC_0014263.jpg
ISIC_0000285.jpg  ISIC_0010105.jpg  ISIC_0012721.jpg  ISIC_0014264.jpg
ISIC_0000288.jpg  ISIC_0010168.jpg  ISIC_0012725.jpg  ISIC_0014272.jpg
ISIC_0000289.jpg  ISIC_0010170.jpg  ISIC_0012726.jpg  ISIC_0014273.jpg
ISIC_0000290.jpg  ISIC_0010171.jpg  ISIC_0012735.jpg  ISIC_0014274.jpg
ISIC_0000292.jpg  ISIC_0010173.jpg  ISIC_0012737.jpg  ISIC_0014286.jpg
ISIC_0000293.jpg  ISIC_0010174.jpg  ISIC_0012739.jpg  ISIC_0014289.jpg
ISIC_0000294.jpg  ISIC_0010176.jpg  ISIC_0012740.jpg  ISIC_0014290.jpg
ISIC_0000295.jpg  ISIC_0010177.jpg  ISIC_0012741.jpg  ISIC_0014291.jpg
ISIC_0000297.jpg  ISIC_0010178.jpg  ISIC_0012742.jpg  ISIC_0014299.jpg
ISIC_0000298.jpg  ISIC_0010180.jpg  ISIC_0012744.jpg  ISIC_0014308.jpg
ISIC_0000299.jpg  ISIC_0010182.jpg  ISIC_0012749.jpg  ISIC_0014311.jpg
ISIC_0000300.jpg  ISIC_0010184.jpg  ISIC_0012756.jpg  ISIC_0014316.jpg
ISIC_0000301.jpg  ISIC_0010185.jpg  ISIC_0012768.jpg  ISIC_0014317.jpg
ISIC_0000302.jpg  ISIC_0010186.jpg  ISIC_0012770.jpg  ISIC_0014324.jpg
ISIC_0000303.jpg  ISIC_0010187.jpg  ISIC_0012772.jpg  ISIC_0014325.jpg
ISIC_0000306.jpg  ISIC_0010191.jpg  ISIC_0012773.jpg  ISIC_0014327.jpg
ISIC_0000307.jpg  ISIC_0010192.jpg  ISIC_0012777.jpg  ISIC_0014328.jpg
ISIC_0000310.jpg  ISIC_0010193.jpg  ISIC_0012785.jpg  ISIC_0014331.jpg
ISIC_0000311.jpg  ISIC_0010194.jpg  ISIC_0012787.jpg  ISIC_0014337.jpg
ISIC_0000313.jpg  ISIC_0010201.jpg  ISIC_0012788.jpg  ISIC_0014341.jpg
ISIC_0000314.jpg  ISIC_0010202.jpg  ISIC_0012789.jpg  ISIC_0014346.jpg
ISIC_0000315.jpg  ISIC_0010205.jpg  ISIC_0012790.jpg  ISIC_0014347.jpg
ISIC_0000316.jpg  ISIC_0010206.jpg  ISIC_0012792.jpg  ISIC_0014353.jpg
ISIC_0000317.jpg  ISIC_0010207.jpg  ISIC_0012793.jpg  ISIC_0014357.jpg
ISIC_0000319.jpg  ISIC_0010212.jpg  ISIC_0012800.jpg  ISIC_0014360.jpg
ISIC_0000320.jpg  ISIC_0010213.jpg  ISIC_0012804.jpg  ISIC_0014361.jpg
ISIC_0000321.jpg  ISIC_0010215.jpg  ISIC_0012806.jpg  ISIC_0014365.jpg
ISIC_0000322.jpg  ISIC_0010216.jpg  ISIC_0012810.jpg  ISIC_0014366.jpg
ISIC_0000323.jpg  ISIC_0010219.jpg  ISIC_0012811.jpg  ISIC_0014372.jpg
ISIC_0000324.jpg  ISIC_0010220.jpg  ISIC_0012813.jpg  ISIC_0014385.jpg
ISIC_0000325.jpg  ISIC_0010222.jpg  ISIC_0012814.jpg  ISIC_0014393.jpg
ISIC_0000326.jpg  ISIC_0010225.jpg  ISIC_0012823.jpg  ISIC_0014394.jpg
ISIC_0000327.jpg  ISIC_0010227.jpg  ISIC_0012826.jpg  ISIC_0014395.jpg
ISIC_0000328.jpg  ISIC_0010229.jpg  ISIC_0012827.jpg  ISIC_0014397.jpg
ISIC_0000329.jpg  ISIC_0010231.jpg  ISIC_0012828.jpg  ISIC_0014410.jpg
ISIC_0000330.jpg  ISIC_0010233.jpg  ISIC_0012833.jpg  ISIC_0014422.jpg
ISIC_0000331.jpg  ISIC_0010234.jpg  ISIC_0012835.jpg  ISIC_0014430.jpg
ISIC_0000332.jpg  ISIC_0010236.jpg  ISIC_0012840.jpg  ISIC_0014431.jpg
ISIC_0000336.jpg  ISIC_0010237.jpg  ISIC_0012844.jpg  ISIC_0014432.jpg
ISIC_0000338.jpg  ISIC_0010240.jpg  ISIC_0012845.jpg  ISIC_0014433.jpg
ISIC_0000340.jpg  ISIC_0010241.jpg  ISIC_0012851.jpg  ISIC_0014438.jpg
ISIC_0000341.jpg  ISIC_0010244.jpg  ISIC_0012854.jpg  ISIC_0014440.jpg
ISIC_0000342.jpg  ISIC_0010246.jpg  ISIC_0012855.jpg  ISIC_0014441.jpg
ISIC_0000343.jpg  ISIC_0010247.jpg  ISIC_0012856.jpg  ISIC_0014453.jpg
ISIC_0000344.jpg  ISIC_0010248.jpg  ISIC_0012865.jpg  ISIC_0014458.jpg
ISIC_0000345.jpg  ISIC_0010249.jpg  ISIC_0012871.jpg  ISIC_0014469.jpg
ISIC_0000346.jpg  ISIC_0010251.jpg  ISIC_0012873.jpg  ISIC_0014473.jpg
ISIC_0000347.jpg  ISIC_0010254.jpg  ISIC_0012877.jpg  ISIC_0014475.jpg
ISIC_0000348.jpg  ISIC_0010255.jpg  ISIC_0012878.jpg  ISIC_0014476.jpg
ISIC_0000349.jpg  ISIC_0010256.jpg  ISIC_0012879.jpg  ISIC_0014480.jpg
ISIC_0000350.jpg  ISIC_0010257.jpg  ISIC_0012880.jpg  ISIC_0014486.jpg
ISIC_0000351.jpg  ISIC_0010261.jpg  ISIC_0012883.jpg  ISIC_0014490.jpg
ISIC_0000352.jpg  ISIC_0010262.jpg  ISIC_0012884.jpg  ISIC_0014498.jpg
ISIC_0000353.jpg  ISIC_0010264.jpg  ISIC_0012887.jpg  ISIC_0014501.jpg
ISIC_0000354.jpg  ISIC_0010265.jpg  ISIC_0012888.jpg  ISIC_0014502.jpg
ISIC_0000355.jpg  ISIC_0010267.jpg  ISIC_0012889.jpg  ISIC_0014504.jpg
ISIC_0000357.jpg  ISIC_0010317.jpg  ISIC_0012891.jpg  ISIC_0014507.jpg
ISIC_0000358.jpg  ISIC_0010318.jpg  ISIC_0012897.jpg  ISIC_0014511.jpg
ISIC_0000359.jpg  ISIC_0010320.jpg  ISIC_0012898.jpg  ISIC_0014515.jpg
ISIC_0000360.jpg  ISIC_0010326.jpg  ISIC_0012901.jpg  ISIC_0014516.jpg
ISIC_0000361.jpg  ISIC_0010327.jpg  ISIC_0012902.jpg  ISIC_0014518.jpg
ISIC_0000363.jpg  ISIC_0010329.jpg  ISIC_0012905.jpg  ISIC_0014522.jpg
ISIC_0000364.jpg  ISIC_0010330.jpg  ISIC_0012907.jpg  ISIC_0014525.jpg
ISIC_0000365.jpg  ISIC_0010332.jpg  ISIC_0012911.jpg  ISIC_0014526.jpg
ISIC_0000366.jpg  ISIC_0010333.jpg  ISIC_0012930.jpg  ISIC_0014527.jpg
ISIC_0000367.jpg  ISIC_0010334.jpg  ISIC_0012932.jpg  ISIC_0014529.jpg
ISIC_0000368.jpg  ISIC_0010336.jpg  ISIC_0012939.jpg  ISIC_0014535.jpg
ISIC_0000369.jpg  ISIC_0010337.jpg  ISIC_0012940.jpg  ISIC_0014537.jpg
ISIC_0000370.jpg  ISIC_0010339.jpg  ISIC_0012944.jpg  ISIC_0014543.jpg
ISIC_0000371.jpg  ISIC_0010340.jpg  ISIC_0012945.jpg  ISIC_0014545.jpg
ISIC_0000372.jpg  ISIC_0010341.jpg  ISIC_0012949.jpg  ISIC_0014547.jpg
ISIC_0000374.jpg  ISIC_0010342.jpg  ISIC_0012950.jpg  ISIC_0014554.jpg
ISIC_0000376.jpg  ISIC_0010344.jpg  ISIC_0012952.jpg  ISIC_0014557.jpg
ISIC_0000377.jpg  ISIC_0010346.jpg  ISIC_0012957.jpg  ISIC_0014569.jpg
ISIC_0000378.jpg  ISIC_0010348.jpg  ISIC_0012961.jpg  ISIC_0014570.jpg
ISIC_0000379.jpg  ISIC_0010350.jpg  ISIC_0012962.jpg  ISIC_0014571.jpg
ISIC_0000380.jpg  ISIC_0010351.jpg  ISIC_0012966.jpg  ISIC_0014573.jpg
ISIC_0000381.jpg  ISIC_0010356.jpg  ISIC_0012969.jpg  ISIC_0014576.jpg
ISIC_0000382.jpg  ISIC_0010357.jpg  ISIC_0012970.jpg  ISIC_0014577.jpg
ISIC_0000383.jpg  ISIC_0010358.jpg  ISIC_0012976.jpg  ISIC_0014578.jpg
ISIC_0000384.jpg  ISIC_0010360.jpg  ISIC_0012981.jpg  ISIC_0014579.jpg
ISIC_0000385.jpg  ISIC_0010362.jpg  ISIC_0012982.jpg  ISIC_0014580.jpg
ISIC_0000386.jpg  ISIC_0010364.jpg  ISIC_0012986.jpg  ISIC_0014581.jpg
ISIC_0000387.jpg  ISIC_0010365.jpg  ISIC_0012987.jpg  ISIC_0014582.jpg
ISIC_0000388.jpg  ISIC_0010367.jpg  ISIC_0012988.jpg  ISIC_0014583.jpg
ISIC_0000390.jpg  ISIC_0010368.jpg  ISIC_0012990.jpg  ISIC_0014585.jpg
ISIC_0000391.jpg  ISIC_0010370.jpg  ISIC_0012998.jpg  ISIC_0014589.jpg
ISIC_0000392.jpg  ISIC_0010371.jpg  ISIC_0012999.jpg  ISIC_0014591.jpg
ISIC_0000393.jpg  ISIC_0010372.jpg  ISIC_0013000.jpg  ISIC_0014592.jpg
ISIC_0000395.jpg  ISIC_0010374.jpg  ISIC_0013001.jpg  ISIC_0014593.jpg
ISIC_0000396.jpg  ISIC_0010379.jpg  ISIC_0013007.jpg  ISIC_0014594.jpg
ISIC_0000397.jpg  ISIC_0010382.jpg  ISIC_0013012.jpg  ISIC_0014595.jpg
ISIC_0000403.jpg  ISIC_0010435.jpg  ISIC_0013014.jpg  ISIC_0014596.jpg
ISIC_0000407.jpg  ISIC_0010441.jpg  ISIC_0013015.jpg  ISIC_0014598.jpg
ISIC_0000408.jpg  ISIC_0010442.jpg  ISIC_0013023.jpg  ISIC_0014599.jpg
ISIC_0000409.jpg  ISIC_0010443.jpg  ISIC_0013024.jpg  ISIC_0014602.jpg
ISIC_0000410.jpg  ISIC_0010444.jpg  ISIC_0013025.jpg  ISIC_0014603.jpg
ISIC_0000412.jpg  ISIC_0010447.jpg  ISIC_0013026.jpg  ISIC_0014605.jpg
ISIC_0000413.jpg  ISIC_0010448.jpg  ISIC_0013027.jpg  ISIC_0014606.jpg
ISIC_0000415.jpg  ISIC_0010449.jpg  ISIC_0013031.jpg  ISIC_0014607.jpg
ISIC_0000416.jpg  ISIC_0010452.jpg  ISIC_0013032.jpg  ISIC_0014609.jpg
ISIC_0000418.jpg  ISIC_0010455.jpg  ISIC_0013033.jpg  ISIC_0014612.jpg
ISIC_0000419.jpg  ISIC_0010456.jpg  ISIC_0013034.jpg  ISIC_0014613.jpg
ISIC_0000420.jpg  ISIC_0010458.jpg  ISIC_0013037.jpg  ISIC_0014615.jpg
ISIC_0000421.jpg  ISIC_0010460.jpg  ISIC_0013039.jpg  ISIC_0014617.jpg
ISIC_0000423.jpg  ISIC_0010461.jpg  ISIC_0013040.jpg  ISIC_0014621.jpg
ISIC_0000425.jpg  ISIC_0010463.jpg  ISIC_0013044.jpg  ISIC_0014622.jpg
ISIC_0000426.jpg  ISIC_0010465.jpg  ISIC_0013047.jpg  ISIC_0014625.jpg
ISIC_0000427.jpg  ISIC_0010466.jpg  ISIC_0013048.jpg  ISIC_0014628.jpg
ISIC_0000431.jpg  ISIC_0010467.jpg  ISIC_0013052.jpg  ISIC_0014630.jpg
ISIC_0000433.jpg  ISIC_0010468.jpg  ISIC_0013053.jpg  ISIC_0014632.jpg
ISIC_0000434.jpg  ISIC_0010471.jpg  ISIC_0013054.jpg  ISIC_0014636.jpg
ISIC_0000436.jpg  ISIC_0010472.jpg  ISIC_0013055.jpg  ISIC_0014638.jpg
ISIC_0000439.jpg  ISIC_0010473.jpg  ISIC_0013056.jpg  ISIC_0014639.jpg
ISIC_0000442.jpg  ISIC_0010474.jpg  ISIC_0013059.jpg  ISIC_0014640.jpg
ISIC_0000443.jpg  ISIC_0010475.jpg  ISIC_0013063.jpg  ISIC_0014641.jpg
ISIC_0000444.jpg  ISIC_0010476.jpg  ISIC_0013065.jpg  ISIC_0014642.jpg
ISIC_0000445.jpg  ISIC_0010477.jpg  ISIC_0013071.jpg  ISIC_0014646.jpg
ISIC_0000447.jpg  ISIC_0010479.jpg  ISIC_0013075.jpg  ISIC_0014650.jpg
ISIC_0000448.jpg  ISIC_0010480.jpg  ISIC_0013079.jpg  ISIC_0014651.jpg
ISIC_0000449.jpg  ISIC_0010481.jpg  ISIC_0013080.jpg  ISIC_0014654.jpg
ISIC_0000451.jpg  ISIC_0010483.jpg  ISIC_0013084.jpg  ISIC_0014657.jpg
ISIC_0000453.jpg  ISIC_0010487.jpg  ISIC_0013086.jpg  ISIC_0014658.jpg
ISIC_0000455.jpg  ISIC_0010488.jpg  ISIC_0013087.jpg  ISIC_0014661.jpg
ISIC_0000456.jpg  ISIC_0010490.jpg  ISIC_0013088.jpg  ISIC_0014664.jpg
ISIC_0000457.jpg  ISIC_0010492.jpg  ISIC_0013089.jpg  ISIC_0014665.jpg
ISIC_0000458.jpg  ISIC_0010493.jpg  ISIC_0013090.jpg  ISIC_0014667.jpg
ISIC_0000460.jpg  ISIC_0010494.jpg  ISIC_0013092.jpg  ISIC_0014680.jpg
ISIC_0000461.jpg  ISIC_0010497.jpg  ISIC_0013094.jpg  ISIC_0014682.jpg
ISIC_0000463.jpg  ISIC_0010498.jpg  ISIC_0013096.jpg  ISIC_0014683.jpg
ISIC_0000465.jpg  ISIC_0010552.jpg  ISIC_0013097.jpg  ISIC_0014684.jpg
ISIC_0000466.jpg  ISIC_0010553.jpg  ISIC_0013106.jpg  ISIC_0014685.jpg
ISIC_0000467.jpg  ISIC_0010554.jpg  ISIC_0013112.jpg  ISIC_0014692.jpg
ISIC_0000468.jpg  ISIC_0010557.jpg  ISIC_0013114.jpg  ISIC_0014694.jpg
ISIC_0000469.jpg  ISIC_0010558.jpg  ISIC_0013118.jpg  ISIC_0014696.jpg
ISIC_0000470.jpg  ISIC_0010562.jpg  ISIC_0013120.jpg  ISIC_0014699.jpg
ISIC_0000471.jpg  ISIC_0010565.jpg  ISIC_0013121.jpg  ISIC_0014702.jpg
ISIC_0000473.jpg  ISIC_0010566.jpg  ISIC_0013124.jpg  ISIC_0014707.jpg
ISIC_0000474.jpg  ISIC_0010567.jpg  ISIC_0013126.jpg  ISIC_0014708.jpg
ISIC_0000475.jpg  ISIC_0010568.jpg  ISIC_0013129.jpg  ISIC_0014711.jpg
ISIC_0000476.jpg  ISIC_0010569.jpg  ISIC_0013134.jpg  ISIC_0014713.jpg
ISIC_0000478.jpg  ISIC_0010570.jpg  ISIC_0013136.jpg  ISIC_0014714.jpg
ISIC_0000479.jpg  ISIC_0010571.jpg  ISIC_0013140.jpg  ISIC_0014715.jpg
ISIC_0000480.jpg  ISIC_0010573.jpg  ISIC_0013141.jpg  ISIC_0014716.jpg
ISIC_0000481.jpg  ISIC_0010574.jpg  ISIC_0013146.jpg  ISIC_0014722.jpg
ISIC_0000482.jpg  ISIC_0010575.jpg  ISIC_0013147.jpg  ISIC_0014723.jpg
ISIC_0000483.jpg  ISIC_0010581.jpg  ISIC_0013150.jpg  ISIC_0014724.jpg
ISIC_0000484.jpg  ISIC_0010582.jpg  ISIC_0013155.jpg  ISIC_0014726.jpg
ISIC_0000485.jpg  ISIC_0010584.jpg  ISIC_0013160.jpg  ISIC_0014730.jpg
ISIC_0000486.jpg  ISIC_0010585.jpg  ISIC_0013163.jpg  ISIC_0014731.jpg
ISIC_0000487.jpg  ISIC_0010586.jpg  ISIC_0013165.jpg  ISIC_0014735.jpg
ISIC_0000488.jpg  ISIC_0010587.jpg  ISIC_0013166.jpg  ISIC_0014739.jpg
ISIC_0000489.jpg  ISIC_0010588.jpg  ISIC_0013167.jpg  ISIC_0014742.jpg
ISIC_0000490.jpg  ISIC_0010589.jpg  ISIC_0013172.jpg  ISIC_0014745.jpg
ISIC_0000491.jpg  ISIC_0010590.jpg  ISIC_0013173.jpg  ISIC_0014748.jpg
ISIC_0000492.jpg  ISIC_0010591.jpg  ISIC_0013174.jpg  ISIC_0014754.jpg
ISIC_0000493.jpg  ISIC_0010592.jpg  ISIC_0013177.jpg  ISIC_0014760.jpg
ISIC_0000494.jpg  ISIC_0010593.jpg  ISIC_0013178.jpg  ISIC_0014762.jpg
ISIC_0000495.jpg  ISIC_0010595.jpg  ISIC_0013181.jpg  ISIC_0014763.jpg
ISIC_0000496.jpg  ISIC_0010596.jpg  ISIC_0013184.jpg  ISIC_0014769.jpg
ISIC_0000498.jpg  ISIC_0010597.jpg  ISIC_0013187.jpg  ISIC_0014770.jpg
ISIC_0000499.jpg  ISIC_0010598.jpg  ISIC_0013189.jpg  ISIC_0014771.jpg
ISIC_0000500.jpg  ISIC_0010599.jpg  ISIC_0013190.jpg  ISIC_0014775.jpg
ISIC_0000501.jpg  ISIC_0010602.jpg  ISIC_0013192.jpg  ISIC_0014778.jpg
ISIC_0000503.jpg  ISIC_0010603.jpg  ISIC_0013193.jpg  ISIC_0014779.jpg
ISIC_0000504.jpg  ISIC_0010606.jpg  ISIC_0013196.jpg  ISIC_0014782.jpg
ISIC_0000505.jpg  ISIC_0010607.jpg  ISIC_0013197.jpg  ISIC_0014783.jpg
ISIC_0000506.jpg  ISIC_0010844.jpg  ISIC_0013198.jpg  ISIC_0014785.jpg
ISIC_0000507.jpg  ISIC_0010846.jpg  ISIC_0013200.jpg  ISIC_0014788.jpg
ISIC_0000508.jpg  ISIC_0010847.jpg  ISIC_0013201.jpg  ISIC_0014791.jpg
ISIC_0000509.jpg  ISIC_0010848.jpg  ISIC_0013204.jpg  ISIC_0014793.jpg
ISIC_0000510.jpg  ISIC_0010850.jpg  ISIC_0013205.jpg  ISIC_0014794.jpg
ISIC_0000511.jpg  ISIC_0010851.jpg  ISIC_0013207.jpg  ISIC_0014795.jpg
ISIC_0000513.jpg  ISIC_0010852.jpg  ISIC_0013208.jpg  ISIC_0014797.jpg
ISIC_0000514.jpg  ISIC_0010853.jpg  ISIC_0013212.jpg  ISIC_0014802.jpg
ISIC_0000515.jpg  ISIC_0010854.jpg  ISIC_0013213.jpg  ISIC_0014803.jpg
ISIC_0000516.jpg  ISIC_0010856.jpg  ISIC_0013217.jpg  ISIC_0014804.jpg
ISIC_0000517.jpg  ISIC_0010857.jpg  ISIC_0013219.jpg  ISIC_0014805.jpg
ISIC_0000518.jpg  ISIC_0010858.jpg  ISIC_0013220.jpg  ISIC_0014806.jpg
ISIC_0000519.jpg  ISIC_0010860.jpg  ISIC_0013222.jpg  ISIC_0014808.jpg
ISIC_0000520.jpg  ISIC_0010861.jpg  ISIC_0013223.jpg  ISIC_0014811.jpg
ISIC_0000521.jpg  ISIC_0010862.jpg  ISIC_0013224.jpg  ISIC_0014812.jpg
ISIC_0000522.jpg  ISIC_0010863.jpg  ISIC_0013227.jpg  ISIC_0014818.jpg
ISIC_0000523.jpg  ISIC_0010864.jpg  ISIC_0013229.jpg  ISIC_0014819.jpg
ISIC_0000524.jpg  ISIC_0011079.jpg  ISIC_0013233.jpg  ISIC_0014821.jpg
ISIC_0000525.jpg  ISIC_0011082.jpg  ISIC_0013235.jpg  ISIC_0014823.jpg
ISIC_0000527.jpg  ISIC_0011083.jpg  ISIC_0013236.jpg  ISIC_0014825.jpg
ISIC_0000528.jpg  ISIC_0011085.jpg  ISIC_0013238.jpg  ISIC_0014830.jpg
ISIC_0000529.jpg  ISIC_0011088.jpg  ISIC_0013243.jpg  ISIC_0014831.jpg
ISIC_0000530.jpg  ISIC_0011089.jpg  ISIC_0013244.jpg  ISIC_0014832.jpg
ISIC_0000531.jpg  ISIC_0011090.jpg  ISIC_0013248.jpg  ISIC_0014834.jpg
ISIC_0000532.jpg  ISIC_0011095.jpg  ISIC_0013249.jpg  ISIC_0014836.jpg
ISIC_0000533.jpg  ISIC_0011097.jpg  ISIC_0013257.jpg  ISIC_0014838.jpg
ISIC_0000534.jpg  ISIC_0011098.jpg  ISIC_0013258.jpg  ISIC_0014839.jpg
ISIC_0000535.jpg  ISIC_0011099.jpg  ISIC_0013268.jpg  ISIC_0014843.jpg
ISIC_0000536.jpg  ISIC_0011101.jpg  ISIC_0013274.jpg  ISIC_0014845.jpg
ISIC_0000538.jpg  ISIC_0011102.jpg  ISIC_0013275.jpg  ISIC_0014846.jpg
ISIC_0000539.jpg  ISIC_0011107.jpg  ISIC_0013287.jpg  ISIC_0014848.jpg
ISIC_0000540.jpg  ISIC_0011110.jpg  ISIC_0013288.jpg  ISIC_0014849.jpg
ISIC_0000541.jpg  ISIC_0011112.jpg  ISIC_0013294.jpg  ISIC_0014850.jpg
ISIC_0000542.jpg  ISIC_0011114.jpg  ISIC_0013302.jpg  ISIC_0014851.jpg
ISIC_0000543.jpg  ISIC_0011115.jpg  ISIC_0013304.jpg  ISIC_0014855.jpg
ISIC_0000544.jpg  ISIC_0011117.jpg  ISIC_0013306.jpg  ISIC_0014860.jpg
ISIC_0000545.jpg  ISIC_0011118.jpg  ISIC_0013310.jpg  ISIC_0014866.jpg
ISIC_0000546.jpg  ISIC_0011119.jpg  ISIC_0013311.jpg  ISIC_0014869.jpg
ISIC_0000547.jpg  ISIC_0011121.jpg  ISIC_0013314.jpg  ISIC_0014890.jpg
ISIC_0000548.jpg  ISIC_0011123.jpg  ISIC_0013315.jpg  ISIC_0014891.jpg
ISIC_0000549.jpg  ISIC_0011124.jpg  ISIC_0013316.jpg  ISIC_0014897.jpg
ISIC_0000550.jpg  ISIC_0011126.jpg  ISIC_0013320.jpg  ISIC_0014898.jpg
ISIC_0000551.jpg  ISIC_0011127.jpg  ISIC_0013326.jpg  ISIC_0014903.jpg
ISIC_0000552.jpg  ISIC_0011130.jpg  ISIC_0013329.jpg  ISIC_0014904.jpg
ISIC_0000554.jpg  ISIC_0011131.jpg  ISIC_0013330.jpg  ISIC_0014908.jpg
ISIC_0000555.jpg  ISIC_0011132.jpg  ISIC_0013333.jpg  ISIC_0014911.jpg
ISIC_0000556.jpg  ISIC_0011135.jpg  ISIC_0013334.jpg  ISIC_0014913.jpg
ISIC_0000882.jpg  ISIC_0011136.jpg  ISIC_0013335.jpg  ISIC_0014915.jpg
ISIC_0000900.jpg  ISIC_0011137.jpg  ISIC_0013340.jpg  ISIC_0014919.jpg
ISIC_0000999.jpg  ISIC_0011140.jpg  ISIC_0013341.jpg  ISIC_0014920.jpg
ISIC_0001100.jpg  ISIC_0011143.jpg  ISIC_0013342.jpg  ISIC_0014922.jpg
ISIC_0001102.jpg  ISIC_0011144.jpg  ISIC_0013346.jpg  ISIC_0014923.jpg
ISIC_0001103.jpg  ISIC_0011145.jpg  ISIC_0013355.jpg  ISIC_0014925.jpg
ISIC_0001105.jpg  ISIC_0011146.jpg  ISIC_0013356.jpg  ISIC_0014926.jpg
ISIC_0001118.jpg  ISIC_0011155.jpg  ISIC_0013359.jpg  ISIC_0014929.jpg
ISIC_0001119.jpg  ISIC_0011157.jpg  ISIC_0013360.jpg  ISIC_0014930.jpg
ISIC_0001126.jpg  ISIC_0011158.jpg  ISIC_0013364.jpg  ISIC_0014933.jpg
ISIC_0001128.jpg  ISIC_0011159.jpg  ISIC_0013365.jpg  ISIC_0014951.jpg
ISIC_0001131.jpg  ISIC_0011161.jpg  ISIC_0013369.jpg  ISIC_0014975.jpg
ISIC_0001133.jpg  ISIC_0011162.jpg  ISIC_0013370.jpg  ISIC_0014983.jpg
ISIC_0001134.jpg  ISIC_0011163.jpg  ISIC_0013371.jpg  ISIC_0014987.jpg
ISIC_0001140.jpg  ISIC_0011164.jpg  ISIC_0013378.jpg  ISIC_0015005.jpg
ISIC_0001142.jpg  ISIC_0011165.jpg  ISIC_0013383.jpg  ISIC_0015006.jpg
ISIC_0001148.jpg  ISIC_0011166.jpg  ISIC_0013385.jpg  ISIC_0015032.jpg
ISIC_0001152.jpg  ISIC_0011167.jpg  ISIC_0013390.jpg  ISIC_0015038.jpg
ISIC_0001960.jpg  ISIC_0011168.jpg  ISIC_0013394.jpg  ISIC_0015044.jpg
ISIC_0002093.jpg  ISIC_0011169.jpg  ISIC_0013395.jpg  ISIC_0015045.jpg
ISIC_0002107.jpg  ISIC_0011170.jpg  ISIC_0013397.jpg  ISIC_0015079.jpg
ISIC_0002206.jpg  ISIC_0011171.jpg  ISIC_0013398.jpg  ISIC_0015082.jpg
ISIC_0002246.jpg  ISIC_0011173.jpg  ISIC_0013400.jpg  ISIC_0015108.jpg
ISIC_0002251.jpg  ISIC_0011176.jpg  ISIC_0013403.jpg  ISIC_0015109.jpg
ISIC_0002287.jpg  ISIC_0011177.jpg  ISIC_0013405.jpg  ISIC_0015110.jpg
ISIC_0002353.jpg  ISIC_0011199.jpg  ISIC_0013409.jpg  ISIC_0015112.jpg
ISIC_0002374.jpg  ISIC_0011203.jpg  ISIC_0013410.jpg  ISIC_0015113.jpg
ISIC_0002438.jpg  ISIC_0011204.jpg  ISIC_0013417.jpg  ISIC_0015153.jpg
ISIC_0002439.jpg  ISIC_0011205.jpg  ISIC_0013423.jpg  ISIC_0015158.jpg
ISIC_0002453.jpg  ISIC_0011207.jpg  ISIC_0013424.jpg  ISIC_0015166.jpg
ISIC_0002459.jpg  ISIC_0011208.jpg  ISIC_0013425.jpg  ISIC_0015168.jpg
ISIC_0002469.jpg  ISIC_0011210.jpg  ISIC_0013427.jpg  ISIC_0015170.jpg
ISIC_0002476.jpg  ISIC_0011211.jpg  ISIC_0013428.jpg  ISIC_0015181.jpg
ISIC_0002488.jpg  ISIC_0011212.jpg  ISIC_0013429.jpg  ISIC_0015182.jpg
ISIC_0002489.jpg  ISIC_0011213.jpg  ISIC_0013430.jpg  ISIC_0015189.jpg
ISIC_0002616.jpg  ISIC_0011214.jpg  ISIC_0013432.jpg  ISIC_0015190.jpg
ISIC_0002647.jpg  ISIC_0011215.jpg  ISIC_0013433.jpg  ISIC_0015200.jpg
ISIC_0002673.jpg  ISIC_0011217.jpg  ISIC_0013434.jpg  ISIC_0015204.jpg
ISIC_0002780.jpg  ISIC_0011218.jpg  ISIC_0013437.jpg  ISIC_0015219.jpg
ISIC_0002806.jpg  ISIC_0011219.jpg  ISIC_0013438.jpg  ISIC_0015220.jpg
ISIC_0002829.jpg  ISIC_0011220.jpg  ISIC_0013443.jpg  ISIC_0015233.jpg
ISIC_0002836.jpg  ISIC_0011223.jpg  ISIC_0013456.jpg  ISIC_0015260.jpg
ISIC_0002871.jpg  ISIC_0011224.jpg  ISIC_0013458.jpg  ISIC_0015284.jpg
ISIC_0002879.jpg  ISIC_0011225.jpg  ISIC_0013461.jpg  ISIC_0015295.jpg

1.3.1.3 Joining the Filenames with the Directory Path of Every File

# pre-process the data for Keras
# Training Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG
# os.path.join(folder, file)
dt = os.walk('/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG')
files = []
for root, d_names, f_names in dt:
    for filename in f_names:
        files.append(os.path.join(root, filename))

files

['/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011217.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011214.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011220.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011230.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011218.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011292.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011223.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011300.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011317.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011322.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011327.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011310.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011297.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011298.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011303.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011304.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011321.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011324.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011306.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011315.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011326.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011305.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011338.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011333.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011339.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011328.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011352.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011348.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011349.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011353.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011336.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011344.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011330.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011343.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011345.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011347.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011358.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011393.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011398.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011402.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011387.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011382.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011362.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011386.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011397.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011363.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011366.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011367.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011359.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011361.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011372.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0011384.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012097.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012105.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012117.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012108.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012118.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012103.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012089.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012094.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012135.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012107.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012090.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012102.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012116.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012150.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012172.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012148.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012173.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012164.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012155.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012156.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012177.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012141.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012170.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012167.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012175.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012137.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012211.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012182.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012217.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012187.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012205.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012209.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012183.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012208.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012203.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012179.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012212.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012213.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012214.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012237.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012228.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012246.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012245.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012238.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012250.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012235.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012232.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012227.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012224.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012233.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012230.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012257.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012263.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012260.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012274.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012261.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012282.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012278.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012253.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012281.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012268.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012259.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012271.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012290.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012311.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012309.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012299.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012298.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012284.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012291.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012303.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012318.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012294.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012320.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012285.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012322.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012359.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012332.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012334.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012342.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012333.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012325.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012348.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012324.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012351.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012339.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012329.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012338.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012390.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012374.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012379.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012378.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012382.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012386.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012363.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012376.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012377.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012360.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012381.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012384.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012391.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012416.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012452.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012406.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012397.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012445.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012442.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012453.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012433.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012415.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012435.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012450.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012413.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012494.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012464.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012459.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012460.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012481.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012487.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012473.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012478.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012469.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012475.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012489.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012455.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012495.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012517.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012506.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012503.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012496.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012511.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012520.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012512.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012501.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012508.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012516.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012518.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012521.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012543.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012549.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012526.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012539.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012527.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012523.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012653.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012529.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012544.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012550.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012658.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012655.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012659.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012666.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012663.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012670.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012662.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012657.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012661.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012669.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012665.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012664.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012672.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012673.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012681.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012679.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012675.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012682.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012677.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012683.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012678.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012676.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012680.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012674.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012671.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012697.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012699.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012701.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012693.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012706.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012702.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012685.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012690.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012704.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012709.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012700.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012692.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012696.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012740.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012725.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012711.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012710.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012719.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012735.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012715.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012713.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012739.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012726.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012741.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012737.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012721.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012742.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012749.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012744.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012787.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012788.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012770.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012777.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012768.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012756.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012773.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012785.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012772.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012814.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012793.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012813.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012804.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012790.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012826.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012823.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012827.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012806.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012811.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012789.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012792.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012800.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012810.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012873.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012856.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012844.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012828.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012840.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012854.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012833.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012851.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012845.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012835.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012871.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012855.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012865.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012884.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012880.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012877.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012898.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012888.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012889.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012887.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012897.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012879.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012891.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012878.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012883.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012949.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012945.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012944.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012905.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012907.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012940.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012950.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012902.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012932.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012911.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012901.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012939.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012930.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012987.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012970.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012982.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012957.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012952.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012986.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012969.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012966.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012988.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012976.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012961.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012962.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012981.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013012.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013024.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013023.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013001.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013015.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013026.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012990.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012999.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013000.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0012998.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013014.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013025.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013007.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013044.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013047.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013032.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013034.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013040.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013048.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013031.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013037.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013027.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013033.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013039.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013065.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013053.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013063.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013079.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013084.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013071.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013059.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013052.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013054.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013056.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013075.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013055.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013080.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013094.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013097.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013114.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013090.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013096.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013118.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013088.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013087.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013089.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013106.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013086.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013112.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013092.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013121.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013141.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013147.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013140.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013124.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013126.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013155.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013129.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013134.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013150.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013136.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013120.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013146.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013177.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013165.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013174.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013184.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013167.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013160.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013178.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013172.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013163.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013166.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013173.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013181.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013196.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013201.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013200.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013187.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013207.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013198.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013192.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013205.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013193.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013189.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013197.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013204.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013190.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013217.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013229.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013233.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013222.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013208.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013223.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013220.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013213.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013227.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013219.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013224.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013212.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013257.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013238.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013236.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013258.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013248.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013249.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013268.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013243.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013244.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013235.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013274.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013275.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013314.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013304.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013302.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013310.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013288.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013287.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013306.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013294.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013311.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013335.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013329.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013330.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013342.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013334.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013326.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013333.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013341.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013340.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013320.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013315.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013316.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013359.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013364.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013370.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013378.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013355.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013369.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013360.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013365.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013371.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013356.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013346.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013395.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013409.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013385.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013400.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013383.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013394.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013405.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013397.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013398.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013410.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013390.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013403.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013429.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013425.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013424.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013433.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013434.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013427.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013417.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013432.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013428.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013423.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013430.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013461.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013443.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013486.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013437.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013489.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013480.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013458.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013488.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013438.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013487.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013474.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013456.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013495.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013490.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013523.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013517.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013500.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013497.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013498.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013492.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013516.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013499.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013493.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013494.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013553.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013525.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013558.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013526.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013573.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013568.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013530.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013559.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013567.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013552.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013572.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013554.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013595.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013585.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013580.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013596.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013597.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013584.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013594.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013578.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013579.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013581.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013592.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013621.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013618.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013606.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013625.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013639.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013603.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013634.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013601.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013610.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013599.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013626.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013635.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013656.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013675.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013672.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013676.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013652.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013667.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013674.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013643.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013664.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013680.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013671.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013670.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013682.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013687.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013691.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013688.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013707.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013690.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013706.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013689.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013695.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013685.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013684.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013709.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013748.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013721.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013747.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013737.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013712.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013742.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013731.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013725.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013719.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013713.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013740.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013749.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013783.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013782.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013772.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013762.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013777.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013789.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013758.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013775.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013765.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013792.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013778.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013802.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013807.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013800.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013798.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013803.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013804.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013795.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013799.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013797.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013801.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013806.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013805.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013796.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013836.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013832.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013808.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013830.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013817.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013831.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013816.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013815.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013835.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013819.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013862.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013844.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013861.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013839.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013864.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013837.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013865.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013841.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013843.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013845.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013874.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013840.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013922.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013918.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013910.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013896.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013876.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013921.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013888.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013929.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013927.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013879.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013890.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013886.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013946.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013961.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013958.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013967.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013970.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013962.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013969.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013935.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013965.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013936.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013942.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013933.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013995.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013980.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013996.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013983.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013975.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013997.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013981.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013971.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013972.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013986.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013984.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0013982.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014004.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014044.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014026.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014029.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014013.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014045.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014001.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014031.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014046.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014049.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014032.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014028.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014072.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014073.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014062.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014061.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014069.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014066.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014074.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014079.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014080.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014076.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014083.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014088.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014082.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014108.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014089.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014114.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014127.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014081.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014094.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014120.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014093.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014092.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014099.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014136.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014131.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014158.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014157.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014149.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014132.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014151.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014156.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014144.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014133.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014163.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014150.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014173.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014187.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014179.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014185.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014171.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014189.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014169.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014183.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014174.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014164.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014190.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014166.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014253.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014238.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014248.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014229.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014249.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014222.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014197.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014216.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014195.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014225.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014191.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014291.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014272.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014289.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014286.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014290.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014273.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014263.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014264.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014274.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014324.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014308.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014316.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014327.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014331.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014337.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014311.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014325.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014341.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014299.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014328.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014317.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014353.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014393.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014395.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014360.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014372.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014346.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014385.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014366.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014361.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014357.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014365.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014394.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014347.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014431.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014438.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014453.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014410.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014422.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014433.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014440.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014430.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014432.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014458.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014397.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014441.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014473.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014476.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014502.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014498.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014486.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014475.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014501.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014504.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014507.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014469.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014480.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014490.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014511.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014527.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014516.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014526.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014525.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014515.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014543.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014518.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014529.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014522.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014535.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014537.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014581.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014557.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014569.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014570.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014580.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014578.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014577.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014547.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014554.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014545.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014576.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014571.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014573.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014579.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014602.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014589.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014593.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014591.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014582.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014583.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014596.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014594.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014599.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014603.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014595.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014592.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014598.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014615.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014622.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014628.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014605.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014630.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014612.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014613.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014609.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014606.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014625.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014617.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014621.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014607.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014638.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014651.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014642.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014658.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014654.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014632.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014640.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014650.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014639.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014641.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014657.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014636.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014646.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014667.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014683.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014682.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014665.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014664.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014661.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014684.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014680.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014694.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014699.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014685.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014692.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014702.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014707.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014696.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014713.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014708.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014716.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014722.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014714.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014715.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014723.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014711.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014739.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014735.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014731.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014726.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014724.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014730.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014742.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014762.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014748.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014760.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014769.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014754.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014745.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014763.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014779.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014771.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014775.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014778.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014782.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014783.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014770.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014802.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014791.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014785.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014794.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014797.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014795.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014793.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014788.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014804.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014805.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014808.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014811.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014806.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014803.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014821.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014819.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014831.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014818.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014812.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014823.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014825.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014830.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014834.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014832.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014845.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014846.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014839.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014836.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014838.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014843.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014866.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014851.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014848.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014855.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014869.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014860.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014849.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014850.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014903.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014904.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014890.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014908.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014891.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014897.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014898.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014922.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014920.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014911.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014913.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014923.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014915.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014919.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014929.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014951.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014933.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014926.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014930.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014925.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014987.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015038.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015005.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014975.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015006.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0014983.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015032.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015109.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015108.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015082.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015110.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015079.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015044.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015045.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015158.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015112.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015166.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015153.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015168.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015170.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015181.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015113.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015189.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015204.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015190.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015220.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015200.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015233.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015219.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015182.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015295.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015260.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG/ISIC_0015284.jpg',
 ...]

1.3.1.4. Converting the Complete Filenames to Tensors

# train_tensors = paths_to_tensor(files).astype('float32')/255

1.3.2. Validation Data

1.3.2.1. Display the Filenames of Validation Data

valid_files

0      ISIC_0001769
1      ISIC_0001852
2      ISIC_0001871
3      ISIC_0003462
4      ISIC_0003539
           ...     
145    ISIC_0015443
146    ISIC_0015445
147    ISIC_0015483
148    ISIC_0015496
149    ISIC_0015627
Name: image_id, Length: 150, dtype: object

1.3.2.2. DIsplay all the Filenames present in the Dataset Directory

import os
os.chdir("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/")
!ls

ISIC_0001769.jpg  ISIC_0012221.jpg  ISIC_0013501.jpg  ISIC_0014611.jpg
ISIC_0001852.jpg  ISIC_0012222.jpg  ISIC_0013518.jpg  ISIC_0014616.jpg
ISIC_0001871.jpg  ISIC_0012254.jpg  ISIC_0013527.jpg  ISIC_0014618.jpg
ISIC_0003462.jpg  ISIC_0012256.jpg  ISIC_0013549.jpg  ISIC_0014620.jpg
ISIC_0003539.jpg  ISIC_0012288.jpg  ISIC_0013561.jpg  ISIC_0014623.jpg
ISIC_0003582.jpg  ISIC_0012306.jpg  ISIC_0013562.jpg  ISIC_0014624.jpg
ISIC_0003657.jpg  ISIC_0012313.jpg  ISIC_0013632.jpg  ISIC_0014633.jpg
ISIC_0003805.jpg  ISIC_0012316.jpg  ISIC_0013637.jpg  ISIC_0014635.jpg
ISIC_0004337.jpg  ISIC_0012335.jpg  ISIC_0013644.jpg  ISIC_0014637.jpg
ISIC_0006651.jpg  ISIC_0012380.jpg  ISIC_0013651.jpg  ISIC_0014688.jpg
ISIC_0006671.jpg  ISIC_0012383.jpg  ISIC_0013663.jpg  ISIC_0014712.jpg
ISIC_0006815.jpg  ISIC_0012400.jpg  ISIC_0013702.jpg  ISIC_0014809.jpg
ISIC_0006914.jpg  ISIC_0012417.jpg  ISIC_0013736.jpg  ISIC_0014829.jpg
ISIC_0007141.jpg  ISIC_0012434.jpg  ISIC_0013793.jpg  ISIC_0014857.jpg
ISIC_0007156.jpg  ISIC_0012492.jpg  ISIC_0013828.jpg  ISIC_0014931.jpg
ISIC_0007235.jpg  ISIC_0012513.jpg  ISIC_0013863.jpg  ISIC_0014937.jpg
ISIC_0007241.jpg  ISIC_0012538.jpg  ISIC_0013898.jpg  ISIC_0014945.jpg
ISIC_0007332.jpg  ISIC_0012547.jpg  ISIC_0013945.jpg  ISIC_0014946.jpg
ISIC_0007344.jpg  ISIC_0012660.jpg  ISIC_0014037.jpg  ISIC_0014979.jpg
ISIC_0007528.jpg  ISIC_0012684.jpg  ISIC_0014038.jpg  ISIC_0014985.jpg
ISIC_0007796.jpg  ISIC_0012720.jpg  ISIC_0014055.jpg  ISIC_0014989.jpg
ISIC_0008025.jpg  ISIC_0012746.jpg  ISIC_0014139.jpg  ISIC_0015043.jpg
ISIC_0008524.jpg  ISIC_0012876.jpg  ISIC_0014162.jpg  ISIC_0015062.jpg
ISIC_0009995.jpg  ISIC_0012927.jpg  ISIC_0014178.jpg  ISIC_0015124.jpg
ISIC_0010459.jpg  ISIC_0012956.jpg  ISIC_0014211.jpg  ISIC_0015144.jpg
ISIC_0012099.jpg  ISIC_0012959.jpg  ISIC_0014212.jpg  ISIC_0015211.jpg
ISIC_0012109.jpg  ISIC_0012965.jpg  ISIC_0014217.jpg  ISIC_0015243.jpg
ISIC_0012126.jpg  ISIC_0013010.jpg  ISIC_0014302.jpg  ISIC_0015256.jpg
ISIC_0012127.jpg  ISIC_0013082.jpg  ISIC_0014310.jpg  ISIC_0015313.jpg
ISIC_0012143.jpg  ISIC_0013104.jpg  ISIC_0014382.jpg  ISIC_0015372.jpg
ISIC_0012151.jpg  ISIC_0013127.jpg  ISIC_0014428.jpg  ISIC_0015401.jpg
ISIC_0012159.jpg  ISIC_0013128.jpg  ISIC_0014558.jpg  ISIC_0015443.jpg
ISIC_0012160.jpg  ISIC_0013132.jpg  ISIC_0014568.jpg  ISIC_0015445.jpg
ISIC_0012191.jpg  ISIC_0013188.jpg  ISIC_0014572.jpg  ISIC_0015483.jpg
ISIC_0012201.jpg  ISIC_0013215.jpg  ISIC_0014597.jpg  ISIC_0015496.jpg
ISIC_0012204.jpg  ISIC_0013232.jpg  ISIC_0014601.jpg  ISIC_0015627.jpg
ISIC_0012206.jpg  ISIC_0013421.jpg  ISIC_0014608.jpg
ISIC_0012210.jpg  ISIC_0013491.jpg  ISIC_0014610.jpg

1.3.2.3 Joining the Filenames with the Directory Path of Every File

dt = os.walk('/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG')
validation_files = []
for root, d_names, f_names in dt:
    for filename in f_names:
        validation_files.append(os.path.join(root, filename))

validation_files

['/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0004337.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003582.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003539.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003805.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006651.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001852.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003657.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003462.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001871.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007241.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006815.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006914.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007141.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007344.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007235.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007796.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008025.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008524.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007528.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007156.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007332.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006671.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0010459.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012099.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012126.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012160.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0009995.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012127.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012151.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012204.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012143.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012191.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012109.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012159.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012201.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012316.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012306.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012206.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012313.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012380.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012256.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012222.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012335.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012383.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012221.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012288.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012254.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012210.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012876.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012720.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012434.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012538.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012684.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012746.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012417.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012400.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012547.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012513.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012492.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012660.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013082.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013132.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013127.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013188.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012965.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012927.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012956.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013215.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013104.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013128.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012959.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013010.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013491.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013549.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013562.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013501.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013232.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013637.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013632.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013561.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013518.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013527.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013421.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013644.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013898.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013828.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013663.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013863.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013702.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014037.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013736.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013651.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014038.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013945.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013793.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014211.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014217.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014428.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014178.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014382.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014055.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014310.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014302.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014139.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014212.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014162.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014618.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014610.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014601.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014620.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014616.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014623.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014572.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014558.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014624.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014633.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014597.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014608.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014611.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014568.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014829.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014635.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014857.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014931.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014809.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014637.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014712.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014688.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014937.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014985.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014945.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014989.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014946.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014979.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015124.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015243.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015144.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015062.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015313.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015043.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015256.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015211.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015443.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015372.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015627.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015445.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015401.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015496.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015483.jpg']

1.3.2.4. Converting the Complete Filenames to Tensors

# valid_tensors = paths_to_tensor(validation_files).astype('float32')/255

1.3.3. Test Data

1.3.3.1. Display the Filenames of Testing Data

test_files

0      ISIC_0012086
1      ISIC_0012092
2      ISIC_0012095
3      ISIC_0012134
4      ISIC_0012136
           ...     
595    ISIC_0016068
596    ISIC_0016069
597    ISIC_0016070
598    ISIC_0016071
599    ISIC_0016072
Name: image_id, Length: 600, dtype: object

1.3.3.2. DIsplay all the Filenames present in the Dataset Directory

import os
os.chdir("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/")
!ls

ISIC_0012086.jpg  ISIC_0014027.jpg  ISIC_0014964.jpg  ISIC_0015482.jpg
ISIC_0012092.jpg  ISIC_0014059.jpg  ISIC_0014966.jpg  ISIC_0015485.jpg
ISIC_0012095.jpg  ISIC_0014077.jpg  ISIC_0014968.jpg  ISIC_0015510.jpg
ISIC_0012134.jpg  ISIC_0014090.jpg  ISIC_0014969.jpg  ISIC_0015526.jpg
ISIC_0012136.jpg  ISIC_0014103.jpg  ISIC_0014973.jpg  ISIC_0015537.jpg
ISIC_0012147.jpg  ISIC_0014110.jpg  ISIC_0014974.jpg  ISIC_0015544.jpg
ISIC_0012149.jpg  ISIC_0014117.jpg  ISIC_0014977.jpg  ISIC_0015559.jpg
ISIC_0012152.jpg  ISIC_0014129.jpg  ISIC_0014982.jpg  ISIC_0015563.jpg
ISIC_0012178.jpg  ISIC_0014148.jpg  ISIC_0014992.jpg  ISIC_0015566.jpg
ISIC_0012199.jpg  ISIC_0014160.jpg  ISIC_0014994.jpg  ISIC_0015568.jpg
ISIC_0012207.jpg  ISIC_0014177.jpg  ISIC_0014998.jpg  ISIC_0015582.jpg
ISIC_0012215.jpg  ISIC_0014181.jpg  ISIC_0015002.jpg  ISIC_0015593.jpg
ISIC_0012216.jpg  ISIC_0014186.jpg  ISIC_0015003.jpg  ISIC_0015603.jpg
ISIC_0012223.jpg  ISIC_0014219.jpg  ISIC_0015004.jpg  ISIC_0015607.jpg
ISIC_0012240.jpg  ISIC_0014221.jpg  ISIC_0015007.jpg  ISIC_0015614.jpg
ISIC_0012248.jpg  ISIC_0014233.jpg  ISIC_0015008.jpg  ISIC_0015617.jpg
ISIC_0012258.jpg  ISIC_0014251.jpg  ISIC_0015009.jpg  ISIC_0015625.jpg
ISIC_0012265.jpg  ISIC_0014255.jpg  ISIC_0015011.jpg  ISIC_0015631.jpg
ISIC_0012266.jpg  ISIC_0014270.jpg  ISIC_0015013.jpg  ISIC_0015636.jpg
ISIC_0012272.jpg  ISIC_0014278.jpg  ISIC_0015015.jpg  ISIC_0015638.jpg
ISIC_0012273.jpg  ISIC_0014284.jpg  ISIC_0015016.jpg  ISIC_0015641.jpg
ISIC_0012314.jpg  ISIC_0014288.jpg  ISIC_0015018.jpg  ISIC_0015645.jpg
ISIC_0012323.jpg  ISIC_0014319.jpg  ISIC_0015019.jpg  ISIC_0015936.jpg
ISIC_0012330.jpg  ISIC_0014336.jpg  ISIC_0015020.jpg  ISIC_0015937.jpg
ISIC_0012356.jpg  ISIC_0014349.jpg  ISIC_0015021.jpg  ISIC_0015938.jpg
ISIC_0012357.jpg  ISIC_0014369.jpg  ISIC_0015023.jpg  ISIC_0015939.jpg
ISIC_0012358.jpg  ISIC_0014386.jpg  ISIC_0015026.jpg  ISIC_0015940.jpg
ISIC_0012364.jpg  ISIC_0014392.jpg  ISIC_0015030.jpg  ISIC_0015941.jpg
ISIC_0012369.jpg  ISIC_0014409.jpg  ISIC_0015031.jpg  ISIC_0015942.jpg
ISIC_0012372.jpg  ISIC_0014419.jpg  ISIC_0015034.jpg  ISIC_0015943.jpg
ISIC_0012375.jpg  ISIC_0014423.jpg  ISIC_0015035.jpg  ISIC_0015944.jpg
ISIC_0012387.jpg  ISIC_0014434.jpg  ISIC_0015037.jpg  ISIC_0015945.jpg
ISIC_0012388.jpg  ISIC_0014454.jpg  ISIC_0015040.jpg  ISIC_0015946.jpg
ISIC_0012395.jpg  ISIC_0014457.jpg  ISIC_0015041.jpg  ISIC_0015947.jpg
ISIC_0012414.jpg  ISIC_0014470.jpg  ISIC_0015046.jpg  ISIC_0015948.jpg
ISIC_0012425.jpg  ISIC_0014474.jpg  ISIC_0015050.jpg  ISIC_0015949.jpg
ISIC_0012428.jpg  ISIC_0014478.jpg  ISIC_0015051.jpg  ISIC_0015950.jpg
ISIC_0012432.jpg  ISIC_0014489.jpg  ISIC_0015056.jpg  ISIC_0015951.jpg
ISIC_0012447.jpg  ISIC_0014500.jpg  ISIC_0015057.jpg  ISIC_0015952.jpg
ISIC_0012448.jpg  ISIC_0014503.jpg  ISIC_0015060.jpg  ISIC_0015953.jpg
ISIC_0012484.jpg  ISIC_0014506.jpg  ISIC_0015064.jpg  ISIC_0015954.jpg
ISIC_0012493.jpg  ISIC_0014513.jpg  ISIC_0015071.jpg  ISIC_0015955.jpg
ISIC_0012510.jpg  ISIC_0014541.jpg  ISIC_0015078.jpg  ISIC_0015956.jpg
ISIC_0012522.jpg  ISIC_0014542.jpg  ISIC_0015089.jpg  ISIC_0015957.jpg
ISIC_0012537.jpg  ISIC_0014546.jpg  ISIC_0015102.jpg  ISIC_0015958.jpg
ISIC_0012548.jpg  ISIC_0014548.jpg  ISIC_0015115.jpg  ISIC_0015959.jpg
ISIC_0012551.jpg  ISIC_0014559.jpg  ISIC_0015118.jpg  ISIC_0015960.jpg
ISIC_0012654.jpg  ISIC_0014567.jpg  ISIC_0015119.jpg  ISIC_0015961.jpg
ISIC_0012656.jpg  ISIC_0014574.jpg  ISIC_0015125.jpg  ISIC_0015962.jpg
ISIC_0012705.jpg  ISIC_0014575.jpg  ISIC_0015127.jpg  ISIC_0015963.jpg
ISIC_0012708.jpg  ISIC_0014586.jpg  ISIC_0015129.jpg  ISIC_0015964.jpg
ISIC_0012722.jpg  ISIC_0014587.jpg  ISIC_0015130.jpg  ISIC_0015965.jpg
ISIC_0012757.jpg  ISIC_0014588.jpg  ISIC_0015132.jpg  ISIC_0015966.jpg
ISIC_0012758.jpg  ISIC_0014590.jpg  ISIC_0015133.jpg  ISIC_0015967.jpg
ISIC_0012786.jpg  ISIC_0014600.jpg  ISIC_0015136.jpg  ISIC_0015968.jpg
ISIC_0012803.jpg  ISIC_0014619.jpg  ISIC_0015139.jpg  ISIC_0015969.jpg
ISIC_0012836.jpg  ISIC_0014626.jpg  ISIC_0015140.jpg  ISIC_0015971.jpg
ISIC_0012837.jpg  ISIC_0014627.jpg  ISIC_0015142.jpg  ISIC_0015972.jpg
ISIC_0012848.jpg  ISIC_0014629.jpg  ISIC_0015146.jpg  ISIC_0015973.jpg
ISIC_0012852.jpg  ISIC_0014631.jpg  ISIC_0015149.jpg  ISIC_0015974.jpg
ISIC_0012903.jpg  ISIC_0014634.jpg  ISIC_0015150.jpg  ISIC_0015975.jpg
ISIC_0012904.jpg  ISIC_0014643.jpg  ISIC_0015152.jpg  ISIC_0015976.jpg
ISIC_0012928.jpg  ISIC_0014644.jpg  ISIC_0015155.jpg  ISIC_0015978.jpg
ISIC_0012941.jpg  ISIC_0014645.jpg  ISIC_0015156.jpg  ISIC_0015979.jpg
ISIC_0012955.jpg  ISIC_0014647.jpg  ISIC_0015157.jpg  ISIC_0015980.jpg
ISIC_0012967.jpg  ISIC_0014648.jpg  ISIC_0015160.jpg  ISIC_0015981.jpg
ISIC_0012974.jpg  ISIC_0014649.jpg  ISIC_0015161.jpg  ISIC_0015982.jpg
ISIC_0012989.jpg  ISIC_0014652.jpg  ISIC_0015163.jpg  ISIC_0015983.jpg
ISIC_0013030.jpg  ISIC_0014653.jpg  ISIC_0015167.jpg  ISIC_0015984.jpg
ISIC_0013035.jpg  ISIC_0014663.jpg  ISIC_0015171.jpg  ISIC_0015985.jpg
ISIC_0013045.jpg  ISIC_0014666.jpg  ISIC_0015173.jpg  ISIC_0015986.jpg
ISIC_0013070.jpg  ISIC_0014675.jpg  ISIC_0015174.jpg  ISIC_0015987.jpg
ISIC_0013072.jpg  ISIC_0014677.jpg  ISIC_0015175.jpg  ISIC_0015988.jpg
ISIC_0013073.jpg  ISIC_0014687.jpg  ISIC_0015176.jpg  ISIC_0015989.jpg
ISIC_0013085.jpg  ISIC_0014693.jpg  ISIC_0015179.jpg  ISIC_0015990.jpg
ISIC_0013109.jpg  ISIC_0014695.jpg  ISIC_0015180.jpg  ISIC_0015991.jpg
ISIC_0013159.jpg  ISIC_0014697.jpg  ISIC_0015184.jpg  ISIC_0015992.jpg
ISIC_0013164.jpg  ISIC_0014698.jpg  ISIC_0015185.jpg  ISIC_0015993.jpg
ISIC_0013169.jpg  ISIC_0014703.jpg  ISIC_0015193.jpg  ISIC_0015994.jpg
ISIC_0013170.jpg  ISIC_0014720.jpg  ISIC_0015201.jpg  ISIC_0015995.jpg
ISIC_0013176.jpg  ISIC_0014725.jpg  ISIC_0015202.jpg  ISIC_0015996.jpg
ISIC_0013191.jpg  ISIC_0014727.jpg  ISIC_0015203.jpg  ISIC_0015997.jpg
ISIC_0013203.jpg  ISIC_0014728.jpg  ISIC_0015206.jpg  ISIC_0015998.jpg
ISIC_0013216.jpg  ISIC_0014729.jpg  ISIC_0015207.jpg  ISIC_0015999.jpg
ISIC_0013226.jpg  ISIC_0014740.jpg  ISIC_0015208.jpg  ISIC_0016000.jpg
ISIC_0013230.jpg  ISIC_0014743.jpg  ISIC_0015212.jpg  ISIC_0016001.jpg
ISIC_0013242.jpg  ISIC_0014746.jpg  ISIC_0015215.jpg  ISIC_0016002.jpg
ISIC_0013269.jpg  ISIC_0014749.jpg  ISIC_0015216.jpg  ISIC_0016003.jpg
ISIC_0013270.jpg  ISIC_0014753.jpg  ISIC_0015217.jpg  ISIC_0016004.jpg
ISIC_0013271.jpg  ISIC_0014755.jpg  ISIC_0015218.jpg  ISIC_0016005.jpg
ISIC_0013277.jpg  ISIC_0014765.jpg  ISIC_0015223.jpg  ISIC_0016006.jpg
ISIC_0013281.jpg  ISIC_0014766.jpg  ISIC_0015224.jpg  ISIC_0016007.jpg
ISIC_0013291.jpg  ISIC_0014768.jpg  ISIC_0015226.jpg  ISIC_0016008.jpg
ISIC_0013319.jpg  ISIC_0014772.jpg  ISIC_0015229.jpg  ISIC_0016009.jpg
ISIC_0013321.jpg  ISIC_0014773.jpg  ISIC_0015232.jpg  ISIC_0016011.jpg
ISIC_0013325.jpg  ISIC_0014780.jpg  ISIC_0015237.jpg  ISIC_0016012.jpg
ISIC_0013374.jpg  ISIC_0014784.jpg  ISIC_0015241.jpg  ISIC_0016013.jpg
ISIC_0013393.jpg  ISIC_0014786.jpg  ISIC_0015244.jpg  ISIC_0016014.jpg
ISIC_0013399.jpg  ISIC_0014787.jpg  ISIC_0015245.jpg  ISIC_0016015.jpg
ISIC_0013411.jpg  ISIC_0014790.jpg  ISIC_0015250.jpg  ISIC_0016016.jpg
ISIC_0013414.jpg  ISIC_0014792.jpg  ISIC_0015251.jpg  ISIC_0016017.jpg
ISIC_0013416.jpg  ISIC_0014796.jpg  ISIC_0015254.jpg  ISIC_0016018.jpg
ISIC_0013455.jpg  ISIC_0014798.jpg  ISIC_0015255.jpg  ISIC_0016019.jpg
ISIC_0013457.jpg  ISIC_0014800.jpg  ISIC_0015258.jpg  ISIC_0016022.jpg
ISIC_0013459.jpg  ISIC_0014807.jpg  ISIC_0015264.jpg  ISIC_0016023.jpg
ISIC_0013465.jpg  ISIC_0014814.jpg  ISIC_0015270.jpg  ISIC_0016024.jpg
ISIC_0013472.jpg  ISIC_0014815.jpg  ISIC_0015273.jpg  ISIC_0016025.jpg
ISIC_0013473.jpg  ISIC_0014820.jpg  ISIC_0015274.jpg  ISIC_0016026.jpg
ISIC_0013511.jpg  ISIC_0014822.jpg  ISIC_0015276.jpg  ISIC_0016027.jpg
ISIC_0013512.jpg  ISIC_0014826.jpg  ISIC_0015279.jpg  ISIC_0016028.jpg
ISIC_0013529.jpg  ISIC_0014833.jpg  ISIC_0015283.jpg  ISIC_0016029.jpg
ISIC_0013565.jpg  ISIC_0014835.jpg  ISIC_0015291.jpg  ISIC_0016030.jpg
ISIC_0013577.jpg  ISIC_0014844.jpg  ISIC_0015293.jpg  ISIC_0016031.jpg
ISIC_0013588.jpg  ISIC_0014853.jpg  ISIC_0015298.jpg  ISIC_0016033.jpg
ISIC_0013600.jpg  ISIC_0014854.jpg  ISIC_0015309.jpg  ISIC_0016034.jpg
ISIC_0013602.jpg  ISIC_0014862.jpg  ISIC_0015310.jpg  ISIC_0016035.jpg
ISIC_0013615.jpg  ISIC_0014863.jpg  ISIC_0015311.jpg  ISIC_0016036.jpg
ISIC_0013617.jpg  ISIC_0014867.jpg  ISIC_0015312.jpg  ISIC_0016037.jpg
ISIC_0013636.jpg  ISIC_0014868.jpg  ISIC_0015330.jpg  ISIC_0016038.jpg
ISIC_0013673.jpg  ISIC_0014872.jpg  ISIC_0015331.jpg  ISIC_0016040.jpg
ISIC_0013678.jpg  ISIC_0014876.jpg  ISIC_0015347.jpg  ISIC_0016041.jpg
ISIC_0013696.jpg  ISIC_0014879.jpg  ISIC_0015353.jpg  ISIC_0016042.jpg
ISIC_0013708.jpg  ISIC_0014883.jpg  ISIC_0015355.jpg  ISIC_0016043.jpg
ISIC_0013733.jpg  ISIC_0014901.jpg  ISIC_0015357.jpg  ISIC_0016044.jpg
ISIC_0013738.jpg  ISIC_0014907.jpg  ISIC_0015360.jpg  ISIC_0016045.jpg
ISIC_0013739.jpg  ISIC_0014910.jpg  ISIC_0015363.jpg  ISIC_0016046.jpg
ISIC_0013764.jpg  ISIC_0014912.jpg  ISIC_0015364.jpg  ISIC_0016048.jpg
ISIC_0013766.jpg  ISIC_0014921.jpg  ISIC_0015368.jpg  ISIC_0016049.jpg
ISIC_0013767.jpg  ISIC_0014927.jpg  ISIC_0015369.jpg  ISIC_0016050.jpg
ISIC_0013794.jpg  ISIC_0014928.jpg  ISIC_0015383.jpg  ISIC_0016051.jpg
ISIC_0013809.jpg  ISIC_0014932.jpg  ISIC_0015386.jpg  ISIC_0016052.jpg
ISIC_0013813.jpg  ISIC_0014936.jpg  ISIC_0015390.jpg  ISIC_0016053.jpg
ISIC_0013814.jpg  ISIC_0014938.jpg  ISIC_0015395.jpg  ISIC_0016054.jpg
ISIC_0013833.jpg  ISIC_0014940.jpg  ISIC_0015403.jpg  ISIC_0016055.jpg
ISIC_0013842.jpg  ISIC_0014941.jpg  ISIC_0015404.jpg  ISIC_0016056.jpg
ISIC_0013867.jpg  ISIC_0014942.jpg  ISIC_0015411.jpg  ISIC_0016057.jpg
ISIC_0013891.jpg  ISIC_0014943.jpg  ISIC_0015412.jpg  ISIC_0016058.jpg
ISIC_0013897.jpg  ISIC_0014944.jpg  ISIC_0015416.jpg  ISIC_0016059.jpg
ISIC_0013908.jpg  ISIC_0014947.jpg  ISIC_0015417.jpg  ISIC_0016060.jpg
ISIC_0013911.jpg  ISIC_0014948.jpg  ISIC_0015418.jpg  ISIC_0016061.jpg
ISIC_0013917.jpg  ISIC_0014949.jpg  ISIC_0015419.jpg  ISIC_0016062.jpg
ISIC_0013925.jpg  ISIC_0014952.jpg  ISIC_0015436.jpg  ISIC_0016063.jpg
ISIC_0013948.jpg  ISIC_0014955.jpg  ISIC_0015440.jpg  ISIC_0016064.jpg
ISIC_0013953.jpg  ISIC_0014956.jpg  ISIC_0015447.jpg  ISIC_0016065.jpg
ISIC_0013966.jpg  ISIC_0014957.jpg  ISIC_0015455.jpg  ISIC_0016066.jpg
ISIC_0013977.jpg  ISIC_0014958.jpg  ISIC_0015464.jpg  ISIC_0016068.jpg
ISIC_0013987.jpg  ISIC_0014959.jpg  ISIC_0015466.jpg  ISIC_0016069.jpg
ISIC_0013988.jpg  ISIC_0014961.jpg  ISIC_0015468.jpg  ISIC_0016070.jpg
ISIC_0013998.jpg  ISIC_0014962.jpg  ISIC_0015476.jpg  ISIC_0016071.jpg
ISIC_0014006.jpg  ISIC_0014963.jpg  ISIC_0015481.jpg  ISIC_0016072.jpg

1.3.3.3 Joining the Filenames with the Directory Path of Every File

# pre-process the data for Keras
# Training Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Training_Data/Data Images JPG
# os.path.join(folder, file)
dt = os.walk('/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG')
test_files = []
for root, d_names, f_names in dt:
    for filename in f_names:
        test_files.append(os.path.join(root, filename))

len(test_files)

600

test_files

['/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012095.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012092.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012086.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012215.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012240.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012207.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012216.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012149.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012178.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012136.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012152.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012199.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012223.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012248.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012147.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012134.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012358.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012266.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012356.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012258.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012314.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012357.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012272.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012364.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012330.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012323.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012265.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012273.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012375.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012448.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012369.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012387.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012428.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012447.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012395.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012425.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012432.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012372.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012414.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012388.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012654.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012708.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012656.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012551.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012537.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012705.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012510.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012548.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012484.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012493.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012722.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012522.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012848.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012903.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012904.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012852.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012955.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012837.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012836.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012786.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012967.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012757.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012928.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012803.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012941.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012758.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013085.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013170.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013030.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013109.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013035.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013169.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013159.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013072.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013045.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013070.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013073.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012974.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013164.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012989.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013203.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013319.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013281.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013291.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013242.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013216.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013230.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013191.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013277.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013176.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013271.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013226.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013270.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013269.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013416.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013393.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013459.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013472.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013399.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013473.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013414.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013325.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013457.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013321.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013455.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013374.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013411.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013465.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013678.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013696.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013511.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013615.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013588.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013617.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013529.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013577.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013636.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013602.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013673.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013512.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013600.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013565.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013813.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013733.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013766.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013764.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013767.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013739.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013794.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013708.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013833.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013738.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013814.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013809.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013842.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013867.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013908.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013897.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013911.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013977.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013917.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013987.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013988.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013966.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013953.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013948.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg',
 '/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg']

1.3.3.4. Converting the Complete Filenames to Tensors

# test_tensors = paths_to_tensor(test_files).astype('float32')/255

1.4. Saving Tensor Files

1.4.1 Saving Files into Drive

# Saving the data
# np.save("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_training_tensors.npy", train_tensors)
# np.save("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_validation_tensors.npy", valid_tensors)
# np.save("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_testing_tensors.npy", test_tensors)

1.4.2 Loading the Tensor Files into Model

# Loading the data
train_tensors = np.load("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_training_tensors.npy")
valid_tensors = np.load("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_validation_tensors.npy")
test_tensors = np.load("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved image tensors/augmented_testing_tensors.npy")

# Checking of the Tensor have loaded into the model
if train_tensors.any():
    print("\nTraining tensor is loaded into the model")
else:
    print("\nTraining tensor is not loaded into the model")

if valid_tensors.any():
    print("\nValidation tensor is loaded into the model")
else:
    print("\nValidation tensor is not loaded into the model")

if test_tensors.any():
    print("\nTesting tensor is loaded into the model")
else:
    print("\nTesting tensor is not loaded into the model")

Training tensor is loaded into the model

Validation tensor is loaded into the model

Testing tensor is loaded into the model

2. Training the model

Working Flowhcart:

2.1. MobileNet Architecture

2.1.1 Defining the MobileNet Architecture Function

def mobilenet_architecture():
    """
    Pre-build architecture of mobilenet for our dataset.
    """
    # Imprting the model
    from keras.applications.mobilenet import MobileNet

    # Pre-build model
    base_model = MobileNet(include_top = False, weights = None, input_shape = (512, 512, 3))

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    mobilenet_model = Model(base_model.input, output)
    
    # Getting the summary of architecture
    mobilenet_model.summary()
    
    # Compiling the model
    mobilenet_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])

    return mobilenet_model

# Getting the mobilenet
mobilenet_model = mobilenet_architecture()

Model: "model"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_1 (InputLayer)         [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d (Gl (None, 1024)              0         
_________________________________________________________________
dense (Dense)                (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________

2.1.2. Creating a Checkpoint for the Model

checkpointer = ModelCheckpoint(filepath='/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5', 
                               verbose=1, 
                               save_best_only=True)

2.1.3. Fitting into the Model

mobilenet_model.fit(train_tensors, 
                    train_targets, 
                    batch_size = 8,
                    validation_data = (valid_tensors, valid_targets),
                    epochs = 5,
                    callbacks=[checkpointer], 
                    verbose=1)

Epoch 1/5
250/250 [==============================] - 69s 204ms/step - loss: 0.6440 - accuracy: 0.7509 - val_loss: 0.6711 - val_accuracy: 0.8000

Epoch 00001: val_loss improved from inf to 0.67107, saving model to /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Epoch 2/5
250/250 [==============================] - 50s 202ms/step - loss: 0.5240 - accuracy: 0.8091 - val_loss: 0.5315 - val_accuracy: 0.8000

Epoch 00002: val_loss improved from 0.67107 to 0.53154, saving model to /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Epoch 3/5
250/250 [==============================] - 50s 201ms/step - loss: 0.5162 - accuracy: 0.7989 - val_loss: 0.5374 - val_accuracy: 0.8000

Epoch 00003: val_loss did not improve from 0.53154
Epoch 4/5
250/250 [==============================] - 50s 201ms/step - loss: 0.4957 - accuracy: 0.8112 - val_loss: 0.5716 - val_accuracy: 0.8000

Epoch 00004: val_loss did not improve from 0.53154
Epoch 5/5
250/250 [==============================] - 50s 200ms/step - loss: 0.5017 - accuracy: 0.8094 - val_loss: 0.5513 - val_accuracy: 0.7867

Epoch 00005: val_loss did not improve from 0.53154

<tensorflow.python.keras.callbacks.History at 0x7fb5c81b3290>

2.1.4. Loading the Weights for the MobileNet

# Loading the weights
mobilenet_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5")

2.2. Inception Architecture

2.2.1 Defining the Inception Architecture Function

def inception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model 
    from keras.applications.inception_v3 import InceptionV3

    # Pre-build model
    base_model = InceptionV3(include_top = False, weights = None, input_shape = (512, 512, 3))

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    inception_model = Model(base_model.input, output)
    
    # Summary of the model
    inception_model.summary()
    
    # Compiling the model
    inception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])
    
    return inception_model

# Getting the inception
inception_model = inception_architecture()

Model: "model_1"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_2 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d (Conv2D)                 (None, 255, 255, 32) 864         input_2[0][0]                    
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 255, 255, 32) 96          conv2d[0][0]                     
__________________________________________________________________________________________________
activation (Activation)         (None, 255, 255, 32) 0           batch_normalization[0][0]        
__________________________________________________________________________________________________
conv2d_1 (Conv2D)               (None, 253, 253, 32) 9216        activation[0][0]                 
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 253, 253, 32) 96          conv2d_1[0][0]                   
__________________________________________________________________________________________________
activation_1 (Activation)       (None, 253, 253, 32) 0           batch_normalization_1[0][0]      
__________________________________________________________________________________________________
conv2d_2 (Conv2D)               (None, 253, 253, 64) 18432       activation_1[0][0]               
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 253, 253, 64) 192         conv2d_2[0][0]                   
__________________________________________________________________________________________________
activation_2 (Activation)       (None, 253, 253, 64) 0           batch_normalization_2[0][0]      
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D)    (None, 126, 126, 64) 0           activation_2[0][0]               
__________________________________________________________________________________________________
conv2d_3 (Conv2D)               (None, 126, 126, 80) 5120        max_pooling2d[0][0]              
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 126, 126, 80) 240         conv2d_3[0][0]                   
__________________________________________________________________________________________________
activation_3 (Activation)       (None, 126, 126, 80) 0           batch_normalization_3[0][0]      
__________________________________________________________________________________________________
conv2d_4 (Conv2D)               (None, 124, 124, 192 138240      activation_3[0][0]               
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 124, 124, 192 576         conv2d_4[0][0]                   
__________________________________________________________________________________________________
activation_4 (Activation)       (None, 124, 124, 192 0           batch_normalization_4[0][0]      
__________________________________________________________________________________________________
max_pooling2d_1 (MaxPooling2D)  (None, 61, 61, 192)  0           activation_4[0][0]               
__________________________________________________________________________________________________
conv2d_8 (Conv2D)               (None, 61, 61, 64)   12288       max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 61, 61, 64)   192         conv2d_8[0][0]                   
__________________________________________________________________________________________________
activation_8 (Activation)       (None, 61, 61, 64)   0           batch_normalization_8[0][0]      
__________________________________________________________________________________________________
conv2d_6 (Conv2D)               (None, 61, 61, 48)   9216        max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
conv2d_9 (Conv2D)               (None, 61, 61, 96)   55296       activation_8[0][0]               
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 61, 61, 48)   144         conv2d_6[0][0]                   
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 61, 61, 96)   288         conv2d_9[0][0]                   
__________________________________________________________________________________________________
activation_6 (Activation)       (None, 61, 61, 48)   0           batch_normalization_6[0][0]      
__________________________________________________________________________________________________
activation_9 (Activation)       (None, 61, 61, 96)   0           batch_normalization_9[0][0]      
__________________________________________________________________________________________________
average_pooling2d (AveragePooli (None, 61, 61, 192)  0           max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
conv2d_5 (Conv2D)               (None, 61, 61, 64)   12288       max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
conv2d_7 (Conv2D)               (None, 61, 61, 64)   76800       activation_6[0][0]               
__________________________________________________________________________________________________
conv2d_10 (Conv2D)              (None, 61, 61, 96)   82944       activation_9[0][0]               
__________________________________________________________________________________________________
conv2d_11 (Conv2D)              (None, 61, 61, 32)   6144        average_pooling2d[0][0]          
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 61, 61, 64)   192         conv2d_5[0][0]                   
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 61, 61, 64)   192         conv2d_7[0][0]                   
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 61, 61, 96)   288         conv2d_10[0][0]                  
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 61, 61, 32)   96          conv2d_11[0][0]                  
__________________________________________________________________________________________________
activation_5 (Activation)       (None, 61, 61, 64)   0           batch_normalization_5[0][0]      
__________________________________________________________________________________________________
activation_7 (Activation)       (None, 61, 61, 64)   0           batch_normalization_7[0][0]      
__________________________________________________________________________________________________
activation_10 (Activation)      (None, 61, 61, 96)   0           batch_normalization_10[0][0]     
__________________________________________________________________________________________________
activation_11 (Activation)      (None, 61, 61, 32)   0           batch_normalization_11[0][0]     
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_5[0][0]               
                                                                 activation_7[0][0]               
                                                                 activation_10[0][0]              
                                                                 activation_11[0][0]              
__________________________________________________________________________________________________
conv2d_15 (Conv2D)              (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 61, 61, 64)   192         conv2d_15[0][0]                  
__________________________________________________________________________________________________
activation_15 (Activation)      (None, 61, 61, 64)   0           batch_normalization_15[0][0]     
__________________________________________________________________________________________________
conv2d_13 (Conv2D)              (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_16 (Conv2D)              (None, 61, 61, 96)   55296       activation_15[0][0]              
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 61, 61, 48)   144         conv2d_13[0][0]                  
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 61, 61, 96)   288         conv2d_16[0][0]                  
__________________________________________________________________________________________________
activation_13 (Activation)      (None, 61, 61, 48)   0           batch_normalization_13[0][0]     
__________________________________________________________________________________________________
activation_16 (Activation)      (None, 61, 61, 96)   0           batch_normalization_16[0][0]     
__________________________________________________________________________________________________
average_pooling2d_1 (AveragePoo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_12 (Conv2D)              (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_14 (Conv2D)              (None, 61, 61, 64)   76800       activation_13[0][0]              
__________________________________________________________________________________________________
conv2d_17 (Conv2D)              (None, 61, 61, 96)   82944       activation_16[0][0]              
__________________________________________________________________________________________________
conv2d_18 (Conv2D)              (None, 61, 61, 64)   16384       average_pooling2d_1[0][0]        
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 61, 61, 64)   192         conv2d_12[0][0]                  
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 61, 61, 64)   192         conv2d_14[0][0]                  
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 61, 61, 96)   288         conv2d_17[0][0]                  
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, 61, 61, 64)   192         conv2d_18[0][0]                  
__________________________________________________________________________________________________
activation_12 (Activation)      (None, 61, 61, 64)   0           batch_normalization_12[0][0]     
__________________________________________________________________________________________________
activation_14 (Activation)      (None, 61, 61, 64)   0           batch_normalization_14[0][0]     
__________________________________________________________________________________________________
activation_17 (Activation)      (None, 61, 61, 96)   0           batch_normalization_17[0][0]     
__________________________________________________________________________________________________
activation_18 (Activation)      (None, 61, 61, 64)   0           batch_normalization_18[0][0]     
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_12[0][0]              
                                                                 activation_14[0][0]              
                                                                 activation_17[0][0]              
                                                                 activation_18[0][0]              
__________________________________________________________________________________________________
conv2d_22 (Conv2D)              (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, 61, 61, 64)   192         conv2d_22[0][0]                  
__________________________________________________________________________________________________
activation_22 (Activation)      (None, 61, 61, 64)   0           batch_normalization_22[0][0]     
__________________________________________________________________________________________________
conv2d_20 (Conv2D)              (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_23 (Conv2D)              (None, 61, 61, 96)   55296       activation_22[0][0]              
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, 61, 61, 48)   144         conv2d_20[0][0]                  
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, 61, 61, 96)   288         conv2d_23[0][0]                  
__________________________________________________________________________________________________
activation_20 (Activation)      (None, 61, 61, 48)   0           batch_normalization_20[0][0]     
__________________________________________________________________________________________________
activation_23 (Activation)      (None, 61, 61, 96)   0           batch_normalization_23[0][0]     
__________________________________________________________________________________________________
average_pooling2d_2 (AveragePoo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_19 (Conv2D)              (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_21 (Conv2D)              (None, 61, 61, 64)   76800       activation_20[0][0]              
__________________________________________________________________________________________________
conv2d_24 (Conv2D)              (None, 61, 61, 96)   82944       activation_23[0][0]              
__________________________________________________________________________________________________
conv2d_25 (Conv2D)              (None, 61, 61, 64)   18432       average_pooling2d_2[0][0]        
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, 61, 61, 64)   192         conv2d_19[0][0]                  
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, 61, 61, 64)   192         conv2d_21[0][0]                  
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, 61, 61, 96)   288         conv2d_24[0][0]                  
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, 61, 61, 64)   192         conv2d_25[0][0]                  
__________________________________________________________________________________________________
activation_19 (Activation)      (None, 61, 61, 64)   0           batch_normalization_19[0][0]     
__________________________________________________________________________________________________
activation_21 (Activation)      (None, 61, 61, 64)   0           batch_normalization_21[0][0]     
__________________________________________________________________________________________________
activation_24 (Activation)      (None, 61, 61, 96)   0           batch_normalization_24[0][0]     
__________________________________________________________________________________________________
activation_25 (Activation)      (None, 61, 61, 64)   0           batch_normalization_25[0][0]     
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_19[0][0]              
                                                                 activation_21[0][0]              
                                                                 activation_24[0][0]              
                                                                 activation_25[0][0]              
__________________________________________________________________________________________________
conv2d_27 (Conv2D)              (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 61, 61, 64)   192         conv2d_27[0][0]                  
__________________________________________________________________________________________________
activation_27 (Activation)      (None, 61, 61, 64)   0           batch_normalization_27[0][0]     
__________________________________________________________________________________________________
conv2d_28 (Conv2D)              (None, 61, 61, 96)   55296       activation_27[0][0]              
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, 61, 61, 96)   288         conv2d_28[0][0]                  
__________________________________________________________________________________________________
activation_28 (Activation)      (None, 61, 61, 96)   0           batch_normalization_28[0][0]     
__________________________________________________________________________________________________
conv2d_26 (Conv2D)              (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_29 (Conv2D)              (None, 30, 30, 96)   82944       activation_28[0][0]              
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, 30, 30, 384)  1152        conv2d_26[0][0]                  
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, 30, 30, 96)   288         conv2d_29[0][0]                  
__________________________________________________________________________________________________
activation_26 (Activation)      (None, 30, 30, 384)  0           batch_normalization_26[0][0]     
__________________________________________________________________________________________________
activation_29 (Activation)      (None, 30, 30, 96)   0           batch_normalization_29[0][0]     
__________________________________________________________________________________________________
max_pooling2d_2 (MaxPooling2D)  (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_26[0][0]              
                                                                 activation_29[0][0]              
                                                                 max_pooling2d_2[0][0]            
__________________________________________________________________________________________________
conv2d_34 (Conv2D)              (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_34 (BatchNo (None, 30, 30, 128)  384         conv2d_34[0][0]                  
__________________________________________________________________________________________________
activation_34 (Activation)      (None, 30, 30, 128)  0           batch_normalization_34[0][0]     
__________________________________________________________________________________________________
conv2d_35 (Conv2D)              (None, 30, 30, 128)  114688      activation_34[0][0]              
__________________________________________________________________________________________________
batch_normalization_35 (BatchNo (None, 30, 30, 128)  384         conv2d_35[0][0]                  
__________________________________________________________________________________________________
activation_35 (Activation)      (None, 30, 30, 128)  0           batch_normalization_35[0][0]     
__________________________________________________________________________________________________
conv2d_31 (Conv2D)              (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_36 (Conv2D)              (None, 30, 30, 128)  114688      activation_35[0][0]              
__________________________________________________________________________________________________
batch_normalization_31 (BatchNo (None, 30, 30, 128)  384         conv2d_31[0][0]                  
__________________________________________________________________________________________________
batch_normalization_36 (BatchNo (None, 30, 30, 128)  384         conv2d_36[0][0]                  
__________________________________________________________________________________________________
activation_31 (Activation)      (None, 30, 30, 128)  0           batch_normalization_31[0][0]     
__________________________________________________________________________________________________
activation_36 (Activation)      (None, 30, 30, 128)  0           batch_normalization_36[0][0]     
__________________________________________________________________________________________________
conv2d_32 (Conv2D)              (None, 30, 30, 128)  114688      activation_31[0][0]              
__________________________________________________________________________________________________
conv2d_37 (Conv2D)              (None, 30, 30, 128)  114688      activation_36[0][0]              
__________________________________________________________________________________________________
batch_normalization_32 (BatchNo (None, 30, 30, 128)  384         conv2d_32[0][0]                  
__________________________________________________________________________________________________
batch_normalization_37 (BatchNo (None, 30, 30, 128)  384         conv2d_37[0][0]                  
__________________________________________________________________________________________________
activation_32 (Activation)      (None, 30, 30, 128)  0           batch_normalization_32[0][0]     
__________________________________________________________________________________________________
activation_37 (Activation)      (None, 30, 30, 128)  0           batch_normalization_37[0][0]     
__________________________________________________________________________________________________
average_pooling2d_3 (AveragePoo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_30 (Conv2D)              (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_33 (Conv2D)              (None, 30, 30, 192)  172032      activation_32[0][0]              
__________________________________________________________________________________________________
conv2d_38 (Conv2D)              (None, 30, 30, 192)  172032      activation_37[0][0]              
__________________________________________________________________________________________________
conv2d_39 (Conv2D)              (None, 30, 30, 192)  147456      average_pooling2d_3[0][0]        
__________________________________________________________________________________________________
batch_normalization_30 (BatchNo (None, 30, 30, 192)  576         conv2d_30[0][0]                  
__________________________________________________________________________________________________
batch_normalization_33 (BatchNo (None, 30, 30, 192)  576         conv2d_33[0][0]                  
__________________________________________________________________________________________________
batch_normalization_38 (BatchNo (None, 30, 30, 192)  576         conv2d_38[0][0]                  
__________________________________________________________________________________________________
batch_normalization_39 (BatchNo (None, 30, 30, 192)  576         conv2d_39[0][0]                  
__________________________________________________________________________________________________
activation_30 (Activation)      (None, 30, 30, 192)  0           batch_normalization_30[0][0]     
__________________________________________________________________________________________________
activation_33 (Activation)      (None, 30, 30, 192)  0           batch_normalization_33[0][0]     
__________________________________________________________________________________________________
activation_38 (Activation)      (None, 30, 30, 192)  0           batch_normalization_38[0][0]     
__________________________________________________________________________________________________
activation_39 (Activation)      (None, 30, 30, 192)  0           batch_normalization_39[0][0]     
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_30[0][0]              
                                                                 activation_33[0][0]              
                                                                 activation_38[0][0]              
                                                                 activation_39[0][0]              
__________________________________________________________________________________________________
conv2d_44 (Conv2D)              (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_44 (BatchNo (None, 30, 30, 160)  480         conv2d_44[0][0]                  
__________________________________________________________________________________________________
activation_44 (Activation)      (None, 30, 30, 160)  0           batch_normalization_44[0][0]     
__________________________________________________________________________________________________
conv2d_45 (Conv2D)              (None, 30, 30, 160)  179200      activation_44[0][0]              
__________________________________________________________________________________________________
batch_normalization_45 (BatchNo (None, 30, 30, 160)  480         conv2d_45[0][0]                  
__________________________________________________________________________________________________
activation_45 (Activation)      (None, 30, 30, 160)  0           batch_normalization_45[0][0]     
__________________________________________________________________________________________________
conv2d_41 (Conv2D)              (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_46 (Conv2D)              (None, 30, 30, 160)  179200      activation_45[0][0]              
__________________________________________________________________________________________________
batch_normalization_41 (BatchNo (None, 30, 30, 160)  480         conv2d_41[0][0]                  
__________________________________________________________________________________________________
batch_normalization_46 (BatchNo (None, 30, 30, 160)  480         conv2d_46[0][0]                  
__________________________________________________________________________________________________
activation_41 (Activation)      (None, 30, 30, 160)  0           batch_normalization_41[0][0]     
__________________________________________________________________________________________________
activation_46 (Activation)      (None, 30, 30, 160)  0           batch_normalization_46[0][0]     
__________________________________________________________________________________________________
conv2d_42 (Conv2D)              (None, 30, 30, 160)  179200      activation_41[0][0]              
__________________________________________________________________________________________________
conv2d_47 (Conv2D)              (None, 30, 30, 160)  179200      activation_46[0][0]              
__________________________________________________________________________________________________
batch_normalization_42 (BatchNo (None, 30, 30, 160)  480         conv2d_42[0][0]                  
__________________________________________________________________________________________________
batch_normalization_47 (BatchNo (None, 30, 30, 160)  480         conv2d_47[0][0]                  
__________________________________________________________________________________________________
activation_42 (Activation)      (None, 30, 30, 160)  0           batch_normalization_42[0][0]     
__________________________________________________________________________________________________
activation_47 (Activation)      (None, 30, 30, 160)  0           batch_normalization_47[0][0]     
__________________________________________________________________________________________________
average_pooling2d_4 (AveragePoo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_40 (Conv2D)              (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_43 (Conv2D)              (None, 30, 30, 192)  215040      activation_42[0][0]              
__________________________________________________________________________________________________
conv2d_48 (Conv2D)              (None, 30, 30, 192)  215040      activation_47[0][0]              
__________________________________________________________________________________________________
conv2d_49 (Conv2D)              (None, 30, 30, 192)  147456      average_pooling2d_4[0][0]        
__________________________________________________________________________________________________
batch_normalization_40 (BatchNo (None, 30, 30, 192)  576         conv2d_40[0][0]                  
__________________________________________________________________________________________________
batch_normalization_43 (BatchNo (None, 30, 30, 192)  576         conv2d_43[0][0]                  
__________________________________________________________________________________________________
batch_normalization_48 (BatchNo (None, 30, 30, 192)  576         conv2d_48[0][0]                  
__________________________________________________________________________________________________
batch_normalization_49 (BatchNo (None, 30, 30, 192)  576         conv2d_49[0][0]                  
__________________________________________________________________________________________________
activation_40 (Activation)      (None, 30, 30, 192)  0           batch_normalization_40[0][0]     
__________________________________________________________________________________________________
activation_43 (Activation)      (None, 30, 30, 192)  0           batch_normalization_43[0][0]     
__________________________________________________________________________________________________
activation_48 (Activation)      (None, 30, 30, 192)  0           batch_normalization_48[0][0]     
__________________________________________________________________________________________________
activation_49 (Activation)      (None, 30, 30, 192)  0           batch_normalization_49[0][0]     
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_40[0][0]              
                                                                 activation_43[0][0]              
                                                                 activation_48[0][0]              
                                                                 activation_49[0][0]              
__________________________________________________________________________________________________
conv2d_54 (Conv2D)              (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_54 (BatchNo (None, 30, 30, 160)  480         conv2d_54[0][0]                  
__________________________________________________________________________________________________
activation_54 (Activation)      (None, 30, 30, 160)  0           batch_normalization_54[0][0]     
__________________________________________________________________________________________________
conv2d_55 (Conv2D)              (None, 30, 30, 160)  179200      activation_54[0][0]              
__________________________________________________________________________________________________
batch_normalization_55 (BatchNo (None, 30, 30, 160)  480         conv2d_55[0][0]                  
__________________________________________________________________________________________________
activation_55 (Activation)      (None, 30, 30, 160)  0           batch_normalization_55[0][0]     
__________________________________________________________________________________________________
conv2d_51 (Conv2D)              (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_56 (Conv2D)              (None, 30, 30, 160)  179200      activation_55[0][0]              
__________________________________________________________________________________________________
batch_normalization_51 (BatchNo (None, 30, 30, 160)  480         conv2d_51[0][0]                  
__________________________________________________________________________________________________
batch_normalization_56 (BatchNo (None, 30, 30, 160)  480         conv2d_56[0][0]                  
__________________________________________________________________________________________________
activation_51 (Activation)      (None, 30, 30, 160)  0           batch_normalization_51[0][0]     
__________________________________________________________________________________________________
activation_56 (Activation)      (None, 30, 30, 160)  0           batch_normalization_56[0][0]     
__________________________________________________________________________________________________
conv2d_52 (Conv2D)              (None, 30, 30, 160)  179200      activation_51[0][0]              
__________________________________________________________________________________________________
conv2d_57 (Conv2D)              (None, 30, 30, 160)  179200      activation_56[0][0]              
__________________________________________________________________________________________________
batch_normalization_52 (BatchNo (None, 30, 30, 160)  480         conv2d_52[0][0]                  
__________________________________________________________________________________________________
batch_normalization_57 (BatchNo (None, 30, 30, 160)  480         conv2d_57[0][0]                  
__________________________________________________________________________________________________
activation_52 (Activation)      (None, 30, 30, 160)  0           batch_normalization_52[0][0]     
__________________________________________________________________________________________________
activation_57 (Activation)      (None, 30, 30, 160)  0           batch_normalization_57[0][0]     
__________________________________________________________________________________________________
average_pooling2d_5 (AveragePoo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_50 (Conv2D)              (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_53 (Conv2D)              (None, 30, 30, 192)  215040      activation_52[0][0]              
__________________________________________________________________________________________________
conv2d_58 (Conv2D)              (None, 30, 30, 192)  215040      activation_57[0][0]              
__________________________________________________________________________________________________
conv2d_59 (Conv2D)              (None, 30, 30, 192)  147456      average_pooling2d_5[0][0]        
__________________________________________________________________________________________________
batch_normalization_50 (BatchNo (None, 30, 30, 192)  576         conv2d_50[0][0]                  
__________________________________________________________________________________________________
batch_normalization_53 (BatchNo (None, 30, 30, 192)  576         conv2d_53[0][0]                  
__________________________________________________________________________________________________
batch_normalization_58 (BatchNo (None, 30, 30, 192)  576         conv2d_58[0][0]                  
__________________________________________________________________________________________________
batch_normalization_59 (BatchNo (None, 30, 30, 192)  576         conv2d_59[0][0]                  
__________________________________________________________________________________________________
activation_50 (Activation)      (None, 30, 30, 192)  0           batch_normalization_50[0][0]     
__________________________________________________________________________________________________
activation_53 (Activation)      (None, 30, 30, 192)  0           batch_normalization_53[0][0]     
__________________________________________________________________________________________________
activation_58 (Activation)      (None, 30, 30, 192)  0           batch_normalization_58[0][0]     
__________________________________________________________________________________________________
activation_59 (Activation)      (None, 30, 30, 192)  0           batch_normalization_59[0][0]     
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_50[0][0]              
                                                                 activation_53[0][0]              
                                                                 activation_58[0][0]              
                                                                 activation_59[0][0]              
__________________________________________________________________________________________________
conv2d_64 (Conv2D)              (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_64 (BatchNo (None, 30, 30, 192)  576         conv2d_64[0][0]                  
__________________________________________________________________________________________________
activation_64 (Activation)      (None, 30, 30, 192)  0           batch_normalization_64[0][0]     
__________________________________________________________________________________________________
conv2d_65 (Conv2D)              (None, 30, 30, 192)  258048      activation_64[0][0]              
__________________________________________________________________________________________________
batch_normalization_65 (BatchNo (None, 30, 30, 192)  576         conv2d_65[0][0]                  
__________________________________________________________________________________________________
activation_65 (Activation)      (None, 30, 30, 192)  0           batch_normalization_65[0][0]     
__________________________________________________________________________________________________
conv2d_61 (Conv2D)              (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_66 (Conv2D)              (None, 30, 30, 192)  258048      activation_65[0][0]              
__________________________________________________________________________________________________
batch_normalization_61 (BatchNo (None, 30, 30, 192)  576         conv2d_61[0][0]                  
__________________________________________________________________________________________________
batch_normalization_66 (BatchNo (None, 30, 30, 192)  576         conv2d_66[0][0]                  
__________________________________________________________________________________________________
activation_61 (Activation)      (None, 30, 30, 192)  0           batch_normalization_61[0][0]     
__________________________________________________________________________________________________
activation_66 (Activation)      (None, 30, 30, 192)  0           batch_normalization_66[0][0]     
__________________________________________________________________________________________________
conv2d_62 (Conv2D)              (None, 30, 30, 192)  258048      activation_61[0][0]              
__________________________________________________________________________________________________
conv2d_67 (Conv2D)              (None, 30, 30, 192)  258048      activation_66[0][0]              
__________________________________________________________________________________________________
batch_normalization_62 (BatchNo (None, 30, 30, 192)  576         conv2d_62[0][0]                  
__________________________________________________________________________________________________
batch_normalization_67 (BatchNo (None, 30, 30, 192)  576         conv2d_67[0][0]                  
__________________________________________________________________________________________________
activation_62 (Activation)      (None, 30, 30, 192)  0           batch_normalization_62[0][0]     
__________________________________________________________________________________________________
activation_67 (Activation)      (None, 30, 30, 192)  0           batch_normalization_67[0][0]     
__________________________________________________________________________________________________
average_pooling2d_6 (AveragePoo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_60 (Conv2D)              (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_63 (Conv2D)              (None, 30, 30, 192)  258048      activation_62[0][0]              
__________________________________________________________________________________________________
conv2d_68 (Conv2D)              (None, 30, 30, 192)  258048      activation_67[0][0]              
__________________________________________________________________________________________________
conv2d_69 (Conv2D)              (None, 30, 30, 192)  147456      average_pooling2d_6[0][0]        
__________________________________________________________________________________________________
batch_normalization_60 (BatchNo (None, 30, 30, 192)  576         conv2d_60[0][0]                  
__________________________________________________________________________________________________
batch_normalization_63 (BatchNo (None, 30, 30, 192)  576         conv2d_63[0][0]                  
__________________________________________________________________________________________________
batch_normalization_68 (BatchNo (None, 30, 30, 192)  576         conv2d_68[0][0]                  
__________________________________________________________________________________________________
batch_normalization_69 (BatchNo (None, 30, 30, 192)  576         conv2d_69[0][0]                  
__________________________________________________________________________________________________
activation_60 (Activation)      (None, 30, 30, 192)  0           batch_normalization_60[0][0]     
__________________________________________________________________________________________________
activation_63 (Activation)      (None, 30, 30, 192)  0           batch_normalization_63[0][0]     
__________________________________________________________________________________________________
activation_68 (Activation)      (None, 30, 30, 192)  0           batch_normalization_68[0][0]     
__________________________________________________________________________________________________
activation_69 (Activation)      (None, 30, 30, 192)  0           batch_normalization_69[0][0]     
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_60[0][0]              
                                                                 activation_63[0][0]              
                                                                 activation_68[0][0]              
                                                                 activation_69[0][0]              
__________________________________________________________________________________________________
conv2d_72 (Conv2D)              (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_72 (BatchNo (None, 30, 30, 192)  576         conv2d_72[0][0]                  
__________________________________________________________________________________________________
activation_72 (Activation)      (None, 30, 30, 192)  0           batch_normalization_72[0][0]     
__________________________________________________________________________________________________
conv2d_73 (Conv2D)              (None, 30, 30, 192)  258048      activation_72[0][0]              
__________________________________________________________________________________________________
batch_normalization_73 (BatchNo (None, 30, 30, 192)  576         conv2d_73[0][0]                  
__________________________________________________________________________________________________
activation_73 (Activation)      (None, 30, 30, 192)  0           batch_normalization_73[0][0]     
__________________________________________________________________________________________________
conv2d_70 (Conv2D)              (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_74 (Conv2D)              (None, 30, 30, 192)  258048      activation_73[0][0]              
__________________________________________________________________________________________________
batch_normalization_70 (BatchNo (None, 30, 30, 192)  576         conv2d_70[0][0]                  
__________________________________________________________________________________________________
batch_normalization_74 (BatchNo (None, 30, 30, 192)  576         conv2d_74[0][0]                  
__________________________________________________________________________________________________
activation_70 (Activation)      (None, 30, 30, 192)  0           batch_normalization_70[0][0]     
__________________________________________________________________________________________________
activation_74 (Activation)      (None, 30, 30, 192)  0           batch_normalization_74[0][0]     
__________________________________________________________________________________________________
conv2d_71 (Conv2D)              (None, 14, 14, 320)  552960      activation_70[0][0]              
__________________________________________________________________________________________________
conv2d_75 (Conv2D)              (None, 14, 14, 192)  331776      activation_74[0][0]              
__________________________________________________________________________________________________
batch_normalization_71 (BatchNo (None, 14, 14, 320)  960         conv2d_71[0][0]                  
__________________________________________________________________________________________________
batch_normalization_75 (BatchNo (None, 14, 14, 192)  576         conv2d_75[0][0]                  
__________________________________________________________________________________________________
activation_71 (Activation)      (None, 14, 14, 320)  0           batch_normalization_71[0][0]     
__________________________________________________________________________________________________
activation_75 (Activation)      (None, 14, 14, 192)  0           batch_normalization_75[0][0]     
__________________________________________________________________________________________________
max_pooling2d_3 (MaxPooling2D)  (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_71[0][0]              
                                                                 activation_75[0][0]              
                                                                 max_pooling2d_3[0][0]            
__________________________________________________________________________________________________
conv2d_80 (Conv2D)              (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_80 (BatchNo (None, 14, 14, 448)  1344        conv2d_80[0][0]                  
__________________________________________________________________________________________________
activation_80 (Activation)      (None, 14, 14, 448)  0           batch_normalization_80[0][0]     
__________________________________________________________________________________________________
conv2d_77 (Conv2D)              (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_81 (Conv2D)              (None, 14, 14, 384)  1548288     activation_80[0][0]              
__________________________________________________________________________________________________
batch_normalization_77 (BatchNo (None, 14, 14, 384)  1152        conv2d_77[0][0]                  
__________________________________________________________________________________________________
batch_normalization_81 (BatchNo (None, 14, 14, 384)  1152        conv2d_81[0][0]                  
__________________________________________________________________________________________________
activation_77 (Activation)      (None, 14, 14, 384)  0           batch_normalization_77[0][0]     
__________________________________________________________________________________________________
activation_81 (Activation)      (None, 14, 14, 384)  0           batch_normalization_81[0][0]     
__________________________________________________________________________________________________
conv2d_78 (Conv2D)              (None, 14, 14, 384)  442368      activation_77[0][0]              
__________________________________________________________________________________________________
conv2d_79 (Conv2D)              (None, 14, 14, 384)  442368      activation_77[0][0]              
__________________________________________________________________________________________________
conv2d_82 (Conv2D)              (None, 14, 14, 384)  442368      activation_81[0][0]              
__________________________________________________________________________________________________
conv2d_83 (Conv2D)              (None, 14, 14, 384)  442368      activation_81[0][0]              
__________________________________________________________________________________________________
average_pooling2d_7 (AveragePoo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_76 (Conv2D)              (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_78 (BatchNo (None, 14, 14, 384)  1152        conv2d_78[0][0]                  
__________________________________________________________________________________________________
batch_normalization_79 (BatchNo (None, 14, 14, 384)  1152        conv2d_79[0][0]                  
__________________________________________________________________________________________________
batch_normalization_82 (BatchNo (None, 14, 14, 384)  1152        conv2d_82[0][0]                  
__________________________________________________________________________________________________
batch_normalization_83 (BatchNo (None, 14, 14, 384)  1152        conv2d_83[0][0]                  
__________________________________________________________________________________________________
conv2d_84 (Conv2D)              (None, 14, 14, 192)  245760      average_pooling2d_7[0][0]        
__________________________________________________________________________________________________
batch_normalization_76 (BatchNo (None, 14, 14, 320)  960         conv2d_76[0][0]                  
__________________________________________________________________________________________________
activation_78 (Activation)      (None, 14, 14, 384)  0           batch_normalization_78[0][0]     
__________________________________________________________________________________________________
activation_79 (Activation)      (None, 14, 14, 384)  0           batch_normalization_79[0][0]     
__________________________________________________________________________________________________
activation_82 (Activation)      (None, 14, 14, 384)  0           batch_normalization_82[0][0]     
__________________________________________________________________________________________________
activation_83 (Activation)      (None, 14, 14, 384)  0           batch_normalization_83[0][0]     
__________________________________________________________________________________________________
batch_normalization_84 (BatchNo (None, 14, 14, 192)  576         conv2d_84[0][0]                  
__________________________________________________________________________________________________
activation_76 (Activation)      (None, 14, 14, 320)  0           batch_normalization_76[0][0]     
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_78[0][0]              
                                                                 activation_79[0][0]              
__________________________________________________________________________________________________
concatenate (Concatenate)       (None, 14, 14, 768)  0           activation_82[0][0]              
                                                                 activation_83[0][0]              
__________________________________________________________________________________________________
activation_84 (Activation)      (None, 14, 14, 192)  0           batch_normalization_84[0][0]     
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_76[0][0]              
                                                                 mixed9_0[0][0]                   
                                                                 concatenate[0][0]                
                                                                 activation_84[0][0]              
__________________________________________________________________________________________________
conv2d_89 (Conv2D)              (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_89 (BatchNo (None, 14, 14, 448)  1344        conv2d_89[0][0]                  
__________________________________________________________________________________________________
activation_89 (Activation)      (None, 14, 14, 448)  0           batch_normalization_89[0][0]     
__________________________________________________________________________________________________
conv2d_86 (Conv2D)              (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_90 (Conv2D)              (None, 14, 14, 384)  1548288     activation_89[0][0]              
__________________________________________________________________________________________________
batch_normalization_86 (BatchNo (None, 14, 14, 384)  1152        conv2d_86[0][0]                  
__________________________________________________________________________________________________
batch_normalization_90 (BatchNo (None, 14, 14, 384)  1152        conv2d_90[0][0]                  
__________________________________________________________________________________________________
activation_86 (Activation)      (None, 14, 14, 384)  0           batch_normalization_86[0][0]     
__________________________________________________________________________________________________
activation_90 (Activation)      (None, 14, 14, 384)  0           batch_normalization_90[0][0]     
__________________________________________________________________________________________________
conv2d_87 (Conv2D)              (None, 14, 14, 384)  442368      activation_86[0][0]              
__________________________________________________________________________________________________
conv2d_88 (Conv2D)              (None, 14, 14, 384)  442368      activation_86[0][0]              
__________________________________________________________________________________________________
conv2d_91 (Conv2D)              (None, 14, 14, 384)  442368      activation_90[0][0]              
__________________________________________________________________________________________________
conv2d_92 (Conv2D)              (None, 14, 14, 384)  442368      activation_90[0][0]              
__________________________________________________________________________________________________
average_pooling2d_8 (AveragePoo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_85 (Conv2D)              (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_87 (BatchNo (None, 14, 14, 384)  1152        conv2d_87[0][0]                  
__________________________________________________________________________________________________
batch_normalization_88 (BatchNo (None, 14, 14, 384)  1152        conv2d_88[0][0]                  
__________________________________________________________________________________________________
batch_normalization_91 (BatchNo (None, 14, 14, 384)  1152        conv2d_91[0][0]                  
__________________________________________________________________________________________________
batch_normalization_92 (BatchNo (None, 14, 14, 384)  1152        conv2d_92[0][0]                  
__________________________________________________________________________________________________
conv2d_93 (Conv2D)              (None, 14, 14, 192)  393216      average_pooling2d_8[0][0]        
__________________________________________________________________________________________________
batch_normalization_85 (BatchNo (None, 14, 14, 320)  960         conv2d_85[0][0]                  
__________________________________________________________________________________________________
activation_87 (Activation)      (None, 14, 14, 384)  0           batch_normalization_87[0][0]     
__________________________________________________________________________________________________
activation_88 (Activation)      (None, 14, 14, 384)  0           batch_normalization_88[0][0]     
__________________________________________________________________________________________________
activation_91 (Activation)      (None, 14, 14, 384)  0           batch_normalization_91[0][0]     
__________________________________________________________________________________________________
activation_92 (Activation)      (None, 14, 14, 384)  0           batch_normalization_92[0][0]     
__________________________________________________________________________________________________
batch_normalization_93 (BatchNo (None, 14, 14, 192)  576         conv2d_93[0][0]                  
__________________________________________________________________________________________________
activation_85 (Activation)      (None, 14, 14, 320)  0           batch_normalization_85[0][0]     
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_87[0][0]              
                                                                 activation_88[0][0]              
__________________________________________________________________________________________________
concatenate_1 (Concatenate)     (None, 14, 14, 768)  0           activation_91[0][0]              
                                                                 activation_92[0][0]              
__________________________________________________________________________________________________
activation_93 (Activation)      (None, 14, 14, 192)  0           batch_normalization_93[0][0]     
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_85[0][0]              
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_1[0][0]              
                                                                 activation_93[0][0]              
__________________________________________________________________________________________________
global_average_pooling2d_1 (Glo (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dense_1 (Dense)                 (None, 2)            4098        global_average_pooling2d_1[0][0] 
==================================================================================================
Total params: 21,806,882
Trainable params: 21,772,450
Non-trainable params: 34,432
__________________________________________________________________________________________________

2.2.2 Creating a Checkpoint for the Model

checkpointer = ModelCheckpoint(filepath='/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5', 
                               verbose=1, 
                               save_best_only=True)

2.2.3 Fitting into the Model

inception_model.fit(train_tensors, 
                    train_targets, 
                    batch_size = 8,
                    validation_data = (valid_tensors, valid_targets),
                    epochs = 5,
                    callbacks=[checkpointer], 
                    verbose=1)

Epoch 1/5
250/250 [==============================] - 60s 213ms/step - loss: 0.6399 - accuracy: 0.7821 - val_loss: 0.5253 - val_accuracy: 0.8000

Epoch 00001: val_loss improved from inf to 0.52525, saving model to /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Epoch 2/5
250/250 [==============================] - 52s 206ms/step - loss: 0.5277 - accuracy: 0.7978 - val_loss: 2.2813 - val_accuracy: 0.8000

Epoch 00002: val_loss did not improve from 0.52525
Epoch 3/5
250/250 [==============================] - 52s 207ms/step - loss: 0.5112 - accuracy: 0.8063 - val_loss: 7.3639 - val_accuracy: 0.4733

Epoch 00003: val_loss did not improve from 0.52525
Epoch 4/5
250/250 [==============================] - 52s 206ms/step - loss: 0.5073 - accuracy: 0.8089 - val_loss: 0.5995 - val_accuracy: 0.8000

Epoch 00004: val_loss did not improve from 0.52525
Epoch 5/5
250/250 [==============================] - 52s 206ms/step - loss: 0.5006 - accuracy: 0.8049 - val_loss: 1.9839 - val_accuracy: 0.8000

Epoch 00005: val_loss did not improve from 0.52525

<tensorflow.python.keras.callbacks.History at 0x7fb53a4fb190>

2.2.4 Loading the Weights for the Inception

# Loading the weights
inception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5")

2.3 Xception architecture

2.3.1 Defining the Xception Architechture

def xception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model
    from keras.applications.xception import Xception

    # Pre-build model
    base_model = Xception(include_top = False, weights = None, input_shape = (512, 512, 3))

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    xception_model = Model(base_model.input, output)

    # Summary of the model
    xception_model.summary()
    
    # Compiling the model
    xception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                           loss = 'categorical_crossentropy', 
                           metrics = ['accuracy'])

    return xception_model

# Getting the xception
xception_model = xception_architecture()

Model: "model_2"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_3 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_3[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_94 (Conv2D)              (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_94 (BatchNo (None, 127, 127, 128 512         conv2d_94[0][0]                  
__________________________________________________________________________________________________
add (Add)                       (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_94[0][0]     
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add[0][0]                        
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_95 (Conv2D)              (None, 64, 64, 256)  32768       add[0][0]                        
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_95 (BatchNo (None, 64, 64, 256)  1024        conv2d_95[0][0]                  
__________________________________________________________________________________________________
add_1 (Add)                     (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_95[0][0]     
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_1[0][0]                      
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_96 (Conv2D)              (None, 32, 32, 728)  186368      add_1[0][0]                      
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_96 (BatchNo (None, 32, 32, 728)  2912        conv2d_96[0][0]                  
__________________________________________________________________________________________________
add_2 (Add)                     (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_96[0][0]     
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_2[0][0]                      
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_3 (Add)                     (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_2[0][0]                      
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_3[0][0]                      
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_4 (Add)                     (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_3[0][0]                      
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_4[0][0]                      
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_5 (Add)                     (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_4[0][0]                      
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_5[0][0]                      
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_6 (Add)                     (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_5[0][0]                      
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_6[0][0]                      
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_7 (Add)                     (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_6[0][0]                      
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_7[0][0]                      
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_8 (Add)                     (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_7[0][0]                      
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_8[0][0]                      
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_9 (Add)                     (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_8[0][0]                      
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_9[0][0]                      
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_10 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_9[0][0]                      
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_10[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_97 (Conv2D)              (None, 16, 16, 1024) 745472      add_10[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_97 (BatchNo (None, 16, 16, 1024) 4096        conv2d_97[0][0]                  
__________________________________________________________________________________________________
add_11 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_97[0][0]     
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_11[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_2 (Glo (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_2 (Dense)                 (None, 2)            4098        global_average_pooling2d_2[0][0] 
==================================================================================================
Total params: 20,865,578
Trainable params: 20,811,050
Non-trainable params: 54,528
__________________________________________________________________________________________________

2.3.2 Creating a Checkpoint for the Model

tensor_board = TensorBoard(log_dir='./logs', histogram_freq = 0, batch_size = 8)

checkpointer = ModelCheckpoint(filepath='/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5', 
                               verbose=1, 
                               save_best_only=True)

WARNING:tensorflow:`batch_size` is no longer needed in the `TensorBoard` Callback and will be ignored in TensorFlow 2.0.

2.3.3 Fitting into the Model

xception_model.fit(train_tensors, 
                   train_targets, 
                   batch_size = 8,
                   validation_data = (valid_tensors, valid_targets),
                   epochs = 2,
                   callbacks=[checkpointer, tensor_board], 
                   verbose=1)

Epoch 1/2
250/250 [==============================] - 145s 563ms/step - loss: 0.6487 - accuracy: 0.7724 - val_loss: 0.5900 - val_accuracy: 0.8000

Epoch 00001: val_loss improved from inf to 0.59001, saving model to /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Epoch 2/2
250/250 [==============================] - 139s 557ms/step - loss: 0.5342 - accuracy: 0.7933 - val_loss: 42.6197 - val_accuracy: 0.8000

Epoch 00002: val_loss did not improve from 0.59001

<tensorflow.python.keras.callbacks.History at 0x7fb53a3ced10>

2.3.4 Loading the Weights

# Loading the weights
xception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5")

3. Prediction

Working Flowchart:

Declaring some Variables

predict_0_0 = 0
predict_0_1 = 0

model_architecture = None
weight_path = ""

Defining the Prediction Function

def predict(img_path,
            model_architecture = model_architecture, 
            path_model_weight = weight_path):
    # Printing the information passed to the Predict Function
    print("Image Path: "+img_path)
    print("Arhitecture Used:")
    print(model_architecture)
    print("Path for Model Weights: ")
    print(path_model_weight)
    # Getting the tensor of image
    image_to_predict = path_to_tensor(img_path).astype('float32')/255
    # Getting the model's architecture
    model = model_architecture
    # Loading the weights
    model.load_weights(path_model_weight)
    # printing the weights
    print("Model Weights: ")
    print(model.load_weights(path_model_weight))
    # Predicting
    pred = model.predict(image_to_predict)
    print("Prediction..." + " Melanoma : ", pred[0][0], " | Other : ", pred[0][1])
    predict_0_0 = pred[0][0]
    print("Predict "+predict_0_0)
    predict_0_1 = pred[0][1]
    print("Predict "+predict_0_1)
    if np.argmax(pred) == 0:
        return [1., 0.]
    elif np.argmax(pred) == 1:
        return [0., 1.]

3.1 MobileNet Architecture

3.1.1 Loading the Model and Weights

model_architecture = mobilenet_architecture()
weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5"

Model: "model_3"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_4 (InputLayer)         [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d_3 ( (None, 1024)              0         
_________________________________________________________________
dense_3 (Dense)              (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________

3.1.3 Predicting for a Sample Image Using MobileNet

predict("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg", model_architecture, weight_path)

Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb3781dba10>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8878556  | Other :  0.11214436

[1.0, 0.0]

3.2 Inception Architecture

3.2.1 Loading the Model and Weights

model_architecture = inception_architecture()
weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5"

Model: "model_4"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_5 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_98 (Conv2D)              (None, 255, 255, 32) 864         input_5[0][0]                    
__________________________________________________________________________________________________
batch_normalization_98 (BatchNo (None, 255, 255, 32) 96          conv2d_98[0][0]                  
__________________________________________________________________________________________________
activation_94 (Activation)      (None, 255, 255, 32) 0           batch_normalization_98[0][0]     
__________________________________________________________________________________________________
conv2d_99 (Conv2D)              (None, 253, 253, 32) 9216        activation_94[0][0]              
__________________________________________________________________________________________________
batch_normalization_99 (BatchNo (None, 253, 253, 32) 96          conv2d_99[0][0]                  
__________________________________________________________________________________________________
activation_95 (Activation)      (None, 253, 253, 32) 0           batch_normalization_99[0][0]     
__________________________________________________________________________________________________
conv2d_100 (Conv2D)             (None, 253, 253, 64) 18432       activation_95[0][0]              
__________________________________________________________________________________________________
batch_normalization_100 (BatchN (None, 253, 253, 64) 192         conv2d_100[0][0]                 
__________________________________________________________________________________________________
activation_96 (Activation)      (None, 253, 253, 64) 0           batch_normalization_100[0][0]    
__________________________________________________________________________________________________
max_pooling2d_4 (MaxPooling2D)  (None, 126, 126, 64) 0           activation_96[0][0]              
__________________________________________________________________________________________________
conv2d_101 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_4[0][0]            
__________________________________________________________________________________________________
batch_normalization_101 (BatchN (None, 126, 126, 80) 240         conv2d_101[0][0]                 
__________________________________________________________________________________________________
activation_97 (Activation)      (None, 126, 126, 80) 0           batch_normalization_101[0][0]    
__________________________________________________________________________________________________
conv2d_102 (Conv2D)             (None, 124, 124, 192 138240      activation_97[0][0]              
__________________________________________________________________________________________________
batch_normalization_102 (BatchN (None, 124, 124, 192 576         conv2d_102[0][0]                 
__________________________________________________________________________________________________
activation_98 (Activation)      (None, 124, 124, 192 0           batch_normalization_102[0][0]    
__________________________________________________________________________________________________
max_pooling2d_5 (MaxPooling2D)  (None, 61, 61, 192)  0           activation_98[0][0]              
__________________________________________________________________________________________________
conv2d_106 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_5[0][0]            
__________________________________________________________________________________________________
batch_normalization_106 (BatchN (None, 61, 61, 64)   192         conv2d_106[0][0]                 
__________________________________________________________________________________________________
activation_102 (Activation)     (None, 61, 61, 64)   0           batch_normalization_106[0][0]    
__________________________________________________________________________________________________
conv2d_104 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_5[0][0]            
__________________________________________________________________________________________________
conv2d_107 (Conv2D)             (None, 61, 61, 96)   55296       activation_102[0][0]             
__________________________________________________________________________________________________
batch_normalization_104 (BatchN (None, 61, 61, 48)   144         conv2d_104[0][0]                 
__________________________________________________________________________________________________
batch_normalization_107 (BatchN (None, 61, 61, 96)   288         conv2d_107[0][0]                 
__________________________________________________________________________________________________
activation_100 (Activation)     (None, 61, 61, 48)   0           batch_normalization_104[0][0]    
__________________________________________________________________________________________________
activation_103 (Activation)     (None, 61, 61, 96)   0           batch_normalization_107[0][0]    
__________________________________________________________________________________________________
average_pooling2d_9 (AveragePoo (None, 61, 61, 192)  0           max_pooling2d_5[0][0]            
__________________________________________________________________________________________________
conv2d_103 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_5[0][0]            
__________________________________________________________________________________________________
conv2d_105 (Conv2D)             (None, 61, 61, 64)   76800       activation_100[0][0]             
__________________________________________________________________________________________________
conv2d_108 (Conv2D)             (None, 61, 61, 96)   82944       activation_103[0][0]             
__________________________________________________________________________________________________
conv2d_109 (Conv2D)             (None, 61, 61, 32)   6144        average_pooling2d_9[0][0]        
__________________________________________________________________________________________________
batch_normalization_103 (BatchN (None, 61, 61, 64)   192         conv2d_103[0][0]                 
__________________________________________________________________________________________________
batch_normalization_105 (BatchN (None, 61, 61, 64)   192         conv2d_105[0][0]                 
__________________________________________________________________________________________________
batch_normalization_108 (BatchN (None, 61, 61, 96)   288         conv2d_108[0][0]                 
__________________________________________________________________________________________________
batch_normalization_109 (BatchN (None, 61, 61, 32)   96          conv2d_109[0][0]                 
__________________________________________________________________________________________________
activation_99 (Activation)      (None, 61, 61, 64)   0           batch_normalization_103[0][0]    
__________________________________________________________________________________________________
activation_101 (Activation)     (None, 61, 61, 64)   0           batch_normalization_105[0][0]    
__________________________________________________________________________________________________
activation_104 (Activation)     (None, 61, 61, 96)   0           batch_normalization_108[0][0]    
__________________________________________________________________________________________________
activation_105 (Activation)     (None, 61, 61, 32)   0           batch_normalization_109[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_99[0][0]              
                                                                 activation_101[0][0]             
                                                                 activation_104[0][0]             
                                                                 activation_105[0][0]             
__________________________________________________________________________________________________
conv2d_113 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_113 (BatchN (None, 61, 61, 64)   192         conv2d_113[0][0]                 
__________________________________________________________________________________________________
activation_109 (Activation)     (None, 61, 61, 64)   0           batch_normalization_113[0][0]    
__________________________________________________________________________________________________
conv2d_111 (Conv2D)             (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_114 (Conv2D)             (None, 61, 61, 96)   55296       activation_109[0][0]             
__________________________________________________________________________________________________
batch_normalization_111 (BatchN (None, 61, 61, 48)   144         conv2d_111[0][0]                 
__________________________________________________________________________________________________
batch_normalization_114 (BatchN (None, 61, 61, 96)   288         conv2d_114[0][0]                 
__________________________________________________________________________________________________
activation_107 (Activation)     (None, 61, 61, 48)   0           batch_normalization_111[0][0]    
__________________________________________________________________________________________________
activation_110 (Activation)     (None, 61, 61, 96)   0           batch_normalization_114[0][0]    
__________________________________________________________________________________________________
average_pooling2d_10 (AveragePo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_110 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_112 (Conv2D)             (None, 61, 61, 64)   76800       activation_107[0][0]             
__________________________________________________________________________________________________
conv2d_115 (Conv2D)             (None, 61, 61, 96)   82944       activation_110[0][0]             
__________________________________________________________________________________________________
conv2d_116 (Conv2D)             (None, 61, 61, 64)   16384       average_pooling2d_10[0][0]       
__________________________________________________________________________________________________
batch_normalization_110 (BatchN (None, 61, 61, 64)   192         conv2d_110[0][0]                 
__________________________________________________________________________________________________
batch_normalization_112 (BatchN (None, 61, 61, 64)   192         conv2d_112[0][0]                 
__________________________________________________________________________________________________
batch_normalization_115 (BatchN (None, 61, 61, 96)   288         conv2d_115[0][0]                 
__________________________________________________________________________________________________
batch_normalization_116 (BatchN (None, 61, 61, 64)   192         conv2d_116[0][0]                 
__________________________________________________________________________________________________
activation_106 (Activation)     (None, 61, 61, 64)   0           batch_normalization_110[0][0]    
__________________________________________________________________________________________________
activation_108 (Activation)     (None, 61, 61, 64)   0           batch_normalization_112[0][0]    
__________________________________________________________________________________________________
activation_111 (Activation)     (None, 61, 61, 96)   0           batch_normalization_115[0][0]    
__________________________________________________________________________________________________
activation_112 (Activation)     (None, 61, 61, 64)   0           batch_normalization_116[0][0]    
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_106[0][0]             
                                                                 activation_108[0][0]             
                                                                 activation_111[0][0]             
                                                                 activation_112[0][0]             
__________________________________________________________________________________________________
conv2d_120 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_120 (BatchN (None, 61, 61, 64)   192         conv2d_120[0][0]                 
__________________________________________________________________________________________________
activation_116 (Activation)     (None, 61, 61, 64)   0           batch_normalization_120[0][0]    
__________________________________________________________________________________________________
conv2d_118 (Conv2D)             (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_121 (Conv2D)             (None, 61, 61, 96)   55296       activation_116[0][0]             
__________________________________________________________________________________________________
batch_normalization_118 (BatchN (None, 61, 61, 48)   144         conv2d_118[0][0]                 
__________________________________________________________________________________________________
batch_normalization_121 (BatchN (None, 61, 61, 96)   288         conv2d_121[0][0]                 
__________________________________________________________________________________________________
activation_114 (Activation)     (None, 61, 61, 48)   0           batch_normalization_118[0][0]    
__________________________________________________________________________________________________
activation_117 (Activation)     (None, 61, 61, 96)   0           batch_normalization_121[0][0]    
__________________________________________________________________________________________________
average_pooling2d_11 (AveragePo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_117 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_119 (Conv2D)             (None, 61, 61, 64)   76800       activation_114[0][0]             
__________________________________________________________________________________________________
conv2d_122 (Conv2D)             (None, 61, 61, 96)   82944       activation_117[0][0]             
__________________________________________________________________________________________________
conv2d_123 (Conv2D)             (None, 61, 61, 64)   18432       average_pooling2d_11[0][0]       
__________________________________________________________________________________________________
batch_normalization_117 (BatchN (None, 61, 61, 64)   192         conv2d_117[0][0]                 
__________________________________________________________________________________________________
batch_normalization_119 (BatchN (None, 61, 61, 64)   192         conv2d_119[0][0]                 
__________________________________________________________________________________________________
batch_normalization_122 (BatchN (None, 61, 61, 96)   288         conv2d_122[0][0]                 
__________________________________________________________________________________________________
batch_normalization_123 (BatchN (None, 61, 61, 64)   192         conv2d_123[0][0]                 
__________________________________________________________________________________________________
activation_113 (Activation)     (None, 61, 61, 64)   0           batch_normalization_117[0][0]    
__________________________________________________________________________________________________
activation_115 (Activation)     (None, 61, 61, 64)   0           batch_normalization_119[0][0]    
__________________________________________________________________________________________________
activation_118 (Activation)     (None, 61, 61, 96)   0           batch_normalization_122[0][0]    
__________________________________________________________________________________________________
activation_119 (Activation)     (None, 61, 61, 64)   0           batch_normalization_123[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_113[0][0]             
                                                                 activation_115[0][0]             
                                                                 activation_118[0][0]             
                                                                 activation_119[0][0]             
__________________________________________________________________________________________________
conv2d_125 (Conv2D)             (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_125 (BatchN (None, 61, 61, 64)   192         conv2d_125[0][0]                 
__________________________________________________________________________________________________
activation_121 (Activation)     (None, 61, 61, 64)   0           batch_normalization_125[0][0]    
__________________________________________________________________________________________________
conv2d_126 (Conv2D)             (None, 61, 61, 96)   55296       activation_121[0][0]             
__________________________________________________________________________________________________
batch_normalization_126 (BatchN (None, 61, 61, 96)   288         conv2d_126[0][0]                 
__________________________________________________________________________________________________
activation_122 (Activation)     (None, 61, 61, 96)   0           batch_normalization_126[0][0]    
__________________________________________________________________________________________________
conv2d_124 (Conv2D)             (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_127 (Conv2D)             (None, 30, 30, 96)   82944       activation_122[0][0]             
__________________________________________________________________________________________________
batch_normalization_124 (BatchN (None, 30, 30, 384)  1152        conv2d_124[0][0]                 
__________________________________________________________________________________________________
batch_normalization_127 (BatchN (None, 30, 30, 96)   288         conv2d_127[0][0]                 
__________________________________________________________________________________________________
activation_120 (Activation)     (None, 30, 30, 384)  0           batch_normalization_124[0][0]    
__________________________________________________________________________________________________
activation_123 (Activation)     (None, 30, 30, 96)   0           batch_normalization_127[0][0]    
__________________________________________________________________________________________________
max_pooling2d_6 (MaxPooling2D)  (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_120[0][0]             
                                                                 activation_123[0][0]             
                                                                 max_pooling2d_6[0][0]            
__________________________________________________________________________________________________
conv2d_132 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_132 (BatchN (None, 30, 30, 128)  384         conv2d_132[0][0]                 
__________________________________________________________________________________________________
activation_128 (Activation)     (None, 30, 30, 128)  0           batch_normalization_132[0][0]    
__________________________________________________________________________________________________
conv2d_133 (Conv2D)             (None, 30, 30, 128)  114688      activation_128[0][0]             
__________________________________________________________________________________________________
batch_normalization_133 (BatchN (None, 30, 30, 128)  384         conv2d_133[0][0]                 
__________________________________________________________________________________________________
activation_129 (Activation)     (None, 30, 30, 128)  0           batch_normalization_133[0][0]    
__________________________________________________________________________________________________
conv2d_129 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_134 (Conv2D)             (None, 30, 30, 128)  114688      activation_129[0][0]             
__________________________________________________________________________________________________
batch_normalization_129 (BatchN (None, 30, 30, 128)  384         conv2d_129[0][0]                 
__________________________________________________________________________________________________
batch_normalization_134 (BatchN (None, 30, 30, 128)  384         conv2d_134[0][0]                 
__________________________________________________________________________________________________
activation_125 (Activation)     (None, 30, 30, 128)  0           batch_normalization_129[0][0]    
__________________________________________________________________________________________________
activation_130 (Activation)     (None, 30, 30, 128)  0           batch_normalization_134[0][0]    
__________________________________________________________________________________________________
conv2d_130 (Conv2D)             (None, 30, 30, 128)  114688      activation_125[0][0]             
__________________________________________________________________________________________________
conv2d_135 (Conv2D)             (None, 30, 30, 128)  114688      activation_130[0][0]             
__________________________________________________________________________________________________
batch_normalization_130 (BatchN (None, 30, 30, 128)  384         conv2d_130[0][0]                 
__________________________________________________________________________________________________
batch_normalization_135 (BatchN (None, 30, 30, 128)  384         conv2d_135[0][0]                 
__________________________________________________________________________________________________
activation_126 (Activation)     (None, 30, 30, 128)  0           batch_normalization_130[0][0]    
__________________________________________________________________________________________________
activation_131 (Activation)     (None, 30, 30, 128)  0           batch_normalization_135[0][0]    
__________________________________________________________________________________________________
average_pooling2d_12 (AveragePo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_128 (Conv2D)             (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_131 (Conv2D)             (None, 30, 30, 192)  172032      activation_126[0][0]             
__________________________________________________________________________________________________
conv2d_136 (Conv2D)             (None, 30, 30, 192)  172032      activation_131[0][0]             
__________________________________________________________________________________________________
conv2d_137 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_12[0][0]       
__________________________________________________________________________________________________
batch_normalization_128 (BatchN (None, 30, 30, 192)  576         conv2d_128[0][0]                 
__________________________________________________________________________________________________
batch_normalization_131 (BatchN (None, 30, 30, 192)  576         conv2d_131[0][0]                 
__________________________________________________________________________________________________
batch_normalization_136 (BatchN (None, 30, 30, 192)  576         conv2d_136[0][0]                 
__________________________________________________________________________________________________
batch_normalization_137 (BatchN (None, 30, 30, 192)  576         conv2d_137[0][0]                 
__________________________________________________________________________________________________
activation_124 (Activation)     (None, 30, 30, 192)  0           batch_normalization_128[0][0]    
__________________________________________________________________________________________________
activation_127 (Activation)     (None, 30, 30, 192)  0           batch_normalization_131[0][0]    
__________________________________________________________________________________________________
activation_132 (Activation)     (None, 30, 30, 192)  0           batch_normalization_136[0][0]    
__________________________________________________________________________________________________
activation_133 (Activation)     (None, 30, 30, 192)  0           batch_normalization_137[0][0]    
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_124[0][0]             
                                                                 activation_127[0][0]             
                                                                 activation_132[0][0]             
                                                                 activation_133[0][0]             
__________________________________________________________________________________________________
conv2d_142 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_142 (BatchN (None, 30, 30, 160)  480         conv2d_142[0][0]                 
__________________________________________________________________________________________________
activation_138 (Activation)     (None, 30, 30, 160)  0           batch_normalization_142[0][0]    
__________________________________________________________________________________________________
conv2d_143 (Conv2D)             (None, 30, 30, 160)  179200      activation_138[0][0]             
__________________________________________________________________________________________________
batch_normalization_143 (BatchN (None, 30, 30, 160)  480         conv2d_143[0][0]                 
__________________________________________________________________________________________________
activation_139 (Activation)     (None, 30, 30, 160)  0           batch_normalization_143[0][0]    
__________________________________________________________________________________________________
conv2d_139 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_144 (Conv2D)             (None, 30, 30, 160)  179200      activation_139[0][0]             
__________________________________________________________________________________________________
batch_normalization_139 (BatchN (None, 30, 30, 160)  480         conv2d_139[0][0]                 
__________________________________________________________________________________________________
batch_normalization_144 (BatchN (None, 30, 30, 160)  480         conv2d_144[0][0]                 
__________________________________________________________________________________________________
activation_135 (Activation)     (None, 30, 30, 160)  0           batch_normalization_139[0][0]    
__________________________________________________________________________________________________
activation_140 (Activation)     (None, 30, 30, 160)  0           batch_normalization_144[0][0]    
__________________________________________________________________________________________________
conv2d_140 (Conv2D)             (None, 30, 30, 160)  179200      activation_135[0][0]             
__________________________________________________________________________________________________
conv2d_145 (Conv2D)             (None, 30, 30, 160)  179200      activation_140[0][0]             
__________________________________________________________________________________________________
batch_normalization_140 (BatchN (None, 30, 30, 160)  480         conv2d_140[0][0]                 
__________________________________________________________________________________________________
batch_normalization_145 (BatchN (None, 30, 30, 160)  480         conv2d_145[0][0]                 
__________________________________________________________________________________________________
activation_136 (Activation)     (None, 30, 30, 160)  0           batch_normalization_140[0][0]    
__________________________________________________________________________________________________
activation_141 (Activation)     (None, 30, 30, 160)  0           batch_normalization_145[0][0]    
__________________________________________________________________________________________________
average_pooling2d_13 (AveragePo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_138 (Conv2D)             (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_141 (Conv2D)             (None, 30, 30, 192)  215040      activation_136[0][0]             
__________________________________________________________________________________________________
conv2d_146 (Conv2D)             (None, 30, 30, 192)  215040      activation_141[0][0]             
__________________________________________________________________________________________________
conv2d_147 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_13[0][0]       
__________________________________________________________________________________________________
batch_normalization_138 (BatchN (None, 30, 30, 192)  576         conv2d_138[0][0]                 
__________________________________________________________________________________________________
batch_normalization_141 (BatchN (None, 30, 30, 192)  576         conv2d_141[0][0]                 
__________________________________________________________________________________________________
batch_normalization_146 (BatchN (None, 30, 30, 192)  576         conv2d_146[0][0]                 
__________________________________________________________________________________________________
batch_normalization_147 (BatchN (None, 30, 30, 192)  576         conv2d_147[0][0]                 
__________________________________________________________________________________________________
activation_134 (Activation)     (None, 30, 30, 192)  0           batch_normalization_138[0][0]    
__________________________________________________________________________________________________
activation_137 (Activation)     (None, 30, 30, 192)  0           batch_normalization_141[0][0]    
__________________________________________________________________________________________________
activation_142 (Activation)     (None, 30, 30, 192)  0           batch_normalization_146[0][0]    
__________________________________________________________________________________________________
activation_143 (Activation)     (None, 30, 30, 192)  0           batch_normalization_147[0][0]    
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_134[0][0]             
                                                                 activation_137[0][0]             
                                                                 activation_142[0][0]             
                                                                 activation_143[0][0]             
__________________________________________________________________________________________________
conv2d_152 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_152 (BatchN (None, 30, 30, 160)  480         conv2d_152[0][0]                 
__________________________________________________________________________________________________
activation_148 (Activation)     (None, 30, 30, 160)  0           batch_normalization_152[0][0]    
__________________________________________________________________________________________________
conv2d_153 (Conv2D)             (None, 30, 30, 160)  179200      activation_148[0][0]             
__________________________________________________________________________________________________
batch_normalization_153 (BatchN (None, 30, 30, 160)  480         conv2d_153[0][0]                 
__________________________________________________________________________________________________
activation_149 (Activation)     (None, 30, 30, 160)  0           batch_normalization_153[0][0]    
__________________________________________________________________________________________________
conv2d_149 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_154 (Conv2D)             (None, 30, 30, 160)  179200      activation_149[0][0]             
__________________________________________________________________________________________________
batch_normalization_149 (BatchN (None, 30, 30, 160)  480         conv2d_149[0][0]                 
__________________________________________________________________________________________________
batch_normalization_154 (BatchN (None, 30, 30, 160)  480         conv2d_154[0][0]                 
__________________________________________________________________________________________________
activation_145 (Activation)     (None, 30, 30, 160)  0           batch_normalization_149[0][0]    
__________________________________________________________________________________________________
activation_150 (Activation)     (None, 30, 30, 160)  0           batch_normalization_154[0][0]    
__________________________________________________________________________________________________
conv2d_150 (Conv2D)             (None, 30, 30, 160)  179200      activation_145[0][0]             
__________________________________________________________________________________________________
conv2d_155 (Conv2D)             (None, 30, 30, 160)  179200      activation_150[0][0]             
__________________________________________________________________________________________________
batch_normalization_150 (BatchN (None, 30, 30, 160)  480         conv2d_150[0][0]                 
__________________________________________________________________________________________________
batch_normalization_155 (BatchN (None, 30, 30, 160)  480         conv2d_155[0][0]                 
__________________________________________________________________________________________________
activation_146 (Activation)     (None, 30, 30, 160)  0           batch_normalization_150[0][0]    
__________________________________________________________________________________________________
activation_151 (Activation)     (None, 30, 30, 160)  0           batch_normalization_155[0][0]    
__________________________________________________________________________________________________
average_pooling2d_14 (AveragePo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_148 (Conv2D)             (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_151 (Conv2D)             (None, 30, 30, 192)  215040      activation_146[0][0]             
__________________________________________________________________________________________________
conv2d_156 (Conv2D)             (None, 30, 30, 192)  215040      activation_151[0][0]             
__________________________________________________________________________________________________
conv2d_157 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_14[0][0]       
__________________________________________________________________________________________________
batch_normalization_148 (BatchN (None, 30, 30, 192)  576         conv2d_148[0][0]                 
__________________________________________________________________________________________________
batch_normalization_151 (BatchN (None, 30, 30, 192)  576         conv2d_151[0][0]                 
__________________________________________________________________________________________________
batch_normalization_156 (BatchN (None, 30, 30, 192)  576         conv2d_156[0][0]                 
__________________________________________________________________________________________________
batch_normalization_157 (BatchN (None, 30, 30, 192)  576         conv2d_157[0][0]                 
__________________________________________________________________________________________________
activation_144 (Activation)     (None, 30, 30, 192)  0           batch_normalization_148[0][0]    
__________________________________________________________________________________________________
activation_147 (Activation)     (None, 30, 30, 192)  0           batch_normalization_151[0][0]    
__________________________________________________________________________________________________
activation_152 (Activation)     (None, 30, 30, 192)  0           batch_normalization_156[0][0]    
__________________________________________________________________________________________________
activation_153 (Activation)     (None, 30, 30, 192)  0           batch_normalization_157[0][0]    
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_144[0][0]             
                                                                 activation_147[0][0]             
                                                                 activation_152[0][0]             
                                                                 activation_153[0][0]             
__________________________________________________________________________________________________
conv2d_162 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_162 (BatchN (None, 30, 30, 192)  576         conv2d_162[0][0]                 
__________________________________________________________________________________________________
activation_158 (Activation)     (None, 30, 30, 192)  0           batch_normalization_162[0][0]    
__________________________________________________________________________________________________
conv2d_163 (Conv2D)             (None, 30, 30, 192)  258048      activation_158[0][0]             
__________________________________________________________________________________________________
batch_normalization_163 (BatchN (None, 30, 30, 192)  576         conv2d_163[0][0]                 
__________________________________________________________________________________________________
activation_159 (Activation)     (None, 30, 30, 192)  0           batch_normalization_163[0][0]    
__________________________________________________________________________________________________
conv2d_159 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_164 (Conv2D)             (None, 30, 30, 192)  258048      activation_159[0][0]             
__________________________________________________________________________________________________
batch_normalization_159 (BatchN (None, 30, 30, 192)  576         conv2d_159[0][0]                 
__________________________________________________________________________________________________
batch_normalization_164 (BatchN (None, 30, 30, 192)  576         conv2d_164[0][0]                 
__________________________________________________________________________________________________
activation_155 (Activation)     (None, 30, 30, 192)  0           batch_normalization_159[0][0]    
__________________________________________________________________________________________________
activation_160 (Activation)     (None, 30, 30, 192)  0           batch_normalization_164[0][0]    
__________________________________________________________________________________________________
conv2d_160 (Conv2D)             (None, 30, 30, 192)  258048      activation_155[0][0]             
__________________________________________________________________________________________________
conv2d_165 (Conv2D)             (None, 30, 30, 192)  258048      activation_160[0][0]             
__________________________________________________________________________________________________
batch_normalization_160 (BatchN (None, 30, 30, 192)  576         conv2d_160[0][0]                 
__________________________________________________________________________________________________
batch_normalization_165 (BatchN (None, 30, 30, 192)  576         conv2d_165[0][0]                 
__________________________________________________________________________________________________
activation_156 (Activation)     (None, 30, 30, 192)  0           batch_normalization_160[0][0]    
__________________________________________________________________________________________________
activation_161 (Activation)     (None, 30, 30, 192)  0           batch_normalization_165[0][0]    
__________________________________________________________________________________________________
average_pooling2d_15 (AveragePo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_158 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_161 (Conv2D)             (None, 30, 30, 192)  258048      activation_156[0][0]             
__________________________________________________________________________________________________
conv2d_166 (Conv2D)             (None, 30, 30, 192)  258048      activation_161[0][0]             
__________________________________________________________________________________________________
conv2d_167 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_15[0][0]       
__________________________________________________________________________________________________
batch_normalization_158 (BatchN (None, 30, 30, 192)  576         conv2d_158[0][0]                 
__________________________________________________________________________________________________
batch_normalization_161 (BatchN (None, 30, 30, 192)  576         conv2d_161[0][0]                 
__________________________________________________________________________________________________
batch_normalization_166 (BatchN (None, 30, 30, 192)  576         conv2d_166[0][0]                 
__________________________________________________________________________________________________
batch_normalization_167 (BatchN (None, 30, 30, 192)  576         conv2d_167[0][0]                 
__________________________________________________________________________________________________
activation_154 (Activation)     (None, 30, 30, 192)  0           batch_normalization_158[0][0]    
__________________________________________________________________________________________________
activation_157 (Activation)     (None, 30, 30, 192)  0           batch_normalization_161[0][0]    
__________________________________________________________________________________________________
activation_162 (Activation)     (None, 30, 30, 192)  0           batch_normalization_166[0][0]    
__________________________________________________________________________________________________
activation_163 (Activation)     (None, 30, 30, 192)  0           batch_normalization_167[0][0]    
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_154[0][0]             
                                                                 activation_157[0][0]             
                                                                 activation_162[0][0]             
                                                                 activation_163[0][0]             
__________________________________________________________________________________________________
conv2d_170 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_170 (BatchN (None, 30, 30, 192)  576         conv2d_170[0][0]                 
__________________________________________________________________________________________________
activation_166 (Activation)     (None, 30, 30, 192)  0           batch_normalization_170[0][0]    
__________________________________________________________________________________________________
conv2d_171 (Conv2D)             (None, 30, 30, 192)  258048      activation_166[0][0]             
__________________________________________________________________________________________________
batch_normalization_171 (BatchN (None, 30, 30, 192)  576         conv2d_171[0][0]                 
__________________________________________________________________________________________________
activation_167 (Activation)     (None, 30, 30, 192)  0           batch_normalization_171[0][0]    
__________________________________________________________________________________________________
conv2d_168 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_172 (Conv2D)             (None, 30, 30, 192)  258048      activation_167[0][0]             
__________________________________________________________________________________________________
batch_normalization_168 (BatchN (None, 30, 30, 192)  576         conv2d_168[0][0]                 
__________________________________________________________________________________________________
batch_normalization_172 (BatchN (None, 30, 30, 192)  576         conv2d_172[0][0]                 
__________________________________________________________________________________________________
activation_164 (Activation)     (None, 30, 30, 192)  0           batch_normalization_168[0][0]    
__________________________________________________________________________________________________
activation_168 (Activation)     (None, 30, 30, 192)  0           batch_normalization_172[0][0]    
__________________________________________________________________________________________________
conv2d_169 (Conv2D)             (None, 14, 14, 320)  552960      activation_164[0][0]             
__________________________________________________________________________________________________
conv2d_173 (Conv2D)             (None, 14, 14, 192)  331776      activation_168[0][0]             
__________________________________________________________________________________________________
batch_normalization_169 (BatchN (None, 14, 14, 320)  960         conv2d_169[0][0]                 
__________________________________________________________________________________________________
batch_normalization_173 (BatchN (None, 14, 14, 192)  576         conv2d_173[0][0]                 
__________________________________________________________________________________________________
activation_165 (Activation)     (None, 14, 14, 320)  0           batch_normalization_169[0][0]    
__________________________________________________________________________________________________
activation_169 (Activation)     (None, 14, 14, 192)  0           batch_normalization_173[0][0]    
__________________________________________________________________________________________________
max_pooling2d_7 (MaxPooling2D)  (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_165[0][0]             
                                                                 activation_169[0][0]             
                                                                 max_pooling2d_7[0][0]            
__________________________________________________________________________________________________
conv2d_178 (Conv2D)             (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_178 (BatchN (None, 14, 14, 448)  1344        conv2d_178[0][0]                 
__________________________________________________________________________________________________
activation_174 (Activation)     (None, 14, 14, 448)  0           batch_normalization_178[0][0]    
__________________________________________________________________________________________________
conv2d_175 (Conv2D)             (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_179 (Conv2D)             (None, 14, 14, 384)  1548288     activation_174[0][0]             
__________________________________________________________________________________________________
batch_normalization_175 (BatchN (None, 14, 14, 384)  1152        conv2d_175[0][0]                 
__________________________________________________________________________________________________
batch_normalization_179 (BatchN (None, 14, 14, 384)  1152        conv2d_179[0][0]                 
__________________________________________________________________________________________________
activation_171 (Activation)     (None, 14, 14, 384)  0           batch_normalization_175[0][0]    
__________________________________________________________________________________________________
activation_175 (Activation)     (None, 14, 14, 384)  0           batch_normalization_179[0][0]    
__________________________________________________________________________________________________
conv2d_176 (Conv2D)             (None, 14, 14, 384)  442368      activation_171[0][0]             
__________________________________________________________________________________________________
conv2d_177 (Conv2D)             (None, 14, 14, 384)  442368      activation_171[0][0]             
__________________________________________________________________________________________________
conv2d_180 (Conv2D)             (None, 14, 14, 384)  442368      activation_175[0][0]             
__________________________________________________________________________________________________
conv2d_181 (Conv2D)             (None, 14, 14, 384)  442368      activation_175[0][0]             
__________________________________________________________________________________________________
average_pooling2d_16 (AveragePo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_174 (Conv2D)             (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_176 (BatchN (None, 14, 14, 384)  1152        conv2d_176[0][0]                 
__________________________________________________________________________________________________
batch_normalization_177 (BatchN (None, 14, 14, 384)  1152        conv2d_177[0][0]                 
__________________________________________________________________________________________________
batch_normalization_180 (BatchN (None, 14, 14, 384)  1152        conv2d_180[0][0]                 
__________________________________________________________________________________________________
batch_normalization_181 (BatchN (None, 14, 14, 384)  1152        conv2d_181[0][0]                 
__________________________________________________________________________________________________
conv2d_182 (Conv2D)             (None, 14, 14, 192)  245760      average_pooling2d_16[0][0]       
__________________________________________________________________________________________________
batch_normalization_174 (BatchN (None, 14, 14, 320)  960         conv2d_174[0][0]                 
__________________________________________________________________________________________________
activation_172 (Activation)     (None, 14, 14, 384)  0           batch_normalization_176[0][0]    
__________________________________________________________________________________________________
activation_173 (Activation)     (None, 14, 14, 384)  0           batch_normalization_177[0][0]    
__________________________________________________________________________________________________
activation_176 (Activation)     (None, 14, 14, 384)  0           batch_normalization_180[0][0]    
__________________________________________________________________________________________________
activation_177 (Activation)     (None, 14, 14, 384)  0           batch_normalization_181[0][0]    
__________________________________________________________________________________________________
batch_normalization_182 (BatchN (None, 14, 14, 192)  576         conv2d_182[0][0]                 
__________________________________________________________________________________________________
activation_170 (Activation)     (None, 14, 14, 320)  0           batch_normalization_174[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_172[0][0]             
                                                                 activation_173[0][0]             
__________________________________________________________________________________________________
concatenate_2 (Concatenate)     (None, 14, 14, 768)  0           activation_176[0][0]             
                                                                 activation_177[0][0]             
__________________________________________________________________________________________________
activation_178 (Activation)     (None, 14, 14, 192)  0           batch_normalization_182[0][0]    
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_170[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_2[0][0]              
                                                                 activation_178[0][0]             
__________________________________________________________________________________________________
conv2d_187 (Conv2D)             (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_187 (BatchN (None, 14, 14, 448)  1344        conv2d_187[0][0]                 
__________________________________________________________________________________________________
activation_183 (Activation)     (None, 14, 14, 448)  0           batch_normalization_187[0][0]    
__________________________________________________________________________________________________
conv2d_184 (Conv2D)             (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_188 (Conv2D)             (None, 14, 14, 384)  1548288     activation_183[0][0]             
__________________________________________________________________________________________________
batch_normalization_184 (BatchN (None, 14, 14, 384)  1152        conv2d_184[0][0]                 
__________________________________________________________________________________________________
batch_normalization_188 (BatchN (None, 14, 14, 384)  1152        conv2d_188[0][0]                 
__________________________________________________________________________________________________
activation_180 (Activation)     (None, 14, 14, 384)  0           batch_normalization_184[0][0]    
__________________________________________________________________________________________________
activation_184 (Activation)     (None, 14, 14, 384)  0           batch_normalization_188[0][0]    
__________________________________________________________________________________________________
conv2d_185 (Conv2D)             (None, 14, 14, 384)  442368      activation_180[0][0]             
__________________________________________________________________________________________________
conv2d_186 (Conv2D)             (None, 14, 14, 384)  442368      activation_180[0][0]             
__________________________________________________________________________________________________
conv2d_189 (Conv2D)             (None, 14, 14, 384)  442368      activation_184[0][0]             
__________________________________________________________________________________________________
conv2d_190 (Conv2D)             (None, 14, 14, 384)  442368      activation_184[0][0]             
__________________________________________________________________________________________________
average_pooling2d_17 (AveragePo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_183 (Conv2D)             (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_185 (BatchN (None, 14, 14, 384)  1152        conv2d_185[0][0]                 
__________________________________________________________________________________________________
batch_normalization_186 (BatchN (None, 14, 14, 384)  1152        conv2d_186[0][0]                 
__________________________________________________________________________________________________
batch_normalization_189 (BatchN (None, 14, 14, 384)  1152        conv2d_189[0][0]                 
__________________________________________________________________________________________________
batch_normalization_190 (BatchN (None, 14, 14, 384)  1152        conv2d_190[0][0]                 
__________________________________________________________________________________________________
conv2d_191 (Conv2D)             (None, 14, 14, 192)  393216      average_pooling2d_17[0][0]       
__________________________________________________________________________________________________
batch_normalization_183 (BatchN (None, 14, 14, 320)  960         conv2d_183[0][0]                 
__________________________________________________________________________________________________
activation_181 (Activation)     (None, 14, 14, 384)  0           batch_normalization_185[0][0]    
__________________________________________________________________________________________________
activation_182 (Activation)     (None, 14, 14, 384)  0           batch_normalization_186[0][0]    
__________________________________________________________________________________________________
activation_185 (Activation)     (None, 14, 14, 384)  0           batch_normalization_189[0][0]    
__________________________________________________________________________________________________
activation_186 (Activation)     (None, 14, 14, 384)  0           batch_normalization_190[0][0]    
__________________________________________________________________________________________________
batch_normalization_191 (BatchN (None, 14, 14, 192)  576         conv2d_191[0][0]                 
__________________________________________________________________________________________________
activation_179 (Activation)     (None, 14, 14, 320)  0           batch_normalization_183[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_181[0][0]             
                                                                 activation_182[0][0]             
__________________________________________________________________________________________________
concatenate_3 (Concatenate)     (None, 14, 14, 768)  0           activation_185[0][0]             
                                                                 activation_186[0][0]             
__________________________________________________________________________________________________
activation_187 (Activation)     (None, 14, 14, 192)  0           batch_normalization_191[0][0]    
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_179[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_3[0][0]              
                                                                 activation_187[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_4 (Glo (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dense_4 (Dense)                 (None, 2)            4098        global_average_pooling2d_4[0][0] 
==================================================================================================
Total params: 21,806,882
Trainable params: 21,772,450
Non-trainable params: 34,432
__________________________________________________________________________________________________

3.2.2 Predicting for a Sample Image Using InceptionV3

predict("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg", model_architecture, weight_path)

Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276ba9c10>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932921  | Other :  0.10670786

[1.0, 0.0]

3.3 Xception Architecture

3.3.1 Loading the Model and Weights

model_architecture = xception_architecture()
weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5"

Model: "model_5"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_6 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_6[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_192 (Conv2D)             (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_192 (BatchN (None, 127, 127, 128 512         conv2d_192[0][0]                 
__________________________________________________________________________________________________
add_12 (Add)                    (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_192[0][0]    
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add_12[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_193 (Conv2D)             (None, 64, 64, 256)  32768       add_12[0][0]                     
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_193 (BatchN (None, 64, 64, 256)  1024        conv2d_193[0][0]                 
__________________________________________________________________________________________________
add_13 (Add)                    (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_193[0][0]    
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_13[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_194 (Conv2D)             (None, 32, 32, 728)  186368      add_13[0][0]                     
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_194 (BatchN (None, 32, 32, 728)  2912        conv2d_194[0][0]                 
__________________________________________________________________________________________________
add_14 (Add)                    (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_194[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_14[0][0]                     
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_15 (Add)                    (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_14[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_15[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_16 (Add)                    (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_15[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_16[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_17 (Add)                    (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_16[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_17[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_18 (Add)                    (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_17[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_18[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_19 (Add)                    (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_18[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_19[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_20 (Add)                    (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_19[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_20[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_21 (Add)                    (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_20[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_21[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_22 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_21[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_22[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_195 (Conv2D)             (None, 16, 16, 1024) 745472      add_22[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_195 (BatchN (None, 16, 16, 1024) 4096        conv2d_195[0][0]                 
__________________________________________________________________________________________________
add_23 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_195[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_23[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_5 (Glo (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_5 (Dense)                 (None, 2)            4098        global_average_pooling2d_5[0][0] 
==================================================================================================
Total params: 20,865,578
Trainable params: 20,811,050
Non-trainable params: 54,528
__________________________________________________________________________________________________

3.3.2 Predicting a Sample Image using Xception

predict("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg", model_architecture, weight_path)

Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb3782db490>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022564  | Other :  0.39774355

[1.0, 0.0]

4. Evaluating the Models Individually on Validation Data

Working Flowchart:

Defining Function to calculatae Receiving Operating Characteristic curve

def compute_roc(y_true, y_score):
    """ 
    Computing the "Receiving Operating Characteristic curve" and area
    """
    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_true, y_score) 
    auroc = auc(false_positive_rate, true_positive_rate) 
    return false_positive_rate, true_positive_rate, auroc

Defining Function for Plotting the Receiving Operating Characteristic curve

def plot_roc(y_true, y_score):
    """ 
    Ploting the Receiving Operating Characteristic curve
    """
    false_positive_rate, true_positive_rate, auroc = compute_roc(y_true, y_score)
    plt.figure(figsize=(10,6))
    plt.grid()
    plt.plot(false_positive_rate, 
             true_positive_rate, 
             color='darkorange',
             lw=2, 
             label='ROC curve (area = {:.2f})'.format(auroc))
    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')
    plt.xlim([0.0, 1.0])
    plt.ylim([0.0, 1.05])
    plt.xlabel('False Positive Rate', fontsize=12)
    plt.ylabel('True Positive Rate', fontsize=12)
    plt.title('Receiver operating characteristic example', fontsize=15)
    plt.legend(loc="lower right", fontsize=14)
    plt.show()

plt.style.available

['Solarize_Light2',
 '_classic_test_patch',
 'bmh',
 'classic',
 'dark_background',
 'fast',
 'fivethirtyeight',
 'ggplot',
 'grayscale',
 'seaborn',
 'seaborn-bright',
 'seaborn-colorblind',
 'seaborn-dark',
 'seaborn-dark-palette',
 'seaborn-darkgrid',
 'seaborn-deep',
 'seaborn-muted',
 'seaborn-notebook',
 'seaborn-paper',
 'seaborn-pastel',
 'seaborn-poster',
 'seaborn-talk',
 'seaborn-ticks',
 'seaborn-white',
 'seaborn-whitegrid',
 'tableau-colorblind10']

plt.style.use("seaborn-white")

4.1 MobileNet Architecture

4.1.1 Computing Test Set Predictions

# Compute test set predictions
#model_architecture,path_model_weight
NUMBER_TEST_SAMPLES = 150

mobilenet_architecture_function = mobilenet_architecture()
mobilenet_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5"

y_true_MobileNet = valid_targets[:NUMBER_TEST_SAMPLES]
y_score_MobileNet = []
for index in range(NUMBER_TEST_SAMPLES): #compute one at a time due to memory constraints
    probs = predict(img_path = validation_files[index], model_architecture = mobilenet_architecture_function, path_model_weight = mobilenet_architecture_weight_path)
    print("Real values..." + "Melanoma : ", valid_targets[index][0], " | Other : ", valid_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_MobileNet.append(probs)
    
correct_MobileNet = np.array(y_true_MobileNet) == np.array(y_score_MobileNet)

Model: "model_6"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_7 (InputLayer)         [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d_6 ( (None, 1024)              0         
_________________________________________________________________
dense_6 (Dense)              (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0004337.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881906  | Other :  0.11180934
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8878556  | Other :  0.11214436
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8884766  | Other :  0.11152334
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003539.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8880564  | Other :  0.11194367
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003805.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887947  | Other :  0.11205301
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872876  | Other :  0.1127124
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001852.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881772  | Other :  0.11182279
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003657.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881499  | Other :  0.11185002
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003462.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874755  | Other :  0.11252455
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001871.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871602  | Other :  0.11283979
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88718355  | Other :  0.11281645
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88728464  | Other :  0.11271535
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006914.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88717246  | Other :  0.112827554
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007141.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88698703  | Other :  0.11301297
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007344.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88778174  | Other :  0.11221828
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007235.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868339  | Other :  0.11316609
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88745826  | Other :  0.11254169
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887834  | Other :  0.11216601
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008524.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88783336  | Other :  0.11216671
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007528.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88800776  | Other :  0.11199225
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88553494  | Other :  0.11446508
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007332.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88592917  | Other :  0.11407082
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006671.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88731647  | Other :  0.11268352
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0010459.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88590485  | Other :  0.114095174
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012099.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871294  | Other :  0.11287054
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012126.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862669  | Other :  0.113733165
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88748974  | Other :  0.11251024
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0009995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866407  | Other :  0.11335926
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860149  | Other :  0.11398512
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012151.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886278  | Other :  0.113722034
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012204.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88696855  | Other :  0.113031484
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012143.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863191  | Other :  0.11368089
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012191.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88706326  | Other :  0.112936676
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012109.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860991  | Other :  0.11390089
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012159.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88741803  | Other :  0.11258205
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881112  | Other :  0.111888774
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012316.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88656276  | Other :  0.113437235
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012306.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8880089  | Other :  0.11199105
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879006  | Other :  0.11209944
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88820034  | Other :  0.11179966
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012380.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88589734  | Other :  0.11410263
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8883873  | Other :  0.1116127
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012222.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864915  | Other :  0.11350856
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012335.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862915  | Other :  0.11370849
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88788766  | Other :  0.112112336
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876418  | Other :  0.11235821
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88771427  | Other :  0.11228568
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8878243  | Other :  0.1121757
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012210.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881639  | Other :  0.11183602
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88541204  | Other :  0.114587925
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8882264  | Other :  0.11177365
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872927  | Other :  0.1127073
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012538.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88556963  | Other :  0.11443039
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012684.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88639545  | Other :  0.11360453
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879224  | Other :  0.11207761
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869916  | Other :  0.11300835
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012400.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875345  | Other :  0.112465434
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012547.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88588834  | Other :  0.11411169
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88620186  | Other :  0.11379817
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012492.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88670063  | Other :  0.11329944
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012660.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860158  | Other :  0.113984175
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013082.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860958  | Other :  0.11390419
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88709277  | Other :  0.11290721
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88765246  | Other :  0.11234754
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013188.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864243  | Other :  0.11357571
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864001  | Other :  0.113599874
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88576263  | Other :  0.1142374
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876488  | Other :  0.11235114
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873123  | Other :  0.11268765
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013104.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875056  | Other :  0.11249436
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013128.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872255  | Other :  0.112774484
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886071  | Other :  0.11392903
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013010.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874715  | Other :  0.1125285
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013491.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88647944  | Other :  0.113520525
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013549.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88719887  | Other :  0.11280119
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013562.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863714  | Other :  0.11362862
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013501.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88731307  | Other :  0.11268699
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881087  | Other :  0.111891344
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88802016  | Other :  0.111979865
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013632.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88583624  | Other :  0.114163704
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013561.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88624793  | Other :  0.113752104
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013518.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88743013  | Other :  0.11256987
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013527.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88690394  | Other :  0.11309607
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013421.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872613  | Other :  0.11273873
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88667417  | Other :  0.113325775
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013898.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886944  | Other :  0.11305603
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013828.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874209  | Other :  0.112579055
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88684255  | Other :  0.113157526
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88686186  | Other :  0.11313815
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013702.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868527  | Other :  0.113147356
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872498  | Other :  0.11275015
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013736.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88653326  | Other :  0.113466725
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876516  | Other :  0.11234833
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88706696  | Other :  0.112933055
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8880996  | Other :  0.11190037
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013793.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860832  | Other :  0.11391685
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869419  | Other :  0.113058135
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875258  | Other :  0.11247423
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014428.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88667446  | Other :  0.11332554
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014178.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88715017  | Other :  0.11284987
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014382.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870297  | Other :  0.112970345
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872977  | Other :  0.112702385
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88709885  | Other :  0.112901144
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014302.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88710654  | Other :  0.112893485
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88728005  | Other :  0.11271993
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88658017  | Other :  0.11341979
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014162.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863534  | Other :  0.113646574
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014618.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861942  | Other :  0.113805756
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014610.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862792  | Other :  0.11372073
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014601.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857669  | Other :  0.114233084
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014620.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863394  | Other :  0.11366055
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014616.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860203  | Other :  0.11397965
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014623.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862573  | Other :  0.11374273
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014572.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862387  | Other :  0.11376131
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014558.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873093  | Other :  0.11269065
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014624.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88633907  | Other :  0.11366094
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014633.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868797  | Other :  0.113120355
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014597.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866781  | Other :  0.11332185
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014608.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860505  | Other :  0.113949455
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014611.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88610816  | Other :  0.113891795
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863647  | Other :  0.113635294
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014829.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879149  | Other :  0.11208513
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014635.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860523  | Other :  0.11394771
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014857.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8865066  | Other :  0.11349335
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014931.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8865068  | Other :  0.11349315
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88648677  | Other :  0.113513194
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857131  | Other :  0.1142869
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014712.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867182  | Other :  0.11328179
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014688.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866517  | Other :  0.113348335
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88550067  | Other :  0.11449934
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872031  | Other :  0.112796895
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88625336  | Other :  0.11374662
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88563716  | Other :  0.11436284
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.885907  | Other :  0.11409298
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88739455  | Other :  0.112605475
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015124.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88495886  | Other :  0.11504115
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015243.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868732  | Other :  0.11312685
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015144.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853072  | Other :  0.11469281
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886039  | Other :  0.113961
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8847107  | Other :  0.115289226
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859675  | Other :  0.114032455
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869993  | Other :  0.113000706
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88546646  | Other :  0.11453361
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015443.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872178  | Other :  0.112782195
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015372.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88638186  | Other :  0.11361816
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874476  | Other :  0.112552464
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015445.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88672537  | Other :  0.11327468
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015401.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88569325  | Other :  0.11430671
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015496.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.885171  | Other :  0.11482901
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015483.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb275e25410>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855857  | Other :  0.11441427
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_MobileNet)*100))

Accuracy = 80.00%

4.1.2 Re-ordering Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_MobileNet = []
for i in range(len(y_true_MobileNet)):
    y_true_2_MobileNet.append(y_true_MobileNet[i][0])

4.1.3 Re-ordering Predicte y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_MobileNet = []
for i in range(len(y_score_MobileNet)):
    y_score_2_MobileNet.append(y_score_MobileNet[i][0])

4.1.4 Plotting the Re-ordered ROC

plot_roc(y_true_2_MobileNet, y_score_2_MobileNet)

4.1.5 Confusion Matrix

4.1.5.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_MobileNet, FALSE_POSITIVE_MobileNet, TRUE_NEGATIVE_MobileNet, FALSE_NEGATIVE_MobileNet = positive_negative_measurement(y_true_2_MobileNet, y_score_2_MobileNet)
postives_negatives_MobileNet = [[TRUE_POSITIVE_MobileNet, FALSE_POSITIVE_MobileNet], 
                                [FALSE_NEGATIVE_MobileNet, TRUE_NEGATIVE_MobileNet]]

postives_negatives_MobileNet

[[120, 30], [0, 0]]

4.1.5.2 Obtaining Labels

sns.set()
labels_MobileNet =  np.array([['True positive: ' + str(TRUE_POSITIVE_MobileNet),
                                'False positive: ' + str(FALSE_POSITIVE_MobileNet)],
                                ['False negative: ' + str(FALSE_NEGATIVE_MobileNet),
                                'True negative: ' + str(TRUE_NEGATIVE_MobileNet)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_MobileNet, annot = labels_MobileNet, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb2751fa7d0>

labels_MobileNet

array([['True positive: 120', 'False positive: 30'],
       ['False negative: 0', 'True negative: 0']], dtype='<U18')

4.1.5.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_MobileNet = TRUE_POSITIVE_MobileNet / (TRUE_POSITIVE_MobileNet + FALSE_NEGATIVE_MobileNet)
print("Sensitivity: ", sensitivity_MobileNet)

Sensitivity:  1.0

4.1.5.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_MobileNet = TRUE_NEGATIVE_MobileNet / (TRUE_NEGATIVE_MobileNet + FALSE_NEGATIVE_MobileNet)
    print("Specifity: ", specifity_MobileNet)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

4.1.5.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_MobileNet = TRUE_POSITIVE_MobileNet / (TRUE_POSITIVE_MobileNet + FALSE_POSITIVE_MobileNet)
print("Precision: ", predcision_MobileNet)

Precision:  0.8

4.1.5.6 Calculating Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_MobileNet = TRUE_NEGATIVE_MobileNet / (TRUE_NEGATIVE_MobileNet + FALSE_NEGATIVE_MobileNet)
    print("Negative predictive value: ", npv_MobileNet)
except:
    print("0 Negative Predictions")

0 Negative Predictions

4.1.5.7 Calculating Accuracy

# Accuracy 
accuracy_MobileNet = (TRUE_POSITIVE_MobileNet + TRUE_NEGATIVE_MobileNet) / (TRUE_POSITIVE_MobileNet + FALSE_POSITIVE_MobileNet + TRUE_NEGATIVE_MobileNet + FALSE_NEGATIVE_MobileNet)
print("Accuracy: ", accuracy_MobileNet)

Accuracy:  0.8

4.2 Inception Architecture

4.2.1 Compute Test Set Predictions

# Compute test set predictions
#model_architecture,path_model_weight
NUMBER_TEST_SAMPLES_Inception = 150

inception_architecture_function = inception_architecture()
inception_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5"

y_true_Inception = valid_targets[:NUMBER_TEST_SAMPLES_Inception]
y_score_Inception = []
for index in range(NUMBER_TEST_SAMPLES_Inception): #compute one at a time due to memory constraints
    probs_Inception = predict(img_path = validation_files[index], model_architecture = inception_architecture_function, path_model_weight = inception_architecture_weight_path)
    print("Real values {}...".format(index+1) + "Melanoma : ", valid_targets[index][0], " | Other : ", valid_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Inception.append(probs_Inception)
    
correct_Inception = np.array(y_true_Inception) == np.array(y_score_Inception)

Model: "model_7"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_8 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_196 (Conv2D)             (None, 255, 255, 32) 864         input_8[0][0]                    
__________________________________________________________________________________________________
batch_normalization_196 (BatchN (None, 255, 255, 32) 96          conv2d_196[0][0]                 
__________________________________________________________________________________________________
activation_188 (Activation)     (None, 255, 255, 32) 0           batch_normalization_196[0][0]    
__________________________________________________________________________________________________
conv2d_197 (Conv2D)             (None, 253, 253, 32) 9216        activation_188[0][0]             
__________________________________________________________________________________________________
batch_normalization_197 (BatchN (None, 253, 253, 32) 96          conv2d_197[0][0]                 
__________________________________________________________________________________________________
activation_189 (Activation)     (None, 253, 253, 32) 0           batch_normalization_197[0][0]    
__________________________________________________________________________________________________
conv2d_198 (Conv2D)             (None, 253, 253, 64) 18432       activation_189[0][0]             
__________________________________________________________________________________________________
batch_normalization_198 (BatchN (None, 253, 253, 64) 192         conv2d_198[0][0]                 
__________________________________________________________________________________________________
activation_190 (Activation)     (None, 253, 253, 64) 0           batch_normalization_198[0][0]    
__________________________________________________________________________________________________
max_pooling2d_8 (MaxPooling2D)  (None, 126, 126, 64) 0           activation_190[0][0]             
__________________________________________________________________________________________________
conv2d_199 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_8[0][0]            
__________________________________________________________________________________________________
batch_normalization_199 (BatchN (None, 126, 126, 80) 240         conv2d_199[0][0]                 
__________________________________________________________________________________________________
activation_191 (Activation)     (None, 126, 126, 80) 0           batch_normalization_199[0][0]    
__________________________________________________________________________________________________
conv2d_200 (Conv2D)             (None, 124, 124, 192 138240      activation_191[0][0]             
__________________________________________________________________________________________________
batch_normalization_200 (BatchN (None, 124, 124, 192 576         conv2d_200[0][0]                 
__________________________________________________________________________________________________
activation_192 (Activation)     (None, 124, 124, 192 0           batch_normalization_200[0][0]    
__________________________________________________________________________________________________
max_pooling2d_9 (MaxPooling2D)  (None, 61, 61, 192)  0           activation_192[0][0]             
__________________________________________________________________________________________________
conv2d_204 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_9[0][0]            
__________________________________________________________________________________________________
batch_normalization_204 (BatchN (None, 61, 61, 64)   192         conv2d_204[0][0]                 
__________________________________________________________________________________________________
activation_196 (Activation)     (None, 61, 61, 64)   0           batch_normalization_204[0][0]    
__________________________________________________________________________________________________
conv2d_202 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_9[0][0]            
__________________________________________________________________________________________________
conv2d_205 (Conv2D)             (None, 61, 61, 96)   55296       activation_196[0][0]             
__________________________________________________________________________________________________
batch_normalization_202 (BatchN (None, 61, 61, 48)   144         conv2d_202[0][0]                 
__________________________________________________________________________________________________
batch_normalization_205 (BatchN (None, 61, 61, 96)   288         conv2d_205[0][0]                 
__________________________________________________________________________________________________
activation_194 (Activation)     (None, 61, 61, 48)   0           batch_normalization_202[0][0]    
__________________________________________________________________________________________________
activation_197 (Activation)     (None, 61, 61, 96)   0           batch_normalization_205[0][0]    
__________________________________________________________________________________________________
average_pooling2d_18 (AveragePo (None, 61, 61, 192)  0           max_pooling2d_9[0][0]            
__________________________________________________________________________________________________
conv2d_201 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_9[0][0]            
__________________________________________________________________________________________________
conv2d_203 (Conv2D)             (None, 61, 61, 64)   76800       activation_194[0][0]             
__________________________________________________________________________________________________
conv2d_206 (Conv2D)             (None, 61, 61, 96)   82944       activation_197[0][0]             
__________________________________________________________________________________________________
conv2d_207 (Conv2D)             (None, 61, 61, 32)   6144        average_pooling2d_18[0][0]       
__________________________________________________________________________________________________
batch_normalization_201 (BatchN (None, 61, 61, 64)   192         conv2d_201[0][0]                 
__________________________________________________________________________________________________
batch_normalization_203 (BatchN (None, 61, 61, 64)   192         conv2d_203[0][0]                 
__________________________________________________________________________________________________
batch_normalization_206 (BatchN (None, 61, 61, 96)   288         conv2d_206[0][0]                 
__________________________________________________________________________________________________
batch_normalization_207 (BatchN (None, 61, 61, 32)   96          conv2d_207[0][0]                 
__________________________________________________________________________________________________
activation_193 (Activation)     (None, 61, 61, 64)   0           batch_normalization_201[0][0]    
__________________________________________________________________________________________________
activation_195 (Activation)     (None, 61, 61, 64)   0           batch_normalization_203[0][0]    
__________________________________________________________________________________________________
activation_198 (Activation)     (None, 61, 61, 96)   0           batch_normalization_206[0][0]    
__________________________________________________________________________________________________
activation_199 (Activation)     (None, 61, 61, 32)   0           batch_normalization_207[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_193[0][0]             
                                                                 activation_195[0][0]             
                                                                 activation_198[0][0]             
                                                                 activation_199[0][0]             
__________________________________________________________________________________________________
conv2d_211 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_211 (BatchN (None, 61, 61, 64)   192         conv2d_211[0][0]                 
__________________________________________________________________________________________________
activation_203 (Activation)     (None, 61, 61, 64)   0           batch_normalization_211[0][0]    
__________________________________________________________________________________________________
conv2d_209 (Conv2D)             (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_212 (Conv2D)             (None, 61, 61, 96)   55296       activation_203[0][0]             
__________________________________________________________________________________________________
batch_normalization_209 (BatchN (None, 61, 61, 48)   144         conv2d_209[0][0]                 
__________________________________________________________________________________________________
batch_normalization_212 (BatchN (None, 61, 61, 96)   288         conv2d_212[0][0]                 
__________________________________________________________________________________________________
activation_201 (Activation)     (None, 61, 61, 48)   0           batch_normalization_209[0][0]    
__________________________________________________________________________________________________
activation_204 (Activation)     (None, 61, 61, 96)   0           batch_normalization_212[0][0]    
__________________________________________________________________________________________________
average_pooling2d_19 (AveragePo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_208 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_210 (Conv2D)             (None, 61, 61, 64)   76800       activation_201[0][0]             
__________________________________________________________________________________________________
conv2d_213 (Conv2D)             (None, 61, 61, 96)   82944       activation_204[0][0]             
__________________________________________________________________________________________________
conv2d_214 (Conv2D)             (None, 61, 61, 64)   16384       average_pooling2d_19[0][0]       
__________________________________________________________________________________________________
batch_normalization_208 (BatchN (None, 61, 61, 64)   192         conv2d_208[0][0]                 
__________________________________________________________________________________________________
batch_normalization_210 (BatchN (None, 61, 61, 64)   192         conv2d_210[0][0]                 
__________________________________________________________________________________________________
batch_normalization_213 (BatchN (None, 61, 61, 96)   288         conv2d_213[0][0]                 
__________________________________________________________________________________________________
batch_normalization_214 (BatchN (None, 61, 61, 64)   192         conv2d_214[0][0]                 
__________________________________________________________________________________________________
activation_200 (Activation)     (None, 61, 61, 64)   0           batch_normalization_208[0][0]    
__________________________________________________________________________________________________
activation_202 (Activation)     (None, 61, 61, 64)   0           batch_normalization_210[0][0]    
__________________________________________________________________________________________________
activation_205 (Activation)     (None, 61, 61, 96)   0           batch_normalization_213[0][0]    
__________________________________________________________________________________________________
activation_206 (Activation)     (None, 61, 61, 64)   0           batch_normalization_214[0][0]    
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_200[0][0]             
                                                                 activation_202[0][0]             
                                                                 activation_205[0][0]             
                                                                 activation_206[0][0]             
__________________________________________________________________________________________________
conv2d_218 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_218 (BatchN (None, 61, 61, 64)   192         conv2d_218[0][0]                 
__________________________________________________________________________________________________
activation_210 (Activation)     (None, 61, 61, 64)   0           batch_normalization_218[0][0]    
__________________________________________________________________________________________________
conv2d_216 (Conv2D)             (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_219 (Conv2D)             (None, 61, 61, 96)   55296       activation_210[0][0]             
__________________________________________________________________________________________________
batch_normalization_216 (BatchN (None, 61, 61, 48)   144         conv2d_216[0][0]                 
__________________________________________________________________________________________________
batch_normalization_219 (BatchN (None, 61, 61, 96)   288         conv2d_219[0][0]                 
__________________________________________________________________________________________________
activation_208 (Activation)     (None, 61, 61, 48)   0           batch_normalization_216[0][0]    
__________________________________________________________________________________________________
activation_211 (Activation)     (None, 61, 61, 96)   0           batch_normalization_219[0][0]    
__________________________________________________________________________________________________
average_pooling2d_20 (AveragePo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_215 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_217 (Conv2D)             (None, 61, 61, 64)   76800       activation_208[0][0]             
__________________________________________________________________________________________________
conv2d_220 (Conv2D)             (None, 61, 61, 96)   82944       activation_211[0][0]             
__________________________________________________________________________________________________
conv2d_221 (Conv2D)             (None, 61, 61, 64)   18432       average_pooling2d_20[0][0]       
__________________________________________________________________________________________________
batch_normalization_215 (BatchN (None, 61, 61, 64)   192         conv2d_215[0][0]                 
__________________________________________________________________________________________________
batch_normalization_217 (BatchN (None, 61, 61, 64)   192         conv2d_217[0][0]                 
__________________________________________________________________________________________________
batch_normalization_220 (BatchN (None, 61, 61, 96)   288         conv2d_220[0][0]                 
__________________________________________________________________________________________________
batch_normalization_221 (BatchN (None, 61, 61, 64)   192         conv2d_221[0][0]                 
__________________________________________________________________________________________________
activation_207 (Activation)     (None, 61, 61, 64)   0           batch_normalization_215[0][0]    
__________________________________________________________________________________________________
activation_209 (Activation)     (None, 61, 61, 64)   0           batch_normalization_217[0][0]    
__________________________________________________________________________________________________
activation_212 (Activation)     (None, 61, 61, 96)   0           batch_normalization_220[0][0]    
__________________________________________________________________________________________________
activation_213 (Activation)     (None, 61, 61, 64)   0           batch_normalization_221[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_207[0][0]             
                                                                 activation_209[0][0]             
                                                                 activation_212[0][0]             
                                                                 activation_213[0][0]             
__________________________________________________________________________________________________
conv2d_223 (Conv2D)             (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_223 (BatchN (None, 61, 61, 64)   192         conv2d_223[0][0]                 
__________________________________________________________________________________________________
activation_215 (Activation)     (None, 61, 61, 64)   0           batch_normalization_223[0][0]    
__________________________________________________________________________________________________
conv2d_224 (Conv2D)             (None, 61, 61, 96)   55296       activation_215[0][0]             
__________________________________________________________________________________________________
batch_normalization_224 (BatchN (None, 61, 61, 96)   288         conv2d_224[0][0]                 
__________________________________________________________________________________________________
activation_216 (Activation)     (None, 61, 61, 96)   0           batch_normalization_224[0][0]    
__________________________________________________________________________________________________
conv2d_222 (Conv2D)             (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_225 (Conv2D)             (None, 30, 30, 96)   82944       activation_216[0][0]             
__________________________________________________________________________________________________
batch_normalization_222 (BatchN (None, 30, 30, 384)  1152        conv2d_222[0][0]                 
__________________________________________________________________________________________________
batch_normalization_225 (BatchN (None, 30, 30, 96)   288         conv2d_225[0][0]                 
__________________________________________________________________________________________________
activation_214 (Activation)     (None, 30, 30, 384)  0           batch_normalization_222[0][0]    
__________________________________________________________________________________________________
activation_217 (Activation)     (None, 30, 30, 96)   0           batch_normalization_225[0][0]    
__________________________________________________________________________________________________
max_pooling2d_10 (MaxPooling2D) (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_214[0][0]             
                                                                 activation_217[0][0]             
                                                                 max_pooling2d_10[0][0]           
__________________________________________________________________________________________________
conv2d_230 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_230 (BatchN (None, 30, 30, 128)  384         conv2d_230[0][0]                 
__________________________________________________________________________________________________
activation_222 (Activation)     (None, 30, 30, 128)  0           batch_normalization_230[0][0]    
__________________________________________________________________________________________________
conv2d_231 (Conv2D)             (None, 30, 30, 128)  114688      activation_222[0][0]             
__________________________________________________________________________________________________
batch_normalization_231 (BatchN (None, 30, 30, 128)  384         conv2d_231[0][0]                 
__________________________________________________________________________________________________
activation_223 (Activation)     (None, 30, 30, 128)  0           batch_normalization_231[0][0]    
__________________________________________________________________________________________________
conv2d_227 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_232 (Conv2D)             (None, 30, 30, 128)  114688      activation_223[0][0]             
__________________________________________________________________________________________________
batch_normalization_227 (BatchN (None, 30, 30, 128)  384         conv2d_227[0][0]                 
__________________________________________________________________________________________________
batch_normalization_232 (BatchN (None, 30, 30, 128)  384         conv2d_232[0][0]                 
__________________________________________________________________________________________________
activation_219 (Activation)     (None, 30, 30, 128)  0           batch_normalization_227[0][0]    
__________________________________________________________________________________________________
activation_224 (Activation)     (None, 30, 30, 128)  0           batch_normalization_232[0][0]    
__________________________________________________________________________________________________
conv2d_228 (Conv2D)             (None, 30, 30, 128)  114688      activation_219[0][0]             
__________________________________________________________________________________________________
conv2d_233 (Conv2D)             (None, 30, 30, 128)  114688      activation_224[0][0]             
__________________________________________________________________________________________________
batch_normalization_228 (BatchN (None, 30, 30, 128)  384         conv2d_228[0][0]                 
__________________________________________________________________________________________________
batch_normalization_233 (BatchN (None, 30, 30, 128)  384         conv2d_233[0][0]                 
__________________________________________________________________________________________________
activation_220 (Activation)     (None, 30, 30, 128)  0           batch_normalization_228[0][0]    
__________________________________________________________________________________________________
activation_225 (Activation)     (None, 30, 30, 128)  0           batch_normalization_233[0][0]    
__________________________________________________________________________________________________
average_pooling2d_21 (AveragePo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_226 (Conv2D)             (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_229 (Conv2D)             (None, 30, 30, 192)  172032      activation_220[0][0]             
__________________________________________________________________________________________________
conv2d_234 (Conv2D)             (None, 30, 30, 192)  172032      activation_225[0][0]             
__________________________________________________________________________________________________
conv2d_235 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_21[0][0]       
__________________________________________________________________________________________________
batch_normalization_226 (BatchN (None, 30, 30, 192)  576         conv2d_226[0][0]                 
__________________________________________________________________________________________________
batch_normalization_229 (BatchN (None, 30, 30, 192)  576         conv2d_229[0][0]                 
__________________________________________________________________________________________________
batch_normalization_234 (BatchN (None, 30, 30, 192)  576         conv2d_234[0][0]                 
__________________________________________________________________________________________________
batch_normalization_235 (BatchN (None, 30, 30, 192)  576         conv2d_235[0][0]                 
__________________________________________________________________________________________________
activation_218 (Activation)     (None, 30, 30, 192)  0           batch_normalization_226[0][0]    
__________________________________________________________________________________________________
activation_221 (Activation)     (None, 30, 30, 192)  0           batch_normalization_229[0][0]    
__________________________________________________________________________________________________
activation_226 (Activation)     (None, 30, 30, 192)  0           batch_normalization_234[0][0]    
__________________________________________________________________________________________________
activation_227 (Activation)     (None, 30, 30, 192)  0           batch_normalization_235[0][0]    
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_218[0][0]             
                                                                 activation_221[0][0]             
                                                                 activation_226[0][0]             
                                                                 activation_227[0][0]             
__________________________________________________________________________________________________
conv2d_240 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_240 (BatchN (None, 30, 30, 160)  480         conv2d_240[0][0]                 
__________________________________________________________________________________________________
activation_232 (Activation)     (None, 30, 30, 160)  0           batch_normalization_240[0][0]    
__________________________________________________________________________________________________
conv2d_241 (Conv2D)             (None, 30, 30, 160)  179200      activation_232[0][0]             
__________________________________________________________________________________________________
batch_normalization_241 (BatchN (None, 30, 30, 160)  480         conv2d_241[0][0]                 
__________________________________________________________________________________________________
activation_233 (Activation)     (None, 30, 30, 160)  0           batch_normalization_241[0][0]    
__________________________________________________________________________________________________
conv2d_237 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_242 (Conv2D)             (None, 30, 30, 160)  179200      activation_233[0][0]             
__________________________________________________________________________________________________
batch_normalization_237 (BatchN (None, 30, 30, 160)  480         conv2d_237[0][0]                 
__________________________________________________________________________________________________
batch_normalization_242 (BatchN (None, 30, 30, 160)  480         conv2d_242[0][0]                 
__________________________________________________________________________________________________
activation_229 (Activation)     (None, 30, 30, 160)  0           batch_normalization_237[0][0]    
__________________________________________________________________________________________________
activation_234 (Activation)     (None, 30, 30, 160)  0           batch_normalization_242[0][0]    
__________________________________________________________________________________________________
conv2d_238 (Conv2D)             (None, 30, 30, 160)  179200      activation_229[0][0]             
__________________________________________________________________________________________________
conv2d_243 (Conv2D)             (None, 30, 30, 160)  179200      activation_234[0][0]             
__________________________________________________________________________________________________
batch_normalization_238 (BatchN (None, 30, 30, 160)  480         conv2d_238[0][0]                 
__________________________________________________________________________________________________
batch_normalization_243 (BatchN (None, 30, 30, 160)  480         conv2d_243[0][0]                 
__________________________________________________________________________________________________
activation_230 (Activation)     (None, 30, 30, 160)  0           batch_normalization_238[0][0]    
__________________________________________________________________________________________________
activation_235 (Activation)     (None, 30, 30, 160)  0           batch_normalization_243[0][0]    
__________________________________________________________________________________________________
average_pooling2d_22 (AveragePo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_236 (Conv2D)             (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_239 (Conv2D)             (None, 30, 30, 192)  215040      activation_230[0][0]             
__________________________________________________________________________________________________
conv2d_244 (Conv2D)             (None, 30, 30, 192)  215040      activation_235[0][0]             
__________________________________________________________________________________________________
conv2d_245 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_22[0][0]       
__________________________________________________________________________________________________
batch_normalization_236 (BatchN (None, 30, 30, 192)  576         conv2d_236[0][0]                 
__________________________________________________________________________________________________
batch_normalization_239 (BatchN (None, 30, 30, 192)  576         conv2d_239[0][0]                 
__________________________________________________________________________________________________
batch_normalization_244 (BatchN (None, 30, 30, 192)  576         conv2d_244[0][0]                 
__________________________________________________________________________________________________
batch_normalization_245 (BatchN (None, 30, 30, 192)  576         conv2d_245[0][0]                 
__________________________________________________________________________________________________
activation_228 (Activation)     (None, 30, 30, 192)  0           batch_normalization_236[0][0]    
__________________________________________________________________________________________________
activation_231 (Activation)     (None, 30, 30, 192)  0           batch_normalization_239[0][0]    
__________________________________________________________________________________________________
activation_236 (Activation)     (None, 30, 30, 192)  0           batch_normalization_244[0][0]    
__________________________________________________________________________________________________
activation_237 (Activation)     (None, 30, 30, 192)  0           batch_normalization_245[0][0]    
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_228[0][0]             
                                                                 activation_231[0][0]             
                                                                 activation_236[0][0]             
                                                                 activation_237[0][0]             
__________________________________________________________________________________________________
conv2d_250 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_250 (BatchN (None, 30, 30, 160)  480         conv2d_250[0][0]                 
__________________________________________________________________________________________________
activation_242 (Activation)     (None, 30, 30, 160)  0           batch_normalization_250[0][0]    
__________________________________________________________________________________________________
conv2d_251 (Conv2D)             (None, 30, 30, 160)  179200      activation_242[0][0]             
__________________________________________________________________________________________________
batch_normalization_251 (BatchN (None, 30, 30, 160)  480         conv2d_251[0][0]                 
__________________________________________________________________________________________________
activation_243 (Activation)     (None, 30, 30, 160)  0           batch_normalization_251[0][0]    
__________________________________________________________________________________________________
conv2d_247 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_252 (Conv2D)             (None, 30, 30, 160)  179200      activation_243[0][0]             
__________________________________________________________________________________________________
batch_normalization_247 (BatchN (None, 30, 30, 160)  480         conv2d_247[0][0]                 
__________________________________________________________________________________________________
batch_normalization_252 (BatchN (None, 30, 30, 160)  480         conv2d_252[0][0]                 
__________________________________________________________________________________________________
activation_239 (Activation)     (None, 30, 30, 160)  0           batch_normalization_247[0][0]    
__________________________________________________________________________________________________
activation_244 (Activation)     (None, 30, 30, 160)  0           batch_normalization_252[0][0]    
__________________________________________________________________________________________________
conv2d_248 (Conv2D)             (None, 30, 30, 160)  179200      activation_239[0][0]             
__________________________________________________________________________________________________
conv2d_253 (Conv2D)             (None, 30, 30, 160)  179200      activation_244[0][0]             
__________________________________________________________________________________________________
batch_normalization_248 (BatchN (None, 30, 30, 160)  480         conv2d_248[0][0]                 
__________________________________________________________________________________________________
batch_normalization_253 (BatchN (None, 30, 30, 160)  480         conv2d_253[0][0]                 
__________________________________________________________________________________________________
activation_240 (Activation)     (None, 30, 30, 160)  0           batch_normalization_248[0][0]    
__________________________________________________________________________________________________
activation_245 (Activation)     (None, 30, 30, 160)  0           batch_normalization_253[0][0]    
__________________________________________________________________________________________________
average_pooling2d_23 (AveragePo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_246 (Conv2D)             (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_249 (Conv2D)             (None, 30, 30, 192)  215040      activation_240[0][0]             
__________________________________________________________________________________________________
conv2d_254 (Conv2D)             (None, 30, 30, 192)  215040      activation_245[0][0]             
__________________________________________________________________________________________________
conv2d_255 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_23[0][0]       
__________________________________________________________________________________________________
batch_normalization_246 (BatchN (None, 30, 30, 192)  576         conv2d_246[0][0]                 
__________________________________________________________________________________________________
batch_normalization_249 (BatchN (None, 30, 30, 192)  576         conv2d_249[0][0]                 
__________________________________________________________________________________________________
batch_normalization_254 (BatchN (None, 30, 30, 192)  576         conv2d_254[0][0]                 
__________________________________________________________________________________________________
batch_normalization_255 (BatchN (None, 30, 30, 192)  576         conv2d_255[0][0]                 
__________________________________________________________________________________________________
activation_238 (Activation)     (None, 30, 30, 192)  0           batch_normalization_246[0][0]    
__________________________________________________________________________________________________
activation_241 (Activation)     (None, 30, 30, 192)  0           batch_normalization_249[0][0]    
__________________________________________________________________________________________________
activation_246 (Activation)     (None, 30, 30, 192)  0           batch_normalization_254[0][0]    
__________________________________________________________________________________________________
activation_247 (Activation)     (None, 30, 30, 192)  0           batch_normalization_255[0][0]    
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_238[0][0]             
                                                                 activation_241[0][0]             
                                                                 activation_246[0][0]             
                                                                 activation_247[0][0]             
__________________________________________________________________________________________________
conv2d_260 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_260 (BatchN (None, 30, 30, 192)  576         conv2d_260[0][0]                 
__________________________________________________________________________________________________
activation_252 (Activation)     (None, 30, 30, 192)  0           batch_normalization_260[0][0]    
__________________________________________________________________________________________________
conv2d_261 (Conv2D)             (None, 30, 30, 192)  258048      activation_252[0][0]             
__________________________________________________________________________________________________
batch_normalization_261 (BatchN (None, 30, 30, 192)  576         conv2d_261[0][0]                 
__________________________________________________________________________________________________
activation_253 (Activation)     (None, 30, 30, 192)  0           batch_normalization_261[0][0]    
__________________________________________________________________________________________________
conv2d_257 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_262 (Conv2D)             (None, 30, 30, 192)  258048      activation_253[0][0]             
__________________________________________________________________________________________________
batch_normalization_257 (BatchN (None, 30, 30, 192)  576         conv2d_257[0][0]                 
__________________________________________________________________________________________________
batch_normalization_262 (BatchN (None, 30, 30, 192)  576         conv2d_262[0][0]                 
__________________________________________________________________________________________________
activation_249 (Activation)     (None, 30, 30, 192)  0           batch_normalization_257[0][0]    
__________________________________________________________________________________________________
activation_254 (Activation)     (None, 30, 30, 192)  0           batch_normalization_262[0][0]    
__________________________________________________________________________________________________
conv2d_258 (Conv2D)             (None, 30, 30, 192)  258048      activation_249[0][0]             
__________________________________________________________________________________________________
conv2d_263 (Conv2D)             (None, 30, 30, 192)  258048      activation_254[0][0]             
__________________________________________________________________________________________________
batch_normalization_258 (BatchN (None, 30, 30, 192)  576         conv2d_258[0][0]                 
__________________________________________________________________________________________________
batch_normalization_263 (BatchN (None, 30, 30, 192)  576         conv2d_263[0][0]                 
__________________________________________________________________________________________________
activation_250 (Activation)     (None, 30, 30, 192)  0           batch_normalization_258[0][0]    
__________________________________________________________________________________________________
activation_255 (Activation)     (None, 30, 30, 192)  0           batch_normalization_263[0][0]    
__________________________________________________________________________________________________
average_pooling2d_24 (AveragePo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_256 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_259 (Conv2D)             (None, 30, 30, 192)  258048      activation_250[0][0]             
__________________________________________________________________________________________________
conv2d_264 (Conv2D)             (None, 30, 30, 192)  258048      activation_255[0][0]             
__________________________________________________________________________________________________
conv2d_265 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_24[0][0]       
__________________________________________________________________________________________________
batch_normalization_256 (BatchN (None, 30, 30, 192)  576         conv2d_256[0][0]                 
__________________________________________________________________________________________________
batch_normalization_259 (BatchN (None, 30, 30, 192)  576         conv2d_259[0][0]                 
__________________________________________________________________________________________________
batch_normalization_264 (BatchN (None, 30, 30, 192)  576         conv2d_264[0][0]                 
__________________________________________________________________________________________________
batch_normalization_265 (BatchN (None, 30, 30, 192)  576         conv2d_265[0][0]                 
__________________________________________________________________________________________________
activation_248 (Activation)     (None, 30, 30, 192)  0           batch_normalization_256[0][0]    
__________________________________________________________________________________________________
activation_251 (Activation)     (None, 30, 30, 192)  0           batch_normalization_259[0][0]    
__________________________________________________________________________________________________
activation_256 (Activation)     (None, 30, 30, 192)  0           batch_normalization_264[0][0]    
__________________________________________________________________________________________________
activation_257 (Activation)     (None, 30, 30, 192)  0           batch_normalization_265[0][0]    
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_248[0][0]             
                                                                 activation_251[0][0]             
                                                                 activation_256[0][0]             
                                                                 activation_257[0][0]             
__________________________________________________________________________________________________
conv2d_268 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_268 (BatchN (None, 30, 30, 192)  576         conv2d_268[0][0]                 
__________________________________________________________________________________________________
activation_260 (Activation)     (None, 30, 30, 192)  0           batch_normalization_268[0][0]    
__________________________________________________________________________________________________
conv2d_269 (Conv2D)             (None, 30, 30, 192)  258048      activation_260[0][0]             
__________________________________________________________________________________________________
batch_normalization_269 (BatchN (None, 30, 30, 192)  576         conv2d_269[0][0]                 
__________________________________________________________________________________________________
activation_261 (Activation)     (None, 30, 30, 192)  0           batch_normalization_269[0][0]    
__________________________________________________________________________________________________
conv2d_266 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_270 (Conv2D)             (None, 30, 30, 192)  258048      activation_261[0][0]             
__________________________________________________________________________________________________
batch_normalization_266 (BatchN (None, 30, 30, 192)  576         conv2d_266[0][0]                 
__________________________________________________________________________________________________
batch_normalization_270 (BatchN (None, 30, 30, 192)  576         conv2d_270[0][0]                 
__________________________________________________________________________________________________
activation_258 (Activation)     (None, 30, 30, 192)  0           batch_normalization_266[0][0]    
__________________________________________________________________________________________________
activation_262 (Activation)     (None, 30, 30, 192)  0           batch_normalization_270[0][0]    
__________________________________________________________________________________________________
conv2d_267 (Conv2D)             (None, 14, 14, 320)  552960      activation_258[0][0]             
__________________________________________________________________________________________________
conv2d_271 (Conv2D)             (None, 14, 14, 192)  331776      activation_262[0][0]             
__________________________________________________________________________________________________
batch_normalization_267 (BatchN (None, 14, 14, 320)  960         conv2d_267[0][0]                 
__________________________________________________________________________________________________
batch_normalization_271 (BatchN (None, 14, 14, 192)  576         conv2d_271[0][0]                 
__________________________________________________________________________________________________
activation_259 (Activation)     (None, 14, 14, 320)  0           batch_normalization_267[0][0]    
__________________________________________________________________________________________________
activation_263 (Activation)     (None, 14, 14, 192)  0           batch_normalization_271[0][0]    
__________________________________________________________________________________________________
max_pooling2d_11 (MaxPooling2D) (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_259[0][0]             
                                                                 activation_263[0][0]             
                                                                 max_pooling2d_11[0][0]           
__________________________________________________________________________________________________
conv2d_276 (Conv2D)             (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_276 (BatchN (None, 14, 14, 448)  1344        conv2d_276[0][0]                 
__________________________________________________________________________________________________
activation_268 (Activation)     (None, 14, 14, 448)  0           batch_normalization_276[0][0]    
__________________________________________________________________________________________________
conv2d_273 (Conv2D)             (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_277 (Conv2D)             (None, 14, 14, 384)  1548288     activation_268[0][0]             
__________________________________________________________________________________________________
batch_normalization_273 (BatchN (None, 14, 14, 384)  1152        conv2d_273[0][0]                 
__________________________________________________________________________________________________
batch_normalization_277 (BatchN (None, 14, 14, 384)  1152        conv2d_277[0][0]                 
__________________________________________________________________________________________________
activation_265 (Activation)     (None, 14, 14, 384)  0           batch_normalization_273[0][0]    
__________________________________________________________________________________________________
activation_269 (Activation)     (None, 14, 14, 384)  0           batch_normalization_277[0][0]    
__________________________________________________________________________________________________
conv2d_274 (Conv2D)             (None, 14, 14, 384)  442368      activation_265[0][0]             
__________________________________________________________________________________________________
conv2d_275 (Conv2D)             (None, 14, 14, 384)  442368      activation_265[0][0]             
__________________________________________________________________________________________________
conv2d_278 (Conv2D)             (None, 14, 14, 384)  442368      activation_269[0][0]             
__________________________________________________________________________________________________
conv2d_279 (Conv2D)             (None, 14, 14, 384)  442368      activation_269[0][0]             
__________________________________________________________________________________________________
average_pooling2d_25 (AveragePo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_272 (Conv2D)             (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_274 (BatchN (None, 14, 14, 384)  1152        conv2d_274[0][0]                 
__________________________________________________________________________________________________
batch_normalization_275 (BatchN (None, 14, 14, 384)  1152        conv2d_275[0][0]                 
__________________________________________________________________________________________________
batch_normalization_278 (BatchN (None, 14, 14, 384)  1152        conv2d_278[0][0]                 
__________________________________________________________________________________________________
batch_normalization_279 (BatchN (None, 14, 14, 384)  1152        conv2d_279[0][0]                 
__________________________________________________________________________________________________
conv2d_280 (Conv2D)             (None, 14, 14, 192)  245760      average_pooling2d_25[0][0]       
__________________________________________________________________________________________________
batch_normalization_272 (BatchN (None, 14, 14, 320)  960         conv2d_272[0][0]                 
__________________________________________________________________________________________________
activation_266 (Activation)     (None, 14, 14, 384)  0           batch_normalization_274[0][0]    
__________________________________________________________________________________________________
activation_267 (Activation)     (None, 14, 14, 384)  0           batch_normalization_275[0][0]    
__________________________________________________________________________________________________
activation_270 (Activation)     (None, 14, 14, 384)  0           batch_normalization_278[0][0]    
__________________________________________________________________________________________________
activation_271 (Activation)     (None, 14, 14, 384)  0           batch_normalization_279[0][0]    
__________________________________________________________________________________________________
batch_normalization_280 (BatchN (None, 14, 14, 192)  576         conv2d_280[0][0]                 
__________________________________________________________________________________________________
activation_264 (Activation)     (None, 14, 14, 320)  0           batch_normalization_272[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_266[0][0]             
                                                                 activation_267[0][0]             
__________________________________________________________________________________________________
concatenate_4 (Concatenate)     (None, 14, 14, 768)  0           activation_270[0][0]             
                                                                 activation_271[0][0]             
__________________________________________________________________________________________________
activation_272 (Activation)     (None, 14, 14, 192)  0           batch_normalization_280[0][0]    
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_264[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_4[0][0]              
                                                                 activation_272[0][0]             
__________________________________________________________________________________________________
conv2d_285 (Conv2D)             (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_285 (BatchN (None, 14, 14, 448)  1344        conv2d_285[0][0]                 
__________________________________________________________________________________________________
activation_277 (Activation)     (None, 14, 14, 448)  0           batch_normalization_285[0][0]    
__________________________________________________________________________________________________
conv2d_282 (Conv2D)             (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_286 (Conv2D)             (None, 14, 14, 384)  1548288     activation_277[0][0]             
__________________________________________________________________________________________________
batch_normalization_282 (BatchN (None, 14, 14, 384)  1152        conv2d_282[0][0]                 
__________________________________________________________________________________________________
batch_normalization_286 (BatchN (None, 14, 14, 384)  1152        conv2d_286[0][0]                 
__________________________________________________________________________________________________
activation_274 (Activation)     (None, 14, 14, 384)  0           batch_normalization_282[0][0]    
__________________________________________________________________________________________________
activation_278 (Activation)     (None, 14, 14, 384)  0           batch_normalization_286[0][0]    
__________________________________________________________________________________________________
conv2d_283 (Conv2D)             (None, 14, 14, 384)  442368      activation_274[0][0]             
__________________________________________________________________________________________________
conv2d_284 (Conv2D)             (None, 14, 14, 384)  442368      activation_274[0][0]             
__________________________________________________________________________________________________
conv2d_287 (Conv2D)             (None, 14, 14, 384)  442368      activation_278[0][0]             
__________________________________________________________________________________________________
conv2d_288 (Conv2D)             (None, 14, 14, 384)  442368      activation_278[0][0]             
__________________________________________________________________________________________________
average_pooling2d_26 (AveragePo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_281 (Conv2D)             (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_283 (BatchN (None, 14, 14, 384)  1152        conv2d_283[0][0]                 
__________________________________________________________________________________________________
batch_normalization_284 (BatchN (None, 14, 14, 384)  1152        conv2d_284[0][0]                 
__________________________________________________________________________________________________
batch_normalization_287 (BatchN (None, 14, 14, 384)  1152        conv2d_287[0][0]                 
__________________________________________________________________________________________________
batch_normalization_288 (BatchN (None, 14, 14, 384)  1152        conv2d_288[0][0]                 
__________________________________________________________________________________________________
conv2d_289 (Conv2D)             (None, 14, 14, 192)  393216      average_pooling2d_26[0][0]       
__________________________________________________________________________________________________
batch_normalization_281 (BatchN (None, 14, 14, 320)  960         conv2d_281[0][0]                 
__________________________________________________________________________________________________
activation_275 (Activation)     (None, 14, 14, 384)  0           batch_normalization_283[0][0]    
__________________________________________________________________________________________________
activation_276 (Activation)     (None, 14, 14, 384)  0           batch_normalization_284[0][0]    
__________________________________________________________________________________________________
activation_279 (Activation)     (None, 14, 14, 384)  0           batch_normalization_287[0][0]    
__________________________________________________________________________________________________
activation_280 (Activation)     (None, 14, 14, 384)  0           batch_normalization_288[0][0]    
__________________________________________________________________________________________________
batch_normalization_289 (BatchN (None, 14, 14, 192)  576         conv2d_289[0][0]                 
__________________________________________________________________________________________________
activation_273 (Activation)     (None, 14, 14, 320)  0           batch_normalization_281[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_275[0][0]             
                                                                 activation_276[0][0]             
__________________________________________________________________________________________________
concatenate_5 (Concatenate)     (None, 14, 14, 768)  0           activation_279[0][0]             
                                                                 activation_280[0][0]             
__________________________________________________________________________________________________
activation_281 (Activation)     (None, 14, 14, 192)  0           batch_normalization_289[0][0]    
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_273[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_5[0][0]              
                                                                 activation_281[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_7 (Glo (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dense_7 (Dense)                 (None, 2)            4098        global_average_pooling2d_7[0][0] 
==================================================================================================
Total params: 21,806,882
Trainable params: 21,772,450
Non-trainable params: 34,432
__________________________________________________________________________________________________
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0004337.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89354306  | Other :  0.10645693
Real values 1...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932921  | Other :  0.10670786
Real values 2...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918999  | Other :  0.10810019
Real values 3...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003539.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926158  | Other :  0.107384145
Real values 4...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003805.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89133435  | Other :  0.10866566
Real values 5...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9052122  | Other :  0.09478781
Real values 6...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001852.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89178693  | Other :  0.10821307
Real values 7...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003657.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89105725  | Other :  0.108942725
Real values 8...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003462.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918746  | Other :  0.108125396
Real values 9...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001871.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8913877  | Other :  0.10861233
Real values 10...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909062  | Other :  0.109093815
Real values 11...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915697  | Other :  0.10843033
Real values 12...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006914.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908398  | Other :  0.1091602
Real values 13...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007141.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909301  | Other :  0.109069884
Real values 14...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007344.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89191145  | Other :  0.10808858
Real values 15...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007235.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8776588  | Other :  0.12234125
Real values 16...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908292  | Other :  0.10917084
Real values 17...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89157385  | Other :  0.10842616
Real values 18...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008524.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8947203  | Other :  0.10527964
Real values 19...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007528.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88074905  | Other :  0.11925092
Real values 20...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8985823  | Other :  0.10141771
Real values 21...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007332.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.81313896  | Other :  0.18686111
Real values 22...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006671.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89086986  | Other :  0.10913013
Real values 23...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0010459.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99986815  | Other :  0.00013178373
Real values 24...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012099.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7426369  | Other :  0.25736308
Real values 25...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012126.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89091736  | Other :  0.109082595
Real values 26...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89093155  | Other :  0.10906847
Real values 27...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0009995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88160884  | Other :  0.11839109
Real values 28...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926175  | Other :  0.10738243
Real values 29...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012151.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89121145  | Other :  0.10878855
Real values 30...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012204.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8550219  | Other :  0.14497812
Real values 31...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012143.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  2.2291592e-11
Real values 32...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012191.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9999336  | Other :  6.6404114e-05
Real values 33...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012109.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89091575  | Other :  0.10908425
Real values 34...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012159.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.847963  | Other :  0.15203704
Real values 35...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8921407  | Other :  0.10785934
Real values 36...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012316.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911685  | Other :  0.10883153
Real values 37...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012306.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910257  | Other :  0.1089743
Real values 38...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916978  | Other :  0.108302206
Real values 39...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910621  | Other :  0.10893794
Real values 40...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012380.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8387856  | Other :  0.16121444
Real values 41...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8914221  | Other :  0.10857797
Real values 42...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012222.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8917738  | Other :  0.10822615
Real values 43...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012335.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8598695  | Other :  0.14013052
Real values 44...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85500187  | Other :  0.14499816
Real values 45...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89286995  | Other :  0.10712998
Real values 46...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89181167  | Other :  0.10818833
Real values 47...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89080507  | Other :  0.109194964
Real values 48...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012210.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919794  | Other :  0.10802054
Real values 49...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85945505  | Other :  0.14054494
Real values 50...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915457  | Other :  0.10845428
Real values 51...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.843516  | Other :  0.15648405
Real values 52...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012538.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8930364  | Other :  0.10696358
Real values 53...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012684.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89121157  | Other :  0.10878845
Real values 54...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8924557  | Other :  0.107544295
Real values 55...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89072335  | Other :  0.109276615
Real values 56...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012400.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89088607  | Other :  0.10911398
Real values 57...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012547.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8950183  | Other :  0.104981676
Real values 58...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.82437456  | Other :  0.17562546
Real values 59...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012492.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.6405953e-09
Real values 60...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012660.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8967837  | Other :  0.10321626
Real values 61...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013082.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87488526  | Other :  0.12511477
Real values 62...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.999997  | Other :  2.9509588e-06
Real values 63...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8493812  | Other :  0.15061876
Real values 64...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013188.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910649  | Other :  0.10893507
Real values 65...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89485747  | Other :  0.10514248
Real values 66...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910488  | Other :  0.10895123
Real values 67...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89143527  | Other :  0.10856476
Real values 68...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89381355  | Other :  0.106186464
Real values 69...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013104.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879941  | Other :  0.112005904
Real values 70...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013128.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89221555  | Other :  0.10778441
Real values 71...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85970795  | Other :  0.14029202
Real values 72...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013010.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8923267  | Other :  0.107673354
Real values 73...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013491.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909344  | Other :  0.109065644
Real values 74...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013549.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9303817  | Other :  0.06961835
Real values 75...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013562.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909088  | Other :  0.109091274
Real values 76...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013501.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926849  | Other :  0.10731515
Real values 77...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8914925  | Other :  0.1085075
Real values 78...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916603  | Other :  0.10833974
Real values 79...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013632.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8903984  | Other :  0.10960163
Real values 80...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013561.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8963026  | Other :  0.10369738
Real values 81...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013518.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89153624  | Other :  0.10846378
Real values 82...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013527.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8906853  | Other :  0.10931466
Real values 83...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013421.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89243186  | Other :  0.10756809
Real values 84...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89214534  | Other :  0.10785464
Real values 85...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013898.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89200306  | Other :  0.107996926
Real values 86...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013828.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86141264  | Other :  0.13858731
Real values 87...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8274367  | Other :  0.17256333
Real values 88...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933322  | Other :  0.1066678
Real values 89...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013702.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.4760261e-10
Real values 90...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8968948  | Other :  0.103105135
Real values 91...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013736.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.95801455  | Other :  0.041985497
Real values 92...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949544  | Other :  0.105045564
Real values 93...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  5.512512e-10
Real values 94...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925436  | Other :  0.10745639
Real values 95...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013793.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7872247  | Other :  0.21277533
Real values 96...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  8.0282054e-17
Real values 97...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89176387  | Other :  0.10823615
Real values 98...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014428.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89095473  | Other :  0.10904528
Real values 99...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014178.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89069015  | Other :  0.10930985
Real values 100...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014382.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89171165  | Other :  0.108288325
Real values 101...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926861  | Other :  0.10731384
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.82253206  | Other :  0.17746799
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014302.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.95465446  | Other :  0.045345575
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89252245  | Other :  0.10747749
Real values 105...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89145213  | Other :  0.10854787
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014162.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8975952  | Other :  0.102404796
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014618.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.77911305  | Other :  0.22088695
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014610.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8892696  | Other :  0.11073042
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014601.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.80314755  | Other :  0.19685249
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014620.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86628467  | Other :  0.13371529
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014616.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86619294  | Other :  0.13380711
Real values 112...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014623.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8951477  | Other :  0.10485226
Real values 113...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014572.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89538777  | Other :  0.1046122
Real values 114...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014558.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8955168  | Other :  0.10448312
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014624.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9002394  | Other :  0.099760614
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014633.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8336916  | Other :  0.16630843
Real values 117...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014597.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88128793  | Other :  0.11871211
Real values 118...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014608.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90096176  | Other :  0.099038236
Real values 119...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014611.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8657261  | Other :  0.13427395
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9018648  | Other :  0.09813521
Real values 121...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014829.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87354314  | Other :  0.12645687
Real values 122...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014635.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8458908  | Other :  0.15410917
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014857.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89341885  | Other :  0.10658111
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014931.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9009717  | Other :  0.09902824
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8497724  | Other :  0.1502276
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89997077  | Other :  0.10002926
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014712.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.93911666  | Other :  0.060883343
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014688.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949769  | Other :  0.10502306
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89771557  | Other :  0.10228448
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8843424  | Other :  0.11565762
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.82252055  | Other :  0.17747946
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8927204  | Other :  0.10727957
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8930652  | Other :  0.106934816
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9785423  | Other :  0.021457616
Real values 135...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015124.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8921381  | Other :  0.10786186
Real values 136...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015243.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926276  | Other :  0.10737236
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015144.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8964629  | Other :  0.10353708
Real values 138...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.82466966  | Other :  0.17533033
Real values 139...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915849  | Other :  0.10841512
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8924706  | Other :  0.10752943
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89579964  | Other :  0.10420035
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89204335  | Other :  0.10795668
Real values 143...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015443.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89205056  | Other :  0.10794947
Real values 144...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015372.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89303565  | Other :  0.10696433
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89378554  | Other :  0.106214456
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015445.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929128  | Other :  0.107087195
Real values 147...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015401.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89677286  | Other :  0.103227116
Real values 148...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015496.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919524  | Other :  0.108047634
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015483.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26c772c90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933887  | Other :  0.10661129
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Inception)*100))

Accuracy = 80.00%

4.2.2 Evaluating the Model

4.2.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Inception = []
for i in range(len(y_true_Inception)):
    y_true_2_Inception.append(y_true_Inception[i][0])

4.2.2.2 Re-ordering the Predicte y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Inception = []
for i in range(len(y_score_Inception)):
    y_score_2_Inception.append(y_score_Inception[i][0])

4.2.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Inception, y_score_2_Inception)

4.2.2.4 Confusion Matrix

4.2.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

4.2.2.4.2 Obtaining Labels

TRUE_POSITIVE_Inception, FALSE_POSITIVE_Inception, TRUE_NEGATIVE_Inception, FALSE_NEGATIVE_Inception = positive_negative_measurement(y_true_2_Inception, y_score_2_Inception)
postives_negatives_Inception = [[TRUE_POSITIVE_Inception, FALSE_POSITIVE_Inception], 
                                [FALSE_NEGATIVE_Inception, TRUE_NEGATIVE_Inception]]

sns.set()
labels_Inception =  np.array([['True positive: ' + str(TRUE_POSITIVE_Inception),
                     'False positive: ' + str(FALSE_POSITIVE_Inception)],
                    ['False negative: ' + str(FALSE_NEGATIVE_Inception),
                     'True negative: ' + str(TRUE_POSITIVE_Inception)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Inception, annot = labels_Inception, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb26a2af1d0>

4.2.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Inception = TRUE_POSITIVE_Inception / (TRUE_POSITIVE_Inception + FALSE_NEGATIVE_Inception)
print("Sensitivity: ", sensitivity_Inception)

Sensitivity:  1.0

4.2.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Inception = TRUE_NEGATIVE_Inception / (TRUE_NEGATIVE_Inception + FALSE_NEGATIVE_Inception)
    print("Specifity: ", specifity_Inception)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

4.2.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Inception = TRUE_POSITIVE_Inception / (TRUE_POSITIVE_Inception + FALSE_POSITIVE_Inception)
print("Precision: ", predcision_Inception)

Precision:  0.8

4.2.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Inception = TRUE_NEGATIVE_Inception / (TRUE_NEGATIVE_Inception + FALSE_NEGATIVE_Inception)
    print("Negative predictive value: ", npv_Inception)
except:
    print("0 Negative Predictions")

0 Negative Predictions

4.2.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Inception = (TRUE_POSITIVE_Inception + TRUE_NEGATIVE_Inception) / (TRUE_POSITIVE_Inception + FALSE_POSITIVE_Inception + TRUE_NEGATIVE_Inception + FALSE_NEGATIVE_Inception)
print("Accuracy: ", accuracy_Inception)

Accuracy:  0.8

4.3 Xception Architecture

4.3.1 Compute Test Set Predictions

# Compute test set predictions
#model_architecture,path_model_weight
NUMBER_TEST_SAMPLES_Xception = 150

xception_architecture_function = xception_architecture()
xception_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5"

y_true_Xception = valid_targets[:NUMBER_TEST_SAMPLES_Xception]
y_score_Xception = []
for index in range(NUMBER_TEST_SAMPLES_Xception): #compute one at a time due to memory constraints
    probs_Xception = predict(img_path = validation_files[index], model_architecture = xception_architecture_function, path_model_weight = xception_architecture_weight_path)
    print("Real values {}...".format(index+1) + "Melanoma : ", valid_targets[index][0], " | Other : ", valid_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Xception.append(probs_Xception)
    
correct_Xception = np.array(y_true_Xception) == np.array(y_score_Xception)

Model: "model_8"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_9 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_9[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_290 (Conv2D)             (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_290 (BatchN (None, 127, 127, 128 512         conv2d_290[0][0]                 
__________________________________________________________________________________________________
add_24 (Add)                    (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_290[0][0]    
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add_24[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_291 (Conv2D)             (None, 64, 64, 256)  32768       add_24[0][0]                     
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_291 (BatchN (None, 64, 64, 256)  1024        conv2d_291[0][0]                 
__________________________________________________________________________________________________
add_25 (Add)                    (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_291[0][0]    
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_25[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_292 (Conv2D)             (None, 32, 32, 728)  186368      add_25[0][0]                     
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_292 (BatchN (None, 32, 32, 728)  2912        conv2d_292[0][0]                 
__________________________________________________________________________________________________
add_26 (Add)                    (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_292[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_26[0][0]                     
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_27 (Add)                    (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_26[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_27[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_28 (Add)                    (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_27[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_28[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_29 (Add)                    (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_28[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_29[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_30 (Add)                    (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_29[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_30[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_31 (Add)                    (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_30[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_31[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_32 (Add)                    (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_31[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_32[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_33 (Add)                    (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_32[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_33[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_34 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_33[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_34[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_293 (Conv2D)             (None, 16, 16, 1024) 745472      add_34[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_293 (BatchN (None, 16, 16, 1024) 4096        conv2d_293[0][0]                 
__________________________________________________________________________________________________
add_35 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_293[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_35[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_8 (Glo (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_8 (Dense)                 (None, 2)            4098        global_average_pooling2d_8[0][0] 
==================================================================================================
Total params: 20,865,578
Trainable params: 20,811,050
Non-trainable params: 54,528
__________________________________________________________________________________________________
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0004337.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022141  | Other :  0.3977859
Real values 1...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022564  | Other :  0.39774355
Real values 2...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227776  | Other :  0.39772224
Real values 3...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003539.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225666  | Other :  0.39774337
Real values 4...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003805.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225546  | Other :  0.39774454
Real values 5...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023868  | Other :  0.39761323
Real values 6...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001852.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022431  | Other :  0.39775693
Real values 7...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003657.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022039  | Other :  0.39779612
Real values 8...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003462.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230684  | Other :  0.39769313
Real values 9...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001871.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023233  | Other :  0.39767668
Real values 10...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225713  | Other :  0.39774293
Real values 11...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023378  | Other :  0.39766222
Real values 12...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006914.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022177  | Other :  0.39778233
Real values 13...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007141.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022578  | Other :  0.39774224
Real values 14...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007344.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60224813  | Other :  0.3977519
Real values 15...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007235.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226387  | Other :  0.3977361
Real values 16...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022226  | Other :  0.39777744
Real values 17...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228115  | Other :  0.39771888
Real values 18...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008524.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023645  | Other :  0.39763552
Real values 19...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007528.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228735  | Other :  0.39771262
Real values 20...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024153  | Other :  0.39758468
Real values 21...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007332.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023483  | Other :  0.39765167
Real values 22...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006671.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022287  | Other :  0.3977713
Real values 23...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0010459.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022559  | Other :  0.39774415
Real values 24...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012099.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237217  | Other :  0.39762783
Real values 25...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012126.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023103  | Other :  0.39768967
Real values 26...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022362  | Other :  0.3977638
Real values 27...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0009995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022582  | Other :  0.3977418
Real values 28...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023121  | Other :  0.39768788
Real values 29...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012151.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230273  | Other :  0.39769727
Real values 30...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012204.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022773  | Other :  0.3977227
Real values 31...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012143.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226166  | Other :  0.3977383
Real values 32...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012191.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023646  | Other :  0.39763534
Real values 33...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012109.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023036  | Other :  0.39769632
Real values 34...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012159.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222644  | Other :  0.39777356
Real values 35...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221577  | Other :  0.39778423
Real values 36...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012316.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228705  | Other :  0.39771292
Real values 37...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012306.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221845  | Other :  0.39778158
Real values 38...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225713  | Other :  0.39774287
Real values 39...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022138  | Other :  0.39778626
Real values 40...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012380.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60236  | Other :  0.39763993
Real values 41...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022525  | Other :  0.39774752
Real values 42...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012222.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234267  | Other :  0.3976573
Real values 43...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012335.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024242  | Other :  0.39757577
Real values 44...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023074  | Other :  0.39769268
Real values 45...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021894  | Other :  0.39781055
Real values 46...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022885  | Other :  0.39771146
Real values 47...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022136  | Other :  0.3977864
Real values 48...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012210.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022291  | Other :  0.39777094
Real values 49...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023948  | Other :  0.39760515
Real values 50...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022666  | Other :  0.3977334
Real values 51...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023134  | Other :  0.39768663
Real values 52...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012538.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021995  | Other :  0.39780053
Real values 53...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012684.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023328  | Other :  0.39766726
Real values 54...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60219544  | Other :  0.3978046
Real values 55...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220927  | Other :  0.39779076
Real values 56...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012400.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022182  | Other :  0.39778185
Real values 57...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012547.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022297  | Other :  0.39777032
Real values 58...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023615  | Other :  0.39763853
Real values 59...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012492.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230774  | Other :  0.39769226
Real values 60...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012660.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237706  | Other :  0.3976229
Real values 61...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013082.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024366  | Other :  0.39756343
Real values 62...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022555  | Other :  0.39774448
Real values 63...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022762  | Other :  0.39772382
Real values 64...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013188.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60217285  | Other :  0.39782715
Real values 65...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244197  | Other :  0.397558
Real values 66...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60229546  | Other :  0.39770454
Real values 67...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60223794  | Other :  0.39776212
Real values 68...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022527  | Other :  0.39774728
Real values 69...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013104.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023462  | Other :  0.39765376
Real values 70...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013128.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221845  | Other :  0.39778158
Real values 71...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230285  | Other :  0.39769718
Real values 72...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013010.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218453  | Other :  0.39781547
Real values 73...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013491.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022964  | Other :  0.3977036
Real values 74...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013549.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022662  | Other :  0.39773384
Real values 75...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013562.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228235  | Other :  0.3977176
Real values 76...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013501.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60229415  | Other :  0.39770582
Real values 77...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225725  | Other :  0.39774275
Real values 78...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021744  | Other :  0.3978256
Real values 79...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013632.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023023  | Other :  0.39769766
Real values 80...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013561.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227144  | Other :  0.3977286
Real values 81...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013518.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021816  | Other :  0.39781833
Real values 82...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013527.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221213  | Other :  0.39778787
Real values 83...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013421.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222924  | Other :  0.39777076
Real values 84...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022079  | Other :  0.39779207
Real values 85...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013898.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602182  | Other :  0.397818
Real values 86...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013828.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240126  | Other :  0.39759874
Real values 87...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024171  | Other :  0.3975829
Real values 88...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022248  | Other :  0.3977751
Real values 89...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013702.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022871  | Other :  0.3977129
Real values 90...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230744  | Other :  0.39769253
Real values 91...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013736.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023806  | Other :  0.39761943
Real values 92...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228294  | Other :  0.39771706
Real values 93...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221255  | Other :  0.39778745
Real values 94...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225296  | Other :  0.397747
Real values 95...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013793.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023038  | Other :  0.3976962
Real values 96...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022359  | Other :  0.39776412
Real values 97...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022488  | Other :  0.39775118
Real values 98...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014428.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022954  | Other :  0.39770454
Real values 99...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014178.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022061  | Other :  0.39779386
Real values 100...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014382.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022748  | Other :  0.39772528
Real values 101...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021951  | Other :  0.39780492
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60231185  | Other :  0.39768812
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014302.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022314  | Other :  0.39776862
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021876  | Other :  0.39781243
Real values 105...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022227  | Other :  0.39777735
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014162.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239774  | Other :  0.39760226
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014618.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235286  | Other :  0.3976471
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014610.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022989  | Other :  0.39770108
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014601.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239637  | Other :  0.39760363
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014620.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235995  | Other :  0.39764008
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014616.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237217  | Other :  0.3976278
Real values 112...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014623.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238904  | Other :  0.397611
Real values 113...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014572.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240954  | Other :  0.39759052
Real values 114...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014558.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022098  | Other :  0.3977902
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014624.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023409  | Other :  0.39765912
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014633.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022799  | Other :  0.3977201
Real values 117...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014597.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60232186  | Other :  0.39767808
Real values 118...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014608.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024174  | Other :  0.39758265
Real values 119...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014611.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024472  | Other :  0.3975528
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235095  | Other :  0.39764905
Real values 121...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014829.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024029  | Other :  0.39759701
Real values 122...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014635.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023231  | Other :  0.39767686
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014857.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023373  | Other :  0.39766276
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014931.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60264444  | Other :  0.39735556
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241127  | Other :  0.39758876
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238445  | Other :  0.39761552
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014712.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024223  | Other :  0.3975777
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014688.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241646  | Other :  0.39758354
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024663  | Other :  0.39753368
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241383  | Other :  0.3975862
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023683  | Other :  0.3976317
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024523  | Other :  0.39754778
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60242295  | Other :  0.39757708
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025727  | Other :  0.39742738
Real values 135...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015124.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026055  | Other :  0.39739448
Real values 136...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015243.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024035  | Other :  0.39759645
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015144.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250777  | Other :  0.39749223
Real values 138...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023954  | Other :  0.39760458
Real values 139...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602523  | Other :  0.39747697
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023913  | Other :  0.3976087
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254866  | Other :  0.39745128
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025106  | Other :  0.39748937
Real values 143...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015443.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60231453  | Other :  0.3976855
Real values 144...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015372.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60252905  | Other :  0.39747098
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025266  | Other :  0.3974734
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015445.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024331  | Other :  0.3975669
Real values 147...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015401.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240436  | Other :  0.39759564
Real values 148...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015496.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60271674  | Other :  0.3972833
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015483.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb37808c6d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023833  | Other :  0.39761668
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Xception)*100))

Accuracy = 80.00%

4.3.2 Evaluating the Model

4.3.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Xception = []
for i in range(len(y_true_Xception)):
    y_true_2_Xception.append(y_true_Xception[i][0])

4.3.2.2 Re-ordering the Predict y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Xception = []
for i in range(len(y_score_Xception)):
    y_score_2_Xception.append(y_score_Xception[i][0])

4.3.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Xception, y_score_2_Xception)

4.3.2.4 Confusion Matrix

4.3.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_Xception, FALSE_POSITIVE_Xception, TRUE_NEGATIVE_Xception, FALSE_NEGATIVE_Xception = positive_negative_measurement(y_true_2_Xception, y_score_2_Xception)
postives_negatives_Xception = [[TRUE_POSITIVE_Xception, FALSE_POSITIVE_Xception], 
                                [FALSE_NEGATIVE_Xception, TRUE_NEGATIVE_Xception]]

4.3.2.4.2 Obtaining the Labels

sns.set()
labels_Xception =  np.array([['True positive: ' + str(TRUE_POSITIVE_Xception),
                     'False positive: ' + str(FALSE_POSITIVE_Xception)],
                    ['False negative: ' + str(FALSE_NEGATIVE_Xception),
                     'True negative: ' + str(TRUE_POSITIVE_Xception)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Xception, annot = labels_Xception, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb379485950>

4.3.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Xception = TRUE_POSITIVE_Xception / (TRUE_POSITIVE_Xception + FALSE_NEGATIVE_Xception)
print("Sensitivity: ", sensitivity_Xception)

Sensitivity:  1.0

4.3.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Xception = TRUE_NEGATIVE_Xception / (TRUE_NEGATIVE_Xception + FALSE_NEGATIVE_Xception)
    print("Specifity: ", specifity_Xception)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

4.3.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Xception = TRUE_POSITIVE_Xception / (TRUE_POSITIVE_Xception + FALSE_POSITIVE_Xception)
print("Precision: ", predcision_Xception)

Precision:  0.8

4.3.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Xception = TRUE_NEGATIVE_Xception / (TRUE_NEGATIVE_Xception + FALSE_NEGATIVE_Xception)
    print("Negative predictive value: ", npv_Xception)
except:
    print("0 Negative Predictions")

0 Negative Predictions

4.3.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Xception = (TRUE_POSITIVE_Xception + TRUE_NEGATIVE_Xception) / (TRUE_POSITIVE_Xception + FALSE_POSITIVE_Xception + TRUE_NEGATIVE_Xception + FALSE_NEGATIVE_Xception)
print("Accuracy: ", accuracy_Xception)

Accuracy:  0.8

5. Evaluating the Models Together on Validation Data - Ensembling the models

Working Flowchart:

5.1 Defining the Input Shape

# Single input for multiple models
model_input = Input(shape=(512, 512, 3))

5.2 Defining all the Models

def mobilenet_architecture():
    """
    Pre-build architecture of mobilenet for our dataset.
    """
    # Imprting the model
    from keras.applications.mobilenet import MobileNet

    # Pre-build model
    base_model = MobileNet(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    mobilenet_model = Model(base_model.input, output)
    
    # Getting the summary of architecture
    mobilenet_model.summary()
    
    # Compiling the model
    mobilenet_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])

    return mobilenet_model

# Model 1
mobilenet_model = mobilenet_architecture()
mobilenet_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5")

Model: "model_9"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_10 (InputLayer)        [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d_9 ( (None, 1024)              0         
_________________________________________________________________
dense_9 (Dense)              (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________

def inception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model 
    from keras.applications.inception_v3 import InceptionV3

    # Pre-build model
    base_model = InceptionV3(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    inception_model = Model(base_model.input, output)
    
    # Summary of the model
    inception_model.summary()
    
    # Compiling the model
    inception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])
    
    return inception_model

# Model 2
inception_model = inception_architecture()
inception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5")

Model: "model_10"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_10 (InputLayer)           [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_294 (Conv2D)             (None, 255, 255, 32) 864         input_10[0][0]                   
__________________________________________________________________________________________________
batch_normalization_294 (BatchN (None, 255, 255, 32) 96          conv2d_294[0][0]                 
__________________________________________________________________________________________________
activation_282 (Activation)     (None, 255, 255, 32) 0           batch_normalization_294[0][0]    
__________________________________________________________________________________________________
conv2d_295 (Conv2D)             (None, 253, 253, 32) 9216        activation_282[0][0]             
__________________________________________________________________________________________________
batch_normalization_295 (BatchN (None, 253, 253, 32) 96          conv2d_295[0][0]                 
__________________________________________________________________________________________________
activation_283 (Activation)     (None, 253, 253, 32) 0           batch_normalization_295[0][0]    
__________________________________________________________________________________________________
conv2d_296 (Conv2D)             (None, 253, 253, 64) 18432       activation_283[0][0]             
__________________________________________________________________________________________________
batch_normalization_296 (BatchN (None, 253, 253, 64) 192         conv2d_296[0][0]                 
__________________________________________________________________________________________________
activation_284 (Activation)     (None, 253, 253, 64) 0           batch_normalization_296[0][0]    
__________________________________________________________________________________________________
max_pooling2d_12 (MaxPooling2D) (None, 126, 126, 64) 0           activation_284[0][0]             
__________________________________________________________________________________________________
conv2d_297 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_12[0][0]           
__________________________________________________________________________________________________
batch_normalization_297 (BatchN (None, 126, 126, 80) 240         conv2d_297[0][0]                 
__________________________________________________________________________________________________
activation_285 (Activation)     (None, 126, 126, 80) 0           batch_normalization_297[0][0]    
__________________________________________________________________________________________________
conv2d_298 (Conv2D)             (None, 124, 124, 192 138240      activation_285[0][0]             
__________________________________________________________________________________________________
batch_normalization_298 (BatchN (None, 124, 124, 192 576         conv2d_298[0][0]                 
__________________________________________________________________________________________________
activation_286 (Activation)     (None, 124, 124, 192 0           batch_normalization_298[0][0]    
__________________________________________________________________________________________________
max_pooling2d_13 (MaxPooling2D) (None, 61, 61, 192)  0           activation_286[0][0]             
__________________________________________________________________________________________________
conv2d_302 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
batch_normalization_302 (BatchN (None, 61, 61, 64)   192         conv2d_302[0][0]                 
__________________________________________________________________________________________________
activation_290 (Activation)     (None, 61, 61, 64)   0           batch_normalization_302[0][0]    
__________________________________________________________________________________________________
conv2d_300 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
conv2d_303 (Conv2D)             (None, 61, 61, 96)   55296       activation_290[0][0]             
__________________________________________________________________________________________________
batch_normalization_300 (BatchN (None, 61, 61, 48)   144         conv2d_300[0][0]                 
__________________________________________________________________________________________________
batch_normalization_303 (BatchN (None, 61, 61, 96)   288         conv2d_303[0][0]                 
__________________________________________________________________________________________________
activation_288 (Activation)     (None, 61, 61, 48)   0           batch_normalization_300[0][0]    
__________________________________________________________________________________________________
activation_291 (Activation)     (None, 61, 61, 96)   0           batch_normalization_303[0][0]    
__________________________________________________________________________________________________
average_pooling2d_27 (AveragePo (None, 61, 61, 192)  0           max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
conv2d_299 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
conv2d_301 (Conv2D)             (None, 61, 61, 64)   76800       activation_288[0][0]             
__________________________________________________________________________________________________
conv2d_304 (Conv2D)             (None, 61, 61, 96)   82944       activation_291[0][0]             
__________________________________________________________________________________________________
conv2d_305 (Conv2D)             (None, 61, 61, 32)   6144        average_pooling2d_27[0][0]       
__________________________________________________________________________________________________
batch_normalization_299 (BatchN (None, 61, 61, 64)   192         conv2d_299[0][0]                 
__________________________________________________________________________________________________
batch_normalization_301 (BatchN (None, 61, 61, 64)   192         conv2d_301[0][0]                 
__________________________________________________________________________________________________
batch_normalization_304 (BatchN (None, 61, 61, 96)   288         conv2d_304[0][0]                 
__________________________________________________________________________________________________
batch_normalization_305 (BatchN (None, 61, 61, 32)   96          conv2d_305[0][0]                 
__________________________________________________________________________________________________
activation_287 (Activation)     (None, 61, 61, 64)   0           batch_normalization_299[0][0]    
__________________________________________________________________________________________________
activation_289 (Activation)     (None, 61, 61, 64)   0           batch_normalization_301[0][0]    
__________________________________________________________________________________________________
activation_292 (Activation)     (None, 61, 61, 96)   0           batch_normalization_304[0][0]    
__________________________________________________________________________________________________
activation_293 (Activation)     (None, 61, 61, 32)   0           batch_normalization_305[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_287[0][0]             
                                                                 activation_289[0][0]             
                                                                 activation_292[0][0]             
                                                                 activation_293[0][0]             
__________________________________________________________________________________________________
conv2d_309 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_309 (BatchN (None, 61, 61, 64)   192         conv2d_309[0][0]                 
__________________________________________________________________________________________________
activation_297 (Activation)     (None, 61, 61, 64)   0           batch_normalization_309[0][0]    
__________________________________________________________________________________________________
conv2d_307 (Conv2D)             (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_310 (Conv2D)             (None, 61, 61, 96)   55296       activation_297[0][0]             
__________________________________________________________________________________________________
batch_normalization_307 (BatchN (None, 61, 61, 48)   144         conv2d_307[0][0]                 
__________________________________________________________________________________________________
batch_normalization_310 (BatchN (None, 61, 61, 96)   288         conv2d_310[0][0]                 
__________________________________________________________________________________________________
activation_295 (Activation)     (None, 61, 61, 48)   0           batch_normalization_307[0][0]    
__________________________________________________________________________________________________
activation_298 (Activation)     (None, 61, 61, 96)   0           batch_normalization_310[0][0]    
__________________________________________________________________________________________________
average_pooling2d_28 (AveragePo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_306 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_308 (Conv2D)             (None, 61, 61, 64)   76800       activation_295[0][0]             
__________________________________________________________________________________________________
conv2d_311 (Conv2D)             (None, 61, 61, 96)   82944       activation_298[0][0]             
__________________________________________________________________________________________________
conv2d_312 (Conv2D)             (None, 61, 61, 64)   16384       average_pooling2d_28[0][0]       
__________________________________________________________________________________________________
batch_normalization_306 (BatchN (None, 61, 61, 64)   192         conv2d_306[0][0]                 
__________________________________________________________________________________________________
batch_normalization_308 (BatchN (None, 61, 61, 64)   192         conv2d_308[0][0]                 
__________________________________________________________________________________________________
batch_normalization_311 (BatchN (None, 61, 61, 96)   288         conv2d_311[0][0]                 
__________________________________________________________________________________________________
batch_normalization_312 (BatchN (None, 61, 61, 64)   192         conv2d_312[0][0]                 
__________________________________________________________________________________________________
activation_294 (Activation)     (None, 61, 61, 64)   0           batch_normalization_306[0][0]    
__________________________________________________________________________________________________
activation_296 (Activation)     (None, 61, 61, 64)   0           batch_normalization_308[0][0]    
__________________________________________________________________________________________________
activation_299 (Activation)     (None, 61, 61, 96)   0           batch_normalization_311[0][0]    
__________________________________________________________________________________________________
activation_300 (Activation)     (None, 61, 61, 64)   0           batch_normalization_312[0][0]    
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_294[0][0]             
                                                                 activation_296[0][0]             
                                                                 activation_299[0][0]             
                                                                 activation_300[0][0]             
__________________________________________________________________________________________________
conv2d_316 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_316 (BatchN (None, 61, 61, 64)   192         conv2d_316[0][0]                 
__________________________________________________________________________________________________
activation_304 (Activation)     (None, 61, 61, 64)   0           batch_normalization_316[0][0]    
__________________________________________________________________________________________________
conv2d_314 (Conv2D)             (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_317 (Conv2D)             (None, 61, 61, 96)   55296       activation_304[0][0]             
__________________________________________________________________________________________________
batch_normalization_314 (BatchN (None, 61, 61, 48)   144         conv2d_314[0][0]                 
__________________________________________________________________________________________________
batch_normalization_317 (BatchN (None, 61, 61, 96)   288         conv2d_317[0][0]                 
__________________________________________________________________________________________________
activation_302 (Activation)     (None, 61, 61, 48)   0           batch_normalization_314[0][0]    
__________________________________________________________________________________________________
activation_305 (Activation)     (None, 61, 61, 96)   0           batch_normalization_317[0][0]    
__________________________________________________________________________________________________
average_pooling2d_29 (AveragePo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_313 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_315 (Conv2D)             (None, 61, 61, 64)   76800       activation_302[0][0]             
__________________________________________________________________________________________________
conv2d_318 (Conv2D)             (None, 61, 61, 96)   82944       activation_305[0][0]             
__________________________________________________________________________________________________
conv2d_319 (Conv2D)             (None, 61, 61, 64)   18432       average_pooling2d_29[0][0]       
__________________________________________________________________________________________________
batch_normalization_313 (BatchN (None, 61, 61, 64)   192         conv2d_313[0][0]                 
__________________________________________________________________________________________________
batch_normalization_315 (BatchN (None, 61, 61, 64)   192         conv2d_315[0][0]                 
__________________________________________________________________________________________________
batch_normalization_318 (BatchN (None, 61, 61, 96)   288         conv2d_318[0][0]                 
__________________________________________________________________________________________________
batch_normalization_319 (BatchN (None, 61, 61, 64)   192         conv2d_319[0][0]                 
__________________________________________________________________________________________________
activation_301 (Activation)     (None, 61, 61, 64)   0           batch_normalization_313[0][0]    
__________________________________________________________________________________________________
activation_303 (Activation)     (None, 61, 61, 64)   0           batch_normalization_315[0][0]    
__________________________________________________________________________________________________
activation_306 (Activation)     (None, 61, 61, 96)   0           batch_normalization_318[0][0]    
__________________________________________________________________________________________________
activation_307 (Activation)     (None, 61, 61, 64)   0           batch_normalization_319[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_301[0][0]             
                                                                 activation_303[0][0]             
                                                                 activation_306[0][0]             
                                                                 activation_307[0][0]             
__________________________________________________________________________________________________
conv2d_321 (Conv2D)             (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_321 (BatchN (None, 61, 61, 64)   192         conv2d_321[0][0]                 
__________________________________________________________________________________________________
activation_309 (Activation)     (None, 61, 61, 64)   0           batch_normalization_321[0][0]    
__________________________________________________________________________________________________
conv2d_322 (Conv2D)             (None, 61, 61, 96)   55296       activation_309[0][0]             
__________________________________________________________________________________________________
batch_normalization_322 (BatchN (None, 61, 61, 96)   288         conv2d_322[0][0]                 
__________________________________________________________________________________________________
activation_310 (Activation)     (None, 61, 61, 96)   0           batch_normalization_322[0][0]    
__________________________________________________________________________________________________
conv2d_320 (Conv2D)             (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_323 (Conv2D)             (None, 30, 30, 96)   82944       activation_310[0][0]             
__________________________________________________________________________________________________
batch_normalization_320 (BatchN (None, 30, 30, 384)  1152        conv2d_320[0][0]                 
__________________________________________________________________________________________________
batch_normalization_323 (BatchN (None, 30, 30, 96)   288         conv2d_323[0][0]                 
__________________________________________________________________________________________________
activation_308 (Activation)     (None, 30, 30, 384)  0           batch_normalization_320[0][0]    
__________________________________________________________________________________________________
activation_311 (Activation)     (None, 30, 30, 96)   0           batch_normalization_323[0][0]    
__________________________________________________________________________________________________
max_pooling2d_14 (MaxPooling2D) (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_308[0][0]             
                                                                 activation_311[0][0]             
                                                                 max_pooling2d_14[0][0]           
__________________________________________________________________________________________________
conv2d_328 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_328 (BatchN (None, 30, 30, 128)  384         conv2d_328[0][0]                 
__________________________________________________________________________________________________
activation_316 (Activation)     (None, 30, 30, 128)  0           batch_normalization_328[0][0]    
__________________________________________________________________________________________________
conv2d_329 (Conv2D)             (None, 30, 30, 128)  114688      activation_316[0][0]             
__________________________________________________________________________________________________
batch_normalization_329 (BatchN (None, 30, 30, 128)  384         conv2d_329[0][0]                 
__________________________________________________________________________________________________
activation_317 (Activation)     (None, 30, 30, 128)  0           batch_normalization_329[0][0]    
__________________________________________________________________________________________________
conv2d_325 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_330 (Conv2D)             (None, 30, 30, 128)  114688      activation_317[0][0]             
__________________________________________________________________________________________________
batch_normalization_325 (BatchN (None, 30, 30, 128)  384         conv2d_325[0][0]                 
__________________________________________________________________________________________________
batch_normalization_330 (BatchN (None, 30, 30, 128)  384         conv2d_330[0][0]                 
__________________________________________________________________________________________________
activation_313 (Activation)     (None, 30, 30, 128)  0           batch_normalization_325[0][0]    
__________________________________________________________________________________________________
activation_318 (Activation)     (None, 30, 30, 128)  0           batch_normalization_330[0][0]    
__________________________________________________________________________________________________
conv2d_326 (Conv2D)             (None, 30, 30, 128)  114688      activation_313[0][0]             
__________________________________________________________________________________________________
conv2d_331 (Conv2D)             (None, 30, 30, 128)  114688      activation_318[0][0]             
__________________________________________________________________________________________________
batch_normalization_326 (BatchN (None, 30, 30, 128)  384         conv2d_326[0][0]                 
__________________________________________________________________________________________________
batch_normalization_331 (BatchN (None, 30, 30, 128)  384         conv2d_331[0][0]                 
__________________________________________________________________________________________________
activation_314 (Activation)     (None, 30, 30, 128)  0           batch_normalization_326[0][0]    
__________________________________________________________________________________________________
activation_319 (Activation)     (None, 30, 30, 128)  0           batch_normalization_331[0][0]    
__________________________________________________________________________________________________
average_pooling2d_30 (AveragePo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_324 (Conv2D)             (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_327 (Conv2D)             (None, 30, 30, 192)  172032      activation_314[0][0]             
__________________________________________________________________________________________________
conv2d_332 (Conv2D)             (None, 30, 30, 192)  172032      activation_319[0][0]             
__________________________________________________________________________________________________
conv2d_333 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_30[0][0]       
__________________________________________________________________________________________________
batch_normalization_324 (BatchN (None, 30, 30, 192)  576         conv2d_324[0][0]                 
__________________________________________________________________________________________________
batch_normalization_327 (BatchN (None, 30, 30, 192)  576         conv2d_327[0][0]                 
__________________________________________________________________________________________________
batch_normalization_332 (BatchN (None, 30, 30, 192)  576         conv2d_332[0][0]                 
__________________________________________________________________________________________________
batch_normalization_333 (BatchN (None, 30, 30, 192)  576         conv2d_333[0][0]                 
__________________________________________________________________________________________________
activation_312 (Activation)     (None, 30, 30, 192)  0           batch_normalization_324[0][0]    
__________________________________________________________________________________________________
activation_315 (Activation)     (None, 30, 30, 192)  0           batch_normalization_327[0][0]    
__________________________________________________________________________________________________
activation_320 (Activation)     (None, 30, 30, 192)  0           batch_normalization_332[0][0]    
__________________________________________________________________________________________________
activation_321 (Activation)     (None, 30, 30, 192)  0           batch_normalization_333[0][0]    
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_312[0][0]             
                                                                 activation_315[0][0]             
                                                                 activation_320[0][0]             
                                                                 activation_321[0][0]             
__________________________________________________________________________________________________
conv2d_338 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_338 (BatchN (None, 30, 30, 160)  480         conv2d_338[0][0]                 
__________________________________________________________________________________________________
activation_326 (Activation)     (None, 30, 30, 160)  0           batch_normalization_338[0][0]    
__________________________________________________________________________________________________
conv2d_339 (Conv2D)             (None, 30, 30, 160)  179200      activation_326[0][0]             
__________________________________________________________________________________________________
batch_normalization_339 (BatchN (None, 30, 30, 160)  480         conv2d_339[0][0]                 
__________________________________________________________________________________________________
activation_327 (Activation)     (None, 30, 30, 160)  0           batch_normalization_339[0][0]    
__________________________________________________________________________________________________
conv2d_335 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_340 (Conv2D)             (None, 30, 30, 160)  179200      activation_327[0][0]             
__________________________________________________________________________________________________
batch_normalization_335 (BatchN (None, 30, 30, 160)  480         conv2d_335[0][0]                 
__________________________________________________________________________________________________
batch_normalization_340 (BatchN (None, 30, 30, 160)  480         conv2d_340[0][0]                 
__________________________________________________________________________________________________
activation_323 (Activation)     (None, 30, 30, 160)  0           batch_normalization_335[0][0]    
__________________________________________________________________________________________________
activation_328 (Activation)     (None, 30, 30, 160)  0           batch_normalization_340[0][0]    
__________________________________________________________________________________________________
conv2d_336 (Conv2D)             (None, 30, 30, 160)  179200      activation_323[0][0]             
__________________________________________________________________________________________________
conv2d_341 (Conv2D)             (None, 30, 30, 160)  179200      activation_328[0][0]             
__________________________________________________________________________________________________
batch_normalization_336 (BatchN (None, 30, 30, 160)  480         conv2d_336[0][0]                 
__________________________________________________________________________________________________
batch_normalization_341 (BatchN (None, 30, 30, 160)  480         conv2d_341[0][0]                 
__________________________________________________________________________________________________
activation_324 (Activation)     (None, 30, 30, 160)  0           batch_normalization_336[0][0]    
__________________________________________________________________________________________________
activation_329 (Activation)     (None, 30, 30, 160)  0           batch_normalization_341[0][0]    
__________________________________________________________________________________________________
average_pooling2d_31 (AveragePo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_334 (Conv2D)             (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_337 (Conv2D)             (None, 30, 30, 192)  215040      activation_324[0][0]             
__________________________________________________________________________________________________
conv2d_342 (Conv2D)             (None, 30, 30, 192)  215040      activation_329[0][0]             
__________________________________________________________________________________________________
conv2d_343 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_31[0][0]       
__________________________________________________________________________________________________
batch_normalization_334 (BatchN (None, 30, 30, 192)  576         conv2d_334[0][0]                 
__________________________________________________________________________________________________
batch_normalization_337 (BatchN (None, 30, 30, 192)  576         conv2d_337[0][0]                 
__________________________________________________________________________________________________
batch_normalization_342 (BatchN (None, 30, 30, 192)  576         conv2d_342[0][0]                 
__________________________________________________________________________________________________
batch_normalization_343 (BatchN (None, 30, 30, 192)  576         conv2d_343[0][0]                 
__________________________________________________________________________________________________
activation_322 (Activation)     (None, 30, 30, 192)  0           batch_normalization_334[0][0]    
__________________________________________________________________________________________________
activation_325 (Activation)     (None, 30, 30, 192)  0           batch_normalization_337[0][0]    
__________________________________________________________________________________________________
activation_330 (Activation)     (None, 30, 30, 192)  0           batch_normalization_342[0][0]    
__________________________________________________________________________________________________
activation_331 (Activation)     (None, 30, 30, 192)  0           batch_normalization_343[0][0]    
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_322[0][0]             
                                                                 activation_325[0][0]             
                                                                 activation_330[0][0]             
                                                                 activation_331[0][0]             
__________________________________________________________________________________________________
conv2d_348 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_348 (BatchN (None, 30, 30, 160)  480         conv2d_348[0][0]                 
__________________________________________________________________________________________________
activation_336 (Activation)     (None, 30, 30, 160)  0           batch_normalization_348[0][0]    
__________________________________________________________________________________________________
conv2d_349 (Conv2D)             (None, 30, 30, 160)  179200      activation_336[0][0]             
__________________________________________________________________________________________________
batch_normalization_349 (BatchN (None, 30, 30, 160)  480         conv2d_349[0][0]                 
__________________________________________________________________________________________________
activation_337 (Activation)     (None, 30, 30, 160)  0           batch_normalization_349[0][0]    
__________________________________________________________________________________________________
conv2d_345 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_350 (Conv2D)             (None, 30, 30, 160)  179200      activation_337[0][0]             
__________________________________________________________________________________________________
batch_normalization_345 (BatchN (None, 30, 30, 160)  480         conv2d_345[0][0]                 
__________________________________________________________________________________________________
batch_normalization_350 (BatchN (None, 30, 30, 160)  480         conv2d_350[0][0]                 
__________________________________________________________________________________________________
activation_333 (Activation)     (None, 30, 30, 160)  0           batch_normalization_345[0][0]    
__________________________________________________________________________________________________
activation_338 (Activation)     (None, 30, 30, 160)  0           batch_normalization_350[0][0]    
__________________________________________________________________________________________________
conv2d_346 (Conv2D)             (None, 30, 30, 160)  179200      activation_333[0][0]             
__________________________________________________________________________________________________
conv2d_351 (Conv2D)             (None, 30, 30, 160)  179200      activation_338[0][0]             
__________________________________________________________________________________________________
batch_normalization_346 (BatchN (None, 30, 30, 160)  480         conv2d_346[0][0]                 
__________________________________________________________________________________________________
batch_normalization_351 (BatchN (None, 30, 30, 160)  480         conv2d_351[0][0]                 
__________________________________________________________________________________________________
activation_334 (Activation)     (None, 30, 30, 160)  0           batch_normalization_346[0][0]    
__________________________________________________________________________________________________
activation_339 (Activation)     (None, 30, 30, 160)  0           batch_normalization_351[0][0]    
__________________________________________________________________________________________________
average_pooling2d_32 (AveragePo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_344 (Conv2D)             (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_347 (Conv2D)             (None, 30, 30, 192)  215040      activation_334[0][0]             
__________________________________________________________________________________________________
conv2d_352 (Conv2D)             (None, 30, 30, 192)  215040      activation_339[0][0]             
__________________________________________________________________________________________________
conv2d_353 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_32[0][0]       
__________________________________________________________________________________________________
batch_normalization_344 (BatchN (None, 30, 30, 192)  576         conv2d_344[0][0]                 
__________________________________________________________________________________________________
batch_normalization_347 (BatchN (None, 30, 30, 192)  576         conv2d_347[0][0]                 
__________________________________________________________________________________________________
batch_normalization_352 (BatchN (None, 30, 30, 192)  576         conv2d_352[0][0]                 
__________________________________________________________________________________________________
batch_normalization_353 (BatchN (None, 30, 30, 192)  576         conv2d_353[0][0]                 
__________________________________________________________________________________________________
activation_332 (Activation)     (None, 30, 30, 192)  0           batch_normalization_344[0][0]    
__________________________________________________________________________________________________
activation_335 (Activation)     (None, 30, 30, 192)  0           batch_normalization_347[0][0]    
__________________________________________________________________________________________________
activation_340 (Activation)     (None, 30, 30, 192)  0           batch_normalization_352[0][0]    
__________________________________________________________________________________________________
activation_341 (Activation)     (None, 30, 30, 192)  0           batch_normalization_353[0][0]    
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_332[0][0]             
                                                                 activation_335[0][0]             
                                                                 activation_340[0][0]             
                                                                 activation_341[0][0]             
__________________________________________________________________________________________________
conv2d_358 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_358 (BatchN (None, 30, 30, 192)  576         conv2d_358[0][0]                 
__________________________________________________________________________________________________
activation_346 (Activation)     (None, 30, 30, 192)  0           batch_normalization_358[0][0]    
__________________________________________________________________________________________________
conv2d_359 (Conv2D)             (None, 30, 30, 192)  258048      activation_346[0][0]             
__________________________________________________________________________________________________
batch_normalization_359 (BatchN (None, 30, 30, 192)  576         conv2d_359[0][0]                 
__________________________________________________________________________________________________
activation_347 (Activation)     (None, 30, 30, 192)  0           batch_normalization_359[0][0]    
__________________________________________________________________________________________________
conv2d_355 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_360 (Conv2D)             (None, 30, 30, 192)  258048      activation_347[0][0]             
__________________________________________________________________________________________________
batch_normalization_355 (BatchN (None, 30, 30, 192)  576         conv2d_355[0][0]                 
__________________________________________________________________________________________________
batch_normalization_360 (BatchN (None, 30, 30, 192)  576         conv2d_360[0][0]                 
__________________________________________________________________________________________________
activation_343 (Activation)     (None, 30, 30, 192)  0           batch_normalization_355[0][0]    
__________________________________________________________________________________________________
activation_348 (Activation)     (None, 30, 30, 192)  0           batch_normalization_360[0][0]    
__________________________________________________________________________________________________
conv2d_356 (Conv2D)             (None, 30, 30, 192)  258048      activation_343[0][0]             
__________________________________________________________________________________________________
conv2d_361 (Conv2D)             (None, 30, 30, 192)  258048      activation_348[0][0]             
__________________________________________________________________________________________________
batch_normalization_356 (BatchN (None, 30, 30, 192)  576         conv2d_356[0][0]                 
__________________________________________________________________________________________________
batch_normalization_361 (BatchN (None, 30, 30, 192)  576         conv2d_361[0][0]                 
__________________________________________________________________________________________________
activation_344 (Activation)     (None, 30, 30, 192)  0           batch_normalization_356[0][0]    
__________________________________________________________________________________________________
activation_349 (Activation)     (None, 30, 30, 192)  0           batch_normalization_361[0][0]    
__________________________________________________________________________________________________
average_pooling2d_33 (AveragePo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_354 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_357 (Conv2D)             (None, 30, 30, 192)  258048      activation_344[0][0]             
__________________________________________________________________________________________________
conv2d_362 (Conv2D)             (None, 30, 30, 192)  258048      activation_349[0][0]             
__________________________________________________________________________________________________
conv2d_363 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_33[0][0]       
__________________________________________________________________________________________________
batch_normalization_354 (BatchN (None, 30, 30, 192)  576         conv2d_354[0][0]                 
__________________________________________________________________________________________________
batch_normalization_357 (BatchN (None, 30, 30, 192)  576         conv2d_357[0][0]                 
__________________________________________________________________________________________________
batch_normalization_362 (BatchN (None, 30, 30, 192)  576         conv2d_362[0][0]                 
__________________________________________________________________________________________________
batch_normalization_363 (BatchN (None, 30, 30, 192)  576         conv2d_363[0][0]                 
__________________________________________________________________________________________________
activation_342 (Activation)     (None, 30, 30, 192)  0           batch_normalization_354[0][0]    
__________________________________________________________________________________________________
activation_345 (Activation)     (None, 30, 30, 192)  0           batch_normalization_357[0][0]    
__________________________________________________________________________________________________
activation_350 (Activation)     (None, 30, 30, 192)  0           batch_normalization_362[0][0]    
__________________________________________________________________________________________________
activation_351 (Activation)     (None, 30, 30, 192)  0           batch_normalization_363[0][0]    
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_342[0][0]             
                                                                 activation_345[0][0]             
                                                                 activation_350[0][0]             
                                                                 activation_351[0][0]             
__________________________________________________________________________________________________
conv2d_366 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_366 (BatchN (None, 30, 30, 192)  576         conv2d_366[0][0]                 
__________________________________________________________________________________________________
activation_354 (Activation)     (None, 30, 30, 192)  0           batch_normalization_366[0][0]    
__________________________________________________________________________________________________
conv2d_367 (Conv2D)             (None, 30, 30, 192)  258048      activation_354[0][0]             
__________________________________________________________________________________________________
batch_normalization_367 (BatchN (None, 30, 30, 192)  576         conv2d_367[0][0]                 
__________________________________________________________________________________________________
activation_355 (Activation)     (None, 30, 30, 192)  0           batch_normalization_367[0][0]    
__________________________________________________________________________________________________
conv2d_364 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_368 (Conv2D)             (None, 30, 30, 192)  258048      activation_355[0][0]             
__________________________________________________________________________________________________
batch_normalization_364 (BatchN (None, 30, 30, 192)  576         conv2d_364[0][0]                 
__________________________________________________________________________________________________
batch_normalization_368 (BatchN (None, 30, 30, 192)  576         conv2d_368[0][0]                 
__________________________________________________________________________________________________
activation_352 (Activation)     (None, 30, 30, 192)  0           batch_normalization_364[0][0]    
__________________________________________________________________________________________________
activation_356 (Activation)     (None, 30, 30, 192)  0           batch_normalization_368[0][0]    
__________________________________________________________________________________________________
conv2d_365 (Conv2D)             (None, 14, 14, 320)  552960      activation_352[0][0]             
__________________________________________________________________________________________________
conv2d_369 (Conv2D)             (None, 14, 14, 192)  331776      activation_356[0][0]             
__________________________________________________________________________________________________
batch_normalization_365 (BatchN (None, 14, 14, 320)  960         conv2d_365[0][0]                 
__________________________________________________________________________________________________
batch_normalization_369 (BatchN (None, 14, 14, 192)  576         conv2d_369[0][0]                 
__________________________________________________________________________________________________
activation_353 (Activation)     (None, 14, 14, 320)  0           batch_normalization_365[0][0]    
__________________________________________________________________________________________________
activation_357 (Activation)     (None, 14, 14, 192)  0           batch_normalization_369[0][0]    
__________________________________________________________________________________________________
max_pooling2d_15 (MaxPooling2D) (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_353[0][0]             
                                                                 activation_357[0][0]             
                                                                 max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
conv2d_374 (Conv2D)             (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_374 (BatchN (None, 14, 14, 448)  1344        conv2d_374[0][0]                 
__________________________________________________________________________________________________
activation_362 (Activation)     (None, 14, 14, 448)  0           batch_normalization_374[0][0]    
__________________________________________________________________________________________________
conv2d_371 (Conv2D)             (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_375 (Conv2D)             (None, 14, 14, 384)  1548288     activation_362[0][0]             
__________________________________________________________________________________________________
batch_normalization_371 (BatchN (None, 14, 14, 384)  1152        conv2d_371[0][0]                 
__________________________________________________________________________________________________
batch_normalization_375 (BatchN (None, 14, 14, 384)  1152        conv2d_375[0][0]                 
__________________________________________________________________________________________________
activation_359 (Activation)     (None, 14, 14, 384)  0           batch_normalization_371[0][0]    
__________________________________________________________________________________________________
activation_363 (Activation)     (None, 14, 14, 384)  0           batch_normalization_375[0][0]    
__________________________________________________________________________________________________
conv2d_372 (Conv2D)             (None, 14, 14, 384)  442368      activation_359[0][0]             
__________________________________________________________________________________________________
conv2d_373 (Conv2D)             (None, 14, 14, 384)  442368      activation_359[0][0]             
__________________________________________________________________________________________________
conv2d_376 (Conv2D)             (None, 14, 14, 384)  442368      activation_363[0][0]             
__________________________________________________________________________________________________
conv2d_377 (Conv2D)             (None, 14, 14, 384)  442368      activation_363[0][0]             
__________________________________________________________________________________________________
average_pooling2d_34 (AveragePo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_370 (Conv2D)             (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_372 (BatchN (None, 14, 14, 384)  1152        conv2d_372[0][0]                 
__________________________________________________________________________________________________
batch_normalization_373 (BatchN (None, 14, 14, 384)  1152        conv2d_373[0][0]                 
__________________________________________________________________________________________________
batch_normalization_376 (BatchN (None, 14, 14, 384)  1152        conv2d_376[0][0]                 
__________________________________________________________________________________________________
batch_normalization_377 (BatchN (None, 14, 14, 384)  1152        conv2d_377[0][0]                 
__________________________________________________________________________________________________
conv2d_378 (Conv2D)             (None, 14, 14, 192)  245760      average_pooling2d_34[0][0]       
__________________________________________________________________________________________________
batch_normalization_370 (BatchN (None, 14, 14, 320)  960         conv2d_370[0][0]                 
__________________________________________________________________________________________________
activation_360 (Activation)     (None, 14, 14, 384)  0           batch_normalization_372[0][0]    
__________________________________________________________________________________________________
activation_361 (Activation)     (None, 14, 14, 384)  0           batch_normalization_373[0][0]    
__________________________________________________________________________________________________
activation_364 (Activation)     (None, 14, 14, 384)  0           batch_normalization_376[0][0]    
__________________________________________________________________________________________________
activation_365 (Activation)     (None, 14, 14, 384)  0           batch_normalization_377[0][0]    
__________________________________________________________________________________________________
batch_normalization_378 (BatchN (None, 14, 14, 192)  576         conv2d_378[0][0]                 
__________________________________________________________________________________________________
activation_358 (Activation)     (None, 14, 14, 320)  0           batch_normalization_370[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_360[0][0]             
                                                                 activation_361[0][0]             
__________________________________________________________________________________________________
concatenate_6 (Concatenate)     (None, 14, 14, 768)  0           activation_364[0][0]             
                                                                 activation_365[0][0]             
__________________________________________________________________________________________________
activation_366 (Activation)     (None, 14, 14, 192)  0           batch_normalization_378[0][0]    
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_358[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_6[0][0]              
                                                                 activation_366[0][0]             
__________________________________________________________________________________________________
conv2d_383 (Conv2D)             (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_383 (BatchN (None, 14, 14, 448)  1344        conv2d_383[0][0]                 
__________________________________________________________________________________________________
activation_371 (Activation)     (None, 14, 14, 448)  0           batch_normalization_383[0][0]    
__________________________________________________________________________________________________
conv2d_380 (Conv2D)             (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_384 (Conv2D)             (None, 14, 14, 384)  1548288     activation_371[0][0]             
__________________________________________________________________________________________________
batch_normalization_380 (BatchN (None, 14, 14, 384)  1152        conv2d_380[0][0]                 
__________________________________________________________________________________________________
batch_normalization_384 (BatchN (None, 14, 14, 384)  1152        conv2d_384[0][0]                 
__________________________________________________________________________________________________
activation_368 (Activation)     (None, 14, 14, 384)  0           batch_normalization_380[0][0]    
__________________________________________________________________________________________________
activation_372 (Activation)     (None, 14, 14, 384)  0           batch_normalization_384[0][0]    
__________________________________________________________________________________________________
conv2d_381 (Conv2D)             (None, 14, 14, 384)  442368      activation_368[0][0]             
__________________________________________________________________________________________________
conv2d_382 (Conv2D)             (None, 14, 14, 384)  442368      activation_368[0][0]             
__________________________________________________________________________________________________
conv2d_385 (Conv2D)             (None, 14, 14, 384)  442368      activation_372[0][0]             
__________________________________________________________________________________________________
conv2d_386 (Conv2D)             (None, 14, 14, 384)  442368      activation_372[0][0]             
__________________________________________________________________________________________________
average_pooling2d_35 (AveragePo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_379 (Conv2D)             (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_381 (BatchN (None, 14, 14, 384)  1152        conv2d_381[0][0]                 
__________________________________________________________________________________________________
batch_normalization_382 (BatchN (None, 14, 14, 384)  1152        conv2d_382[0][0]                 
__________________________________________________________________________________________________
batch_normalization_385 (BatchN (None, 14, 14, 384)  1152        conv2d_385[0][0]                 
__________________________________________________________________________________________________
batch_normalization_386 (BatchN (None, 14, 14, 384)  1152        conv2d_386[0][0]                 
__________________________________________________________________________________________________
conv2d_387 (Conv2D)             (None, 14, 14, 192)  393216      average_pooling2d_35[0][0]       
__________________________________________________________________________________________________
batch_normalization_379 (BatchN (None, 14, 14, 320)  960         conv2d_379[0][0]                 
__________________________________________________________________________________________________
activation_369 (Activation)     (None, 14, 14, 384)  0           batch_normalization_381[0][0]    
__________________________________________________________________________________________________
activation_370 (Activation)     (None, 14, 14, 384)  0           batch_normalization_382[0][0]    
__________________________________________________________________________________________________
activation_373 (Activation)     (None, 14, 14, 384)  0           batch_normalization_385[0][0]    
__________________________________________________________________________________________________
activation_374 (Activation)     (None, 14, 14, 384)  0           batch_normalization_386[0][0]    
__________________________________________________________________________________________________
batch_normalization_387 (BatchN (None, 14, 14, 192)  576         conv2d_387[0][0]                 
__________________________________________________________________________________________________
activation_367 (Activation)     (None, 14, 14, 320)  0           batch_normalization_379[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_369[0][0]             
                                                                 activation_370[0][0]             
__________________________________________________________________________________________________
concatenate_7 (Concatenate)     (None, 14, 14, 768)  0           activation_373[0][0]             
                                                                 activation_374[0][0]             
__________________________________________________________________________________________________
activation_375 (Activation)     (None, 14, 14, 192)  0           batch_normalization_387[0][0]    
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_367[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_7[0][0]              
                                                                 activation_375[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_10 (Gl (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dense_10 (Dense)                (None, 2)            4098        global_average_pooling2d_10[0][0]
==================================================================================================
Total params: 21,806,882
Trainable params: 21,772,450
Non-trainable params: 34,432
__________________________________________________________________________________________________

def xception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model
    from keras.applications.xception import Xception

    # Pre-build model
    base_model = Xception(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    xception_model = Model(base_model.input, output)

    # Summary of the model
    xception_model.summary()
    
    # Compiling the model
    xception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                           loss = 'categorical_crossentropy', 
                           metrics = ['accuracy'])

    return xception_model

# Model 3
xception_model = xception_architecture()
xception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5")

Model: "model_11"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_10 (InputLayer)           [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_10[0][0]                   
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_388 (Conv2D)             (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_388 (BatchN (None, 127, 127, 128 512         conv2d_388[0][0]                 
__________________________________________________________________________________________________
add_36 (Add)                    (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_388[0][0]    
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add_36[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_389 (Conv2D)             (None, 64, 64, 256)  32768       add_36[0][0]                     
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_389 (BatchN (None, 64, 64, 256)  1024        conv2d_389[0][0]                 
__________________________________________________________________________________________________
add_37 (Add)                    (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_389[0][0]    
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_37[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_390 (Conv2D)             (None, 32, 32, 728)  186368      add_37[0][0]                     
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_390 (BatchN (None, 32, 32, 728)  2912        conv2d_390[0][0]                 
__________________________________________________________________________________________________
add_38 (Add)                    (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_390[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_38[0][0]                     
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_39 (Add)                    (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_38[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_39[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_40 (Add)                    (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_39[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_40[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_41 (Add)                    (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_40[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_41[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_42 (Add)                    (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_41[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_42[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_43 (Add)                    (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_42[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_43[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_44 (Add)                    (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_43[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_44[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_45 (Add)                    (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_44[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_45[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_46 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_45[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_46[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_391 (Conv2D)             (None, 16, 16, 1024) 745472      add_46[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_391 (BatchN (None, 16, 16, 1024) 4096        conv2d_391[0][0]                 
__________________________________________________________________________________________________
add_47 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_391[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_47[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_11 (Gl (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_11 (Dense)                (None, 2)            4098        global_average_pooling2d_11[0][0]
==================================================================================================
Total params: 20,865,578
Trainable params: 20,811,050
Non-trainable params: 54,528
__________________________________________________________________________________________________

5.3 Appending All the Models

# Appending all models
models = [mobilenet_model, inception_model, xception_model]

5.4 Defining the Ensembling Function

def ensemble(models, model_input):
    outputs = [model.outputs[0] for model in models]
    print("Outputs: ")
    print(outputs)
    y = keras.layers.Average()(outputs)
    print("y: ")
    print(y)
    model = Model(model_input, y, name='ensemble')
    print("Model: ")
    print(model)
    return model

# Getting ensemble model
ensemble_model = ensemble(models, model_input)

Outputs: 
[<KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'dense_9')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'dense_10')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'dense_11')>]
y: 
KerasTensor(type_spec=TensorSpec(shape=(None, 2), dtype=tf.float32, name=None), name='average/truediv:0', description="created by layer 'average'")
Model: 
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>

5.5 Obtaing the Weights of all the Models combined

# load models from file
def load_all_models(weight_file_names_with_path):
	all_models = list()
	for epoch in range(0,len(weight_file_names_with_path)):
		# define filename for this ensemble
		filename = weight_file_names_with_path[epoch] #'model_' + str(epoch) + '.h5'
		# load model from file
		model = load_model(filename)
		# add to list of members
		all_models.append(model)
		print('>loaded %s' % filename)
	return all_models

weight_file_names_with_path = ["/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5","/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5","/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5"]

# load all models into memory
members = load_all_models(weight_file_names_with_path)
print('Loaded %d models' % len(members))

>loaded /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
>loaded /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
>loaded /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Loaded 3 models

members

[<tensorflow.python.keras.engine.functional.Functional at 0x7fb3782ba410>,
 <tensorflow.python.keras.engine.functional.Functional at 0x7fb269db78d0>,
 <tensorflow.python.keras.engine.functional.Functional at 0x7fb27541f490>]

# prepare an array of equal weights
n_models = len(members)
total_weights = [1/n_models for i in range(1, n_models+1)] #[1/3 for i in range(1,(3+1))]

n_models

3

total_weights

[0.3333333333333333, 0.3333333333333333, 0.3333333333333333]

for weight in total_weights:
    weight = float(weight)

total_weights

[0.3333333333333333, 0.3333333333333333, 0.3333333333333333]

type(total_weights)

list

type(total_weights[0])

float

new_model = None

weights_of_MobileNet = members[0].get_weights()
print(weights_of_MobileNet)

[array([[[[ 0.08003967,  0.06701884, -0.00917125,  0.05773374,
          -0.02334076,  0.12947375, -0.10602847,  0.09505112,
          -0.06066425,  0.05592565,  0.13367547,  0.04283908,
           0.05161681,  0.08721521,  0.12351125, -0.07602793,
          -0.0898913 , -0.01630283,  0.09825794, -0.06842069,
          -0.15861864, -0.09215762, -0.14614232, -0.12056299,
           0.00958671, -0.03404507,  0.01396995, -0.0709205 ,
          -0.01550387,  0.11480875,  0.11634406, -0.05098934],
         [-0.11754993,  0.06420571, -0.03418145,  0.07967197,
          -0.15266584,  0.03503007,  0.10631548, -0.11289222,
           0.02884442,  0.09748194, -0.08833795,  0.13553801,
           0.03066746,  0.10255408,  0.05984911, -0.07956097,
           0.1091667 ,  0.07544538,  0.09672935, -0.02542743,
          -0.05302359,  0.12555109,  0.09628654, -0.1098905 ,
          -0.05914559,  0.10889119, -0.03936303,  0.04397286,
           0.00689034, -0.07094186,  0.06161569,  0.10272525],
         [ 0.03102707,  0.01178086,  0.11593208,  0.01477468,
          -0.09420621,  0.05188668, -0.06471226, -0.09906521,
           0.08183951, -0.08016194,  0.02181085,  0.02097014,
          -0.10567269, -0.10835019, -0.10033327, -0.00898785,
          -0.03692527,  0.08060358,  0.0637159 , -0.09965546,
          -0.1616874 ,  0.07156506, -0.04259282,  0.09585604,
           0.06940774,  0.06971691, -0.02352723,  0.0080339 ,
          -0.00635403,  0.00442745,  0.03460172,  0.05833453]],

        [[ 0.00695247,  0.00471924,  0.14426477,  0.00058385,
          -0.0436728 , -0.05792462,  0.00875165, -0.11001103,
           0.10095387, -0.02825973, -0.11677517,  0.13918765,
           0.09292979, -0.0601979 , -0.03098716,  0.10255738,
           0.13868849, -0.07613563,  0.08308743, -0.07082194,
          -0.00792184, -0.12130015,  0.12146827, -0.03238769,
           0.01416447,  0.12545156,  0.06389817, -0.0134991 ,
          -0.02749915,  0.06142865, -0.0905382 , -0.12312108],
         [-0.02183109,  0.06427856,  0.10762891,  0.0726292 ,
          -0.14616443, -0.11819902, -0.04019972,  0.06583542,
          -0.11931179, -0.08067856, -0.09988974, -0.01231556,
           0.12123062, -0.05624576,  0.05583556, -0.07332164,
           0.08795073, -0.12819086, -0.08118466,  0.02130767,
           0.07710715,  0.04272947, -0.01709427,  0.06498932,
           0.00931086, -0.10229146,  0.05188456,  0.00600362,
          -0.07808179, -0.07597332,  0.07252023, -0.10837749],
         [-0.09883164,  0.04068341, -0.00887908,  0.11916742,
           0.10222055,  0.08000942, -0.00694548, -0.04964423,
           0.09760603,  0.04459826, -0.08953381,  0.1331718 ,
           0.05350536,  0.05588256, -0.11203333, -0.01308048,
          -0.13725077,  0.0311048 ,  0.06267859,  0.06501984,
           0.10461377, -0.06616857,  0.06460639, -0.09579871,
           0.01977726,  0.12191592, -0.11486652, -0.12196404,
          -0.13940346, -0.06606551,  0.13429138,  0.03155424]],

        [[ 0.09038043, -0.06964921, -0.05347313, -0.0452428 ,
           0.13643283, -0.08290562,  0.03057508,  0.109111  ,
           0.0341032 , -0.10148726, -0.08533561,  0.03883333,
          -0.10305514,  0.10992431, -0.00858552,  0.08613879,
          -0.092384  , -0.13081992, -0.09334698,  0.02270075,
           0.08481742, -0.00948169, -0.12341185,  0.01601155,
           0.01509676,  0.11427563,  0.06991914,  0.10096669,
          -0.06661161, -0.10937992,  0.02258415, -0.0475747 ],
         [ 0.02890788, -0.03774353, -0.0654062 ,  0.04639338,
           0.06390826,  0.09272024, -0.0802696 , -0.00116412,
          -0.0922244 ,  0.02242612, -0.13513947,  0.00424453,
          -0.07359263,  0.06153493,  0.09454129,  0.06443928,
          -0.04430386, -0.13909748, -0.07175265,  0.09957287,
          -0.09480529, -0.06608137,  0.04384995,  0.1438494 ,
           0.09700811, -0.07140335, -0.11765399, -0.07397863,
          -0.0987126 , -0.14254025, -0.03436549,  0.02162071],
         [-0.13181457, -0.1387666 ,  0.00310841, -0.01015603,
           0.00158709,  0.07216203, -0.11215337,  0.11983041,
          -0.14441986, -0.00544816, -0.11533022, -0.0966631 ,
          -0.04172823,  0.08781462,  0.12322967,  0.1291672 ,
          -0.02536417, -0.06459461,  0.00925332,  0.02646021,
           0.05950025,  0.0223687 ,  0.06178823,  0.04580371,
           0.02172172,  0.10101365, -0.08366393,  0.08619494,
          -0.02377004, -0.13867705,  0.11056394,  0.00645594]]],


       [[[-0.02984591,  0.14553161,  0.0508716 ,  0.04614235,
          -0.03219702, -0.02602464,  0.06190509, -0.15978181,
           0.07551015, -0.05041312,  0.00579625, -0.07614888,
          -0.09281002, -0.03295409,  0.01584308, -0.08704739,
          -0.03381349,  0.03587921, -0.10922135, -0.06025077,
           0.03237732, -0.08475717,  0.11464108, -0.10521103,
           0.11927051, -0.02621956, -0.07932819,  0.01821999,
          -0.05940498, -0.06001169, -0.09475481,  0.05353018],
         [ 0.03240233, -0.05911161,  0.02365742, -0.03863018,
           0.08086011, -0.10995619, -0.10822936, -0.05614195,
          -0.01707025,  0.02669683, -0.13580486, -0.082422  ,
           0.09291192,  0.12896797,  0.07111618, -0.1213998 ,
          -0.05868091, -0.06171649,  0.11953177,  0.03752872,
           0.00973747,  0.09728366,  0.10545039,  0.05002955,
           0.10572688, -0.13172658, -0.05573305, -0.0610614 ,
           0.00403686,  0.03171724, -0.10326949, -0.00454319],
         [-0.10664029, -0.03910515,  0.11255802,  0.08305684,
           0.04685831, -0.1188888 ,  0.02999429,  0.1288633 ,
           0.02240152, -0.09894315,  0.08439668,  0.11205082,
           0.07505779,  0.02199851, -0.12703635,  0.14434561,
           0.02468775, -0.02406991, -0.11524384,  0.03512704,
          -0.12995103, -0.0749918 , -0.00087453,  0.05904675,
           0.0699559 , -0.00893272, -0.0572848 , -0.06830772,
           0.08225786,  0.01655459, -0.0870102 ,  0.07986389]],

        [[-0.09075534,  0.00456474, -0.11902454,  0.08549408,
           0.02299694, -0.11551689, -0.09306116,  0.03916756,
          -0.05119455, -0.06498867,  0.12527657,  0.03741521,
           0.04084676, -0.08596158, -0.0640067 , -0.07199902,
           0.1303064 , -0.11387078,  0.13985138, -0.02589918,
          -0.02423203,  0.11245368,  0.11468272,  0.12202665,
           0.08433066, -0.0577034 , -0.01593571, -0.05062377,
          -0.04872382,  0.09901507,  0.09440424,  0.02607791],
         [ 0.00988852,  0.01745099,  0.01137866,  0.03096857,
          -0.13189207, -0.11390599, -0.08520476, -0.12757908,
           0.04495005, -0.13767737,  0.06512965,  0.08898906,
           0.08561593, -0.07320201, -0.01154245,  0.14611524,
          -0.01851234,  0.1422457 ,  0.11547671,  0.03752927,
           0.06778905,  0.06848953,  0.13527581,  0.1373267 ,
           0.07467669,  0.11351319, -0.01746203, -0.02892278,
           0.09035175,  0.01772481, -0.11964016,  0.05583654],
         [ 0.08200721,  0.01768816,  0.0413871 ,  0.09855786,
          -0.02487629,  0.06944259, -0.0351283 ,  0.03720064,
           0.05606438, -0.11838818,  0.02351972, -0.00673357,
          -0.12384885,  0.03640115, -0.13032214, -0.08708297,
           0.06318569,  0.03348094,  0.11173801,  0.03571498,
           0.04551458,  0.09768766,  0.08571486,  0.07107718,
           0.10453384, -0.05588401,  0.03508557, -0.14338723,
          -0.02304512,  0.05231867,  0.00583608, -0.09538563]],

        [[ 0.15202865, -0.10199393,  0.10973282, -0.02993715,
          -0.02330341, -0.11556442,  0.0746132 , -0.08579011,
           0.05125686, -0.12020919, -0.11698996, -0.01062987,
           0.06213389, -0.0289795 ,  0.07444265,  0.05339759,
          -0.07757818,  0.05515982, -0.0075224 ,  0.04985338,
          -0.1119193 , -0.07131388,  0.00180924, -0.02457109,
          -0.05625205, -0.11297491,  0.00095293,  0.02866088,
           0.04641582,  0.04635878,  0.0508337 ,  0.043173  ],
         [-0.04437496,  0.07959335,  0.00587196, -0.07871412,
           0.08037584,  0.07789128, -0.12208204, -0.07521409,
           0.01867775,  0.01638946, -0.07298494, -0.12064841,
           0.04016455,  0.02019038,  0.04677459,  0.02443541,
          -0.04290102,  0.04441332, -0.11654333,  0.06916092,
           0.09190457,  0.00683884,  0.01229054, -0.03924207,
           0.01082106,  0.04654453, -0.07365119, -0.06221369,
           0.06077598, -0.00569101,  0.03036912, -0.04685553],
         [-0.09590702, -0.11172572,  0.08007952, -0.09351138,
           0.0125387 ,  0.11734404,  0.0311004 , -0.0367786 ,
          -0.07076506,  0.10942113,  0.08337071,  0.04784434,
           0.00772755,  0.0983236 ,  0.03538076,  0.07113694,
           0.03935843, -0.1301666 ,  0.03583546, -0.00239446,
          -0.11049514,  0.07741249, -0.04824267,  0.09402268,
           0.02325376, -0.03976533,  0.08527937, -0.10975566,
          -0.01787509,  0.08637717, -0.08908485,  0.00981965]]],


       [[[ 0.09056461,  0.08390243,  0.12802555, -0.12677717,
           0.13755636, -0.01853593,  0.01097767, -0.13213587,
          -0.15310629,  0.05116278,  0.04162168,  0.01106944,
          -0.06788407,  0.01840547,  0.15337719,  0.15098082,
           0.00305877,  0.03120011, -0.01321382,  0.11434495,
           0.09834344,  0.0681811 , -0.00987351,  0.13720691,
          -0.08069672,  0.03157091, -0.02219615, -0.05810291,
          -0.08481006, -0.11186066,  0.01545114,  0.04464108],
         [-0.06986142,  0.07012778,  0.128923  ,  0.06576104,
          -0.1365377 , -0.11142381, -0.11556736, -0.05678521,
           0.10006635, -0.01208107,  0.06604688, -0.12293527,
          -0.08206314,  0.05858034, -0.02277251,  0.10913601,
          -0.0706777 ,  0.00288409,  0.07094925, -0.12701733,
           0.03729674, -0.00637962,  0.10010105, -0.11773462,
          -0.10713284,  0.05381555, -0.02326755, -0.04588238,
          -0.10007037, -0.10869775, -0.13661356, -0.07907082],
         [ 0.02374944, -0.04500759,  0.00763621, -0.02487346,
           0.08404142, -0.06426077,  0.09548146,  0.11908014,
          -0.01200817,  0.01968322, -0.08803074, -0.0263763 ,
          -0.09793035, -0.01272094, -0.12471068,  0.14053676,
          -0.13067289, -0.00602704,  0.02517141,  0.11965312,
          -0.09560583, -0.01756755, -0.02519952, -0.02899948,
          -0.03927438, -0.06987545,  0.04628979,  0.12520522,
           0.03242727,  0.08000426, -0.149264  ,  0.07226408]],

        [[-0.11173446, -0.08578662, -0.07096707,  0.09870818,
          -0.0350247 , -0.02869418, -0.11553004, -0.12082101,
           0.03386271, -0.02056597, -0.01256185, -0.05536598,
          -0.11989012,  0.06635252,  0.14282775, -0.07927992,
          -0.09574829, -0.01868471,  0.09582473, -0.02465393,
          -0.02098274,  0.01838031, -0.06547995, -0.10463241,
           0.01509506,  0.01056188,  0.08818209, -0.08487871,
           0.04316008,  0.02258445,  0.03548159,  0.05564847],
         [-0.0543713 , -0.08536784,  0.0007002 ,  0.04111828,
          -0.04672715, -0.00750103, -0.1404203 ,  0.00624776,
           0.03095804,  0.06989639, -0.08728603,  0.08427734,
          -0.06335954, -0.13809822,  0.09949932, -0.11510354,
          -0.11444696, -0.01909978,  0.01410128, -0.1407088 ,
           0.10493827,  0.1268847 ,  0.07425763,  0.03240895,
          -0.03572486, -0.04638692, -0.06911834,  0.08767448,
          -0.06314736, -0.11444329, -0.01144686,  0.06371113],
         [-0.13172327, -0.16187468,  0.14275847, -0.05306448,
           0.0309928 ,  0.01236707,  0.07023086,  0.01968252,
          -0.00429218,  0.03808338, -0.0526533 ,  0.0467958 ,
           0.02365939, -0.0188813 ,  0.09761018, -0.08497018,
           0.02213316,  0.00321389, -0.11183998, -0.06048004,
          -0.13221258,  0.07516433,  0.04350816,  0.08413642,
           0.08901523,  0.10911408, -0.02982878,  0.01962051,
           0.05558495, -0.03030293, -0.08711713,  0.02953597]],

        [[ 0.09406487, -0.08579446, -0.07337274,  0.04336292,
          -0.12050322, -0.0444902 ,  0.09031063, -0.1574151 ,
           0.0386866 ,  0.10961696,  0.01052026,  0.0469555 ,
          -0.00206451, -0.10894608,  0.04568684,  0.06156035,
          -0.04893908, -0.03172801, -0.09400756, -0.11545743,
          -0.13045238, -0.08615037, -0.10034026, -0.07106197,
           0.01847986,  0.02906877,  0.02721578,  0.13206908,
          -0.09155186,  0.0117079 , -0.08920289,  0.10544272],
         [ 0.01458425,  0.06712376, -0.10063295,  0.14126942,
           0.04223863, -0.14037031, -0.10004249, -0.12323932,
           0.0175689 , -0.13612624, -0.00158303,  0.08682149,
          -0.0341155 , -0.01701755, -0.01847473,  0.14204228,
           0.03416816,  0.09553892, -0.01306614, -0.13519585,
           0.06666402,  0.09927521,  0.06193526, -0.02846929,
          -0.02939643,  0.1411735 , -0.1032325 ,  0.08595792,
          -0.01830455,  0.024335  , -0.04667107,  0.09042729],
         [ 0.06731981, -0.10591428, -0.05532357, -0.06639116,
          -0.04544847,  0.00157975,  0.02137013,  0.01493613,
           0.1484868 ,  0.10384225, -0.10916635,  0.03250845,
          -0.13107939, -0.08569106,  0.02687251,  0.07356635,
          -0.01830893, -0.02936403, -0.01601532,  0.11932884,
          -0.01806743, -0.05047882,  0.07478981,  0.0759911 ,
           0.04370127,  0.1117762 ,  0.09091385, -0.00275905,
           0.07164925,  0.05495712,  0.05412957,  0.08746493]]]],
      dtype=float32), array([1.0116947 , 0.99607134, 0.9972682 , 1.0094858 , 1.019429  ,
       0.9913172 , 0.99040955, 0.99062866, 0.96807957, 0.99351066,
       1.0320045 , 1.0251229 , 0.99822146, 1.0047857 , 0.9663147 ,
       0.99729365, 0.9791835 , 1.0076885 , 1.0186099 , 1.0181692 ,
       0.9766168 , 1.0223039 , 1.0038531 , 1.0043573 , 0.97375137,
       0.9863457 , 0.9898142 , 0.99583423, 1.0124199 , 1.014896  ,
       0.99701864, 0.9995635 ], dtype=float32), array([-0.01132925,  0.00433579, -0.01937866,  0.01207361, -0.01134302,
       -0.03722537,  0.00648496,  0.0205779 , -0.01657603,  0.02537948,
       -0.01722033,  0.02220796, -0.00640057,  0.00443062,  0.01786522,
        0.00518779, -0.00474894, -0.02907063,  0.01882604,  0.00480896,
        0.01455369, -0.0194147 ,  0.02441232,  0.02286402, -0.0151797 ,
       -0.00689606,  0.00011407, -0.02835473, -0.00901855, -0.01455965,
        0.03007717,  0.00026928], dtype=float32), array([-0.11151354, -0.17740038,  0.34611353,  0.3345144 , -0.15064853,
       -0.36058027, -0.38355753, -0.49169916,  0.19041438, -0.17584124,
       -0.41668966,  0.30032617, -0.19278921,  0.10167897,  0.3422816 ,
        0.32574353, -0.26832283, -0.25082427,  0.19147256, -0.09833881,
       -0.13680314,  0.17818092,  0.4281339 ,  0.1320503 ,  0.34812155,
        0.31585452, -0.16253902, -0.14399952, -0.30533767, -0.13312754,
       -0.15011545,  0.26950508], dtype=float32), array([0.01131933, 0.01091691, 0.01600982, 0.01361739, 0.00836701,
       0.01320626, 0.01667036, 0.01859246, 0.00978047, 0.0082695 ,
       0.02064158, 0.01224529, 0.0098371 , 0.00760268, 0.01298115,
       0.01511444, 0.01154027, 0.00990988, 0.00892878, 0.00754368,
       0.00924723, 0.01187045, 0.02137613, 0.01114347, 0.01473321,
       0.01446668, 0.00981357, 0.00875431, 0.01119436, 0.0086489 ,
       0.00923724, 0.01189734], dtype=float32), array([[[[ 2.95556001e-02],
         [ 1.19775884e-01],
         [-5.24070263e-02],
         [-5.32923639e-02],
         [ 1.10916033e-01],
         [-6.99056089e-02],
         [ 9.11175832e-02],
         [-1.36864856e-01],
         [ 1.07356302e-01],
         [ 1.20126441e-01],
         [ 4.54347534e-03],
         [-2.48557571e-02],
         [ 1.18309915e-01],
         [ 4.50464189e-02],
         [-8.09024796e-02],
         [ 3.16152442e-03],
         [-1.06884867e-01],
         [ 6.24022149e-02],
         [-7.30631202e-02],
         [-5.55443428e-02],
         [-4.29260433e-02],
         [ 1.76381931e-01],
         [-1.80107448e-02],
         [ 7.02006444e-02],
         [-1.07369713e-01],
         [-1.01456814e-01],
         [-3.45528685e-02],
         [ 7.21419454e-02],
         [ 9.09703821e-02],
         [-3.71972546e-02],
         [ 1.33736178e-01],
         [-1.13892242e-01]],

        [[-3.02617233e-02],
         [ 6.26576468e-02],
         [ 1.17358468e-01],
         [ 5.60325645e-02],
         [ 1.16583921e-01],
         [-3.31120715e-02],
         [ 6.31986484e-02],
         [-1.08385175e-01],
         [ 3.25450450e-02],
         [-5.78248315e-02],
         [-5.50813600e-02],
         [ 5.22708297e-02],
         [-1.04355156e-01],
         [ 1.03927404e-02],
         [ 6.67244121e-02],
         [ 4.28404659e-03],
         [-1.22881487e-01],
         [-4.62576374e-02],
         [-7.04906806e-02],
         [-1.37188077e-01],
         [ 7.61295557e-02],
         [ 1.53412178e-01],
         [ 4.56631556e-02],
         [-2.04493944e-02],
         [ 1.12186586e-02],
         [-7.87648465e-03],
         [ 6.51681349e-02],
         [ 1.00925885e-01],
         [-1.16414845e-01],
         [ 6.64504841e-02],
         [-6.24369159e-02],
         [-1.28178233e-02]],

        [[ 7.49551281e-02],
         [ 4.81622517e-02],
         [-7.29915947e-02],
         [ 1.33452401e-01],
         [-6.81223497e-02],
         [ 6.54807985e-02],
         [-1.02721922e-01],
         [ 1.45025812e-02],
         [-8.60702544e-02],
         [-1.30531833e-01],
         [-5.37587628e-02],
         [ 7.30845407e-02],
         [-1.19588032e-01],
         [ 1.37873247e-01],
         [ 4.35974598e-02],
         [ 1.14670753e-01],
         [ 1.36857465e-01],
         [ 1.15331262e-01],
         [-1.18826933e-01],
         [-1.46832973e-01],
         [-7.69534484e-02],
         [ 6.10438064e-02],
         [ 1.18165210e-01],
         [-4.38390411e-02],
         [ 4.05863225e-02],
         [ 1.16106577e-03],
         [-7.09386021e-02],
         [-9.50326025e-03],
         [ 1.32999167e-01],
         [ 8.87401327e-02],
         [ 1.08595468e-01],
         [-1.53581733e-02]]],


       [[[ 5.36192805e-02],
         [-8.39448571e-02],
         [-2.24099290e-02],
         [ 8.22108537e-02],
         [-6.51942566e-02],
         [-6.70094639e-02],
         [ 5.37282415e-02],
         [-1.19549729e-01],
         [ 9.85014662e-02],
         [-1.21057630e-01],
         [-6.87014312e-02],
         [ 4.05324884e-02],
         [ 1.33541420e-01],
         [ 2.20729187e-02],
         [ 1.07400909e-01],
         [ 6.68395460e-02],
         [-1.16568357e-01],
         [-6.24983571e-02],
         [-3.32308784e-02],
         [ 2.27457732e-02],
         [ 1.49564683e-01],
         [-7.03510046e-02],
         [ 2.40114592e-02],
         [-3.93991265e-03],
         [-8.66659805e-02],
         [-2.72292290e-02],
         [ 1.18315272e-01],
         [ 1.11727342e-01],
         [ 1.39901504e-01],
         [-3.12538370e-02],
         [ 4.69435267e-02],
         [ 1.89764611e-02]],

        [[ 1.40297711e-01],
         [ 8.08212999e-03],
         [ 2.35673673e-02],
         [ 9.59308594e-02],
         [ 1.22407891e-01],
         [ 1.36901692e-01],
         [-4.10035998e-03],
         [-5.94646074e-02],
         [-1.84687842e-02],
         [-1.19042071e-02],
         [ 1.19518235e-01],
         [-8.50331038e-02],
         [-7.15548694e-02],
         [ 6.70210421e-02],
         [ 1.65815353e-02],
         [-5.95633909e-02],
         [ 6.84339255e-02],
         [ 1.37998328e-01],
         [-9.47962552e-02],
         [ 1.46062747e-02],
         [ 4.64751609e-02],
         [-4.73616570e-02],
         [ 7.18726367e-02],
         [ 2.96719521e-02],
         [-3.91260386e-02],
         [-1.10252433e-01],
         [ 3.28944959e-02],
         [ 9.35810879e-02],
         [ 4.70280685e-02],
         [ 1.22388706e-01],
         [ 8.16757977e-02],
         [ 1.51293159e-01]],

        [[ 1.19169373e-02],
         [-3.90449837e-02],
         [-1.17857732e-01],
         [ 4.47687395e-02],
         [-1.00857206e-01],
         [ 6.06503524e-02],
         [ 6.57577217e-02],
         [-1.29718900e-01],
         [ 8.34249780e-02],
         [ 7.12871924e-02],
         [ 5.27597219e-02],
         [ 9.34090987e-02],
         [ 1.28255144e-01],
         [-3.09117585e-02],
         [ 8.27559084e-03],
         [ 1.27225280e-01],
         [ 1.31490119e-02],
         [-9.76860970e-02],
         [-5.36997020e-02],
         [ 8.60775784e-02],
         [-8.12787265e-02],
         [ 9.31693092e-02],
         [-1.66920181e-02],
         [-1.18170731e-01],
         [ 1.13018982e-01],
         [ 1.18204569e-02],
         [ 9.40141529e-02],
         [-5.27156927e-02],
         [-1.28686249e-01],
         [-3.36229540e-02],
         [-1.49809197e-01],
         [ 5.71130216e-02]]],


       [[[ 2.24707332e-02],
         [ 8.68379790e-03],
         [ 1.16436996e-01],
         [-1.17741771e-01],
         [ 3.41590829e-02],
         [ 2.90450174e-02],
         [ 5.04661426e-02],
         [ 3.39311510e-02],
         [-2.77696010e-02],
         [-8.78420547e-02],
         [-1.27111211e-01],
         [-2.30234526e-02],
         [-5.73663078e-02],
         [-1.10801436e-01],
         [ 4.91070859e-02],
         [ 9.27211195e-02],
         [-4.77412641e-02],
         [-8.68820250e-02],
         [-8.30825493e-02],
         [ 8.65088701e-02],
         [ 6.42145574e-02],
         [ 9.79830623e-02],
         [ 6.71050847e-02],
         [-1.40216202e-01],
         [ 1.72583908e-02],
         [ 6.69077858e-02],
         [ 1.25886872e-01],
         [ 8.87647197e-02],
         [ 5.23349307e-02],
         [-2.71850340e-02],
         [-2.20761709e-02],
         [ 1.85377762e-01]],

        [[ 4.94822264e-02],
         [ 1.89750716e-02],
         [-1.14052311e-01],
         [ 7.73540288e-02],
         [-3.13426112e-03],
         [-8.07190835e-02],
         [ 2.49616783e-02],
         [-4.22114208e-02],
         [-4.96958941e-02],
         [ 4.31031920e-02],
         [ 8.17255378e-02],
         [-3.72380726e-02],
         [ 2.14906801e-02],
         [-1.33109204e-02],
         [ 1.20589167e-01],
         [-4.96898293e-02],
         [-1.16328694e-01],
         [ 3.93519998e-02],
         [ 4.99250740e-03],
         [ 4.26920913e-02],
         [ 4.37901691e-02],
         [ 1.75021868e-02],
         [-4.96309102e-02],
         [ 4.60480014e-03],
         [-6.67211637e-02],
         [ 2.21982189e-02],
         [ 9.64178815e-02],
         [-4.64772917e-02],
         [-9.68638584e-02],
         [-1.13236241e-01],
         [-6.78928569e-02],
         [ 2.88443323e-02]],

        [[ 6.33347227e-05],
         [ 3.28029357e-02],
         [-7.44863600e-02],
         [ 2.97077186e-02],
         [-5.29188365e-02],
         [-9.25845802e-02],
         [ 1.25185192e-01],
         [ 7.86941573e-02],
         [-5.91059364e-02],
         [-9.94201377e-02],
         [-1.31485060e-01],
         [ 8.23419690e-02],
         [ 3.61588523e-02],
         [-1.47901982e-01],
         [-3.25565115e-02],
         [ 7.56834224e-02],
         [-4.28245850e-02],
         [ 1.02355666e-01],
         [-4.59831208e-02],
         [-2.63176709e-02],
         [ 1.06047414e-01],
         [-3.77716087e-02],
         [ 2.14160588e-02],
         [-9.12842527e-02],
         [-1.14328541e-01],
         [ 2.71859001e-02],
         [-2.15683486e-02],
         [-3.32022756e-02],
         [ 1.15334995e-01],
         [ 6.07047006e-02],
         [-3.08403559e-02],
         [ 1.08902216e-01]]]], dtype=float32), array([1.0083424 , 0.98638004, 0.9967846 , 1.0144076 , 1.0222653 ,
       0.9983566 , 0.98841465, 0.9848646 , 0.9668609 , 1.0009238 ,
       1.0384072 , 1.0272243 , 1.000505  , 1.0065044 , 0.962429  ,
       0.9954204 , 0.980134  , 1.0164682 , 1.0118909 , 1.0194438 ,
       0.9965449 , 1.0211698 , 1.0069344 , 1.0071517 , 0.96966475,
       0.98523694, 0.9938702 , 0.9842587 , 1.0187156 , 1.0153402 ,
       1.0070516 , 0.9965552 ], dtype=float32), array([ 0.00192684, -0.01368205,  0.01884213,  0.01981261, -0.01013349,
        0.01055005, -0.00347678, -0.03617752, -0.0357139 , -0.01721989,
        0.04200221,  0.02517658, -0.00235413,  0.04122072, -0.02255856,
        0.00011871, -0.01018246, -0.00664502,  0.0058722 ,  0.02133135,
        0.00532367,  0.00430373,  0.02152884,  0.013504  , -0.0242344 ,
        0.00294869, -0.01156376, -0.03234636, -0.00170229, -0.01093967,
        0.00628786, -0.00550099], dtype=float32), array([ 0.11374234,  0.0546744 , -0.07263396,  0.12303823,  0.02329646,
       -0.02212481,  0.12933026, -0.16237976,  0.03603587, -0.08335476,
       -0.0696851 ,  0.06022331,  0.02193742,  0.00344895,  0.10012098,
        0.12829751, -0.10204066,  0.05165722, -0.17654239, -0.02185931,
        0.09197502,  0.1520687 ,  0.09405566, -0.11559457, -0.08946916,
       -0.04150132,  0.13164121,  0.10021521,  0.07368086,  0.01919498,
        0.01804485,  0.1396669 ], dtype=float32), array([0.04121853, 0.01527549, 0.0176246 , 0.03457902, 0.01021327,
       0.0104667 , 0.05431169, 0.08810031, 0.00962824, 0.02627724,
       0.022357  , 0.01356696, 0.01269385, 0.01052042, 0.02470051,
       0.03617501, 0.03790378, 0.01594317, 0.06226002, 0.0111504 ,
       0.02779756, 0.05153067, 0.02262689, 0.03247958, 0.02225022,
       0.01004429, 0.05445518, 0.03469063, 0.02421084, 0.00928075,
       0.01054194, 0.04317801], dtype=float32), array([[[[ 0.25496784, -0.04934003, -0.05159465, ..., -0.14281942,
          -0.1317516 , -0.16535805],
         [ 0.18013304, -0.19201204,  0.22039536, ..., -0.10563517,
           0.13972034, -0.19732107],
         [-0.13824846, -0.06806026,  0.13378108, ...,  0.08226853,
           0.02778996,  0.0747294 ],
         ...,
         [ 0.08347616,  0.24778226,  0.03700222, ...,  0.12273995,
           0.22482912,  0.04563395],
         [-0.12487882, -0.13505255, -0.10634625, ...,  0.08165364,
          -0.13588004,  0.1540924 ],
         [-0.03267678,  0.20243889, -0.19315241, ..., -0.15288216,
          -0.01865002,  0.03016651]]]], dtype=float32), array([0.9857526 , 0.99770874, 0.9850288 , 1.0150813 , 1.0127444 ,
       1.0014201 , 1.0024669 , 1.0184914 , 1.0033612 , 1.037983  ,
       1.0264208 , 1.0018224 , 1.0125197 , 0.9884134 , 0.9790624 ,
       0.9886727 , 0.95824164, 0.9980072 , 0.99312836, 0.9944759 ,
       1.0192419 , 0.98800135, 0.98980963, 1.0069582 , 1.0003257 ,
       0.9691357 , 1.0019857 , 0.9968254 , 0.992267  , 0.9916628 ,
       1.0020186 , 1.0155225 , 1.0039799 , 1.0011507 , 1.0145782 ,
       0.9813915 , 0.99609506, 1.0072955 , 1.0177788 , 0.98469746,
       1.0084367 , 1.0078118 , 0.99291104, 0.9986405 , 1.0028577 ,
       1.012738  , 0.9938384 , 0.9841884 , 0.99935675, 0.94604474,
       0.99760526, 1.0250278 , 1.0122122 , 1.013465  , 1.0176365 ,
       1.0031742 , 0.98291326, 1.0172073 , 0.94934905, 1.0146257 ,
       1.0023617 , 0.98529595, 1.0024977 , 0.9918223 ], dtype=float32), array([-0.01848058,  0.01088173,  0.01470235,  0.00891005, -0.01548589,
        0.01011036, -0.00468519,  0.00548058, -0.01304612,  0.01100101,
        0.00441467, -0.00170938, -0.00507063, -0.00827603, -0.01372367,
        0.01851122, -0.01018363, -0.02185583, -0.01249426,  0.00940321,
        0.03253313, -0.00199064, -0.0278215 ,  0.02303662,  0.03612682,
       -0.0057359 , -0.00800068,  0.01038041, -0.01184124, -0.00110855,
        0.00805689,  0.01666154,  0.00702424,  0.02197539,  0.00094307,
       -0.04007384,  0.01631629, -0.00683358,  0.0240899 , -0.01059895,
        0.01340119, -0.01221105, -0.0131151 ,  0.02164775,  0.02343373,
       -0.00227941, -0.01771162,  0.00312028,  0.00973773, -0.02683033,
       -0.00757813,  0.01425221,  0.01161402,  0.01192947, -0.01323079,
        0.01664765,  0.00955332, -0.00975921, -0.03607217,  0.00280488,
       -0.00915653,  0.00214115, -0.02007346,  0.01830361], dtype=float32), array([ 0.08764772, -0.26613542,  0.11463159,  0.0012322 ,  0.2980036 ,
        0.20447505, -0.5825306 ,  0.15945798, -0.12514637, -0.01084444,
        0.4858876 ,  0.29517415,  0.34965396,  0.25097334,  0.0469772 ,
        0.26583698,  0.18283147,  0.074343  , -0.06010276, -0.11150738,
       -0.42700556,  0.10784036,  0.62978214,  0.29621312,  0.01820382,
       -0.2866262 ,  0.2977116 ,  0.28558373, -0.0037823 ,  0.24796885,
        0.00133907, -0.3519575 , -0.47984004, -0.23226078, -0.5448577 ,
        0.13002151, -0.3334058 ,  0.2979588 , -0.30201775,  0.3907591 ,
        0.76856357,  0.0298341 , -0.712051  ,  0.07956086,  0.31937706,
        0.19672352, -0.23521377, -0.22216699,  0.42770928,  0.0703435 ,
       -0.3455759 , -0.30128738, -0.14824344,  0.09316625, -0.21136121,
       -0.20172745, -0.10906828, -0.4478446 ,  0.16321348,  0.17776072,
       -0.2978754 , -0.3010034 ,  0.12881862, -0.35240513], dtype=float32), array([0.44487247, 0.15287113, 0.23306905, 0.2490024 , 0.3295214 ,
       0.22840337, 0.24281707, 0.20989195, 0.2096476 , 0.0893496 ,
       0.12092313, 0.13791993, 0.12643243, 0.36948568, 0.23910002,
       0.09465656, 0.29260993, 0.20322411, 0.12361932, 0.26497203,
       0.5526204 , 0.2465406 , 0.34900331, 0.32894498, 0.41923818,
       0.10039598, 0.3108709 , 0.19342758, 0.280488  , 0.12470761,
       0.13825412, 0.19914529, 0.49340364, 0.10521688, 0.6386877 ,
       0.28792185, 0.5818859 , 0.62417424, 0.2781595 , 0.18222988,
       0.56394255, 0.4812397 , 0.5138419 , 0.62772775, 0.15417235,
       0.26492205, 0.66368574, 0.09059105, 0.3949282 , 0.16111784,
       0.3248954 , 0.19284834, 0.37438026, 0.38511586, 0.4125866 ,
       0.36385927, 0.16303152, 0.2844291 , 0.34272316, 0.08207371,
       0.19172242, 0.21227986, 0.11526531, 0.44302928], dtype=float32), array([[[[-5.73993064e-02],
         [-3.40915956e-02],
         [-5.15258797e-02],
         [-8.09507146e-02],
         [ 6.37921691e-02],
         [-3.54121067e-02],
         [ 7.18686357e-02],
         [-7.72600845e-02],
         [-5.14092632e-02],
         [-2.60464344e-02],
         [ 1.70331970e-02],
         [-4.64696772e-02],
         [-2.21744571e-02],
         [-7.28184730e-02],
         [-4.21771891e-02],
         [-7.54293650e-02],
         [-2.57494915e-02],
         [ 1.01451002e-01],
         [ 1.59120429e-02],
         [ 1.43265259e-02],
         [ 6.05478929e-03],
         [ 1.19434576e-02],
         [-6.40677139e-02],
         [ 3.50700691e-02],
         [ 5.64280860e-02],
         [-4.73262891e-02],
         [-4.05872203e-02],
         [ 6.79656714e-02],
         [-1.45246356e-03],
         [ 1.32483497e-01],
         [ 4.61900495e-02],
         [ 5.99313192e-02],
         [-7.04020336e-02],
         [ 1.06126770e-01],
         [-7.55689219e-02],
         [ 1.01449147e-01],
         [-2.60665677e-02],
         [-8.96946900e-03],
         [-8.15157872e-03],
         [-1.27665447e-02],
         [ 5.95875494e-02],
         [ 2.21488755e-02],
         [ 5.64397639e-03],
         [ 7.76610300e-02],
         [ 6.59606978e-02],
         [-4.62623239e-02],
         [-2.88818050e-02],
         [-9.95921195e-02],
         [ 3.63871641e-02],
         [-1.19055249e-02],
         [-7.43244216e-03],
         [-7.32522681e-02],
         [-9.35807601e-02],
         [ 2.55685095e-02],
         [ 4.06262130e-02],
         [-6.19129650e-02],
         [-6.09226786e-02],
         [ 2.32862569e-02],
         [-3.52252051e-02],
         [ 7.91172013e-02],
         [-4.79751676e-02],
         [-4.31981049e-02],
         [ 5.59145510e-02],
         [ 2.21840777e-02]],

        [[ 2.24545449e-02],
         [ 3.01421359e-02],
         [ 2.16735620e-02],
         [ 2.19308957e-02],
         [-7.71658169e-03],
         [ 6.28607348e-02],
         [ 4.03802432e-02],
         [-4.74629365e-02],
         [ 7.99785331e-02],
         [-1.81037392e-02],
         [ 3.98379634e-04],
         [-6.96897507e-02],
         [ 5.49660176e-02],
         [ 3.85488421e-02],
         [-4.49967943e-02],
         [-2.32587140e-02],
         [ 1.37887746e-02],
         [-2.40776036e-02],
         [ 1.09806910e-01],
         [ 3.57907228e-02],
         [-1.21551137e-02],
         [-3.74138653e-02],
         [-5.34016779e-03],
         [-3.01455203e-02],
         [-4.89027463e-02],
         [ 2.70871483e-02],
         [ 6.10283762e-02],
         [-3.82636394e-03],
         [ 8.15920085e-02],
         [-2.30942778e-02],
         [-9.46761891e-02],
         [ 9.62975994e-02],
         [ 4.25142273e-02],
         [-1.23103475e-02],
         [ 4.39722165e-02],
         [ 4.89160083e-02],
         [-2.90802810e-02],
         [ 5.94345853e-02],
         [-5.54624721e-02],
         [ 1.66914668e-02],
         [ 4.32006530e-02],
         [ 5.37383147e-02],
         [-8.70558843e-02],
         [ 4.36952487e-02],
         [ 2.13694703e-02],
         [-5.39011881e-02],
         [-6.08610548e-02],
         [ 5.83639480e-02],
         [ 5.38573638e-02],
         [ 6.79488257e-02],
         [ 9.39037725e-02],
         [-5.80041371e-02],
         [-2.95949485e-02],
         [ 8.51060525e-02],
         [ 1.23114586e-02],
         [-8.96088555e-02],
         [-2.88507994e-02],
         [ 1.11599609e-01],
         [-5.74864969e-02],
         [-4.21722978e-02],
         [-7.64359012e-02],
         [ 9.28215906e-02],
         [ 4.37966362e-02],
         [ 7.60971084e-02]],

        [[-5.35072535e-02],
         [-6.41290247e-02],
         [-3.85311320e-02],
         [-1.03380136e-01],
         [-4.39892113e-02],
         [-4.43869308e-02],
         [-4.94810678e-02],
         [ 9.46167335e-02],
         [-1.57511979e-02],
         [-1.63286701e-02],
         [-9.86264125e-02],
         [-5.01603149e-02],
         [-1.01962529e-01],
         [ 1.11838602e-01],
         [-3.07970755e-02],
         [-9.53416228e-02],
         [ 4.98624481e-02],
         [ 1.64983347e-02],
         [ 1.93689000e-02],
         [ 3.48367286e-03],
         [-4.96412925e-02],
         [-2.59998143e-02],
         [-4.54113707e-02],
         [-1.51101397e-02],
         [-2.58115269e-02],
         [ 1.32002890e-01],
         [ 2.90627638e-03],
         [-1.00436047e-01],
         [-2.72542406e-02],
         [ 8.11122581e-02],
         [-2.27113180e-02],
         [-6.82953596e-02],
         [ 3.43325250e-02],
         [-7.52680898e-02],
         [-6.51229247e-02],
         [-7.12778494e-02],
         [-6.30191416e-02],
         [ 1.27845956e-02],
         [-1.21085487e-01],
         [ 6.75451458e-02],
         [ 6.07530363e-02],
         [ 3.84489484e-02],
         [-5.18108420e-02],
         [ 2.09613494e-03],
         [-4.93711866e-02],
         [-4.19632578e-03],
         [-1.12524137e-01],
         [ 3.60111380e-03],
         [ 3.30046192e-02],
         [ 1.16819896e-01],
         [-3.27693857e-02],
         [-8.21721554e-02],
         [ 5.84948733e-02],
         [-7.47496635e-03],
         [-9.62942615e-02],
         [ 6.31536320e-02],
         [-2.45993733e-02],
         [ 5.83126470e-02],
         [-6.56180009e-02],
         [-3.93606797e-02],
         [ 5.41243255e-02],
         [-8.78811479e-02],
         [ 3.70404907e-02],
         [ 5.38103767e-02]]],


       [[[-8.33443105e-02],
         [-1.08490951e-01],
         [ 8.40547122e-03],
         [ 2.34352701e-04],
         [-4.45490554e-02],
         [ 3.28225642e-02],
         [-8.11623111e-02],
         [ 8.16695206e-03],
         [ 1.31008709e-02],
         [ 8.75820145e-02],
         [-1.04845082e-02],
         [-7.55394027e-02],
         [-2.61026602e-02],
         [ 4.27795984e-02],
         [ 5.48023060e-02],
         [ 4.83500250e-02],
         [-5.38563170e-02],
         [ 1.12021245e-01],
         [-6.74550459e-02],
         [ 6.31929711e-02],
         [-1.28205374e-01],
         [ 4.46989387e-02],
         [-2.24633534e-02],
         [-4.78574680e-03],
         [-4.61376458e-03],
         [ 9.64879617e-02],
         [ 2.87696607e-02],
         [-6.49207309e-02],
         [-6.67856038e-02],
         [-2.49358062e-02],
         [ 3.29190418e-02],
         [ 1.35109857e-01],
         [ 6.30509481e-02],
         [ 1.05916530e-01],
         [-3.40014719e-03],
         [-4.89773937e-02],
         [-1.09032243e-02],
         [ 8.88702571e-02],
         [ 4.83002476e-02],
         [-4.29139333e-03],
         [-8.03453699e-02],
         [ 8.29263553e-02],
         [-9.93899405e-02],
         [ 7.53106773e-02],
         [ 7.63963759e-02],
         [-8.93050805e-03],
         [-1.00143291e-01],
         [ 7.79831186e-02],
         [ 1.50962099e-02],
         [ 3.30923460e-02],
         [-4.30575898e-03],
         [-6.71484023e-02],
         [-7.10504055e-02],
         [-7.22421408e-02],
         [ 9.67357382e-02],
         [-1.95672400e-02],
         [ 6.44165352e-02],
         [ 7.40575716e-02],
         [-7.41256252e-02],
         [ 1.05303407e-01],
         [ 7.41142109e-02],
         [ 5.14578028e-03],
         [-7.11261481e-02],
         [ 1.91788785e-02]],

        [[-3.54397446e-02],
         [ 9.50234756e-02],
         [ 5.62927425e-02],
         [-7.93001056e-02],
         [ 1.02681629e-02],
         [ 7.53512606e-02],
         [ 4.73592281e-02],
         [-4.18480709e-02],
         [ 6.40762672e-02],
         [ 8.27791542e-02],
         [-2.78857304e-03],
         [ 6.81391135e-02],
         [-7.00430796e-02],
         [ 3.00463667e-04],
         [-7.57566765e-02],
         [ 5.82607761e-02],
         [ 4.76665348e-02],
         [ 1.27359629e-02],
         [ 9.34881717e-02],
         [-6.58634724e-03],
         [ 1.13215121e-02],
         [ 2.58173551e-02],
         [-7.12198243e-02],
         [ 5.20463437e-02],
         [-5.71541227e-02],
         [ 2.80030398e-03],
         [-7.11642131e-02],
         [ 4.65252288e-02],
         [-4.32433821e-02],
         [ 6.13203421e-02],
         [ 5.62695079e-02],
         [ 9.71831828e-02],
         [ 9.56286676e-03],
         [-9.08334553e-03],
         [-3.84150557e-02],
         [ 8.89872015e-02],
         [-7.90830106e-02],
         [-1.54832134e-03],
         [-7.98512992e-05],
         [ 6.15480356e-02],
         [ 4.57436638e-03],
         [ 9.57061723e-02],
         [-1.55016277e-02],
         [-5.25686294e-02],
         [ 7.43712932e-02],
         [-4.88292426e-03],
         [-6.60458952e-02],
         [-8.63547903e-03],
         [ 2.62735169e-02],
         [-1.10283811e-02],
         [ 3.50092864e-03],
         [-1.11859692e-02],
         [-8.33176672e-02],
         [-3.67586203e-02],
         [-5.31184077e-02],
         [ 9.42410678e-02],
         [-5.18292263e-02],
         [-4.69191968e-02],
         [-4.05046418e-02],
         [ 7.86125064e-02],
         [-1.04141928e-01],
         [ 2.84299795e-02],
         [ 8.88823196e-02],
         [-3.27621140e-02]],

        [[-5.57611249e-02],
         [ 5.85785657e-02],
         [ 4.45619598e-02],
         [-6.99062794e-02],
         [ 9.84354392e-02],
         [ 1.61311813e-02],
         [-2.96146851e-02],
         [-2.96210647e-02],
         [ 9.01201647e-03],
         [-1.97260417e-02],
         [-3.52343395e-02],
         [ 5.13043627e-02],
         [ 6.11215048e-02],
         [-4.49307190e-05],
         [ 7.32635409e-02],
         [-7.41851330e-02],
         [-9.27845240e-02],
         [-3.26115154e-02],
         [-8.30762684e-02],
         [ 5.69145270e-02],
         [-8.47865455e-03],
         [ 5.75679727e-02],
         [-7.22152088e-03],
         [ 8.23324025e-02],
         [-2.14550719e-02],
         [-5.74912541e-02],
         [-7.64592215e-02],
         [-2.33516041e-02],
         [ 4.51716371e-02],
         [-3.41203846e-02],
         [-2.16088407e-02],
         [ 2.67642345e-02],
         [-5.26960902e-02],
         [-2.73992196e-02],
         [ 2.14359127e-02],
         [-5.14464490e-02],
         [ 5.86206131e-02],
         [-5.64844236e-02],
         [-7.49528036e-02],
         [-8.14052820e-02],
         [ 3.51803266e-02],
         [ 3.56260799e-02],
         [-1.75548960e-02],
         [ 5.63306957e-02],
         [-1.15091819e-02],
         [-2.41696164e-02],
         [-7.37223327e-02],
         [ 1.77147910e-02],
         [-5.74358217e-02],
         [ 1.05845025e-02],
         [ 9.32808891e-02],
         [ 1.48717761e-02],
         [-6.11596927e-02],
         [-6.47523701e-02],
         [ 5.63578233e-02],
         [ 8.69195685e-02],
         [-3.31594434e-04],
         [-5.44762686e-02],
         [-1.13427028e-01],
         [-1.69770233e-02],
         [-8.55797678e-02],
         [ 4.18662652e-02],
         [-3.72332372e-02],
         [ 3.81099246e-02]]],


       [[[-1.05229169e-01],
         [-9.34616923e-02],
         [-5.09723602e-03],
         [ 7.43007213e-02],
         [ 8.42370316e-02],
         [ 7.30853975e-02],
         [ 8.74236152e-02],
         [ 9.82104391e-02],
         [-4.63129170e-02],
         [-7.28046522e-02],
         [ 1.71566512e-02],
         [-8.47148895e-02],
         [ 8.63868860e-04],
         [-3.86206806e-02],
         [-7.32771866e-03],
         [ 6.59865746e-03],
         [-1.09673239e-01],
         [-4.16822024e-02],
         [ 8.50692689e-02],
         [ 8.04073662e-02],
         [-7.44774053e-03],
         [-8.35493505e-02],
         [ 8.72120857e-02],
         [-8.30999911e-02],
         [ 6.54337332e-02],
         [-7.37120584e-02],
         [ 6.62651435e-02],
         [-9.24154297e-02],
         [ 4.85795513e-02],
         [-9.16432869e-03],
         [ 1.61225237e-02],
         [-7.05027059e-02],
         [-1.22367576e-01],
         [ 1.72050316e-02],
         [-1.10706620e-01],
         [ 8.08818266e-02],
         [ 2.04912070e-02],
         [ 8.88728425e-02],
         [-8.61009434e-02],
         [-7.24704266e-02],
         [ 3.74787161e-03],
         [-7.09815323e-03],
         [ 6.04264401e-02],
         [-7.09804893e-02],
         [ 2.92222877e-03],
         [-5.06285317e-02],
         [-5.98785542e-02],
         [-9.29501355e-02],
         [-5.46483509e-03],
         [-5.76444529e-02],
         [ 8.88047889e-02],
         [ 6.01406693e-02],
         [ 4.98300306e-02],
         [-5.81307374e-02],
         [ 5.96606918e-02],
         [ 3.87964062e-02],
         [ 7.81132579e-02],
         [-4.82198112e-02],
         [-3.78706791e-02],
         [-2.87772976e-02],
         [ 7.84582272e-02],
         [ 3.60200517e-02],
         [-2.46626604e-02],
         [ 4.97883223e-02]],

        [[ 6.04970306e-02],
         [-9.12446305e-02],
         [-7.99121931e-02],
         [-5.09897545e-02],
         [-3.32712345e-02],
         [-2.80995611e-02],
         [ 8.58178958e-02],
         [ 7.50768036e-02],
         [-3.69828455e-02],
         [ 1.26319319e-01],
         [-6.12799823e-02],
         [ 8.08044896e-03],
         [-9.89633724e-02],
         [ 6.24127537e-02],
         [-3.02360523e-02],
         [-6.66694343e-02],
         [ 2.81338245e-02],
         [-1.70013346e-02],
         [ 6.80196360e-02],
         [ 8.00242424e-02],
         [-1.69122387e-02],
         [-7.16185346e-02],
         [ 4.25948091e-02],
         [ 1.02634899e-01],
         [-1.99860744e-02],
         [ 6.12901673e-02],
         [-6.20474815e-02],
         [ 4.81890664e-02],
         [ 3.88343185e-02],
         [ 3.61422487e-02],
         [ 1.16279535e-02],
         [ 5.64449131e-02],
         [-7.83450007e-02],
         [-5.71236685e-02],
         [ 7.96366408e-02],
         [ 4.98043932e-02],
         [-6.26768470e-02],
         [ 7.80416355e-02],
         [ 3.09457667e-02],
         [ 8.00354034e-02],
         [-6.75120950e-02],
         [-2.75670048e-02],
         [ 8.02919865e-02],
         [-8.96557271e-02],
         [ 7.17827827e-02],
         [-1.05816789e-01],
         [ 9.62352976e-02],
         [-8.19472149e-02],
         [-2.30656378e-02],
         [-5.24449833e-02],
         [ 5.33927642e-02],
         [-9.32961479e-02],
         [-2.65900530e-02],
         [-8.83844197e-02],
         [-1.19070234e-02],
         [-2.25417432e-04],
         [ 9.59895737e-03],
         [ 4.96427305e-02],
         [ 9.63286161e-02],
         [ 1.11717835e-01],
         [-8.36266056e-02],
         [ 6.18445985e-02],
         [ 4.41668381e-04],
         [-4.06439230e-02]],

        [[ 6.92014322e-02],
         [-8.24661851e-02],
         [-8.73225033e-02],
         [-4.09141593e-02],
         [ 1.03036225e-01],
         [ 8.31263363e-02],
         [ 3.57812420e-02],
         [ 2.55878754e-02],
         [-1.04636483e-01],
         [-5.94092309e-02],
         [-1.06684223e-01],
         [ 5.87755218e-02],
         [-1.04046449e-01],
         [-4.86880392e-02],
         [ 3.95626901e-03],
         [ 8.29005688e-02],
         [ 2.61076819e-02],
         [-7.16489628e-02],
         [ 5.04278876e-02],
         [-4.01914008e-02],
         [ 4.34951000e-02],
         [-8.18920359e-02],
         [ 6.24137092e-03],
         [ 2.91937608e-02],
         [-7.82760978e-02],
         [-5.79367541e-02],
         [-4.57278565e-02],
         [-9.77765992e-02],
         [ 8.25074539e-02],
         [ 6.86460882e-02],
         [-6.03135712e-02],
         [-7.72911385e-02],
         [ 3.10084615e-02],
         [-2.08190344e-02],
         [-6.95029572e-02],
         [-4.69970852e-02],
         [ 9.05495659e-02],
         [-3.76016251e-03],
         [ 4.58515026e-02],
         [ 9.71717164e-02],
         [ 1.13412417e-01],
         [-4.75829514e-03],
         [-6.84076697e-02],
         [ 8.52241889e-02],
         [ 7.24513037e-03],
         [-4.06628475e-02],
         [ 2.07248125e-02],
         [ 6.98724911e-02],
         [ 2.96426043e-02],
         [ 7.12593645e-02],
         [-1.32691544e-02],
         [ 7.95685053e-02],
         [ 9.82115883e-03],
         [ 2.19095889e-02],
         [ 5.44872358e-02],
         [-6.38932735e-02],
         [-1.04569897e-01],
         [ 6.05842397e-02],
         [ 1.17898211e-02],
         [-2.68453336e-03],
         [ 2.64957957e-02],
         [ 7.79954568e-02],
         [-9.23764035e-02],
         [ 4.13578711e-02]]]], dtype=float32), array([0.97973436, 1.0077293 , 0.9917283 , 1.0164683 , 1.0395056 ,
       1.0041186 , 1.0124846 , 1.0019019 , 0.9899879 , 1.0180072 ,
       1.0186169 , 1.0093735 , 1.022379  , 0.9935312 , 0.9815246 ,
       0.99082917, 0.9654472 , 0.99559426, 1.0132579 , 0.9950731 ,
       1.0329903 , 0.9732024 , 0.9850467 , 1.0195589 , 1.0140377 ,
       0.971174  , 0.9990376 , 0.9728655 , 0.9954254 , 0.9902654 ,
       0.98858035, 1.0302832 , 0.99904794, 0.9956694 , 1.0130426 ,
       1.0073528 , 0.99487704, 0.99915427, 1.0227762 , 1.000037  ,
       1.0018786 , 1.000309  , 0.992465  , 1.0004394 , 1.0041143 ,
       1.0149915 , 0.9932012 , 0.9816357 , 0.9899602 , 0.95609945,
       0.995365  , 1.0106428 , 1.0114844 , 1.0017976 , 1.0211681 ,
       0.99926925, 0.9837889 , 1.0312722 , 0.9674466 , 1.0212238 ,
       1.0074753 , 0.9866609 , 0.9949067 , 0.98537225], dtype=float32), array([-0.00109517,  0.01377786,  0.0299959 ,  0.01557614,  0.0153412 ,
        0.00992106, -0.00743466, -0.02002155, -0.00964171, -0.00281503,
        0.01959005,  0.01651382,  0.05059163, -0.01230305,  0.00473617,
        0.00718779, -0.01603626,  0.00094636,  0.01166142,  0.00490234,
        0.01570559,  0.00473486, -0.02326408,  0.03465236,  0.00405427,
       -0.00947107,  0.01054529, -0.03353858, -0.00253421, -0.01956925,
        0.02077661,  0.04853246, -0.00409037,  0.0122213 ,  0.00587655,
       -0.02497185, -0.01427479, -0.01057265,  0.02301552, -0.00881556,
        0.00592428, -0.01701007, -0.00267839,  0.01801619,  0.02385394,
        0.01879196, -0.00832207, -0.00053784, -0.01385561, -0.04288378,
       -0.00697602, -0.01067808,  0.02956139, -0.01007131,  0.00536364,
       -0.01046281, -0.01067982,  0.0111186 , -0.01849339,  0.0105506 ,
        0.01422894, -0.01564467,  0.00943367, -0.00328238], dtype=float32), array([-0.07458672, -0.09768756, -0.04098741, -0.11360011,  0.08065206,
        0.08077639,  0.0671835 ,  0.03495861, -0.02094752,  0.02352576,
       -0.10084669, -0.03559919, -0.0974726 ,  0.02118153, -0.03148687,
       -0.04677176, -0.03637561,  0.00895113,  0.10273877,  0.105799  ,
       -0.05883735, -0.05677633, -0.02361501,  0.05635911, -0.04408528,
        0.01971925, -0.04420562, -0.07384243,  0.05581579,  0.10941599,
       -0.00866966,  0.09384894, -0.06966656,  0.00477459, -0.0710832 ,
        0.04542485, -0.04120378,  0.08772491, -0.08349738,  0.04853115,
        0.06400436,  0.1109085 , -0.07106021,  0.07054985,  0.10327481,
       -0.122734  , -0.11940797, -0.0268347 ,  0.03591372,  0.05217458,
        0.08829794, -0.08752938, -0.09332488, -0.06585097,  0.05076955,
        0.01225921, -0.02805666,  0.08088542, -0.09859977,  0.07279489,
       -0.05505406,  0.0683588 ,  0.00128641,  0.07076886], dtype=float32), array([0.03231842, 0.02932146, 0.01185444, 0.04486344, 0.0371462 ,
       0.03112459, 0.01914813, 0.01393114, 0.01085773, 0.01088715,
       0.03668096, 0.01716037, 0.04219563, 0.01186325, 0.01290079,
       0.01884948, 0.01280558, 0.01107499, 0.03415933, 0.04403335,
       0.01236436, 0.01279562, 0.01066159, 0.02470106, 0.01529414,
       0.0089271 , 0.01311542, 0.03298334, 0.01122037, 0.02971445,
       0.01008477, 0.02155704, 0.01187485, 0.01221474, 0.01108235,
       0.02195179, 0.00945798, 0.05226123, 0.01473177, 0.01910839,
       0.02088309, 0.04691229, 0.01122241, 0.02280613, 0.03458178,
       0.05876862, 0.01580777, 0.01179139, 0.01458656, 0.01764629,
       0.02008551, 0.02299994, 0.01565627, 0.03018578, 0.01122714,
       0.00785194, 0.01444467, 0.02298277, 0.03894144, 0.03353228,
       0.01252195, 0.01258503, 0.00920734, 0.00981453], dtype=float32), array([[[[-5.22472709e-02,  1.45377964e-01, -1.44265622e-01, ...,
           6.18325360e-02, -1.36974528e-01,  1.92266181e-01],
         [-1.38102785e-01, -5.17016985e-02, -9.83625725e-02, ...,
          -4.75341193e-02, -1.44348472e-01, -1.35099024e-01],
         [ 8.46700370e-02, -5.80410026e-02, -1.59126982e-01, ...,
          -1.17907405e-01,  5.64498976e-02, -7.34321922e-02],
         ...,
         [-1.87698394e-01,  8.40396732e-02, -4.45328429e-02, ...,
          -7.50208199e-02,  8.04523155e-02, -2.09410377e-02],
         [-4.04506063e-05,  5.04303314e-02,  1.51658937e-01, ...,
          -1.11197814e-01,  1.03202745e-01, -1.76712759e-02],
         [-3.56882550e-02, -1.47608131e-01,  1.34881049e-01, ...,
          -8.84314328e-02,  3.53758037e-02, -1.32619113e-01]]]],
      dtype=float32), array([1.0120953 , 1.0142627 , 0.9877505 , 0.9901661 , 0.98111457,
       0.97466964, 1.0015996 , 0.9880226 , 0.994657  , 0.9855441 ,
       1.0207405 , 1.0088116 , 0.99655575, 1.0175217 , 1.0136086 ,
       0.98158073, 0.99336517, 0.98618734, 1.0103773 , 1.0212581 ,
       1.006344  , 0.99913806, 1.0028139 , 1.0322974 , 1.0041765 ,
       1.0141828 , 1.0091285 , 1.0242306 , 1.0102658 , 0.9876347 ,
       0.98956174, 1.0237448 , 0.97922   , 1.0246935 , 1.0103126 ,
       0.99114555, 0.9776425 , 0.9971975 , 1.0061604 , 1.0009568 ,
       1.0001535 , 1.0166091 , 0.9913108 , 0.98646694, 0.9889582 ,
       0.9958462 , 1.0052055 , 0.9997494 , 0.9993264 , 0.9994134 ,
       1.0001544 , 1.0102925 , 0.9983292 , 1.0108137 , 0.9955772 ,
       1.0069058 , 0.990949  , 1.0115675 , 0.9708382 , 1.0297177 ,
       1.0050864 , 1.0272648 , 1.0133318 , 1.0176237 , 0.9892827 ,
       1.0220255 , 1.001351  , 1.0073564 , 0.9707626 , 0.9941118 ,
       1.0321126 , 0.9985361 , 1.0047839 , 1.0020295 , 0.9964256 ,
       1.0066391 , 1.0131629 , 0.97407997, 0.96786743, 1.0130235 ,
       0.9873059 , 1.0154562 , 0.9823157 , 0.98370117, 1.0065548 ,
       0.984999  , 0.99765897, 0.98911786, 1.0187637 , 0.98234993,
       0.9923913 , 1.0149553 , 0.99890465, 1.0007385 , 1.0115432 ,
       1.0238823 , 0.9836397 , 1.0085441 , 0.9970719 , 1.0122447 ,
       0.97374505, 0.989399  , 0.9855868 , 0.99386257, 0.9755637 ,
       0.99990773, 0.98881716, 0.97943014, 1.0259032 , 0.9973752 ,
       1.0060939 , 0.9911906 , 1.0103544 , 0.9826654 , 0.97697   ,
       1.0081688 , 1.0062662 , 0.99161327, 1.0198158 , 0.9866104 ,
       1.0160967 , 1.0169348 , 0.989676  , 0.9900339 , 0.9923925 ,
       0.9906448 , 0.99672633, 0.9931613 ], dtype=float32), array([ 0.0154781 ,  0.01132477, -0.02652795, -0.03015235,  0.0147311 ,
       -0.04147452, -0.00984271,  0.01379541, -0.00051878, -0.01173416,
       -0.00211727,  0.00691985, -0.02349628,  0.00546432,  0.00057805,
       -0.0052025 ,  0.03143073,  0.01501629, -0.01199154,  0.01273432,
        0.01331461, -0.01164118, -0.01120931,  0.02030892,  0.01665234,
        0.00791563, -0.00783635,  0.02158372, -0.00310035, -0.00541796,
       -0.01763911,  0.00246234,  0.04334062,  0.00850171, -0.00326799,
        0.01231885, -0.01449198,  0.00011638, -0.0186015 ,  0.00318825,
        0.01516371,  0.00170099, -0.01852018,  0.03303117, -0.00764141,
        0.01396958, -0.01810666,  0.01898752,  0.02319832, -0.03242633,
       -0.00212782, -0.0034324 ,  0.01035753,  0.01144623,  0.03008356,
        0.01485716, -0.00637113,  0.00706541, -0.00486966,  0.00375392,
       -0.0116172 , -0.00224539, -0.01183338, -0.00675378, -0.00661285,
       -0.00085956,  0.03413973,  0.03573604, -0.00926059, -0.0338167 ,
        0.04893193, -0.02299807,  0.01029699, -0.00157973, -0.02304801,
       -0.0203936 ,  0.00499489, -0.00787132,  0.00279039, -0.02494604,
       -0.00091487,  0.01895913,  0.03349843,  0.02145119,  0.00480773,
       -0.00981353,  0.00456726, -0.00750225,  0.00034726,  0.0055261 ,
        0.02763321,  0.0006099 , -0.0122572 ,  0.01591199, -0.00194841,
        0.02117793, -0.01117745, -0.00503334, -0.00734637,  0.01071079,
        0.02897871, -0.02270937, -0.00891243, -0.00408631, -0.00784631,
        0.00447617,  0.01916443,  0.00399177,  0.00416529, -0.02516957,
        0.01070135, -0.00364253,  0.01659903, -0.02433075, -0.01612385,
       -0.01373401, -0.02706265,  0.00440403, -0.01435933, -0.01695905,
       -0.0184971 ,  0.01820164,  0.00915143,  0.00851781, -0.00723261,
       -0.04866242, -0.0172497 , -0.02812107], dtype=float32), array([-0.25437438,  0.4108471 ,  0.18796219,  0.09703656,  0.17090307,
        0.09719785,  0.1706612 ,  0.10019141,  0.01590112,  0.09129512,
       -0.27054572, -0.09271769,  0.33696356, -0.1409452 , -0.15959823,
        0.17973192,  0.10379064, -0.2899249 , -0.33771738,  0.18929392,
       -0.26822993,  0.5201404 , -0.02990247,  0.0850772 ,  0.1172784 ,
       -0.2667607 ,  0.38498968,  0.0213436 ,  0.16213264, -0.05560765,
        0.23895451,  0.21535513,  0.01627783, -0.22585137,  0.4963437 ,
        0.05723444, -0.01708693,  0.20764033,  0.3150203 ,  0.30374715,
       -0.24295314,  0.20926403,  0.06152204, -0.25226155,  0.16304854,
        0.07079279,  0.23559454,  0.06490917, -0.4026761 , -0.42352402,
       -0.25903133, -0.36123967,  0.33072066, -0.59851456, -0.3037223 ,
       -0.01718755, -0.47653383,  0.35936403,  0.5979123 ,  0.5618323 ,
        0.24802572, -0.16830406, -0.41543654, -0.00876712,  0.11322314,
        0.1929116 , -0.20714554, -0.05343348, -0.0999098 ,  0.15237935,
       -0.21332988, -0.455579  ,  0.05658843, -0.07532433,  0.12770215,
        0.5073648 ,  0.6401794 , -0.07445304,  0.06894745, -0.02116107,
        0.48238203,  0.0992024 , -0.02285702, -0.38498726,  0.00956684,
        0.05280525,  0.06289091, -0.03714803, -0.14503093,  0.17407878,
       -0.23038699,  0.03362926, -0.05043451, -0.4081461 , -0.33003438,
       -0.02649973, -0.21449415, -0.13690248,  0.41305688, -0.39850584,
       -0.5072481 ,  0.2387603 ,  0.14800799,  0.392138  ,  0.22706693,
       -0.10913588, -0.21011627, -0.06234475,  0.30198193,  0.83318734,
        0.05271772,  0.1633768 ,  0.29742742, -0.03519098,  0.09678081,
       -0.2434464 , -0.85960543,  0.12519592,  0.32391366, -0.18779474,
        0.2839975 ,  0.19911987,  0.63897866,  0.15956001,  0.46819395,
        0.41650316,  0.5773484 ,  0.20636539], dtype=float32), array([0.2939981 , 0.5216473 , 0.23104633, 0.4029951 , 0.21974866,
       0.39059156, 0.25840843, 0.32937378, 0.21813774, 0.13594778,
       0.18155672, 0.2615773 , 0.46927163, 0.41831005, 0.3003646 ,
       0.18210472, 0.14887606, 0.30911472, 0.7343222 , 0.15732   ,
       0.13987134, 0.24689251, 0.5655777 , 0.14119752, 0.21179096,
       0.3264151 , 0.26646444, 0.20062445, 0.12647435, 0.16102688,
       0.2237304 , 0.15602764, 0.2549845 , 0.17214996, 0.2316451 ,
       0.29128584, 0.15754947, 0.23793396, 0.24132037, 0.21894044,
       0.24068715, 0.510257  , 0.11578706, 0.37718734, 0.22300385,
       0.20659602, 0.17777862, 0.23097157, 0.33176923, 0.26116297,
       0.29286706, 0.245136  , 0.1041465 , 0.40965885, 0.59941524,
       0.17016207, 0.19677565, 0.25000703, 0.40585887, 0.34065315,
       0.47135708, 0.10556667, 0.22712524, 0.21166717, 0.2396511 ,
       0.44748497, 0.2078294 , 0.21039174, 0.27116287, 0.21504118,
       0.20399661, 0.14483492, 0.25453505, 0.33955795, 0.29928833,
       0.17330338, 0.3387605 , 0.10003706, 0.15267123, 0.19565725,
       0.14230289, 0.1463857 , 0.24882507, 0.21177042, 0.33921948,
       0.356418  , 0.2076193 , 0.21128382, 0.36442086, 0.17706105,
       0.12362435, 0.24970455, 0.18639566, 0.19265209, 0.5021536 ,
       0.55443025, 0.30247396, 0.17184344, 0.20336728, 0.3744557 ,
       0.5628381 , 0.29352602, 0.26452255, 0.138657  , 0.14466506,
       0.53178906, 0.2674763 , 0.3113608 , 0.15463798, 0.30532992,
       0.3177177 , 0.15240343, 0.13776729, 0.14916566, 0.40242007,
       0.30863306, 0.5474481 , 0.23490773, 0.2264481 , 0.2484063 ,
       0.3703512 , 0.40907708, 0.26427314, 0.2589362 , 0.3306297 ,
       0.2893491 , 0.68924266, 0.15268932], dtype=float32), array([[[[ 0.0539665 ],
         [-0.07022564],
         [-0.01310894],
         ...,
         [-0.05576419],
         [ 0.02415404],
         [ 0.06597373]],

        [[ 0.03635123],
         [-0.03724016],
         [ 0.02051994],
         ...,
         [ 0.03748759],
         [ 0.02052078],
         [ 0.03445964]],

        [[ 0.03213444],
         [-0.00262149],
         [-0.04825363],
         ...,
         [ 0.0549885 ],
         [-0.04226449],
         [-0.02533004]]],


       [[[ 0.06540736],
         [ 0.06165644],
         [-0.06323851],
         ...,
         [ 0.03176455],
         [ 0.07878605],
         [ 0.00351474]],

        [[-0.00946215],
         [ 0.00928935],
         [-0.03470292],
         ...,
         [-0.04214735],
         [-0.02690222],
         [-0.06633429]],

        [[ 0.04364247],
         [ 0.08142173],
         [-0.00064307],
         ...,
         [-0.02837368],
         [ 0.04891985],
         [-0.07029362]]],


       [[[-0.02742201],
         [ 0.00549335],
         [ 0.04086323],
         ...,
         [-0.00158216],
         [ 0.06776708],
         [ 0.06085123]],

        [[-0.02877881],
         [ 0.03971192],
         [-0.03618682],
         ...,
         [-0.04458491],
         [ 0.01119793],
         [-0.03491483]],

        [[ 0.01155528],
         [ 0.01640042],
         [ 0.03466531],
         ...,
         [-0.06000936],
         [-0.00581672],
         [-0.01906325]]]], dtype=float32), array([1.0114269 , 1.0162553 , 0.98833054, 0.978193  , 0.9833854 ,
       0.97682184, 1.0053478 , 0.98695016, 0.9983822 , 0.97941095,
       1.0228803 , 1.0002366 , 0.98587364, 1.012256  , 1.0170507 ,
       0.9890943 , 1.0002656 , 0.9880355 , 1.0112907 , 1.0285343 ,
       1.0075899 , 1.0021269 , 0.9951011 , 1.0193119 , 0.9952396 ,
       1.0115752 , 1.0054184 , 1.0193992 , 1.0027251 , 0.9786433 ,
       0.9913911 , 1.0162339 , 0.98060703, 1.0153252 , 1.0048254 ,
       0.9909389 , 0.9832989 , 0.9869783 , 1.0054482 , 0.9923164 ,
       0.9940738 , 1.0298032 , 0.97812474, 0.9879187 , 0.9968827 ,
       1.000081  , 1.0128924 , 0.98740745, 0.99494654, 0.9957126 ,
       0.9953927 , 1.0135881 , 0.99741226, 1.0001258 , 0.9934811 ,
       0.9896659 , 0.99279267, 1.0239427 , 0.9610524 , 1.03241   ,
       1.0057187 , 1.0260851 , 1.0128582 , 1.0094175 , 0.9802084 ,
       1.0301037 , 1.0083208 , 1.0361724 , 0.9786895 , 0.9937039 ,
       1.0404155 , 1.0059314 , 0.99740046, 0.98962635, 0.9963955 ,
       1.0229822 , 0.9875508 , 1.0047582 , 0.97076595, 0.9850462 ,
       0.9764875 , 1.001457  , 1.0023566 , 0.97658765, 1.0005922 ,
       0.97350687, 0.99415845, 1.0021778 , 1.0133504 , 1.0037141 ,
       0.99535674, 1.0111719 , 1.0020058 , 1.009904  , 1.0183829 ,
       1.0134605 , 0.9807605 , 1.0054806 , 1.0036976 , 1.015001  ,
       0.97936255, 0.9820244 , 1.0024257 , 0.99109614, 0.97154266,
       0.99847704, 0.99156123, 0.97834873, 1.0298107 , 0.9957734 ,
       1.0153663 , 0.99468637, 1.0213647 , 0.9778534 , 0.99039066,
       1.0105054 , 1.0130807 , 0.98827255, 1.0042719 , 0.9823556 ,
       1.0442582 , 1.0233796 , 0.99822587, 0.98806053, 0.9863808 ,
       0.99883974, 1.0178953 , 1.0029752 ], dtype=float32), array([ 2.24679466e-02,  3.16342451e-02, -3.89535655e-03, -2.63136309e-02,
        5.00802556e-03,  5.93586499e-03,  4.27471288e-02, -9.74938832e-03,
        6.26306515e-03, -1.65079720e-02,  1.74834952e-02, -7.75779271e-03,
       -1.31991191e-03,  1.10025620e-02,  3.45523059e-02, -2.41431780e-02,
        2.88900957e-02,  3.35534755e-03, -2.26520915e-02,  3.22702061e-03,
        1.39185796e-02, -1.34122539e-02, -1.55779738e-02, -2.83837691e-03,
       -1.39046402e-03, -5.25185060e-05, -6.66951807e-03,  3.18831317e-02,
        9.89380758e-04, -2.80580632e-02, -4.95200558e-03,  1.74066741e-02,
        1.40983257e-02, -8.16567056e-03,  3.88644985e-03, -6.13656500e-03,
        8.28579720e-03,  4.58640046e-04,  3.72059494e-02, -2.44500814e-04,
        6.09313743e-03,  4.70783561e-03, -2.20654253e-02,  1.87921003e-02,
        8.71942658e-03,  1.85450613e-02, -9.57068335e-03,  1.66211161e-03,
       -1.23597989e-02,  3.17119025e-02, -2.03238241e-03, -7.64173688e-04,
       -5.39097842e-03, -8.65663216e-03,  3.61225917e-03, -1.78330187e-02,
       -2.49596778e-02,  2.10913885e-02, -3.35642695e-02,  3.04131154e-02,
       -2.39624027e-02, -1.16237206e-02, -3.42692249e-03,  3.10363062e-02,
       -1.95737761e-02,  5.57149053e-02,  1.81829073e-02,  5.24832904e-02,
       -1.58912279e-02,  1.98725853e-02,  4.01106812e-02,  3.11943945e-02,
        1.15947966e-02, -1.04799485e-02,  3.69893052e-02,  1.86916336e-03,
       -1.05222454e-02, -1.11531210e-03, -2.40182001e-02, -5.25790406e-03,
       -1.66462399e-02,  5.65530267e-03, -1.69110615e-02,  1.12805897e-02,
        8.08261149e-03, -2.51895729e-02,  2.50775134e-03,  2.46954942e-03,
       -3.24670621e-03,  1.00039784e-02,  4.95104492e-03,  1.08739745e-03,
       -2.80985665e-02,  9.06645693e-03,  2.20312681e-02,  2.77274270e-02,
       -1.75799243e-02,  5.23746639e-05, -7.48126442e-03,  2.26438120e-02,
        2.96365889e-03, -1.76250245e-02, -8.24174006e-03,  2.64003244e-03,
       -2.49445741e-03, -2.57652123e-02, -1.37907509e-02, -1.12858126e-02,
        1.09086474e-02,  7.42573990e-03,  1.75359827e-02, -1.24891168e-02,
        3.91070032e-03, -3.47585604e-03,  2.55367383e-02, -5.08447876e-03,
        6.19679037e-03,  2.64695962e-03,  3.92898498e-03, -1.21489251e-02,
        1.14738727e-02,  7.37834303e-03, -7.50067830e-03, -1.69090852e-02,
        2.03494411e-02,  3.58540239e-03, -1.47273857e-02, -7.63883581e-03],
      dtype=float32), array([ 0.06089081,  0.03085962, -0.02921203,  0.02738748, -0.01743134,
       -0.04018721,  0.00475666, -0.02406067, -0.07989486, -0.05735929,
        0.04573452,  0.1220663 , -0.02333371, -0.01419826, -0.07030837,
        0.00672533, -0.01968392,  0.06058376,  0.02870579,  0.02582179,
       -0.03488709,  0.04800505,  0.00507145,  0.0740409 , -0.03774479,
       -0.08552174, -0.03345773,  0.09207834,  0.05402902, -0.04178369,
       -0.04665389,  0.07328028,  0.08919529,  0.02062912, -0.04612722,
        0.05148789, -0.0102356 , -0.04651649, -0.03392752,  0.00760774,
        0.03972061,  0.05026579, -0.10372794, -0.07881396, -0.04307534,
        0.03480926, -0.04759162,  0.08097841, -0.02571418, -0.04293397,
        0.00973901,  0.0679826 , -0.08036482, -0.06272249, -0.01861765,
       -0.05340055,  0.03591985,  0.02408637, -0.06453644, -0.09693348,
        0.04763549,  0.00353859,  0.07084949, -0.03778341,  0.05437389,
       -0.05306593, -0.02580125,  0.12897944,  0.04556532, -0.01493301,
       -0.02696431, -0.0481002 ,  0.07933611, -0.1164697 , -0.06496481,
        0.04344435,  0.04514308,  0.01010697, -0.01586279, -0.00726637,
        0.10877123,  0.02900031, -0.13499627,  0.08318085,  0.01465817,
       -0.03572926, -0.08261526, -0.06668368,  0.0004    ,  0.09262487,
       -0.04087761,  0.03705108,  0.05798926, -0.06393643,  0.05183551,
        0.0513697 , -0.05720476,  0.05359577,  0.01401042,  0.05866227,
       -0.04862349, -0.0335286 , -0.03176119, -0.04654885,  0.03198295,
       -0.02096446,  0.04703381,  0.08437427,  0.03333191, -0.06273604,
       -0.01575958,  0.02421041,  0.01326177,  0.05772928, -0.07181149,
        0.028443  ,  0.06191833, -0.03867354,  0.00705867, -0.03965261,
        0.05389276, -0.11083456, -0.03211973, -0.07593835, -0.06791608,
       -0.03104126,  0.05057524, -0.01528594], dtype=float32), array([0.01344419, 0.01460162, 0.00975982, 0.01062353, 0.00978011,
       0.01667778, 0.00757661, 0.01139668, 0.02308171, 0.01092266,
       0.01271005, 0.04851311, 0.015701  , 0.00847746, 0.02537745,
       0.00933076, 0.01045543, 0.00989032, 0.00813723, 0.00918852,
       0.00975221, 0.01472788, 0.00783627, 0.02386365, 0.01196719,
       0.01280271, 0.01378548, 0.03463418, 0.01753473, 0.01082141,
       0.01104465, 0.02036481, 0.02029091, 0.01112737, 0.01482446,
       0.02125116, 0.00845793, 0.01897678, 0.01443554, 0.01021449,
       0.01417192, 0.01577533, 0.04339132, 0.02346629, 0.01194581,
       0.01243046, 0.0114409 , 0.02796569, 0.00845223, 0.00836579,
       0.00861815, 0.02873546, 0.02503697, 0.01198196, 0.00745191,
       0.01669843, 0.0103403 , 0.01083094, 0.0293451 , 0.02636031,
       0.01384655, 0.01109679, 0.01323603, 0.01204072, 0.01623362,
       0.01460693, 0.01099879, 0.03007883, 0.01616585, 0.00869335,
       0.00912715, 0.01104775, 0.02540695, 0.04901018, 0.02590186,
       0.01888276, 0.02253189, 0.00990717, 0.0090603 , 0.01167909,
       0.04498086, 0.01235807, 0.04759426, 0.01419572, 0.01045152,
       0.01158209, 0.02343962, 0.02402147, 0.00852691, 0.0248937 ,
       0.0128186 , 0.00908876, 0.02282777, 0.01189919, 0.00924773,
       0.0088484 , 0.01285242, 0.01968888, 0.00975206, 0.00998276,
       0.0088822 , 0.01042242, 0.0114434 , 0.01463174, 0.0124356 ,
       0.00770929, 0.01475592, 0.01583296, 0.01245076, 0.02097179,
       0.00838081, 0.0093445 , 0.01048755, 0.01787732, 0.03055531,
       0.00848716, 0.01046668, 0.01022847, 0.0088558 , 0.01389035,
       0.02971725, 0.02110096, 0.0130573 , 0.01661171, 0.03349692,
       0.01045398, 0.02493456, 0.01233352], dtype=float32), array([[[[-0.02890042,  0.12482965,  0.08250518, ...,  0.01456838,
          -0.15861547,  0.08041178],
         [ 0.12195809, -0.08875148, -0.01270617, ...,  0.09909873,
           0.03245188,  0.04469257],
         [ 0.09561569, -0.0801645 , -0.01064403, ...,  0.01886643,
          -0.08007185,  0.04409453],
         ...,
         [ 0.05434465, -0.07378934,  0.12069704, ...,  0.13380365,
          -0.0262427 ,  0.1182864 ],
         [-0.06677648,  0.1162613 ,  0.13830782, ..., -0.16073298,
           0.07713398, -0.1224094 ],
         [ 0.03891358,  0.10557069, -0.00822637, ...,  0.13661303,
           0.09764542,  0.12468851]]]], dtype=float32), array([1.0038296 , 1.0080519 , 0.987231  , 0.9934232 , 1.0114594 ,
       0.98804134, 0.9960267 , 0.96482974, 0.9792158 , 0.9773031 ,
       1.0008562 , 1.0125171 , 0.99359196, 0.98170805, 1.0273728 ,
       0.98621595, 1.0101593 , 0.97109604, 1.0027969 , 0.98468786,
       0.99614006, 1.0002005 , 0.99616957, 0.99536836, 1.0060356 ,
       0.9888123 , 1.0269468 , 0.9930542 , 1.0298737 , 1.0090727 ,
       1.0044723 , 1.0085034 , 1.0036356 , 1.0226796 , 0.98691124,
       1.017837  , 0.9946837 , 1.0250522 , 1.0006442 , 0.9903235 ,
       0.9913191 , 1.0046321 , 1.009651  , 0.9950959 , 0.98154205,
       0.99189425, 1.0008763 , 0.9979821 , 1.045756  , 0.9971757 ,
       1.0111073 , 0.99674886, 0.97664326, 0.99658513, 0.9965575 ,
       1.0050186 , 1.0049287 , 1.01072   , 1.0015687 , 1.0193437 ,
       0.99613214, 1.0121665 , 0.9871876 , 0.94541353, 1.0090387 ,
       1.0359296 , 1.0052533 , 0.9920058 , 1.0015682 , 1.0063885 ,
       0.99668753, 0.99067193, 1.0117073 , 1.0162175 , 0.98748404,
       0.9784847 , 0.9954129 , 0.98311853, 1.0176044 , 0.9935307 ,
       1.0145262 , 0.98761827, 1.0119843 , 1.0091785 , 0.9880235 ,
       0.9677123 , 1.031479  , 0.9917051 , 0.98568314, 0.9781993 ,
       0.992951  , 1.0083079 , 1.0204611 , 1.0046136 , 1.0105857 ,
       1.0026147 , 1.0159138 , 1.0158658 , 0.99179673, 1.0119274 ,
       0.98616403, 1.0180339 , 0.99442345, 1.0076623 , 1.0074552 ,
       1.0057265 , 0.9933876 , 1.0026321 , 0.9976941 , 1.0086732 ,
       0.9897472 , 1.0258541 , 1.0067202 , 0.99060225, 1.0075814 ,
       0.98366404, 1.0300949 , 1.0372798 , 0.9947485 , 0.99155504,
       0.9776152 , 0.99134547, 1.0062344 , 0.96473   , 0.9833962 ,
       1.010999  , 0.9912871 , 1.019072  ], dtype=float32), array([ 3.79737816e-04, -4.60424740e-03, -1.18906433e-02, -9.15214885e-03,
       -6.70273043e-03,  5.14962198e-03, -5.12603670e-03,  5.38929505e-03,
        2.85920147e-02, -1.20052253e-03,  7.50141172e-03,  2.25712601e-02,
       -3.95638719e-02,  5.97700551e-02,  7.69664254e-03, -6.15094090e-03,
       -8.47081281e-03,  1.58183537e-02,  4.98032989e-03, -1.56639647e-02,
        3.79222818e-03,  1.61229689e-02,  3.14118490e-02, -1.02671916e-02,
       -2.59788670e-02,  9.29212198e-03,  3.43435556e-02, -1.33606442e-03,
        3.31784296e-03, -1.00007365e-02, -5.64045925e-03, -1.36308083e-02,
        1.47311296e-02,  2.21986081e-02, -2.20800322e-02,  3.25293541e-02,
       -5.17345220e-03,  2.05732603e-02,  1.18724713e-02,  1.74406301e-02,
        9.85853188e-03, -2.78491396e-02,  1.27304578e-03, -6.18858822e-03,
       -2.46778373e-02, -4.67645749e-03, -1.38065163e-02, -5.61502716e-03,
       -1.23825315e-02,  1.08683193e-02, -5.18932659e-03,  9.49778967e-03,
       -3.59687663e-04, -5.46796154e-03,  1.08226016e-02, -1.21592497e-02,
        1.03362622e-02,  1.65331010e-02, -9.97167546e-03, -8.33855302e-04,
       -8.47215299e-03,  3.15830507e-03, -7.16851646e-05,  1.76552329e-02,
        3.12689081e-05, -1.55821843e-02,  7.24821002e-04,  1.58784315e-02,
        4.24894020e-02,  1.54631482e-02, -9.93470196e-03,  3.27921298e-04,
       -1.78407189e-02,  1.11495256e-02,  2.25528814e-02, -3.23888473e-02,
       -4.56020273e-02,  2.76717283e-02, -1.44439889e-02,  9.62352008e-03,
        8.24757479e-03, -3.24168019e-02, -1.16049359e-02, -2.99691614e-02,
       -2.90130433e-02,  2.52671838e-02,  1.87986679e-02, -2.40975115e-02,
        3.55062485e-02, -1.65120326e-02,  6.22943789e-03, -5.39575564e-03,
       -6.17541047e-03, -1.75048281e-02, -2.44621234e-03,  1.71441548e-02,
       -2.01986320e-02,  2.33017057e-02,  3.38290595e-02, -1.62478592e-02,
        6.55434467e-03, -3.30764498e-03,  4.30371007e-03,  3.19265993e-03,
        1.87788985e-03,  1.65865868e-02,  3.46939708e-03,  2.36572828e-02,
        2.37177387e-02,  1.10237366e-02, -2.08424814e-02,  1.26015665e-02,
       -1.71882156e-02,  1.67661521e-03,  2.82136607e-03, -2.44453419e-02,
       -1.90102756e-02, -3.59168253e-03,  2.27034907e-03, -9.91920475e-03,
       -3.70814577e-02,  3.88172502e-03,  7.02711241e-03,  2.87957210e-03,
        3.48899746e-03, -3.08423042e-02, -2.63438839e-02,  1.48276926e-03],
      dtype=float32), array([ 7.71991760e-02,  3.14558655e-01,  8.79025578e-01, -2.50585645e-01,
        2.11435467e-01, -3.01110476e-01,  3.17034632e-01, -7.44835362e-02,
        6.64384440e-02,  1.13960743e-01, -2.46232063e-01, -2.40295395e-01,
        4.28735554e-01, -5.26043236e-01, -6.90641999e-02,  4.13114548e-01,
       -7.79306889e-02,  1.68441832e-01,  1.12461664e-01,  1.42152414e-01,
        4.89900354e-03, -7.65170872e-01,  2.01271817e-01,  3.64474542e-02,
        6.50331825e-02,  3.50521088e-01,  2.04238519e-01,  2.08410025e-01,
        9.08664346e-01, -3.01363498e-01, -9.91550237e-02,  3.89366835e-01,
       -3.20203155e-01, -1.45105734e-01,  5.82705557e-01,  4.78327237e-02,
       -2.42106318e-01, -5.27327657e-01,  2.69803345e-01, -2.17556253e-01,
        6.28677905e-01, -2.05900431e-01, -1.07934065e-01, -7.80161172e-02,
        6.84846580e-01,  1.34878203e-01, -3.53873521e-01,  3.05835247e-01,
        2.38056555e-01,  3.30221862e-01, -2.33499914e-01,  3.28031719e-01,
       -7.09762394e-01,  2.67304666e-02, -3.30732256e-01, -6.78901613e-01,
        2.30713621e-01, -2.74816126e-01,  1.38068840e-01, -3.11384261e-01,
       -3.92301202e-01, -4.50934857e-01, -2.71281958e-01, -1.70864895e-01,
       -8.46418813e-02, -1.26406923e-01, -4.20007221e-02, -4.25925143e-02,
       -4.96464819e-01, -2.77682126e-01,  3.11310533e-02, -2.07885027e-01,
        2.02128395e-01,  3.43465060e-01, -4.85176176e-01, -2.03648750e-02,
        8.50453451e-02, -5.92914104e-01, -9.66089964e-02,  3.56032521e-01,
        6.73542768e-02,  5.38724922e-02, -7.59785175e-01,  5.45717061e-01,
        2.14767069e-01,  1.93673462e-01,  4.25170749e-01,  2.40773901e-01,
        2.85867929e-01,  4.54814672e-01, -2.25551754e-01, -1.22643933e-01,
        2.86110938e-01, -6.15943193e-01, -2.98252046e-01,  1.55116037e-01,
       -2.18386501e-02,  1.67408854e-01,  1.33779747e-02,  3.97863328e-01,
       -1.70087323e-01,  1.12702191e-01, -3.29736710e-01,  3.42946112e-01,
       -2.48032928e-01, -2.86014259e-01,  2.85580844e-01, -4.83210146e-01,
       -3.93926591e-01, -2.72227108e-01,  2.25995943e-01, -3.58234346e-01,
        3.36953104e-01, -4.03175652e-01,  6.18399680e-01, -1.73774138e-01,
       -4.81703967e-01,  3.33316654e-01,  8.60314220e-02,  4.12947088e-02,
        1.28005981e-01, -2.83085834e-03,  3.47615443e-02, -2.47718573e-01,
        3.51441592e-01,  3.02525936e-04, -3.95186603e-01, -3.02448064e-01],
      dtype=float32), array([0.47304574, 0.55096436, 0.6169121 , 0.31502602, 0.30782855,
       0.3890442 , 0.33754444, 0.21617739, 0.36377555, 0.24497361,
       0.3587269 , 0.36877382, 0.22338572, 0.6122077 , 0.3715543 ,
       0.37226984, 0.2929264 , 0.37390772, 0.64708656, 0.3617014 ,
       0.22172894, 0.30398527, 0.30592117, 0.5000447 , 0.49369183,
       0.4646945 , 0.70439625, 0.36239046, 0.7949379 , 0.32037085,
       0.5744859 , 0.36294457, 0.2983014 , 0.35218188, 0.2539162 ,
       0.24308603, 0.42332217, 0.4722921 , 0.52556837, 0.5583672 ,
       0.40907526, 0.8055136 , 0.23929788, 0.44676456, 0.48521405,
       0.68779486, 0.3600162 , 0.6291951 , 0.2144799 , 0.81104326,
       0.24580821, 0.5277318 , 0.3289455 , 0.7092871 , 0.38810286,
       0.24909024, 0.24913795, 0.37755224, 0.4842563 , 0.40668628,
       0.30934238, 0.41030666, 0.5189246 , 0.32227868, 0.25899723,
       0.37407637, 0.45399588, 0.31575346, 0.5911093 , 0.44810873,
       1.3832942 , 0.36442503, 0.26388475, 0.22540188, 0.67360014,
       0.46212044, 0.38322404, 0.49142915, 0.27287394, 0.35733965,
       0.23003373, 0.33948877, 0.6106552 , 0.5058332 , 0.77325773,
       0.311273  , 0.36337453, 0.50793296, 0.72410715, 0.32772735,
       0.30014336, 0.38091278, 0.24841666, 0.4112059 , 0.35896903,
       0.30012208, 0.30619577, 0.38564506, 0.30114466, 0.31727064,
       0.6682192 , 0.36141688, 0.398541  , 0.3889643 , 0.45843586,
       0.48826587, 0.5692145 , 0.6393325 , 0.39206487, 0.25357047,
       0.3182917 , 0.38404775, 0.22587949, 0.41799602, 0.55456054,
       0.43989858, 0.6288046 , 0.32320783, 0.27658266, 0.359775  ,
       0.35964707, 0.36549518, 0.3586085 , 0.5134324 , 0.46593347,
       0.33981165, 0.5319482 , 0.28063118], dtype=float32), array([[[[ 0.00542799],
         [-0.04916988],
         [ 0.06699399],
         ...,
         [ 0.01334389],
         [ 0.05068087],
         [-0.01584117]],

        [[ 0.06832968],
         [ 0.08992139],
         [-0.06022861],
         ...,
         [-0.02799312],
         [-0.00690103],
         [-0.01393677]],

        [[ 0.04468885],
         [ 0.0513006 ],
         [-0.07942529],
         ...,
         [ 0.02328619],
         [-0.01887304],
         [-0.02479845]]],


       [[[ 0.00656236],
         [-0.02748368],
         [-0.03395716],
         ...,
         [ 0.00560895],
         [ 0.03506278],
         [ 0.05511   ]],

        [[-0.0173333 ],
         [ 0.05361018],
         [ 0.03500406],
         ...,
         [ 0.00474614],
         [-0.0515228 ],
         [-0.0290284 ]],

        [[ 0.03538893],
         [-0.01651753],
         [ 0.00126963],
         ...,
         [-0.00122805],
         [-0.02354012],
         [ 0.01565039]]],


       [[[ 0.04833706],
         [ 0.05988973],
         [-0.02183489],
         ...,
         [ 0.03189822],
         [-0.06091809],
         [-0.02468066]],

        [[ 0.05949245],
         [-0.05628692],
         [ 0.03114075],
         ...,
         [ 0.00255167],
         [-0.05776875],
         [-0.09321683]],

        [[ 0.02303218],
         [ 0.04383142],
         [-0.0710186 ],
         ...,
         [ 0.09622347],
         [ 0.01265571],
         [-0.00395539]]]], dtype=float32), array([0.99555504, 1.0122083 , 0.99548167, 0.9949471 , 1.0123833 ,
       0.9729772 , 0.983075  , 0.96927583, 0.98901296, 0.98238873,
       1.0035982 , 1.007352  , 0.99552697, 0.9920337 , 1.0488923 ,
       0.9860467 , 1.0106146 , 0.9864487 , 1.0057335 , 0.98227614,
       1.0018924 , 1.0029081 , 1.0002995 , 0.99075764, 1.0138545 ,
       0.99042976, 1.0206367 , 0.9968816 , 1.0124694 , 0.9952751 ,
       0.99728435, 1.0101342 , 1.001411  , 1.0189908 , 0.9775021 ,
       1.0160515 , 0.99301845, 1.0262619 , 0.9998025 , 0.9891573 ,
       0.97581774, 1.0182385 , 1.0075039 , 0.9929288 , 0.9744308 ,
       1.0004907 , 1.0021869 , 0.9965962 , 1.0321859 , 0.9929117 ,
       1.0154717 , 0.9918986 , 0.9732654 , 0.9886742 , 0.99332744,
       1.0076146 , 1.0170538 , 1.013081  , 0.9996607 , 0.9901459 ,
       0.99580836, 0.9990392 , 0.9878597 , 0.9514258 , 1.0077506 ,
       1.0385616 , 1.0023905 , 0.9900486 , 1.0042442 , 1.0067295 ,
       1.0047929 , 0.985445  , 1.010656  , 0.9967708 , 0.9942921 ,
       0.98858005, 1.0107143 , 0.9844362 , 1.0123867 , 0.988785  ,
       1.0171094 , 0.99169207, 1.0123196 , 1.0029421 , 1.0055729 ,
       0.968906  , 1.028713  , 0.9967034 , 0.97490394, 0.99472165,
       0.9957395 , 0.9992093 , 1.0170003 , 1.0197033 , 1.0046098 ,
       0.99228185, 1.015317  , 1.0213319 , 0.9930051 , 1.0126939 ,
       0.9852443 , 1.0298581 , 0.99567723, 0.9937177 , 1.0014186 ,
       1.0170068 , 0.98471314, 0.9991195 , 1.0001527 , 1.0073401 ,
       0.9719008 , 1.0216869 , 0.9837174 , 0.9842275 , 0.9985999 ,
       0.98757106, 1.0328041 , 1.0191205 , 1.00732   , 0.9988485 ,
       0.9876239 , 1.0035311 , 1.0091509 , 0.9731571 , 0.98379785,
       1.0106057 , 0.987709  , 1.0155722 ], dtype=float32), array([ 1.00456749e-03,  3.67442705e-03, -6.31917547e-03, -2.97977608e-02,
        6.95987325e-03, -1.70050319e-02, -1.72769334e-02, -2.24993583e-02,
       -1.22854235e-02, -1.41294429e-03,  2.80395709e-03,  2.33060587e-02,
       -2.65979506e-02, -8.13090522e-03,  2.53811199e-02,  4.20552259e-03,
       -1.61780859e-03, -1.17013846e-02, -1.22857457e-02, -2.43921415e-04,
        9.87740606e-03, -1.93495192e-02,  7.93412887e-03, -1.60900392e-02,
        2.13297587e-02, -8.08224175e-03,  2.05112025e-02,  3.76513824e-02,
        2.24300427e-03,  2.71137734e-03, -8.99107568e-03,  1.47695059e-03,
        7.60172307e-03,  2.96172183e-02, -1.96499918e-02, -5.93404612e-03,
       -1.08767767e-03,  2.52950694e-02, -3.38071212e-03,  1.54493637e-02,
       -2.51811817e-02,  1.02681676e-02, -7.26757292e-03,  9.41632967e-03,
        1.24709413e-03, -6.61909301e-03,  3.03103589e-02,  4.93226107e-03,
        2.02982295e-02, -1.04617458e-02,  2.70304605e-02,  3.44600342e-03,
       -8.26589670e-03, -2.01970022e-02,  1.71607397e-02, -4.91361506e-03,
        2.78926939e-02,  6.26783911e-03, -1.71470307e-02,  3.30387685e-03,
       -9.80499026e-05, -2.19324790e-03,  1.64562725e-02, -1.50678651e-02,
       -3.02369799e-02,  1.77006982e-02,  3.27997329e-03,  1.10499086e-02,
       -1.17404219e-02,  1.42402807e-02,  5.60902292e-04, -1.95157006e-02,
        1.06915226e-03,  1.26428821e-03, -1.40814413e-03, -9.12215933e-03,
       -1.32545335e-02, -8.64220690e-03,  5.82505716e-03,  8.19842890e-03,
        7.61655672e-03,  1.00142518e-02,  6.34467287e-04, -1.29680457e-02,
        1.12058595e-02, -1.43778650e-02,  2.05099564e-02,  5.71780698e-03,
        1.49010941e-02, -2.03068182e-02, -2.64160633e-02, -3.38466081e-04,
        3.68894124e-03,  1.04352995e-03,  1.14782248e-02,  1.78567823e-02,
        2.95767374e-02, -1.23501644e-02, -1.48839932e-02,  8.77107494e-03,
       -1.21334614e-02,  4.60983254e-03, -1.44326594e-02, -1.59303530e-03,
        1.08363479e-02,  2.01204643e-02,  1.06983806e-03, -1.81074850e-02,
        5.23219071e-03,  1.32380230e-02, -1.48273725e-02,  2.46917419e-02,
       -1.63736138e-02, -6.58742618e-03, -3.69071309e-03, -1.23800933e-02,
        1.28149036e-02,  7.42402812e-03,  1.15824537e-02, -2.21933657e-03,
        1.96390506e-02,  3.37698264e-03,  5.76081220e-03, -1.46865286e-02,
       -6.37737056e-03,  1.51666589e-02,  2.40872521e-03,  1.89501233e-02],
      dtype=float32), array([ 0.10041599,  0.04859509, -0.04115539,  0.02040027, -0.02671961,
        0.02512207,  0.03950081,  0.05317516, -0.01389654, -0.02137895,
       -0.10185204,  0.08218335,  0.04191366, -0.05842293,  0.06432303,
       -0.00343961,  0.07514506, -0.01030625,  0.00434756, -0.01752366,
        0.0547637 , -0.08240628,  0.00222078, -0.03639331,  0.03044803,
       -0.06668533, -0.0500432 , -0.04331086,  0.03705433,  0.04111175,
       -0.06305133,  0.03223242, -0.06453253,  0.03357622,  0.03713551,
       -0.02404284,  0.02654464,  0.08705605, -0.06750385,  0.0167317 ,
        0.03761061,  0.02465279,  0.00075768, -0.04815451, -0.05751912,
        0.03215018, -0.02011148, -0.04730311,  0.0512953 , -0.10117772,
        0.03270926,  0.11004152,  0.02990132, -0.01036674,  0.07460194,
        0.06127683,  0.05024313,  0.00133947,  0.04408526,  0.12175234,
        0.0386732 , -0.1322515 ,  0.07745797, -0.01550731, -0.01264832,
        0.04427756, -0.0405693 ,  0.00681705, -0.0347397 , -0.01087592,
        0.0419264 , -0.00057564, -0.0502916 , -0.06748305, -0.0298282 ,
       -0.01244551,  0.06909157, -0.01445237,  0.02588887, -0.0408861 ,
       -0.02340778, -0.05140182,  0.01861124,  0.07289207, -0.02972187,
       -0.03383767,  0.02570652,  0.02699254,  0.15054028,  0.00244435,
       -0.01789498, -0.0529173 , -0.02234314,  0.05149474,  0.09305794,
       -0.01718193, -0.05989339, -0.00527413, -0.03480319, -0.0317861 ,
        0.04163143,  0.02742284, -0.08649024, -0.03896509, -0.06133536,
        0.10569022,  0.06770086, -0.05256254, -0.02821606,  0.06442918,
        0.06606064,  0.02289876,  0.01937725,  0.06851773, -0.03413859,
        0.01104384,  0.05122861,  0.01829975,  0.02173976,  0.04348528,
       -0.07350878, -0.06119908,  0.05731257, -0.04184652, -0.06713209,
        0.04892194, -0.04332098, -0.04816894], dtype=float32), array([0.01675546, 0.01887613, 0.01636203, 0.01131566, 0.01158697,
       0.01032491, 0.01186891, 0.01520496, 0.00976951, 0.01072469,
       0.02460212, 0.01393152, 0.01142739, 0.01071974, 0.01711765,
       0.00958068, 0.01473806, 0.00884427, 0.00767679, 0.00991553,
       0.01256361, 0.01559695, 0.00927544, 0.01475159, 0.01327746,
       0.02904391, 0.01607417, 0.01009867, 0.01568288, 0.00968168,
       0.02125183, 0.01268631, 0.01075227, 0.00870747, 0.01311848,
       0.01064348, 0.01064367, 0.01418753, 0.02253512, 0.00901622,
       0.01752912, 0.0103169 , 0.00937453, 0.01841314, 0.02321433,
       0.01486407, 0.00984733, 0.0206021 , 0.01400931, 0.04092824,
       0.01142334, 0.0698875 , 0.0085957 , 0.00868214, 0.01239004,
       0.01885792, 0.01518656, 0.00810824, 0.01732101, 0.03926826,
       0.0098698 , 0.02572578, 0.01467384, 0.01001983, 0.01015702,
       0.01100427, 0.01505935, 0.01132486, 0.00878111, 0.00972955,
       0.01495609, 0.00845885, 0.01032306, 0.0254011 , 0.00843359,
       0.007249  , 0.01373819, 0.0085703 , 0.01235354, 0.01111529,
       0.01115412, 0.01686473, 0.00743967, 0.03589497, 0.01443122,
       0.01182235, 0.00933157, 0.01316358, 0.02357427, 0.00931841,
       0.01101001, 0.01712032, 0.00936448, 0.01198612, 0.01936194,
       0.00909127, 0.02394042, 0.01103534, 0.00913395, 0.01302044,
       0.00934129, 0.01151725, 0.01731096, 0.01577536, 0.01111554,
       0.01726889, 0.0233424 , 0.00882667, 0.01340396, 0.01551304,
       0.01953438, 0.00909145, 0.01373765, 0.01115281, 0.01518229,
       0.00794391, 0.01010414, 0.01148273, 0.01257715, 0.013771  ,
       0.02872964, 0.01078598, 0.01706309, 0.01529579, 0.02490824,
       0.01503462, 0.01690865, 0.01052468], dtype=float32), array([[[[ 0.00627485, -0.06294723,  0.01222062, ...,  0.09570299,
           0.07085875, -0.09621584],
         [ 0.10999089, -0.09950833, -0.12151879, ..., -0.03714765,
          -0.05368652, -0.11559444],
         [ 0.04658402, -0.06165827,  0.06566055, ...,  0.10247029,
           0.09139313,  0.0602399 ],
         ...,
         [-0.01427997, -0.06847031,  0.06655838, ..., -0.0299559 ,
          -0.11940986,  0.03412874],
         [ 0.1328794 ,  0.00884127, -0.08172705, ..., -0.0726181 ,
           0.08644721,  0.04301633],
         [-0.13114533,  0.13148703,  0.01411596, ..., -0.10283806,
           0.11775263, -0.09590814]]]], dtype=float32), array([1.01149   , 0.9903384 , 1.0226114 , 1.0306089 , 1.0115207 ,
       1.0295647 , 0.9877093 , 1.0149341 , 0.9725789 , 0.9979289 ,
       0.9872568 , 0.9839561 , 0.99247956, 1.0023053 , 1.00196   ,
       0.9776247 , 1.0115777 , 1.0101326 , 1.0026011 , 1.0068575 ,
       1.0207963 , 0.9940241 , 0.9672311 , 1.0137198 , 1.0054333 ,
       0.98017603, 0.98857903, 1.0275977 , 1.0140774 , 0.98831916,
       1.0168046 , 0.98258495, 0.9853478 , 1.0202056 , 0.98729134,
       0.98197496, 0.9964848 , 0.9729789 , 1.0164839 , 1.025805  ,
       1.029008  , 1.0076263 , 1.0029135 , 1.0144956 , 1.0005168 ,
       1.0234488 , 1.0060824 , 0.9962435 , 1.0180719 , 1.0122201 ,
       1.0161711 , 1.001939  , 1.0062206 , 0.98331404, 1.0195123 ,
       1.0004615 , 1.0301268 , 1.0072242 , 0.9981714 , 1.0249267 ,
       1.0192583 , 0.97890854, 0.9889039 , 1.0076348 , 0.9957849 ,
       1.0078971 , 0.9882613 , 1.021262  , 0.97051907, 0.96824133,
       0.9778458 , 1.0296271 , 1.0090624 , 1.0001903 , 0.97942525,
       0.98434955, 1.0096244 , 0.99916154, 0.98302215, 0.95628333,
       1.0256181 , 1.0106345 , 1.0263796 , 0.96489465, 1.0093571 ,
       1.0014098 , 0.97739077, 0.98852926, 1.000644  , 0.9806648 ,
       0.99718714, 0.9984525 , 1.0024513 , 1.000814  , 1.031864  ,
       1.0242654 , 0.9777081 , 1.0420203 , 0.99705523, 0.96888477,
       0.99755585, 0.97965854, 1.0106852 , 0.99412555, 1.0117217 ,
       0.9996435 , 1.0189407 , 1.0160007 , 0.9839669 , 1.0022192 ,
       0.9778429 , 0.9880833 , 1.0062917 , 0.9975965 , 0.9942282 ,
       1.0119085 , 0.9778484 , 1.0484636 , 0.99972   , 0.9828241 ,
       0.9988883 , 1.0049002 , 0.9987324 , 0.9833477 , 1.0150176 ,
       0.9813702 , 1.0356696 , 0.9908932 , 1.0081977 , 0.98151416,
       0.99892205, 1.0186181 , 0.9801387 , 0.988101  , 0.98269975,
       1.0197008 , 1.0006146 , 0.98418707, 0.9893366 , 1.0212897 ,
       0.98846304, 0.99902827, 0.99754554, 0.98344433, 1.0262687 ,
       1.0530674 , 1.0032455 , 1.0155004 , 1.0239248 , 1.0035045 ,
       1.0066109 , 1.0063493 , 0.97544503, 0.97719955, 0.9999842 ,
       1.0081849 , 0.99913484, 1.0010504 , 1.0115764 , 1.0089341 ,
       1.0037018 , 0.99002147, 0.99413633, 1.0027192 , 1.0075439 ,
       0.9701418 , 0.9975745 , 1.0092577 , 1.0324792 , 0.9900065 ,
       1.0036148 , 1.0157528 , 1.0170377 , 0.99608994, 1.0297827 ,
       0.98602563, 0.989169  , 1.0126576 , 0.97036713, 0.9838007 ,
       1.0165265 , 0.9812115 , 1.006311  , 0.97435296, 0.9960777 ,
       0.97693497, 0.98507005, 1.0207908 , 1.0272715 , 0.99686754,
       0.9999468 , 1.0074161 , 1.0287883 , 0.9964775 , 1.0008518 ,
       1.0066702 , 1.0087922 , 0.9923192 , 0.9979087 , 0.99866265,
       1.0139947 , 0.98259705, 0.98748136, 0.988215  , 1.0205184 ,
       0.99938893, 0.9989795 , 1.0127151 , 0.99102235, 0.9802927 ,
       0.99826604, 1.0041242 , 0.99739784, 0.9882735 , 0.98379123,
       0.99318534, 1.0102925 , 0.98393095, 1.0270479 , 0.99208164,
       1.0089238 , 1.0132433 , 0.986042  , 1.0148965 , 1.0121326 ,
       1.0469112 , 0.97468495, 0.9992409 , 1.0163447 , 1.020963  ,
       1.0121908 , 1.0317495 , 1.040613  , 0.984747  , 0.99095756,
       0.9797895 , 0.9874108 , 0.98936903, 1.0102621 , 0.9947162 ,
       0.99127364, 0.98109347, 0.9986807 , 0.97750705, 0.9855242 ,
       0.97626996, 0.97592247, 0.9911607 , 0.985406  , 0.9984068 ,
       0.9891729 , 0.9941356 , 1.0074197 , 1.0186988 , 0.99843454,
       0.9820305 ], dtype=float32), array([ 2.31843702e-02, -1.48257772e-02,  9.40941460e-03,  3.58903827e-03,
       -7.53100356e-03,  2.15073861e-02, -1.18011236e-02,  2.63134949e-02,
        7.06486125e-03, -9.34025366e-03, -1.30453687e-02, -1.67964101e-02,
       -8.22020601e-03,  3.45629305e-02,  1.93427596e-02,  2.40495168e-02,
        1.70991849e-02,  2.48046033e-02, -6.61623571e-03, -1.85294133e-02,
       -1.91405360e-02,  1.61261354e-02,  3.39484550e-02, -9.97881312e-03,
        3.00357793e-03,  1.89948175e-03, -3.87947112e-02,  1.18473684e-03,
        2.52997037e-02, -4.05105464e-02,  2.57714698e-03, -8.99367779e-03,
       -6.47551520e-03, -2.63691205e-03,  8.74443818e-03, -3.35900635e-02,
       -5.87750645e-03, -2.30628084e-02,  1.71568189e-02,  5.86114265e-03,
        7.89885968e-03, -8.85926094e-03, -1.62090957e-02,  1.05867516e-02,
       -1.04803992e-02,  9.06458590e-03,  8.09231494e-03,  2.70922426e-02,
        7.31142284e-03,  7.88071472e-03,  1.89203899e-02,  8.19264445e-03,
        2.13015191e-02, -1.65804185e-03, -3.34297530e-02, -2.69821677e-02,
        7.74803432e-03,  4.40664552e-02, -1.35763399e-02, -1.46383466e-02,
       -1.97431836e-02, -3.82827921e-03, -3.05289049e-02, -3.68782170e-02,
       -4.27379215e-04, -6.32706610e-03, -1.55753568e-02, -1.64442398e-02,
        4.01178841e-03,  2.83647832e-02, -3.31539963e-03,  1.87414531e-02,
       -6.29694667e-04, -1.10011082e-02, -1.47118839e-02, -1.89486463e-02,
       -5.72809903e-03,  1.34913931e-02, -2.03980017e-03,  1.14363628e-02,
        1.83780435e-02,  1.58147663e-02, -2.48521776e-03, -1.96489040e-02,
       -1.31891649e-02,  1.33421952e-02,  1.17618646e-02, -5.44502912e-03,
        4.95239859e-04,  3.98563743e-02, -1.50556322e-02,  1.20658698e-02,
       -7.60489050e-03,  4.06720676e-03, -1.09974423e-03,  9.17158555e-03,
        1.64120607e-02,  8.19663238e-03,  1.07588377e-02, -5.36869187e-03,
       -8.52876995e-03,  5.28959371e-03, -1.83042940e-02, -8.82413238e-03,
        2.95180250e-02, -3.63943609e-03,  9.88869369e-03, -2.39610560e-02,
        5.76107856e-03,  2.77155265e-03, -7.52081303e-03,  1.15872780e-03,
        9.43777990e-03,  3.22462283e-02,  8.25532526e-03,  1.55285271e-02,
       -2.12569293e-02,  2.23808158e-02,  3.82932392e-03,  1.59451757e-02,
       -1.18482625e-02, -8.90598865e-04, -2.40122396e-02, -1.05662467e-02,
       -1.91585422e-02, -2.85595432e-02,  1.57933533e-02,  6.97297603e-03,
        3.59490700e-03, -1.04532507e-03,  1.45694474e-02,  1.27082663e-02,
       -2.71990877e-02,  3.68901668e-03,  8.67414940e-03, -2.07701977e-02,
        9.28035442e-05, -4.21137214e-02,  3.26138921e-03,  1.81823429e-02,
       -1.86100155e-02, -1.48090879e-02,  1.29121980e-02,  1.70593373e-02,
        1.61606595e-02,  1.36460655e-03, -2.28787703e-03, -1.59489345e-02,
        3.22234780e-02,  2.27772631e-02, -1.21289743e-02,  5.40117314e-03,
       -2.42135189e-02, -2.43646856e-02,  1.78948045e-02, -3.55276978e-03,
       -7.17289653e-03, -1.96095873e-02,  1.81313138e-02, -2.25128010e-02,
       -4.82454244e-03, -1.34351803e-02,  1.18688848e-02, -1.68449599e-02,
       -8.16192385e-03,  9.51694418e-03, -3.02970149e-02,  1.22725302e-02,
       -7.06785824e-03,  4.03158255e-02, -7.13056093e-03,  2.64384244e-02,
       -1.83660034e-02, -1.91435404e-02,  1.62390601e-02,  1.47933550e-02,
       -5.98451169e-03, -1.37882205e-02,  1.47348456e-02, -4.78137797e-03,
        1.14939278e-02, -1.33880340e-02,  4.08908501e-02,  8.66961759e-03,
       -4.84474283e-03,  1.18460376e-02, -6.25140779e-03, -1.42272655e-02,
        5.27157960e-03,  1.08735505e-02, -2.30387896e-02, -1.11972708e-02,
        8.77976883e-03, -2.66305101e-03, -1.17436806e-02, -2.12994730e-03,
        8.02248251e-03,  4.45187371e-03,  9.61474515e-03,  1.44524425e-02,
        1.90686435e-02, -2.87253736e-03,  3.78473336e-03, -1.58229154e-02,
        2.82349829e-02,  1.72995143e-02, -4.47156327e-03,  1.75561160e-02,
        1.09316958e-02, -3.11433600e-04,  1.29997404e-02,  4.70510162e-02,
        5.39966580e-03,  2.34059859e-02, -1.37166996e-02, -3.74238081e-02,
        2.03760546e-02, -1.71863120e-02,  4.03608009e-02,  9.26708523e-03,
       -2.79662553e-02,  7.32089859e-03, -1.73365381e-02, -1.25382347e-02,
        6.27844827e-03,  2.18845587e-02, -1.28067927e-02, -5.42853354e-03,
       -9.47213452e-03,  2.16161963e-02, -2.72554788e-03,  1.01677631e-03,
        2.42254660e-02, -1.16092702e-02,  6.32499019e-03,  2.97317430e-02,
        3.32593173e-02, -1.65023822e-02, -2.13440787e-02,  2.33568400e-02,
        3.59300189e-02, -6.37510279e-03,  7.65346782e-03, -6.76409854e-03,
       -1.97366513e-02,  2.15302594e-02, -1.60731655e-02, -1.30921174e-02,
        1.92133952e-02,  1.05913691e-02, -3.76298577e-02, -7.38148391e-03,
        6.13408163e-03,  5.39818173e-03,  1.26148751e-02, -2.76631583e-02],
      dtype=float32), array([-2.63659060e-01, -2.94502437e-01, -2.74972349e-01,  3.71682346e-02,
        3.62982720e-01,  6.53334558e-02,  7.29273632e-02, -1.56760365e-01,
       -9.44157660e-01, -3.37585747e-01, -3.82768959e-01,  1.68560222e-01,
       -1.04478791e-01,  1.72999263e-01, -3.07575077e-01, -1.42084584e-01,
       -1.94393277e-01,  1.14678137e-01,  8.71752352e-02,  3.95122021e-01,
       -9.51091871e-02, -1.55739054e-01, -8.03750873e-01,  1.14308693e-01,
       -2.50820875e-01, -2.61903077e-01,  5.04666448e-01, -4.54912454e-01,
        2.18853746e-02,  1.24989629e-01,  3.49280208e-01,  1.40879795e-01,
        1.75850824e-01, -6.63511753e-01,  5.52563071e-01, -4.36379537e-02,
        2.25815386e-01,  1.99311167e-01,  2.85355542e-02, -3.62802856e-02,
        8.81378949e-02, -1.08351864e-01,  3.85286212e-01,  1.07860617e-01,
        4.57147136e-02,  1.11946888e-01,  3.32346931e-02, -1.44763365e-01,
        1.06957361e-01,  1.11356899e-01, -2.53660023e-01,  3.40003192e-01,
       -2.74348259e-02, -7.87057042e-01,  2.57079482e-01,  6.47693500e-02,
        2.06993833e-01,  9.82547775e-02, -3.93658876e-01, -9.79575962e-02,
        6.49361432e-01,  3.53231318e-02, -6.72414079e-02,  2.44664654e-01,
        4.56691012e-02,  2.97802836e-01,  7.46680498e-02,  2.99367100e-01,
       -1.72258779e-01,  4.45276678e-01,  3.05501550e-01, -1.41204506e-01,
        1.57021452e-02, -7.92665407e-02,  4.84977402e-02,  8.80706236e-02,
       -3.10192555e-02, -4.27321881e-01,  2.07265377e-01, -2.21428331e-02,
       -2.00077653e-01, -1.92850456e-02,  1.80977330e-01,  1.19057387e-01,
        1.28359953e-02, -3.09008151e-01,  5.73625743e-01, -3.41352910e-01,
        1.63834855e-01,  4.82511938e-01,  6.05662167e-02,  1.66514561e-01,
        1.95321277e-01, -2.92932820e-02, -8.95765517e-03, -5.05583286e-01,
        1.51430801e-01, -9.91004519e-03, -5.10446787e-01, -5.51941171e-02,
       -2.62956262e-01,  2.49152631e-01,  1.80199608e-01, -1.10066704e-01,
        2.26535365e-01,  8.15364160e-03,  1.04709610e-01,  8.43557194e-02,
       -3.43460858e-01,  1.53236195e-01,  9.31895450e-02,  3.46346587e-01,
       -1.78221062e-01, -7.53242373e-01,  1.54553846e-01,  5.62629104e-03,
       -4.17573899e-02, -3.65439951e-02, -8.97673657e-04,  3.94469976e-01,
        3.90449241e-02,  7.17530549e-01,  2.41184905e-01,  1.25573874e-01,
        4.62344676e-01,  2.10551485e-01, -2.52425969e-01,  2.20888466e-01,
        5.85385002e-02,  2.52429247e-01, -3.11807871e-01, -9.28952992e-02,
       -1.84695274e-01, -1.75808862e-01,  1.54606342e-01,  2.26124033e-01,
        3.40198427e-01,  5.18077552e-01,  1.36527985e-01, -1.09942198e-01,
        1.35305941e-01, -2.08504826e-01, -1.10889614e-01, -3.87395233e-01,
       -3.49189937e-01, -5.29749803e-02, -3.08849216e-01, -1.07310601e-01,
        1.86271921e-01, -1.58875450e-01,  1.36334062e-01,  6.96509778e-02,
        1.99866340e-01,  1.31980002e-01, -4.53071415e-01, -3.31895471e-01,
        3.14292572e-02, -3.20526630e-01, -1.68715626e-01,  3.47524464e-01,
        3.42108607e-01,  4.86750722e-01,  1.65228724e-01, -1.16562046e-01,
       -1.55288324e-01, -3.96548063e-01,  9.64233801e-02, -4.85910475e-01,
        1.13503993e-01, -9.32459757e-02,  2.22947910e-01, -2.07904428e-01,
       -9.30521414e-02, -2.71889478e-01,  5.62580749e-02,  5.92404187e-01,
       -2.28246227e-01,  9.78691950e-02, -8.08508322e-02, -3.57389778e-01,
       -4.30775076e-01, -4.83260483e-01, -2.10713878e-01, -3.00917953e-01,
        2.76299298e-01,  8.90014768e-02, -1.00751579e-01, -3.97579551e-01,
       -1.38802856e-01,  4.75694925e-01,  1.77097484e-01, -7.83978254e-02,
       -2.81526577e-02,  3.89911309e-02,  4.07133251e-02, -2.80214369e-01,
       -3.20756882e-02, -1.02019817e-01, -3.53102475e-01,  1.69551328e-01,
        2.40352571e-01,  8.10992718e-02,  7.77192637e-02, -3.30831736e-01,
        1.40680730e-01,  9.78087485e-02,  7.13396743e-02, -3.94134343e-01,
       -3.46897334e-01, -3.85655575e-02, -1.25870824e-01, -3.06894541e-01,
       -3.94968927e-01, -2.45811269e-01,  5.05783975e-01,  7.46028244e-01,
       -2.14654565e-01,  3.37848514e-01, -1.47562593e-01, -2.11239129e-01,
        1.27980411e-01,  1.26912460e-01, -5.31795502e-01,  4.29763973e-01,
        3.14266652e-01, -2.27998152e-01,  3.56330544e-01, -9.54286456e-02,
       -2.62574404e-01,  2.27496013e-01, -9.41706449e-02, -1.85978457e-01,
        3.03358734e-01,  1.90313816e-01,  3.15813959e-01,  3.50529671e-01,
       -4.60025728e-01,  4.98233825e-01,  1.97339222e-01,  2.46052355e-01,
       -7.32771903e-02,  2.55783498e-01, -2.17062086e-02,  1.11008272e-01,
        5.53311169e-01, -4.77469146e-01, -2.36957744e-01, -1.45899087e-01,
        1.09123394e-01,  5.41121840e-01, -3.16557229e-01, -5.03927886e-01,
       -1.60122201e-01,  5.66878868e-03,  2.81619728e-01,  4.36254680e-01],
      dtype=float32), array([0.28941205, 0.28548506, 0.23393957, 0.2177179 , 0.14300177,
       0.18940115, 0.30865288, 0.34846798, 0.27732933, 0.20646343,
       0.21795417, 0.30784208, 0.3461832 , 0.22510712, 0.20828894,
       0.38413903, 0.22594672, 0.25913668, 0.28798458, 0.21283284,
       0.32004258, 0.24190418, 0.4050477 , 0.1407083 , 0.33768207,
       0.22245798, 0.29048628, 0.27617013, 0.1984598 , 0.2906706 ,
       0.20189843, 0.39616355, 0.38872045, 0.26268545, 0.29276145,
       0.2652944 , 0.1845457 , 0.23513974, 0.22685267, 0.2409565 ,
       0.36547446, 0.18472937, 0.25294292, 0.18447591, 0.19311146,
       0.3599301 , 0.20468509, 0.34361628, 0.34996483, 0.32252494,
       0.34001878, 0.4617874 , 0.17929031, 0.26070982, 0.18016355,
       0.30640155, 0.3101999 , 0.21566622, 0.316846  , 0.21032509,
       0.20404181, 0.21719752, 0.26791897, 0.16677831, 0.20236987,
       0.26731512, 0.21516211, 0.22329576, 0.29135692, 0.21480803,
       0.17624922, 0.14756368, 0.27440888, 0.20973918, 0.16265324,
       0.30385658, 0.2868875 , 0.18727078, 0.17224519, 0.33074632,
       0.2654701 , 0.35019547, 0.18678042, 0.16683201, 0.15004137,
       0.20796995, 0.24393605, 0.2543766 , 0.23745449, 0.37678918,
       0.25456122, 0.2411154 , 0.23758195, 0.2869581 , 0.2463613 ,
       0.23054837, 0.30903432, 0.21350947, 0.2879681 , 0.2967362 ,
       0.22594665, 0.20334102, 0.21956602, 0.20213568, 0.21700081,
       0.40732956, 0.23913121, 0.3450004 , 0.4643733 , 0.21560559,
       0.17950462, 0.4026193 , 0.2667689 , 0.3620564 , 0.47387838,
       0.19515814, 0.25723073, 0.31422985, 0.14194568, 0.20517163,
       0.22750732, 0.45548657, 0.21925695, 0.24043348, 0.2890611 ,
       0.42266327, 0.2786067 , 0.18335417, 0.15327743, 0.20296383,
       0.23325454, 0.1952253 , 0.25255793, 0.23691657, 0.21762984,
       0.14225356, 0.27196106, 0.19839795, 0.20113996, 0.20637974,
       0.5060875 , 0.21982677, 0.29347438, 0.18348874, 0.31971315,
       0.31197995, 0.40078235, 0.13192874, 0.17546938, 0.21080865,
       0.19382128, 0.23708156, 0.29135677, 0.19335711, 0.24144906,
       0.23361756, 0.27666748, 0.22144778, 0.22748208, 0.2493555 ,
       0.17009296, 0.38177323, 0.2591086 , 0.26992002, 0.42568886,
       0.53314114, 0.37829253, 0.36103094, 0.20309977, 0.22823355,
       0.41229928, 0.17131495, 0.22811684, 0.37268913, 0.24802558,
       0.2334571 , 0.37769058, 0.2779964 , 0.31398615, 0.20711863,
       0.21065322, 0.34527066, 0.19154233, 0.18138596, 0.5108185 ,
       0.2849317 , 0.21732016, 0.20062068, 0.27378428, 0.22316623,
       0.23238544, 0.26726177, 0.13799615, 0.22320406, 0.18355398,
       0.23061854, 0.41536736, 0.24737856, 0.3261968 , 0.16873513,
       0.24218628, 0.1598126 , 0.42577147, 0.20213689, 0.24574065,
       0.21188013, 0.22901562, 0.5435785 , 0.2806686 , 0.29313138,
       0.21754438, 0.16004682, 0.23067038, 0.26055792, 0.3390246 ,
       0.39295357, 0.22019652, 0.3100965 , 0.20024669, 0.16705371,
       0.14750838, 0.27767766, 0.31643057, 0.24468032, 0.26595935,
       0.22770011, 0.32531184, 0.34726757, 0.22389632, 0.18676873,
       0.30308154, 0.4548575 , 0.1959645 , 0.16952886, 0.30756095,
       0.17069186, 0.18651198, 0.3373512 , 0.437578  , 0.22314402,
       0.4582254 , 0.2731467 , 0.49106565, 0.1999608 , 0.49146208,
       0.1620207 , 0.24190302, 0.24977805, 0.19784507, 0.27464575,
       0.23667084, 0.20345473, 0.28588438, 0.19622529, 0.23448928,
       0.27432612], dtype=float32), array([[[[ 0.04181817],
         [-0.03136285],
         [ 0.04769605],
         ...,
         [-0.06722221],
         [ 0.02202944],
         [-0.02203455]],

        [[ 0.04354478],
         [ 0.00502345],
         [ 0.00915809],
         ...,
         [-0.0015295 ],
         [-0.03566987],
         [ 0.02275468]],

        [[-0.05343833],
         [ 0.01656384],
         [ 0.00341499],
         ...,
         [-0.0402272 ],
         [-0.020349  ],
         [-0.05478487]]],


       [[[ 0.06238627],
         [-0.00303477],
         [ 0.02234761],
         ...,
         [-0.03867763],
         [-0.03644041],
         [ 0.02590133]],

        [[-0.00184722],
         [ 0.0311714 ],
         [ 0.01806981],
         ...,
         [-0.03116427],
         [-0.06323522],
         [ 0.00298404]],

        [[-0.00765948],
         [ 0.05909911],
         [ 0.07422253],
         ...,
         [-0.04242856],
         [ 0.03748941],
         [-0.03644214]]],


       [[[-0.01057085],
         [-0.04037609],
         [-0.03116543],
         ...,
         [-0.00131632],
         [-0.00058879],
         [-0.01889267]],

        [[ 0.0305844 ],
         [-0.00469759],
         [-0.00089817],
         ...,
         [-0.04544753],
         [-0.01695172],
         [ 0.01742592]],

        [[ 0.05341689],
         [ 0.01756297],
         [ 0.03256579],
         ...,
         [ 0.02658821],
         [ 0.05400362],
         [-0.05250924]]]], dtype=float32), array([1.0123509 , 0.9906171 , 1.0251108 , 1.0281868 , 1.0061395 ,
       1.0460974 , 0.98534006, 1.0072123 , 0.9779511 , 1.0001695 ,
       0.98170984, 0.9821542 , 0.9793609 , 1.0072858 , 0.9995535 ,
       0.983708  , 1.0072993 , 1.0065368 , 1.0040448 , 1.007174  ,
       1.0179607 , 0.9871369 , 0.9718859 , 1.0038424 , 1.0021223 ,
       0.97364783, 0.98632216, 1.0255162 , 1.0189204 , 0.9976003 ,
       1.0200365 , 0.9837339 , 0.98572665, 1.0273988 , 0.97969484,
       0.9717272 , 0.9972846 , 0.96892154, 1.0144316 , 1.0276461 ,
       1.0202081 , 1.0032774 , 0.9947704 , 1.0148343 , 1.0014759 ,
       1.0237186 , 1.0086128 , 0.99506944, 1.0189803 , 1.0071284 ,
       1.0132406 , 0.99372596, 1.0038618 , 0.98168486, 1.023811  ,
       0.99439746, 1.026068  , 1.0050174 , 0.997065  , 1.0246433 ,
       1.0238224 , 0.98765707, 0.98495007, 1.024328  , 0.9980725 ,
       0.99905854, 0.99540275, 1.0120499 , 0.96863097, 0.99348974,
       0.97849816, 1.0216187 , 1.0094492 , 0.998763  , 0.9738259 ,
       0.9833488 , 1.0075519 , 0.9960521 , 0.97827166, 0.97027284,
       1.021576  , 1.0165449 , 1.021299  , 0.96249527, 1.0129476 ,
       1.0033599 , 1.0014405 , 0.98581314, 0.9982298 , 0.9821026 ,
       0.99896127, 0.9972349 , 0.99412453, 0.9889751 , 1.0290241 ,
       1.0228682 , 0.9763002 , 1.0350755 , 0.9946828 , 0.9737831 ,
       0.9985145 , 0.9769599 , 1.0099497 , 0.9935604 , 1.0190685 ,
       1.0041926 , 1.0225692 , 1.0152769 , 0.9724333 , 0.999947  ,
       0.9720592 , 0.9848696 , 1.0068269 , 0.9999793 , 0.99373734,
       1.0132709 , 0.9768026 , 1.0446684 , 0.99850625, 0.98781633,
       0.99211144, 0.9997297 , 1.0040802 , 0.9725055 , 1.0060618 ,
       0.9811221 , 1.044125  , 0.9887522 , 1.0029843 , 0.9794229 ,
       0.99615395, 1.0138475 , 0.9831253 , 0.98240703, 0.98513573,
       1.0241367 , 0.9963733 , 0.9919264 , 0.9892935 , 1.0177648 ,
       0.98543143, 0.99513584, 0.9968707 , 0.9877201 , 1.0263523 ,
       1.0448786 , 1.0016584 , 1.0168679 , 1.0248559 , 1.0088404 ,
       1.0041505 , 1.0040681 , 0.9929402 , 0.97373694, 1.0000478 ,
       1.0121562 , 0.99933463, 1.0045089 , 1.0066313 , 1.0102597 ,
       1.0088472 , 0.9919237 , 0.9889912 , 1.0006193 , 1.0063059 ,
       0.9683111 , 0.99875087, 1.011039  , 1.0178616 , 0.9905583 ,
       1.0008605 , 1.0118483 , 1.0106606 , 0.9916764 , 1.0280737 ,
       0.98941976, 0.9779294 , 1.0126853 , 0.96830344, 0.9816164 ,
       1.0199478 , 0.98554754, 1.0079083 , 0.9684485 , 0.97743684,
       0.9700948 , 0.9877152 , 1.0228314 , 1.026795  , 1.0052323 ,
       1.0032378 , 1.0120143 , 1.0273373 , 0.9959366 , 1.0151014 ,
       1.0056312 , 1.0031986 , 0.99112296, 0.9983158 , 1.0012947 ,
       1.0037315 , 0.981734  , 0.9889396 , 0.9907344 , 1.0274547 ,
       0.9975343 , 1.0016329 , 1.0114212 , 1.0001698 , 1.0037738 ,
       1.0040592 , 1.0112998 , 0.9957334 , 0.98751104, 0.98385453,
       0.99910647, 1.0059178 , 0.99525344, 1.0180117 , 0.990639  ,
       1.0064217 , 1.0005083 , 0.98229414, 1.0041368 , 1.0170012 ,
       1.0484217 , 0.9669607 , 1.0012838 , 1.018347  , 1.0167217 ,
       1.0191121 , 1.0248723 , 1.0307951 , 0.98896897, 1.0001781 ,
       0.993339  , 0.9862797 , 0.9733548 , 1.013806  , 0.9955561 ,
       0.9933075 , 0.9769906 , 0.9908044 , 0.9828741 , 0.9960985 ,
       0.97712034, 0.9719241 , 0.993783  , 0.9812912 , 1.0045395 ,
       0.9720377 , 0.9890934 , 1.0071943 , 1.0149221 , 1.0016481 ,
       0.9897425 ], dtype=float32), array([ 9.08813532e-03, -1.87534411e-02,  2.88373698e-02,  4.35738340e-02,
        2.11441629e-02,  4.17988971e-02, -1.63832004e-03,  9.13689658e-03,
       -2.41605993e-02, -1.17517728e-02, -1.51790725e-02,  2.74887751e-03,
       -1.77926607e-02,  8.27408955e-03, -3.20679322e-03, -1.23908222e-02,
       -3.45828012e-03,  7.37792067e-03,  3.32203731e-02, -4.53735469e-03,
        1.95003650e-03, -1.94679480e-02,  8.23902804e-03,  8.66020378e-03,
       -3.70925968e-03, -1.79826953e-02, -1.92426164e-02,  2.62726452e-02,
        8.82485881e-03, -6.28438964e-03,  9.05223482e-04, -1.37124741e-02,
       -1.76085718e-02,  1.34196889e-03,  2.49307416e-03, -1.14628132e-02,
        1.44354664e-02, -2.95745935e-02,  9.54808574e-03,  1.82238575e-02,
        5.56818815e-03,  1.80173269e-03, -1.16366509e-03,  2.57281270e-02,
       -1.60734057e-02,  3.20755802e-02,  6.81862468e-03, -5.76449232e-03,
        1.31984875e-02,  1.53784105e-03,  6.58244453e-03,  5.43633243e-03,
        3.68508436e-02, -2.72673601e-03, -1.99234933e-02,  2.57951692e-02,
        2.28339266e-02,  6.26704516e-03, -1.78819057e-02,  2.04582140e-02,
        6.31521456e-03, -3.50730680e-02, -1.66140590e-02, -6.30328525e-03,
        2.37369742e-02,  3.98334488e-03,  1.54959131e-02,  1.36160860e-02,
       -8.54845997e-03,  1.76882781e-02, -4.88083065e-03, -3.59634083e-04,
        1.24823023e-02,  1.54144662e-02, -1.97257642e-02, -2.69796588e-02,
        7.44934147e-03,  2.05512214e-02,  1.04515934e-02,  1.05607361e-02,
        7.60627445e-03,  2.05720346e-02, -2.19853828e-03, -1.72931552e-02,
        7.24236760e-03, -1.71010138e-03,  1.88720168e-03,  1.98917575e-02,
        1.69281866e-02,  1.13709131e-02,  9.60681029e-03, -1.51116773e-02,
        4.70535131e-03, -8.96492135e-03,  5.54858753e-03,  2.67764926e-02,
        9.81049798e-03,  7.97725748e-03, -2.18797894e-03, -2.11279672e-02,
        2.31342297e-03, -7.77927972e-03, -5.11651253e-03,  9.90448799e-03,
        1.87472273e-02, -6.35021226e-03,  1.08956462e-02,  7.21617369e-03,
       -2.88861021e-02,  6.70510577e-03, -3.88295855e-03, -1.95189763e-03,
       -1.40626496e-02,  2.76930332e-02,  1.27117857e-02,  1.05099485e-03,
       -1.78147927e-02,  2.95880530e-02, -3.32613825e-03,  1.03647867e-03,
       -2.05161627e-02,  2.07858067e-02,  6.22522319e-03, -1.50567293e-02,
        1.14327976e-02, -1.01884194e-02,  3.16880755e-02,  1.30237006e-02,
        4.96949116e-03, -1.78365894e-02,  1.32594374e-03,  1.78191140e-02,
       -3.06348559e-02, -2.14264244e-02,  1.64916050e-02,  1.90478880e-02,
        1.21201584e-02, -2.01431960e-02, -2.82028504e-03,  1.46996314e-02,
       -9.64532793e-03, -2.44977251e-02, -1.34695079e-02, -1.74979714e-03,
        3.14741842e-02,  2.50989962e-02,  5.51448576e-03,  7.61354982e-04,
        2.68865749e-02,  8.94155819e-03, -7.20332901e-04,  7.87818106e-04,
       -1.13993026e-02, -5.16260276e-03, -2.56803688e-02,  2.96759210e-03,
        3.43842874e-03, -1.05591130e-03, -5.03407372e-03,  1.15281669e-02,
        1.02635054e-02, -1.00712292e-02, -5.18854521e-03,  1.71404816e-02,
        1.78680755e-02, -3.48172225e-02, -9.49315540e-03,  1.35461409e-02,
        6.13039220e-03,  1.76517945e-02,  1.19825834e-02, -2.06873985e-03,
        1.29951835e-02, -1.16405124e-02,  8.26283917e-03, -7.31985876e-03,
        6.17810409e-04, -3.44324159e-04, -1.34246908e-02, -1.16313845e-02,
        2.06311070e-03, -3.20783537e-03,  2.03064308e-02,  1.90581067e-03,
       -9.15228855e-03, -7.70656578e-03, -3.75033123e-03, -9.04173404e-03,
        8.10020510e-03,  2.13388670e-02,  3.34869744e-03, -4.20910027e-03,
        1.47293415e-02, -2.12441501e-03,  3.98775982e-03,  9.16693732e-03,
        1.20260213e-02,  1.93090513e-02, -2.22429968e-02, -1.50097487e-02,
        3.73293534e-02, -1.69739984e-02, -7.79757043e-03, -8.89723469e-03,
        4.75264005e-02,  1.24837449e-02,  6.40087412e-04,  3.59359430e-03,
        4.18761221e-04, -1.50058419e-02, -1.17163183e-02, -1.22430651e-02,
       -2.04100832e-02, -2.23422162e-02,  1.25629967e-03, -1.63553841e-02,
       -2.41946876e-02, -2.90513616e-02,  1.11599744e-03,  1.55203119e-02,
       -6.59868866e-03,  2.19086017e-02, -2.59564444e-02,  6.07728912e-03,
        9.40816384e-03,  4.08206023e-02, -2.85846107e-02,  3.82364233e-05,
        1.19201820e-02,  2.34880503e-02, -1.21130096e-02,  3.43565717e-02,
        1.37308240e-02, -2.05384325e-02,  1.56926624e-02,  1.85791310e-02,
       -4.18631248e-02,  4.35094023e-03,  1.03837000e-02, -1.43828243e-02,
        2.53686775e-02,  8.10518488e-03,  7.88262580e-03, -5.74250752e-03,
        7.92718143e-04, -7.57176103e-03, -4.36001755e-02, -1.72817856e-02,
       -2.29420830e-02, -1.33981109e-02, -3.32649872e-02, -8.96995328e-03,
        2.33471803e-02,  7.46859144e-03, -1.55739591e-03,  1.18563101e-02],
      dtype=float32), array([ 6.50346428e-02,  2.37013586e-02,  6.70753419e-02, -4.32627946e-02,
       -2.93726623e-02, -4.69967024e-03,  2.38105264e-02,  4.07919033e-05,
       -5.21110147e-02,  4.43709753e-02, -1.54516231e-02, -2.08822023e-02,
        3.60729061e-02, -3.18741575e-02, -6.01716042e-02,  2.23269481e-02,
        7.19629452e-02, -4.79265526e-02, -3.87901887e-02, -1.32519600e-03,
        6.91391751e-02, -6.06861077e-02, -2.97960658e-02,  1.12851085e-02,
        9.25814137e-02, -6.45036772e-02,  3.37580265e-03,  1.86468437e-02,
        1.28277559e-02,  2.28329301e-02, -4.95520085e-02,  3.02902125e-02,
       -9.37490631e-03,  9.02865902e-02, -3.80976200e-02, -4.05082777e-02,
       -5.81987798e-02,  8.59783590e-03, -5.84930927e-03,  3.11973933e-02,
       -4.62078117e-03,  2.16532648e-02,  3.86227854e-02,  2.05929019e-02,
        8.31443164e-03,  7.34774917e-02,  1.27249099e-02, -1.11053046e-02,
        9.34959278e-02, -8.56503621e-02,  2.26689279e-02,  4.54268232e-02,
        2.20602900e-02,  4.11897451e-02,  2.45519374e-02, -4.50752070e-03,
        3.61295082e-02, -5.62616549e-02,  1.40935611e-02,  1.38410982e-02,
        4.24345396e-02,  8.78874883e-02,  4.27196249e-02,  4.55457084e-02,
       -3.36073004e-02,  4.56301570e-02, -6.30916050e-03,  2.07106322e-02,
        2.52727373e-03,  6.54705912e-02, -5.07048219e-02,  1.67395454e-02,
       -3.59389298e-02,  3.01762726e-02,  2.95125265e-02,  1.98244844e-02,
       -2.11626533e-02, -6.38898239e-02,  1.80357080e-02,  5.51153645e-02,
       -9.01204571e-02, -5.61846234e-02,  3.25911380e-02, -6.12577843e-03,
        8.66067875e-03,  1.63400844e-02, -3.32740135e-02, -2.74917725e-02,
       -3.26990592e-03, -3.96993347e-02, -5.35256080e-02,  4.21268493e-02,
       -6.16440699e-02,  6.67283162e-02, -2.65897197e-05, -7.79441074e-02,
        9.93750244e-03,  4.46948688e-03, -2.49277428e-02,  2.88212928e-03,
       -2.75431368e-02,  2.06583664e-02,  5.78119792e-02,  4.06178529e-04,
       -6.54008612e-02, -2.96579255e-03,  5.65065369e-02,  5.66504151e-02,
       -8.37550759e-02, -1.87877156e-02,  2.40199622e-02, -8.98998007e-02,
        3.52128432e-03,  5.46706133e-02,  5.11379465e-02, -6.46448731e-02,
       -3.58913466e-02, -6.89936429e-02, -2.87500061e-02,  1.31713180e-02,
        4.77267839e-02, -5.93634062e-02,  1.10818241e-02,  5.38292825e-02,
       -5.23793735e-02, -3.73424478e-02, -2.76679173e-02, -3.69143412e-02,
        1.55702746e-03, -4.27219868e-02, -1.86658856e-02,  5.68876043e-02,
       -2.99721546e-02, -4.88137491e-02,  1.02241505e-02,  3.83760110e-02,
        1.85410324e-02,  2.18323898e-02, -4.42288481e-02, -5.74298464e-02,
       -3.60134467e-02,  3.66996676e-02, -7.82146081e-02, -2.00896487e-02,
        3.84654105e-02,  2.74152253e-02, -4.56657866e-03,  6.15389198e-02,
        1.69182625e-02,  5.07916510e-03,  2.41371524e-02, -1.50252366e-02,
        4.02756706e-02, -2.26618052e-02, -6.36590198e-02, -4.25321385e-02,
        2.43839379e-02, -2.96527855e-02, -6.62190989e-02, -9.38412324e-02,
        7.67028844e-03, -4.47506681e-02, -5.41902892e-02,  4.35251668e-02,
       -5.64617179e-02, -5.07833920e-02,  1.71678718e-02,  5.26445620e-02,
       -1.86328683e-02,  7.11658150e-02,  4.59937565e-02, -3.91381346e-02,
        4.35989499e-02,  3.90084833e-02,  3.86121720e-02, -4.43962887e-02,
        6.99107647e-02,  2.57771350e-02,  5.67054264e-02, -4.14292701e-02,
        9.28981304e-02, -1.49731049e-02,  4.14228030e-02, -5.71742766e-02,
        5.17528281e-02,  4.93148491e-02,  2.19907388e-02,  1.80831092e-04,
        4.70570056e-03,  7.35766999e-03, -2.82713328e-04,  2.36244667e-02,
       -5.87673159e-03, -6.53178692e-02,  5.91692254e-02, -1.39731113e-02,
        4.39513139e-02, -5.71184466e-03, -1.24042935e-03, -1.92550477e-02,
        2.05474868e-02, -2.49484349e-02,  7.03166872e-02,  1.60852615e-02,
       -7.58404210e-02,  2.09456161e-02,  1.57432072e-02,  7.10124895e-02,
        1.36539889e-02,  2.27218196e-02,  1.48721933e-02,  2.92023793e-02,
       -7.81244785e-02,  6.45982707e-03, -8.19130465e-02,  5.26043884e-02,
       -6.94989190e-02,  2.93319002e-02,  9.63743310e-03,  6.27699792e-02,
        3.23117748e-02,  8.21447670e-02,  5.27283810e-02,  5.33255225e-04,
        6.24722317e-02,  4.04386409e-02,  5.76077513e-02, -3.20783071e-02,
        4.98056337e-02, -2.09363783e-03,  8.60008299e-02, -3.63028571e-02,
       -1.74821168e-02, -1.10146934e-02,  5.87588884e-02, -1.89067740e-02,
       -4.00885791e-02, -2.98227072e-02,  3.03662252e-02, -3.71748656e-02,
        6.69658035e-02, -4.69546542e-02,  3.61254103e-02, -2.43889764e-02,
       -4.56699021e-02, -2.86945105e-02, -1.75635144e-02,  2.35091113e-02,
        1.46971759e-03,  3.00242789e-02,  3.50295715e-02,  2.54205409e-02,
       -9.50675458e-03, -8.62947404e-02, -2.89212633e-02, -3.71682309e-02],
      dtype=float32), array([0.01287685, 0.01022529, 0.01368072, 0.01072146, 0.00991093,
       0.00961629, 0.00812586, 0.00861455, 0.00990226, 0.01035428,
       0.00977533, 0.0097045 , 0.01311625, 0.01121293, 0.01192776,
       0.00792718, 0.01259156, 0.00966773, 0.01217986, 0.01006733,
       0.01309495, 0.01454123, 0.00799789, 0.01065443, 0.01964116,
       0.01329113, 0.00995353, 0.00751777, 0.00856098, 0.01031204,
       0.01354054, 0.01215074, 0.0107453 , 0.01479698, 0.00942034,
       0.00973309, 0.0152024 , 0.00949512, 0.00800682, 0.01130013,
       0.01046564, 0.00996064, 0.01232134, 0.0094363 , 0.00802766,
       0.01420512, 0.01028734, 0.00804163, 0.0192099 , 0.01418724,
       0.00830093, 0.01579667, 0.00881113, 0.00949169, 0.00911579,
       0.00789426, 0.01317488, 0.0128338 , 0.0081651 , 0.00827855,
       0.01266805, 0.02724781, 0.01386426, 0.01050646, 0.0086613 ,
       0.01475976, 0.00864837, 0.00924407, 0.00788277, 0.01352149,
       0.01197137, 0.00907573, 0.01082718, 0.00830912, 0.00957337,
       0.00924336, 0.01007472, 0.01128493, 0.00834992, 0.00966079,
       0.01444669, 0.01020599, 0.01090402, 0.00901017, 0.00798076,
       0.00811286, 0.01094546, 0.00803092, 0.0085562 , 0.01281909,
       0.01332488, 0.0103207 , 0.01647793, 0.01593662, 0.00890021,
       0.01533929, 0.00776081, 0.00931389, 0.00767766, 0.00848251,
       0.0097772 , 0.00843056, 0.01312723, 0.0090202 , 0.01189291,
       0.00795924, 0.01256514, 0.01143391, 0.01663803, 0.01007331,
       0.00924861, 0.02609373, 0.00853382, 0.01130565, 0.00960884,
       0.01294733, 0.01158514, 0.01472828, 0.01000249, 0.00900411,
       0.0135511 , 0.02441144, 0.00894551, 0.0153587 , 0.01593062,
       0.01466567, 0.00842953, 0.01326388, 0.00821708, 0.01315199,
       0.00857474, 0.01018796, 0.01059182, 0.01283703, 0.00878641,
       0.01111672, 0.01007158, 0.008684  , 0.01145083, 0.01226454,
       0.0121268 , 0.01021517, 0.01395671, 0.00852735, 0.00827657,
       0.01510783, 0.00714113, 0.01126533, 0.01097911, 0.0078535 ,
       0.01167749, 0.00995011, 0.0126288 , 0.00965552, 0.01089988,
       0.01010568, 0.00959353, 0.01032947, 0.01352664, 0.02763433,
       0.01076803, 0.01757729, 0.01408349, 0.01507643, 0.00961546,
       0.00869879, 0.00935838, 0.01159723, 0.00927251, 0.01387772,
       0.01000457, 0.00980496, 0.00932875, 0.01034005, 0.01071856,
       0.01278051, 0.01185206, 0.01074415, 0.00966843, 0.00968608,
       0.01722541, 0.00752412, 0.00900607, 0.00995923, 0.01805709,
       0.01287599, 0.009616  , 0.00879805, 0.0088868 , 0.00878684,
       0.00774041, 0.00938547, 0.01193525, 0.01367863, 0.01482847,
       0.00809452, 0.00932254, 0.00919776, 0.00778671, 0.00868233,
       0.00865584, 0.01088153, 0.01270545, 0.00848367, 0.02135345,
       0.00816634, 0.00957039, 0.01056518, 0.00943531, 0.0101103 ,
       0.00779877, 0.01052561, 0.01142582, 0.00783191, 0.02473985,
       0.02250805, 0.01125429, 0.0104526 , 0.00850681, 0.0124436 ,
       0.00909129, 0.02586729, 0.01140699, 0.01015698, 0.01495228,
       0.01016282, 0.01826739, 0.01273387, 0.01192676, 0.01094759,
       0.01431634, 0.01289617, 0.01094958, 0.00973043, 0.017595  ,
       0.01054003, 0.00978545, 0.01009351, 0.01028726, 0.01002436,
       0.01122074, 0.0131754 , 0.01165665, 0.00820146, 0.01431672,
       0.00888817, 0.00963814, 0.00892419, 0.00831667, 0.00988034,
       0.01024631, 0.00828186, 0.00842447, 0.02002283, 0.01015105,
       0.0113078 ], dtype=float32), array([[[[ 0.06924244, -0.14281425, -0.0153842 , ...,  0.01194856,
          -0.02828293, -0.05670845],
         [-0.03266442,  0.01741049, -0.08160466, ...,  0.0977862 ,
          -0.01060771,  0.07299902],
         [ 0.02913456, -0.10472159,  0.03186137, ..., -0.09036846,
           0.08980382,  0.02813266],
         ...,
         [-0.11032296,  0.12376281, -0.1029596 , ..., -0.06628171,
          -0.04743321, -0.06047775],
         [ 0.0467485 ,  0.02114042, -0.09045973, ...,  0.00231692,
           0.04235414,  0.0895707 ],
         [ 0.00525716,  0.0126749 , -0.07994784, ..., -0.04959538,
           0.05222078,  0.02982064]]]], dtype=float32), array([1.0190836 , 1.0077474 , 1.0099661 , 0.9739669 , 1.0087407 ,
       1.0064002 , 0.993389  , 1.0118157 , 1.0129765 , 0.97450644,
       1.0056976 , 0.97871387, 1.0232482 , 0.99029005, 0.99389076,
       1.0411499 , 0.9993896 , 1.0249875 , 1.0022504 , 1.005641  ,
       1.0019717 , 0.99160516, 0.98609227, 1.0038325 , 0.9858976 ,
       1.0157999 , 1.0014179 , 1.0197889 , 0.9990681 , 0.9786795 ,
       0.98428595, 0.9731295 , 1.0359374 , 0.9678627 , 1.0347974 ,
       0.9914097 , 0.9770162 , 1.0023426 , 1.0039142 , 0.9988198 ,
       0.9812849 , 0.9746606 , 0.9952286 , 1.0172489 , 1.0009456 ,
       0.9745632 , 0.97392154, 0.9932431 , 0.9931177 , 0.99157387,
       1.0034306 , 1.0090524 , 0.97888154, 0.990389  , 0.9769557 ,
       1.0294983 , 0.9914544 , 0.99527526, 1.0044658 , 0.98988557,
       1.0001199 , 0.9882094 , 1.0125453 , 1.0048783 , 1.026792  ,
       1.0024002 , 0.9949125 , 0.99235594, 0.99509007, 0.9945321 ,
       1.0010115 , 1.0025324 , 1.0146121 , 1.0084918 , 0.9890825 ,
       0.97961885, 0.99896276, 1.0106707 , 1.0315139 , 1.0242999 ,
       0.9795478 , 1.0213342 , 1.0277905 , 1.0232428 , 0.9880184 ,
       1.0065458 , 0.9917188 , 1.0142952 , 0.9887827 , 1.0003022 ,
       1.0386794 , 1.0211217 , 0.99105877, 0.97406167, 0.98520756,
       0.98995274, 0.9856785 , 0.98262733, 1.0175005 , 0.99510837,
       1.0115367 , 1.0082995 , 1.0117897 , 1.0133587 , 1.0102859 ,
       0.97000366, 1.0162381 , 1.024282  , 0.99043787, 1.0082172 ,
       1.0019996 , 1.0056181 , 0.9967155 , 0.97796506, 0.987587  ,
       1.0112767 , 1.0161583 , 0.9972239 , 1.0196599 , 0.9860155 ,
       0.99711376, 0.9998014 , 1.0037873 , 1.0084231 , 1.0110346 ,
       1.0030828 , 0.9746316 , 0.99834174, 1.0068654 , 1.0163656 ,
       0.990881  , 1.0100819 , 0.9972255 , 1.0115819 , 1.0010387 ,
       0.99971956, 0.9599202 , 0.9792993 , 1.0230899 , 0.99018043,
       1.014587  , 1.0021617 , 1.0054982 , 1.0075747 , 1.008889  ,
       1.0201418 , 0.9981967 , 0.98480594, 1.0208398 , 1.0140707 ,
       1.004717  , 0.9973961 , 1.0044197 , 0.9817936 , 0.99847686,
       1.0129886 , 1.0095667 , 1.0430003 , 0.9876708 , 1.0045551 ,
       1.0187817 , 1.0038637 , 0.99205416, 1.0258989 , 1.028694  ,
       1.0278878 , 0.9926772 , 0.99189234, 1.0114753 , 0.9960312 ,
       0.9802843 , 1.0034877 , 1.0211627 , 0.9813085 , 0.99199665,
       0.98825264, 0.9887649 , 0.97695464, 0.98665047, 1.005067  ,
       1.0021546 , 0.99359286, 0.99422514, 0.9917267 , 0.9942888 ,
       1.0190306 , 1.0034387 , 0.97452176, 1.0136335 , 1.0044674 ,
       0.99894905, 0.9903417 , 1.0201008 , 0.9897856 , 0.97389203,
       1.0060325 , 0.9889233 , 0.99105203, 0.99170023, 0.9906663 ,
       0.9939865 , 0.9814854 , 1.0014545 , 0.9848767 , 0.9649337 ,
       1.0039724 , 1.0014256 , 1.0190302 , 1.0093973 , 0.97742903,
       1.0161178 , 0.9913481 , 0.977329  , 0.99731064, 0.9855484 ,
       1.002127  , 0.98742336, 1.010883  , 1.0332849 , 0.99189585,
       0.9612909 , 1.0193933 , 0.98415375, 1.0122395 , 1.0107359 ,
       1.021417  , 0.9890314 , 1.010039  , 1.0057212 , 1.0391288 ,
       0.9858692 , 0.93809396, 1.0242722 , 1.0330516 , 0.994466  ,
       1.0135564 , 0.99904186, 1.0017256 , 0.99682385, 0.99301827,
       0.9915421 , 0.97984123, 0.98335195, 0.9889858 , 0.98171127,
       0.99027044, 1.0188967 , 1.005041  , 1.0241499 , 0.9981024 ,
       1.0170949 , 0.9869993 , 1.001723  , 1.0234143 , 1.0057759 ,
       1.0050784 ], dtype=float32), array([-6.52120262e-03, -2.03019325e-02,  2.44542520e-04,  2.55873203e-02,
        1.79284718e-02,  2.07755342e-03, -1.08192246e-02,  4.46416438e-03,
        8.14433489e-03, -1.88262556e-02, -1.65039077e-02,  1.12460213e-04,
       -6.14361325e-03, -2.21626982e-02,  1.38972271e-02, -3.85437161e-03,
       -1.25374703e-03, -1.46215102e-02, -4.07004170e-02,  1.96045246e-02,
       -7.76038691e-03, -7.78599875e-03,  6.11732903e-05,  2.92979404e-02,
       -9.15444363e-03,  1.69922151e-02,  1.03570176e-02, -2.31552459e-02,
       -1.17079737e-02,  2.02991813e-02, -2.86318026e-02, -8.84098001e-03,
        1.71819851e-02,  2.40186173e-02, -5.85411955e-03, -2.79076658e-02,
        1.38001665e-02, -1.44397318e-02,  1.08466139e-02,  5.92866726e-03,
       -4.55363654e-02, -1.80554315e-02, -2.99487524e-02, -3.74480002e-02,
        1.87317431e-02,  2.03343816e-02, -2.30472116e-03,  1.66730452e-02,
        3.13907675e-02,  2.48364750e-02,  1.23848664e-02,  5.33711538e-03,
        6.78143930e-03,  2.60182582e-02,  2.19658781e-02,  3.33914421e-02,
       -1.37254046e-02, -1.25793023e-02, -1.87456571e-02,  2.82076374e-03,
        4.75589791e-03,  1.75631139e-02, -2.01663282e-02, -4.03327942e-02,
       -9.84321255e-03,  5.83890593e-03,  2.41642930e-02,  1.19792558e-02,
       -4.87940758e-03,  2.13628337e-02, -2.04581246e-02, -3.07573052e-03,
        4.49124910e-03, -1.81801012e-03, -7.53998430e-03, -5.91330370e-03,
        2.44895313e-02,  2.44823582e-02,  7.41261337e-03,  6.70280168e-03,
        2.64604259e-02, -2.46985909e-03,  7.44024571e-03,  1.17709981e-02,
       -3.73860821e-02,  1.33391917e-02, -2.23912429e-02, -2.45998763e-02,
       -3.13929878e-02,  2.09907144e-02, -1.45639507e-02, -4.95788688e-03,
        1.03227198e-02,  1.81314368e-02, -2.45300680e-03,  4.98833414e-03,
        4.37996164e-03,  1.78959232e-03,  8.81640334e-03,  2.34530051e-03,
        1.86585691e-02,  1.99411642e-02, -2.13728822e-03,  1.36633003e-02,
        2.71810312e-02, -2.35814205e-03,  1.14485240e-02,  2.96055768e-02,
        4.12394479e-03, -5.08287316e-03,  8.77916347e-03,  4.21099272e-03,
       -5.36855869e-03,  3.78481112e-03, -1.22565646e-02, -9.85624734e-03,
       -1.31248841e-02, -1.56356581e-03, -1.92604568e-02, -2.89194216e-03,
       -2.50661094e-02, -6.49388740e-03,  1.69195682e-02, -1.04593681e-02,
        6.08484633e-03,  2.18461007e-02,  2.23972965e-02, -1.23964367e-03,
        1.80257112e-02,  1.28877945e-02,  3.91723886e-02,  9.58581548e-03,
        4.10906691e-03,  5.55428118e-03, -3.86191159e-02, -3.65146482e-03,
       -7.09652528e-03, -3.54059599e-03, -1.76493451e-02,  1.11434981e-03,
        1.79863418e-03,  8.92433524e-03, -1.81046072e-02, -3.69948559e-02,
       -1.84866432e-02, -2.81512621e-03, -1.07032275e-02, -3.02324817e-02,
       -2.25525927e-02, -3.19541711e-03,  1.87015980e-02, -2.38247216e-02,
        4.60027345e-02, -6.41948683e-03,  4.04525502e-03,  2.46563717e-03,
        1.20621240e-02,  9.47227329e-03,  1.60887931e-02,  1.83971087e-03,
       -9.87780862e-04,  1.72448587e-02,  2.82356534e-02,  8.67104810e-03,
        2.19608955e-02, -1.64882354e-02, -7.08093494e-03,  2.11143196e-02,
       -7.59370392e-04,  6.88842125e-03,  1.66022908e-02, -9.79275722e-03,
        6.50053611e-03, -2.77987868e-02, -6.72865240e-03,  7.12196250e-03,
       -2.75197085e-02,  1.72902551e-02,  2.63259169e-02,  1.33536961e-02,
        5.49771823e-03,  2.02257764e-02, -9.47866961e-03, -1.95743162e-02,
       -1.52008412e-02,  1.82906783e-03, -1.28089366e-02, -8.89652874e-03,
       -2.46416591e-02,  4.86801099e-03,  1.67354234e-02,  1.86583083e-02,
        5.49206976e-03,  7.48685654e-03, -1.57107390e-03,  1.81904645e-03,
        5.48277190e-03,  1.59463584e-02, -2.87516927e-03, -1.17870690e-02,
        1.11697279e-02, -1.96829308e-02,  1.84122566e-02, -1.36007331e-02,
       -3.52862142e-02, -1.83236096e-02,  4.22367603e-02,  3.93675081e-02,
        3.79532129e-02, -2.68320255e-02,  6.23248098e-03, -1.64108668e-02,
        7.54330214e-03, -5.91156313e-05,  7.64996558e-03, -2.41295435e-02,
       -5.52572729e-03,  1.07658152e-02,  7.75361201e-03, -5.47539815e-03,
       -1.39082698e-02, -7.66166206e-03,  2.70606987e-02, -6.96721626e-03,
        3.05199549e-02,  3.15535697e-03,  6.18673570e-04, -1.13676153e-02,
       -9.21747088e-03,  1.88874267e-02,  5.34149306e-03, -4.67314348e-02,
        2.85126027e-02,  6.38498459e-04,  6.74495474e-03, -1.91013776e-02,
       -7.05332262e-03, -6.72731409e-03,  9.74766910e-03, -1.53495530e-02,
        3.45689617e-02,  8.79143365e-03, -1.68813430e-02, -1.25083355e-02,
       -2.38154754e-02,  3.93720008e-02,  1.76301375e-02,  1.06914772e-03,
        3.11659537e-02, -2.68434193e-02,  3.43813449e-02, -1.22934412e-02,
       -8.88929237e-03, -4.50459011e-02, -1.61650665e-02, -1.39516303e-02],
      dtype=float32), array([-1.04020104e-01, -7.17260242e-01, -7.63311744e-01, -2.18563914e-01,
       -4.90035087e-01, -6.08567774e-01, -1.63572207e-01, -5.57403326e-01,
       -2.68793911e-01,  7.48003840e-01, -2.19299003e-01,  1.72368735e-01,
        1.42710149e-01, -3.96727085e-01, -3.45470667e-01,  3.56889069e-02,
       -3.09812367e-01, -5.70919514e-01, -1.52248845e-01, -4.62250948e-01,
        1.94841363e-02,  5.57753205e-01,  6.63365364e-01, -1.04648337e-01,
       -2.50788093e-01,  1.39275759e-01,  6.65021420e-01,  6.71508074e-01,
        3.35422486e-01, -9.57663059e-02,  3.73390377e-01,  5.38210690e-01,
       -1.05238771e+00,  3.59343261e-01, -2.23512843e-01,  2.62772143e-01,
        3.62601131e-01,  1.21191835e+00, -1.21514844e-02, -3.64031881e-01,
       -2.79902220e-02,  5.85090935e-01,  1.64260473e-02,  1.07846111e-02,
        1.51512280e-01,  3.85472998e-02,  1.54982150e-01, -2.92601258e-01,
        1.68940853e-02,  3.87521535e-01, -2.67796487e-01,  3.64739060e-01,
        1.32976577e-01,  3.07724386e-01,  3.68759900e-01, -1.01288982e-01,
        2.12077707e-01, -4.55372483e-01,  1.97477341e-01, -1.00896508e-01,
        4.35121775e-01, -1.08133562e-01,  1.30885392e-01, -1.92073107e-01,
       -1.62772849e-01,  5.10943770e-01,  2.15627894e-01,  7.42559433e-02,
        1.95381984e-01, -2.52084821e-01,  4.80328828e-01,  2.52163410e-02,
       -5.80028653e-01, -8.05123866e-01,  4.44227159e-01, -7.16567934e-02,
       -2.14375451e-01,  7.68655956e-01,  3.74797195e-01, -1.76406682e-01,
       -1.54632866e-01,  4.57344726e-02,  1.35484800e-01, -1.88549310e-01,
        3.13196748e-01,  4.27333623e-01,  1.87102973e-01, -3.17545891e-01,
       -4.06047314e-01, -4.73061651e-01, -3.27511817e-01, -5.46747684e-01,
        4.65008289e-01,  9.29043815e-02,  1.94642186e-01, -7.43205905e-01,
       -2.47959226e-01, -7.53782392e-02, -5.54831982e-01,  6.36756063e-01,
       -3.08265954e-01, -6.94781601e-01,  1.82734318e-02, -8.38668942e-02,
        4.89566755e-03,  7.15665162e-01, -4.93516475e-01, -2.63225079e-01,
       -1.36094883e-01, -3.59855711e-01,  4.61618811e-01,  4.63030964e-01,
       -4.68220532e-01,  2.88719893e-01,  4.07726347e-01,  7.71677375e-01,
        4.78540584e-02, -5.16080499e-01,  1.20363049e-01, -1.67645350e-01,
        4.11157519e-01, -2.07957476e-01,  8.80747586e-02,  8.16362441e-01,
       -1.05422072e-01, -1.51344165e-01, -2.23610744e-01,  4.35381472e-01,
       -1.30254850e-01, -2.00802431e-01,  1.41397417e-01,  2.90209830e-01,
       -6.93970770e-02, -3.38470221e-01, -6.16497874e-01, -7.16100186e-02,
        2.60873228e-01,  1.12726554e-01,  1.65075079e-01, -7.78980851e-02,
       -1.59181073e-01,  4.00234729e-01,  3.24285507e-01,  1.57195821e-01,
       -1.01843551e-02,  6.31584883e-01,  7.69564152e-01, -1.78706050e-01,
        8.58638167e-01, -3.61827314e-01,  3.82277161e-01, -6.28035963e-01,
       -9.27882433e-01, -7.87273399e-04, -4.06317413e-01, -2.64789492e-01,
        2.96801746e-01, -1.27070948e-01,  3.91244978e-01, -2.53307611e-01,
        3.29734311e-02,  4.25555140e-01, -1.78505391e-01, -2.36652702e-01,
       -6.48694709e-02,  3.49815696e-01,  2.31227666e-01,  1.39916660e-02,
        2.74496675e-01, -9.47156549e-01, -3.32024544e-01, -2.96912462e-01,
       -8.39220881e-02,  4.42977309e-01,  2.66851276e-01, -4.53122891e-02,
       -3.32420468e-01, -3.55392814e-01, -1.75290629e-01,  1.03152208e-01,
        3.38913649e-01, -4.53983605e-01,  6.03118777e-01,  3.92407954e-01,
        6.75778866e-01,  1.59620672e-01, -3.25087249e-01,  2.10255727e-01,
        4.34668154e-01, -2.46303156e-02, -3.57684404e-01, -7.14053035e-01,
        1.62908271e-01,  2.08830371e-01,  4.13472205e-01,  2.75581956e-01,
        9.41417217e-02,  5.13232708e-01,  3.16800147e-01, -1.00083804e+00,
        2.58117020e-01,  2.39978656e-01,  1.09968401e-01, -4.76222008e-01,
        7.25198865e-01, -6.13692030e-02, -5.48016131e-01, -7.04016209e-01,
       -3.64046633e-01, -2.40597010e-01, -1.21475337e-03, -1.42849386e-01,
       -3.98343742e-01, -7.08237469e-01,  5.93258440e-02,  2.89944589e-01,
        4.71452147e-01,  3.73549104e-01,  1.20742068e-01, -1.14555515e-01,
       -6.13849938e-01,  3.14336866e-01, -2.74087507e-02, -7.43399203e-01,
        2.38032848e-01, -2.02208996e-01,  3.09385899e-02,  1.79189473e-01,
       -1.90828115e-01,  1.24909252e-01, -3.41385193e-02,  5.93943775e-01,
       -7.04952121e-01, -1.11790016e-01, -5.07520549e-02, -2.15955541e-01,
       -1.58073619e-01,  1.08200423e-02, -5.42264700e-01, -1.94054872e-01,
       -2.70894915e-01, -3.68874818e-01,  3.91544610e-01,  4.58837658e-01,
       -5.08163154e-01,  2.61879086e-01,  3.86744618e-01,  4.90991443e-01,
       -1.05424561e-01, -8.50618705e-02, -2.55630553e-01,  2.69407153e-01,
        1.22785144e-01,  4.62474406e-01,  2.09845409e-01, -3.59676212e-01],
      dtype=float32), array([0.37074387, 0.46716157, 0.35670665, 0.26503837, 0.5365635 ,
       0.32507935, 0.623158  , 0.4328574 , 0.3874899 , 0.5181467 ,
       0.32803303, 0.35016754, 0.31468788, 0.2961837 , 0.30541572,
       0.37420726, 0.4024473 , 0.42684484, 0.39115688, 0.59221613,
       0.35598257, 0.3735404 , 0.38750988, 0.43124753, 0.4794776 ,
       0.37588453, 0.25191453, 0.7442356 , 0.2917348 , 0.35802647,
       0.29042143, 0.6709375 , 0.69892645, 0.7206522 , 0.38103387,
       0.49684227, 0.3922106 , 0.4506343 , 0.37013373, 0.29613566,
       0.36228594, 0.27968898, 0.34262165, 0.40086666, 0.3303992 ,
       0.34080616, 0.4284229 , 0.40976906, 0.29706836, 0.3064259 ,
       0.5018032 , 0.48109004, 0.3453073 , 0.34785646, 0.36508152,
       0.38341397, 0.44925871, 0.41462865, 0.3910792 , 0.57214165,
       0.34112185, 0.39492923, 0.32044888, 0.4097529 , 0.289925  ,
       0.49199903, 0.4271345 , 0.39389816, 0.3266791 , 0.39092267,
       0.49752715, 0.6149581 , 0.4255252 , 0.44927725, 0.6371409 ,
       0.28645113, 0.46037516, 0.30238232, 0.36758885, 0.45355615,
       0.5101096 , 0.29142565, 0.3983807 , 0.51431036, 0.36898085,
       0.6130904 , 0.36500087, 0.36071596, 0.37372196, 0.43185002,
       0.27666187, 0.36310932, 0.3635926 , 0.2932719 , 0.25464192,
       0.57209283, 0.29431456, 0.47387215, 0.2679453 , 0.3430164 ,
       0.4308698 , 0.7127423 , 0.25050044, 0.2689008 , 0.4558802 ,
       0.6852192 , 0.40904087, 0.36706987, 0.35186774, 0.26937932,
       0.48061737, 0.81464946, 0.48576185, 0.45494714, 0.39110556,
       0.34194422, 0.2816254 , 0.3707197 , 0.43945345, 0.38390183,
       0.43525872, 0.50887764, 0.261468  , 0.3646093 , 0.4117732 ,
       0.2616534 , 0.30050394, 0.3015617 , 0.5327291 , 0.31593972,
       0.29149872, 0.43116763, 0.28289446, 0.5937155 , 0.35997313,
       0.34203562, 0.29061   , 0.40070716, 0.34129685, 0.37741163,
       0.31547594, 0.24562442, 0.40634155, 0.39203325, 0.51702845,
       0.4283359 , 0.38540906, 0.24947152, 0.2839293 , 0.3304462 ,
       0.41959617, 0.3506125 , 0.46065286, 0.6040013 , 0.40085936,
       0.23746474, 0.26621687, 0.53079575, 0.47585544, 0.4886589 ,
       0.3816219 , 0.4390355 , 0.4686566 , 0.30795038, 0.37653828,
       0.30996013, 0.43255177, 0.4559455 , 0.60767233, 0.36173818,
       0.7405866 , 0.7192982 , 0.4149091 , 0.3625382 , 0.41839582,
       0.2520223 , 0.5145151 , 0.4516082 , 0.4033543 , 0.33465096,
       0.6814187 , 0.50843465, 0.5240091 , 0.3461692 , 0.7404525 ,
       0.32521823, 0.3407659 , 0.32744193, 0.41184247, 0.37331554,
       0.5007906 , 0.46377167, 0.28694472, 0.48122892, 0.3823293 ,
       0.5270073 , 0.4567942 , 0.5520329 , 0.53212035, 0.5972149 ,
       0.26889673, 0.44934848, 0.33909205, 0.30937302, 0.44527107,
       0.30117843, 0.3360414 , 0.59792465, 0.50492835, 0.38271382,
       0.46833935, 0.4445577 , 0.324125  , 0.31302786, 0.3879295 ,
       0.58478117, 0.37825605, 0.4178274 , 0.31660813, 0.47162694,
       0.3874039 , 0.33578336, 0.36466733, 0.41260445, 0.25537747,
       0.32001778, 0.31585   , 0.42556038, 0.33167362, 0.5526484 ,
       0.3985246 , 0.3978124 , 0.3383523 , 0.46004876, 0.7465058 ,
       0.41389912, 0.36440685, 0.6060928 , 0.33361948, 0.43876213,
       0.42406762, 0.38730735, 0.39024848, 0.33843058, 1.0879403 ,
       0.3703642 , 0.46784368, 0.5367554 , 0.3240855 , 0.31772986,
       0.64098257, 0.6457408 , 0.5254867 , 0.6722529 , 0.47148067,
       0.34456733], dtype=float32), array([[[[ 1.1900288e-02],
         [-4.6164598e-02],
         [-3.7412480e-02],
         ...,
         [ 1.0548892e-02],
         [ 1.2447764e-02],
         [-1.2923255e-02]],

        [[-6.3575287e-03],
         [ 2.7126539e-02],
         [ 3.2181513e-02],
         ...,
         [-1.3998323e-02],
         [-3.5905298e-03],
         [-1.7011454e-02]],

        [[-2.3193525e-02],
         [ 1.9735893e-02],
         [-2.9470507e-02],
         ...,
         [ 3.1748276e-02],
         [-3.8498178e-02],
         [-4.1887811e-03]]],


       [[[-1.0456208e-02],
         [-6.0120691e-02],
         [-5.6151528e-02],
         ...,
         [-1.4110774e-02],
         [ 3.8330581e-02],
         [-4.8851403e-03]],

        [[-1.4359482e-02],
         [ 2.6852997e-02],
         [ 2.2994500e-02],
         ...,
         [ 8.8312343e-02],
         [ 1.4138281e-02],
         [ 5.5984024e-02]],

        [[ 8.5102119e-02],
         [-1.6591633e-02],
         [-8.1498297e-03],
         ...,
         [-1.3254383e-02],
         [-6.9867931e-02],
         [ 5.6950968e-02]]],


       [[[ 3.8945414e-02],
         [-6.4549260e-02],
         [ 2.4637491e-02],
         ...,
         [ 5.8857299e-02],
         [-7.0610486e-02],
         [-1.3550376e-02]],

        [[-4.0867746e-02],
         [ 5.6662243e-02],
         [ 8.1445776e-02],
         ...,
         [ 5.0157025e-02],
         [ 9.7166441e-05],
         [ 2.6075331e-02]],

        [[-2.2111269e-02],
         [ 3.8756751e-02],
         [-5.9138178e-03],
         ...,
         [ 2.9365018e-02],
         [-4.1609358e-02],
         [-6.7249802e-04]]]], dtype=float32), array([1.0173918 , 1.0068201 , 1.0140002 , 0.96609586, 1.0092334 ,
       1.0113344 , 0.9903634 , 1.0065479 , 1.0069633 , 0.96756715,
       1.0011586 , 0.973082  , 1.0138048 , 0.9877299 , 0.9942528 ,
       1.043661  , 1.0016106 , 1.0333512 , 1.004621  , 1.0083417 ,
       0.996904  , 0.9925606 , 0.98883533, 1.0141706 , 0.9830184 ,
       1.0142795 , 0.9943325 , 1.0197176 , 0.98965603, 0.9779327 ,
       0.9858476 , 0.9701233 , 1.034879  , 0.96884173, 1.0316238 ,
       0.9951197 , 0.9725758 , 0.9926124 , 1.0131457 , 1.000876  ,
       0.98188704, 0.9761288 , 0.9930113 , 1.0108931 , 1.0006557 ,
       0.9886529 , 0.9833998 , 0.9889243 , 0.9895846 , 0.99818647,
       1.000691  , 0.9942995 , 0.9712974 , 0.9881157 , 0.98390174,
       1.0269709 , 0.99243855, 0.9957507 , 1.0059171 , 0.98532516,
       0.99224496, 0.9815187 , 1.0149456 , 1.0006704 , 1.0278969 ,
       1.0053427 , 0.99884903, 0.9849653 , 0.98689646, 1.0012107 ,
       0.99871933, 1.0138891 , 1.0208575 , 1.0041919 , 0.975867  ,
       0.9712186 , 0.9989561 , 1.0119042 , 1.0212028 , 1.0237375 ,
       0.98146814, 1.0225322 , 1.0181757 , 1.0279578 , 0.9874053 ,
       1.0419247 , 0.98654926, 1.01298   , 0.9908984 , 0.9998068 ,
       1.0455995 , 1.0205196 , 0.9938416 , 0.98890114, 0.98174644,
       0.98959506, 0.98000073, 0.98391145, 1.0169975 , 0.99549353,
       1.0088651 , 1.0082096 , 1.0160178 , 1.0197885 , 1.0178865 ,
       0.9676136 , 1.0156393 , 1.0268335 , 0.9942975 , 1.0077928 ,
       1.0076089 , 1.0010464 , 0.99262184, 0.97212875, 0.98722255,
       1.0263498 , 1.020593  , 0.99089485, 1.0289857 , 0.98815906,
       1.0027549 , 1.0034127 , 1.0020267 , 1.003612  , 1.00401   ,
       1.0087036 , 0.97475517, 0.9961161 , 1.0121996 , 1.0216639 ,
       0.9885693 , 1.0185418 , 1.0022911 , 1.0087603 , 1.0020021 ,
       0.99579453, 0.97272515, 0.9814013 , 1.020559  , 0.98866606,
       1.0126677 , 0.99573493, 0.9943625 , 1.0155677 , 1.0094028 ,
       1.0209676 , 0.99519664, 0.98953587, 1.0256819 , 1.0126649 ,
       0.9987135 , 1.0015966 , 1.0062796 , 0.97716874, 0.9977283 ,
       1.0168071 , 1.0121175 , 1.0401518 , 0.99474084, 1.0054315 ,
       1.0175694 , 0.9901877 , 0.99111265, 1.016605  , 1.0280571 ,
       1.0143541 , 0.98717636, 0.99354404, 1.0011078 , 0.9897952 ,
       0.98087275, 1.0023204 , 1.0176395 , 1.0014106 , 0.98516256,
       0.9847224 , 0.98831296, 0.9810498 , 0.988046  , 0.995774  ,
       1.0061127 , 0.9932275 , 0.99524367, 0.99279517, 0.973335  ,
       1.0223155 , 1.0057639 , 0.97622025, 1.001931  , 1.0050375 ,
       1.0006545 , 0.99258614, 1.0250883 , 0.99592274, 0.96772665,
       1.0010225 , 0.9788185 , 0.9899847 , 0.9903653 , 0.9858959 ,
       0.9882744 , 0.984465  , 1.0015506 , 0.9824987 , 0.9577826 ,
       0.9994616 , 1.0194653 , 1.0245795 , 1.0025266 , 0.98122436,
       1.0176704 , 0.9870995 , 0.9742637 , 1.0000832 , 0.98207927,
       1.0085856 , 0.9784998 , 1.0129198 , 1.0321683 , 0.98654664,
       0.9548567 , 1.016406  , 0.98911726, 1.0074304 , 1.0150068 ,
       1.0188199 , 0.9812743 , 1.0088887 , 1.0055407 , 1.0319824 ,
       0.9734396 , 0.948633  , 1.0196189 , 1.0352525 , 0.9891193 ,
       1.01543   , 0.9988428 , 0.99544924, 0.99576974, 0.9939705 ,
       0.9867118 , 0.97973186, 0.9746406 , 0.9766093 , 0.9829409 ,
       0.99529827, 1.0196823 , 1.0142363 , 1.024134  , 0.99763435,
       1.019072  , 0.9795469 , 1.0009755 , 1.0468956 , 0.98833764,
       1.0091618 ], dtype=float32), array([-2.24355608e-03, -2.56529427e-03,  3.98318004e-03, -3.48306559e-02,
       -3.15360120e-03,  1.50402626e-02, -1.69229750e-02, -6.59888331e-03,
        2.85054501e-02, -1.16808508e-02, -3.84557131e-03, -2.70757172e-02,
        1.28896823e-02, -8.03128630e-03, -1.11853173e-02,  2.55023185e-02,
        1.89267118e-02,  2.11763382e-02,  2.00186484e-03,  2.20553931e-02,
       -7.22632860e-04,  1.11133447e-02, -4.87817870e-03,  2.60263756e-02,
        8.13157298e-03, -3.66540998e-03, -4.74855257e-03, -1.60888694e-02,
        7.35927932e-03, -8.87103844e-03, -1.48829855e-02, -9.35611594e-03,
        2.14098208e-02, -1.18905548e-02, -2.06277519e-02, -6.20157458e-03,
       -1.22632980e-02, -1.89793308e-03, -3.74981388e-03, -1.16694858e-02,
        5.58754691e-05, -3.22525250e-03,  1.11487089e-02,  1.73685909e-03,
       -1.07016489e-02, -3.56866070e-03, -1.39421066e-02, -8.87786876e-03,
        5.74204000e-03, -7.25251390e-03,  1.79057345e-02,  6.75172638e-03,
       -2.93553416e-02, -1.94277633e-02,  8.54014652e-04,  2.81963162e-02,
       -1.98100526e-02, -5.61544206e-03,  2.14957148e-02, -1.27950618e-02,
       -1.35951489e-02,  8.84267036e-03,  2.10810872e-03, -1.10293180e-02,
        1.29312240e-02, -1.01124002e-02,  8.74180440e-03, -1.04428679e-02,
        4.28114273e-03,  1.59751102e-02,  9.40050744e-03, -7.59155955e-03,
        3.00880186e-02,  4.94988635e-03,  3.77058610e-03, -1.94643639e-04,
       -4.73917462e-03, -1.31062362e-02,  4.15367866e-03,  3.38916965e-02,
       -2.15526018e-02,  2.50294730e-02,  2.85618287e-02,  3.45011465e-02,
       -7.57340807e-03,  2.51019429e-02, -5.94982738e-03,  7.32382666e-03,
       -6.22265157e-04,  1.04452390e-02,  2.79330425e-02,  1.69937741e-02,
        9.87515505e-03,  6.65684056e-04, -1.21354228e-02, -4.73873084e-03,
       -3.48255187e-02, -2.29681213e-03,  4.05977340e-03, -7.04376213e-03,
        1.65296579e-03,  6.88934559e-03,  2.20173094e-02,  2.46813335e-02,
        1.68049522e-02, -1.53903943e-02,  2.07563769e-03,  2.42683683e-02,
        2.17249617e-02,  2.36177910e-02, -9.64515284e-03,  1.52343558e-02,
       -5.13060438e-03, -4.39303141e-04,  1.69961993e-02, -1.85970962e-02,
        4.57494892e-03,  6.70093996e-03,  4.89378627e-03,  7.78630201e-04,
        1.52515247e-02, -5.77030529e-04, -2.47679162e-03,  3.69744003e-02,
        2.15038452e-02,  2.80374545e-03,  1.72688230e-03, -1.22121917e-02,
        1.46957729e-02, -2.90628268e-05,  1.02022598e-02,  4.16942164e-02,
        1.53876608e-02, -6.01868611e-03, -1.11721866e-02, -8.04866024e-04,
       -2.66645150e-03,  1.01446977e-03,  3.59290442e-03, -9.60058440e-03,
       -1.15468726e-02,  3.19996029e-02, -9.24568251e-03, -1.34133557e-02,
        1.22298868e-02,  5.13401907e-03, -1.68211479e-02, -1.03639830e-02,
       -4.95550781e-03,  2.93128770e-02,  6.41352672e-05,  1.15000298e-02,
        3.77820954e-02, -2.07449459e-02,  6.17084233e-03,  2.65364163e-02,
        2.56023668e-02,  1.87562704e-02,  3.86181939e-03,  6.44476200e-03,
        9.86497197e-03, -2.81011220e-02, -2.30317609e-03,  2.52446998e-02,
        2.66261511e-02,  1.20384386e-03,  9.20777675e-03, -4.83135972e-03,
       -2.84109376e-02, -5.52399643e-03, -2.47493871e-02, -1.33801214e-02,
        8.50758574e-04,  6.48410642e-04, -9.21718590e-03,  1.45868966e-02,
        3.77836870e-03, -2.51051467e-02,  1.73575450e-02,  2.50387210e-02,
        1.08132232e-02, -1.52373901e-02, -3.98429955e-04, -2.08427422e-02,
       -2.89148800e-02,  1.77930724e-02,  6.44344231e-03,  2.31479369e-02,
       -5.83479274e-03,  1.41502107e-02,  2.38585602e-02, -9.30242799e-03,
        1.60634350e-02,  9.60003119e-03,  4.90469206e-03, -4.14162921e-03,
       -2.77725719e-02, -1.58904605e-02, -7.68932374e-03, -1.39440512e-02,
        1.17228262e-03, -1.87659208e-02, -2.50164904e-02,  5.88870514e-03,
       -4.51034643e-02, -1.90830082e-02,  7.98286870e-03,  7.96076842e-03,
        2.42981804e-03, -1.07807061e-02,  2.16734130e-02, -1.27754454e-02,
       -1.87984691e-03, -8.96733068e-03, -9.43634775e-04, -1.88710038e-02,
       -2.24122610e-02,  1.08928774e-02,  1.69277899e-02,  7.46913534e-03,
       -3.08088139e-02,  4.85781766e-03, -1.77755337e-02,  4.05618269e-03,
        8.70626047e-03, -2.20333915e-02, -3.30163203e-02, -2.03175321e-02,
        2.17444933e-04,  1.86591186e-02, -7.32276356e-03, -4.89371382e-02,
        1.16058988e-02,  2.10738089e-02, -1.45679256e-02, -1.37076825e-02,
        1.91777423e-02,  1.69534907e-02, -1.01015493e-02, -5.61740890e-04,
        4.04105783e-02, -1.89336464e-02,  9.22322087e-03, -1.41067952e-02,
        1.46542001e-03,  1.44374720e-03, -2.38013803e-03,  2.40929965e-02,
        6.32512290e-03,  5.89471718e-04,  2.75107734e-02,  5.80081111e-03,
       -2.33165524e-03,  2.19756626e-02,  2.61566732e-02,  4.65646712e-03],
      dtype=float32), array([ 4.62291902e-03, -7.50513840e-03,  1.88808292e-02, -2.70937569e-03,
        3.28945406e-02, -6.65680170e-02,  4.53379266e-02,  5.18813729e-02,
        2.97528300e-02, -7.70986751e-02,  1.33082026e-03,  2.55973265e-02,
       -5.33892661e-02,  7.90275820e-03, -4.84332889e-02,  3.03232800e-02,
       -4.12232764e-02,  1.32468333e-02,  6.49970248e-02,  3.31961811e-02,
       -1.20335687e-02, -4.12434526e-02,  4.80141193e-02,  2.37581339e-02,
        1.01477876e-02,  9.63826757e-03, -4.71666269e-02,  2.41970997e-02,
       -1.09553700e-02, -4.31798771e-02, -3.46755646e-02, -3.41076180e-02,
        4.04742211e-02,  2.90358700e-02,  2.75709797e-02,  1.89911295e-02,
        7.16568604e-02, -8.29917565e-02,  5.79460710e-02, -5.70796803e-02,
       -5.47013879e-02, -4.96875048e-02, -1.61532816e-02,  3.61429490e-02,
       -1.23178186e-02,  3.07879560e-02,  5.98820334e-04, -5.63078485e-02,
        7.58963525e-02, -5.85104153e-02,  4.03088182e-02,  2.26184335e-02,
       -6.41334280e-02, -5.40954843e-02,  4.65548746e-02,  3.56189273e-02,
       -2.23103203e-02, -2.46902686e-02, -3.23802829e-02, -4.81775403e-02,
       -4.30181473e-02, -4.35410663e-02, -3.62866232e-03,  4.22666185e-02,
        3.35360132e-02, -2.00432315e-02, -1.44143868e-02, -7.21024424e-02,
       -3.79079133e-02, -3.97265442e-02, -7.04493150e-02,  5.02559766e-02,
        5.71327433e-02,  3.14135216e-02, -3.60886604e-02, -1.27018401e-02,
       -2.47077905e-02, -9.45851393e-03,  1.13098025e-02, -3.39436978e-02,
       -9.80798751e-02, -8.52086917e-02,  1.76594052e-02, -1.67109501e-02,
       -2.25557815e-02,  1.36063145e-02, -1.53838908e-02,  4.23186570e-02,
        1.10160224e-02,  5.06772613e-03,  1.89298671e-02,  2.97124498e-02,
       -6.90340102e-02, -3.61866914e-02, -2.59515755e-02,  4.60208505e-02,
       -5.63627966e-02, -3.13108899e-02, -6.29112124e-02, -3.04769780e-02,
       -2.94791590e-02, -1.74913444e-02, -8.29652345e-05, -5.19127622e-02,
       -7.86410868e-02, -2.90026870e-02,  4.99639809e-02, -4.87907566e-02,
        6.12876844e-03, -4.98445295e-02,  2.40779631e-02, -4.42931205e-02,
        2.80612819e-02, -3.95627022e-02, -1.69382058e-03,  2.58379821e-02,
       -4.61836858e-03,  3.16928886e-02,  5.57462014e-02, -6.06340915e-02,
       -8.21081698e-02,  2.92024352e-02, -1.45556394e-03, -5.11678159e-02,
        4.21022922e-02,  1.85487848e-02, -3.52587923e-02,  4.83897962e-02,
       -1.14570884e-03,  4.63382788e-02, -2.15842873e-02,  3.88308838e-02,
       -3.68844084e-02,  4.37560827e-02,  3.04841492e-02,  4.82044630e-02,
       -1.01914359e-02, -3.42407934e-02,  2.58910041e-02,  4.04216833e-02,
        2.90567912e-02, -2.41567008e-02,  5.62987514e-02,  2.01999750e-02,
        2.08520666e-02,  4.07837741e-02,  5.07454872e-02,  1.54306844e-03,
        3.57886814e-02, -3.08679659e-02, -5.04670553e-02, -2.15344019e-02,
        5.22339344e-02, -4.43013897e-03, -4.50549014e-02, -8.88828561e-02,
        1.64435674e-02, -5.30247837e-02, -1.70506518e-02, -1.74857359e-02,
        2.92578600e-02,  3.01672127e-02, -3.21781822e-02,  2.08887924e-02,
        1.75937696e-03,  1.61858797e-02, -5.69690503e-02,  1.86189485e-03,
        3.80194783e-02, -1.99581943e-02,  8.28564353e-03,  6.83790371e-02,
       -4.23052423e-02,  3.28861736e-02,  6.07518181e-02,  4.32206579e-02,
        5.14203347e-02, -1.59620307e-02,  1.51533401e-02, -4.74358946e-02,
        5.27633652e-02, -4.84236591e-02, -6.30493537e-02,  4.84059453e-02,
        5.62220216e-02, -7.70221800e-02, -2.84304060e-02, -5.01385033e-02,
       -4.13186289e-02, -3.51994708e-02,  5.48978522e-02, -2.88938284e-02,
        1.93522200e-02, -6.36258647e-02,  3.54568809e-02, -3.90262604e-02,
       -8.63613337e-02, -4.46122549e-02, -3.60611677e-02,  4.95731086e-02,
        3.25051285e-02,  3.52043547e-02, -3.57059017e-02, -1.55066522e-02,
       -4.26319651e-02,  3.60425897e-02, -8.25041607e-02,  5.35834469e-02,
        3.85481939e-02,  7.30151590e-03,  6.02039099e-02, -7.82303065e-02,
       -3.19793001e-02, -8.59208405e-03, -2.51236688e-02,  5.74529208e-02,
       -6.40756711e-02,  2.46773195e-02,  1.21018421e-02,  5.64925112e-02,
       -4.75972742e-02, -3.30147520e-02, -3.37764397e-02, -6.36705905e-02,
        1.60659533e-02,  4.03173678e-02,  2.25458276e-02,  3.56318504e-02,
        4.25306261e-02, -1.41652739e-02,  7.00293183e-02, -1.75128237e-03,
       -4.53772694e-02,  2.61158813e-02, -7.50240535e-02,  3.99610512e-02,
       -4.72697057e-02,  4.21615429e-02, -3.72662544e-02, -9.53314267e-03,
        1.06152687e-02,  1.67724993e-02, -5.06539680e-02, -6.29371032e-02,
        3.00782900e-02, -2.31900662e-02,  8.38444754e-02, -8.14532414e-02,
       -1.50118889e-02,  7.09875301e-02, -6.69941353e-03, -5.22395000e-02,
        3.22279222e-02,  7.17178658e-02, -4.91778590e-02,  3.41315567e-02],
      dtype=float32), array([0.00860609, 0.00918102, 0.0111963 , 0.00838735, 0.00843753,
       0.01252117, 0.01459553, 0.01064677, 0.00917183, 0.01986682,
       0.00882076, 0.00972519, 0.01613464, 0.00812095, 0.00927358,
       0.01058031, 0.00940011, 0.0088191 , 0.0150419 , 0.00859421,
       0.00917852, 0.01225086, 0.01410121, 0.00887716, 0.00735539,
       0.0089381 , 0.01532866, 0.01197816, 0.0115919 , 0.00951768,
       0.01084571, 0.0123889 , 0.0089547 , 0.00837903, 0.01014432,
       0.01106066, 0.01952176, 0.02018169, 0.01551662, 0.01229044,
       0.01622164, 0.01224372, 0.01047722, 0.01029042, 0.00791912,
       0.00858447, 0.00812678, 0.01137321, 0.01490294, 0.01179163,
       0.01085717, 0.01077844, 0.017128  , 0.01475608, 0.01270321,
       0.00969903, 0.01038447, 0.00846367, 0.01026524, 0.00979661,
       0.01338021, 0.01175435, 0.0098784 , 0.01186042, 0.01056408,
       0.00810037, 0.00759723, 0.01631854, 0.01167032, 0.01053784,
       0.01936066, 0.0126465 , 0.01065578, 0.00822619, 0.01218836,
       0.00869174, 0.00845284, 0.00898524, 0.00960807, 0.01123529,
       0.01833175, 0.01652037, 0.00879019, 0.00924901, 0.00953251,
       0.01451559, 0.00978466, 0.01053356, 0.00871169, 0.0077416 ,
       0.00929668, 0.00911252, 0.01290394, 0.01055704, 0.00901513,
       0.00877104, 0.01113222, 0.00844314, 0.01067122, 0.01130693,
       0.00911134, 0.00773992, 0.01032977, 0.01174243, 0.01375339,
       0.01242008, 0.0133715 , 0.01062025, 0.00826651, 0.01024422,
       0.01086887, 0.01654352, 0.00858033, 0.0126874 , 0.00795188,
       0.01040337, 0.00881987, 0.008837  , 0.01223345, 0.01265012,
       0.01910903, 0.00843136, 0.00996773, 0.01433042, 0.00968276,
       0.01114073, 0.0088961 , 0.01211676, 0.00774543, 0.01143468,
       0.00850835, 0.00998367, 0.01064233, 0.00974095, 0.0099372 ,
       0.00979465, 0.00777883, 0.01153042, 0.00917766, 0.01104066,
       0.00969199, 0.00965129, 0.01432887, 0.00977163, 0.00779602,
       0.01201236, 0.01411232, 0.00871249, 0.01004186, 0.00990085,
       0.01355272, 0.00937742, 0.0099032 , 0.00816761, 0.01012024,
       0.01640016, 0.00983263, 0.00997215, 0.00866508, 0.00742698,
       0.00908067, 0.0099784 , 0.00829502, 0.01043015, 0.0084352 ,
       0.00883804, 0.01528774, 0.01041165, 0.01253267, 0.0092471 ,
       0.00716723, 0.01395794, 0.01156726, 0.01196278, 0.01298051,
       0.01130667, 0.01093433, 0.01198389, 0.00775413, 0.01198855,
       0.01784272, 0.01120208, 0.01786486, 0.01552939, 0.01982515,
       0.01409587, 0.01059951, 0.0149833 , 0.01394388, 0.00967437,
       0.01199409, 0.00780325, 0.0087214 , 0.01859513, 0.01084045,
       0.01135574, 0.01589435, 0.01225038, 0.01084221, 0.00939974,
       0.00953075, 0.01165151, 0.009964  , 0.00874123, 0.01069352,
       0.0093409 , 0.01371784, 0.01035857, 0.00849989, 0.00910607,
       0.01466837, 0.01329324, 0.0098341 , 0.00901445, 0.00975389,
       0.01548664, 0.01536273, 0.00971894, 0.0095174 , 0.00986818,
       0.00924489, 0.01169547, 0.00915428, 0.01101955, 0.00883721,
       0.01285017, 0.00877393, 0.00991174, 0.01126923, 0.00765965,
       0.01495207, 0.00715752, 0.01016053, 0.00842016, 0.0222999 ,
       0.01166008, 0.01106002, 0.00873504, 0.01009458, 0.01117893,
       0.00818024, 0.0085944 , 0.01309553, 0.01448571, 0.00860833,
       0.00986794, 0.02087429, 0.02571915, 0.01010256, 0.01488534,
       0.0077291 , 0.01578551, 0.01084846, 0.03029615, 0.01611266,
       0.01119145], dtype=float32), array([[[[ 0.00841996,  0.01860669,  0.07630448, ...,  0.05424757,
           0.06092168,  0.04987837],
         [ 0.05339243, -0.02009327, -0.05286615, ...,  0.0707375 ,
           0.10398078, -0.02228657],
         [-0.08069848, -0.00224358, -0.02819784, ..., -0.03559938,
           0.00618275, -0.08021477],
         ...,
         [ 0.05395672, -0.11613674,  0.04219058, ..., -0.01690966,
           0.0061096 , -0.01954252],
         [-0.04864442,  0.12534943,  0.09357969, ..., -0.06735776,
           0.05654531, -0.06430772],
         [ 0.08800406,  0.01933037,  0.07507786, ...,  0.08851808,
           0.02964086,  0.04003896]]]], dtype=float32), array([1.005829  , 1.0215725 , 0.9768518 , 1.0052619 , 0.9740737 ,
       0.9952358 , 0.9619503 , 0.99123293, 0.99441993, 1.0057254 ,
       1.0209684 , 0.9938071 , 0.9906557 , 1.0119779 , 1.0151362 ,
       1.03352   , 0.9863144 , 1.0301051 , 0.9895308 , 1.0017035 ,
       0.98478705, 0.97173303, 1.0085576 , 1.0176522 , 0.99045163,
       1.0052722 , 1.0315125 , 0.9968333 , 1.0053766 , 1.0011653 ,
       0.9938219 , 1.0012807 , 1.010236  , 0.99209297, 0.9958047 ,
       0.9915746 , 0.99957794, 1.0171648 , 1.0049593 , 1.0260079 ,
       1.0181822 , 0.997018  , 1.0023118 , 0.93444294, 1.0134517 ,
       0.9849808 , 1.0310252 , 1.019292  , 0.96720034, 1.0059704 ,
       0.9707821 , 1.0139904 , 0.996887  , 0.9742157 , 0.9831897 ,
       1.0280584 , 0.99853826, 1.0047354 , 0.9920403 , 0.9748382 ,
       0.996043  , 1.0109005 , 0.97441286, 1.0054682 , 0.99530774,
       1.0134463 , 0.9858421 , 1.0232149 , 1.0090456 , 0.99569964,
       0.97928977, 1.0065079 , 0.98808557, 1.0235307 , 1.0088773 ,
       0.98711073, 1.0075784 , 1.0191863 , 1.0115327 , 0.9927487 ,
       1.0176405 , 0.9882988 , 0.9819849 , 1.0128592 , 1.0062308 ,
       1.0008838 , 1.0251036 , 1.0208018 , 0.99317956, 1.0126238 ,
       0.9708704 , 0.9837843 , 0.9985995 , 1.0298089 , 1.0323516 ,
       0.9759279 , 0.99243665, 1.0081239 , 1.0063844 , 0.9983575 ,
       1.0178479 , 0.9758654 , 1.0060743 , 1.0179789 , 0.9530198 ,
       0.9943365 , 1.006559  , 0.9929115 , 1.0123978 , 0.9759259 ,
       0.97620124, 0.9996833 , 1.0135583 , 0.99664575, 1.0033644 ,
       1.0124403 , 1.0107534 , 1.0151414 , 0.9892066 , 1.0070003 ,
       1.0108349 , 0.96959174, 0.97998935, 1.0031829 , 1.0045911 ,
       0.9767091 , 0.9868837 , 0.99812394, 1.004239  , 1.0038282 ,
       0.99253976, 1.045624  , 1.0025734 , 1.0120348 , 0.99220127,
       0.98550034, 0.9848136 , 0.9909441 , 0.98012555, 1.018518  ,
       1.0059537 , 0.9995032 , 1.000467  , 1.0157946 , 1.0162508 ,
       0.99802184, 0.98556894, 1.0250847 , 0.98285913, 1.0247037 ,
       0.98536766, 0.980337  , 0.9994229 , 0.9870031 , 0.99435586,
       1.008707  , 0.9968249 , 1.0302217 , 1.0063312 , 1.0108649 ,
       0.9878026 , 0.96972984, 0.98424864, 1.0003257 , 0.98311496,
       0.98408765, 0.98745656, 0.99158394, 0.98512286, 0.9897512 ,
       1.0106535 , 0.95915645, 1.0149798 , 1.0102724 , 1.0074378 ,
       1.0091035 , 0.99765134, 0.99099976, 0.97825617, 0.99127376,
       1.0192815 , 1.0278717 , 1.0366368 , 0.9751455 , 1.0036415 ,
       0.98596424, 0.9868139 , 1.0070732 , 1.0057474 , 1.0051062 ,
       1.0076556 , 0.9667958 , 1.0080118 , 0.9726406 , 1.0208046 ,
       0.99390143, 1.0397049 , 1.01456   , 0.9713533 , 0.977725  ,
       0.99439424, 1.0023721 , 0.9709434 , 1.0104892 , 0.99548125,
       0.9970049 , 0.9999197 , 0.99927586, 0.98719203, 0.9900075 ,
       1.007869  , 0.982393  , 0.9940511 , 0.98809576, 1.0043167 ,
       0.99478596, 0.9766341 , 0.9796007 , 1.0027646 , 0.9764693 ,
       0.97973037, 0.996545  , 0.9976651 , 1.0064489 , 1.0129983 ,
       0.9854977 , 0.99366933, 0.98794377, 1.0110017 , 0.99397296,
       0.9972906 , 1.020902  , 0.98879296, 1.0012002 , 1.009625  ,
       1.0070426 , 0.98070997, 1.0012754 , 1.0291885 , 1.00205   ,
       0.96601677, 1.0001822 , 1.0118412 , 0.9923491 , 0.9638241 ,
       1.0122111 , 1.0131596 , 1.0096309 , 1.0294977 , 1.0128876 ,
       0.9894605 , 1.0103953 , 1.0088917 , 1.0323865 , 1.0128974 ,
       1.0375367 , 0.9923634 , 1.0119454 , 1.0170246 , 0.9480894 ,
       0.9988793 , 1.0266125 , 0.96546984, 1.0070698 , 1.0177915 ,
       0.9689031 , 1.0088177 , 0.9908656 , 1.0294477 , 0.97687227,
       0.98042303, 1.025547  , 0.9737924 , 0.9683552 , 0.99378866,
       1.0182185 , 1.0110637 , 1.0015105 , 1.0114437 , 0.9983151 ,
       1.0006049 , 1.0016396 , 0.98123807, 0.9837061 , 1.0182983 ,
       1.0053148 , 1.0025822 , 0.99695325, 1.0148834 , 1.0233085 ,
       1.0094573 , 1.0363376 , 1.030805  , 0.99247986, 1.0128771 ,
       0.9949245 , 1.0210781 , 0.99902505, 1.026842  , 0.997487  ,
       0.9972985 , 1.0328563 , 0.9999513 , 1.009335  , 0.98024344,
       0.9857196 , 0.99983454, 0.99896544, 1.0032465 , 0.9992069 ,
       1.0321324 , 1.0052432 , 0.989585  , 0.99096614, 0.99953514,
       1.0352302 , 0.98087144, 1.0322574 , 1.0028741 , 0.9964151 ,
       0.99491423, 0.9821959 , 1.034907  , 1.0040716 , 1.0114039 ,
       1.0084882 , 0.99663764, 0.9994796 , 0.99957746, 0.9928871 ,
       1.0178646 , 0.99192315, 0.9949923 , 0.9766793 , 0.98106754,
       0.9917423 , 0.99116105, 0.9885353 , 1.0099463 , 0.9842362 ,
       1.0163218 , 1.0171975 , 0.9896186 , 0.99394697, 0.9764819 ,
       0.9921468 , 1.0043854 , 1.0173223 , 1.0130795 , 0.9970426 ,
       1.0358188 , 0.98502064, 0.96972257, 0.96776944, 0.98271066,
       1.0206205 , 0.99993956, 1.0116054 , 1.0032036 , 0.9980834 ,
       1.0317596 , 0.99981606, 1.0416685 , 0.9875263 , 0.98395145,
       0.9998242 , 1.0103465 , 1.0229698 , 1.0290889 , 0.9712277 ,
       1.0095061 , 0.9795046 , 0.9974401 , 1.0106343 , 0.9850702 ,
       1.0113349 , 0.9996062 , 0.9710091 , 0.9981923 , 0.98906076,
       1.0074053 , 0.9958655 , 0.9831711 , 0.9980319 , 1.0348597 ,
       0.98917145, 1.0171726 , 0.98147666, 0.9730996 , 0.9971306 ,
       0.9712892 , 1.001649  , 1.0055488 , 1.0220515 , 1.0274565 ,
       1.009563  , 1.0237676 , 0.98278105, 0.9812869 , 1.0103586 ,
       1.0201279 , 1.0107529 , 1.0109738 , 0.9887462 , 0.99276185,
       1.0292763 , 1.0148607 , 0.9981584 , 1.0146241 , 0.95724255,
       1.000852  , 0.9982102 , 1.0108507 , 1.0016918 , 1.0321517 ,
       1.0031619 , 1.0032483 , 1.0097077 , 1.0019975 , 0.97827125,
       0.96811265, 0.99923867, 0.97762173, 1.0285777 , 1.004129  ,
       1.0036123 , 0.99927086, 0.9815605 , 0.986955  , 1.0020555 ,
       1.0003713 , 1.0014305 , 1.0056559 , 1.0031384 , 0.99277073,
       1.013293  , 0.9818407 , 0.97497547, 0.9916936 , 0.99242383,
       0.996846  , 0.9937462 , 1.0103462 , 0.99523324, 1.0038329 ,
       0.99799937, 0.99792033, 1.0036899 , 0.9922875 , 1.0287023 ,
       1.0289868 , 1.0510205 , 0.9677971 , 1.0126177 , 1.0005211 ,
       0.99441725, 0.98676413, 0.97237486, 1.0219405 , 0.9848363 ,
       1.0021592 , 1.009873  , 0.98611724, 1.0180409 , 1.0011363 ,
       0.9866996 , 0.9700775 , 1.0082864 , 0.9931096 , 0.9923548 ,
       1.024415  , 0.98436964, 1.0117754 , 0.9566414 , 0.98403287,
       1.0009817 , 0.98559445, 0.9666999 , 1.0046966 , 0.997345  ,
       0.9786021 , 1.009692  , 1.0091946 , 1.0049512 , 0.9843088 ,
       1.0082686 , 0.99961567, 1.0104637 , 1.0008012 , 1.0136993 ,
       0.9965377 , 1.0409861 , 1.0033264 , 1.0354967 , 0.9620698 ,
       0.96573126, 1.0241939 , 1.0164987 , 0.98060644, 0.98586375,
       1.0299827 , 1.0164522 , 0.9745507 , 0.99476814, 0.99301696,
       1.0338969 , 1.0100892 , 0.9992724 , 0.97541887, 1.0032948 ,
       1.0130106 , 1.001737  ], dtype=float32), array([ 1.22596705e-02,  9.34628118e-03,  9.65308119e-03, -9.19620157e-04,
       -2.70974655e-02,  1.76154412e-02, -1.95910167e-02,  1.91162489e-02,
       -1.32902549e-03,  4.98462692e-02,  5.19929044e-02, -4.11014073e-02,
        1.01119801e-02, -2.85478067e-02, -2.23646872e-03,  3.89434621e-02,
        2.60760672e-02,  1.85288815e-03, -6.25315681e-03, -1.35527393e-02,
        1.60553344e-02, -8.91135447e-03, -1.35416137e-02,  2.07646098e-02,
       -2.26793196e-02, -1.92462448e-02, -2.14266311e-02, -1.42700393e-02,
       -2.06910763e-02,  1.54093979e-02,  7.24085420e-03,  1.03907119e-02,
        1.57404952e-02, -6.39969367e-05,  1.90097559e-02, -1.46044493e-02,
        3.84287094e-03,  2.02505123e-02, -3.77326459e-02, -1.50117064e-02,
        2.37065405e-02,  1.38737066e-02, -8.25791806e-03, -3.43013182e-02,
        1.16219893e-02, -2.37735733e-03,  1.56205446e-02,  1.54245272e-02,
       -3.22548524e-02, -1.37256123e-02, -2.36343429e-03, -1.88307045e-03,
       -1.93161555e-02, -1.93457752e-02,  3.76725895e-03, -6.16247160e-03,
       -7.79499533e-03,  2.39568241e-02,  1.21368188e-03, -2.35388093e-02,
       -2.06168927e-02, -6.65423286e-04, -1.66312940e-02,  8.83684866e-03,
       -5.15467534e-03, -1.11193042e-02, -3.12590860e-02,  3.59806349e-03,
        1.60536021e-02,  6.83775451e-03, -2.40803957e-02,  4.97316057e-03,
       -8.73404276e-03,  1.13895135e-02, -5.87568805e-03,  5.41856606e-03,
        2.14500614e-02,  2.05193032e-02,  8.93399678e-03, -1.99261270e-02,
        1.44920591e-02, -1.44246267e-02, -3.29568498e-02,  1.58701465e-02,
       -7.96658860e-04,  5.26068639e-03, -5.22473454e-03, -4.05885652e-03,
       -2.57003936e-03, -1.57112554e-02, -3.94944176e-02,  2.26131715e-02,
        1.87257472e-02,  1.35786533e-02,  3.60643454e-02,  1.50311762e-03,
       -9.15702153e-03, -2.61198101e-03, -8.02473724e-03, -4.13168259e-02,
        7.57220015e-03,  1.13650914e-02,  1.49477152e-02, -1.20358979e-02,
       -1.50679275e-02,  3.02009787e-02,  2.11488660e-02, -3.44846621e-02,
        2.01901589e-02,  5.73024387e-03,  1.48832723e-02,  1.57637894e-02,
       -1.50869796e-02,  7.64875254e-03,  7.24828010e-03,  2.02336907e-02,
        6.27777399e-03, -1.64778978e-02, -3.16768046e-03,  1.28119802e-02,
       -1.71855204e-02, -1.65527463e-02, -1.92545149e-02, -8.22139345e-03,
        1.11894496e-03, -2.07443852e-02,  7.04569684e-04, -1.89067405e-02,
        1.79088283e-02,  7.74260005e-03,  2.19874270e-02,  2.51490008e-02,
       -9.43323225e-03,  5.38170291e-03, -8.65759887e-03, -3.95711605e-03,
       -2.46172231e-02, -2.22777319e-03,  1.66625883e-02, -1.71416346e-02,
       -1.08382646e-02, -2.81724446e-02, -7.97835924e-03, -2.57444419e-02,
       -1.57184750e-02, -1.68505833e-02, -1.19592864e-02,  1.13213044e-02,
       -5.12454612e-03,  9.44407284e-03,  7.79619673e-03, -1.26580326e-02,
        2.28884700e-03, -1.50556630e-03,  3.86401974e-02,  2.66860835e-02,
        9.38175060e-03,  2.91099790e-02, -1.16134314e-02, -5.53853530e-03,
       -1.47998624e-03, -1.38429375e-02,  8.70160107e-03,  1.45278275e-02,
        1.04223127e-02, -1.06061529e-02,  7.74442684e-03,  2.62475829e-03,
       -1.02698011e-02, -5.25816577e-03,  1.02588371e-03, -1.87202971e-02,
        1.12664299e-02,  6.96377736e-03, -9.20002628e-03, -3.19430546e-05,
        2.43028644e-02, -2.54259026e-03, -2.15525590e-02, -2.17530336e-02,
        2.94854138e-02,  9.89202783e-03,  1.24878576e-02,  2.20961515e-02,
        2.06736731e-03, -2.09752587e-03, -1.20037524e-02, -1.60717797e-02,
        2.63104535e-04,  1.49252275e-02, -1.14022112e-02, -1.86546091e-02,
       -1.19318739e-02, -1.18189603e-02, -1.27716633e-02,  1.96945183e-02,
        8.23582429e-03,  8.47659819e-03,  2.10166443e-02,  7.68477982e-03,
       -1.18884714e-02,  2.33592186e-03, -2.70508844e-02, -1.01305302e-02,
        1.07154511e-02, -1.16916681e-02, -1.02844927e-02, -1.21799363e-02,
       -2.16082260e-02, -2.37495005e-02, -9.06749070e-03, -2.51741637e-03,
       -4.71355626e-03,  2.54872218e-02, -1.17990328e-02,  1.86538808e-02,
       -6.47397107e-03, -7.87760969e-03, -1.29508572e-02,  9.36666783e-03,
        1.64101610e-03, -6.02140464e-03, -7.47783389e-03, -2.08789371e-02,
       -5.86888613e-03, -1.30363135e-02,  6.13918249e-03,  3.54906055e-03,
        2.55381828e-03,  2.14508437e-02, -5.47995185e-03,  5.06352913e-03,
        2.65428051e-02,  1.33043574e-02,  7.64517719e-03, -1.84450150e-02,
       -1.27103096e-02, -4.11047880e-03,  8.97947932e-04,  1.23044634e-02,
        5.58083598e-03,  2.33773375e-03,  3.77042405e-03, -7.17720622e-03,
       -1.74436048e-02,  2.56741401e-02,  5.38695371e-04,  1.10493954e-02,
       -2.25467719e-02, -1.28322728e-02, -8.36524740e-03, -2.40503848e-02,
       -3.19749676e-03,  2.32796557e-02,  3.56306732e-02,  1.62736513e-04,
       -2.68050246e-02,  2.23650062e-03,  1.89578682e-02, -1.93336830e-02,
        1.24276401e-02,  3.96322040e-03, -2.69275606e-02, -8.31639487e-03,
       -4.64903656e-03,  2.03410611e-02,  1.55665139e-02, -9.38088924e-04,
        3.83338556e-02, -1.79597065e-02,  2.44804216e-03, -3.60708334e-03,
        1.32970503e-02, -2.63065379e-02,  9.16277990e-03,  5.09818201e-04,
       -1.04500726e-02,  5.27436240e-03,  4.93684877e-03, -6.07416499e-03,
        2.38972548e-02, -8.26468598e-03,  1.70746893e-02, -1.40280714e-02,
       -2.28548553e-02,  4.82520275e-03, -2.29833424e-02,  1.62071642e-02,
        2.37410776e-02,  2.10286975e-02,  3.51503380e-02,  3.54464836e-02,
       -2.21152473e-02, -3.26164663e-02,  2.58374102e-02,  6.54611131e-03,
       -1.94012895e-02, -1.12731224e-02,  1.36788506e-02, -2.67206114e-02,
        8.50065611e-03, -1.73229370e-02, -8.30450188e-03, -2.27542631e-02,
       -8.96570552e-03,  1.09886816e-02, -1.43998163e-02, -1.98816080e-02,
       -1.58722722e-03,  2.15182640e-03, -1.07014338e-02, -1.89624238e-03,
        6.58773570e-05,  3.36910076e-02,  1.12070153e-02,  7.28596235e-03,
       -3.83432657e-02, -9.16314777e-03,  7.43975281e-04, -1.28737185e-02,
       -6.52528042e-03, -1.36508504e-02,  2.86703687e-02,  2.51436681e-02,
       -3.99099775e-02, -3.11012659e-02,  5.67390956e-03,  1.32536341e-03,
       -8.24736338e-03,  9.31599736e-03, -1.52764479e-02, -9.11571737e-03,
       -4.73151973e-04, -1.83023252e-02, -3.68766636e-02, -2.41000596e-02,
        1.82165559e-02, -9.27725993e-03, -9.86453961e-04,  9.46049672e-03,
        1.04002329e-02,  1.49549460e-02,  3.10898898e-03, -6.57284120e-03,
       -2.17787293e-03,  8.19999725e-03, -1.72972251e-02,  9.54600051e-03,
        8.28139856e-03,  1.96303055e-02,  4.00881935e-03, -1.54660745e-02,
       -9.37156286e-03, -2.26041470e-02, -3.17070745e-02,  2.10372452e-02,
        4.95239440e-03,  1.72929075e-02,  1.15663018e-02,  5.61756194e-02,
        1.18696058e-04, -3.42856906e-03,  1.45914052e-02,  4.55345633e-03,
       -1.28929717e-02,  1.86971463e-02,  8.65121465e-03,  7.37859681e-03,
        1.36354538e-02, -3.33156362e-02, -1.25931334e-02, -2.16296734e-03,
       -3.13654840e-02,  9.31081455e-03,  2.76957117e-02,  9.55087226e-03,
        6.30268501e-03,  6.21587038e-04,  2.35668644e-02, -2.72917794e-03,
        9.92411561e-03,  3.12514640e-02, -2.49168370e-02, -2.19415594e-02,
       -2.38274876e-03,  2.32056044e-02,  1.46315238e-02, -2.60114223e-02,
        7.68755516e-03,  8.24984442e-03, -2.91371774e-02, -1.27979815e-02,
       -1.06532574e-02,  1.89598333e-02, -3.56909097e-03,  2.10638698e-02,
        4.18531522e-02,  7.77121074e-03, -4.99343674e-04, -2.15566270e-02,
        1.67225078e-02, -7.66386092e-03, -7.15047121e-03,  6.69330824e-03,
        2.72291880e-02,  1.70319900e-02, -1.06578330e-02,  5.64366812e-03,
        9.04147420e-03, -1.78493559e-02,  1.31422589e-02, -8.57655331e-03,
       -1.06826797e-02,  3.93235199e-02,  9.28862300e-03, -3.58355902e-02,
       -1.67029805e-03, -1.21112564e-03,  6.95340568e-03, -1.15514314e-02,
       -3.42172012e-02, -9.07836948e-03, -3.09132971e-02,  6.49542287e-02,
       -2.22813264e-02, -1.30545469e-02, -6.84159284e-04,  4.99213859e-03,
        5.11736982e-03,  2.00285409e-02, -1.85896438e-02,  3.23120994e-03,
       -6.61155907e-03, -1.58176403e-02, -7.15950951e-02,  7.89600331e-03,
       -5.39063290e-03, -1.82352867e-02, -2.88793296e-02, -2.08124034e-02,
       -2.68793814e-02,  4.27613361e-03,  3.02802143e-03,  7.40012480e-03,
       -1.85586568e-02,  1.88422669e-03, -8.67018197e-03,  1.21063087e-03,
       -4.62717451e-02, -4.84166155e-03,  1.38664329e-02,  3.97207635e-03,
        9.46889725e-03, -3.81389400e-03,  2.53549516e-02, -9.22238640e-03,
       -6.97630690e-03,  3.24434079e-02,  1.14867380e-02, -1.12066446e-02,
        2.98405141e-02,  1.36050377e-02, -9.04809777e-03, -2.09116121e-03,
       -3.60430442e-02,  1.19639654e-02, -3.08612753e-02, -7.26023549e-03,
       -2.65736300e-02, -1.70469824e-02,  1.38839772e-02, -1.55985095e-02,
        6.29973551e-03, -3.22664417e-02, -6.84643770e-03,  1.94488224e-02,
        1.00816321e-03, -1.01141110e-02, -6.00416353e-03,  9.25346371e-03,
        1.69167928e-02,  2.84951204e-03,  4.47304137e-02, -3.23367608e-03,
       -2.26384439e-02,  4.09387378e-03, -7.77166628e-04,  3.21660973e-02,
        3.30803357e-02,  4.69911322e-02,  1.00288158e-02,  3.46220396e-02,
        4.11693901e-02,  4.18723710e-02, -3.36277746e-02, -1.26704993e-02,
       -2.02643732e-03,  1.85410969e-03, -3.25910747e-02,  2.33050380e-02,
       -1.77239478e-02,  3.25898044e-02, -7.28362647e-04,  7.98484019e-04,
        2.22220011e-02, -7.73706939e-03,  1.35895750e-02,  1.30191110e-02,
       -3.25840339e-02, -2.48346664e-02, -7.05451530e-04,  1.16372444e-02],
      dtype=float32), array([-4.81563583e-02,  4.98208374e-01, -2.06203863e-01,  4.90019530e-01,
        2.84930114e-02, -3.02213788e-01, -6.77251965e-02, -1.53454272e-02,
        2.44607508e-01,  7.83373713e-02,  1.69709008e-02,  6.38713129e-03,
       -6.75482690e-01, -7.57752120e-01, -3.11538815e-01, -4.41124961e-02,
       -4.64208126e-01, -6.12439752e-01,  3.62021953e-01, -7.94359267e-01,
        2.88468450e-01, -1.84059590e-01, -4.08809120e-03,  4.06299345e-03,
        1.81984887e-01,  2.52325296e-01, -3.09282899e-01, -1.82540849e-01,
        3.08499455e-01, -9.28946137e-02,  5.10870695e-01, -8.71987194e-02,
       -3.57240021e-01,  3.07112783e-01, -6.03773713e-01, -3.62796158e-01,
        4.15739641e-02, -2.66978323e-01,  3.10069531e-01, -1.63861036e-01,
       -1.63937390e-01, -3.38095962e-03,  2.22382173e-02, -2.03043893e-01,
        1.11042112e-01, -1.32054493e-01, -1.30680725e-01, -5.83234549e-01,
       -3.61150563e-01,  1.20618053e-01, -3.93461883e-01, -3.79795432e-01,
        5.63020147e-02,  1.43652454e-01,  5.01157105e-01, -2.78290570e-01,
        2.01669738e-01, -7.63926804e-02,  9.40613225e-02,  2.18356177e-01,
       -2.00739920e-01, -3.10284615e-01, -5.01964808e-01, -3.23310703e-01,
        4.59496006e-02,  4.74271238e-01, -1.06831968e-01, -1.82456151e-01,
       -2.52985418e-01,  3.09004933e-01, -3.94351035e-01, -4.69037071e-02,
        4.08926398e-01, -2.91332841e-01, -1.41873419e-01, -1.86793894e-01,
        4.52114880e-01,  3.23112130e-01, -2.54015028e-02,  5.51633716e-01,
        5.41644841e-02,  1.44909561e-01, -3.61147016e-01, -2.48096526e-01,
        9.31866542e-02,  1.62762523e-01, -7.09263310e-02,  1.02308154e-01,
        3.37910280e-02, -3.34429801e-01,  4.22090031e-02,  1.25980526e-01,
       -4.05818671e-01,  7.17412010e-02, -1.04107067e-01,  6.57772660e-01,
        1.30963832e-01, -1.56128377e-01,  7.18967011e-03,  8.52421969e-02,
        3.97432655e-01, -2.63870537e-01, -2.82882810e-01,  1.17549710e-01,
       -3.08379591e-01, -2.99753517e-01,  2.71743201e-02,  2.34442398e-01,
        1.55105695e-01,  3.77594352e-01,  4.36265580e-03, -1.68472841e-01,
        2.70936131e-01,  1.33314535e-01, -1.00173104e+00,  8.46007526e-01,
        2.25761965e-01, -1.30344719e-01,  3.14639747e-01, -5.04056513e-01,
       -1.46171451e-01,  3.75025690e-01,  1.06879115e-01, -4.01066355e-02,
       -2.77459502e-01, -5.88520430e-02, -3.35043460e-01, -6.93640858e-02,
        3.06821525e-01,  8.02395791e-02, -4.95838642e-04,  2.44384855e-01,
        2.01388225e-01, -4.82451379e-01,  2.69917279e-01, -4.38670039e-01,
       -6.82476282e-01,  3.79515916e-01,  4.63765979e-01, -2.71445699e-02,
        4.59155172e-01, -2.70881087e-01,  2.82468170e-01, -3.01903665e-01,
       -2.36111864e-01,  4.04477166e-03, -1.05016053e-01,  3.39384116e-02,
        2.37049893e-01, -2.51375139e-01,  2.00860053e-01, -4.18813735e-01,
        5.21365464e-01, -5.67537069e-01, -5.20793319e-01, -5.24468720e-01,
       -1.05494693e-01,  2.53972188e-02, -4.79778908e-02,  4.05167550e-01,
        3.01087052e-02, -3.97403061e-01,  1.90798104e-01,  1.67412981e-01,
       -1.24028347e-01, -4.35405746e-02,  1.42108411e-01,  1.28994405e-01,
        6.69869501e-03,  1.09255217e-01, -2.88928486e-03,  3.23287010e-01,
       -2.15707347e-01, -1.87968969e-01,  4.24607962e-01, -1.62999585e-01,
        1.30331159e-01, -2.14638874e-01,  5.89531064e-01, -1.82890207e-01,
        2.52103597e-01, -6.60012364e-02,  1.66446850e-01, -5.02740107e-02,
        4.31859314e-01, -5.78656793e-01, -1.58967286e-01, -2.14189187e-01,
       -6.59632087e-01, -1.08491264e-01,  2.12797508e-01,  4.54002261e-01,
        4.80455548e-01,  2.11473316e-01, -2.31300130e-01, -6.87424466e-02,
       -4.23447996e-01, -3.82012613e-02,  3.22571129e-01,  3.24460417e-02,
        9.05655101e-02,  1.58325471e-02,  6.49991259e-02, -4.99727309e-01,
        3.30173910e-01,  5.10506928e-01,  6.99498892e-01,  1.96744382e-01,
        9.48607773e-02,  3.08625400e-01,  1.06179163e-01,  9.29000825e-02,
        4.83081490e-01,  1.18495509e-01,  1.80312842e-01,  2.79910803e-01,
        1.23943768e-01,  1.65370390e-01,  1.55877993e-01, -3.32373023e-01,
       -2.83175141e-01,  1.90017924e-01,  1.78035602e-01, -3.48105505e-02,
       -5.97047865e-01, -4.50045615e-01,  4.50678378e-01,  2.77301282e-01,
       -1.63816791e-02,  2.23764009e-03,  4.81820703e-01, -2.39976287e-01,
        1.74940880e-02,  3.02985050e-02, -3.20499569e-01,  4.41481560e-01,
        2.03818396e-01,  4.21618253e-01, -3.51796538e-01,  6.78967908e-02,
       -3.00524652e-01,  2.82838531e-02,  3.18109393e-01, -1.68558076e-01,
       -4.67268825e-02,  1.30146623e-01, -4.20430243e-01,  3.93166065e-01,
       -2.26888686e-01, -3.43613803e-01, -3.03539991e-01,  1.28881231e-01,
       -7.38362446e-02, -1.93414226e-01,  1.16129078e-01, -2.77605295e-01,
        1.24120645e-01,  2.18206659e-01, -1.64416760e-01,  2.15523809e-01,
        5.95544465e-02,  6.42834380e-02, -4.66804743e-01,  5.46054803e-02,
       -2.99305260e-01, -4.31850284e-01,  1.28491372e-01,  4.00372982e-01,
       -3.05544818e-03,  2.79414773e-01, -2.58143842e-01, -1.46350548e-01,
        2.48733233e-03,  1.92123756e-01, -1.84311718e-01, -6.13412142e-01,
        4.60965075e-02, -2.94686884e-01, -2.62058735e-01, -6.59454584e-01,
       -1.21893667e-01,  5.38697988e-02,  3.86791795e-01,  5.50121844e-01,
        8.52333903e-02, -1.46030605e-01, -2.90920824e-01,  2.33623564e-01,
       -3.88497680e-01, -3.08202446e-01,  6.70735389e-02, -1.28847837e-01,
       -4.61181700e-02,  2.37557948e-01,  8.60417448e-03, -1.02274038e-01,
        1.13083785e-02,  7.38473535e-01,  2.32204229e-01, -1.33371294e-01,
       -5.07138193e-01,  1.06487319e-01, -3.25413942e-01,  2.22553030e-01,
       -5.69361269e-01,  1.05732851e-01,  2.61682689e-01, -4.55075443e-01,
        8.95983875e-02,  2.37965807e-01, -9.61670354e-02, -6.62576079e-01,
        9.01232436e-02, -1.53292462e-01, -7.97152102e-01,  2.44448595e-02,
       -3.41103673e-01,  4.20157574e-02,  3.98712784e-01, -1.96552008e-01,
        3.15164983e-01,  6.26737595e-01,  4.77181524e-01,  1.09620631e-01,
        2.96687663e-01,  1.21659236e-02, -2.15120062e-01, -1.52908817e-01,
       -3.37292850e-01,  5.29969158e-03,  1.32942647e-01, -9.19795260e-02,
       -6.95219859e-02,  4.65400547e-01,  1.15363397e-01,  1.53872788e-01,
       -7.62008429e-02,  8.81995931e-02,  3.04590940e-01,  6.06777854e-02,
        9.90232527e-02, -5.94938278e-01,  6.49292469e-02, -6.51673153e-02,
        4.07829612e-01, -5.42077720e-01, -2.14073092e-01,  3.29099149e-01,
       -5.65743558e-02,  4.84084696e-01,  3.79936546e-01,  2.13748543e-03,
        3.54280740e-01, -1.58857867e-01, -2.16968775e-01, -5.01806498e-01,
        2.60016173e-01,  7.47397095e-02, -4.90102500e-01,  1.09711893e-01,
       -1.09550953e-01,  5.50268292e-02,  3.26428950e-01,  1.36240795e-01,
        2.22430259e-01, -3.22942644e-01,  2.41850868e-01, -2.92501211e-01,
       -2.66968191e-01,  4.51679707e-01, -2.28225905e-02,  2.04993799e-01,
       -2.70179689e-01,  1.32611454e-01,  6.38648927e-01,  5.26520833e-02,
        9.93693247e-02, -5.09911060e-01,  2.20834285e-01, -3.27065557e-01,
        5.18902205e-02, -4.15923089e-01, -5.36565334e-02, -1.33462682e-01,
       -3.00517648e-01, -2.61746228e-01, -1.85813472e-01, -2.75657266e-01,
        6.23040497e-01,  5.83411276e-01,  2.54122913e-01, -1.68192625e-01,
       -3.62131834e-01, -8.53538290e-02, -6.69277191e-01,  2.30649397e-01,
       -7.80194476e-02,  6.25610232e-01,  2.74843395e-01, -7.23761246e-02,
       -2.36037094e-02, -9.11350399e-02, -8.98238048e-02,  1.52316317e-01,
       -1.17907543e-02, -1.45364851e-01,  3.57827283e-02,  4.41614017e-02,
        3.51065755e-01,  2.22688705e-01,  2.68298894e-01,  1.71581537e-01,
       -4.48891148e-03,  3.19460094e-01,  4.26546782e-01, -3.42892349e-01,
       -2.37038478e-01,  3.72919917e-01,  3.38271320e-01,  5.36738992e-01,
        4.63915281e-02,  2.54164755e-01, -9.26555619e-02,  2.87423909e-01,
        3.11917290e-02,  6.81545138e-02,  1.20485537e-01,  1.47835910e-01,
        9.05416429e-01, -4.54198956e-01, -2.95899697e-02, -2.12668255e-01,
       -1.80693656e-01, -3.18465114e-01,  4.61772159e-02,  2.41613597e-01,
        4.14375901e-01,  4.56706166e-01,  3.61704171e-01,  4.50768292e-01,
        4.55639601e-01,  2.65179068e-01, -4.12022799e-01,  3.18443239e-01,
        4.21235077e-02,  2.03692034e-01, -1.28713861e-01, -1.68842435e-01,
        7.40010291e-02, -1.94331035e-01, -1.86015606e-01, -8.57769400e-02,
       -2.16395155e-01, -1.57931298e-01, -1.56747088e-01, -2.89925560e-02,
        1.82254687e-01, -1.98921524e-02, -4.60868955e-01,  6.91583678e-02,
       -1.06214494e-01, -3.07151526e-01, -7.83111230e-02, -1.66551277e-01,
        1.81403905e-01,  3.09272647e-01, -2.01741263e-01,  2.37131000e-01,
       -4.37093407e-01, -2.02697188e-01,  3.52098137e-01,  4.82503980e-01,
        2.81359375e-01,  3.72081131e-01, -9.46850404e-02, -2.20951334e-01,
       -1.41259953e-01, -7.94450566e-02, -1.02815375e-01, -3.07359219e-01,
        1.21178046e-01,  7.52830952e-02, -6.80346847e-01, -7.65077770e-01,
        8.54210835e-03, -3.25489968e-01,  2.13354558e-01,  2.12023139e-01,
        9.79022607e-02, -2.80670673e-01,  1.75513804e-01,  2.31720239e-01,
       -3.02556843e-01, -6.24425054e-01,  1.37093306e-01, -5.18670678e-02,
       -1.08319134e-01, -2.77738214e-01,  1.89195558e-01, -7.36685455e-01,
       -5.71229875e-01, -1.29508182e-01,  6.83401763e-01,  5.29806376e-01,
       -6.08916283e-01,  5.65064311e-01, -1.86631083e-01, -4.25482616e-02,
        3.45234901e-01,  1.90609679e-01,  2.73458570e-01, -9.47695374e-02],
      dtype=float32), array([0.33204982, 0.20153503, 0.3025733 , 0.3970784 , 0.22013323,
       0.2696964 , 0.39849022, 0.22666307, 0.24849957, 0.1945359 ,
       0.15435837, 0.16220702, 0.34166017, 0.247504  , 0.33331367,
       0.24088052, 0.23285966, 0.33967292, 0.38702568, 0.23147126,
       0.22003648, 0.2595875 , 0.2242931 , 0.29124075, 0.21828592,
       0.2744013 , 0.16314778, 0.23622838, 0.35984084, 0.22029474,
       0.2127879 , 0.14759196, 0.23321013, 0.23932694, 0.25357375,
       0.19340052, 0.3762402 , 0.30789715, 0.3847764 , 0.23372503,
       0.34276822, 0.27497625, 0.18089856, 0.20893836, 0.19328375,
       0.1820541 , 0.18470085, 0.1686888 , 0.38801217, 0.2875885 ,
       0.42648444, 0.2796995 , 0.32969248, 0.3768774 , 0.30228367,
       0.18832836, 0.21778053, 0.30891907, 0.19988927, 0.23733383,
       0.21710098, 0.260496  , 0.20400244, 0.20774509, 0.38334784,
       0.32433057, 0.20181902, 0.28852946, 0.23912823, 0.16370453,
       0.31041172, 0.34815478, 0.20797862, 0.3275713 , 0.24394467,
       0.48473507, 0.29222086, 0.23886383, 0.29247096, 0.21071517,
       0.2381996 , 0.3793494 , 0.2554064 , 0.17997476, 0.19398397,
       0.2758085 , 0.22435252, 0.33386803, 0.22231168, 0.19924279,
       0.34938753, 0.26550636, 0.2119583 , 0.29763383, 0.2299987 ,
       0.27706155, 0.259762  , 0.43272936, 0.18426691, 0.21312736,
       0.256638  , 0.32329318, 0.18603578, 0.25387377, 0.31754813,
       0.26756847, 0.34770793, 0.27694315, 0.28196922, 0.24357851,
       0.25548902, 0.252924  , 0.18698135, 0.31000555, 0.36616057,
       0.1982817 , 0.32597467, 0.24042602, 0.36577243, 0.21400416,
       0.32101756, 0.2884664 , 0.24855739, 0.3927021 , 0.2442413 ,
       0.23896025, 0.24520126, 0.19111107, 0.2600496 , 0.33141035,
       0.29623583, 0.177282  , 0.24725752, 0.20234418, 0.3414982 ,
       0.23753239, 0.26988974, 0.26427892, 0.35476112, 0.23890124,
       0.33157417, 0.22735146, 0.23177879, 0.2506106 , 0.18922605,
       0.2855058 , 0.21804616, 0.263951  , 0.24934655, 0.19804049,
       0.23345283, 0.33541924, 0.20531327, 0.23912561, 0.23869534,
       0.18583082, 0.29183418, 0.38094482, 0.2045012 , 0.26380122,
       0.31781462, 0.26408523, 0.50725394, 0.231775  , 0.20761783,
       0.21434653, 0.2281528 , 0.23396187, 0.40640068, 0.18936637,
       0.2716299 , 0.2025281 , 0.18104556, 0.20949692, 0.1716671 ,
       0.21032763, 0.21547781, 0.18424146, 0.50505805, 0.30511096,
       0.2601506 , 0.26308072, 0.20312703, 0.21518987, 0.5230934 ,
       0.22074814, 0.18455632, 0.31975812, 0.20655352, 0.25837487,
       0.32662505, 0.19855408, 0.24868894, 0.29959297, 0.22243673,
       0.22432865, 0.27570376, 0.28028777, 0.31699812, 0.19985583,
       0.17732011, 0.20196341, 0.32176992, 0.21503825, 0.27953276,
       0.30480325, 0.35634208, 0.19838986, 0.42104778, 0.33480382,
       0.2278061 , 0.3500032 , 0.28553343, 0.18280491, 0.28121302,
       0.30207095, 0.3617032 , 0.27687794, 0.32360274, 0.4352718 ,
       0.2576055 , 0.2798171 , 0.3359751 , 0.26519373, 0.2150763 ,
       0.29366416, 0.28218204, 0.38319883, 0.37591562, 0.15853141,
       0.35596532, 0.61156464, 0.31572923, 0.23506129, 0.39428073,
       0.31315356, 0.25695696, 0.4531167 , 0.27338594, 0.31376255,
       0.19866502, 0.28839177, 0.22083928, 0.22365262, 0.240456  ,
       0.17971583, 0.19060953, 0.26969725, 0.28306583, 0.2544607 ,
       0.2956292 , 0.16270201, 0.29432857, 0.2630217 , 0.34822413,
       0.27750143, 0.2990363 , 0.22151043, 0.25136942, 0.15886475,
       0.5103461 , 0.26198795, 0.1918341 , 0.22172216, 0.20080563,
       0.33281913, 0.31788367, 0.29291764, 0.20620279, 0.4089063 ,
       0.298555  , 0.20433752, 0.23796244, 0.27148855, 0.1795378 ,
       0.2629779 , 0.35351366, 0.23547418, 0.18740347, 0.3269798 ,
       0.17578703, 0.3006694 , 0.20700318, 0.35499486, 0.3961421 ,
       0.3333606 , 0.21241456, 0.20367157, 0.20548846, 0.36400202,
       0.24989225, 0.18143544, 0.3159102 , 0.23568934, 0.23298201,
       0.20169614, 0.3280186 , 0.2532983 , 0.2365754 , 0.1947127 ,
       0.1728936 , 0.259858  , 0.2467334 , 0.17110147, 0.38014263,
       0.17080685, 0.25758353, 0.36993784, 0.37328637, 0.2652458 ,
       0.19838333, 0.35867816, 0.35063875, 0.27648616, 0.27489853,
       0.2151695 , 0.17106414, 0.19111669, 0.26015028, 0.17173062,
       0.18770166, 0.20081672, 0.2727951 , 0.22348233, 0.28039017,
       0.366101  , 0.3087874 , 0.27274755, 0.25754556, 0.3188176 ,
       0.21102706, 0.31816426, 0.2426494 , 0.3290739 , 0.22587726,
       0.21894701, 0.341949  , 0.25002298, 0.2399136 , 0.3201767 ,
       0.43667126, 0.25559193, 0.2946935 , 0.15982644, 0.20822215,
       0.4004862 , 0.29476833, 0.2343677 , 0.30210745, 0.2158074 ,
       0.17849354, 0.26409957, 0.26053092, 0.23745002, 0.29448664,
       0.19968626, 0.5171809 , 0.32074392, 0.29504684, 0.23828782,
       0.17637664, 0.23497385, 0.2579365 , 0.18104309, 0.25879183,
       0.19197491, 0.26465446, 0.2352502 , 0.23264256, 0.37914535,
       0.27425435, 0.25579897, 0.24020384, 0.2673136 , 0.20612285,
       0.22800986, 0.3440289 , 0.30283183, 0.21744885, 0.22119719,
       0.28460583, 0.33129728, 0.24718429, 0.26572332, 0.21850222,
       0.26429036, 0.21090358, 0.20585328, 0.38695645, 0.2920153 ,
       0.3070889 , 0.30203733, 0.27687314, 0.31381404, 0.26584694,
       0.26982298, 0.25134283, 0.22407249, 0.3694131 , 0.22767855,
       0.4327084 , 0.25034145, 0.27197367, 0.24228321, 0.23144034,
       0.43024933, 0.28418818, 0.23621544, 0.19071764, 0.2486438 ,
       0.32780334, 0.33950529, 0.37667036, 0.37129542, 0.26769266,
       0.2240529 , 0.22740148, 0.22113082, 0.2510195 , 0.28524375,
       0.3135743 , 0.2533277 , 0.20486006, 0.23481756, 0.29208487,
       0.22714281, 0.25358808, 0.22602302, 0.32421923, 0.2277227 ,
       0.19296956, 0.2972524 , 0.34078053, 0.24124935, 0.23482078,
       0.1732569 , 0.24019781, 0.29402995, 0.2479433 , 0.35942733,
       0.24461637, 0.7129381 , 0.21076296, 0.14811333, 0.36920634,
       0.2479468 , 0.17234097, 0.1866933 , 0.14769936, 0.25933594,
       0.20388992, 0.20770231, 0.23650487, 0.23157099, 0.24408941,
       0.27342048, 0.3375022 , 0.23169242, 0.19981074, 0.22525975,
       0.1971659 , 0.3340778 , 0.22746906, 0.29710174, 0.18540934,
       0.20695935, 0.1863359 , 0.1979598 , 0.23026995, 0.25537357,
       0.24424706, 0.31299445, 0.285604  , 0.26727575, 0.2490761 ,
       0.20676519, 0.19651434, 0.33110014, 0.3354379 , 0.31716442,
       0.23188528, 0.3553691 , 0.28859258, 0.29764542, 0.20424117,
       0.21763952, 0.27224648, 0.37408093, 0.2771609 , 0.33145323,
       0.22931796, 0.26876578, 0.30490372, 0.27723533, 0.41886994,
       0.21466145, 0.25459713, 0.22585118, 0.37994748, 0.28127682,
       0.19264609, 0.21018031, 0.23554239, 0.2314849 , 0.22146201,
       0.27038118, 0.23749904, 0.24971388, 0.36764196, 0.36307716,
       0.23009768, 0.32623938], dtype=float32), array([[[[ 0.01374866],
         [-0.02482863],
         [ 0.00349307],
         ...,
         [-0.03244509],
         [ 0.02097577],
         [ 0.01893216]],

        [[ 0.02546888],
         [ 0.02619023],
         [ 0.01355421],
         ...,
         [-0.01797151],
         [-0.00859552],
         [-0.00584849]],

        [[ 0.01174123],
         [ 0.03382753],
         [-0.02930221],
         ...,
         [ 0.03308417],
         [-0.02804893],
         [-0.03940592]]],


       [[[ 0.01356719],
         [-0.00724797],
         [-0.02595358],
         ...,
         [ 0.00197264],
         [ 0.03744978],
         [ 0.01352972]],

        [[ 0.04784543],
         [ 0.04464675],
         [-0.010643  ],
         ...,
         [-0.05183452],
         [ 0.04593245],
         [ 0.03024371]],

        [[ 0.02402718],
         [ 0.01048603],
         [-0.01023397],
         ...,
         [-0.00392472],
         [-0.02500834],
         [ 0.00192144]]],


       [[[-0.01345611],
         [ 0.02216   ],
         [ 0.00212035],
         ...,
         [ 0.00474208],
         [-0.00162716],
         [-0.01376739]],

        [[ 0.01557056],
         [ 0.00032364],
         [ 0.00552032],
         ...,
         [-0.04190061],
         [-0.00171923],
         [-0.02569536]],

        [[ 0.0191554 ],
         [ 0.00914219],
         [ 0.02992011],
         ...,
         [-0.02537635],
         [-0.02968002],
         [-0.03875106]]]], dtype=float32), array([1.0027083 , 1.0350056 , 0.970283  , 1.0064181 , 0.97888035,
       0.998513  , 0.96301466, 0.98727226, 0.993451  , 1.0135988 ,
       1.0231586 , 0.9951694 , 0.9899853 , 1.0153648 , 1.0183197 ,
       1.0402801 , 0.9853099 , 1.0331258 , 0.9876702 , 0.99894637,
       0.98655826, 0.96824145, 1.0015748 , 1.0166218 , 0.98500586,
       1.0068357 , 1.0326937 , 0.99770826, 1.0128964 , 1.0009755 ,
       0.9838147 , 0.9974987 , 1.0097685 , 0.9882955 , 0.99480534,
       0.9909716 , 1.0026835 , 1.0258343 , 0.9928288 , 1.035852  ,
       1.0200213 , 0.9980933 , 0.9984235 , 0.9368906 , 1.0167778 ,
       0.98455286, 1.034343  , 1.020718  , 0.96845496, 1.0069543 ,
       0.9704708 , 1.015969  , 0.99672943, 0.9659634 , 0.9813491 ,
       1.0265619 , 0.99796313, 1.0084938 , 0.9888784 , 0.97337276,
       1.0018827 , 1.0136693 , 0.97730684, 1.0087273 , 1.0021524 ,
       1.010529  , 0.98550475, 1.0201253 , 1.0077503 , 1.0104871 ,
       0.97809684, 1.0065103 , 0.9947268 , 1.025585  , 1.0077133 ,
       0.9882146 , 1.0043699 , 1.0225903 , 1.0110728 , 0.994605  ,
       1.0211215 , 0.993339  , 0.98050857, 1.0117396 , 1.0071311 ,
       1.0001597 , 1.0248184 , 1.0233349 , 0.9938255 , 1.0149819 ,
       0.97208303, 0.98455364, 1.001948  , 1.0325627 , 1.0357498 ,
       0.9727782 , 0.985623  , 1.0057478 , 0.99911094, 0.9985252 ,
       1.018819  , 0.97658277, 1.006608  , 1.0139217 , 0.95350266,
       0.9923699 , 1.0021735 , 0.9912226 , 1.0201013 , 0.9734728 ,
       0.97239333, 1.0034275 , 1.0111665 , 0.9955337 , 0.9993239 ,
       1.0144684 , 1.0102544 , 1.0134012 , 0.98903203, 1.0051821 ,
       1.0111386 , 0.96240175, 0.97423714, 0.99921757, 1.007962  ,
       0.9785487 , 0.98536277, 0.9963931 , 0.99861044, 1.0074085 ,
       0.98529357, 1.050882  , 1.0018543 , 1.0137902 , 0.9868876 ,
       0.98375624, 0.98469526, 0.9981096 , 0.9754967 , 1.0299317 ,
       1.0082278 , 0.9963325 , 1.0051067 , 1.0156271 , 1.0195996 ,
       0.99581206, 0.98013896, 1.0234675 , 0.9833592 , 1.0296841 ,
       0.98242766, 0.9818867 , 0.99834114, 0.9853176 , 0.9942246 ,
       1.0143812 , 0.99482316, 1.0283804 , 1.0054393 , 1.0118136 ,
       0.9805392 , 0.9702576 , 0.9838312 , 1.003073  , 0.9749615 ,
       0.9866898 , 0.982778  , 0.9931997 , 0.98565376, 0.9916324 ,
       1.0151782 , 0.9630474 , 1.0093927 , 1.0100892 , 1.0077606 ,
       1.0103468 , 1.0001901 , 0.9926327 , 0.98026896, 0.9912233 ,
       1.0183704 , 1.0264246 , 1.0325267 , 0.97130257, 1.0135984 ,
       0.9836918 , 0.9874071 , 1.0089124 , 1.0051728 , 1.0068201 ,
       1.001507  , 0.9721586 , 1.0121205 , 0.97118   , 1.0256392 ,
       0.99590063, 1.0422956 , 1.0205314 , 0.9720441 , 0.9784512 ,
       0.99455357, 1.0029066 , 0.9661346 , 1.0130744 , 0.9990843 ,
       0.99343747, 0.98987883, 0.99875623, 0.98685366, 0.98407364,
       1.006746  , 0.9820712 , 0.99165213, 0.98555684, 1.0076871 ,
       1.0006263 , 0.9767681 , 0.97640085, 1.0091999 , 0.9796449 ,
       0.9752891 , 0.99579936, 0.9950556 , 1.0072852 , 1.0186865 ,
       0.9853193 , 0.99280626, 0.98114836, 1.0085465 , 0.9958854 ,
       1.0016785 , 1.0199487 , 0.989819  , 0.9953026 , 1.0092559 ,
       1.0080117 , 0.9805779 , 1.0035508 , 1.0310053 , 1.0023482 ,
       0.966202  , 0.99653125, 1.0047016 , 0.98691094, 0.9605657 ,
       1.0109345 , 1.0112627 , 0.9993636 , 1.0285003 , 1.0111443 ,
       0.98514366, 1.010747  , 1.0102541 , 1.0321844 , 1.0086386 ,
       1.0391825 , 0.9924404 , 1.014552  , 1.0190938 , 0.9478927 ,
       1.0097727 , 1.025012  , 0.9601467 , 1.0070412 , 1.0200485 ,
       0.97257996, 1.0137386 , 0.9853724 , 1.0283881 , 0.9794719 ,
       0.984002  , 1.0247176 , 0.9749892 , 0.96365434, 0.9933584 ,
       1.0174428 , 1.0111272 , 0.999372  , 1.0109229 , 1.0032135 ,
       0.99695987, 0.9987208 , 0.9812446 , 0.98243314, 1.0240357 ,
       1.0069524 , 1.0044488 , 0.989515  , 1.0230043 , 1.0246952 ,
       1.0074338 , 1.0414917 , 1.0374895 , 0.99084675, 1.0268779 ,
       0.99000245, 1.0193076 , 0.9951241 , 1.0262192 , 0.99384767,
       0.996376  , 1.0329378 , 0.99989957, 1.0078554 , 0.9801112 ,
       0.98368245, 0.99501354, 0.9985379 , 1.0067083 , 0.9964501 ,
       1.0361335 , 1.0035366 , 0.9867362 , 0.98023725, 1.0029436 ,
       1.0330098 , 0.98096037, 1.0351695 , 1.0004452 , 0.99222434,
       0.9951118 , 0.9782257 , 1.0295879 , 1.0053215 , 1.0221199 ,
       1.0056216 , 0.9996825 , 0.99166566, 0.9968619 , 0.99198407,
       1.0253223 , 0.98862845, 0.9933499 , 0.97385377, 0.9782734 ,
       0.99518216, 0.990052  , 0.9879732 , 1.01138   , 0.98078084,
       1.0177561 , 1.0189073 , 0.9863657 , 0.99281037, 0.97991383,
       0.98944104, 1.0020413 , 1.0211047 , 1.0157707 , 0.9919989 ,
       1.0354455 , 0.98432285, 0.97024244, 0.96422195, 0.9832315 ,
       1.0262432 , 1.0016825 , 1.012877  , 1.0011008 , 0.99808735,
       1.0273017 , 1.0020078 , 1.0485468 , 0.98739254, 0.9855449 ,
       0.9958774 , 1.0078831 , 1.0241598 , 1.0322398 , 0.9660066 ,
       1.0135143 , 0.97674847, 0.9944778 , 1.0157269 , 0.98645246,
       1.0166315 , 0.9977023 , 0.9673662 , 1.0038781 , 0.9874192 ,
       1.0041718 , 0.99698406, 0.97884697, 0.9952816 , 1.0292857 ,
       0.9848844 , 1.0184939 , 0.9785193 , 0.9755868 , 0.9968334 ,
       0.9712227 , 1.0008538 , 1.0044969 , 1.0233797 , 1.0286292 ,
       1.0076857 , 1.0233953 , 0.98212695, 0.98300827, 1.0122908 ,
       1.0245835 , 1.0141956 , 1.0086008 , 0.98901355, 0.99230707,
       1.0293387 , 1.016879  , 1.0044338 , 1.0149921 , 0.9590259 ,
       0.9999824 , 0.997735  , 1.0032837 , 1.0028862 , 1.0361142 ,
       1.0016896 , 1.005139  , 1.0073422 , 1.0017226 , 0.97336173,
       0.9678121 , 1.0002022 , 0.9795506 , 1.0246875 , 0.996124  ,
       1.0087538 , 0.99693894, 0.97887075, 0.98186034, 1.0027609 ,
       1.0126137 , 1.0052797 , 1.0055548 , 1.005075  , 0.99421054,
       1.0136354 , 0.98071337, 0.9750286 , 0.9945283 , 0.99172056,
       0.989674  , 0.9866148 , 1.0093884 , 0.99840695, 1.0157882 ,
       1.0007387 , 0.9925836 , 0.99698704, 0.99521524, 1.031578  ,
       1.0318717 , 1.0730947 , 0.9628983 , 1.0103524 , 1.0012643 ,
       0.9979029 , 0.9831643 , 0.9742875 , 1.0215483 , 0.9843229 ,
       0.9999915 , 1.0090498 , 0.98456997, 1.0281067 , 0.9990007 ,
       0.9838523 , 0.9672024 , 1.0089324 , 0.9988935 , 0.9875918 ,
       1.0211405 , 0.9759324 , 1.0098711 , 0.9567578 , 0.9811351 ,
       1.0007142 , 0.9860007 , 0.96863604, 1.0029925 , 0.999596  ,
       0.9733905 , 1.005908  , 1.0096396 , 1.0098728 , 0.9856336 ,
       1.010194  , 1.0036979 , 1.0144259 , 0.9979674 , 1.0214913 ,
       0.99325144, 1.0335215 , 1.0030627 , 1.0405328 , 0.95855767,
       0.96404713, 1.0267321 , 1.0138435 , 0.98010397, 0.9844642 ,
       1.0359043 , 1.016658  , 0.9727855 , 0.99932015, 0.99381304,
       1.0288385 , 1.0108553 , 0.99681675, 0.9754292 , 1.0040659 ,
       1.0202996 , 1.0023172 ], dtype=float32), array([ 7.70619931e-03,  9.22461879e-03, -1.26477936e-02, -1.76451227e-03,
       -4.20007519e-02, -2.94422451e-02, -1.71662420e-02,  1.05678337e-02,
       -1.98984593e-02,  2.86359265e-02,  2.02605911e-02, -1.22803813e-02,
        1.35294134e-02,  2.66951658e-02,  7.06236111e-03,  2.48522591e-02,
       -1.20320544e-02,  3.98997441e-02, -8.26990791e-03, -2.76503083e-03,
        1.22690909e-02, -2.65106261e-02, -8.67849682e-03,  1.31453173e-02,
       -2.28155069e-02, -1.99520066e-02,  2.69736219e-02, -4.09710873e-03,
       -8.95486306e-03, -6.64354244e-04, -1.95378978e-02,  7.62151182e-03,
       -6.21092971e-03, -2.09035818e-02, -6.67334255e-03, -1.47233196e-02,
        7.96082057e-03,  3.07027027e-02, -5.05707823e-02,  2.92285979e-02,
       -1.40754553e-02, -2.10206048e-03,  1.10841868e-02, -6.13955185e-02,
        2.61694212e-02, -1.83805693e-02, -3.17489286e-03,  3.88047919e-02,
        2.49724975e-03, -1.15032867e-03, -4.47431020e-02, -2.35837558e-03,
       -1.47148101e-02, -4.33331802e-02, -2.29454879e-02,  2.38270778e-02,
       -3.73393930e-02,  1.37598636e-02, -1.06096659e-02, -3.23552988e-04,
       -1.36967385e-02,  2.30345130e-02, -2.65008421e-04, -5.78977307e-03,
        6.19593915e-03, -8.75531603e-03, -8.77181254e-03,  6.92891702e-03,
       -8.85659456e-03,  3.81933004e-02, -1.55422771e-02,  5.82559919e-03,
       -2.53165048e-03,  2.32758634e-02, -6.92681922e-03, -1.92211997e-02,
        1.27248736e-02, -6.54639630e-03,  1.04174903e-02, -1.81771461e-02,
        1.57889929e-02, -2.15773061e-02, -2.16774587e-02,  7.87389558e-03,
        2.66522504e-02,  9.21291485e-03,  2.43181791e-02, -1.83517300e-02,
        1.17955925e-02,  8.89840536e-03, -3.09533179e-02, -3.06768995e-03,
        9.34121199e-03,  3.54996994e-02,  2.19672974e-02, -1.65507756e-02,
        1.86564995e-03, -1.88600160e-02,  3.03788930e-02,  4.54794662e-03,
        6.10986305e-03, -2.57192086e-02,  1.24172235e-04,  2.31699664e-02,
       -4.33059819e-02, -2.71051880e-02,  2.86437403e-02, -3.28159565e-03,
        5.34761604e-03, -2.42418367e-02, -2.92681362e-02,  1.94106419e-02,
        2.06655562e-02,  4.63426905e-03,  9.64497309e-03, -6.21740473e-03,
        1.26694748e-02,  2.28677243e-02,  9.12853051e-03,  1.47554120e-02,
        8.54138657e-03, -1.70943271e-02, -9.45307780e-03,  4.50093672e-02,
        3.28039303e-02, -2.41556522e-02,  4.61616693e-03, -1.08641414e-02,
        2.39232257e-02,  1.44283986e-02, -1.47792033e-03,  1.83915254e-02,
       -1.43719427e-02,  4.82096663e-03, -1.30574321e-02, -3.93205769e-02,
       -2.99162269e-02,  2.25287816e-03, -3.89627144e-02,  1.94964446e-02,
       -2.79910434e-02,  2.25629425e-03, -2.46282830e-03, -9.62939393e-03,
        2.29330454e-02, -7.01819779e-03,  1.74508579e-02,  1.52156875e-02,
       -1.44588817e-02,  2.92664822e-02, -1.86963212e-02,  3.13524739e-03,
       -5.95013890e-03, -1.90085601e-02,  5.77184092e-03,  2.49936581e-02,
       -3.87851382e-03,  1.89508442e-02,  1.48464739e-02,  1.86076295e-02,
        6.80977886e-04, -3.61384894e-03, -2.85260696e-02,  1.57670770e-02,
       -2.96589807e-02,  1.06863128e-02, -5.16733667e-03,  4.99498053e-03,
        8.76650121e-03, -2.25695292e-03,  2.10032109e-02, -2.30062157e-02,
        1.78709049e-02,  3.37031996e-03,  2.19413247e-02, -3.14286142e-03,
        7.89649226e-03, -3.96963488e-03, -2.05592290e-02,  1.57852694e-02,
        4.51755784e-02,  3.64258252e-02, -2.68874993e-03,  2.01568147e-03,
        6.84676925e-03, -1.54336756e-02,  6.77814474e-03,  4.45048604e-03,
        4.84245177e-03, -9.41515900e-04, -6.62342878e-03, -4.38111462e-02,
       -1.13595382e-03, -1.88962407e-02,  2.27094907e-02, -1.60755850e-02,
       -2.07371414e-02,  1.44799268e-02, -2.37365607e-02, -4.22755592e-02,
       -1.06663918e-02, -5.89602999e-03, -2.57479660e-02, -9.36688762e-03,
       -3.94711504e-03,  2.02272297e-03, -2.22060606e-02,  1.28527535e-02,
       -2.13174690e-02, -1.12290047e-02,  1.33899171e-02,  7.99469126e-04,
       -8.33414306e-05, -1.07448529e-02,  2.45946329e-02,  5.79248357e-04,
       -6.49052160e-03, -2.75466088e-02,  2.75271144e-02, -2.45141634e-03,
       -3.02228867e-03, -6.61765318e-03, -1.45647686e-03,  1.15001632e-03,
        4.03892100e-02, -2.00101137e-02, -4.29840293e-03,  8.80874787e-03,
        2.08575409e-02, -4.77160240e-04,  2.84232711e-03,  4.38083559e-02,
       -1.50971645e-02,  5.96322957e-03,  7.74277933e-03, -1.62247214e-02,
        6.42522518e-03, -6.56374730e-03,  2.08882187e-02, -1.34295039e-02,
       -2.15628091e-02, -1.25764357e-02,  2.57095695e-03, -3.82278264e-02,
       -2.23078784e-02,  1.82887670e-02,  1.68537768e-03,  6.04350772e-03,
        2.12784484e-02, -1.03771398e-02, -5.52445231e-03,  1.22869704e-02,
       -5.50234807e-04,  3.99169363e-02,  1.50600737e-02,  2.23776232e-02,
       -1.76240075e-02,  1.54391536e-02,  1.06097246e-02, -3.57357748e-02,
       -1.31837586e-02,  4.58354969e-03, -2.13182885e-02,  2.93602864e-03,
        6.94387220e-03, -4.88929935e-02,  3.60532547e-03, -1.54597964e-02,
        2.79599130e-02, -2.83858720e-02, -3.93131231e-05, -8.45883600e-03,
       -2.25193482e-02, -4.17406447e-02, -2.27266969e-03, -2.24628933e-02,
       -4.35483363e-03, -1.64772142e-02, -7.96705578e-03,  1.20226843e-02,
       -1.71437133e-02,  1.63007155e-02, -1.57496072e-02, -1.98637042e-02,
       -1.91461444e-02, -4.11316473e-03, -4.70699230e-03,  1.32806329e-02,
        2.55364999e-02, -4.00684820e-03,  1.86427161e-02,  2.33027712e-02,
        3.71130481e-02,  1.91371590e-02,  1.50129963e-02,  2.79306644e-03,
        7.67953182e-03, -1.39270481e-02, -7.32494844e-03, -4.10228828e-03,
       -1.41213974e-03,  2.31928565e-02,  1.83515921e-02, -4.16831579e-03,
       -1.08631011e-02, -1.45742949e-02, -1.60299614e-02, -7.51850568e-03,
       -2.68331897e-02, -1.91171560e-02,  2.18839217e-02,  8.73502810e-03,
       -1.97405834e-02,  3.88874486e-03,  9.53611918e-03,  5.34427501e-02,
       -9.58296843e-03,  2.30528712e-02,  1.15235290e-02, -2.34079249e-02,
       -1.93532016e-02, -1.07195852e-02,  6.29918138e-03,  1.20997746e-02,
       -6.48066576e-04,  8.44893104e-04,  4.07118984e-02,  6.85884012e-03,
       -2.49767653e-03,  1.15308044e-02, -6.38269680e-03, -6.09888835e-03,
        1.93322022e-02, -1.49379866e-02, -1.72252748e-02,  4.09599347e-03,
       -1.31258601e-02, -1.84066724e-02,  2.01679189e-02,  8.79327767e-03,
        7.26532610e-03,  2.23388057e-02, -7.93546066e-03, -1.22396946e-02,
       -8.85906629e-03, -1.13708507e-02, -4.93445667e-03,  1.59216914e-02,
        3.90574033e-03,  7.87875336e-03,  5.05757444e-02, -8.76713544e-03,
       -2.63216719e-02, -1.55609166e-02, -2.41504313e-04,  4.58643632e-03,
        8.75227526e-03,  2.14329958e-02,  1.19032376e-02,  2.48451084e-02,
        1.09120263e-02,  9.58118401e-03,  5.21507002e-02,  1.30189294e-02,
       -3.02042756e-02, -1.93995722e-02, -4.43444774e-03,  1.39308525e-02,
        3.34128961e-02, -4.21773978e-02,  4.54768958e-03, -2.80677713e-02,
        4.88250842e-03,  2.07546121e-03, -5.63502498e-03,  1.67524870e-02,
        1.61892921e-02, -4.57266085e-02,  9.63667408e-03, -4.55805287e-03,
        1.19531369e-02, -3.51294801e-02, -1.93619877e-02,  3.72918876e-04,
        2.21266355e-02, -1.47536704e-02, -1.11631001e-03, -3.17325220e-02,
        4.48742969e-04,  4.33092297e-04, -2.66829338e-02, -4.79549449e-03,
        2.14461447e-03,  2.40436196e-03,  6.37326622e-04,  3.47615592e-02,
        1.78734418e-02, -1.20051624e-02, -2.95970663e-02, -8.04979447e-03,
        2.33218856e-02,  1.90193094e-02,  3.00290249e-02, -2.91885957e-02,
       -2.70237606e-02,  1.38122449e-02, -7.12057296e-03,  1.96491368e-02,
        5.77504281e-03, -2.98282802e-02, -1.03859848e-03,  1.83569291e-03,
       -3.19891647e-02, -1.48835890e-02,  2.15248317e-02,  7.09137786e-03,
       -1.25031732e-02, -2.23852601e-02,  1.68932006e-02, -1.23306299e-02,
       -6.97730063e-03,  3.19210207e-03, -4.91895154e-03,  3.30845602e-02,
       -3.71231027e-02, -1.74273842e-03, -8.51498544e-03, -2.37816237e-02,
       -7.81328604e-03, -1.98935252e-02,  6.21267036e-03,  5.88448020e-03,
       -6.35721488e-03,  2.27273498e-02, -4.30679135e-02,  1.07874135e-02,
       -2.69562588e-04, -2.30155829e-02, -4.13217023e-02, -2.24348065e-02,
       -2.79405322e-02, -1.48927113e-02,  2.25037686e-03,  6.20420557e-03,
        3.09083220e-02, -1.00663602e-02,  2.23008748e-02, -2.02086214e-02,
       -1.41813476e-02,  3.34130786e-02,  2.16683336e-02,  2.62861848e-02,
        1.60129890e-02, -4.88091540e-03,  1.77738757e-03, -6.81012683e-03,
       -7.16520147e-03, -1.53140379e-02,  3.92894959e-03, -6.72327774e-03,
        1.33959278e-02,  1.35905687e-02,  1.28488075e-02,  2.92848106e-02,
       -6.17225189e-03, -1.08492235e-02, -9.45261307e-03,  1.26219103e-02,
        2.07533222e-02, -2.65508965e-02,  4.74641239e-03, -1.88504923e-02,
        4.46906388e-02, -4.85282578e-02, -3.89264710e-02, -1.48415267e-02,
        1.70300296e-03,  5.57229808e-03,  9.23477858e-03,  1.07140513e-02,
       -1.35085229e-02, -8.09694268e-03,  1.00800702e-02,  1.37910563e-02,
        1.14687788e-03,  3.80023546e-03,  5.49616758e-03,  1.32029178e-02,
        2.37646233e-02,  3.25633287e-02,  1.52239008e-02,  6.90018572e-03,
        1.51893636e-02,  3.70675921e-02, -2.01638658e-02, -7.59575656e-03,
        5.15316874e-02,  5.59474993e-03, -2.24241838e-02,  1.42842662e-02,
        1.46124316e-02,  8.21709912e-03, -2.73206811e-02, -1.91657036e-03,
       -1.25665804e-02,  2.86168978e-02,  8.36101826e-03,  2.13382971e-02,
       -1.25809154e-02,  1.88918076e-02,  3.55907832e-03, -1.08895889e-02],
      dtype=float32), array([ 0.0549445 ,  0.0405733 , -0.00072961, -0.00876103, -0.00122138,
       -0.02828679,  0.01929724,  0.04703747, -0.04933682,  0.06462757,
       -0.00803403,  0.00898184, -0.00988233, -0.02016694,  0.05030103,
       -0.0075403 , -0.00350419,  0.00577748, -0.02827416, -0.02331332,
       -0.04521045, -0.01273068, -0.00494899, -0.05008184, -0.05622138,
        0.02445932,  0.02846617, -0.0353474 ,  0.07874355, -0.01412365,
       -0.0370855 , -0.03441495, -0.03717684, -0.03992673,  0.00296307,
        0.04316434,  0.00565255,  0.04503518,  0.02200022, -0.05805796,
       -0.03002268, -0.03622052, -0.01996637, -0.01205278, -0.04805455,
        0.03406704, -0.01893791, -0.02057226,  0.00401166,  0.01219752,
       -0.02825445,  0.04245931,  0.03964795, -0.02234015, -0.00739728,
        0.02918199, -0.00205898, -0.02264   , -0.0222616 ,  0.00104753,
        0.00766282,  0.04822625, -0.03653098,  0.00625242, -0.03255835,
        0.02110077, -0.02994881,  0.07517612, -0.04625062, -0.04689788,
       -0.02691418, -0.06248461,  0.00813836,  0.0049337 ,  0.03813407,
       -0.05105187,  0.00873146, -0.00639842, -0.00239272,  0.05103315,
       -0.01593597,  0.02496822, -0.00604891, -0.01428787,  0.02701091,
       -0.03843372,  0.03398502,  0.04829888,  0.01966121,  0.00538318,
        0.04845916, -0.05086002,  0.0114357 ,  0.01484657,  0.0219893 ,
        0.00212886, -0.03343093,  0.00998043, -0.06591305, -0.03221405,
        0.00604091, -0.01508073, -0.02160668, -0.05000778, -0.00665446,
        0.0029997 ,  0.03618094,  0.03828967,  0.04716074, -0.00152043,
       -0.05406116,  0.0114571 ,  0.00767447,  0.00482667, -0.07521336,
       -0.00251592, -0.0044392 , -0.05212962, -0.01784163,  0.00930061,
       -0.04060133,  0.04493836,  0.03809375,  0.00361464, -0.0300878 ,
        0.00999518,  0.00934956,  0.02009342, -0.02880572, -0.03184283,
       -0.04733333, -0.02750663,  0.01599309, -0.0503998 ,  0.01230569,
       -0.00716595, -0.0139624 ,  0.05118734, -0.01551826,  0.04760383,
        0.02766931, -0.01367801,  0.0657768 ,  0.01937796, -0.0450981 ,
        0.0283992 , -0.02368579,  0.00986925,  0.02634729, -0.04076495,
        0.03640351,  0.00781017, -0.04329101,  0.03138425,  0.06751851,
       -0.02134877, -0.03772859, -0.0366705 , -0.01467524,  0.02073519,
       -0.04156189,  0.04610468,  0.03607307, -0.01733501, -0.04871112,
       -0.01855652, -0.03721743, -0.01174959,  0.01396065, -0.01748689,
       -0.07257769, -0.02664199,  0.0228949 , -0.02185957,  0.0059683 ,
        0.05228658, -0.02963196, -0.01979717, -0.0580655 , -0.01932133,
        0.04411327,  0.012029  ,  0.03121638, -0.0122869 ,  0.053789  ,
       -0.01017281, -0.01446381, -0.03128244, -0.02592043,  0.01501572,
        0.04601737,  0.00821428,  0.00662353, -0.03325442,  0.00990485,
       -0.00788926,  0.01077126, -0.02292974,  0.03232469, -0.02140289,
       -0.00955252,  0.03689783,  0.00965069,  0.04626766, -0.05319091,
       -0.0651458 ,  0.04335234,  0.01531126,  0.04969661,  0.0349011 ,
        0.00812464, -0.03695713, -0.04785493, -0.0172482 , -0.04486302,
        0.00244894, -0.01392045, -0.02806543, -0.03117095,  0.04700547,
       -0.02603433, -0.01543581, -0.02389666,  0.02961262, -0.00118766,
       -0.05282263, -0.04784962, -0.04247602, -0.0296767 , -0.05836812,
        0.03153386, -0.01331388,  0.03064823, -0.04451446,  0.03569932,
        0.06027185, -0.04193214,  0.04307268,  0.05249759,  0.0007451 ,
        0.00155366,  0.03704954,  0.00100644, -0.05242039, -0.03362275,
       -0.02258608,  0.02796273, -0.00134183,  0.0236282 , -0.02819343,
       -0.03111422, -0.02541811,  0.02736793,  0.00364007, -0.02808742,
        0.04254467,  0.05781903,  0.00252074,  0.01110904, -0.02787411,
        0.0408145 , -0.0221318 ,  0.01629069,  0.01951297,  0.00178773,
       -0.03409457,  0.04107365, -0.03501971, -0.0287584 ,  0.05530368,
       -0.02874428,  0.01894362,  0.04691786, -0.01348621,  0.04626409,
       -0.01717605, -0.0088027 , -0.02185622, -0.03882171, -0.04986506,
       -0.06418438,  0.00991186,  0.04022017, -0.04367053,  0.03788356,
       -0.00923113,  0.03675681, -0.01134387,  0.02914473, -0.01570956,
       -0.05981248,  0.01885502,  0.00611915, -0.0058068 , -0.05556789,
        0.02925797,  0.04687622,  0.02228095, -0.00426992, -0.01246005,
       -0.03586612, -0.00335897, -0.04944546, -0.00167155,  0.01535423,
       -0.0203861 ,  0.01252473, -0.02282169, -0.00625145, -0.03032165,
        0.01927464, -0.05376117,  0.02676841,  0.02989342,  0.00063694,
        0.00181233, -0.02369946,  0.01216239, -0.04693794, -0.00159687,
       -0.01662851, -0.0456993 ,  0.01121689, -0.05090126,  0.02019531,
        0.00908015, -0.0263575 , -0.00779177,  0.02320584, -0.01793754,
        0.03463756, -0.02162057, -0.01514988, -0.0369975 , -0.02317774,
        0.02484371, -0.03598031,  0.04570969, -0.01670627, -0.0437278 ,
        0.04422855, -0.00156448, -0.01882236, -0.02888474,  0.03510546,
       -0.03330512,  0.02699234, -0.05159998, -0.01184352, -0.00506854,
        0.01006076,  0.00298948,  0.02114944,  0.01491434, -0.02858068,
       -0.04097997,  0.02200949, -0.0633059 ,  0.03715954,  0.02851628,
       -0.0216214 , -0.02245698,  0.06518841,  0.03040427,  0.00666815,
       -0.03883497,  0.01274438, -0.03801354,  0.02608074,  0.02572184,
       -0.04672617,  0.02136283, -0.02009447,  0.03528274,  0.04472996,
       -0.05113974, -0.052433  , -0.05736518, -0.01485559, -0.00354698,
        0.05255063, -0.05165749, -0.01653688,  0.0043709 ,  0.02126661,
       -0.05363381,  0.0143283 ,  0.04509796,  0.00723637, -0.04592481,
       -0.01586909, -0.03789321,  0.05149912, -0.02451324,  0.05190303,
       -0.01290986,  0.01156232, -0.04422409, -0.00333507,  0.01830846,
        0.00593399,  0.04439657,  0.00206115, -0.00383519, -0.02890307,
       -0.01899312,  0.03894151, -0.04486357, -0.00445587, -0.00446268,
        0.007354  , -0.00581481,  0.02634391, -0.02492544, -0.05023909,
       -0.01826488,  0.02708259,  0.01443402,  0.04075091, -0.02939262,
        0.0359326 ,  0.02652057, -0.01354157,  0.04852057,  0.016578  ,
        0.04969686, -0.05097799, -0.00472083, -0.03527706, -0.02472503,
        0.01835105,  0.05131163, -0.01672557,  0.00908427,  0.00079185,
        0.01078775, -0.00204662, -0.03665552,  0.03304987,  0.05107806,
        0.03353511,  0.02755641,  0.01020963, -0.07000262, -0.04451478,
       -0.05036349, -0.02123431, -0.03778982, -0.03198456,  0.00018017,
        0.03393952,  0.0536729 ,  0.02505632,  0.00863427, -0.01185845,
        0.02617911,  0.02997673, -0.02994251, -0.01840862, -0.01543021,
       -0.00186119,  0.02289317,  0.0119175 , -0.05901146,  0.00800449,
       -0.04010751, -0.02456706, -0.0312549 ,  0.02060375, -0.04901853,
        0.01250998, -0.03404457, -0.00175267,  0.02353146, -0.02910897,
       -0.0311861 , -0.03462795, -0.00607112, -0.03339013, -0.05792614,
        0.0333226 ,  0.02893654,  0.00354222,  0.03481075,  0.00195053,
       -0.04823225,  0.03320385, -0.05085778,  0.00980498,  0.03405543,
       -0.01123982,  0.01493197,  0.02005514,  0.00102531,  0.00255849,
        0.02196434, -0.06335744, -0.01489618,  0.00621159, -0.00071343,
        0.04039133, -0.05083152, -0.0126973 , -0.00869706, -0.05024641,
       -0.01589523,  0.02092016, -0.01414104, -0.04563028, -0.04708335,
        0.00085824, -0.02131196], dtype=float32), array([0.01419125, 0.01034228, 0.00822629, 0.01355295, 0.00780616,
       0.00869831, 0.00708835, 0.00941426, 0.00981743, 0.01117045,
       0.00844935, 0.00816168, 0.00707992, 0.00793506, 0.01440518,
       0.00911114, 0.00775624, 0.00753362, 0.00915162, 0.00830056,
       0.00937854, 0.00720529, 0.00856734, 0.01244158, 0.01121309,
       0.00804204, 0.00975386, 0.0100053 , 0.01979406, 0.00774405,
       0.00944522, 0.00991204, 0.00880051, 0.00934836, 0.00857363,
       0.01063375, 0.00789189, 0.01037045, 0.0123595 , 0.01132148,
       0.00837511, 0.00852118, 0.00794754, 0.00701922, 0.01016612,
       0.00851235, 0.008683  , 0.00929312, 0.00707096, 0.00791857,
       0.00737636, 0.01050005, 0.0132304 , 0.00786076, 0.00795672,
       0.00978427, 0.00791736, 0.00935329, 0.00827849, 0.00862978,
       0.00797019, 0.00925601, 0.00919755, 0.00868225, 0.01018918,
       0.00904909, 0.00814622, 0.01275633, 0.00928691, 0.00949826,
       0.00770828, 0.01446563, 0.00856587, 0.00760236, 0.00893095,
       0.0088595 , 0.00822326, 0.00876273, 0.00752021, 0.01171137,
       0.00833569, 0.00941722, 0.00822804, 0.00861645, 0.00924297,
       0.00845827, 0.00899937, 0.0099129 , 0.00855473, 0.00784014,
       0.01285721, 0.00915325, 0.00820786, 0.00767092, 0.00893821,
       0.00878851, 0.00980201, 0.00765312, 0.013676  , 0.00893259,
       0.00868572, 0.0072763 , 0.00807355, 0.01256968, 0.0070902 ,
       0.00762392, 0.00925481, 0.01089735, 0.01083836, 0.00788588,
       0.0100277 , 0.00810517, 0.00805533, 0.00725002, 0.01244964,
       0.00817182, 0.00786781, 0.01163789, 0.00853009, 0.0084272 ,
       0.0083003 , 0.0138244 , 0.00894165, 0.0108735 , 0.01016993,
       0.0076838 , 0.00744991, 0.00827143, 0.00878823, 0.00917644,
       0.01011375, 0.00852719, 0.01170696, 0.00948898, 0.00773623,
       0.00850602, 0.00750354, 0.01546997, 0.00773147, 0.01175162,
       0.01043316, 0.00746418, 0.01223465, 0.00851065, 0.00925918,
       0.00870143, 0.00843111, 0.00832201, 0.00803067, 0.00942812,
       0.00834378, 0.00715076, 0.00981995, 0.00829958, 0.01205691,
       0.00872879, 0.00905533, 0.00830675, 0.00868538, 0.00790123,
       0.01236364, 0.00978049, 0.01221745, 0.00792161, 0.01015692,
       0.00761628, 0.00965674, 0.0080634 , 0.00741887, 0.00802199,
       0.01810692, 0.00877075, 0.00882756, 0.00953212, 0.00822871,
       0.0102946 , 0.00858813, 0.00860889, 0.01539027, 0.0100881 ,
       0.00875321, 0.00771177, 0.00965701, 0.00806713, 0.01377632,
       0.00776655, 0.00785869, 0.00834098, 0.00818187, 0.0081396 ,
       0.00925886, 0.00901359, 0.00845045, 0.00836486, 0.00770544,
       0.00788165, 0.00880647, 0.00842131, 0.0108525 , 0.00828008,
       0.00818276, 0.00946365, 0.00741216, 0.00933633, 0.01258411,
       0.01509086, 0.01236181, 0.00857386, 0.00920707, 0.00959996,
       0.00773262, 0.00791675, 0.01152743, 0.00833717, 0.01275868,
       0.00810014, 0.00907202, 0.00810988, 0.01042702, 0.00901941,
       0.00860836, 0.00811034, 0.00921371, 0.00932263, 0.00798029,
       0.00908271, 0.0110178 , 0.01452763, 0.01054163, 0.01219865,
       0.01175224, 0.00783418, 0.00863373, 0.00903985, 0.00853835,
       0.01501291, 0.00954197, 0.01240438, 0.01027657, 0.00773575,
       0.00880842, 0.00988691, 0.009686  , 0.01065483, 0.0084202 ,
       0.00896243, 0.00874383, 0.0078813 , 0.00875299, 0.00923041,
       0.00823335, 0.00833986, 0.00850625, 0.01010343, 0.00938462,
       0.00949008, 0.01233376, 0.00820144, 0.00850584, 0.00877471,
       0.00923656, 0.00789669, 0.00754184, 0.00815916, 0.00786206,
       0.00836126, 0.0090528 , 0.01077944, 0.01044153, 0.01570207,
       0.00810714, 0.00857655, 0.01094397, 0.00821935, 0.01116546,
       0.00822093, 0.00773792, 0.00841943, 0.00956   , 0.00963787,
       0.01092211, 0.00951927, 0.00954533, 0.01398178, 0.01448873,
       0.00763932, 0.00952221, 0.0076558 , 0.00975844, 0.00893201,
       0.01004941, 0.00863562, 0.00993592, 0.00832826, 0.01180782,
       0.00837229, 0.00943294, 0.00870243, 0.00949749, 0.00810692,
       0.00923011, 0.00825224, 0.01007291, 0.00919529, 0.00733305,
       0.00787504, 0.00862548, 0.00772371, 0.00792753, 0.0081346 ,
       0.00850857, 0.00931274, 0.0077574 , 0.00826881, 0.00737364,
       0.00926999, 0.00842572, 0.00883676, 0.00881461, 0.00774783,
       0.00932101, 0.010667  , 0.00877374, 0.01150585, 0.00825016,
       0.00843438, 0.0093447 , 0.00813108, 0.00845056, 0.00818567,
       0.00964827, 0.01011464, 0.00834237, 0.01214764, 0.00779155,
       0.00849494, 0.00857104, 0.0091566 , 0.00887311, 0.00868818,
       0.013811  , 0.00791538, 0.00846234, 0.00804956, 0.00857695,
       0.00776602, 0.00960056, 0.0116005 , 0.00882239, 0.00865566,
       0.0098849 , 0.00946384, 0.00777413, 0.00740583, 0.0077648 ,
       0.00922849, 0.01213834, 0.0099941 , 0.00810617, 0.00915028,
       0.00993339, 0.00895075, 0.01406411, 0.00881903, 0.00766327,
       0.00835926, 0.007868  , 0.00935704, 0.0088125 , 0.00901775,
       0.00911686, 0.00866316, 0.00864271, 0.00991646, 0.00933007,
       0.01180898, 0.01154618, 0.00907198, 0.00904995, 0.00747338,
       0.01292931, 0.00881096, 0.00887193, 0.00778322, 0.00857529,
       0.00933434, 0.00817375, 0.00898093, 0.01081466, 0.01120883,
       0.00711291, 0.01072954, 0.00899393, 0.00856132, 0.01129977,
       0.00785307, 0.00842787, 0.00897363, 0.00731944, 0.00817028,
       0.00741759, 0.00994891, 0.00828618, 0.00712772, 0.00853521,
       0.00793367, 0.01065588, 0.01139908, 0.00755416, 0.00737838,
       0.00766102, 0.00804497, 0.00997914, 0.00830031, 0.01088683,
       0.00898038, 0.0082443 , 0.00881999, 0.01040915, 0.01044908,
       0.01146913, 0.0128782 , 0.0080442 , 0.01018833, 0.00896616,
       0.01005701, 0.00869583, 0.00726635, 0.01132303, 0.00835798,
       0.01029469, 0.01215459, 0.0075608 , 0.00855998, 0.00834453,
       0.00849147, 0.00750606, 0.01015871, 0.00961125, 0.01099048,
       0.01052683, 0.00954692, 0.00813229, 0.01129529, 0.01053679,
       0.00927159, 0.00844711, 0.00823   , 0.0087512 , 0.00803119,
       0.00928028, 0.01184914, 0.00755736, 0.00805026, 0.00791989,
       0.00826784, 0.0096305 , 0.0088139 , 0.00847643, 0.00869465,
       0.00840342, 0.00743337, 0.00782496, 0.01191439, 0.00820357,
       0.00963555, 0.00818914, 0.01024399, 0.00766158, 0.00993692,
       0.00816429, 0.00905807, 0.00846373, 0.00858554, 0.00888468,
       0.00839147, 0.00884524, 0.0074314 , 0.01123204, 0.00946645,
       0.00800225, 0.00922186, 0.00792583, 0.0084145 , 0.00826817,
       0.01169997, 0.00854853, 0.00914101, 0.00800348, 0.00952244,
       0.00859571, 0.00812525, 0.00781231, 0.0077448 , 0.00747291,
       0.00856921, 0.01489899, 0.00826983, 0.00911458, 0.00749194,
       0.01040943, 0.01021042, 0.00786815, 0.00805803, 0.01082724,
       0.00914816, 0.00801972, 0.00807427, 0.01320828, 0.01280848,
       0.00855081, 0.00750065], dtype=float32), array([[[[ 0.03134119, -0.05252892,  0.0209724 , ...,  0.02804641,
           0.01820452,  0.05997317],
         [-0.04696393, -0.01285721,  0.0376615 , ..., -0.02747732,
           0.07308377, -0.03968979],
         [ 0.03082402, -0.00956168,  0.02499636, ...,  0.04892471,
          -0.00064777,  0.04837745],
         ...,
         [ 0.04132307,  0.02330105,  0.04632905, ...,  0.05077988,
           0.0476767 ,  0.03315867],
         [-0.00860347, -0.02829352, -0.04182379, ..., -0.06132035,
          -0.08018781,  0.08252075],
         [ 0.03556455, -0.00159226,  0.06643242, ..., -0.04401814,
          -0.04401486,  0.02372354]]]], dtype=float32), array([0.9934308 , 1.0007983 , 0.9915828 , 1.0100873 , 0.99077564,
       0.99237293, 0.9774544 , 0.99378926, 1.0137526 , 0.9971515 ,
       1.0060248 , 1.0235443 , 1.0066323 , 0.96320266, 1.0213325 ,
       1.0148392 , 0.9779967 , 1.0529273 , 0.9785166 , 1.0280074 ,
       1.0051367 , 1.0213174 , 0.98219156, 1.0010422 , 1.025335  ,
       0.963647  , 1.021107  , 0.9937999 , 1.0063263 , 0.98245   ,
       1.0027655 , 1.0275073 , 1.0122523 , 0.99977136, 0.9969804 ,
       0.9760145 , 0.9834331 , 1.009597  , 0.9894035 , 0.9864121 ,
       0.98265535, 0.9831465 , 0.9955292 , 1.0057164 , 1.031388  ,
       1.024659  , 0.9688564 , 0.99681365, 0.9825005 , 0.99110633,
       0.98939556, 0.99292177, 0.9640911 , 1.018048  , 0.98057455,
       1.0062025 , 0.98153305, 0.99419826, 1.0055841 , 1.0283791 ,
       0.98947746, 0.97151476, 1.0015632 , 1.0109708 , 1.0046929 ,
       1.0024266 , 1.0059311 , 0.98806083, 0.98718125, 0.98255086,
       0.9955005 , 1.0010899 , 0.9821667 , 1.0056627 , 1.018357  ,
       0.983443  , 1.0128    , 0.98604196, 0.99850225, 0.98603654,
       1.0084187 , 0.9679208 , 0.9902071 , 0.99454737, 0.99621576,
       1.0065684 , 0.98102653, 0.99857765, 1.0136113 , 0.99460226,
       1.0101924 , 1.0352901 , 0.9976774 , 1.0308121 , 0.97357845,
       1.0054008 , 1.0146784 , 0.9704273 , 1.0011394 , 1.0146595 ,
       0.9847082 , 0.98915446, 1.016681  , 0.9899098 , 1.00241   ,
       1.0107433 , 0.9823571 , 0.98727274, 0.97672135, 1.012678  ,
       0.9885431 , 1.0130585 , 0.95498276, 1.0158107 , 0.9863683 ,
       1.0185937 , 1.0014179 , 1.0163003 , 1.0134183 , 1.0031037 ,
       0.9820645 , 0.9929643 , 1.0425221 , 0.9990118 , 0.98543173,
       1.0510296 , 1.0291927 , 0.98802495, 0.99539894, 0.99159235,
       0.9877437 , 0.9960642 , 1.0033364 , 0.99066705, 1.0054938 ,
       1.0212239 , 1.0016418 , 1.0073146 , 0.9972918 , 1.0257176 ,
       1.0328071 , 1.014874  , 0.98669404, 0.9740694 , 0.9911398 ,
       0.9919239 , 1.0102934 , 1.024085  , 1.0162572 , 1.0108988 ,
       0.98132676, 0.98849124, 0.9960034 , 1.0003053 , 1.0037304 ,
       1.023374  , 0.981055  , 1.0035733 , 0.9957666 , 0.9865974 ,
       0.96614087, 0.9777513 , 0.98038334, 0.9994555 , 1.013474  ,
       0.9976167 , 1.0087547 , 0.98981553, 0.97717196, 1.0124011 ,
       1.0233002 , 0.9869145 , 1.0090839 , 0.9852267 , 0.9867527 ,
       0.99015206, 0.9796514 , 0.99050325, 0.9794883 , 0.9964239 ,
       0.9749446 , 1.0044082 , 0.9708287 , 0.99382937, 0.9723123 ,
       1.0072975 , 1.0340064 , 1.0423886 , 1.0136511 , 1.011178  ,
       1.0121801 , 0.98332506, 0.99922264, 0.9621587 , 0.96168864,
       1.0114006 , 0.9784273 , 1.0161073 , 1.0252376 , 0.9758768 ,
       0.9779188 , 0.98415184, 0.9734145 , 0.9853051 , 1.008963  ,
       0.99481195, 0.99100757, 1.0110003 , 1.003842  , 0.99092275,
       0.9810504 , 1.0068455 , 0.9810856 , 1.0072405 , 0.99029607,
       1.0040789 , 1.0150023 , 1.000531  , 1.0053537 , 1.0277528 ,
       0.9847425 , 0.97620684, 1.0197691 , 0.98813087, 1.0104299 ,
       1.0061957 , 0.9662356 , 0.98147434, 0.99341077, 0.9859624 ,
       0.9744786 , 1.0003126 , 0.98720455, 0.9917882 , 0.98028207,
       0.98748213, 0.9856618 , 1.0167656 , 0.98525345, 1.0008652 ,
       0.9835251 , 1.0144898 , 1.0130202 , 0.99065495, 1.0012083 ,
       0.9837881 , 0.9854478 , 0.9974194 , 1.0274508 , 1.0027069 ,
       1.0298901 , 0.9974986 , 1.0042282 , 0.98024803, 1.0016288 ,
       1.014031  , 0.99319947, 0.97876865, 1.0072196 , 1.0283253 ,
       0.9818359 , 0.9931572 , 0.99648786, 0.99485636, 1.007836  ,
       1.0552858 , 1.0058881 , 1.0092086 , 1.0102184 , 1.0220997 ,
       1.030385  , 1.0241656 , 1.0174357 , 0.9993897 , 0.9841203 ,
       1.0038085 , 1.0113448 , 0.9877249 , 0.99406797, 0.9901693 ,
       0.98249483, 1.0033278 , 1.0285008 , 1.0235486 , 0.98091054,
       0.99548054, 1.0300831 , 0.99668443, 1.0497197 , 1.0039226 ,
       1.0003917 , 0.9926175 , 0.9959984 , 1.007316  , 1.0020502 ,
       0.95857626, 0.99997795, 0.98745984, 1.0036266 , 0.9800058 ,
       1.0126579 , 0.9795064 , 0.9662134 , 0.9642002 , 1.0000565 ,
       1.0119648 , 0.99009025, 0.98285306, 1.0017322 , 1.0298909 ,
       0.9747229 , 1.006788  , 0.9923124 , 0.9981739 , 0.9862702 ,
       0.97117746, 1.0161978 , 1.0064934 , 0.98603946, 0.99422985,
       1.008881  , 0.9878002 , 0.993794  , 0.9968424 , 0.999421  ,
       0.9762682 , 1.0032188 , 1.0336401 , 1.0128084 , 1.0526896 ,
       1.0249896 , 1.0232133 , 1.0214736 , 0.97157085, 0.9913154 ,
       0.9872468 , 1.0201306 , 1.0383785 , 0.98585576, 0.9916201 ,
       0.99994576, 1.0155355 , 1.0025558 , 0.99690866, 1.0182414 ,
       0.98240703, 0.99179286, 1.0115304 , 1.0248153 , 1.0022558 ,
       0.99697167, 1.028243  , 1.0218449 , 1.0344752 , 1.0226669 ,
       0.9980895 , 1.0106062 , 1.0036054 , 1.0471895 , 0.9826353 ,
       0.9998893 , 1.0027655 , 0.99206924, 0.998815  , 0.9940524 ,
       1.0212071 , 0.9937779 , 0.9854283 , 0.9902479 , 1.0125206 ,
       0.9795795 , 0.9988099 , 1.0033884 , 0.9880451 , 0.97668666,
       1.0036938 , 0.9791681 , 1.0371758 , 0.99654764, 1.0126046 ,
       1.0144652 , 1.0097133 , 1.0349532 , 0.9760915 , 0.9887886 ,
       1.0584474 , 1.0129052 , 1.0275197 , 1.0257947 , 0.9740399 ,
       0.9984057 , 1.0073    , 0.9961969 , 0.9818172 , 1.0199955 ,
       1.0122101 , 1.0109673 , 1.0056936 , 1.019253  , 1.0290793 ,
       0.9921407 , 0.9807567 , 0.9960619 , 0.994371  , 1.0068045 ,
       1.01842   , 1.0349422 , 0.99475765, 1.0367789 , 0.9944569 ,
       0.98055345, 0.9538301 , 1.0003326 , 0.9602224 , 1.031708  ,
       1.0166552 , 1.0043005 , 0.9743596 , 1.015891  , 1.0065517 ,
       0.9960857 , 1.0023865 , 1.028011  , 0.96512336, 1.0132194 ,
       1.0001843 , 1.0045542 , 0.9997222 , 1.0462251 , 0.9848327 ,
       0.99219966, 0.9837499 , 0.98639154, 0.9912173 , 1.020238  ,
       0.9991721 , 0.9898193 , 1.0030066 , 1.0112212 , 0.99651355,
       1.0088923 , 1.0096575 , 0.9993702 , 1.0029172 , 0.9945447 ,
       1.012409  , 0.987789  , 1.0118518 , 0.9459327 , 1.014788  ,
       1.0201776 , 0.9905092 , 1.0087932 , 1.0016454 , 1.0335066 ,
       1.0016412 , 0.9993425 , 1.0101552 , 1.0124314 , 1.0125366 ,
       0.9996183 , 1.0334855 , 0.9998448 , 1.0227592 , 0.948159  ,
       1.0250396 , 1.0045811 , 0.99711925, 1.031783  , 1.0031554 ,
       1.0359833 , 0.9903578 , 1.0039266 , 0.9694533 , 0.9800795 ,
       1.0237281 , 1.0162785 , 1.0034086 , 1.0201991 , 1.0044577 ,
       0.98901105, 1.0288792 , 1.0220021 , 1.0107942 , 0.9764094 ,
       1.018235  , 0.9795094 , 0.99084646, 1.0014288 , 0.9993771 ,
       1.0015316 , 1.0009453 , 1.018523  , 1.0129175 , 0.9871195 ,
       0.97604966, 1.0081632 , 0.98171693, 1.0319068 , 1.0048753 ,
       0.9917234 , 1.0110122 , 0.98928875, 1.0323014 , 1.0056164 ,
       1.0033942 , 0.979359  , 1.0100363 , 1.0088085 , 1.0122582 ,
       0.98322505, 0.9865185 ], dtype=float32), array([-1.16784973e-02, -9.67289601e-03, -3.96592263e-03,  1.44640151e-02,
       -5.52001828e-03,  1.44174765e-03,  4.80195181e-03,  5.67544578e-03,
        2.14162022e-02, -4.62850928e-03,  1.73620451e-02,  5.95378317e-03,
        1.05101531e-02, -1.38147557e-02, -1.61223356e-02,  3.72857065e-03,
       -1.11692362e-02,  2.76209367e-03, -2.51022051e-03,  9.06138215e-03,
        3.06548830e-02,  3.01860869e-02, -1.23395352e-02, -6.61457190e-03,
       -4.29563299e-02, -5.81244566e-03,  1.29962130e-03, -2.25563068e-02,
       -1.27316872e-02, -7.82903098e-03, -8.95725936e-03,  6.18571369e-03,
        1.98676791e-02, -6.52879104e-03, -1.67811029e-02,  1.57423839e-02,
       -4.44422709e-03, -1.78442942e-03,  2.36766320e-02, -1.39918877e-02,
       -3.45086888e-03, -3.56843397e-02,  2.17700303e-02, -8.72482266e-03,
        2.23473199e-02, -3.12647969e-02, -4.02859151e-02, -2.31611617e-02,
       -5.43875294e-03, -2.22056229e-02,  2.85400916e-02,  1.05523970e-02,
       -2.48641409e-02,  2.66568903e-02,  9.15986835e-04, -1.63692199e-02,
        7.68543594e-03, -3.97527218e-03,  1.31790601e-02, -2.79696267e-02,
       -5.91632025e-03, -1.41480647e-03, -3.29891741e-02,  1.32308714e-02,
       -1.33297015e-02, -1.79422610e-02,  2.15283632e-02, -1.91362004e-03,
       -1.49954315e-02,  1.52450809e-02, -9.40778386e-03, -7.34288013e-03,
       -4.70470488e-02,  2.27934755e-02, -5.56899933e-03, -2.62034424e-02,
        4.86453995e-03,  3.57507286e-03,  8.66012275e-03, -2.04328205e-02,
        1.60376318e-02, -4.52917852e-02, -9.90616716e-03,  4.81253490e-03,
       -3.76437954e-03, -2.14631259e-02, -2.42440403e-02, -2.40987204e-02,
        4.35204320e-02, -3.91225889e-03, -1.43780392e-02, -3.42983156e-02,
        8.58066604e-03, -2.01045815e-02, -3.30829658e-02, -3.21461656e-03,
       -1.60246044e-02, -3.27211310e-04,  4.72281277e-02,  3.03487647e-02,
        1.12676537e-02,  2.12544035e-02,  4.00939696e-02, -2.92314333e-03,
       -2.05986761e-02,  4.23673959e-03,  1.29950223e-02, -1.82407163e-02,
       -4.22994746e-03,  5.48671335e-02,  1.55693199e-02,  5.82793291e-05,
        5.19267935e-03, -4.80193383e-04, -8.46697483e-03,  4.66464646e-02,
       -2.80439184e-04,  4.10577804e-02, -2.58552463e-04,  2.08974704e-02,
        2.34253122e-03,  8.45511351e-03, -3.94334085e-03, -2.67396811e-02,
        1.22945011e-02,  1.76955760e-02,  1.67966038e-02, -9.91542358e-03,
       -1.90890941e-03,  2.95334719e-02, -6.66978350e-03, -1.99287408e-03,
       -1.49228545e-02, -1.35240713e-02,  5.71539951e-03, -7.37957517e-03,
        2.58061085e-02,  1.85031677e-03,  1.37187373e-02,  2.51837168e-03,
        2.42150389e-02,  3.12109507e-04, -2.15757266e-03, -5.28963422e-03,
       -9.11436882e-03,  2.72324006e-03,  2.36984789e-02,  2.75614094e-02,
        7.93215260e-03,  3.56690697e-02,  8.41061771e-03,  9.72962845e-03,
        1.88860949e-02, -2.42953878e-02, -2.33527515e-02,  4.07764642e-03,
        1.00301318e-02,  4.30496875e-03, -1.28254173e-02,  4.15695645e-03,
       -3.70568410e-02, -3.66182392e-03,  6.92247879e-03, -1.26507850e-02,
        1.55388480e-02, -1.45019367e-02, -3.16241421e-02,  2.45286040e-02,
       -5.46607794e-03, -2.72717290e-02,  1.82675329e-04, -1.16444239e-02,
        2.01407750e-03, -2.84106587e-03, -4.75048721e-02, -5.10863168e-03,
       -7.37803755e-03, -2.55259946e-02, -1.40454136e-02,  1.89764891e-02,
       -1.92391686e-02,  1.05101836e-03, -3.60738039e-02, -2.37262249e-02,
       -2.77434476e-02, -7.42249843e-03, -1.32280355e-02,  9.40530002e-03,
        1.94287242e-03, -1.28839230e-02,  2.61957548e-03, -1.65333655e-02,
        1.53632853e-02,  1.29055534e-03, -3.14273760e-02,  9.00320429e-03,
       -4.83821593e-02,  1.01159168e-02,  1.82893928e-02,  5.69920428e-03,
       -2.87596472e-02, -2.01249011e-02, -2.50684805e-02, -1.26036694e-02,
       -2.01610825e-03, -3.35677085e-03, -2.32332386e-02,  3.32059362e-03,
       -3.22991214e-03,  1.71428658e-02, -7.00010220e-03,  6.06850395e-03,
       -1.62304044e-02,  3.08376607e-02,  2.37531271e-02,  2.64506787e-02,
        7.27615412e-03,  3.58270593e-02, -2.79965922e-02,  2.54370123e-02,
       -9.21664946e-03, -5.07639721e-03, -1.18531967e-02,  2.05322001e-02,
        1.71551928e-02,  5.18526230e-03, -1.56968385e-02, -4.48660813e-02,
       -1.90675016e-02, -1.25741167e-02, -1.49020087e-02,  2.56951004e-02,
        7.88226817e-03, -1.70530658e-02, -2.71514952e-02, -5.74503699e-03,
       -1.47402352e-02,  2.99340696e-04,  5.71770826e-04,  2.42684484e-02,
       -7.60101946e-03,  5.85417151e-02,  3.51813324e-02,  1.47901243e-02,
       -2.58432310e-02, -2.27911584e-03, -2.38892622e-02,  2.68355198e-02,
       -1.35829486e-03,  1.68152954e-02, -3.69574991e-05,  6.21775351e-03,
       -3.00680585e-02,  1.67662650e-02,  1.11295106e-02,  6.74812309e-03,
        1.08239735e-02, -1.95209384e-02, -3.93741485e-03, -2.93212035e-03,
       -9.97332507e-04,  3.48369665e-02,  9.13313776e-03,  1.20294504e-02,
        1.37382699e-02,  3.45324655e-03, -1.86747741e-02, -5.70960809e-03,
       -2.33545061e-02,  4.06349488e-02, -2.50446424e-03, -6.80156285e-03,
       -4.42301156e-03,  1.15093980e-02,  2.13663024e-03, -1.75430123e-02,
        4.01477925e-02, -1.84706356e-02, -1.39508769e-02, -4.23890278e-02,
       -6.56164531e-03, -5.63392462e-03,  5.26869064e-03,  8.16921983e-03,
       -4.96213743e-03,  2.09320360e-03,  3.93055677e-02, -3.54170538e-02,
        5.78950485e-03,  3.57263386e-02, -8.29827785e-03, -1.43647175e-02,
        2.69049890e-02,  6.37239730e-03,  2.34539714e-02, -1.83651261e-02,
        1.96862854e-02,  1.24476776e-02,  1.04839820e-02, -8.36837199e-03,
       -2.24063024e-02,  1.40591594e-03,  5.27767744e-03, -3.20420712e-02,
        5.12400642e-02,  1.45782502e-02,  1.58155733e-03, -1.17970975e-02,
       -1.41026569e-04,  1.87208299e-02,  8.50055367e-03,  3.99340736e-03,
       -1.04978969e-02, -2.44547240e-03, -3.81177128e-03, -2.26027817e-02,
       -1.51661234e-02, -1.45962993e-02,  5.95629914e-04,  9.58875287e-03,
       -1.17822941e-02, -3.78004014e-02,  2.90299356e-02,  2.91307829e-02,
        2.60509122e-02, -1.50756212e-02,  1.44731710e-02, -1.61913056e-02,
        1.22894756e-02, -1.40778664e-02,  9.51885432e-03,  6.32984797e-03,
       -2.24549379e-02, -2.52813529e-02,  1.68872345e-02, -2.61216261e-03,
       -1.90536547e-02,  1.24172615e-02, -1.69842259e-03, -4.90994280e-05,
       -1.24226781e-02,  3.50433849e-02,  6.62839692e-03,  1.92465447e-02,
       -1.84972808e-02, -1.09717259e-02,  2.46483125e-02,  8.39315075e-03,
        9.40119661e-03,  5.24455728e-03,  7.87500641e-04,  8.31956510e-03,
       -2.85170376e-02, -1.58507877e-03,  7.93163292e-03,  1.26704331e-02,
       -3.66932750e-02, -9.35698207e-03,  4.84132208e-03, -2.18599476e-02,
       -2.20427439e-02, -1.14825107e-02, -4.86941403e-03, -1.14304610e-02,
        4.00672965e-02,  4.93818894e-03,  9.99838486e-03, -1.73544418e-02,
       -1.41035039e-02,  2.58215722e-02, -3.64311934e-02, -1.36841899e-02,
       -7.22086523e-03,  2.03428939e-02,  2.67352606e-03, -1.53331058e-02,
       -4.11732160e-02, -2.05000211e-02,  6.15883898e-03, -6.33946294e-03,
        8.47131293e-03, -2.12233476e-02,  3.04722767e-02, -1.35280881e-02,
       -2.86391620e-02,  3.83336730e-02,  1.04512600e-02,  9.18646902e-03,
       -7.86055904e-03, -2.64126807e-02, -1.76276676e-02, -1.15041842e-03,
        1.42050106e-02, -1.37283176e-03,  2.32006703e-02, -4.36129002e-03,
        1.66970422e-04, -2.54010060e-03, -5.59838349e-03,  4.87789232e-03,
       -2.63892077e-02,  1.83238499e-02,  1.52982483e-02, -1.87401194e-02,
        3.38282436e-02,  2.72247158e-02,  4.51150462e-02, -1.89000312e-02,
        3.27564776e-02,  1.36584730e-03,  1.37373460e-02, -2.34376127e-03,
       -2.76866718e-03, -1.41041027e-02, -1.06998142e-02, -1.49770901e-02,
       -2.09321994e-02, -2.10297424e-02, -1.37010235e-02,  1.17402598e-02,
       -5.08443033e-03,  9.06175002e-03,  5.09264208e-02,  1.03873871e-02,
       -2.84106247e-02,  4.15219599e-03,  6.18008804e-03,  8.13964847e-03,
        5.01083136e-02,  5.19352704e-02,  2.05768179e-02, -1.14734769e-02,
        8.09340831e-03,  1.26254540e-02,  1.91271342e-02,  4.30973619e-02,
        5.78538096e-03,  5.08835074e-03, -3.13866232e-03, -3.43603566e-02,
        6.74059009e-03,  6.80824369e-03,  9.80331283e-03, -2.92332191e-02,
        4.67456318e-03,  3.68351862e-02,  4.84353816e-03,  2.84669120e-02,
       -2.73530334e-02,  4.53085545e-03,  2.06110887e-02,  2.36733677e-03,
        7.35394191e-03,  5.91683947e-03, -3.38829239e-03,  5.28534269e-03,
       -2.02061292e-02,  1.00370850e-02,  3.28417756e-02,  8.02885089e-03,
       -1.91479886e-03, -2.70256065e-02, -1.25135435e-02, -4.32626437e-03,
       -2.83879670e-03, -8.29741452e-03, -1.35905724e-02,  9.60120745e-03,
        8.27676995e-05, -6.41141320e-03, -6.49851095e-03, -5.95027348e-03,
       -1.15353067e-03, -4.05005924e-03,  2.73583289e-02,  1.56343989e-02,
       -6.70253811e-03, -1.68483779e-02,  1.15942387e-02,  4.00526263e-02,
       -1.35027030e-02,  7.67286960e-03,  2.82947831e-02,  8.37893318e-03,
        3.14058550e-02, -1.21837519e-02, -3.22959200e-02, -2.19662003e-02,
        1.57536715e-02, -7.16142124e-03, -2.38043517e-02, -6.70758495e-03,
       -1.61954220e-02,  6.66796416e-03,  3.87656991e-03, -3.72155905e-02,
        7.39186164e-03, -5.36951516e-03, -9.59620439e-03, -1.16191590e-02,
        2.72535775e-02,  1.04077039e-02, -4.33639623e-03,  8.00111331e-03,
        6.56677643e-03, -1.83402430e-02, -2.58687139e-03,  2.57651769e-02,
       -1.53221618e-02, -1.16940932e-02,  1.09184971e-02,  9.35710501e-03],
      dtype=float32), array([ 0.64945585, -0.22679049,  0.00454745, -0.7657713 ,  0.03427992,
       -0.78264594, -0.04269292,  0.6057594 , -0.22679278,  0.74872684,
        0.19799225, -0.2047268 ,  0.28967237,  0.10075285,  0.3884246 ,
       -0.5944687 ,  0.09484965, -0.28549308, -0.72461855, -0.24606913,
       -0.19312102, -0.48519984,  0.4258783 , -0.17079149,  0.19141033,
        0.06093247,  0.1531234 ,  0.650788  ,  0.18705192, -0.11876294,
       -0.13872857,  0.16670291,  0.44552645,  0.2968615 ,  0.88881725,
       -1.1118331 ,  0.17311265, -0.18089448,  0.09696565, -0.02327013,
       -0.44468656,  0.4987571 , -0.57778543,  0.84871227, -0.17582054,
       -0.10562237,  0.2881093 , -0.13376193,  0.03217195,  0.5970374 ,
       -0.1584192 ,  0.18189926,  0.1883825 , -0.08073944, -0.4399655 ,
        0.01248981, -0.8359577 ,  0.90100217,  0.13417147,  0.5597391 ,
        0.16017017,  0.2604799 , -0.9733046 , -0.2633338 , -0.4833159 ,
        0.41110042, -0.752726  ,  0.6972517 ,  0.5459613 , -0.39548823,
       -0.294962  ,  0.15165924, -0.23081172, -0.13448407, -0.08603178,
        0.08632101, -0.3739373 , -0.0514354 ,  0.36031774, -0.15527424,
        0.4357565 ,  0.15368304,  0.08020953,  0.57564616,  0.5160559 ,
       -0.8339122 ,  0.52283597,  0.45650443, -0.33928686, -0.46983963,
        0.04574946, -0.33928746,  0.17040034, -0.68034315,  0.21095258,
        0.01523037,  0.18467332,  0.02991191, -0.01972518, -0.36947945,
       -0.7208622 , -0.04023935, -0.29123205,  0.15570572,  1.0580424 ,
       -0.3531436 ,  0.29253486, -0.7330281 ,  0.01833281, -0.3008871 ,
       -0.02421508,  0.16935071, -0.32361746, -0.0988321 ,  0.12358136,
       -0.34638405, -0.33120754, -0.5941445 , -0.3455702 , -0.4776853 ,
        0.07525979, -0.16764575, -0.42990002,  0.77599716,  0.1859145 ,
        0.17598698, -0.08903211,  0.92438173, -0.37536812, -0.4807057 ,
       -0.5287282 ,  0.22310174,  0.45784283, -0.59743947, -0.13146017,
       -0.8561154 , -0.18877214,  0.20960124, -0.42657843,  0.73430324,
        0.14021018, -0.19747148, -0.11744008,  1.1764566 ,  0.1437947 ,
        0.18434097, -0.77972364, -0.5618352 , -0.2755312 , -0.57732534,
       -0.5392356 , -0.4123758 , -0.3422085 ,  0.90336806, -0.6029198 ,
        0.00906521,  0.1202577 , -0.24023643,  0.3589494 , -0.12410961,
       -0.23487124,  0.34837347, -0.09177662, -0.26721352, -0.27802822,
       -0.28489605,  0.15012027,  0.17679892,  0.49427813, -0.38689116,
        0.0574357 ,  0.48885936,  0.0316525 , -0.20453337,  0.09185822,
       -0.09228235,  0.3789502 ,  0.4312506 , -0.11076502, -0.656717  ,
       -0.46182016, -0.56578344,  0.16754211, -0.05599371, -0.65308046,
       -0.3660646 , -0.5410027 , -0.16266018,  0.22350377,  0.21845661,
        0.04482237,  0.65818363,  0.01663915, -0.10196245,  0.5518071 ,
        0.2889435 , -0.20271926, -0.9497291 ,  0.02255454, -0.28038606,
       -0.60654503,  0.45962232,  0.6787646 , -0.30193174,  0.6155169 ,
        0.19824208, -0.26818922, -0.9951477 , -0.74300194,  0.24384193,
        0.28685412, -0.43787244,  0.519617  , -0.01334737, -0.2798349 ,
        0.532835  , -0.7246875 , -0.20476529,  0.53552663, -0.22883645,
       -0.55505604,  0.11773206,  0.32729292,  0.12916793,  0.1576314 ,
        0.14155474,  0.2118075 ,  0.30399334,  0.04595311, -0.14171629,
       -0.49289232, -0.06570543, -0.18673785,  0.23913954,  0.04239882,
       -0.43944725, -0.23555595,  0.6355768 ,  0.38988438,  0.4617565 ,
        0.14164403, -0.33054364,  0.06141178,  0.44939145,  0.09896675,
        0.25041625, -0.13090396, -0.3041739 ,  0.03133118,  0.60224843,
       -0.22033271,  0.68483   , -0.44573286,  0.39727795, -0.7835424 ,
       -0.00830467, -0.76613647,  0.48349592, -0.04166165, -0.1193762 ,
       -0.674163  , -0.06551562,  0.0578653 , -0.13141836,  0.5568054 ,
        0.17330858, -0.09960049, -0.40742895,  0.32700613, -0.4811459 ,
        0.06748375,  0.32292125,  0.03930537,  0.6234286 ,  0.2904137 ,
       -0.44590157,  0.08037923,  0.208398  ,  0.42386332, -0.79596645,
       -0.36599573,  0.16904473, -0.6171189 ,  0.32878113, -0.50007164,
        0.24061444, -1.0656443 ,  0.6809722 , -0.44037193, -0.90047604,
        0.12190678,  0.02767917, -0.25950977, -0.46223703, -0.34421703,
       -0.9602546 , -0.40374753,  0.2080861 , -0.44493622, -0.26179296,
        0.2900744 , -0.01305193,  0.22488703,  0.12145307, -0.6773082 ,
       -0.17445332,  0.14665546, -0.08483817,  0.11530922, -0.0336502 ,
       -0.36048135,  0.13950625,  0.4155232 ,  0.39973813,  0.34099522,
       -0.20058973, -0.19771197,  0.75712264, -0.42653847,  0.06399583,
        0.3465058 ,  0.04236137, -0.09098392,  0.05539483, -0.6978592 ,
        0.3663893 , -0.2833132 , -0.40253752, -0.02564062, -0.08774116,
       -0.7247825 , -0.7321635 ,  0.2736446 ,  0.44109747,  0.07295303,
       -0.46835092,  0.47485965, -0.34667793,  0.19863443,  0.00951119,
        0.2946672 , -0.27999884, -0.05593408,  0.00690204, -0.24196868,
        0.5425268 ,  0.7655878 , -0.3081538 ,  0.24389559, -0.7107597 ,
        0.14992975,  0.49369076,  0.11374772,  0.08565287, -0.412055  ,
       -0.3717575 ,  0.30360565,  0.4686243 ,  0.52794874, -0.09522863,
        0.4356031 ,  0.1164678 , -0.37877846,  0.28891504, -0.37750784,
       -0.7722778 ,  0.07791986,  0.7099637 , -0.14374945, -0.17933482,
       -0.22484042,  1.0825092 , -0.27382416,  0.24100934,  0.00302868,
       -0.48067433,  0.71152574, -0.05029787, -0.15182471,  0.0159455 ,
       -0.0591251 , -0.30271783,  0.0127338 ,  0.43938497, -0.5069524 ,
       -0.37048393,  0.2574066 ,  0.46226725, -0.10188741,  0.14203905,
        0.7588433 ,  0.17241465, -0.0885965 , -0.12598327, -0.00458434,
       -0.01646258, -0.31880957, -0.03071869, -0.17582233, -0.3384671 ,
        0.3406929 ,  0.16747445, -0.29580423, -0.1433953 , -0.40877134,
       -0.33718282, -0.48980975, -0.03222016, -0.26267526, -0.26927   ,
       -1.109146  ,  0.01074589,  0.46500626,  0.51664376,  0.08173214,
       -0.17118713, -0.0411384 , -0.31069878,  0.36469734,  0.04306698,
        0.02233841, -0.18482172, -0.31921   , -0.73679805,  0.35079676,
       -0.50848585, -0.20391883, -0.27280188, -0.22792369, -0.04209101,
       -0.3217415 ,  0.15148002,  0.38183537,  0.4274827 ,  0.10967602,
        0.17736657, -0.2633743 ,  0.84971195,  0.03167365,  0.10739458,
       -0.42087647,  0.5721706 , -0.16824034,  0.02405482,  0.3466872 ,
        0.4166991 , -0.5847048 , -0.22675654, -0.05567083, -0.0412192 ,
        0.06890415, -0.48162872, -0.06396791,  0.09602168,  0.4389771 ,
       -0.06622662,  0.08132794, -0.5313405 , -0.39004683, -0.20020306,
        0.4404328 ,  0.4244148 ,  0.29336023, -0.7670795 ,  0.19682135,
        0.22448961,  0.06545702, -0.41591987,  0.41410926, -0.16685255,
       -0.2267355 ,  0.32118976,  0.8521005 , -0.14660642, -0.544683  ,
       -0.05495918, -0.15624823,  0.2151081 , -0.8670349 , -0.5205739 ,
        0.47077262,  0.05976633, -0.00710671,  0.07431284, -0.16063948,
        0.8527552 ,  0.33838853,  1.0515414 , -0.08670532,  0.3705991 ,
       -0.05414758,  0.14665592, -0.11726627,  0.25175416, -0.47648123,
       -0.06196085,  0.20994332, -0.3780055 , -0.21712741,  0.1371713 ,
        0.41817075,  0.00453581, -0.08743002, -0.40734872,  0.21375766,
       -0.12849247, -0.26326564, -0.30477375, -0.50448495,  0.75673264,
        0.39021927,  0.20562035], dtype=float32), array([0.50364506, 0.37650087, 0.307822  , 0.40265617, 0.3323698 ,
       0.73864377, 0.3240486 , 0.4319571 , 0.2903193 , 0.47782552,
       0.32428095, 0.24464059, 0.36767432, 0.35279626, 0.65771645,
       0.2650524 , 0.47237664, 0.36116713, 0.78100723, 0.41609403,
       0.30129957, 0.40142205, 0.3877057 , 0.38626564, 0.3393764 ,
       0.48736402, 0.26851636, 0.3892094 , 0.3351146 , 0.39733168,
       0.45558324, 0.3434549 , 0.4499811 , 0.39849517, 0.54971355,
       0.79552096, 0.41976234, 0.42640314, 0.34677455, 0.3427251 ,
       0.33307746, 0.3534763 , 0.47443536, 0.7385766 , 0.27712804,
       0.30475888, 0.25633493, 0.37945443, 0.29674402, 0.36691236,
       0.42466354, 0.5677702 , 0.33579963, 0.50275296, 0.32197204,
       0.3572491 , 0.80433786, 0.380022  , 0.44815412, 0.7687995 ,
       0.3104871 , 0.30737582, 0.32142967, 0.3217698 , 0.32877046,
       0.47007242, 0.3511524 , 0.42555147, 0.42284128, 0.44758624,
       0.29683322, 0.33792096, 0.49047196, 0.44211167, 0.29174334,
       0.31293306, 0.50293523, 0.43341118, 0.3812    , 0.295165  ,
       0.56603444, 0.40840626, 0.29942584, 0.27176937, 0.31545714,
       0.7874832 , 0.5325741 , 0.6642964 , 0.4502014 , 0.36530966,
       0.3094128 , 0.4490203 , 0.31110838, 0.3662772 , 0.35432062,
       0.34147072, 0.35482675, 0.25799283, 0.28921735, 0.2811776 ,
       0.60858196, 0.50655717, 0.404704  , 0.4422064 , 0.54452944,
       0.45424664, 0.35897136, 0.42032534, 0.3753836 , 0.33634052,
       0.49393335, 0.4867228 , 0.47067913, 0.6024794 , 0.39318514,
       0.6225427 , 0.4077982 , 0.4035936 , 0.38417125, 0.38363823,
       0.3895159 , 0.35571966, 0.5208339 , 0.5177098 , 0.30691028,
       0.29716462, 0.3793855 , 0.47350362, 0.39623508, 0.3758229 ,
       0.42344588, 0.45008996, 0.47392243, 0.5093252 , 0.4892599 ,
       0.29795513, 0.4152702 , 0.3323289 , 0.37357533, 0.4243632 ,
       0.49267444, 0.5718991 , 0.42734057, 0.9082692 , 0.36239576,
       0.34635517, 0.42946324, 0.6926242 , 0.3961113 , 0.60765797,
       0.46465555, 0.51561594, 0.42173046, 0.51325285, 0.29728258,
       0.3134955 , 0.42563242, 0.5494792 , 0.47446606, 0.34385946,
       0.42529613, 0.2834424 , 0.3648189 , 0.31802166, 0.40561554,
       0.55598575, 0.7355788 , 0.41088346, 0.3001415 , 0.4556464 ,
       0.28513685, 0.44019967, 0.3548632 , 0.359311  , 0.32962546,
       0.3389355 , 0.39699855, 0.30482662, 0.3705579 , 0.38793477,
       0.4510235 , 0.31128496, 0.37699795, 0.6288353 , 0.5127699 ,
       0.31181523, 0.6518893 , 0.4974191 , 0.46493402, 0.35493523,
       0.40057358, 0.6094222 , 0.49488324, 0.4545838 , 0.43490472,
       0.49731544, 0.3396197 , 0.477959  , 0.29235685, 0.37388328,
       0.47985175, 0.5233027 , 0.7214551 , 0.59285605, 0.5770239 ,
       0.46894124, 0.36938128, 0.6329172 , 0.40845358, 0.34220967,
       0.49171034, 0.5934405 , 0.9053473 , 0.3394858 , 0.3549501 ,
       0.43779907, 0.48588353, 0.35306355, 0.47623587, 0.39390802,
       0.28915903, 0.39766634, 0.36081573, 0.48334533, 0.34419304,
       0.2973047 , 0.41569784, 0.54212403, 0.47545615, 0.22256847,
       0.2659343 , 0.63953334, 0.31859583, 0.39378574, 0.30686224,
       0.26127827, 0.39463165, 0.33785155, 0.4328786 , 0.34505433,
       0.48211017, 0.4101503 , 0.51842886, 0.42822024, 0.6376411 ,
       0.39472067, 0.44486353, 0.32780236, 0.35025802, 0.30941895,
       0.5181092 , 0.4208197 , 0.44014838, 0.40336785, 0.55141246,
       0.48619267, 0.5870503 , 0.35355526, 0.56793064, 0.4145705 ,
       0.41999635, 0.48190305, 0.27882227, 0.46749732, 0.5519648 ,
       0.43224567, 0.6944646 , 0.5530007 , 0.4836665 , 0.36917627,
       0.33839446, 0.4825728 , 0.34704328, 0.40349498, 0.39257392,
       0.3584131 , 0.3494291 , 0.34326813, 0.47672865, 0.3408084 ,
       0.2826197 , 0.43772256, 0.3419283 , 0.30166656, 0.42923504,
       0.4198032 , 0.85623485, 0.8412716 , 0.42914164, 0.49283612,
       0.33397394, 0.31035328, 0.45692897, 0.2884197 , 0.49078664,
       0.73546356, 0.476848  , 0.3638729 , 0.28113088, 0.44394818,
       0.4227559 , 0.2471829 , 0.44115832, 0.38347006, 0.5116372 ,
       0.44544488, 0.37575325, 0.5696697 , 0.44958326, 0.29810223,
       0.6448313 , 0.31448644, 0.5426347 , 0.4485743 , 0.2793496 ,
       0.33945534, 0.33881953, 0.39211488, 0.34160444, 0.38328987,
       0.35198504, 0.614578  , 0.2836455 , 0.44770634, 0.52202135,
       0.23906173, 0.5536212 , 0.38846475, 0.61884487, 0.31894183,
       0.78575546, 0.51087606, 0.4271157 , 0.64438784, 0.28155503,
       0.6091501 , 0.53563035, 0.59753835, 0.36443555, 0.49780637,
       0.47550687, 0.48031822, 0.3875683 , 0.39575008, 0.52395797,
       0.31409043, 0.38630444, 0.43928868, 0.38832292, 0.43192202,
       0.30091685, 0.3147661 , 0.46766043, 0.49801165, 0.7377645 ,
       0.35821575, 0.41741544, 0.58597434, 0.35093677, 0.48865968,
       0.5707479 , 0.44042778, 0.3832863 , 0.43748745, 0.73094213,
       0.32723466, 0.31791404, 0.3812872 , 0.41509995, 0.29939094,
       0.37094542, 0.37574974, 0.41790855, 0.27271497, 0.36170295,
       0.25298753, 0.4918882 , 0.4487693 , 0.36479348, 0.43410972,
       0.4113008 , 0.30859557, 0.30839115, 0.52195954, 0.47600347,
       0.4347233 , 0.33433187, 0.26352513, 0.38731548, 0.42574057,
       0.507153  , 0.29777837, 0.28429118, 0.3496908 , 0.44960338,
       0.3353211 , 0.37909973, 0.3108953 , 0.46017674, 0.44698337,
       0.4607796 , 0.43427035, 0.29461503, 0.40525755, 0.42892355,
       0.42920148, 0.57312584, 0.47201777, 0.47062358, 0.33705816,
       0.82208806, 0.27931598, 0.44434726, 0.3278478 , 0.46467334,
       0.560497  , 0.41013464, 0.41937798, 0.3967082 , 0.5296057 ,
       0.31281233, 0.3203524 , 0.6417203 , 0.562101  , 0.38240284,
       0.26456437, 0.46812996, 0.30228916, 0.3145663 , 0.31350112,
       0.47437698, 0.3251095 , 0.32837144, 0.35462236, 0.4407732 ,
       0.22844939, 0.39470187, 1.1662875 , 0.37868327, 0.46757513,
       0.38922518, 0.42417493, 0.33646464, 0.33597282, 0.36114186,
       0.32614094, 0.37179676, 0.28976277, 0.40000325, 0.39447132,
       0.40730998, 0.49617732, 0.25348786, 0.50717133, 0.3956219 ,
       0.3214983 , 0.27647206, 0.57783   , 0.49752712, 0.29351887,
       0.4024205 , 0.26289076, 0.4249819 , 0.5028428 , 0.3752395 ,
       0.35411343, 0.35746783, 0.30286315, 0.3705235 , 0.36359793,
       0.69537807, 0.5163459 , 0.45795593, 0.42440128, 0.5242097 ,
       0.3093108 , 0.32569438, 0.34679344, 0.65575874, 0.72488385,
       0.4986339 , 0.30511573, 0.32600415, 0.46220687, 0.56548065,
       0.73172855, 0.47655165, 0.4117131 , 0.3447032 , 0.5382115 ,
       0.4087656 , 0.35931346, 0.30358708, 0.40902898, 0.5847833 ,
       0.3364367 , 0.32006726, 0.5768285 , 0.35079926, 0.31954947,
       0.4685217 , 0.35702753, 0.2918512 , 0.6839807 , 0.28868133,
       0.4415615 , 0.26392278, 0.36168224, 0.4315138 , 0.512283  ,
       0.3327838 , 0.41072413], dtype=float32), array([[[[ 0.00460817],
         [ 0.04738725],
         [ 0.02154442],
         ...,
         [ 0.0448969 ],
         [-0.05734485],
         [-0.02983045]],

        [[-0.00622252],
         [ 0.01573956],
         [-0.01354907],
         ...,
         [ 0.06053247],
         [-0.03432796],
         [-0.01286952]],

        [[-0.00483466],
         [-0.03349074],
         [ 0.01599517],
         ...,
         [ 0.04041845],
         [-0.00056722],
         [-0.03133551]]],


       [[[ 0.03694985],
         [ 0.01476422],
         [ 0.01341465],
         ...,
         [ 0.02466706],
         [-0.04210359],
         [ 0.0362174 ]],

        [[ 0.06120275],
         [-0.00804468],
         [ 0.00334467],
         ...,
         [-0.00438537],
         [ 0.01764718],
         [ 0.01630393]],

        [[ 0.00362417],
         [ 0.0032499 ],
         [-0.01050496],
         ...,
         [-0.01179396],
         [-0.00666313],
         [-0.01681366]]],


       [[[-0.00725736],
         [ 0.03308388],
         [ 0.02857294],
         ...,
         [-0.00517572],
         [-0.00783536],
         [-0.02322384]],

        [[-0.00018983],
         [-0.00499514],
         [ 0.04437005],
         ...,
         [-0.01909127],
         [-0.01786658],
         [-0.00040274]],

        [[ 0.00266958],
         [ 0.00685368],
         [ 0.00597298],
         ...,
         [-0.00809819],
         [ 0.0084976 ],
         [ 0.03270354]]]], dtype=float32), array([0.9843595 , 0.99920416, 0.9886597 , 1.0112088 , 0.99311036,
       0.9904218 , 0.9754187 , 0.990548  , 1.0184166 , 0.9929801 ,
       1.0089349 , 1.0238909 , 0.9977738 , 0.9633427 , 1.0241094 ,
       1.0167668 , 0.97731453, 1.0516663 , 0.979671  , 1.0308328 ,
       1.0064288 , 1.0289376 , 0.9865475 , 0.9970548 , 1.0325304 ,
       0.9576025 , 1.0206008 , 1.0058777 , 1.0083733 , 0.9798051 ,
       1.0023589 , 1.03401   , 1.0081313 , 0.99456143, 0.9988514 ,
       0.9755541 , 0.9823867 , 1.0070876 , 0.9881399 , 0.98190224,
       0.9820966 , 0.98150295, 0.99493545, 1.0050887 , 1.0330582 ,
       1.0276306 , 0.96825796, 0.9999354 , 0.9828221 , 0.9895914 ,
       0.99158275, 0.9908751 , 0.9640309 , 1.0202372 , 0.98085296,
       1.0032665 , 0.97604084, 0.99147075, 1.0025567 , 1.035209  ,
       0.9889982 , 0.96703637, 1.0012728 , 1.0100518 , 1.0019739 ,
       1.0035411 , 1.0070697 , 0.986389  , 0.9854245 , 0.9859673 ,
       0.9963447 , 1.0018053 , 0.9861019 , 1.0056273 , 1.0099258 ,
       0.9820715 , 1.0117066 , 0.9861257 , 0.9947029 , 0.9818961 ,
       1.0088359 , 0.96389353, 0.99194044, 0.99127775, 0.99087274,
       1.0055401 , 0.9846597 , 0.9967009 , 1.0146042 , 0.9950292 ,
       1.0089967 , 1.0411085 , 0.99457055, 1.0376686 , 0.97098446,
       0.99924946, 1.0156571 , 0.9695081 , 0.9998082 , 1.0147425 ,
       0.9864913 , 0.98267615, 1.0173326 , 0.98914564, 1.0071965 ,
       1.0096432 , 0.9852719 , 0.98625803, 0.97723633, 1.0213362 ,
       0.98692954, 1.0076623 , 0.95620203, 1.0128275 , 0.986719  ,
       1.0154973 , 1.0019035 , 1.0197039 , 1.0132054 , 1.0012901 ,
       0.9817792 , 0.98671883, 1.0488884 , 0.99035746, 0.986371  ,
       1.0546303 , 1.0373119 , 0.98334265, 0.99607325, 0.99198496,
       0.9857428 , 0.9907539 , 0.9967529 , 0.98926085, 1.0049586 ,
       1.0225725 , 0.99808913, 1.0084456 , 0.9938217 , 1.0310305 ,
       1.0353374 , 1.0091972 , 0.98454005, 0.95352596, 0.9916377 ,
       0.9931191 , 1.01139   , 1.0255318 , 1.0182606 , 1.0113517 ,
       0.98114586, 0.98939955, 0.9938289 , 1.0042493 , 1.0088603 ,
       1.0255356 , 0.9717958 , 1.0022359 , 0.9936765 , 0.9864119 ,
       0.96532106, 0.9796691 , 0.98099345, 1.0026883 , 1.0139447 ,
       1.0083115 , 1.0088394 , 0.988133  , 0.9704295 , 1.0102022 ,
       1.0268272 , 0.9948914 , 1.0035976 , 0.9847392 , 0.98564005,
       0.986923  , 0.9779107 , 0.98912615, 0.9751217 , 0.99843377,
       0.9681776 , 1.0009785 , 0.9766085 , 0.9928426 , 0.97572803,
       1.009703  , 1.0292095 , 1.0446962 , 1.0121905 , 1.0092725 ,
       1.0087209 , 0.98977274, 0.9959853 , 0.96167874, 0.9565036 ,
       1.0109288 , 0.9781041 , 1.018887  , 1.025475  , 0.9716966 ,
       0.9810358 , 0.98620665, 0.96799237, 0.98669106, 1.0176073 ,
       0.985387  , 0.99408567, 1.0037714 , 1.0009927 , 0.98978776,
       0.986044  , 1.0072697 , 0.96420527, 1.0060518 , 0.9948527 ,
       1.0070233 , 1.0149996 , 1.0024053 , 0.9996665 , 1.0272923 ,
       0.98193073, 0.97879815, 1.0262604 , 0.9871836 , 1.0166285 ,
       1.0085123 , 0.96040004, 0.97545785, 0.9963726 , 0.9832444 ,
       0.9710116 , 1.0009727 , 0.97823894, 0.98615307, 0.98212796,
       0.98672473, 0.9874611 , 1.0186312 , 0.9824775 , 1.0100917 ,
       0.98064786, 1.0150346 , 1.0130227 , 0.9905992 , 0.9955774 ,
       0.97555876, 0.9890503 , 0.9984779 , 1.0326829 , 1.000453  ,
       1.0306016 , 1.0001593 , 1.0062312 , 0.98332065, 1.0088285 ,
       1.0137457 , 0.993315  , 0.9779459 , 1.0076071 , 1.0290097 ,
       0.97371215, 0.99914634, 1.0039191 , 0.9927252 , 1.015556  ,
       1.056008  , 1.0148445 , 1.0056559 , 1.0135032 , 1.0268049 ,
       1.0325419 , 1.0215385 , 1.0266513 , 0.99677086, 0.97697234,
       1.0028905 , 1.0069493 , 0.98923665, 0.9919513 , 0.9885654 ,
       0.98107827, 0.99465233, 1.030517  , 1.0232124 , 0.9761397 ,
       0.99493647, 1.0420954 , 0.99181515, 1.0550761 , 1.0039746 ,
       1.0018059 , 0.9936015 , 0.99124646, 1.0101763 , 1.0028086 ,
       0.959297  , 0.9938786 , 0.98448384, 0.9986547 , 0.9766071 ,
       1.0154483 , 0.97550434, 0.96678793, 0.963053  , 1.0011629 ,
       1.0096053 , 0.9927816 , 0.98905396, 0.9979381 , 1.035358  ,
       0.97062165, 0.9995055 , 0.9918741 , 0.9958432 , 0.98794466,
       0.96960086, 1.0157553 , 1.0063498 , 0.9824762 , 0.9936601 ,
       1.0092807 , 0.9884733 , 0.99549633, 0.9989693 , 0.99407125,
       0.9783694 , 1.0040414 , 1.0339245 , 1.0152472 , 1.0549939 ,
       1.0230731 , 1.0243009 , 1.0230777 , 0.9704974 , 0.98568255,
       0.9888905 , 1.0327251 , 1.0408455 , 0.98148656, 0.9837111 ,
       0.9974073 , 1.0167156 , 0.9986032 , 0.9885361 , 1.0220631 ,
       0.98504686, 0.9920359 , 1.0091906 , 1.0216146 , 1.002306  ,
       1.0014575 , 1.0275267 , 1.0235804 , 1.046516  , 1.0234383 ,
       0.99516684, 1.0144567 , 1.0017058 , 1.0460312 , 0.9817593 ,
       0.9936906 , 0.99864614, 0.9923066 , 0.99789554, 0.99278915,
       1.0205798 , 0.9892406 , 0.9828849 , 0.9925147 , 1.0083323 ,
       0.9723198 , 1.002464  , 1.0022489 , 0.98394585, 0.9753122 ,
       1.0024567 , 0.97101754, 1.0425888 , 0.9966064 , 1.0105512 ,
       1.0125409 , 1.0118402 , 1.0360348 , 0.97827744, 0.9829162 ,
       1.0649519 , 1.0186764 , 1.0284394 , 1.0265113 , 0.97639406,
       0.99748474, 1.0062395 , 0.9929061 , 0.97355664, 1.0289075 ,
       1.010428  , 1.0093781 , 1.0058402 , 1.0192415 , 1.0275898 ,
       0.9917956 , 0.98002774, 0.9922256 , 0.99693376, 1.0044339 ,
       1.015278  , 1.0372138 , 0.9966336 , 1.0353743 , 0.9926594 ,
       0.9783361 , 0.9522582 , 1.0007824 , 0.9518926 , 1.0327978 ,
       1.0170364 , 0.99807215, 0.9717963 , 1.0107572 , 1.0102936 ,
       0.99524605, 0.99938154, 1.0227504 , 0.96457267, 1.0171577 ,
       0.9985562 , 1.0011114 , 0.9946206 , 1.051029  , 0.9891862 ,
       0.9901211 , 0.9763432 , 0.98331755, 0.9886435 , 1.0245557 ,
       1.0035812 , 0.9891429 , 1.0052091 , 1.0082554 , 1.0019734 ,
       1.008278  , 1.0096675 , 0.9961413 , 1.0063695 , 0.9919482 ,
       1.0138654 , 0.9855895 , 1.0110457 , 0.9461289 , 1.0188872 ,
       1.0078919 , 0.9857508 , 1.0090569 , 0.99937475, 1.0540725 ,
       1.0018405 , 1.0038612 , 1.0084996 , 1.0139613 , 1.0087397 ,
       0.9851773 , 1.0324509 , 0.99953496, 1.0207961 , 0.9427748 ,
       1.0242318 , 1.0056194 , 0.99348533, 1.040809  , 1.0007545 ,
       1.0396769 , 0.9883529 , 1.0063874 , 0.9685795 , 0.983784  ,
       1.0337523 , 1.0142962 , 1.0012416 , 1.0196242 , 1.0108247 ,
       0.99612856, 1.0356208 , 1.0193641 , 1.0112945 , 0.97486454,
       1.0229583 , 0.9793324 , 0.9840876 , 1.0032953 , 0.9995065 ,
       1.0009459 , 0.9975985 , 1.0206597 , 1.0127321 , 0.987936  ,
       0.9760248 , 1.0099365 , 0.9730657 , 1.037988  , 1.0014085 ,
       0.9894882 , 1.0128196 , 0.9892973 , 1.0372727 , 1.0029973 ,
       1.003279  , 0.9790905 , 1.0115572 , 1.0082763 , 1.0151886 ,
       0.9845204 , 0.985469  ], dtype=float32), array([-2.71502547e-02,  1.10315243e-02, -1.86802298e-02,  5.26031060e-03,
       -7.09493225e-03, -1.65157169e-02, -2.74256081e-03,  1.26245050e-02,
       -7.59209692e-03, -1.35100419e-02, -1.20091438e-03,  1.18958028e-02,
       -1.65131167e-02, -4.11338285e-02,  5.74090984e-03,  2.76925378e-02,
       -9.59495734e-03,  4.55695353e-02, -1.40147703e-02,  2.31942721e-02,
        2.22433312e-03,  2.22107559e-03, -9.09759942e-03,  7.29291141e-03,
        2.76666358e-02, -3.42787020e-02,  6.10622577e-03, -6.23204932e-03,
        8.83673877e-03,  3.72323673e-03, -1.03183661e-03,  1.46643622e-02,
       -5.17763942e-03,  1.12079550e-02, -2.64247265e-02, -9.40380711e-03,
       -1.47054400e-02,  2.10643373e-02,  5.62389055e-03, -1.79900993e-02,
        1.08632706e-02, -9.66702995e-04,  8.78382660e-03, -2.20417231e-02,
        9.53130983e-03, -1.87590700e-02,  9.30051785e-03,  7.33261555e-03,
       -2.82955952e-02, -6.92075724e-03, -2.42109019e-02,  5.30207530e-03,
       -2.46717390e-02,  6.39814232e-03,  1.29885618e-02,  1.29828583e-02,
       -3.12446654e-02,  1.55323651e-03, -1.61393303e-02, -3.96228163e-03,
       -7.43500097e-03,  3.65184015e-03, -3.18751335e-02,  2.22798437e-02,
        4.83927969e-03,  1.58117879e-02,  2.40782299e-03, -1.46455010e-02,
       -2.88388897e-02,  2.77961860e-03, -1.12553043e-02,  5.90174226e-03,
        4.09839908e-04,  3.27096391e-03, -1.16047813e-02, -3.58629273e-03,
        1.53807560e-02, -1.52878240e-02,  8.89161043e-03,  1.22818118e-02,
       -7.39137642e-03, -2.81312689e-02, -1.71192139e-02, -2.80387010e-02,
       -1.47111472e-02, -1.51611054e-02, -2.04701303e-03, -2.11133976e-02,
        8.85319151e-03,  1.44605199e-03,  9.03979596e-03,  1.10683180e-02,
       -1.60143580e-02,  6.32589730e-03, -3.59141715e-02,  5.41859912e-03,
        2.69652717e-03, -1.05051585e-02, -3.69366468e-03,  1.50688421e-02,
       -2.19092742e-02,  1.97989531e-02,  4.13797535e-02, -1.67759508e-03,
       -8.22424795e-03,  2.22864505e-02,  1.19351607e-05, -1.62478890e-02,
       -7.31541403e-03,  2.21011415e-02, -2.91358177e-02, -4.87586297e-03,
       -4.75459211e-02, -9.11993440e-03, -4.07757834e-02,  2.00548805e-02,
       -5.06862393e-03,  2.31410228e-02,  1.67076010e-02,  1.07588526e-02,
       -1.49009214e-03, -1.43686226e-02,  3.39595973e-02,  5.40268747e-03,
       -1.24684265e-02,  1.26810670e-02,  3.39201503e-02,  7.78396556e-04,
        1.11192446e-02, -1.14917324e-03, -2.33313050e-02, -4.96346829e-03,
       -3.22901905e-02, -1.98810734e-02,  2.46431082e-02,  2.61848536e-03,
        7.81504624e-03, -1.84340612e-03,  2.40663327e-02, -2.85541988e-03,
        1.77901462e-02,  1.36272023e-02, -1.22907171e-02, -6.52865171e-02,
       -4.87205572e-03, -9.33020469e-03,  1.64133906e-02,  7.55467778e-03,
        9.48359724e-03,  8.02598707e-03, -2.08565686e-02, -1.96630731e-02,
       -6.45942707e-03, -3.95580754e-02,  1.10938754e-02,  1.48335295e-02,
       -7.36773526e-03,  1.23585900e-02,  2.07570642e-02, -8.58120737e-04,
       -1.45077391e-03, -1.13088144e-02, -7.04580080e-03, -2.83562858e-02,
        5.41145122e-03, -1.17857549e-02,  2.31313985e-02, -5.28030144e-03,
       -3.65672223e-02,  1.02878222e-02,  2.55897399e-02, -6.93257898e-03,
       -9.34995420e-04,  1.12336073e-02,  1.13018192e-02,  9.82347596e-03,
       -2.45931279e-02, -2.86416467e-02, -2.84341108e-02,  1.00179659e-02,
       -2.92655788e-02,  1.13649350e-02, -3.23058441e-02, -1.00195454e-02,
        1.14269191e-02, -4.11451096e-03,  2.07338519e-02,  1.36109823e-02,
        1.24872942e-02, -1.68989860e-02, -6.60239160e-03, -3.09931021e-02,
        4.45405766e-03, -7.21263047e-03, -2.33362261e-02,  2.63320319e-02,
       -3.92439961e-03,  1.05900904e-02,  6.90490566e-03, -2.28595268e-02,
       -2.42191032e-02, -1.98949054e-02, -3.66067924e-02, -1.32495938e-02,
        8.23124126e-03, -2.01164298e-02, -1.66275650e-02,  1.28062554e-02,
       -1.73823293e-02, -9.81223886e-04, -5.06033748e-03,  2.34501064e-03,
       -6.69405097e-03,  1.04060546e-02, -1.07010761e-02,  1.41967763e-03,
        1.71714947e-02, -9.98820271e-03,  5.77139086e-04, -1.22098885e-02,
        4.79149120e-03, -9.39902291e-03,  2.66442653e-02, -2.42185332e-02,
       -1.69975439e-03,  1.55827003e-02, -2.48676278e-02, -5.44470921e-02,
        1.10278721e-03, -2.78155804e-02, -2.99954638e-02, -1.11499177e-02,
       -2.73999777e-02, -2.06444468e-02, -4.58394410e-03, -2.50258949e-02,
       -8.77941027e-03,  1.07407356e-02, -1.08758537e-02,  1.27297901e-02,
       -1.31637286e-02,  3.38421613e-02,  1.60962772e-02, -9.54467524e-03,
       -1.89993754e-02,  5.12920506e-03, -2.10226569e-02, -2.46067857e-03,
        2.75505893e-03,  2.47294568e-02,  2.17016097e-02,  1.45156812e-02,
       -9.30773001e-03, -3.50741460e-03,  1.51968431e-02,  9.85947903e-03,
        8.29720777e-03, -8.17323383e-03, -1.89215168e-02,  6.01142198e-02,
       -2.31778827e-02,  1.24039897e-03,  2.10562274e-02,  2.00658925e-02,
        2.48850901e-02,  1.14756534e-02,  2.27123802e-03,  1.32617848e-02,
        9.80883837e-03,  2.18171664e-02,  4.82024858e-03,  2.39130389e-02,
        2.28228681e-02,  1.45441750e-02, -1.72314402e-02,  9.21354722e-03,
        1.29599106e-02,  6.87637320e-03, -1.48643916e-02, -9.26052220e-03,
       -8.89483187e-03,  6.34873658e-03,  4.22225185e-02, -4.45090188e-03,
       -8.93986225e-03,  7.86559843e-03,  5.20672537e-02,  1.58353206e-02,
        4.95617986e-02,  2.45164079e-03,  2.05030479e-02, -4.24743252e-04,
        1.79505907e-03,  2.68045273e-02,  1.15871858e-02, -3.04135308e-02,
       -7.93397147e-03, -3.02887429e-03,  3.39255668e-02, -1.90972611e-02,
        1.20593030e-02, -3.29328282e-03, -2.52964124e-02, -9.38557927e-03,
        3.49216093e-03,  1.13021852e-02,  8.88451654e-03,  1.65868644e-02,
       -4.41891549e-04,  4.47350740e-02,  1.01777725e-02,  1.40543990e-02,
        1.70227955e-03, -9.20147728e-03, -1.78946892e-03, -4.51797061e-02,
       -2.17719789e-04, -7.53514981e-03, -4.19226624e-02, -4.40127067e-02,
        1.10967439e-02,  7.58979120e-04,  3.08405608e-02,  2.17775907e-03,
        5.74431289e-03, -2.20272131e-02,  1.51675483e-02, -1.02679851e-02,
       -2.72815523e-04,  4.03352864e-02,  4.36726287e-02,  3.87369618e-02,
       -7.42685609e-03,  1.02573377e-03, -1.73405353e-02, -1.11459219e-03,
        2.21327599e-02,  4.13572490e-02,  6.37682294e-03, -2.36002053e-03,
        1.02426866e-02,  2.47496683e-02, -1.49804084e-02,  2.68323137e-03,
       -1.45867737e-02, -6.99542277e-03, -1.03214383e-02,  7.70388823e-03,
        4.21748087e-02,  1.50153348e-02, -2.34650634e-03,  1.79658849e-02,
       -5.44641307e-03,  3.90573703e-02,  1.94480103e-02,  5.26811881e-03,
       -1.02983695e-02, -5.39596844e-03,  3.29315290e-02, -1.60814263e-02,
       -9.84017272e-03, -8.64783302e-04, -2.40936074e-02, -2.15039756e-02,
       -2.56111063e-02,  5.98723534e-03, -1.33864721e-02, -1.19580049e-02,
       -2.92265993e-02,  9.62567516e-03,  3.49184335e-03, -3.67424637e-02,
       -1.49203222e-02, -1.75179094e-02, -1.58978403e-02, -1.50662344e-02,
       -4.00596671e-02,  1.67873297e-02,  2.18221862e-02, -6.22021360e-03,
        2.46836133e-02,  2.62205489e-02,  2.61120796e-02, -1.67207455e-03,
       -2.88874917e-02,  5.16707376e-02,  3.97293344e-02,  1.96147058e-02,
        7.92515744e-03, -2.87438557e-02,  4.51490143e-03, -1.42997857e-02,
        1.68938318e-03, -2.21568532e-02, -1.00092534e-02, -1.86076970e-03,
        7.46117113e-03, -1.30364997e-03,  8.30375124e-03,  4.34354357e-02,
        7.44756835e-04, -1.05843414e-02,  1.92555059e-02, -7.53720582e-04,
        1.89826090e-03, -1.04411161e-02,  1.45306196e-02, -1.07696345e-02,
        3.91384549e-02,  9.50850197e-04, -1.02306074e-02, -3.91549021e-02,
        1.09382262e-02, -5.28658144e-02,  1.45438174e-02,  1.64198666e-03,
        8.91017495e-04, -3.88193130e-02, -4.43716794e-02, -2.02652737e-02,
       -2.25910754e-03,  9.39402636e-03,  2.55752392e-02, -3.12329270e-03,
        3.73271815e-02,  3.09483632e-02, -6.75740093e-03, -5.30896615e-03,
        3.24811004e-02, -6.31657802e-03, -2.77155475e-03,  1.64703317e-02,
        2.63138744e-03, -7.13622896e-03,  1.27031114e-02,  1.85481161e-02,
        9.05064400e-03,  1.15143051e-02,  2.28997674e-02,  7.83906691e-03,
        2.10710224e-02,  1.96357463e-02,  1.53734088e-02,  3.49055938e-02,
        1.19548868e-02,  2.44418811e-02, -1.14947250e-02,  2.43383478e-02,
       -4.99310009e-02,  3.03291567e-02,  3.90283763e-03, -1.54354293e-02,
        1.05389347e-03, -3.97425983e-03,  2.37017199e-02,  1.08583765e-02,
        1.44174171e-03, -2.21795449e-03,  3.04746162e-02, -1.15524894e-02,
        1.80761435e-03,  2.56615914e-02,  1.99029390e-02,  2.12725047e-02,
       -2.94541679e-02,  7.19719827e-02, -2.76649967e-02,  9.05508548e-03,
       -3.66507494e-03, -4.89733415e-03,  2.08107173e-03, -3.37852836e-02,
        8.03864375e-03, -2.14467701e-02,  8.82584509e-03,  1.84573568e-02,
        1.48950117e-02, -6.78926520e-03,  1.82391033e-02,  3.73067521e-02,
       -2.06935015e-02,  1.71141885e-02,  2.13838387e-02, -1.43624339e-02,
       -3.88170965e-02,  4.55737347e-03, -7.56061589e-03, -4.22100350e-02,
        1.67393275e-02,  8.54662713e-03,  9.23092826e-04,  1.27574801e-02,
        1.12656849e-02,  6.38763281e-03, -3.54933063e-03, -2.85146330e-02,
        1.22390891e-04, -2.05307305e-02,  3.08716875e-02, -1.16860075e-02,
       -2.14797426e-02,  1.34071363e-02, -3.44252326e-02,  3.45567688e-02,
        1.41948776e-03,  3.55241611e-03, -5.88752562e-03, -1.11252535e-02,
       -1.07473824e-02, -1.94017440e-02,  1.12961337e-03, -1.22635001e-02],
      dtype=float32), array([ 3.01798582e-02,  1.07561303e-02,  3.43907624e-02, -7.85129797e-03,
        2.15822039e-03, -3.98810580e-03, -9.66012012e-03,  2.64089406e-02,
       -5.14705479e-02, -2.57551968e-02, -1.30788377e-02, -3.76093760e-02,
       -6.44378422e-04, -3.91228218e-03,  5.21805137e-02,  4.17895608e-05,
       -2.24464908e-02,  2.20263340e-02,  4.11585486e-03,  5.49529232e-02,
       -5.59767559e-02, -5.14111221e-02,  8.52451567e-03,  1.46824690e-02,
        3.11446525e-02,  4.67026755e-02,  7.15868268e-03,  3.23267207e-02,
       -4.24513705e-02,  1.91262036e-04,  2.06510071e-02, -2.57079154e-02,
        1.08596254e-02, -4.95080426e-02,  4.29812260e-02, -4.13327031e-02,
        2.28043310e-02,  1.74547471e-02, -2.51613315e-02, -1.36339283e-02,
        1.38166603e-02, -2.31816489e-02, -2.81165745e-02,  4.09886912e-02,
       -7.73650408e-03,  4.23011333e-02,  6.62485557e-03, -4.69826087e-02,
        1.56991128e-02,  3.03904228e-02, -4.16058935e-02, -4.32720333e-02,
        2.50697527e-02, -2.81084869e-02,  4.15468775e-02, -7.37568643e-03,
       -3.88528965e-02,  3.20011601e-02,  3.04419138e-02,  4.61461470e-02,
        5.62252440e-02,  4.96515911e-03,  3.46771777e-02,  8.19282234e-03,
        3.14216055e-02, -4.25077118e-02,  6.10414799e-03,  3.01988404e-02,
        3.92252766e-02, -2.45122518e-02,  3.51022445e-02, -1.87026418e-03,
        1.99966766e-02, -4.05482315e-02,  1.90131050e-02, -1.24527980e-02,
       -1.12306233e-02,  3.89146176e-03, -4.90029380e-02, -4.09420319e-02,
        3.21041271e-02, -4.37631160e-02,  1.38833327e-02, -2.86644474e-02,
       -1.55788111e-02, -1.75937861e-02, -3.15169916e-02,  4.56445813e-02,
       -6.35541826e-02, -5.31894937e-02, -6.73386594e-03,  2.35011373e-02,
        3.94634530e-03,  2.76000774e-03,  3.72610837e-02, -3.28013599e-02,
        1.27652995e-02, -4.26126132e-03, -6.41865283e-02,  4.27558972e-03,
       -3.11987232e-02,  4.77711819e-02,  2.93927006e-02, -1.38061959e-02,
        2.22040936e-02,  3.52064297e-02, -2.88401917e-02,  1.09719234e-02,
       -1.75117627e-02, -4.80685644e-02, -4.40691672e-02,  4.10461128e-02,
        2.00129021e-02,  2.58964542e-02, -2.25947648e-02,  5.95467128e-02,
        3.74573246e-02, -3.92238684e-02,  4.33390252e-02,  1.57497227e-02,
        2.76809037e-02, -5.15491404e-02,  5.18761985e-02, -4.74192724e-02,
       -3.75280902e-02,  2.62256153e-02,  5.79921529e-02, -4.79376428e-02,
        1.29304975e-02, -2.82092933e-02, -3.20886150e-02,  1.63190980e-02,
        4.69216257e-02,  3.49123701e-02, -2.06474103e-02, -6.17711665e-03,
       -3.30003798e-02, -2.31244732e-02,  6.80970168e-03,  3.24278139e-02,
       -1.37953041e-02,  4.61054444e-02,  1.90149620e-02, -6.04377165e-02,
        1.05657196e-02, -9.23059136e-03, -1.10379944e-03, -1.09864762e-02,
       -5.79330027e-02,  3.69427092e-02,  3.95372463e-03, -1.10335776e-03,
        1.50886620e-03,  3.98082510e-02,  1.00582431e-03, -1.68640763e-02,
        3.18788551e-03,  3.81308049e-03, -4.18813154e-02, -1.70461424e-02,
       -2.53268592e-02,  1.71425268e-02, -4.18246835e-02, -1.95330707e-03,
        1.55073032e-02,  2.32137367e-02, -5.33177294e-02,  4.57659289e-02,
       -4.40928377e-02,  2.00697426e-02, -3.61779481e-02,  4.35674302e-02,
        5.36077935e-03, -5.10141775e-02, -2.07609367e-02, -2.70759780e-02,
       -3.53428014e-02,  3.82113568e-02, -6.24015694e-03,  6.70117214e-02,
        2.14696564e-02,  1.22529734e-02, -1.56585723e-02,  2.97880732e-02,
        1.06419493e-02,  9.97931510e-03,  3.36195645e-03,  2.42834575e-02,
        1.85581192e-03,  1.99209787e-02,  3.05913407e-02,  3.58171500e-02,
        3.87249365e-02, -1.44366249e-02, -3.60967917e-03,  8.42154212e-03,
        1.61141083e-02,  2.76146550e-02,  1.27714844e-02,  2.24342756e-02,
        1.47263715e-02, -8.55216105e-03,  2.53482070e-02,  4.60997671e-02,
        3.33445966e-02,  4.92243282e-02,  3.47143970e-02,  3.74788232e-02,
        2.48533674e-02, -2.21692752e-02,  2.55333353e-02,  5.92230894e-02,
        4.57077809e-02, -5.18211126e-02, -9.88157280e-03, -5.15053757e-02,
        6.80809915e-02, -2.12191176e-02, -4.84396629e-02,  5.58281178e-03,
        1.14134373e-02, -5.99531010e-02,  3.07923555e-02,  7.58220488e-03,
       -3.24043259e-02,  2.36505419e-02,  2.93223970e-02,  2.07705982e-02,
       -3.08272354e-02,  5.54630347e-03,  2.83918176e-02, -4.36633127e-04,
        2.88879815e-02, -1.63067169e-02,  2.44061276e-02, -8.63279775e-03,
       -6.31588418e-03, -7.35380203e-02,  2.71636760e-03, -9.61699244e-03,
        1.55195547e-02,  3.24208066e-02,  3.02138347e-02, -3.86462733e-02,
        3.96725833e-02,  3.93194780e-02, -3.16142626e-02, -6.48805574e-02,
        3.35524380e-02, -2.30096513e-03,  6.49889484e-02, -5.59472777e-02,
       -2.16624583e-03, -3.28596756e-02,  3.37996408e-02,  3.66655216e-02,
       -1.36440080e-02, -2.97188461e-02,  2.55324654e-02,  1.73421204e-02,
       -1.92628335e-02, -7.54848570e-02, -4.09403816e-02,  3.88524085e-02,
       -7.03020543e-02,  8.38420726e-03,  3.79608050e-02,  3.56050767e-02,
        2.00746153e-02, -1.67107638e-02,  3.57451513e-02,  1.81360077e-02,
        4.59619947e-02, -1.91691834e-02, -3.57920863e-02, -1.63330454e-02,
        5.73761878e-04, -4.36037667e-02, -4.98306118e-02,  2.97074504e-02,
       -2.08351761e-02, -1.80136375e-02,  3.18593569e-02,  1.30610662e-02,
       -3.60401385e-02, -1.15979230e-02,  6.42179921e-02, -3.36649232e-02,
       -1.86716579e-02,  2.34265756e-02, -1.90033522e-02,  8.96932278e-03,
        5.10718934e-02, -2.18339078e-02, -3.90038267e-02,  2.80147307e-02,
        5.46015203e-02,  3.08810174e-02,  6.04788214e-02, -2.86391638e-02,
        3.37190814e-02, -2.10999437e-02, -2.66197268e-02, -2.11517848e-02,
       -1.03891827e-02,  1.79377217e-02,  3.43466476e-02, -4.95880097e-03,
        3.58733651e-03, -3.48634906e-02,  2.83672940e-02,  1.34961409e-02,
       -5.76113760e-02,  1.10742617e-02,  8.56802426e-03,  2.34086113e-03,
        3.45522389e-02, -2.01161229e-03, -3.01089287e-02, -1.52035952e-02,
       -3.13550085e-02, -3.35726812e-02, -4.32463037e-03, -4.04773876e-02,
       -4.93647195e-02, -7.39077851e-03, -2.30819099e-02,  1.01279300e-02,
       -1.71564948e-02,  6.48935698e-03,  3.76531780e-02,  1.41195031e-02,
        2.70463713e-02, -2.78580077e-02, -6.25966722e-03, -3.58718671e-02,
        4.06907611e-02,  2.10921727e-02,  2.26745009e-02,  5.44314459e-02,
       -2.19738148e-02, -3.54968011e-02,  2.26186160e-02, -3.47910635e-02,
        3.07838582e-02, -2.14974843e-02,  2.97274496e-02,  2.58989632e-03,
       -3.71895283e-02,  6.29118979e-02,  2.03576479e-02, -4.41755839e-02,
        2.32836530e-02,  4.28760424e-02,  5.44825308e-02, -1.96707267e-02,
        3.41372937e-03, -1.75398327e-02,  1.26654990e-02,  1.92009043e-02,
        2.32661907e-02, -3.53688374e-02, -7.74422148e-03,  4.21997607e-02,
       -3.74925584e-02, -5.61062992e-02,  4.21659509e-03,  2.63846498e-02,
       -9.00671293e-04,  1.00880433e-02, -3.77192758e-02,  2.05021743e-02,
       -2.69016419e-02, -2.94476189e-02, -4.09719832e-02,  7.62617402e-03,
        3.89521904e-02,  4.03674468e-02,  6.14663810e-02,  2.78530922e-02,
        3.33370664e-03, -2.54447628e-02, -1.16689913e-02,  9.04490799e-03,
        8.79582949e-03,  6.14125049e-03, -3.66634056e-02, -3.37957330e-02,
        1.96013525e-02,  1.67504437e-02, -6.56065717e-02,  3.14939655e-02,
        1.90889873e-02,  1.35282157e-02,  4.23106626e-02,  2.30793897e-02,
        5.01032919e-02, -1.95494276e-02,  1.22156730e-02,  1.02580003e-02,
        1.80786625e-02,  2.45013479e-02, -3.84593122e-02, -2.09459420e-02,
       -1.95763875e-02, -6.39354764e-03,  6.51570223e-03, -3.23683210e-02,
        2.04798169e-02, -5.26999356e-03,  3.65129560e-02, -1.95583655e-03,
        3.09458934e-02, -3.67985889e-02,  4.13934439e-02,  5.31140305e-02,
        1.35717522e-02,  2.22753803e-03,  2.28665327e-03,  3.25764753e-02,
       -2.29278877e-02,  3.82317565e-02,  4.78387251e-02,  4.44352888e-02,
       -6.75627142e-02,  3.20111332e-03,  4.45156246e-02,  6.79213600e-03,
       -4.06083874e-02, -4.22366783e-02,  1.49307074e-02, -3.83347534e-02,
       -4.55382429e-02,  3.64420675e-02, -2.63222810e-02, -2.47902535e-02,
       -1.66032519e-02, -5.42933904e-02, -1.74956881e-02, -3.21739316e-02,
        1.53927375e-02, -5.77581227e-02,  1.55855287e-02, -9.40797757e-03,
       -1.21097942e-03,  1.18227527e-02, -3.18463072e-02, -1.16196582e-02,
        8.90504941e-03, -3.65225896e-02,  1.69646759e-02, -3.19304876e-02,
       -2.81621981e-02, -6.01643100e-02,  2.76500937e-02,  9.93081089e-03,
       -1.27355894e-02, -6.70645311e-02, -3.35347839e-02,  1.87906902e-02,
        2.11174544e-02, -5.86128468e-03, -5.20830089e-03,  1.15163866e-02,
       -2.32754927e-02, -2.63333786e-02, -6.06694538e-03, -8.75650067e-03,
        3.96161862e-02,  2.46271901e-02,  4.09428887e-02,  2.80280281e-02,
       -7.78431967e-02,  6.00500219e-03, -3.46233994e-02,  5.52927554e-02,
        4.22822457e-04,  8.53224099e-03, -1.07102245e-02,  5.77761382e-02,
        1.52882859e-02, -1.31657999e-02, -1.38163492e-02,  4.11369614e-02,
       -1.59027670e-02,  4.06203158e-02,  1.49310408e-02,  3.55576798e-02,
       -5.52271551e-04, -4.66387384e-02, -3.89854703e-03, -2.98530813e-02,
        5.09447744e-03, -5.96727803e-02,  8.44012760e-03,  1.17008323e-02,
       -1.34656148e-03, -5.21139130e-02, -5.70362434e-02,  2.11843867e-02,
       -3.76930088e-02, -1.71586871e-02,  5.43959613e-04,  4.31347676e-02,
       -1.35716330e-02,  3.62147056e-02, -2.49481853e-02,  1.78683475e-02,
        1.18446741e-02,  4.37577814e-02, -5.03933579e-02, -3.46959023e-05],
      dtype=float32), array([0.01051086, 0.00792865, 0.00859011, 0.00827377, 0.00786935,
       0.00717553, 0.00759887, 0.00836982, 0.01049904, 0.00965629,
       0.00807195, 0.00966165, 0.00874394, 0.00753471, 0.01449133,
       0.00866445, 0.00915866, 0.00863559, 0.00691552, 0.01025498,
       0.01264321, 0.00985857, 0.00784869, 0.00788052, 0.0093567 ,
       0.01098062, 0.00817538, 0.00925351, 0.010741  , 0.00732654,
       0.00917939, 0.00880076, 0.00762157, 0.01255238, 0.01228254,
       0.00811465, 0.00839239, 0.00829645, 0.00759587, 0.00917843,
       0.00766428, 0.00911929, 0.00826   , 0.01444077, 0.00888162,
       0.01026037, 0.00728534, 0.0102819 , 0.00752017, 0.00838576,
       0.00915172, 0.01032963, 0.00850112, 0.00891881, 0.00877563,
       0.01009525, 0.0082559 , 0.00953861, 0.0118113 , 0.01590892,
       0.01242258, 0.00793345, 0.00875357, 0.0079012 , 0.00879444,
       0.01140693, 0.00768801, 0.00952772, 0.01162888, 0.00828871,
       0.00868459, 0.00776892, 0.00748331, 0.01022261, 0.00840733,
       0.00822989, 0.00759173, 0.00743837, 0.01082318, 0.00909065,
       0.01129402, 0.01056417, 0.00842036, 0.00867729, 0.0078289 ,
       0.0074405 , 0.00910799, 0.01507747, 0.00948592, 0.01154616,
       0.0087446 , 0.00868814, 0.00834404, 0.00823018, 0.01017131,
       0.01053565, 0.00798555, 0.00829042, 0.01222656, 0.00850019,
       0.00794895, 0.01025914, 0.00942616, 0.0081475 , 0.0094858 ,
       0.00849127, 0.00897109, 0.0077676 , 0.0080668 , 0.01153182,
       0.00817185, 0.0119336 , 0.00751197, 0.00779685, 0.00856468,
       0.01093792, 0.00837159, 0.00857814, 0.01031179, 0.0089471 ,
       0.00840964, 0.01115402, 0.01042782, 0.01204266, 0.00911847,
       0.00885972, 0.01121244, 0.01233805, 0.00794371, 0.00877211,
       0.00836448, 0.00831588, 0.01280271, 0.008369  , 0.00771239,
       0.00860531, 0.0092411 , 0.00905261, 0.00766204, 0.00991803,
       0.0081442 , 0.01009608, 0.00771144, 0.01913947, 0.00842522,
       0.00794392, 0.00803332, 0.00759415, 0.01038707, 0.00862907,
       0.00745594, 0.00711073, 0.00798827, 0.01104798, 0.00785621,
       0.00973235, 0.0114241 , 0.00881455, 0.01067443, 0.00810252,
       0.00764465, 0.00826972, 0.01053145, 0.00777826, 0.0078251 ,
       0.01245515, 0.01674212, 0.01224888, 0.0100627 , 0.00810862,
       0.00929529, 0.01074123, 0.00809664, 0.010986  , 0.00842708,
       0.00836652, 0.01020049, 0.00922353, 0.00804301, 0.01273004,
       0.0078345 , 0.00811751, 0.00782637, 0.0116153 , 0.00742409,
       0.00843721, 0.00779384, 0.00976538, 0.00798343, 0.00813612,
       0.01169797, 0.01173325, 0.00860013, 0.00748037, 0.00733768,
       0.01492862, 0.00770008, 0.00834997, 0.0083283 , 0.00882249,
       0.00728944, 0.00752805, 0.00973894, 0.00927292, 0.01075026,
       0.01238927, 0.00889955, 0.00873218, 0.00805648, 0.00781265,
       0.00963037, 0.01186978, 0.01483268, 0.00963146, 0.00810987,
       0.01380732, 0.01475269, 0.00783167, 0.01154929, 0.00799712,
       0.00876707, 0.01445675, 0.00954458, 0.00772929, 0.01087026,
       0.00950775, 0.00829121, 0.01259752, 0.00844342, 0.00823524,
       0.00874672, 0.00729328, 0.00927496, 0.00814789, 0.00850287,
       0.00719054, 0.00799064, 0.0152671 , 0.00913938, 0.00797695,
       0.00972815, 0.0084378 , 0.00930147, 0.01173496, 0.01127458,
       0.00989054, 0.00809991, 0.01250976, 0.00999023, 0.00782654,
       0.01059215, 0.01214067, 0.00821799, 0.00919076, 0.00821374,
       0.00863923, 0.00774362, 0.00912015, 0.01016779, 0.00839269,
       0.01011534, 0.0105303 , 0.00942164, 0.01026233, 0.02331544,
       0.00819394, 0.01342257, 0.00888633, 0.00904388, 0.00830272,
       0.01093043, 0.00913167, 0.01030664, 0.00902272, 0.01025075,
       0.00747945, 0.00844516, 0.01015323, 0.01262899, 0.00797338,
       0.00878783, 0.01028389, 0.00959854, 0.00820439, 0.00894651,
       0.00734459, 0.01062518, 0.01144772, 0.00796029, 0.0080569 ,
       0.0087649 , 0.00802865, 0.01069133, 0.00894908, 0.01028133,
       0.00739909, 0.01106988, 0.00944017, 0.01211351, 0.01069749,
       0.00955288, 0.00791101, 0.00877323, 0.00841946, 0.0077136 ,
       0.0086432 , 0.00969112, 0.00761106, 0.00792834, 0.00975258,
       0.00785369, 0.00796459, 0.01511159, 0.01165988, 0.00831495,
       0.00803733, 0.01060955, 0.00811406, 0.00883749, 0.00856453,
       0.00911813, 0.01106161, 0.00846046, 0.00879833, 0.00899903,
       0.00824634, 0.00794993, 0.00806701, 0.0076395 , 0.00940779,
       0.00883707, 0.00771104, 0.00842435, 0.01028404, 0.00859972,
       0.00821017, 0.01081103, 0.00930307, 0.00770949, 0.01188215,
       0.00931427, 0.00837244, 0.00776356, 0.00815779, 0.01076234,
       0.00897138, 0.00963526, 0.00833858, 0.01029059, 0.0119532 ,
       0.00863216, 0.00937592, 0.01037768, 0.00912423, 0.01007485,
       0.00804317, 0.0081086 , 0.01015951, 0.00805294, 0.00757954,
       0.01058295, 0.01064384, 0.00743926, 0.01242474, 0.00818496,
       0.00996956, 0.0083508 , 0.00854652, 0.00752806, 0.00825944,
       0.01042993, 0.00852501, 0.00904079, 0.00912188, 0.00934105,
       0.00849633, 0.01257968, 0.00926914, 0.01262576, 0.00898861,
       0.00789687, 0.00885206, 0.00858686, 0.00823125, 0.01019873,
       0.00889482, 0.00923991, 0.01013099, 0.00787301, 0.00926492,
       0.01765101, 0.00922209, 0.00802368, 0.0082862 , 0.01172726,
       0.00830183, 0.00999084, 0.00804884, 0.00855951, 0.00803418,
       0.00833283, 0.0090193 , 0.0092008 , 0.00930175, 0.00836551,
       0.00789003, 0.00799849, 0.00856597, 0.0084541 , 0.00774252,
       0.00790234, 0.00837494, 0.00966931, 0.01045672, 0.00993755,
       0.00959885, 0.00781252, 0.00771658, 0.0078288 , 0.01143383,
       0.00904296, 0.00945503, 0.00985787, 0.00839004, 0.0147881 ,
       0.00810894, 0.01136427, 0.00780755, 0.00945621, 0.00921547,
       0.00769409, 0.01047187, 0.00916648, 0.00962834, 0.00943896,
       0.00888684, 0.00824633, 0.01677344, 0.00854337, 0.01113719,
       0.00791542, 0.0141415 , 0.00864141, 0.00825816, 0.00755627,
       0.00796108, 0.00812895, 0.00811884, 0.00738085, 0.0108233 ,
       0.0091784 , 0.00798267, 0.00909983, 0.01042191, 0.01061282,
       0.00863627, 0.00845096, 0.01143904, 0.00861753, 0.00925789,
       0.00983423, 0.00896029, 0.00952015, 0.00893858, 0.00913117,
       0.00915296, 0.00784501, 0.00857353, 0.01040077, 0.00931595,
       0.00911099, 0.01125402, 0.02062078, 0.00761865, 0.00930895,
       0.01052791, 0.00878814, 0.00797373, 0.00749597, 0.00980039,
       0.00826998, 0.00888743, 0.00856072, 0.01184525, 0.00743517,
       0.01400271, 0.00799923, 0.01056064, 0.00834325, 0.01269673,
       0.00833356, 0.00864669, 0.00888444, 0.01431401, 0.00733812,
       0.00815252, 0.00910044, 0.00865727, 0.01045361, 0.00784022,
       0.00928264, 0.00871725, 0.00738681, 0.01007003, 0.00832089,
       0.01500522, 0.00827914, 0.00947051, 0.00803813, 0.0149838 ,
       0.01174905, 0.00851483], dtype=float32), array([[[[-0.04303433, -0.00891516, -0.00857285, ..., -0.00880229,
           0.05378536, -0.04182024],
         [-0.05760291, -0.02637785,  0.04846361, ...,  0.07989526,
          -0.00709552, -0.0392017 ],
         [ 0.03732767, -0.02322683, -0.03824552, ...,  0.013149  ,
           0.03848189,  0.02037756],
         ...,
         [ 0.04308758,  0.03331973,  0.0440894 , ...,  0.0652732 ,
          -0.01105372, -0.08883595],
         [ 0.05549465, -0.08303066, -0.06162279, ...,  0.02919448,
           0.03980184,  0.00223326],
         [ 0.02077441,  0.00211856, -0.03696276, ..., -0.00246135,
          -0.07393694,  0.05266704]]]], dtype=float32), array([1.0063734 , 1.0096018 , 0.98527503, 0.970991  , 1.0358499 ,
       1.0058553 , 1.0173185 , 1.032243  , 1.001202  , 1.0171387 ,
       0.9881222 , 1.0002373 , 0.9912512 , 0.98505163, 1.012793  ,
       1.0237175 , 0.97373915, 0.98223394, 1.0192779 , 1.0117815 ,
       1.0000122 , 0.9918086 , 0.98390263, 1.02789   , 0.9911783 ,
       0.9785912 , 1.0094614 , 1.0066535 , 1.0095626 , 1.0156121 ,
       1.0240141 , 0.980412  , 0.9914609 , 1.0040977 , 1.0103799 ,
       0.9964205 , 0.9908291 , 1.0030454 , 1.0129956 , 1.0415351 ,
       0.998807  , 1.0285199 , 1.0252204 , 0.98990464, 0.9833476 ,
       0.9943226 , 0.99277246, 1.0084554 , 1.0025392 , 0.9866341 ,
       1.0133237 , 1.0110167 , 0.9991818 , 0.96752894, 1.0000699 ,
       0.9840354 , 1.0067916 , 1.0111518 , 1.0011867 , 0.9979706 ,
       0.98932946, 0.97965324, 0.9919387 , 1.0089722 , 0.9789069 ,
       0.9839025 , 0.99680877, 1.0086396 , 0.97078073, 1.0045797 ,
       0.98349684, 1.0139024 , 0.96604866, 1.000656  , 1.0262284 ,
       1.0176008 , 1.0044457 , 0.9836738 , 0.9985606 , 0.9931902 ,
       0.9979658 , 1.0160011 , 0.9718441 , 1.0066332 , 0.9908941 ,
       1.0030936 , 1.029225  , 0.9732566 , 0.99934816, 1.0336167 ,
       0.99835056, 0.99009323, 1.0289682 , 0.96500766, 1.0215695 ,
       0.9874714 , 0.95515233, 1.0008637 , 0.9981625 , 0.9914977 ,
       1.016417  , 1.006783  , 1.0004988 , 1.0137568 , 1.0346591 ,
       1.026778  , 1.0009092 , 0.9927203 , 1.0011785 , 1.000782  ,
       1.0134995 , 0.99652714, 1.0011878 , 0.99540484, 0.9980647 ,
       0.98317605, 1.0027654 , 0.9961984 , 1.0025395 , 1.0172174 ,
       0.96248055, 0.9982575 , 1.0345197 , 0.98225313, 1.0062138 ,
       0.9891604 , 0.98019534, 0.99671984, 1.0056995 , 0.97648245,
       1.0163155 , 1.0252779 , 1.005193  , 1.01578   , 1.0335872 ,
       1.0218369 , 0.98424435, 1.0258938 , 0.9734366 , 1.0093919 ,
       1.0185333 , 0.97298324, 1.0209733 , 1.0088488 , 0.99645096,
       0.99032223, 1.0010878 , 1.0113004 , 1.0284781 , 0.9883324 ,
       0.9619609 , 1.0008159 , 0.96928346, 1.0033427 , 0.9780436 ,
       1.0270911 , 0.9797592 , 0.98160297, 0.9872661 , 1.0361792 ,
       0.9942373 , 0.99303085, 0.99838346, 1.0065967 , 0.98021233,
       0.9900544 , 1.0098959 , 0.9974265 , 0.97447246, 0.98480636,
       1.0056043 , 0.982739  , 0.9876558 , 1.0091496 , 0.97040635,
       1.042903  , 0.9980673 , 1.0366143 , 1.0053891 , 0.98495966,
       1.0052106 , 0.99003905, 0.99351853, 1.0138367 , 1.0103849 ,
       0.99198204, 0.9887434 , 0.97769636, 1.0123613 , 0.99137646,
       1.0244203 , 0.9916718 , 0.9828604 , 0.99608964, 1.0061648 ,
       0.9877437 , 1.0269434 , 0.9838916 , 0.9915625 , 0.9827469 ,
       0.97529256, 1.0191147 , 0.9945003 , 1.0082548 , 1.0412838 ,
       1.0156437 , 0.9915315 , 0.98375547, 0.9860523 , 0.99821657,
       0.99436027, 0.9967526 , 1.010289  , 1.0140483 , 1.0106167 ,
       1.0061933 , 1.0078889 , 0.9939382 , 1.0263076 , 0.9983909 ,
       1.0205988 , 0.9982589 , 0.9836034 , 1.0079838 , 1.0133597 ,
       0.9899207 , 0.9863589 , 0.9959531 , 0.9939248 , 0.96656716,
       0.9907449 , 0.9972986 , 0.9703755 , 1.0075454 , 1.0029691 ,
       0.9936279 , 0.99727875, 0.9781102 , 0.99786407, 1.0343311 ,
       0.99234295, 0.9985005 , 1.0038289 , 1.0005547 , 1.0058215 ,
       0.9836108 , 0.99335665, 0.99887866, 1.0066283 , 1.0154644 ,
       1.0316767 , 1.0151287 , 1.0222236 , 0.97604305, 0.99913543,
       0.99267626, 0.9782948 , 1.0159998 , 1.0051626 , 0.9924603 ,
       0.98006964, 1.0101035 , 0.984562  , 0.9738675 , 0.94835305,
       0.9894723 , 1.010341  , 1.001195  , 1.0232713 , 0.969359  ,
       1.0187528 , 0.99928176, 1.0064216 , 1.0102109 , 0.99210227,
       1.002997  , 1.0310327 , 0.99936014, 0.974368  , 1.0042467 ,
       0.9743991 , 0.9938537 , 1.0054286 , 1.0228539 , 1.0097357 ,
       0.98626757, 1.0380925 , 0.99621254, 0.99975294, 1.0100529 ,
       0.99126136, 1.0240083 , 1.0024623 , 0.98995984, 1.0094199 ,
       1.0290669 , 1.0044242 , 1.0371593 , 1.004314  , 1.005688  ,
       0.9672921 , 1.0166767 , 0.98430806, 0.99474525, 1.0173433 ,
       0.9913845 , 1.0111915 , 1.0030712 , 1.0147458 , 0.9995628 ,
       0.99404037, 0.9941391 , 0.99583256, 0.9935136 , 1.0069852 ,
       0.99247783, 0.998013  , 1.0087646 , 1.0003723 , 0.9841245 ,
       1.0092634 , 0.99151975, 0.9770949 , 1.0651474 , 1.0293909 ,
       0.98930264, 0.9949634 , 0.9919913 , 0.9904944 , 1.003299  ,
       1.0126787 , 1.0261871 , 1.0018501 , 1.0091443 , 1.0079443 ,
       1.0092071 , 0.97722644, 0.9989701 , 0.9970635 , 0.98962456,
       0.99810785, 0.9903525 , 0.9825152 , 0.99977505, 1.0411221 ,
       1.0063672 , 1.0177876 , 1.0041252 , 0.9869055 , 1.0155696 ,
       0.99564224, 1.0105493 , 1.0086246 , 0.99584335, 0.9920767 ,
       1.0049839 , 1.0114833 , 1.0197802 , 0.9738863 , 1.0076    ,
       1.0029981 , 0.9936536 , 1.0058322 , 0.9898512 , 0.99728966,
       0.9995142 , 0.9840751 , 1.0091205 , 1.007926  , 1.0018361 ,
       1.0357141 , 1.0108252 , 1.0046    , 0.99421453, 1.0281596 ,
       0.9883065 , 1.0292785 , 1.009926  , 1.0003378 , 0.99420655,
       0.9920595 , 0.9833767 , 0.9770174 , 1.0434556 , 1.018967  ,
       0.99426186, 0.9916974 , 0.9975014 , 1.0339855 , 0.9993294 ,
       1.0093638 , 1.0051905 , 0.9977548 , 1.0101833 , 1.0219069 ,
       0.98362887, 1.026841  , 1.0211998 , 0.99993855, 1.019479  ,
       1.0095233 , 0.99210477, 0.99708474, 1.0097877 , 0.99718535,
       1.0116014 , 1.0050205 , 1.0048392 , 1.0170838 , 1.0207149 ,
       1.0009216 , 0.9817575 , 0.97480077, 0.978497  , 0.988714  ,
       0.9793222 , 0.99452555, 1.006293  , 0.9950383 , 0.9822841 ,
       1.0112164 , 0.9965782 , 0.98946816, 0.98259515, 0.973032  ,
       1.0361915 , 0.9997373 , 0.98682076, 0.95413697, 0.9996922 ,
       1.01689   , 0.9778787 , 0.993438  , 1.0086808 , 0.99105865,
       1.0068715 , 0.9981726 , 0.991874  , 1.0211515 , 0.9870822 ,
       1.014328  , 0.99742526, 1.0237343 , 1.0036111 , 1.0306411 ,
       1.0253309 , 0.9764346 , 1.0162019 , 1.002816  , 1.0178684 ,
       1.0123103 , 0.9952856 , 0.9829154 , 0.9979582 , 1.0182309 ,
       1.0223768 , 1.0201957 , 1.0308988 , 1.0292962 , 0.9985047 ,
       1.0027789 , 0.9914428 , 0.9888733 , 1.0157582 , 0.9931608 ,
       1.0027031 , 1.0033293 , 0.9831541 , 1.005308  , 1.0093509 ,
       1.011835  , 0.98098385, 1.0047902 , 1.0061896 , 1.0000428 ,
       0.9780335 , 0.99386215, 1.0092305 , 1.002424  , 1.0099751 ,
       1.0069147 , 0.9969671 , 0.97420156, 1.0272869 , 1.0130711 ,
       0.99967194, 1.0061069 , 1.0114166 , 1.0000676 , 1.020689  ,
       1.0235016 , 0.9752145 , 1.0002395 , 1.006126  , 0.9962764 ,
       0.99205995, 1.0004885 , 1.0161207 , 1.0108799 , 0.9959567 ,
       0.98550814, 1.0215993 , 0.9924745 , 0.9892214 , 0.98505896,
       0.9909106 , 0.992848  , 1.0215135 , 1.0022744 , 0.97149974,
       1.0144696 , 1.0111158 ], dtype=float32), array([ 1.13734826e-02,  2.03978410e-03,  7.31594278e-04, -3.23889591e-02,
        1.14318533e-02,  1.93221141e-02,  1.54435690e-02,  2.45842841e-02,
       -9.15481895e-03,  1.84771381e-02,  2.42991373e-03,  1.46277016e-02,
       -9.55063850e-03, -1.46254357e-02,  1.61161274e-03,  5.21993777e-03,
        1.72646530e-02, -3.98707204e-02, -7.55782239e-03,  2.86177117e-02,
        1.51035665e-02,  1.24898518e-03, -3.44724432e-02, -9.47752618e-04,
       -1.40928160e-02, -1.02144284e-02, -7.48167513e-03,  3.11318394e-02,
       -6.35416759e-03, -9.33621265e-03, -1.23614203e-02,  1.02181761e-02,
        2.47944035e-02,  7.40361912e-03, -5.57920709e-03, -1.64599046e-02,
        2.47972086e-02,  9.80765931e-03, -9.35904402e-03,  3.19303162e-02,
       -1.81277487e-02,  2.92189624e-02,  1.88362729e-02,  1.93710476e-02,
       -5.57571789e-03,  1.66633241e-02, -2.43729446e-03,  3.58204804e-02,
        3.69056710e-04,  1.10062221e-02,  2.58011930e-02, -8.79008695e-03,
       -1.00591438e-04,  2.34298389e-02,  7.40527920e-03,  2.00097561e-02,
        1.17021454e-02, -3.45883984e-03,  3.53303701e-02, -8.83487985e-03,
       -1.17750838e-02, -1.28034176e-02, -1.65429637e-02,  1.62798818e-02,
        3.25451866e-02, -2.62980852e-02,  2.95909066e-02, -1.06129271e-03,
       -3.48537555e-03, -7.41770165e-03, -1.83840506e-02, -4.16581286e-03,
       -2.09888667e-02,  4.59220074e-02,  1.26149580e-02,  8.81626830e-03,
        8.08358565e-03, -4.36416967e-03, -2.39046048e-02, -7.16093183e-03,
       -9.40452702e-03,  1.36270132e-02, -2.27887426e-02,  7.42752850e-03,
       -3.11913081e-02,  2.62722857e-02, -8.40708520e-03, -3.90340341e-03,
       -6.46576984e-03, -1.44633669e-02, -5.55054937e-03, -1.29089486e-02,
        5.37504628e-02, -2.50201183e-03, -1.22079346e-02, -4.50384198e-03,
       -1.47186248e-02, -1.32183572e-02,  1.01760263e-02,  2.58168597e-02,
        3.75942178e-02,  1.40075479e-02, -6.75388519e-03,  2.19389908e-02,
        3.50674242e-02, -2.11510416e-02,  8.04301724e-03,  3.68492417e-02,
        1.70797464e-02, -2.49835663e-03, -1.53686758e-03, -3.66547098e-03,
        2.95458697e-02, -1.98292881e-02,  3.05151660e-03,  1.22057204e-03,
       -1.94805544e-02,  1.49572268e-02, -3.86122637e-03,  1.87231717e-03,
       -2.10421272e-02,  1.81106143e-02,  3.20948698e-02, -1.82933100e-02,
       -8.21164064e-03, -1.11276517e-02, -8.78812373e-03, -9.42148268e-03,
       -1.46607158e-03, -1.71676800e-02,  1.25555713e-02,  4.10103751e-03,
       -4.45852638e-04,  1.50960525e-02,  1.60187054e-02, -1.51244095e-02,
       -2.44597495e-02, -1.05496601e-03,  8.17110471e-04,  1.83931682e-02,
       -2.68376749e-02, -9.40088741e-03, -1.36416769e-02, -6.20002626e-03,
       -1.05261439e-02, -1.35105066e-02, -2.42294464e-02, -3.43220159e-02,
        1.94688682e-02, -1.65446810e-02, -5.45319868e-03,  1.15842475e-02,
       -2.15813760e-02,  1.27894180e-02, -2.89085545e-02,  3.70720886e-02,
       -3.52444164e-02,  1.68982167e-02,  5.80345187e-03,  5.45132831e-02,
        1.23435967e-02, -2.53700782e-02,  1.28467185e-02,  6.52423408e-03,
        2.63822591e-03, -1.52442092e-02,  6.52599288e-03,  3.23150009e-02,
       -1.09077198e-02,  6.29191380e-03,  1.82052162e-02, -2.05178075e-02,
        6.25093514e-03,  1.08615486e-02, -3.94486915e-03,  2.42792480e-02,
        1.87266618e-02, -5.41784335e-03,  2.24692356e-02, -1.98776610e-02,
       -8.79548304e-03,  4.76951478e-03,  9.17925779e-03, -1.50104025e-02,
        5.45082707e-03, -1.80810150e-02, -1.28794089e-03,  6.97702495e-03,
       -1.59454793e-02,  3.36689921e-03, -1.17415767e-02, -1.01410616e-02,
        4.37762402e-02,  2.68824585e-02,  2.47991905e-02, -1.91682149e-02,
       -1.65606439e-02, -4.52662352e-03,  2.63485312e-02,  3.75978369e-03,
       -1.49275949e-02,  7.57568050e-03, -2.13667192e-02,  4.67485785e-02,
        2.04557814e-02,  7.22798146e-03, -1.90378483e-02,  5.44893648e-03,
        6.24199212e-03, -1.70421656e-02, -1.20204156e-02, -1.12789674e-02,
        1.65214166e-02, -1.43677113e-03,  1.96088422e-02, -2.20360905e-02,
       -1.65094901e-02,  5.79965534e-03, -2.45979838e-02,  2.32421327e-02,
        4.09806669e-02,  4.92305309e-02,  2.63264682e-03, -2.12523174e-02,
        6.29140157e-03, -2.10874565e-02,  6.24935236e-03,  1.22563588e-03,
       -7.52994465e-03,  2.19404977e-02, -4.30554710e-03, -3.58815957e-03,
        1.13213863e-02,  2.97911577e-02, -1.99557245e-02,  2.31785700e-02,
        6.57453155e-03, -4.83840145e-03,  9.79314744e-03, -1.86019414e-03,
        1.92432497e-02, -2.35471185e-02,  2.59769186e-02,  1.01452880e-02,
       -2.13265885e-02,  1.31831095e-02,  2.02928800e-02,  1.23125473e-02,
        1.93179101e-02, -1.58433244e-02,  1.36049394e-03,  1.71753000e-02,
        2.35623661e-02,  1.39046228e-02, -2.85370722e-02, -2.04748325e-02,
       -4.13935147e-02,  1.84619557e-02,  1.20587712e-02,  2.26234645e-02,
       -1.49820726e-02, -2.24675573e-02, -2.07249187e-02, -1.39242467e-02,
       -2.90083252e-02, -1.73173565e-02,  4.43940610e-03,  3.23816645e-03,
       -1.62871517e-02, -2.61991695e-02,  1.23335943e-02,  4.94330516e-03,
       -4.26506903e-03,  2.90556229e-03, -8.43821838e-03,  5.14024915e-03,
        4.03977111e-02, -2.51151789e-02,  3.17068887e-03,  2.75714938e-02,
       -4.25788835e-02, -1.85912419e-02, -1.03246933e-02,  1.14612794e-02,
        3.26096527e-02,  1.26222065e-02,  4.44017835e-02,  1.79934353e-02,
       -1.35696353e-03, -5.51334210e-03, -2.16354951e-02, -1.83629282e-02,
        4.84605366e-03, -1.07231806e-03, -8.69435538e-03,  9.66080464e-03,
        4.10306267e-02,  7.35097146e-03, -2.25776201e-03, -4.33128473e-04,
       -2.67438088e-02, -2.07062531e-02, -3.30753215e-02, -9.38432477e-03,
        3.33895371e-03, -8.37718882e-03, -1.21420715e-02, -8.89426284e-03,
        3.88865359e-03, -1.71332574e-03, -2.83919722e-02, -1.51439551e-02,
       -1.45054758e-02, -1.43648824e-02, -5.14450809e-03,  1.53162740e-02,
        3.23269777e-02, -1.78935975e-02,  2.70404909e-02, -2.80239079e-02,
        1.01695824e-02,  3.91427707e-03,  2.28766967e-02,  3.63587365e-02,
       -1.50014441e-02, -4.35044523e-03, -1.57168843e-02,  3.06016183e-03,
       -2.09704507e-02, -5.89666143e-03,  5.25736511e-02,  7.90463388e-03,
        2.03431351e-03, -3.09645422e-02, -2.82564433e-03,  1.48816574e-02,
       -1.33536087e-04,  4.09141518e-02, -1.75308045e-02,  3.25966105e-02,
        1.10037709e-02, -2.28703991e-02, -1.44177359e-02,  7.77360424e-03,
       -2.55332179e-02, -9.53345001e-03,  2.50933822e-02,  6.37626555e-03,
        1.76379681e-02,  1.68393422e-02, -1.88393816e-02, -1.03859734e-02,
       -4.58974279e-02, -1.86023000e-03, -6.33381587e-03,  1.84784569e-02,
       -2.23672707e-02,  2.38533262e-02, -1.44090829e-03,  2.49960795e-02,
       -2.88709383e-02, -5.62827010e-03,  3.31063494e-02, -9.02870391e-03,
        5.83285838e-03, -1.85170770e-02,  5.81308268e-03, -7.24424236e-03,
        5.64571284e-03, -1.00544067e-02,  4.96749915e-02,  1.38018075e-02,
        8.65591783e-03, -3.87663804e-02, -2.19290927e-02,  2.41548680e-02,
       -3.21091153e-02, -1.97980111e-03,  1.67390108e-02, -4.04929146e-02,
       -2.58199032e-02, -1.98785756e-02,  3.03856330e-03,  1.29094794e-02,
       -1.43997362e-02, -1.66147798e-02, -1.49477385e-02, -1.09332763e-02,
        5.00298245e-03, -4.76058982e-02,  7.20777968e-03,  2.28068326e-02,
        1.83592718e-02, -1.24188103e-02, -3.80378310e-03,  8.45478289e-03,
       -6.00321870e-03,  2.35923752e-02, -2.06084307e-02,  1.61032118e-02,
       -1.77059751e-02,  1.20387226e-02,  4.38982770e-02,  3.95589042e-03,
        3.85340583e-03,  1.86205823e-02,  5.02182404e-03,  3.46330665e-02,
        1.76404584e-02,  1.81447603e-02, -1.77847836e-02,  2.25973446e-02,
       -3.83391045e-02,  1.72059741e-02, -3.51488800e-03, -1.13637568e-02,
       -1.15907099e-02,  3.69821936e-02, -1.79318301e-02,  4.30477457e-03,
       -1.43941434e-05,  1.36127528e-02, -1.42626208e-03, -1.76102184e-02,
        2.39622295e-02,  3.56210582e-02, -3.02877259e-02, -1.55787878e-02,
       -2.44918782e-02, -1.83702167e-03,  3.54702808e-02,  2.55987956e-03,
       -3.46233062e-02,  9.71072260e-03, -7.58082652e-03, -8.63317773e-03,
        1.24090919e-02,  9.26427823e-03,  3.63500253e-03, -4.23744582e-02,
        8.62486288e-03, -1.76011026e-02,  9.33984760e-03, -2.50981003e-02,
        2.59562824e-02, -1.50026260e-02,  2.84812953e-02,  1.31018385e-02,
       -2.88160751e-04, -1.75265521e-02,  3.33661609e-03,  9.12624970e-03,
       -1.62137876e-04,  2.60408735e-03, -5.86584536e-03,  2.41358839e-02,
       -1.59124676e-02,  4.11460130e-03,  1.58843379e-02, -8.74009449e-03,
        1.84846632e-02, -3.96675766e-02,  7.69955292e-03,  2.12751189e-03,
        1.85994748e-02, -3.90180498e-02,  2.61951089e-02, -2.41405889e-03,
       -1.82068720e-02, -2.61956267e-03,  5.10886731e-03,  1.67483799e-02,
       -1.09012593e-02, -1.40345255e-02,  5.08492347e-04, -1.46333443e-03,
       -7.45267654e-03, -1.01524973e-02, -9.97988414e-03,  2.91376077e-02,
       -2.13345103e-02, -3.28706093e-02, -4.04856540e-02,  4.62833745e-03,
        3.49227376e-02, -2.08016522e-02,  8.76330421e-04,  1.25321262e-02,
       -6.90211728e-03, -1.18683446e-02, -1.18529312e-02, -1.74839534e-02,
        1.42872380e-03,  6.80710771e-04,  2.67712772e-03,  1.78402085e-02,
        1.03034843e-02, -7.31331063e-04, -1.93803222e-03, -5.88220265e-03,
        9.68950987e-03,  1.79154761e-02, -2.67173517e-02, -2.68502091e-03,
        3.34020294e-02, -2.49681692e-03, -3.16642784e-02,  4.05815765e-02,
       -8.89686588e-03, -2.56747622e-02,  1.52693819e-02,  2.90947631e-02],
      dtype=float32), array([-0.8609978 ,  0.12666433, -0.2295763 , -0.08622824, -0.16957724,
        0.39217994,  0.36342424,  0.30105308, -0.32197776,  0.3102944 ,
        0.50988054, -0.33307198, -0.67659   , -0.34162033, -0.2903768 ,
        0.39559907, -0.55292445,  0.22183359, -0.15149339, -0.5187036 ,
       -0.44371226, -0.44676098,  0.4838046 , -0.34495074,  0.14201358,
        0.5791586 , -0.18353443, -0.7710103 , -0.00187842, -0.46479627,
       -0.19689511,  0.34391767,  0.5903765 , -0.333727  ,  0.26450196,
       -0.20784213, -0.21878025, -0.07481427,  0.24126281,  0.28940946,
       -0.24168144, -0.04271912,  0.16327658, -0.41356173, -0.36375093,
        0.3199313 ,  0.40515068, -0.6844212 ,  0.08561388, -0.3031978 ,
       -0.54192233, -0.3254597 , -0.608108  , -0.20770769,  0.2555951 ,
       -0.03919832, -0.26351368, -0.3399236 , -0.49188083, -0.0650941 ,
        0.6670402 , -0.27262896, -0.0724134 , -0.2969177 , -0.05808639,
        0.26373008, -0.690856  ,  0.30542588,  0.04267423, -0.07483178,
       -0.13648377,  0.29825023,  0.05432167, -0.5680875 , -0.10268614,
        0.07081768,  0.6948987 , -0.02889758, -0.06202358, -0.40398562,
       -0.41332012, -0.78626573, -0.35278496,  0.02531072, -0.2880082 ,
        0.35050765,  0.31613132, -0.3188087 , -0.29798216,  0.3543884 ,
        0.52554274, -0.27259555,  0.27616504, -0.6109219 ,  0.33887395,
       -0.14243259, -0.5226725 ,  0.42571214, -0.11332371,  0.11185779,
       -0.20134135, -0.6016207 , -0.59555346,  0.44985557, -0.8081694 ,
        0.46207938,  0.47445714,  0.04137548,  0.54311466, -0.00646364,
       -0.2318867 ,  0.80464303,  0.2138749 ,  0.2917859 ,  0.6313444 ,
        0.27699745,  0.12083716, -0.275259  , -0.0318215 , -0.5892064 ,
       -0.28011554, -0.11060078, -0.6054443 , -0.03708755,  0.5325659 ,
       -0.34583423, -0.39852053, -0.7312008 ,  0.07180487,  0.9735053 ,
        0.67879206, -0.15540762,  0.26562986, -0.04350119,  0.7177974 ,
        0.3071063 ,  0.42864335, -0.44183174, -0.25595132, -0.59834033,
       -0.08287686, -0.11695709, -0.2171582 , -0.32678315,  0.4357436 ,
        0.32686558, -0.3020523 ,  0.5926852 , -0.05238296,  0.5075323 ,
        0.30443564,  0.2814237 ,  0.52616847,  0.19957857,  0.11819316,
       -0.17548335, -0.03916715, -0.3258263 , -0.4428935 , -0.37881973,
       -0.33692273,  0.093887  ,  0.27862686, -0.21465044,  0.10243426,
       -0.2643002 ,  0.2009381 , -0.42327923, -0.50443953, -0.30503786,
       -0.6498734 , -0.37469396,  0.10605364, -0.81842935, -0.21581   ,
       -0.50301456,  0.36708826,  0.00291211, -0.517302  ,  0.47608715,
       -0.17633064, -0.4423922 , -0.16606814,  0.22004707,  0.36684197,
        0.641375  ,  0.08756309, -0.0432131 , -0.4121766 ,  0.15752906,
       -0.23250464, -0.24417919, -0.33589745, -0.7168121 , -0.42956755,
        0.15499675,  0.05100667,  0.34378165, -0.5602106 ,  0.47475016,
        0.01350699,  0.08526385,  0.32260188,  0.52750874, -0.3054229 ,
        0.18648893,  0.32343644,  0.47561857,  0.19197376,  0.21494375,
        0.3635746 ,  0.24305518, -0.2834049 ,  0.09927276,  0.50707114,
       -0.54179037,  0.09038071, -0.96601444,  0.49080154,  0.23425217,
        0.09004887,  0.1498057 ,  0.713607  ,  0.21685904,  0.27352595,
       -0.30237395, -0.79767054,  0.101612  , -0.37437668, -0.8775612 ,
       -0.18128687, -0.05698987, -0.04898616, -1.022834  , -0.15553811,
        0.31978524,  0.5633602 , -0.17204279, -0.10176922, -0.7570146 ,
       -0.11389326,  0.02169685, -0.7868809 ,  0.32051477, -0.5116276 ,
        0.27056754, -0.4086794 , -0.5426704 ,  0.5568916 , -0.2998902 ,
       -0.7046522 , -0.36476448,  0.40625992, -0.11987811, -0.35056195,
       -0.1587542 , -0.20210229,  0.07056401,  0.05643344,  0.03300346,
        0.449142  ,  0.22812833,  0.21894301, -0.07378034,  0.37257954,
       -0.27212036, -0.53940827, -0.02451573,  0.09435461, -0.38012218,
       -0.13550103, -0.1702789 , -0.32042354,  0.14249532, -0.01996405,
       -0.41299978, -0.26725173, -0.41705817, -0.06289502, -0.8516377 ,
       -0.12419024, -0.471144  , -0.4112524 ,  0.28130212, -0.35209483,
       -0.26175588, -0.5178987 ,  0.2762328 , -0.37979537, -0.47101548,
       -0.35098842, -0.45255995, -0.5315255 ,  0.24596842, -0.23985115,
       -0.22061671, -0.6663815 ,  0.21125084,  0.14846922,  0.20961404,
       -0.21577634,  0.26905409,  0.07896399,  0.24465673, -0.8261913 ,
        0.20211788,  0.23580037, -0.3104222 , -0.32991582, -0.09128788,
       -0.6474558 ,  0.24741346,  0.8102801 , -0.34603637, -0.5030565 ,
       -0.05861391,  0.3405109 , -0.33213115, -0.06653448,  0.18698636,
        0.52201647, -0.739379  , -0.36227238,  0.15500353,  0.48585436,
       -0.14852636, -0.56223327,  0.5517866 ,  0.20818548,  0.44612354,
        0.2515213 , -0.4732861 , -0.8461102 ,  0.37862882,  0.07432565,
       -0.29279515, -0.5078436 , -0.35672614,  0.5868111 ,  0.4171287 ,
       -0.6119324 , -0.2760284 ,  0.02158231, -0.6421874 ,  0.15884112,
        0.05567972,  0.46831623,  0.00256531,  0.5438112 , -0.299464  ,
       -0.36935624,  0.5273454 ,  0.6622935 ,  0.79100156,  0.10678965,
       -0.4132647 ,  0.19694413, -0.49461237,  0.27651727, -0.21847725,
        0.20411713,  0.5437356 , -0.00948908,  0.35427317,  0.18341732,
        0.17610069,  0.19848059,  0.13011695,  0.45513186,  0.48886064,
       -0.5979473 , -0.36974883,  0.17267857,  0.90225303,  0.28648362,
       -0.6541002 ,  0.06353224, -1.033557  , -0.24444641, -0.44333616,
       -0.25433588,  0.5210665 , -0.16594745,  0.3813616 , -0.38393366,
       -0.19700892, -0.03007729, -0.40966046,  0.09833565,  0.02755377,
        0.46764788, -0.27788714,  0.08613144, -0.72040296, -0.45078477,
        0.24464688, -0.15521869, -0.4818502 ,  0.2872511 , -0.18731269,
        0.6729532 ,  0.2998123 , -0.7590212 , -0.32914448,  0.61112994,
        0.44147694,  0.5317429 ,  0.14157335, -0.08723088, -0.13927126,
       -0.18974023, -0.12097908,  0.12184799, -0.16536929,  0.10808472,
        0.07239145,  0.23736209, -0.9637128 ,  0.43604386, -0.33333102,
        0.4122578 , -0.20885074, -0.2592826 ,  0.4240338 ,  0.31337887,
        0.03120325, -0.2512945 ,  0.06159026,  0.27833155,  0.2829265 ,
       -0.30325615, -0.18322265,  0.2977425 , -0.09405349,  0.22661784,
       -0.62175083, -0.15000825,  0.15874259,  0.45977807,  0.68417513,
       -0.33066848, -0.22253574, -0.9687519 , -0.35669047, -0.4000382 ,
       -0.6001001 , -0.87750447, -0.02588039, -0.10336864,  0.35629436,
       -0.3000429 ,  0.23447737,  0.4820839 , -0.08851643, -0.20881326,
        0.1908632 ,  0.32761917,  0.3241049 , -0.83293265,  0.5564652 ,
       -0.25190592,  0.22847348,  0.13223436,  0.10882783, -0.571195  ,
        0.25587764, -0.47237545,  0.43926802, -0.0207971 , -0.215633  ,
        0.06247192, -0.88529897, -0.05092121,  0.13624276,  0.08424425,
       -0.32396314, -0.26511645,  0.15751387,  0.2282734 , -0.48307067,
        0.0358727 ,  0.35011473,  0.18164766, -0.03104882, -0.3364635 ,
       -0.14100294, -0.6717064 ,  0.00807868,  0.11917218, -0.04819752,
        0.5434505 ,  1.1529694 , -0.589461  ,  0.03753499, -0.11854783,
       -0.12911108,  0.08983273, -0.04672306, -0.8783082 , -0.19267471,
       -0.36849257, -0.30849972,  0.23372261,  0.17908351, -0.6456842 ,
       -0.03017994,  0.25637096, -0.08459464,  0.08220122,  0.12339534,
        0.00589156, -0.22077385], dtype=float32), array([0.32817632, 0.54489535, 0.35905144, 0.40923026, 0.43209472,
       0.5402896 , 0.55768484, 0.50859016, 0.3414898 , 0.36460382,
       0.31408426, 0.87586427, 0.43863195, 0.41886216, 0.4761546 ,
       0.4012119 , 0.50591785, 0.6207257 , 0.47293007, 0.544146  ,
       0.4085821 , 0.5781421 , 0.6938528 , 0.3361356 , 0.4394594 ,
       0.42010227, 0.4252746 , 0.7724512 , 0.3546021 , 0.33731347,
       0.44985315, 0.64016885, 0.4176709 , 0.39523712, 0.26819694,
       0.59210885, 0.543626  , 0.30877903, 0.5512282 , 0.4432505 ,
       0.34101352, 0.43934283, 0.32480362, 0.6615845 , 0.7685543 ,
       0.3830631 , 0.34149778, 0.394323  , 0.5276047 , 0.3506485 ,
       0.56660384, 0.49476135, 0.3838513 , 0.37597457, 0.44102147,
       0.44386533, 0.43072468, 0.4568594 , 0.5564771 , 0.4298066 ,
       0.48598367, 0.48160076, 0.4020609 , 0.41504315, 0.31176603,
       0.6862889 , 0.49130392, 0.849282  , 0.32580015, 0.34850198,
       0.3895748 , 0.26416805, 0.2889825 , 0.7951154 , 0.5290253 ,
       0.31472382, 0.38048828, 0.6682815 , 0.48013195, 0.4022094 ,
       0.3645315 , 0.41396037, 0.5350082 , 0.48046398, 0.51216215,
       0.52049655, 0.49979725, 0.59226805, 0.8462718 , 0.5140758 ,
       0.7396005 , 0.40870696, 0.42370883, 0.36582053, 0.53192276,
       0.33469847, 0.44328585, 0.6356993 , 0.4339778 , 0.32923117,
       0.6460089 , 0.39329022, 0.4411382 , 0.41742888, 0.85630924,
       0.38923904, 1.0174699 , 0.6337339 , 0.6763236 , 0.8094551 ,
       0.62450254, 0.8214013 , 0.33417124, 0.46182004, 0.838355  ,
       0.45624506, 0.44678476, 0.37671274, 0.42285508, 0.7336747 ,
       0.7858354 , 0.5096819 , 0.55809194, 0.62299824, 0.6822183 ,
       0.4635176 , 0.5831114 , 0.4418108 , 0.42907423, 0.7372545 ,
       0.7690502 , 0.5267677 , 0.36943784, 0.41612425, 0.33692887,
       0.29179427, 0.31583068, 0.4037453 , 0.46977183, 0.51218915,
       0.74532443, 0.67629766, 0.29733196, 0.5846897 , 0.4920285 ,
       0.37855777, 0.44517496, 0.42066804, 0.51869816, 0.52511734,
       0.5612255 , 0.39362663, 0.49907476, 0.41293147, 0.7156022 ,
       0.41375944, 0.36296365, 0.38028288, 0.39417467, 0.3072231 ,
       0.60540545, 0.6840132 , 0.27999774, 0.37794828, 0.40239072,
       0.74993956, 0.67448103, 0.40493986, 0.30812135, 0.5682012 ,
       0.4652236 , 0.53038764, 0.4470132 , 0.32889053, 0.49803403,
       0.26884735, 0.4731162 , 0.35610166, 0.3588846 , 0.6810521 ,
       0.73887   , 0.42699647, 0.50547564, 0.38432574, 0.44909364,
       0.43068376, 0.2950137 , 0.35166016, 0.74241894, 0.57869107,
       0.4105934 , 0.6580243 , 0.41205457, 0.5624934 , 0.6004076 ,
       0.54673755, 0.71336305, 0.65529764, 0.8444386 , 0.40287915,
       0.35675725, 0.37386465, 0.48717365, 0.51135   , 0.47953466,
       0.33232492, 0.5345236 , 0.4027567 , 0.47772068, 0.43114993,
       0.7609176 , 0.3700771 , 0.4086281 , 0.39853767, 0.3947308 ,
       0.25994238, 0.48729637, 0.56694806, 0.37175256, 0.577089  ,
       0.43168792, 0.29678166, 0.4038946 , 0.40596092, 0.7317842 ,
       0.3848425 , 0.36219978, 0.40992564, 0.59947836, 0.7901313 ,
       0.66146266, 0.3957099 , 0.63595665, 0.51704293, 0.46450597,
       0.45831466, 0.72805727, 0.64238673, 0.48651546, 0.4128336 ,
       0.5723847 , 0.61994183, 0.55514544, 0.6203846 , 0.4391204 ,
       0.3859648 , 0.75330263, 0.70456153, 0.42801315, 0.34972647,
       0.50634694, 0.5145088 , 0.40571347, 0.39655653, 0.355061  ,
       0.44695184, 0.47319862, 0.6568833 , 0.51065713, 0.6266575 ,
       0.5496352 , 0.41889504, 0.47434428, 0.30054572, 0.5629906 ,
       0.2924719 , 0.47925794, 0.44767165, 0.31855002, 0.32833838,
       0.5031309 , 0.46327707, 0.42346615, 0.44742864, 0.4157452 ,
       0.35901326, 0.716828  , 0.34123266, 0.36270872, 0.6768912 ,
       0.5926241 , 1.0891259 , 0.29173872, 0.35891402, 0.796973  ,
       0.49867296, 0.42488205, 0.35795277, 0.5433886 , 0.5325974 ,
       0.32014135, 0.47742626, 0.51975465, 0.66417295, 0.67663366,
       0.401818  , 0.43695718, 0.3528848 , 0.6164932 , 0.33595365,
       0.5993814 , 0.8401125 , 0.31111163, 0.52541167, 0.5536264 ,
       0.38422573, 0.6242725 , 0.6250082 , 0.66327417, 0.5633979 ,
       0.42634556, 0.847305  , 0.5482771 , 0.3596293 , 0.42394343,
       0.29600096, 0.31442398, 0.4342748 , 0.5635719 , 0.4494558 ,
       0.38345054, 0.44994372, 0.91868705, 0.46351445, 0.48282105,
       0.36263886, 0.49158782, 0.43316332, 0.4971957 , 0.45905373,
       0.39946806, 0.46817777, 0.854045  , 0.80405605, 0.4381155 ,
       0.5185789 , 0.72685355, 0.47394666, 0.38155276, 0.556018  ,
       0.26230577, 0.48461086, 0.85885334, 0.33023772, 0.4038036 ,
       0.5686064 , 0.77300775, 0.31630993, 0.58869225, 0.61784506,
       0.5846644 , 0.33625358, 0.76200044, 0.3940165 , 0.4256362 ,
       0.40468118, 0.47764164, 0.37946826, 0.4198069 , 0.36711213,
       0.29894748, 0.7444599 , 0.36912894, 0.37104318, 0.35854548,
       0.33538407, 0.4370064 , 0.5429603 , 0.30529368, 0.52219623,
       0.49113905, 0.36779708, 0.3351602 , 0.4137516 , 0.6446119 ,
       1.0230032 , 0.34685555, 0.7168741 , 0.48586285, 0.36507747,
       0.8202939 , 0.7337175 , 0.4210662 , 0.50110155, 0.47995728,
       0.3760757 , 0.4774835 , 0.29762378, 0.4133897 , 0.37591514,
       0.9868793 , 0.4610763 , 0.32515627, 0.52596325, 0.34623572,
       0.35444972, 0.4427745 , 0.5867571 , 0.6928784 , 0.29514182,
       0.81325996, 0.36621255, 1.418663  , 0.30371708, 0.6447119 ,
       0.6094713 , 0.45473135, 0.48301166, 0.40490738, 0.45494002,
       0.46137273, 0.46448627, 0.33400834, 0.37042385, 0.32328224,
       0.29450172, 0.3562848 , 0.57468104, 0.7126935 , 0.36175805,
       0.52894944, 0.4021114 , 0.55552757, 0.71020806, 0.58793455,
       0.321109  , 0.31029454, 0.3995366 , 0.3974777 , 0.51299435,
       0.33768874, 0.4926822 , 0.773107  , 0.49298543, 0.5655475 ,
       0.40640995, 0.39005145, 0.2853416 , 0.56125677, 0.5987012 ,
       0.41594404, 0.363479  , 0.5125647 , 0.42642787, 0.47028136,
       0.32841682, 0.6065554 , 0.7144787 , 0.4391876 , 0.5014114 ,
       0.28977984, 0.34923235, 0.71794516, 0.53954756, 0.4986275 ,
       0.36160883, 0.355443  , 0.5467134 , 0.71256614, 0.41363326,
       0.588226  , 0.4403938 , 0.35507593, 0.4545704 , 0.38267097,
       0.58100075, 0.5081716 , 0.5526092 , 0.46941334, 0.43887708,
       0.41576156, 0.79928803, 0.4328869 , 0.68602675, 0.45712537,
       0.44622964, 0.58254564, 0.60736126, 0.49157053, 0.4729582 ,
       0.46317953, 0.63198423, 0.38649827, 0.436231  , 0.393857  ,
       0.5792692 , 0.5746052 , 0.32237142, 0.61705863, 0.34306172,
       0.44524297, 0.7737089 , 0.40489942, 0.5500943 , 0.27785814,
       0.370905  , 0.414088  , 0.5835289 , 0.64676106, 0.57747155,
       0.35812917, 0.47913054, 0.4768419 , 0.47726405, 0.57996124,
       0.4339174 , 0.5085163 , 0.37190768, 0.36074156, 0.64012843,
       0.43612456, 0.51348084], dtype=float32), array([[[[ 0.01387648],
         [ 0.01842728],
         [ 0.04499955],
         ...,
         [-0.01838309],
         [ 0.03385267],
         [-0.05049341]],

        [[-0.01478109],
         [ 0.02755223],
         [-0.03951278],
         ...,
         [-0.00106806],
         [-0.03851604],
         [-0.00342046]],

        [[-0.04289914],
         [ 0.02652806],
         [-0.04541204],
         ...,
         [-0.00375971],
         [-0.01049747],
         [ 0.03727669]]],


       [[[-0.04474609],
         [-0.01833668],
         [-0.0223636 ],
         ...,
         [ 0.00998807],
         [-0.00543329],
         [ 0.00299602]],

        [[-0.00237129],
         [ 0.00955118],
         [-0.01496431],
         ...,
         [ 0.03934499],
         [-0.01075036],
         [ 0.03320144]],

        [[ 0.02473919],
         [ 0.04400234],
         [-0.01006034],
         ...,
         [-0.01112928],
         [ 0.00767071],
         [ 0.0223692 ]]],


       [[[ 0.01117636],
         [ 0.01415128],
         [-0.02641626],
         ...,
         [ 0.04628922],
         [-0.03144042],
         [ 0.02621216]],

        [[-0.0213071 ],
         [ 0.04979638],
         [ 0.00812892],
         ...,
         [-0.02219217],
         [-0.0635746 ],
         [ 0.03705258]],

        [[ 0.05701116],
         [-0.00172534],
         [-0.00452027],
         ...,
         [ 0.02414861],
         [-0.02504326],
         [-0.00161759]]]], dtype=float32), array([1.0032858 , 1.0070314 , 0.9837879 , 0.966594  , 1.0364785 ,
       1.0008717 , 1.0181845 , 1.0336343 , 0.9984213 , 1.023192  ,
       0.98993707, 1.0039822 , 0.98462075, 0.9826312 , 1.0145324 ,
       1.0199515 , 0.9706322 , 0.9841679 , 1.020653  , 1.0122627 ,
       0.99824494, 0.9883837 , 0.9790347 , 1.0336286 , 0.9920245 ,
       0.9750515 , 1.010237  , 1.0056106 , 1.0100456 , 1.0172954 ,
       1.0162398 , 0.9753211 , 0.9935762 , 1.0054172 , 1.0158597 ,
       0.9963493 , 0.9880612 , 0.99904346, 1.014848  , 1.0348307 ,
       1.0027672 , 1.0385653 , 1.0287229 , 0.98507875, 0.9799135 ,
       0.9959856 , 0.9939759 , 1.0081012 , 0.99779075, 0.98760957,
       1.0129778 , 1.0092572 , 0.99752855, 0.96221554, 1.0010955 ,
       0.97569144, 1.0110385 , 1.011908  , 1.0039209 , 0.9917912 ,
       0.9922296 , 0.97558737, 0.99353874, 1.0125489 , 0.97768575,
       0.98604673, 0.9970562 , 1.0144403 , 0.9625528 , 1.0018399 ,
       0.98417395, 1.0126019 , 0.975261  , 1.0031215 , 1.0167868 ,
       1.0189103 , 1.0058358 , 0.9871366 , 1.001614  , 0.99732506,
       0.9966338 , 1.0146873 , 0.9723846 , 1.010216  , 0.98800826,
       1.0050282 , 1.0350403 , 0.966911  , 0.9940839 , 1.0483276 ,
       0.9965536 , 0.9877596 , 1.0312114 , 0.9596609 , 1.0236232 ,
       0.9796545 , 0.952848  , 1.0037227 , 0.9841607 , 0.9902241 ,
       1.0172764 , 1.0022498 , 1.0039704 , 1.0056897 , 1.0381421 ,
       1.0227643 , 0.9943721 , 1.0059094 , 1.0030957 , 1.0086358 ,
       1.0082232 , 0.9971464 , 1.0052369 , 0.9956947 , 0.9963309 ,
       0.98580766, 1.0012401 , 0.98624   , 0.9977726 , 1.0197871 ,
       0.96317285, 0.9871406 , 1.035606  , 0.98985726, 1.0057698 ,
       0.9885405 , 0.9773111 , 0.99704146, 0.9995521 , 0.9619144 ,
       1.01366   , 1.0204402 , 1.0033175 , 1.0256766 , 1.0377283 ,
       1.0219018 , 0.98529786, 1.0263071 , 0.9686828 , 1.0082659 ,
       1.0258002 , 0.9746062 , 1.0216105 , 1.0039624 , 0.9949767 ,
       0.9885619 , 1.0019879 , 1.0097791 , 1.0284857 , 0.9852003 ,
       0.95820963, 1.003814  , 0.9654248 , 0.999277  , 0.9735694 ,
       1.0251038 , 0.9813109 , 0.9783684 , 0.9958658 , 1.0380878 ,
       0.9945724 , 0.9943286 , 0.9995195 , 1.0084368 , 0.98185855,
       0.9924716 , 1.011978  , 0.995187  , 0.97323346, 0.98029864,
       1.008591  , 0.9806214 , 0.98673385, 1.006792  , 0.96246564,
       1.0478874 , 1.0052544 , 1.0478467 , 1.011866  , 0.98778045,
       1.0080206 , 0.9890017 , 0.9929731 , 1.0097455 , 1.0076244 ,
       0.995323  , 0.99081016, 0.97241586, 1.015946  , 0.9903848 ,
       1.0181779 , 0.9815824 , 0.9916446 , 0.99512565, 1.0062077 ,
       0.97822654, 1.0306816 , 0.9791234 , 0.99144363, 0.9797589 ,
       0.976582  , 1.0178026 , 0.9945291 , 1.0052682 , 1.0431561 ,
       1.0034866 , 0.9879731 , 0.98157257, 0.9873125 , 0.99760014,
       0.9848093 , 0.9945732 , 1.0047041 , 1.0252806 , 1.0057874 ,
       1.0079528 , 1.0087183 , 0.9934542 , 1.0246979 , 0.9977117 ,
       1.0222273 , 1.0082786 , 0.98159647, 1.01058   , 1.0171851 ,
       0.986785  , 0.9820665 , 0.99751073, 0.992748  , 0.9671125 ,
       0.98569065, 0.9950569 , 0.96994275, 1.0072191 , 1.0125322 ,
       0.99218696, 0.9988775 , 0.98339844, 0.9970818 , 1.0325257 ,
       0.9929508 , 0.99414873, 1.0041279 , 0.9821924 , 1.0056458 ,
       0.98761886, 1.0018288 , 1.0011871 , 1.0083219 , 1.0207243 ,
       1.03386   , 1.0163007 , 1.021417  , 0.9723005 , 1.0025171 ,
       0.99104863, 0.98367023, 1.0154481 , 1.0036123 , 0.9867816 ,
       0.97203535, 1.0047234 , 0.9826699 , 0.97186434, 0.94891286,
       0.98353565, 1.0081187 , 1.0009239 , 1.0298477 , 0.96684057,
       1.007012  , 0.9999164 , 1.0067896 , 1.0085624 , 0.98319083,
       1.0013205 , 1.0394253 , 0.9979345 , 0.97367513, 0.99837244,
       0.976197  , 0.9964168 , 1.0132297 , 1.0290539 , 1.0118507 ,
       0.9800687 , 1.0428274 , 0.9950761 , 0.9984856 , 1.0120522 ,
       0.9880591 , 1.0139322 , 0.9986257 , 0.99007237, 0.9988841 ,
       1.0287647 , 1.0082917 , 1.0449455 , 1.0084596 , 0.999959  ,
       0.9678107 , 1.01468   , 0.9867519 , 0.9977007 , 1.0170437 ,
       0.9796737 , 1.0187402 , 0.99781394, 1.0115227 , 0.9935414 ,
       0.99299055, 0.9925837 , 0.9805536 , 0.99129754, 1.006515  ,
       0.99133825, 0.99452376, 1.0080338 , 1.0022665 , 0.9817281 ,
       1.0091622 , 0.99001515, 0.9774474 , 1.064796  , 1.0402578 ,
       0.98115164, 0.9949956 , 0.9866489 , 0.99630713, 0.99946666,
       1.0103155 , 1.0228232 , 0.9994699 , 1.0081996 , 1.0038642 ,
       1.0157369 , 0.9772196 , 0.9964326 , 0.9964086 , 0.98767483,
       0.9987462 , 0.983932  , 0.9794952 , 0.99942434, 1.0433233 ,
       1.0069846 , 1.021178  , 1.0113797 , 0.97829247, 1.0130806 ,
       0.99052083, 1.0117173 , 1.0056771 , 0.99847025, 0.99090034,
       1.0013006 , 1.0136496 , 1.0217319 , 0.96776956, 1.0134282 ,
       1.0009205 , 0.9894577 , 1.0140934 , 0.9877435 , 0.99796325,
       0.989181  , 0.983938  , 1.0087012 , 1.0083351 , 1.0025096 ,
       1.03459   , 1.0021    , 1.0038823 , 0.9817965 , 1.0216081 ,
       0.9895265 , 1.0333142 , 1.0078156 , 0.99766463, 0.9966601 ,
       0.99299985, 0.98610747, 0.97565156, 1.0451859 , 1.0217503 ,
       0.9915071 , 0.9915727 , 0.9970571 , 1.0350193 , 0.99800324,
       1.0008707 , 0.99708873, 0.9973232 , 1.0203512 , 1.0221003 ,
       0.9831432 , 1.0202159 , 1.018342  , 0.9970983 , 1.0156351 ,
       1.0083528 , 0.9908663 , 0.99732304, 1.0177289 , 0.9872836 ,
       1.011124  , 1.0061452 , 1.0041022 , 1.0128077 , 1.0162277 ,
       0.9988931 , 0.9805693 , 0.98193514, 0.9835401 , 0.9808011 ,
       0.9675781 , 0.98921514, 1.00744   , 1.0016484 , 0.97556186,
       1.0122449 , 0.99596363, 0.9921997 , 0.98022276, 0.9678523 ,
       1.0416893 , 0.9964221 , 0.98742557, 0.9646311 , 0.998783  ,
       1.0164189 , 0.98042136, 0.9969693 , 1.0077586 , 0.9895316 ,
       1.0066856 , 1.0007421 , 0.9881925 , 1.0270592 , 0.9893602 ,
       1.008786  , 0.992532  , 1.0275496 , 0.99812675, 1.0426655 ,
       1.025557  , 0.9709905 , 1.0107843 , 1.003217  , 1.0157914 ,
       1.0146523 , 1.0037881 , 0.97726387, 0.9918788 , 1.0198767 ,
       1.0213228 , 1.0203661 , 1.0322512 , 1.0265869 , 0.9938725 ,
       1.0035595 , 1.0008112 , 0.9899959 , 1.0209833 , 0.99546206,
       0.99918824, 1.0016091 , 0.98113257, 1.0047857 , 1.0046142 ,
       1.0083874 , 0.982216  , 1.000143  , 0.9978802 , 1.0007896 ,
       0.9738561 , 0.9864204 , 1.0064589 , 0.9986164 , 1.0103173 ,
       1.0078053 , 0.99573284, 0.9730538 , 1.0303321 , 1.0073593 ,
       1.001448  , 1.0034891 , 1.0126109 , 1.0027001 , 1.0192648 ,
       1.0199933 , 0.96154904, 0.99876875, 1.0164626 , 0.99721503,
       0.98529625, 0.9971689 , 1.0230149 , 1.0060296 , 1.0015799 ,
       0.9855334 , 1.0242862 , 0.98792183, 0.98887306, 0.9779713 ,
       0.9931449 , 0.99055815, 1.0229653 , 1.0020194 , 0.97577304,
       1.0187974 , 1.0154806 ], dtype=float32), array([ 5.02710789e-03,  9.84067749e-03, -1.82272233e-02, -3.94529328e-02,
        2.71424670e-02,  5.19093685e-03,  1.02150096e-02,  3.92232612e-02,
        1.63930911e-03,  2.65888758e-02, -3.76722077e-03,  1.79314725e-02,
        2.64691235e-03,  3.63502768e-03,  1.89664774e-02,  5.39621012e-03,
       -2.49064062e-02,  1.50904781e-03,  5.13334945e-02,  1.72832720e-02,
        1.83705445e-02, -1.97000001e-02, -4.46857475e-02,  3.06289475e-02,
        7.06939842e-04, -2.65824292e-02,  3.09886448e-02,  1.45391412e-02,
        1.38193900e-02,  1.89339016e-02,  1.30048802e-03, -5.21346889e-02,
       -1.36737002e-03,  6.63531013e-04,  2.67439391e-02, -1.20225642e-02,
       -3.27635109e-02, -2.17121863e-03,  2.42348183e-02,  4.38796449e-03,
       -6.73247874e-03,  2.94037145e-02,  3.08330264e-02, -3.33596690e-05,
       -2.03049500e-02, -4.29370403e-02,  1.31925410e-02, -1.91180065e-04,
        2.18946692e-02, -3.73061113e-02,  1.63287073e-02, -3.11463093e-03,
       -4.28311620e-03, -2.98278574e-02, -1.78096984e-02, -2.82580741e-02,
        8.93888180e-04, -2.68489448e-03, -1.13877449e-02, -1.42882194e-03,
       -8.00015754e-04, -2.73192078e-02,  2.66017187e-02,  1.20407706e-02,
        3.10032512e-03, -3.23970914e-02, -1.29009886e-02,  7.11273868e-03,
       -3.60083953e-02, -1.40855080e-02, -7.42664468e-03, -2.61438498e-03,
       -1.07338643e-02,  5.22232428e-03,  1.50694055e-02,  1.58161018e-02,
        4.38109552e-03, -3.64822894e-02, -1.10698901e-02, -1.84457265e-02,
       -9.12129506e-03,  5.13438368e-03, -3.75430956e-02, -2.41900254e-02,
        1.63913816e-02,  5.34417108e-03,  3.49610462e-03, -2.15735119e-02,
       -7.22309249e-03,  1.67919137e-02,  5.08776912e-03,  8.36274028e-03,
        3.82905342e-02, -2.32499819e-02, -7.09451549e-03, -4.16853465e-03,
       -2.73802374e-02,  1.00090867e-02,  1.68815702e-02, -2.98280790e-02,
       -1.03802355e-02,  2.34287023e-03,  1.16441967e-02, -9.15483851e-03,
       -9.53798648e-03,  8.63922108e-03,  2.03175732e-04,  3.32975481e-03,
        2.01161336e-02,  2.69444454e-02,  8.69167130e-03, -1.22176381e-02,
        5.06184809e-03, -1.56896524e-02,  1.78188912e-03, -3.04524191e-02,
       -4.88263497e-04,  2.52494286e-03, -1.22111887e-02, -1.04102930e-02,
       -3.56987715e-02,  6.42056810e-03,  5.49380574e-03, -7.70585565e-03,
       -1.60695277e-02, -1.87185910e-02, -2.41620112e-02, -2.96197608e-02,
       -1.76028665e-02, -3.13463695e-02,  9.82270483e-03,  4.93895188e-02,
        2.00046748e-02,  9.69502085e-04,  3.39840576e-02,  8.54937453e-03,
        2.36365036e-03,  2.04774458e-02, -2.07266975e-02, -1.91068295e-02,
       -5.83388377e-03, -2.21087951e-02,  2.79733799e-02,  5.94872748e-03,
       -2.36018188e-02, -1.57187153e-02, -1.52510367e-02,  1.92810073e-02,
        2.05095410e-02, -2.02182513e-02, -3.62032615e-02,  1.15773231e-02,
       -2.92080082e-02,  2.98474566e-03, -9.96593572e-03,  3.14183533e-03,
        5.77348843e-03, -7.47730862e-03, -1.46700833e-02,  2.84773037e-02,
       -3.95630719e-03,  2.95593357e-03, -5.54853759e-04,  1.24121280e-02,
        2.08159094e-03,  3.21233124e-02, -2.32655508e-03, -1.70555077e-02,
       -1.30099403e-02, -2.17034668e-02, -1.67570040e-02, -3.42824459e-02,
        3.32631916e-03, -1.15019865e-02, -2.35408265e-02,  3.55285704e-02,
       -6.69076992e-03,  3.75887305e-02,  6.37034792e-03, -1.87215433e-02,
       -1.73643790e-02,  2.70388881e-03,  1.47138210e-02,  1.18345544e-02,
        2.01040562e-02, -1.82423182e-02,  6.63576461e-03, -5.55931404e-03,
       -1.64277926e-02,  1.82242529e-03, -7.41946232e-03, -2.63858680e-02,
       -3.42320502e-02, -8.30321200e-03, -6.67629763e-03, -2.63024289e-02,
       -7.51121901e-03, -1.18371332e-02, -1.66147556e-02,  6.25638524e-03,
       -1.59742907e-02,  6.23621698e-03, -1.58895701e-02,  3.25804465e-02,
        2.29335278e-02, -3.73130548e-03, -1.83640104e-02, -5.00120874e-03,
       -2.89572664e-02, -1.59179494e-02, -7.64818257e-03, -3.58455293e-02,
        2.31178775e-02, -7.57618109e-03, -6.80403784e-03, -7.35258916e-03,
        2.66387500e-02, -2.64135399e-03,  1.35832289e-02, -2.82438807e-02,
        2.67843679e-02,  9.70832165e-03, -4.65387292e-03, -9.12511349e-03,
       -4.38627228e-03, -1.40090641e-02, -3.58606651e-02,  2.35449169e-02,
       -8.91910773e-03, -2.11713798e-02, -2.51129754e-02, -1.03768371e-02,
       -2.65500769e-02,  2.17346586e-02, -7.60636153e-03, -8.01746827e-03,
        6.36906875e-03, -2.20226292e-02,  1.70850586e-02,  1.58161633e-02,
        3.24050244e-03, -2.80452538e-02,  4.11046029e-04,  6.75771246e-03,
       -8.35169107e-03,  1.71900988e-02,  9.27562919e-03,  2.29361225e-02,
       -1.36928922e-02,  3.57955997e-03,  3.62930745e-02, -1.92058273e-03,
        2.37711463e-02, -1.07480213e-02, -3.54575855e-03,  1.27205020e-02,
       -2.48875655e-03,  5.07438602e-03, -2.36256258e-03, -1.29260123e-02,
       -1.31021040e-02, -1.09389955e-02, -3.16002853e-02,  1.23720535e-03,
       -4.10963222e-02, -5.89321321e-03,  1.82104092e-02,  3.49091948e-03,
        1.44900531e-02, -2.23659165e-02,  7.45529449e-03, -1.04862591e-02,
       -2.72809286e-02,  2.97103240e-03, -5.11842594e-03,  5.41797793e-03,
        2.02636067e-02,  2.06187530e-03, -2.10102852e-02,  2.13487260e-03,
       -3.63569371e-02, -2.15710327e-02,  4.32369895e-02,  3.76571193e-02,
        2.25614198e-02, -1.48874670e-02,  6.51123235e-03,  2.19748495e-03,
       -1.07619371e-02,  4.66327975e-03, -6.89891400e-04, -8.14781711e-03,
        1.28563019e-02, -1.76429451e-02, -1.30680474e-02,  2.90436298e-02,
       -3.52629903e-03,  2.38716844e-02, -1.07013080e-02, -8.48795346e-04,
       -2.86145955e-02,  2.24643108e-02, -2.98786983e-02, -1.07100084e-02,
       -6.14851434e-03, -1.80372726e-02, -5.38042095e-03, -6.97949203e-03,
        2.29548700e-02, -1.04639260e-02, -1.78716071e-02, -2.90870685e-02,
       -2.02943731e-04, -2.15596557e-02, -1.54298879e-02, -2.44223513e-02,
        8.86401907e-03, -8.65095702e-04,  3.88623611e-03, -1.45161729e-02,
        6.02999981e-03, -2.86505558e-02,  1.41581446e-02,  7.75232688e-02,
       -8.11782491e-04, -6.54065935e-03, -1.11223254e-02, -7.81347137e-03,
        1.89855564e-02, -2.30475403e-02,  2.15769578e-02,  1.60513632e-02,
       -3.81205161e-03,  1.02325156e-02, -1.44243296e-02, -3.53504159e-03,
       -1.85683370e-02, -1.78487317e-04,  9.65555292e-03,  4.05115727e-03,
       -2.08097766e-03, -1.70253199e-02, -2.61279643e-02, -1.15359137e-02,
       -1.13143567e-02, -1.78968180e-02,  2.81692832e-03, -1.33606303e-03,
       -5.02705632e-04,  4.43611201e-03, -2.87169907e-02, -1.45701482e-03,
       -1.96705759e-03,  1.48942806e-02, -2.02901550e-02, -1.50915366e-02,
        2.16352716e-02,  2.75607407e-02, -5.15825255e-03,  1.35148931e-02,
        1.64455101e-02, -9.20980878e-04,  1.53840138e-02,  7.96626322e-03,
       -1.09147364e-02,  2.43115425e-02, -1.81624759e-02,  7.63026159e-03,
        1.28735527e-02,  1.79533921e-02,  2.50633117e-02,  1.04408478e-02,
        5.16818510e-03, -3.35000604e-02, -1.54730165e-02, -2.48382818e-02,
        4.60835407e-03,  4.14283760e-02, -1.15630804e-02, -2.47193631e-02,
        1.55253978e-02, -2.88542286e-02,  1.03089167e-02,  1.05288904e-02,
        2.63263918e-02, -1.42880399e-02, -2.59582326e-02,  1.11950864e-03,
       -7.54431449e-03,  1.53799634e-03, -1.56989656e-02, -7.71153206e-03,
       -6.34268299e-03, -1.48949586e-02,  3.62419114e-02, -7.61589792e-04,
       -9.38373711e-03, -4.26002545e-03, -1.01546841e-02, -8.12387280e-03,
        6.34207157e-03, -1.67965796e-03,  9.95787699e-03,  8.34546331e-03,
        1.07221631e-02,  1.77793577e-02, -5.99088287e-03,  3.57667580e-02,
        2.72840336e-02,  8.58322426e-04, -9.34365729e-04, -1.03579890e-02,
       -2.70114690e-02,  3.59764649e-03, -2.54643541e-02, -3.66103486e-03,
       -3.22228740e-03,  6.60079299e-03, -3.56139727e-02,  1.58343406e-03,
        6.91830181e-03, -1.01270713e-02, -8.47678632e-03, -6.01531845e-03,
       -6.97869668e-03,  4.28759828e-02,  6.64686132e-03,  2.38208659e-02,
       -7.96730164e-03, -1.76889042e-03, -2.04116106e-02, -9.44126211e-03,
       -2.74608843e-02, -1.86831355e-02,  1.37675861e-02, -1.24171581e-02,
       -2.22886563e-04, -2.47775065e-03,  1.33941863e-02,  2.08873581e-02,
        1.29874703e-02,  6.25335146e-03, -2.68905773e-03, -1.13305673e-02,
        3.54527086e-02,  1.79771371e-02, -1.59863122e-02,  1.53513448e-02,
        7.70685496e-03,  3.95836122e-03,  9.12394468e-03, -3.80426622e-03,
        2.25871848e-03, -7.43767153e-03,  2.43426226e-02, -9.57899634e-03,
       -1.08075887e-02,  1.37209781e-02, -6.52869092e-03, -1.75947770e-02,
       -2.42793374e-03,  2.61993408e-02, -7.30204768e-03,  3.29622533e-03,
        5.84409107e-03, -1.96747389e-02,  4.42936784e-03, -1.64082609e-02,
       -1.86632772e-03, -3.53486720e-03,  7.71155115e-03, -2.20162366e-02,
        3.90700856e-03, -1.65792927e-02,  2.34539583e-02, -1.37504945e-02,
       -1.64778773e-02, -2.39991676e-02, -9.24374722e-03, -1.05014285e-02,
       -7.62749987e-04, -2.67314073e-02, -2.18578130e-02,  4.48930003e-02,
        9.89605952e-03, -1.75219513e-02,  3.74302268e-03,  3.03058214e-02,
       -7.22635118e-03, -1.00257900e-02,  3.67027335e-03, -3.19486740e-03,
        2.02262588e-03,  1.45316347e-02, -3.60644497e-02, -2.16622893e-02,
       -6.26825355e-03,  1.95513219e-02,  9.72271897e-03, -1.96297243e-02,
        3.82358721e-03,  1.08652879e-02, -1.22842565e-02,  1.35982456e-02,
       -9.78589710e-03, -1.90614928e-02,  2.41826288e-03,  2.36253999e-02,
        3.45965149e-03, -3.24582681e-02,  2.32946035e-02,  4.24860530e-02],
      dtype=float32), array([-0.00705422,  0.05762047, -0.03485768,  0.02983429, -0.00437942,
        0.05200282,  0.03963261,  0.02057748, -0.01346681, -0.04713062,
       -0.0093249 , -0.02111378, -0.03881151, -0.02928653, -0.00663856,
        0.02352469,  0.027454  ,  0.02146322,  0.0267756 , -0.01325567,
       -0.01494228, -0.03819482,  0.03272309, -0.01804921,  0.00395806,
        0.04396347, -0.00356716, -0.01431942, -0.03205065, -0.00433289,
        0.04050669, -0.0380124 , -0.02475853,  0.02632218, -0.02253102,
       -0.03261603, -0.0403499 ,  0.00510996,  0.01539416,  0.00811872,
       -0.01711535, -0.06448408, -0.04031879, -0.04008225, -0.01773705,
       -0.00076865,  0.01767235, -0.03802233, -0.04055835, -0.01527432,
        0.05095073,  0.02931255,  0.011877  , -0.03918783,  0.01886333,
       -0.06247352, -0.03088344, -0.00150596, -0.01897459,  0.00813238,
       -0.02713844,  0.01913985, -0.02191465,  0.04370955, -0.04084226,
       -0.02420527, -0.04741734,  0.02988692,  0.04729613, -0.00453914,
       -0.02967319, -0.00855414, -0.02749591, -0.05362013, -0.03301892,
       -0.04577023,  0.03535238,  0.04232053,  0.00598466,  0.0415303 ,
       -0.06367995, -0.03785169,  0.00883886,  0.00203072, -0.04816198,
        0.0062269 ,  0.04006572, -0.01524766, -0.03582977,  0.01607677,
       -0.01392661, -0.05410099, -0.01123114, -0.03435512,  0.0331009 ,
        0.0240054 ,  0.02015808, -0.05828656,  0.02317919, -0.00116163,
        0.00636684, -0.06580278, -0.02281404, -0.04021808,  0.00086318,
        0.0506145 ,  0.05616953, -0.01483877, -0.04374061,  0.00277426,
       -0.02584911,  0.05674161, -0.0328519 ,  0.00658272,  0.04330004,
       -0.03699759,  0.02751707, -0.07267415,  0.01882834,  0.00185863,
        0.02014909,  0.0416934 ,  0.01826123,  0.00757016,  0.05828288,
       -0.00118238, -0.01713335, -0.03216959,  0.0289686 , -0.03496039,
       -0.02897876, -0.01147461, -0.00429363,  0.03950811, -0.00814955,
       -0.00686551, -0.03399127, -0.00417149, -0.01037527, -0.00189356,
        0.03387504,  0.00203657, -0.02042881, -0.01958024,  0.01037996,
       -0.01019587,  0.00975334,  0.00367487,  0.02788574,  0.00640522,
       -0.03887082, -0.02447536, -0.0338741 , -0.05133466,  0.01011663,
       -0.05760412, -0.03562586,  0.00622968, -0.02750559, -0.01543036,
       -0.0078408 ,  0.00837269, -0.04110791,  0.00020642,  0.01195591,
       -0.00259978,  0.00497375, -0.03025294, -0.02619918,  0.0325662 ,
       -0.03693702,  0.03303514, -0.00654398,  0.01082385,  0.00416059,
       -0.01470458,  0.02032717,  0.03682015, -0.03623988,  0.00325104,
        0.00642227, -0.03431039, -0.04770453, -0.01518557, -0.03209715,
        0.02998232, -0.02710156, -0.02717565,  0.04173591, -0.03388365,
        0.02368794,  0.01901351, -0.02758102, -0.0224552 ,  0.00906153,
       -0.05816618,  0.0316389 , -0.04397879, -0.02893943,  0.02031042,
       -0.01396452,  0.00154581,  0.01210043, -0.01512148,  0.01520471,
       -0.00379549,  0.02543651,  0.004633  ,  0.02068103, -0.0113583 ,
       -0.04577444,  0.00189644,  0.05122041,  0.01981669, -0.05558314,
        0.01910003,  0.01018808,  0.00189933, -0.02234547, -0.06681945,
       -0.03456479, -0.02853506, -0.04744356,  0.01953139,  0.05360075,
       -0.0284654 , -0.03955074, -0.05762649,  0.03895584,  0.01424589,
        0.04931858, -0.01048546,  0.03566309, -0.02593162,  0.03608982,
        0.01965938,  0.04710647, -0.00112959, -0.0254011 ,  0.03192381,
       -0.0347677 ,  0.02531458,  0.02100075,  0.0588612 ,  0.00502017,
        0.01405911,  0.01965984,  0.03502999,  0.01254724, -0.04248942,
        0.00066306, -0.03834914,  0.01794685,  0.02038466, -0.02190354,
       -0.02687537,  0.00557997, -0.02234948,  0.02297643, -0.00499441,
        0.04230668,  0.03385551,  0.00285533, -0.02549965,  0.00879896,
       -0.01071607,  0.02628282, -0.02991786, -0.0221733 , -0.01606905,
       -0.02327031, -0.02527451, -0.03669791,  0.04046078,  0.04969138,
       -0.00377132,  0.01240121,  0.00858461, -0.03744864, -0.03223613,
       -0.00991494,  0.03911177, -0.00997331, -0.06040954, -0.04563764,
       -0.0504243 , -0.05335097, -0.05983842,  0.01806423, -0.04461987,
        0.01008607,  0.00922898,  0.03841664,  0.0473504 ,  0.04062257,
        0.0373674 , -0.05034343,  0.01973296,  0.05288051,  0.0444319 ,
       -0.03155369, -0.03808894,  0.00358702,  0.0044127 ,  0.04235922,
       -0.01548407,  0.03036473,  0.03527347,  0.02814139,  0.0336622 ,
        0.01028453,  0.04758444, -0.06973069, -0.00133821,  0.01429329,
        0.00413318, -0.03411032,  0.01284846, -0.02326593,  0.00996002,
        0.01065026, -0.00910785, -0.00653561,  0.01531698,  0.08210988,
        0.0480394 ,  0.02754756,  0.01325971, -0.05544572,  0.0262552 ,
       -0.02487463,  0.03293062, -0.01896711,  0.02652671,  0.00261969,
       -0.04352248,  0.01113359, -0.01743178, -0.03733903, -0.05282805,
       -0.01279218, -0.05339841,  0.03170111, -0.00674126,  0.04805979,
        0.04496546, -0.0822963 , -0.02570006, -0.0411538 , -0.02056996,
        0.04498302, -0.01686745, -0.01468924, -0.05123317, -0.05040384,
       -0.01206447,  0.03281184, -0.04483659,  0.02016191, -0.04548056,
       -0.01784354,  0.01673698, -0.0109433 , -0.03056446,  0.01673139,
        0.03174651,  0.01271554,  0.04840936,  0.00398685,  0.0045249 ,
       -0.01424518,  0.00603596,  0.00154911, -0.0100461 ,  0.05938326,
       -0.04677734,  0.02559932, -0.03402155, -0.07512545,  0.01337538,
       -0.03381331, -0.01426237, -0.02795195,  0.04971587,  0.03233918,
        0.0523813 , -0.01060923, -0.02842747,  0.00750306,  0.00852637,
        0.05694495, -0.0457154 , -0.0087443 ,  0.04565703,  0.00136866,
       -0.0094039 ,  0.03288947, -0.03233392, -0.02564828, -0.01565178,
        0.03150536, -0.04075595, -0.04001448,  0.00346499, -0.01908272,
       -0.05384564,  0.02919558, -0.01087496, -0.00225877, -0.01534516,
       -0.0190328 ,  0.00701044,  0.02298406,  0.00226921,  0.01283733,
       -0.00718614,  0.01873524, -0.01705479,  0.0304596 , -0.02535833,
        0.00023776,  0.02991161, -0.01467091, -0.02642495, -0.00548009,
       -0.03345225,  0.00206091, -0.01108021, -0.04090955,  0.03069444,
       -0.02834655, -0.01981956,  0.02791995, -0.00889193, -0.03561686,
        0.01529999, -0.04965458, -0.06080274,  0.02109147, -0.01590842,
        0.03760155, -0.03833001,  0.04446563, -0.01556951,  0.0600622 ,
       -0.02664761, -0.03488357,  0.04926508,  0.00989213,  0.01472826,
       -0.01024333,  0.02175925,  0.04144165,  0.01988798, -0.00050603,
       -0.01597908,  0.03028548,  0.06317993,  0.01675704,  0.01158527,
       -0.01357939, -0.03356737, -0.00873804,  0.04679696, -0.04137135,
        0.02744105,  0.03567052,  0.00082416, -0.05328355,  0.01698465,
        0.0192693 , -0.01146217, -0.01172886,  0.04226561, -0.04662991,
       -0.07331011,  0.03532446,  0.01438751, -0.06112825,  0.0138515 ,
        0.00622812,  0.03570525, -0.02346124,  0.01352268,  0.0069995 ,
        0.0311726 ,  0.00354176, -0.04946509,  0.05844411,  0.02396902,
       -0.02814216, -0.04661152,  0.02839504,  0.04354464, -0.02327588,
       -0.05161746,  0.03245336,  0.0016018 ,  0.02698481,  0.06967973,
       -0.04781226, -0.03925558, -0.02967273, -0.01193428, -0.06133601,
        0.04709444, -0.03699771, -0.03988695,  0.00998667,  0.01441376,
       -0.05606333,  0.03941678], dtype=float32), array([0.00811038, 0.01147624, 0.00956466, 0.0083896 , 0.01068025,
       0.01261555, 0.00926556, 0.00866727, 0.00811609, 0.01189542,
       0.00759236, 0.00788344, 0.01027476, 0.00835631, 0.0112341 ,
       0.01084776, 0.007822  , 0.00860666, 0.00850127, 0.0077765 ,
       0.00860297, 0.00814418, 0.01362306, 0.00864098, 0.00815878,
       0.00960244, 0.00843333, 0.00800569, 0.00939622, 0.00820688,
       0.01153554, 0.00874207, 0.0090287 , 0.00964182, 0.00815686,
       0.00875749, 0.0082437 , 0.00792983, 0.00884236, 0.00823469,
       0.01372243, 0.01289053, 0.01013488, 0.008384  , 0.00727661,
       0.00838829, 0.00833921, 0.00859391, 0.01262495, 0.00738334,
       0.01639756, 0.00900594, 0.00772317, 0.0085443 , 0.00956775,
       0.00966185, 0.00870189, 0.00862514, 0.00784871, 0.00854553,
       0.0098778 , 0.00817481, 0.00846937, 0.00892956, 0.01015981,
       0.00783216, 0.00863185, 0.01197954, 0.00915858, 0.00862015,
       0.00919843, 0.00812231, 0.00818987, 0.00899989, 0.0115387 ,
       0.00931721, 0.00856382, 0.00887221, 0.00858478, 0.01006419,
       0.01137103, 0.00907294, 0.00783831, 0.00860671, 0.00953664,
       0.00776028, 0.01166932, 0.00959902, 0.00809236, 0.00901202,
       0.00927162, 0.01328972, 0.00813138, 0.00844669, 0.01058824,
       0.00914674, 0.00748391, 0.01697768, 0.00795328, 0.00768816,
       0.00790294, 0.01087783, 0.00816659, 0.01152277, 0.00713446,
       0.01103471, 0.01908099, 0.01066525, 0.01274604, 0.00789085,
       0.0103343 , 0.0191853 , 0.00893998, 0.00754183, 0.01454291,
       0.00847749, 0.01030391, 0.01148388, 0.00847623, 0.00884237,
       0.00908457, 0.01267249, 0.00812707, 0.00740826, 0.01719739,
       0.00757305, 0.00730824, 0.00864018, 0.00911207, 0.01340074,
       0.00974768, 0.0076324 , 0.00781171, 0.01005413, 0.00817134,
       0.0084642 , 0.0091189 , 0.00884883, 0.00770124, 0.007623  ,
       0.0125307 , 0.00723428, 0.00848778, 0.00729769, 0.01123794,
       0.00802768, 0.00792582, 0.00780887, 0.00936282, 0.00787272,
       0.00873693, 0.00826806, 0.01059588, 0.01078977, 0.0081955 ,
       0.01159522, 0.00981744, 0.00819825, 0.00778454, 0.0082894 ,
       0.00776173, 0.00756264, 0.00981099, 0.00768506, 0.00862141,
       0.00732984, 0.00743292, 0.00851115, 0.00798707, 0.00805422,
       0.00812429, 0.00804286, 0.00759859, 0.0080442 , 0.00979439,
       0.00916639, 0.00938227, 0.01036769, 0.01054729, 0.00749849,
       0.00769052, 0.00858698, 0.01302657, 0.00795387, 0.01190122,
       0.01005774, 0.00840727, 0.00760757, 0.0140064 , 0.011     ,
       0.00828124, 0.00901069, 0.00810746, 0.00771726, 0.00790223,
       0.01489055, 0.00863514, 0.01164285, 0.00751218, 0.00797377,
       0.00763411, 0.00839535, 0.00783114, 0.00841822, 0.0079822 ,
       0.00813209, 0.00871043, 0.00768892, 0.00936587, 0.00883918,
       0.01544993, 0.00846438, 0.01282732, 0.00970871, 0.01259638,
       0.00891756, 0.00771718, 0.00793734, 0.00967263, 0.01249646,
       0.00872266, 0.00966565, 0.01270729, 0.00878962, 0.01854101,
       0.01091054, 0.00877242, 0.01086388, 0.0098482 , 0.00746116,
       0.01080499, 0.00804737, 0.01130394, 0.00847904, 0.00971282,
       0.00898634, 0.01499736, 0.00726279, 0.00790277, 0.00943748,
       0.00846478, 0.00886068, 0.00778162, 0.01280994, 0.00764458,
       0.00777362, 0.00806366, 0.00797824, 0.00841567, 0.01061815,
       0.00815876, 0.00869142, 0.00903083, 0.00775013, 0.00819498,
       0.00803083, 0.00753214, 0.00901294, 0.00960249, 0.00760378,
       0.01179382, 0.00938053, 0.00733991, 0.00788092, 0.00744815,
       0.00750308, 0.0082413 , 0.00858165, 0.00940733, 0.00760557,
       0.00827027, 0.0082213 , 0.00965736, 0.00885381, 0.01163415,
       0.00808778, 0.00943196, 0.00860591, 0.00881691, 0.00833551,
       0.00760631, 0.00888962, 0.00855585, 0.01057828, 0.00885116,
       0.01416963, 0.01143475, 0.01135227, 0.00776041, 0.00923415,
       0.00760385, 0.00831539, 0.00835728, 0.01676647, 0.01479386,
       0.00864217, 0.01073366, 0.00795647, 0.01041044, 0.01067176,
       0.00786429, 0.01138872, 0.00738269, 0.00749341, 0.00940358,
       0.0085276 , 0.01212766, 0.0121116 , 0.00835299, 0.0091665 ,
       0.00816643, 0.01669697, 0.01786258, 0.00765171, 0.00859678,
       0.00856155, 0.00913081, 0.00794919, 0.00894507, 0.00773361,
       0.00877923, 0.00730165, 0.00718684, 0.00860987, 0.01953523,
       0.01200804, 0.00835301, 0.00847277, 0.01300063, 0.00972189,
       0.00919061, 0.00889212, 0.0074021 , 0.01195453, 0.00831963,
       0.00895461, 0.00701384, 0.00765067, 0.01035795, 0.01411007,
       0.00806734, 0.01724426, 0.01167107, 0.00767008, 0.01149715,
       0.00904922, 0.01281702, 0.00952005, 0.01240386, 0.00807292,
       0.0125092 , 0.00784851, 0.00870834, 0.01376378, 0.01070676,
       0.00798433, 0.01138175, 0.00985845, 0.0087034 , 0.01056151,
       0.00849078, 0.00783675, 0.00978756, 0.0090476 , 0.00790541,
       0.00981105, 0.00773247, 0.01503236, 0.00791595, 0.00841182,
       0.01010791, 0.0079894 , 0.00856138, 0.00786667, 0.01847576,
       0.00864661, 0.00898204, 0.00855584, 0.01362644, 0.00789699,
       0.01105975, 0.00928271, 0.00942026, 0.01290966, 0.01002654,
       0.01121764, 0.00726828, 0.0092902 , 0.00810848, 0.00778028,
       0.01076306, 0.00924686, 0.00741611, 0.01197086, 0.00773014,
       0.0083314 , 0.00911937, 0.00857881, 0.00955844, 0.00826768,
       0.01146055, 0.00990208, 0.00817511, 0.00844733, 0.01321999,
       0.01725242, 0.01053602, 0.00762369, 0.00871967, 0.00818044,
       0.00793199, 0.00749296, 0.00990313, 0.00756062, 0.00849113,
       0.00809191, 0.00925942, 0.00761356, 0.01032257, 0.00884816,
       0.00737379, 0.01018532, 0.00814791, 0.01057508, 0.00770331,
       0.00921154, 0.00756035, 0.00776483, 0.00991979, 0.00926583,
       0.00848205, 0.00777925, 0.00976115, 0.00744166, 0.01145879,
       0.00794282, 0.01175952, 0.01146662, 0.00918047, 0.00910974,
       0.011435  , 0.00930583, 0.00873492, 0.00830782, 0.01360995,
       0.00943744, 0.00790659, 0.00916533, 0.00795085, 0.00861057,
       0.00798324, 0.00857429, 0.01288845, 0.00804119, 0.00787552,
       0.00881874, 0.00907157, 0.02151334, 0.00805896, 0.0083672 ,
       0.00748677, 0.0102965 , 0.0077432 , 0.01385015, 0.0091502 ,
       0.01000263, 0.00929024, 0.00833553, 0.00960837, 0.00872565,
       0.00870132, 0.00695258, 0.00768819, 0.01818093, 0.01200904,
       0.0186106 , 0.00847818, 0.00909729, 0.0146472 , 0.00784268,
       0.00809972, 0.01257169, 0.00814084, 0.00874558, 0.0086438 ,
       0.0126006 , 0.00719676, 0.00966388, 0.01134768, 0.0083599 ,
       0.00927128, 0.01591685, 0.00902679, 0.01245202, 0.00870315,
       0.01218199, 0.00868223, 0.01026097, 0.0078764 , 0.0125873 ,
       0.01146467, 0.00882138, 0.00968314, 0.00781014, 0.00979876,
       0.012932  , 0.01135903, 0.00979547, 0.00789675, 0.00788294,
       0.01151298, 0.01023093], dtype=float32), array([[[[ 0.01975336, -0.04136827, -0.01981475, ..., -0.02672251,
           0.04657466,  0.05580618],
         [ 0.02992021, -0.03769051,  0.0019313 , ..., -0.08299991,
          -0.03222642, -0.05485666],
         [ 0.03776915,  0.0513159 , -0.05027932, ...,  0.05848086,
           0.05950139, -0.03447171],
         ...,
         [-0.02578815,  0.01314513, -0.04028864, ..., -0.07837445,
          -0.06478844,  0.01345323],
         [ 0.04285358, -0.03578597, -0.02296819, ..., -0.01953428,
          -0.0152576 , -0.05281388],
         [-0.0422351 , -0.13383067, -0.058369  , ..., -0.03068578,
           0.01628209, -0.05353565]]]], dtype=float32), array([1.0028591 , 1.0051414 , 0.9685889 , 0.94483155, 1.0107071 ,
       0.9735812 , 1.0092491 , 1.010709  , 1.014229  , 1.0104373 ,
       1.0036455 , 1.0084039 , 1.0069244 , 1.0265733 , 1.0090488 ,
       0.97495985, 1.0103687 , 1.0275179 , 0.99932456, 0.9815722 ,
       0.99858886, 1.0251026 , 0.9773082 , 0.9843099 , 0.9641027 ,
       1.0397772 , 0.9999515 , 0.9840331 , 0.9926551 , 1.0140064 ,
       1.0157782 , 1.009944  , 1.0089976 , 1.0203605 , 0.99983066,
       0.9561685 , 1.0090852 , 1.009844  , 0.98636496, 0.9829207 ,
       1.0407736 , 0.99240553, 1.0350022 , 1.0020046 , 0.9924107 ,
       0.98260695, 0.9958779 , 0.97257644, 1.0133439 , 1.0156811 ,
       1.0236478 , 1.0033543 , 0.99071074, 0.97392535, 1.0012183 ,
       1.0304495 , 0.9959844 , 1.0062839 , 1.0109814 , 1.0042883 ,
       0.98430854, 0.99136806, 1.0308372 , 1.0239353 , 1.0079792 ,
       0.9943117 , 1.0062401 , 1.0159128 , 0.9832257 , 1.0208174 ,
       1.0237767 , 0.99976987, 1.0227877 , 0.9909694 , 0.98742974,
       0.96951395, 1.0119689 , 0.9778466 , 1.0169536 , 1.032681  ,
       0.98172605, 0.9999361 , 0.98478097, 1.0076535 , 0.9707761 ,
       0.98424363, 1.0163379 , 1.0057435 , 0.97527015, 1.017605  ,
       0.99983585, 1.0303637 , 0.976194  , 0.9982487 , 1.0094849 ,
       1.0082608 , 1.0394697 , 1.0167527 , 0.9890414 , 0.9761357 ,
       1.0583706 , 1.0060035 , 1.0004328 , 1.0136765 , 1.0004687 ,
       1.0154933 , 0.9824525 , 0.9953858 , 1.0095345 , 1.019913  ,
       0.98520577, 1.0169001 , 1.0144958 , 1.0301664 , 0.9900315 ,
       1.0146095 , 1.0354378 , 1.0110513 , 1.0501407 , 1.0382749 ,
       0.99006176, 0.97388965, 1.0085249 , 1.0543153 , 0.999049  ,
       0.97513425, 0.99325913, 0.9658107 , 0.99145705, 1.023648  ,
       0.9875897 , 1.0132215 , 1.0082911 , 0.9859514 , 1.0025858 ,
       0.99146485, 1.0000508 , 1.0081705 , 1.0186404 , 0.9976721 ,
       0.9897321 , 0.99602765, 0.96712726, 1.0159876 , 0.98661673,
       1.0282154 , 1.0066233 , 0.9906573 , 1.0200527 , 0.9936128 ,
       1.0030588 , 1.0053838 , 1.0093118 , 0.9958236 , 0.99424547,
       1.0369711 , 0.9911491 , 0.9979943 , 0.96497846, 1.017097  ,
       0.9977309 , 1.0009558 , 1.0142134 , 1.0102357 , 1.0095128 ,
       0.968856  , 1.0069258 , 0.94930756, 1.0047414 , 1.0344058 ,
       0.99974906, 0.9667856 , 0.98646736, 0.99487114, 1.0191047 ,
       0.9859074 , 1.0303518 , 1.0047003 , 1.037574  , 1.0100721 ,
       0.98686516, 1.0013714 , 0.991172  , 1.0222949 , 0.99155706,
       0.998633  , 1.0140407 , 0.9936934 , 0.9981123 , 0.97689635,
       1.0162082 , 1.0056944 , 1.0216092 , 0.9965757 , 1.0006229 ,
       1.0305895 , 1.0036721 , 1.0056934 , 1.0108124 , 0.97827286,
       0.9765622 , 0.99283385, 0.9887011 , 1.0251058 , 0.98725545,
       0.9511286 , 1.0245796 , 1.0449067 , 0.99195606, 1.0010943 ,
       1.0140675 , 1.013915  , 0.9830111 , 1.0322816 , 1.0318364 ,
       0.9905378 , 1.0100386 , 0.98234713, 1.0294689 , 1.0150362 ,
       1.0037948 , 0.98998576, 1.0183738 , 1.0016375 , 1.0356383 ,
       0.98128134, 1.0079596 , 1.0187902 , 0.9831216 , 0.9924156 ,
       1.0120277 , 1.006304  , 0.9878369 , 1.0707139 , 1.0161746 ,
       0.98865515, 0.9867423 , 0.97423434, 0.98468846, 0.9877128 ,
       0.98237014, 1.004355  , 1.0075735 , 1.0285411 , 0.9809406 ,
       1.0042967 , 1.0179424 , 0.97625256, 1.0422086 , 0.9945827 ,
       0.99016154, 1.0113864 , 0.9943435 , 1.0116581 , 0.9764465 ,
       0.97388875, 0.99803966, 0.9657562 , 1.0110862 , 0.98199016,
       0.99831676, 1.0298055 , 0.98799396, 1.0004302 , 0.99543864,
       0.99402344, 1.0049572 , 1.009965  , 1.0097566 , 0.9934603 ,
       1.0210999 , 1.0126013 , 1.018064  , 0.99104947, 1.0392367 ,
       1.0114076 , 1.0039735 , 1.0145271 , 0.98772895, 1.0082828 ,
       0.9715636 , 1.014394  , 1.0000684 , 1.0336654 , 0.9904464 ,
       1.0278336 , 0.9845503 , 1.0136253 , 1.0052847 , 1.022078  ,
       1.0066447 , 1.0076692 , 1.0016971 , 1.0235491 , 0.9983453 ,
       1.0172074 , 1.0546983 , 1.0165204 , 1.0101414 , 1.0190061 ,
       1.0138098 , 1.0208493 , 1.0234692 , 1.0103766 , 0.97977215,
       1.000351  , 1.0402584 , 0.98605347, 1.0302398 , 1.0108389 ,
       1.0148847 , 1.0311264 , 1.001416  , 0.98559606, 1.0173391 ,
       1.005067  , 1.0392997 , 1.0631403 , 1.0403631 , 1.0288616 ,
       0.98583037, 0.99948114, 1.0231019 , 0.9914445 , 1.0311221 ,
       1.0228994 , 0.99178284, 0.99178565, 0.9884842 , 0.9953711 ,
       0.9908208 , 1.0189877 , 1.0411162 , 0.9836898 , 1.0225049 ,
       1.0019789 , 1.0103767 , 0.9972581 , 1.0041457 , 0.9950287 ,
       0.98890805, 1.0053309 , 1.0186248 , 0.97781247, 1.0098337 ,
       1.0087745 , 0.9540896 , 0.995287  , 1.0065451 , 0.95895505,
       1.0017015 , 0.97642344, 0.9777595 , 1.0092623 , 1.0215105 ,
       1.030091  , 0.9867604 , 1.0186228 , 1.0154396 , 1.0112981 ,
       1.027001  , 0.98752016, 0.9837961 , 0.99732655, 1.0170039 ,
       0.98051643, 1.0102676 , 1.0629776 , 1.0037905 , 0.99220127,
       0.9676946 , 1.0082984 , 1.0087463 , 0.97296447, 1.0032218 ,
       1.0091136 , 0.9993097 , 0.9959254 , 0.96368384, 1.0105407 ,
       0.996491  , 0.9890657 , 0.98287624, 0.9904221 , 0.98385626,
       0.9822043 , 0.9946741 , 1.011855  , 1.0289221 , 1.0188991 ,
       1.0215471 , 1.0175066 , 1.0185425 , 0.9995024 , 1.0031719 ,
       1.0245476 , 0.9928679 , 0.97685015, 1.0039507 , 0.99794245,
       0.9982606 , 1.0124649 , 1.0216879 , 0.99686205, 0.97957724,
       1.0207546 , 0.99736184, 1.0015998 , 0.98567164, 0.98354656,
       1.0034839 , 1.0254579 , 1.009784  , 1.0165037 , 0.9792641 ,
       0.9748895 , 0.9870827 , 1.0087744 , 1.014339  , 0.9919625 ,
       1.0045722 , 0.97377694, 0.9900779 , 0.9725946 , 0.9882422 ,
       0.9866917 , 1.0097647 , 0.989744  , 0.9802485 , 1.0238541 ,
       0.99777424, 1.0001901 , 0.98150647, 1.0121372 , 1.0099547 ,
       0.97316694, 0.9789965 , 0.96321714, 1.0289094 , 0.9746773 ,
       0.9642387 , 1.0309255 , 1.0040199 , 0.9925538 , 1.0135094 ,
       0.9981954 , 1.0372673 , 0.97666013, 0.98758847, 0.9793965 ,
       0.9811981 , 0.9806974 , 1.0166098 , 0.99757916, 0.9937225 ,
       0.9967753 , 1.0105773 , 1.0273751 , 0.9971281 , 0.97609645,
       0.97834706, 1.0082393 , 0.98162794, 0.9897625 , 1.0128706 ,
       0.970863  , 0.9814411 , 0.9975983 , 1.0256767 , 0.98778075,
       1.0045266 , 0.9916238 , 1.0226368 , 1.0312492 , 1.0173938 ,
       1.026226  , 0.9981018 , 0.98823166, 1.0059378 , 1.001195  ,
       1.0166012 , 0.9767875 , 1.002012  , 1.0135146 , 0.9907698 ,
       1.0219828 , 0.9950197 , 1.0228798 , 1.0069723 , 1.0044    ,
       1.0203431 , 0.9980619 , 0.9998134 , 0.97056067, 1.0127251 ,
       0.9642531 , 1.0357703 , 1.0034007 , 0.9869806 , 1.0152087 ,
       1.0026809 , 1.0150911 , 1.0263764 , 0.95826495, 0.97828484,
       0.9650649 , 1.0041376 , 0.99068457, 1.006401  , 1.021929  ,
       0.98496056, 0.99571943], dtype=float32), array([ 1.89588163e-02,  6.15868047e-02, -1.67646259e-02, -3.92906703e-02,
       -3.56669049e-03,  4.58617834e-03, -1.53528387e-02, -2.09172908e-02,
       -2.58149803e-02, -3.07430066e-02,  1.30103882e-02, -2.26508826e-03,
        3.21769193e-02,  1.00565713e-03,  4.82582673e-02, -3.80494930e-02,
       -1.64013077e-03,  3.00787166e-02,  2.73090112e-03, -1.60713494e-02,
       -9.36775468e-03, -1.35289229e-04, -1.31632043e-02, -4.07353789e-02,
       -2.00923975e-03,  3.07145938e-02, -8.29613674e-03, -2.01703850e-02,
        1.83229847e-03,  1.75009891e-02,  1.06803756e-02, -2.53545865e-03,
        5.16544003e-03,  9.04318783e-03,  2.38926783e-02, -5.19993454e-02,
       -1.57357417e-02, -1.79488547e-02, -9.82429250e-04,  7.87413865e-03,
        1.90170929e-02,  1.82003505e-03,  3.35657708e-02,  3.70181389e-02,
        2.19515851e-03,  7.23584183e-03,  1.18308105e-02, -3.90432775e-03,
        8.61083157e-03,  6.18987679e-02,  1.35024330e-02,  1.86056306e-03,
        4.51833121e-02, -1.20374877e-02, -2.81800907e-02,  3.34548391e-02,
        3.46542825e-03,  3.18903960e-02, -2.10232176e-02, -1.45030078e-02,
        1.91878024e-02, -9.74464230e-03,  1.52938403e-02,  1.67722572e-02,
       -6.84717018e-03, -2.43488979e-02,  2.36915965e-02, -1.19231874e-02,
        1.75460335e-02,  2.06540083e-03, -4.61194478e-02, -5.90722950e-04,
        7.71651138e-03, -2.96614766e-02, -3.21758687e-02, -2.36068778e-02,
        5.83984191e-03, -1.62070654e-02,  3.85148195e-03, -2.73858551e-02,
        1.47637920e-02,  1.91916190e-02, -1.17835961e-02, -4.03280882e-03,
       -1.87520068e-02, -7.35471491e-03,  1.98637508e-02,  2.82258578e-02,
        7.32007157e-03, -1.90721126e-03, -2.35490259e-02,  2.21321043e-02,
       -3.39773260e-02,  1.89307742e-02,  2.28726640e-02,  1.26641421e-02,
       -4.92076986e-02,  3.64180724e-03, -3.45677771e-02, -3.54469493e-02,
        2.81544346e-02,  1.05515039e-02, -1.04027605e-02, -4.33409773e-02,
       -1.28302341e-02,  4.42397734e-03, -2.14912705e-02,  2.45920848e-02,
       -1.23612992e-02,  1.21601894e-02, -4.09850813e-02,  9.29838046e-03,
       -1.62769239e-02, -2.80257105e-03, -3.91615182e-02,  4.59738187e-02,
       -6.61701942e-03, -1.03310533e-02,  4.46752924e-03,  2.53885631e-02,
       -2.03413609e-03,  2.26433645e-03, -2.78394129e-02,  3.91610302e-02,
        4.04828880e-03, -2.52403524e-02, -6.46962132e-03,  5.85535262e-03,
       -2.25091930e-02,  2.86713261e-02,  1.57179013e-02,  8.65145866e-03,
        5.33449557e-03, -1.38506880e-02, -4.57599992e-03,  1.51161049e-02,
       -1.73431996e-04, -1.99880195e-03,  4.00965149e-03,  2.61776499e-03,
       -6.47476083e-03,  1.06663667e-02, -5.33872396e-02,  1.95660815e-02,
       -1.62123963e-02,  1.37850996e-02,  9.74660832e-03, -2.78076772e-02,
       -1.96680017e-02,  1.98999699e-02,  9.83289629e-03,  7.66217429e-03,
        6.92437729e-03,  1.14337914e-02, -5.11292461e-03, -4.26260580e-04,
        3.72350514e-02, -2.19264068e-03,  1.16475793e-02, -1.71075447e-03,
        1.01872925e-02,  2.01635505e-03,  4.14462127e-02, -1.51572991e-02,
        2.68315282e-02,  1.19009521e-02, -6.49955263e-03, -4.67535630e-02,
        2.47598964e-05, -4.40964894e-03,  6.61360659e-03, -1.24626458e-02,
       -1.99890938e-02, -8.54976382e-03,  2.07558200e-02,  2.32453775e-02,
        3.45825553e-02,  5.31609589e-03,  3.26587260e-02,  8.43096245e-03,
        2.42043342e-02, -3.73764709e-03,  4.75561991e-02, -2.83618458e-02,
       -5.02283080e-03, -7.78190326e-03,  1.30080746e-03,  3.45185213e-02,
       -2.39285734e-02, -3.26715386e-03,  2.18726080e-02, -3.54223332e-04,
        5.98771460e-02,  3.87192294e-02, -1.22988876e-02, -1.88264635e-03,
       -9.59352497e-03, -1.62714869e-02,  2.36502718e-02, -1.39872162e-02,
       -1.24577787e-02,  1.08714160e-02,  7.13702990e-03,  2.22862028e-02,
        2.43474395e-04, -3.60118896e-02,  1.33401956e-02, -1.33779654e-02,
       -5.27730398e-03,  3.09982430e-02,  2.01052222e-02,  1.34520289e-02,
        1.79889966e-02, -2.21486278e-02,  4.41241153e-02, -5.62308868e-03,
        1.30473673e-02,  1.32466881e-02, -2.35690828e-02,  2.69102282e-03,
        5.77882677e-02, -1.50108840e-02,  1.63266924e-03, -2.58620139e-02,
        1.57086998e-02, -1.00372150e-03,  4.45210142e-03, -4.31278488e-03,
       -5.62085351e-03, -8.69872328e-03, -1.68022085e-02,  2.79769320e-02,
        4.04469408e-02, -5.63730346e-03, -2.63785552e-02, -9.74346511e-03,
       -1.33764166e-02, -2.98148207e-02, -1.32302446e-02,  2.34064348e-02,
       -6.06201915e-03, -3.27172987e-02,  1.16704563e-02,  7.27324747e-03,
       -1.99531820e-02, -9.83418059e-03,  3.29999626e-03, -5.84317232e-03,
       -2.79304478e-02, -7.91481230e-03, -2.29851087e-03, -4.58216341e-03,
        2.46257074e-02,  2.39603152e-03,  1.78048257e-02, -3.51179652e-02,
       -4.51827981e-02, -4.26754355e-03,  7.27609452e-03,  2.22425605e-03,
        1.41312517e-02, -1.74506530e-02, -1.18768997e-02,  1.27617328e-03,
        8.74328706e-03, -3.83544192e-02, -2.27333531e-02,  2.54256185e-03,
       -2.95569152e-02,  2.56927125e-02,  2.07202379e-02,  6.92661339e-03,
       -1.05524473e-02, -3.18899192e-02, -7.48742931e-03, -6.65036077e-03,
        2.36525480e-03, -1.76919922e-02,  2.34957673e-02, -2.23195739e-03,
        4.77237254e-03, -3.36954445e-02, -8.55301507e-03,  4.25871648e-02,
        2.39365385e-03,  2.18081772e-02, -2.46181097e-02,  2.53525600e-02,
        1.06920977e-03, -5.98530332e-03, -8.26704036e-03,  5.22999577e-02,
        3.65858572e-03,  2.11587232e-02, -2.54371646e-03, -7.88214151e-03,
        2.88511924e-02,  4.16352861e-02,  1.40487170e-02,  1.00825410e-02,
       -1.40259955e-02,  2.25795228e-02, -2.93130763e-02, -8.85976013e-03,
       -2.67924163e-02,  3.84981697e-03,  1.14647169e-02,  1.90772321e-02,
        2.00517029e-02,  1.44157335e-02, -1.81839112e-02, -1.58593170e-02,
        2.64082383e-03, -2.87659355e-02,  4.61743027e-02,  1.08499324e-03,
       -1.62009634e-02,  3.55210938e-02,  4.01321948e-02, -1.89267453e-02,
       -6.78299414e-03, -1.08579639e-03, -3.72850895e-02,  6.24406105e-03,
        1.89439114e-02,  5.29782511e-02,  1.74228474e-02,  3.12769203e-03,
        9.20390431e-03, -3.17917066e-03,  7.12337438e-03, -1.07146632e-02,
        2.48866621e-02, -3.34203080e-03, -1.31844366e-02,  2.85873772e-03,
       -1.45690320e-02, -5.29395556e-03, -2.90776379e-02, -4.97802813e-03,
       -2.95932759e-02, -3.72759365e-02,  4.43236018e-03, -2.56233849e-02,
       -2.58966312e-02, -2.25051714e-04,  1.55143309e-02, -1.70027222e-02,
       -1.15162227e-02, -9.48728621e-03, -5.42623224e-03, -3.30492370e-02,
       -8.22951086e-04,  1.91631494e-03, -4.19784617e-03,  3.44350655e-03,
       -1.53060397e-02, -9.94064007e-03, -3.27535048e-02, -1.12125995e-02,
        1.19361132e-02, -3.66121419e-02,  2.03278642e-02,  1.74247916e-03,
        5.25522381e-02, -2.82071400e-02,  1.90849397e-02,  5.37339877e-03,
        4.23611887e-03, -6.48816396e-03,  1.89738511e-03, -4.25729156e-03,
        3.06390645e-03, -4.53999229e-02,  4.46908474e-02,  1.94724984e-02,
        2.82982532e-02, -2.54817996e-02, -2.25283951e-02,  3.00620776e-03,
        1.19754989e-02, -7.43059022e-03, -2.16933638e-02,  2.17459705e-02,
       -1.95821933e-03, -2.20922865e-02,  1.72305088e-02, -2.25415062e-02,
        2.79491860e-02,  2.71106418e-03, -2.68608455e-05,  9.60220955e-03,
       -3.90815288e-02,  1.84698980e-02,  5.41112982e-02,  2.93869730e-02,
       -3.81870531e-02, -2.88914926e-02,  6.86367834e-03,  5.20654628e-03,
       -3.57516319e-03,  1.12377722e-02,  3.43647227e-02,  1.54824834e-03,
        3.32348272e-02, -1.53678479e-02, -4.40781331e-03, -3.50815356e-02,
       -1.32072717e-03, -2.96059828e-02,  6.22754637e-03,  5.95860940e-04,
        3.97672504e-02, -7.81264901e-03, -8.15554615e-03,  9.74691380e-03,
        2.41906065e-02, -8.86283815e-03,  3.20329480e-02,  2.03408934e-02,
        1.55018838e-02, -3.97607349e-02, -1.80732254e-02, -2.30443315e-03,
       -1.38058851e-03, -1.08111780e-02, -2.22243369e-02,  1.67672914e-02,
       -1.06747830e-02, -1.63989142e-02, -3.30227576e-02,  3.37966606e-02,
       -1.03526143e-02,  2.08203476e-02, -4.32653129e-02, -3.24570313e-02,
       -3.77987465e-03, -1.00714117e-02, -9.32123233e-03,  4.96549420e-02,
       -3.52619812e-02,  1.28323818e-03, -1.19983181e-02, -8.31830548e-04,
        1.98712922e-03, -1.65167861e-02, -2.77970568e-03,  3.21895517e-02,
        1.29853347e-02, -3.18747503e-03, -1.24287978e-02, -2.13394724e-02,
       -8.49454198e-03, -1.14241326e-02, -2.70607993e-02, -3.30793969e-02,
       -5.26051037e-03, -5.06946072e-03, -1.41301006e-02, -1.67468805e-02,
        2.66338121e-02,  1.62115395e-02,  3.86145636e-02, -3.31944935e-02,
       -3.12872529e-02,  3.69019248e-02, -4.99330414e-03, -1.65508557e-02,
        4.09972891e-02,  1.72042996e-02,  3.99400620e-03,  1.07847890e-02,
       -1.33892344e-02, -4.91081923e-03,  6.00049831e-03,  4.42802021e-03,
       -4.11321148e-02, -4.05842625e-02, -7.14840717e-04,  1.22408355e-02,
       -1.10571710e-02,  1.00326147e-02, -8.01426545e-03, -1.55143710e-02,
        4.42963131e-02,  2.12054309e-02, -2.48507131e-02,  1.13824224e-02,
        4.15447839e-02, -2.50382209e-03, -7.48818333e-04, -5.47506241e-03,
        8.10466614e-03, -2.64675654e-02, -2.95242853e-02, -2.40560304e-02,
        1.89063307e-02,  2.07100958e-02,  1.80747695e-02,  8.57903250e-03,
        2.31811218e-03,  1.04358457e-02,  3.27767013e-03, -1.40564060e-02,
        1.07030990e-02, -1.30988900e-02,  4.81796032e-03,  2.37552021e-02,
        1.81037150e-02,  4.16742032e-03, -2.33639288e-03,  1.39860613e-02],
      dtype=float32), array([-0.2196301 , -0.2087597 , -0.3927154 , -0.5625967 ,  0.1379615 ,
       -0.24878173, -0.08709582,  0.5229314 , -0.6173515 , -0.2955765 ,
       -0.11336479, -0.31303784, -0.68925685,  0.02274968,  0.38794988,
        0.19393022, -0.18708073,  0.2976801 ,  0.13101806, -0.11853879,
       -0.04441617,  0.35628012, -0.04596721, -0.16670963,  0.24801672,
       -0.04361303,  0.15386932,  0.71625876, -0.2984459 ,  0.10743926,
       -0.74763495,  0.04910135,  0.07704992, -0.19340192, -0.06236093,
       -0.06851414,  0.97534084, -0.21388888,  0.23158512, -0.17681313,
       -0.45778516, -0.09304596, -1.033407  , -0.03471509,  0.04178332,
       -0.41759196, -0.2591747 , -0.21600883, -0.11675627, -0.45118746,
       -0.355847  , -0.2980828 , -0.17274342, -0.39866057, -0.6803514 ,
        0.261201  , -0.0885908 , -0.48599178, -0.30373666,  0.3484288 ,
       -0.40725964, -0.03213827, -0.28934184,  0.6338166 , -0.46295682,
        0.6014991 , -0.633564  , -0.7889887 , -0.22606796, -0.06742538,
       -0.25403836, -0.25614786, -0.02936402,  0.38002756,  0.1998092 ,
       -0.06956659, -0.11989106, -0.2322161 , -0.43020257,  0.21332748,
       -0.51301336,  0.20102343, -0.05035414,  0.06157589,  0.16432023,
       -0.3964954 , -0.03361718, -0.39000124, -0.2938633 ,  0.32039067,
        0.10993166, -0.61339146, -0.14831759, -0.15634735, -0.10374387,
       -0.0622427 ,  0.43706286, -0.66385746,  0.95179784,  0.09031942,
       -0.12106942,  0.84565973, -0.52066916, -0.18686084, -0.14365909,
       -0.3481733 , -0.56436604, -0.12578458, -0.21431924, -0.57500434,
        0.27233732,  0.0516257 ,  0.8108567 , -0.20308313,  0.43552834,
       -0.22604504,  0.6868176 , -0.26821885,  0.21114837, -0.350368  ,
        0.33354095,  0.14937903, -0.31610247, -0.46828258, -0.6185499 ,
        0.3807064 , -0.26519543, -0.4742942 , -0.3054631 ,  0.03259922,
        0.04713736, -0.26409838, -0.11442922,  0.26561075,  0.6694571 ,
       -0.67066824,  0.01207941, -0.05825622, -0.14529966, -0.59193075,
        0.07477141,  0.23290102,  0.51157457, -0.41868782,  0.24725069,
       -0.40500292, -0.3576436 ,  0.34778973, -0.06344458,  0.36267546,
        0.23134886,  0.09627197,  0.36146113, -0.5865031 , -0.6011491 ,
       -0.01175123, -0.06002957, -0.13570419, -0.4112324 , -0.6378906 ,
       -1.1531287 ,  0.14517766, -0.8826392 , -0.32124823,  0.13345265,
        0.17867129, -0.05916324, -0.24137773, -0.09881718, -0.19602697,
       -0.8358927 , -0.29721507,  0.0618385 ,  0.41871417, -0.2753052 ,
        0.1905219 , -0.32951748,  0.32791498, -0.5987249 ,  0.23432045,
       -0.36374718, -0.03941025,  0.18843259, -0.00236499,  0.58295894,
        0.00851598, -0.252738  ,  0.13625912,  0.42114246,  0.24603029,
       -0.6246986 ,  0.05799655, -0.35406858,  0.21295479,  0.10844132,
        0.16990007, -0.37538546,  0.65340036, -0.04360104,  0.21432678,
       -0.38744852, -0.536208  , -0.11386421, -0.25741723, -0.0317193 ,
        0.02928257, -0.4419606 ,  0.38133794,  0.7894594 , -0.54790217,
       -0.12533087,  0.25978526, -0.43776566,  0.06111563, -0.46378735,
       -0.44159582, -0.03624339,  0.89847505,  0.21955001, -0.02149784,
       -0.37836894,  0.69813544,  0.10012921,  0.05837746, -0.22997098,
       -0.42080247, -0.28540376, -0.12385881, -0.3292734 ,  0.41335502,
        0.15770173, -0.7071128 , -0.31346643,  0.335178  ,  0.12005486,
        0.19563176, -0.15797304,  0.49979457,  0.21619444, -1.062162  ,
        0.8655288 , -0.02320208, -0.51080227,  0.19052097, -0.81317246,
        0.35232687, -0.37825716, -0.04959468,  0.23429887,  0.68936056,
       -0.4713644 ,  0.44504425, -0.2574277 ,  0.746291  , -0.49212185,
        0.759858  , -0.1676745 , -0.10453261,  0.36182436, -0.07230397,
       -0.3349553 ,  0.01710661, -0.08768804, -0.21369837, -0.5782665 ,
        0.49015728,  0.38706464,  0.5871467 ,  0.02529717,  0.21090257,
       -0.0504095 ,  0.3154827 , -0.45794094,  0.45777282, -0.15671465,
        0.2471544 , -0.01796505, -0.36051035, -0.29341346, -0.5402933 ,
       -0.39123306,  0.57786936, -0.12492797, -0.23253398, -0.61035746,
       -0.23117776, -0.6441264 ,  0.22027731, -0.35762522,  0.04027409,
       -0.25130966, -0.5017039 ,  0.62750185,  0.26957273, -0.04101853,
       -0.29843494, -0.24256878, -0.69175464,  0.5385119 , -0.20995277,
        0.16678722, -0.536452  ,  0.5627849 ,  0.3585047 , -0.4246467 ,
       -0.06826093,  0.7874554 ,  0.25342673, -0.62232226,  0.00231391,
        0.26290953,  0.4740899 , -0.23745601,  0.44881296, -0.3887292 ,
       -0.5210774 , -0.22442101,  0.0717428 , -0.5646417 , -0.7097249 ,
        0.35830796,  0.5667791 , -0.11477572,  0.27185398,  0.01270259,
        0.0966281 ,  0.6215624 ,  0.3908529 , -0.8781478 , -0.04724635,
        0.42562938,  0.4726475 , -0.08884306,  0.40444353, -0.26259238,
        0.12002273, -0.01368636,  0.05998314,  0.2407404 , -0.08160132,
        1.1807708 ,  0.01982552, -0.43555307, -0.13451476,  0.05839595,
       -0.14896101, -0.07467191, -0.37720525,  0.2859367 , -0.26472342,
        0.07250424, -0.66670126, -0.5522846 , -0.5150698 ,  0.26346943,
        0.05588347,  0.2681058 ,  0.44256768,  0.34921888,  0.0887327 ,
       -0.32451496,  0.5043753 ,  0.15573964, -0.80099905, -0.07187647,
       -0.19249184,  0.06359226, -0.54383236,  0.09976155,  0.00230035,
       -0.56726056,  0.70454514,  0.00985345,  0.22178166, -0.28542963,
        0.12045177,  0.1783691 , -0.3533394 ,  0.2986715 ,  0.24798846,
       -0.45357108, -0.39325854,  0.3827145 , -0.93977726, -0.732362  ,
       -0.3411574 , -0.27170214,  0.770694  , -0.7912134 ,  0.11824147,
       -0.21676573, -0.30183613, -0.02420801, -0.09807873, -0.74977636,
        0.2389753 ,  0.01807426,  0.38739562, -0.24847944, -0.4728537 ,
        0.187837  ,  0.42438817, -0.17245103,  0.1265015 , -0.5074485 ,
       -0.1458759 , -0.08727793,  0.3616617 , -0.341906  , -0.56732327,
        0.3724803 ,  0.0565774 , -0.09706279, -0.12275453, -0.7346416 ,
       -0.42028046,  0.43527544,  0.10911696,  0.1587813 , -0.02169908,
       -0.12557712,  0.6653311 ,  0.71039826, -0.4736449 ,  0.4194687 ,
        0.30210197,  0.39302948,  0.02763417,  0.17749245,  0.47280273,
        0.44654128, -0.48628452,  0.76533234, -0.23366964,  0.02098861,
       -0.06142372,  0.73869646,  0.68950486, -0.67334574,  0.3279801 ,
        0.73780036, -0.585862  ,  0.2989271 , -0.00862416, -0.38703543,
       -0.24835141,  0.13880756, -0.6353122 , -0.4240959 ,  0.6655618 ,
        0.7852061 , -0.025455  , -0.02771753,  0.07122368, -0.17186368,
       -0.19998112, -1.001073  ,  0.01613791, -0.08112212,  0.0934215 ,
       -0.7902824 ,  0.17575629, -0.5897043 ,  0.6806952 ,  0.46178463,
       -0.41006917,  0.14588894,  0.3679672 , -0.4470852 , -0.59222806,
        0.23789145,  0.10921062, -0.22461045,  0.37211767, -0.09105125,
       -0.48342744,  0.07300626,  0.14150418, -0.17180184,  0.23384994,
        0.1625362 , -0.08545914, -0.02740425,  0.49644524, -0.22282714,
       -0.06850461, -0.20254616, -0.22002658, -0.23085953, -0.41658896,
        0.56211424,  0.66946894, -0.34276554, -0.4217928 ,  0.66748315,
        0.21044278,  0.01556514, -0.9758183 , -0.07461734, -0.4815224 ,
       -0.5413386 ,  0.32487148, -0.21451017, -0.3780384 , -0.3237602 ,
        0.10802944,  0.2412706 , -0.47800186, -0.16226153,  0.00937711,
        0.5525045 , -1.1156493 ], dtype=float32), array([0.3408612 , 0.5205964 , 0.3161186 , 0.44744688, 0.53128535,
       0.481368  , 0.55187505, 1.0667472 , 0.3779953 , 0.7142477 ,
       0.48122865, 0.3612357 , 0.56187207, 0.61697567, 0.29299498,
       0.50198394, 0.4231449 , 0.33517018, 0.30015957, 0.48891413,
       0.41749775, 0.3422736 , 0.4102845 , 0.29410273, 0.36732498,
       0.5643533 , 0.5232274 , 0.4177317 , 0.40969795, 0.35564306,
       0.8501155 , 0.46543884, 0.6188032 , 0.38475195, 0.37561604,
       0.65194845, 0.6568407 , 0.57965386, 0.4050062 , 0.48222926,
       0.45604342, 0.45828474, 0.4636695 , 0.3416095 , 0.72223496,
       0.40263316, 0.71068114, 0.5680858 , 0.6675191 , 0.49163124,
       0.3925231 , 0.4959014 , 0.45199364, 0.5218839 , 0.36115435,
       0.3673861 , 0.568854  , 0.28261018, 0.5039231 , 0.5269    ,
       0.5295739 , 0.47589785, 0.5433989 , 0.38303113, 0.3100067 ,
       0.7652273 , 0.7066907 , 0.9318011 , 0.45381364, 0.42678598,
       0.3580969 , 0.45073047, 0.36368954, 0.43039778, 0.4365903 ,
       0.36524287, 0.52688235, 0.553697  , 0.28849828, 0.37647352,
       0.5968946 , 0.3756224 , 0.34210494, 0.4066499 , 0.4326194 ,
       0.29889643, 0.5494169 , 0.5720428 , 0.46652564, 0.27346846,
       0.787344  , 0.66662043, 0.3803418 , 0.62166905, 0.4017184 ,
       0.62894315, 0.3101363 , 0.3291339 , 0.52601933, 0.46240488,
       0.6165393 , 0.529435  , 0.34073803, 0.38067287, 0.61323243,
       0.34338856, 0.55001307, 0.40449393, 0.3270804 , 0.5038524 ,
       0.5323198 , 0.30320108, 0.41302893, 0.5431158 , 0.64868426,
       0.43006593, 0.66766864, 0.59166944, 0.639366  , 0.3678447 ,
       0.588889  , 0.75332963, 0.50063413, 0.4068771 , 0.63222694,
       0.3813621 , 0.36659992, 0.93558913, 0.49640298, 0.35893375,
       0.28041136, 0.3909495 , 0.31483918, 0.33292773, 0.6975069 ,
       0.7666691 , 0.3162859 , 0.32872054, 0.42616913, 0.39275837,
       0.49991462, 0.32489163, 0.8845499 , 0.65651226, 0.44285932,
       0.7014854 , 0.53114074, 0.48797318, 0.3144679 , 0.44282144,
       0.35579506, 0.7702392 , 0.46658534, 0.89774865, 0.5434733 ,
       0.42293835, 0.40985698, 0.6397126 , 0.5490403 , 0.44915956,
       0.5121432 , 0.4222217 , 0.5479245 , 0.29133597, 0.3438052 ,
       0.41197422, 0.4444838 , 0.4143399 , 0.376781  , 0.7031942 ,
       0.7789523 , 0.41420946, 0.3134654 , 0.40654838, 0.53080755,
       0.43679303, 0.42723626, 0.6308164 , 0.32303113, 0.35029233,
       0.68311954, 0.4590602 , 0.39607438, 0.56749517, 0.60009766,
       0.40068522, 0.43441287, 0.3167162 , 0.5059152 , 0.48289534,
       0.38623118, 0.51079524, 0.44330812, 0.38720775, 0.5910973 ,
       0.57864743, 0.609904  , 0.6023889 , 0.5081678 , 0.5431427 ,
       0.80029386, 0.43626222, 0.4024803 , 0.6264225 , 0.33088547,
       0.56790787, 0.574961  , 0.35111752, 0.7435167 , 0.54895   ,
       0.4287458 , 0.387722  , 0.43581405, 0.45312038, 0.43722072,
       0.25210416, 0.21899986, 0.55286926, 0.49929392, 0.4073319 ,
       0.66565853, 0.78289336, 0.2863001 , 0.54565144, 0.2859511 ,
       0.82712996, 0.4908033 , 0.4618679 , 0.6176733 , 0.58086216,
       0.51009756, 0.43261555, 0.44978893, 0.24519181, 0.37460852,
       0.59887415, 0.42018765, 0.41882235, 0.48828477, 0.62162596,
       0.71242857, 0.45132178, 0.39923242, 0.3527901 , 0.35090628,
       0.44461846, 0.7779601 , 0.3385866 , 0.48808393, 0.52220213,
       0.85307294, 0.5540474 , 0.6087005 , 0.79389995, 0.54557115,
       0.7332742 , 0.3690523 , 0.4583285 , 0.2969044 , 0.24804719,
       0.47289106, 0.32556358, 0.42522106, 0.30079442, 0.55002874,
       0.3638506 , 0.62842387, 0.42507327, 0.3021654 , 0.3237367 ,
       0.31918025, 0.27101114, 0.39303067, 0.7086969 , 0.32491684,
       0.39482155, 0.3369749 , 0.3791157 , 0.3445548 , 0.44246617,
       1.0634935 , 0.35928077, 0.32327652, 1.1532013 , 0.51023453,
       0.3722314 , 0.52699137, 0.53540576, 0.51815945, 0.30339035,
       0.49564803, 0.46562335, 1.067731  , 0.37055212, 0.37085634,
       0.36646613, 0.44752845, 0.37801573, 0.714913  , 0.47084236,
       0.5138654 , 0.58053696, 0.5995888 , 0.56044745, 0.63800496,
       0.4357976 , 0.8087618 , 0.41578937, 0.3770151 , 0.33888865,
       0.9596122 , 0.2745886 , 0.32402572, 0.35778874, 0.5149427 ,
       0.3499564 , 0.28443238, 0.3415806 , 0.63353544, 0.36892545,
       0.39941195, 0.64256305, 0.3118246 , 0.6930282 , 0.45675027,
       0.36271644, 0.47165015, 0.41974777, 0.3858927 , 0.31901443,
       0.291347  , 0.8164113 , 0.38540155, 0.40796688, 0.36121586,
       0.5701749 , 0.46949768, 0.5605784 , 0.3933767 , 0.33107415,
       0.5922087 , 0.47386354, 0.33128244, 0.3007242 , 0.31275517,
       0.32348427, 0.43744168, 0.5818771 , 0.8433523 , 0.3590063 ,
       0.57422006, 0.4759337 , 0.4959793 , 0.8115873 , 0.6461427 ,
       0.32267067, 0.76412773, 0.44620338, 0.34399682, 0.613477  ,
       0.584535  , 0.5676806 , 0.28987753, 0.44008306, 0.5104932 ,
       0.54573303, 0.48047572, 0.47182554, 0.71058416, 0.52326477,
       0.36963558, 0.8013192 , 0.68489933, 0.35107318, 0.5197697 ,
       0.48205164, 0.4282345 , 0.5571762 , 0.29603368, 0.45611793,
       0.4460299 , 0.453534  , 0.53357005, 0.38777152, 0.38087198,
       0.4174376 , 0.6417559 , 0.38435137, 0.58548856, 0.36519775,
       0.33958298, 0.39107448, 0.8615119 , 0.3966705 , 0.3302868 ,
       0.2885178 , 0.34189472, 0.4650127 , 0.39865196, 0.46021795,
       0.6289656 , 0.59420866, 0.510752  , 0.25083268, 0.64839387,
       0.31796205, 0.2973634 , 0.5632251 , 0.47411355, 0.5840773 ,
       0.34923813, 0.37786835, 0.5060279 , 0.4489876 , 0.42206088,
       0.46572742, 0.42082134, 0.39286354, 0.4660723 , 0.3941416 ,
       0.4027918 , 0.5029467 , 0.48296177, 0.39405578, 0.42348868,
       0.4893433 , 0.7653243 , 0.36050442, 0.49918157, 0.751572  ,
       0.50966495, 0.83732206, 0.40795553, 0.45333302, 0.38232103,
       0.26009142, 0.39242196, 0.32921204, 0.40966365, 0.59913856,
       0.85177344, 0.33705518, 0.31813484, 0.41000453, 0.37861887,
       0.567353  , 0.39138183, 0.44540432, 0.37538463, 0.65770954,
       0.5570111 , 0.41053766, 0.3814718 , 0.4621013 , 0.59928423,
       0.4281551 , 0.4078442 , 0.35546306, 0.5875606 , 0.56311995,
       0.67827   , 0.3974501 , 0.7587316 , 0.46346208, 0.6470494 ,
       1.5352434 , 0.48978508, 0.3960394 , 0.5306607 , 0.42159566,
       0.3293731 , 0.62581426, 0.3352225 , 0.22798023, 0.32606494,
       0.47340783, 0.35808927, 0.52896017, 0.33300766, 0.41908726,
       0.380275  , 0.2947082 , 0.45780236, 0.51243556, 0.9742716 ,
       0.3117524 , 0.39454883, 0.3554343 , 0.38427207, 0.52314895,
       0.38058323, 0.6825263 , 0.76002413, 0.27984202, 0.84860426,
       0.7592692 , 0.49483725, 0.6243305 , 0.33035472, 0.3055346 ,
       0.30004445, 0.38587198, 0.4939792 , 0.34329313, 0.2917114 ,
       0.42866892, 0.31055394, 0.42315763, 0.5717893 , 0.5295944 ,
       0.8254322 , 0.62598014], dtype=float32), array([[[[ 0.03385554],
         [ 0.01583535],
         [-0.00188353],
         ...,
         [-0.02299683],
         [ 0.0294988 ],
         [ 0.00860954]],

        [[-0.05693815],
         [-0.03061146],
         [ 0.02611884],
         ...,
         [ 0.02659125],
         [-0.03926934],
         [ 0.01568156]],

        [[-0.01443282],
         [-0.01120623],
         [ 0.0163763 ],
         ...,
         [-0.02952187],
         [ 0.02243192],
         [ 0.03799804]]],


       [[[-0.04436369],
         [ 0.04032138],
         [ 0.02460959],
         ...,
         [ 0.00118495],
         [ 0.02025993],
         [-0.0191223 ]],

        [[-0.01747308],
         [ 0.02514945],
         [ 0.00312983],
         ...,
         [ 0.01943739],
         [-0.00448671],
         [ 0.00010307]],

        [[ 0.01925807],
         [ 0.00537938],
         [-0.0316653 ],
         ...,
         [ 0.00811825],
         [ 0.02416994],
         [-0.04291481]]],


       [[[ 0.00221146],
         [-0.03424863],
         [-0.04772343],
         ...,
         [-0.02887578],
         [ 0.02269247],
         [-0.05427265]],

        [[ 0.00316556],
         [-0.00819002],
         [ 0.03887615],
         ...,
         [-0.00720873],
         [ 0.00614111],
         [-0.01047502]],

        [[-0.00599989],
         [ 0.04150064],
         [ 0.00121161],
         ...,
         [-0.05697148],
         [ 0.02191809],
         [-0.03542843]]]], dtype=float32), array([1.0011301 , 1.009698  , 0.9637905 , 0.9479184 , 1.0041211 ,
       0.9736754 , 1.0047038 , 1.0096644 , 1.0131205 , 1.0066471 ,
       1.0073228 , 1.0073814 , 1.0048876 , 1.01919   , 1.0097278 ,
       0.96349424, 1.0061659 , 1.0265272 , 0.99753016, 0.9814674 ,
       0.9957494 , 1.0250217 , 0.9774757 , 0.97996646, 0.96603966,
       1.0322459 , 0.99434614, 0.9921004 , 0.9918142 , 1.0136186 ,
       1.0157927 , 1.0055736 , 1.0074936 , 1.0210809 , 1.009547  ,
       0.95519567, 1.011307  , 1.0016401 , 0.9826674 , 0.9805799 ,
       1.0418401 , 0.99698466, 1.0349127 , 1.0038412 , 0.99392194,
       0.97793144, 0.99505144, 0.9664945 , 1.0106    , 1.0271053 ,
       1.0205278 , 1.0024151 , 0.9952485 , 0.9750492 , 1.0051379 ,
       1.0316979 , 0.9917951 , 1.007153  , 1.0111933 , 0.9923131 ,
       0.9807405 , 0.99269634, 1.0283539 , 1.0159366 , 1.0033166 ,
       1.0030762 , 1.003939  , 1.011786  , 0.9807887 , 1.0187787 ,
       1.0259889 , 0.99811375, 1.0194381 , 0.98909914, 0.9862427 ,
       0.9640905 , 1.011488  , 0.97698665, 1.0209044 , 1.0533695 ,
       0.9796639 , 0.99516857, 0.97638935, 1.0102348 , 0.97115785,
       0.98208374, 1.009856  , 1.0053455 , 0.9813916 , 1.0160134 ,
       1.000684  , 1.0312649 , 0.971317  , 0.9968145 , 1.0086586 ,
       1.0138003 , 1.0394619 , 1.0134904 , 0.98083615, 0.97953004,
       1.0592679 , 1.0009595 , 1.0013803 , 1.0166284 , 1.0084355 ,
       1.0152911 , 0.98045915, 0.99417853, 1.0069413 , 1.0206033 ,
       0.9914482 , 1.0202812 , 1.0120059 , 1.0140597 , 0.9832442 ,
       1.0214325 , 1.0346161 , 1.0070894 , 1.0204086 , 1.034533  ,
       0.98055005, 0.9750158 , 0.99880934, 1.0593935 , 0.99539167,
       0.97557163, 0.9899651 , 0.96421534, 0.9858255 , 1.0277429 ,
       0.9874207 , 1.0144016 , 1.006757  , 0.98308104, 1.0011853 ,
       0.9905006 , 0.9983396 , 1.0054904 , 1.0210989 , 0.9980108 ,
       0.987831  , 0.9998792 , 0.9672083 , 1.0153972 , 0.9874602 ,
       1.0242825 , 1.0080031 , 0.9905449 , 1.0218965 , 0.99162734,
       0.9989213 , 1.0076249 , 0.99684906, 0.9959496 , 0.99212545,
       1.0381403 , 0.98989785, 0.99176717, 0.9623188 , 1.0173453 ,
       0.991509  , 0.9988189 , 1.0092711 , 1.0077497 , 1.01029   ,
       0.9664744 , 1.0071305 , 0.95184666, 0.99926746, 1.035803  ,
       0.9980025 , 0.965014  , 0.9896055 , 0.99395955, 1.0179598 ,
       0.9840133 , 1.0345093 , 1.0047756 , 1.0374097 , 1.0135492 ,
       0.9846859 , 0.99663806, 0.99296886, 1.0176635 , 0.9842468 ,
       0.9958494 , 1.0130047 , 1.0008694 , 0.99689186, 0.9762933 ,
       1.0156463 , 1.0126717 , 1.0263437 , 0.99900144, 0.99781525,
       1.0279489 , 1.0033095 , 1.0053662 , 1.0020764 , 0.98248523,
       0.9846526 , 0.9893164 , 0.98387194, 1.0287831 , 0.9908732 ,
       0.9474101 , 1.0285193 , 1.046309  , 0.9990302 , 1.0016521 ,
       1.0135372 , 1.0141655 , 0.9833678 , 1.0300201 , 1.0340828 ,
       0.9894043 , 1.010903  , 0.97730666, 1.0042585 , 1.0185606 ,
       1.0040463 , 0.98581696, 1.0170907 , 0.9929543 , 1.035601  ,
       0.98095626, 1.0073644 , 1.0126079 , 0.97589856, 0.9826879 ,
       1.0208771 , 1.0080193 , 0.98832273, 1.0729069 , 1.0183537 ,
       0.98060113, 0.9841556 , 0.9717127 , 0.97829837, 0.98727137,
       0.98233396, 1.0031401 , 1.0081304 , 1.0377647 , 0.98407525,
       1.0018305 , 1.0173852 , 0.9736659 , 1.0374708 , 0.98752993,
       0.9886509 , 1.0030178 , 0.99514014, 0.9953957 , 0.9752053 ,
       0.96794605, 0.99834514, 0.9727893 , 1.0055788 , 0.98156375,
       0.9942559 , 1.0242507 , 0.9882757 , 0.999064  , 0.991241  ,
       0.99856967, 1.0086608 , 0.99879974, 1.0121632 , 0.990175  ,
       1.0120224 , 1.0027572 , 1.0153854 , 0.98534995, 1.0392305 ,
       1.007209  , 1.0071127 , 1.009899  , 0.9868682 , 1.0071464 ,
       0.9649877 , 1.0110466 , 0.9997082 , 1.0374646 , 0.9850265 ,
       1.02968   , 0.98001206, 1.0121088 , 1.008114  , 1.0198383 ,
       1.006772  , 1.0069371 , 1.016826  , 1.0195912 , 0.9978593 ,
       1.0184213 , 1.0579035 , 1.0182557 , 1.0083866 , 1.0243381 ,
       1.0094    , 1.0151314 , 1.0197976 , 1.0076988 , 0.9711434 ,
       0.99863315, 1.0384212 , 0.98364294, 1.0317605 , 1.0122527 ,
       1.013997  , 1.0326666 , 0.9998847 , 0.9775699 , 1.0248121 ,
       1.0094317 , 1.0387415 , 1.0699813 , 1.0441995 , 1.0322859 ,
       0.9854515 , 0.9962824 , 1.0227251 , 0.99201745, 1.0318731 ,
       1.0164741 , 0.99738187, 0.98413026, 0.98605436, 0.9920362 ,
       0.9912657 , 1.0260628 , 1.0458148 , 0.99242425, 1.0226287 ,
       0.99970293, 1.0084863 , 0.9958465 , 1.0052907 , 0.99468595,
       0.9812886 , 1.0015308 , 1.0194011 , 0.9734343 , 1.0113912 ,
       1.0162119 , 0.9496788 , 0.98953915, 0.99793637, 0.9656154 ,
       0.9982343 , 0.9740368 , 0.97520065, 1.0075763 , 1.03366   ,
       1.0315803 , 0.9799547 , 1.0282774 , 1.0163056 , 1.0046517 ,
       1.0276195 , 0.9861006 , 0.97999   , 0.9951852 , 1.0250012 ,
       0.97171533, 1.0078063 , 1.0640597 , 1.0033265 , 0.99068344,
       0.96211255, 1.0037644 , 1.002265  , 0.97149867, 1.0022341 ,
       1.0017595 , 1.0022529 , 0.9937127 , 0.9643068 , 1.0132545 ,
       0.9933037 , 0.9875816 , 0.9761397 , 0.9907946 , 0.9803031 ,
       0.98359567, 0.99426764, 1.0031414 , 1.0316789 , 1.0168169 ,
       1.0123523 , 1.0160843 , 1.0245374 , 0.9951927 , 1.0118507 ,
       1.0291731 , 0.99018764, 0.976311  , 0.9987595 , 0.9917744 ,
       0.995731  , 1.0148475 , 1.0164206 , 0.99408066, 0.98076296,
       1.0223196 , 0.99260736, 0.99846745, 0.9849311 , 0.98739946,
       1.0016531 , 1.0250804 , 1.01888   , 1.0125458 , 0.9753893 ,
       0.9704508 , 0.9876227 , 1.0062194 , 1.0193876 , 0.99746406,
       1.0082403 , 0.97373587, 0.99048305, 0.97491574, 0.97420686,
       0.98440063, 0.99560106, 0.9935654 , 0.97754085, 1.0256017 ,
       0.98639137, 0.99790084, 0.9798651 , 1.0125202 , 1.011891  ,
       0.9743968 , 0.97679174, 0.9691718 , 1.0288433 , 0.98461825,
       0.96088594, 1.0306792 , 1.0025496 , 0.9932657 , 1.0117017 ,
       0.99725467, 1.0379617 , 0.9771618 , 0.99011797, 0.97807   ,
       0.98077315, 0.9710441 , 1.0207422 , 0.99322903, 0.9960959 ,
       0.9976853 , 1.0097187 , 1.0270262 , 0.9843099 , 0.9694523 ,
       0.97925633, 1.0031993 , 0.9823355 , 0.9889623 , 1.0121174 ,
       0.97409105, 0.98148453, 0.99584645, 1.0309986 , 0.99080473,
       1.0008036 , 0.9904178 , 1.0221577 , 1.0369946 , 1.0167282 ,
       1.025269  , 0.99293524, 0.9797266 , 1.0040559 , 1.0016487 ,
       0.99781835, 0.9722141 , 1.0051146 , 1.0062544 , 0.9931923 ,
       1.021579  , 0.9870885 , 1.020535  , 1.0082337 , 1.0003778 ,
       1.0142924 , 0.9816988 , 0.9955125 , 0.96768206, 1.0097754 ,
       0.95955145, 1.0343565 , 1.0022004 , 0.9845848 , 1.0185565 ,
       1.0056716 , 1.0124959 , 1.0257345 , 0.9623252 , 0.9787034 ,
       0.9679733 , 1.0059237 , 0.98305774, 1.0052344 , 0.9879066 ,
       0.9864244 , 0.9966076 ], dtype=float32), array([-7.62011670e-03,  4.02744859e-02, -2.78794635e-02, -4.56566811e-02,
        1.65902711e-02, -4.21033949e-02, -2.77432892e-03, -1.00447054e-04,
        5.33218728e-03, -2.64908299e-02,  2.88008004e-02,  3.75602115e-03,
        1.83478813e-03,  1.40920179e-02, -6.75918860e-03, -2.49245670e-02,
        3.98111559e-04, -3.38416721e-04,  1.65256369e-03, -1.88967921e-02,
       -2.28756778e-02,  1.54447891e-02, -2.81627700e-02, -2.21071858e-02,
       -7.82635622e-03, -2.08506454e-02, -1.47669809e-02, -1.26439310e-03,
        1.59583185e-02,  2.12548450e-02,  2.36223545e-02, -1.41069600e-02,
        4.28463928e-02,  1.42254196e-02,  1.40386643e-02, -3.72451022e-02,
       -2.00046673e-02, -1.97915975e-02,  9.39245615e-03, -1.96828926e-03,
        2.33217534e-02, -1.70775468e-03,  2.10590530e-02,  9.24802758e-03,
        2.95139151e-04,  1.05880043e-02,  8.71101627e-04, -8.90802685e-03,
        6.29218761e-03,  1.21915340e-02,  1.22772455e-02,  1.51616288e-02,
       -3.59897166e-02, -2.92658880e-02, -3.31191011e-02,  4.18540612e-02,
       -4.78349440e-03,  1.02675492e-02,  1.68098323e-02, -1.06591200e-02,
       -1.60937775e-02, -2.63142399e-03,  3.64987850e-02,  8.35330319e-03,
       -1.17301000e-02, -2.97359470e-02, -8.88242200e-03,  1.32849356e-02,
       -3.06588179e-03,  3.58120613e-02,  4.28043585e-03,  1.17582316e-02,
        4.71740663e-02, -1.63005330e-02,  2.10158024e-02, -3.91246825e-02,
       -3.74434912e-03,  6.55695377e-03,  1.62031911e-02,  3.71315442e-02,
       -3.76375280e-02, -2.59754626e-04, -1.11836037e-02, -2.19063764e-03,
       -7.73689942e-03, -2.03953870e-02,  1.59929991e-02,  1.05842343e-02,
       -1.82552654e-02,  1.30527914e-02,  2.21857801e-02,  2.76597366e-02,
       -4.10862938e-02,  7.06836639e-04,  2.48180646e-02,  1.07518416e-02,
        2.56810915e-02,  6.10667281e-04, -2.10335087e-02, -2.59709023e-02,
        2.96275225e-02, -7.71258818e-03, -7.57033518e-03,  8.71371198e-03,
       -7.08022155e-03,  2.23539937e-02, -6.65447209e-03, -1.22828782e-02,
       -2.67503061e-03,  2.64201425e-02, -4.62911185e-03,  2.96958573e-02,
        8.91935313e-04, -2.70282663e-03, -3.15541811e-02,  2.13082656e-02,
        4.03268300e-02, -6.63929945e-03,  2.60841008e-02,  2.88488045e-02,
       -1.95054598e-02, -2.77454406e-02, -1.21084293e-02,  2.13437509e-02,
        1.81313530e-02, -1.50906593e-02, -6.30799448e-03, -3.04896384e-02,
       -1.97148393e-03,  3.18719447e-02, -7.06063677e-03,  1.90736577e-02,
       -6.92626275e-03, -1.64446365e-02, -1.56478044e-02, -9.02960950e-04,
        7.79625447e-03, -1.96903595e-03,  8.60498985e-04, -3.43820341e-02,
       -1.33280447e-02,  1.54445330e-02,  3.31452186e-03,  1.01453345e-02,
       -1.10858800e-02,  5.71120828e-02,  9.67794750e-03, -2.90374625e-02,
       -1.77283981e-03,  1.50616067e-02,  1.04931975e-03,  8.97934381e-03,
        4.09420133e-02, -2.50417553e-02,  9.04241670e-03,  3.04284431e-02,
       -2.57044565e-03,  4.76452569e-03, -2.46269722e-02, -2.31070854e-02,
       -1.93758830e-02,  8.81802000e-04,  4.78115231e-02,  1.46646732e-02,
       -6.20842911e-03, -8.13777465e-03,  4.77646850e-03, -3.97086218e-02,
        3.60506997e-02,  2.67363396e-02,  2.91435979e-02, -2.89603528e-02,
        2.05730479e-02,  4.78580734e-03,  4.46616113e-03,  5.21338952e-04,
        1.75234415e-02,  1.61455236e-02,  1.35498131e-02,  1.17044114e-02,
       -2.96844542e-02, -8.98563862e-03, -3.29436213e-02, -7.92801753e-03,
       -1.39721967e-02,  3.10536176e-02,  1.18261259e-02, -2.92974617e-03,
       -1.32603571e-02,  6.37391629e-03,  1.32529009e-02, -4.64843959e-03,
        2.48587765e-02,  1.88348759e-02, -2.83717699e-02, -1.54651683e-02,
        7.84048997e-03,  1.32324873e-02,  2.10670307e-02,  1.04802439e-03,
       -6.13958994e-03, -1.45988772e-04, -1.50760552e-02,  7.46464415e-04,
       -1.77465391e-03, -4.91292067e-02,  1.49742756e-02, -2.56848382e-03,
       -2.33073011e-02,  1.88397951e-02,  3.04716709e-03,  2.28130501e-02,
       -1.10178478e-02,  3.04382760e-04,  1.68687273e-02, -3.62447686e-02,
        1.84726517e-03,  6.03315537e-04,  6.37926720e-03,  2.17666700e-02,
       -1.42605100e-02, -3.74357169e-03,  1.94994509e-02, -8.66848568e-04,
        1.42206615e-02, -1.39109399e-02, -5.74908126e-03, -4.27883817e-03,
       -2.25737388e-03, -5.23390947e-03,  2.37862561e-02,  2.74592377e-02,
        1.45437254e-03,  5.38320802e-02, -1.18756779e-02, -1.49135496e-02,
       -1.11119747e-02, -8.60855915e-03, -1.66641157e-02, -1.73531286e-02,
        4.22274554e-03, -4.07929951e-03, -2.67042848e-03,  3.81629728e-02,
       -2.60975901e-02, -2.79636210e-04,  2.23602727e-03, -5.22818416e-03,
        3.67551260e-02, -2.77693365e-02,  1.07780537e-02,  1.59160849e-02,
        5.31190773e-04, -1.08544957e-02, -1.81688536e-02, -1.50172152e-02,
       -6.17704773e-03, -1.45460423e-02, -4.86490084e-03, -1.52363991e-02,
       -2.24422943e-02,  4.04542219e-03, -1.47168189e-02,  1.17715551e-02,
       -2.22290028e-02, -7.03376625e-03, -2.23032907e-02,  1.57900192e-02,
        9.49526206e-03, -2.98528671e-02,  3.81724909e-03, -6.83446089e-03,
        2.20634360e-02, -2.08559595e-02,  1.16979554e-02,  7.45480042e-03,
        6.38803840e-03,  1.46763455e-02,  5.06465649e-03,  2.27905028e-02,
       -4.38790470e-02,  9.22856946e-03,  1.32875619e-02,  3.88706103e-02,
       -1.54559175e-02,  2.24593244e-02,  1.34996139e-03, -9.76570975e-03,
       -9.20516718e-03,  3.07624992e-02, -2.49448773e-02,  4.13721753e-03,
        6.72395527e-03,  1.35512212e-02,  1.24795251e-02,  3.15836049e-03,
        4.15731408e-02,  5.19131916e-03,  7.23767653e-03, -1.28176820e-03,
        2.38457491e-04,  2.84473915e-02, -2.30619162e-02, -1.16833644e-02,
       -4.55353893e-02, -2.80155800e-02,  1.48300314e-02, -2.63854340e-02,
        3.13721336e-02, -1.12899893e-03,  1.26709640e-02,  3.64443250e-02,
       -1.58502182e-04, -1.42831253e-02,  3.42640504e-02, -3.15467757e-03,
        2.75136828e-02,  4.20129597e-02,  2.94617694e-02, -9.41407634e-04,
       -1.26285562e-02, -1.86735671e-02,  2.30479464e-02, -1.48730353e-02,
        4.14428227e-02,  9.43965651e-03, -2.22634990e-03, -1.71872191e-02,
       -1.67285569e-03, -1.03821233e-02, -7.88675994e-03,  8.86747800e-03,
        1.69594828e-02, -1.23321442e-02,  1.42161483e-02, -1.43823298e-02,
       -4.40174527e-03,  3.12093571e-02, -2.24565268e-02,  1.60137042e-02,
       -4.19084430e-02,  1.68150961e-02,  6.53942535e-03, -4.27686349e-02,
        3.21094841e-02,  3.26509029e-02, -3.58810499e-02,  2.62282137e-02,
       -1.11103114e-02, -1.26158781e-02,  1.41572570e-02, -3.20929103e-02,
       -1.45019619e-02,  1.67138036e-02,  2.48192176e-02,  1.70207899e-02,
        4.99405491e-04,  3.15397903e-02, -3.20963026e-03, -1.29546793e-02,
        2.32144333e-02, -1.53337298e-02, -2.71648355e-03, -7.12979306e-03,
        4.27653035e-03, -5.23960683e-03,  7.00024888e-03,  1.04628513e-02,
        5.50258765e-03,  4.44501126e-03, -1.75232198e-02,  1.90072600e-03,
        1.49705419e-02, -2.19562929e-03, -2.31335917e-03, -2.72206427e-03,
       -1.36404224e-02, -1.35007109e-02, -3.07176877e-02, -1.60609577e-02,
       -7.64794694e-03,  1.91508848e-02, -2.64899097e-02, -1.91178676e-02,
        1.05009014e-02,  1.17580127e-02, -9.47633386e-03,  1.00063970e-02,
        2.26395726e-02,  4.34655063e-02, -1.64140516e-03,  4.09674903e-05,
       -7.41917826e-03,  1.39087802e-02,  3.93787548e-02,  2.77397372e-02,
       -6.76897028e-03, -3.20349820e-02,  1.06046500e-03, -6.35448610e-03,
       -2.48835771e-03,  1.22618526e-02,  2.24649850e-02, -1.39789116e-02,
       -2.62093730e-02, -1.18301797e-03, -1.30133349e-02, -1.14350067e-02,
       -1.68439606e-03, -2.53008846e-02, -2.15379093e-02,  1.14128366e-02,
        1.85084511e-02,  6.86763972e-03, -3.99924181e-02, -1.45130847e-02,
       -5.44571271e-03,  4.68376838e-03,  1.95813924e-02,  1.70191303e-02,
        1.99442431e-02, -2.03435197e-02, -1.62380412e-02, -2.40413416e-02,
       -1.00346468e-02, -1.11657586e-02, -6.34005805e-03, -2.71019083e-03,
       -2.90916655e-02,  9.52659640e-04, -2.91439556e-02,  1.87498517e-02,
       -2.64728423e-02, -8.41942523e-03, -5.35499258e-03, -3.83031368e-02,
       -2.96403258e-03, -2.23974530e-02,  2.03981493e-02, -1.64589714e-02,
       -4.78035025e-02,  1.34023810e-02, -1.21512115e-02, -1.96289271e-03,
       -3.22925020e-03, -2.41793552e-03,  4.03545564e-03, -3.27022113e-02,
       -1.65886804e-02, -2.38486417e-02, -2.04456467e-02, -2.40571331e-02,
       -1.41984166e-03,  5.41052967e-03, -1.21421516e-02,  2.51048729e-02,
        1.83711536e-02,  8.02936126e-03, -2.11883765e-02, -7.67922960e-03,
        3.30698001e-03,  1.00670080e-03, -1.19725848e-02,  3.79993604e-03,
       -2.35771965e-02, -2.25987658e-02, -1.14066424e-02, -2.26622950e-02,
        2.97136363e-02,  1.54609908e-03,  7.47741852e-03,  6.97476324e-03,
        2.36579366e-02,  3.87648977e-02, -3.65781342e-03,  2.90600695e-02,
        2.15526968e-02, -5.79099217e-03,  1.36958510e-02,  6.87015848e-03,
       -1.20099764e-02,  2.10937439e-03, -5.68186166e-03, -3.29126343e-02,
        2.09356826e-02,  1.46929231e-02,  9.96474084e-03,  1.96112152e-02,
       -1.18334219e-02,  9.93737392e-03,  3.84122855e-03,  3.53450235e-03,
        8.59503169e-03, -4.10868563e-02, -1.68139804e-02, -9.10804141e-03,
       -1.57239998e-03,  2.88864747e-02, -2.20622532e-02,  4.45759710e-04,
        8.93616583e-03,  1.57405194e-02,  3.00029642e-03, -4.22386155e-02,
       -3.43203433e-02, -2.59173885e-02,  7.20118266e-03, -2.36751814e-03,
        3.56354378e-03, -1.65252760e-02, -8.19807220e-03, -8.56306031e-03],
      dtype=float32), array([-2.65433155e-02,  1.85639821e-02,  2.35731062e-02, -1.82976238e-02,
        1.07232882e-02,  7.49571715e-03, -1.32318418e-02,  3.89927663e-02,
        1.50553575e-02,  2.43144706e-02, -2.97867730e-02, -1.93359945e-02,
       -1.39030591e-02,  2.38903984e-02, -2.64384244e-02, -2.36345152e-03,
        2.26060227e-02,  6.90451637e-03,  4.97876527e-03,  6.30719308e-03,
       -2.80506089e-02, -1.78617369e-02, -5.21890493e-03,  1.19957160e-02,
       -1.85738392e-02, -3.68579812e-02,  3.09816934e-02, -2.95355860e-02,
       -3.91420983e-02,  2.84803677e-02, -4.07637982e-03, -4.20604125e-02,
       -2.82285362e-02, -3.63491811e-02, -3.38371210e-02, -1.62505955e-02,
        2.79739127e-02,  1.04149822e-02, -2.79958043e-02, -1.49424281e-02,
        3.05541861e-03, -7.64848897e-03,  2.62526013e-02, -3.03531047e-02,
       -3.72186899e-02,  3.78772058e-02, -2.01349203e-02, -4.40117195e-02,
       -8.62373039e-03, -4.09795307e-02,  1.52654760e-02,  7.57868681e-03,
       -1.76996421e-02, -2.84666792e-02,  3.74593884e-02, -2.85682734e-02,
       -4.64074202e-02, -1.97550491e-03, -1.86799001e-02,  6.08897442e-03,
        3.29060219e-02,  2.43786220e-02,  9.72719584e-03,  7.42806308e-03,
        1.19419843e-02,  3.82800251e-02, -6.05196785e-03, -3.02308295e-02,
       -2.16039065e-02, -3.85919586e-02,  1.53054828e-02, -2.63003539e-02,
       -4.71541397e-02, -1.25563536e-02, -1.26855811e-02, -6.99581206e-02,
        1.27605451e-02, -3.14708538e-02, -8.51328019e-03,  9.55830980e-03,
        3.16310227e-02, -2.44959425e-02, -3.76436710e-02, -3.05557847e-02,
       -2.21231952e-02, -4.14985279e-03, -3.00703067e-02, -2.37787832e-02,
        9.39898752e-03, -7.75912823e-03, -4.09702994e-02, -1.77842509e-02,
        1.47761218e-03, -1.64607540e-02,  8.64574499e-03,  3.83241475e-02,
        2.80806678e-03, -4.43233829e-03, -2.35228688e-02, -8.87169316e-03,
       -1.32352058e-02, -4.42840047e-02, -6.18295334e-02,  2.66481116e-02,
        7.36308401e-04, -2.78466148e-04, -2.66942307e-02,  3.22839641e-03,
       -2.55932156e-02, -5.50302826e-02, -3.71580082e-03, -1.99763011e-02,
       -2.39463802e-02, -3.23939249e-02,  3.33679169e-02,  1.14694482e-03,
       -3.68409194e-02,  1.78556261e-03,  4.89477552e-02, -3.08595691e-02,
        2.70941406e-02, -3.01433839e-02,  3.88928056e-02,  1.11254416e-02,
       -3.67606767e-02, -2.87903063e-02,  1.50593994e-02,  2.72097625e-02,
       -4.99081276e-02,  1.14310747e-02, -2.29983628e-02,  2.31630877e-02,
       -2.73240805e-02, -6.93755085e-03,  3.60411704e-02, -4.38753851e-02,
       -8.39897804e-03, -1.49233751e-02,  2.06083786e-02,  1.91226359e-02,
        2.81725172e-02, -7.44473655e-03, -2.61423718e-02,  7.69179687e-03,
       -2.18907315e-02,  5.80512499e-03, -1.45900147e-02,  2.00381186e-02,
        9.27781221e-03,  3.74362469e-02,  1.57514345e-02,  2.88755391e-02,
       -4.11662050e-02, -1.46651501e-02, -4.01235260e-02, -2.49613747e-02,
        1.21329697e-02, -8.01683962e-03,  3.16637894e-03,  1.46909170e-02,
       -6.90239146e-02, -1.78482456e-04,  3.10536511e-02, -8.27333331e-03,
       -5.05310968e-02,  3.46058123e-02,  1.29430573e-02,  4.27370146e-03,
       -2.50613037e-02,  3.30475643e-02, -6.09062286e-03, -3.58681269e-02,
       -3.27353999e-02, -1.45967212e-02, -1.54079515e-02, -3.97805758e-02,
       -4.75963168e-02, -4.07247767e-02, -4.47761789e-02, -6.01992533e-02,
        1.81782711e-02, -3.01749762e-02, -3.21854837e-02,  3.09292525e-02,
        5.43436781e-02,  1.25855841e-02, -1.15123084e-02, -2.94045229e-02,
        2.44552568e-02, -7.62615167e-03, -4.24739979e-02, -2.10619941e-02,
       -5.41157350e-02, -2.96662636e-02,  1.69952642e-02,  2.65259054e-02,
        2.70093810e-02, -4.56180088e-02, -2.10387073e-02, -1.44297741e-02,
        1.20700831e-02,  1.06840683e-02, -6.53958842e-02, -3.69496010e-02,
        3.54872532e-02,  2.15263199e-03,  1.86875779e-02, -8.66580638e-04,
        3.09514012e-02,  1.01383068e-02, -2.05399469e-02,  2.82239970e-02,
       -4.75120582e-02, -4.83946502e-03, -1.43838497e-02, -1.08239250e-02,
       -2.16102097e-02, -2.72150971e-02, -3.79122980e-02, -2.17627753e-02,
       -4.84442450e-02, -3.81284393e-02,  7.00396067e-03, -4.89244871e-02,
        1.37908722e-03,  1.54248420e-02, -1.49588902e-02,  3.83736677e-02,
        1.01320343e-02, -3.58466692e-02,  4.66317572e-02, -4.26740982e-02,
       -2.85605527e-02, -9.17883590e-03,  2.80134915e-03,  2.31590010e-02,
       -1.72743052e-02, -3.70384902e-02,  1.42329270e-02,  5.63836796e-03,
        2.12278659e-03, -1.69143751e-02, -2.94005536e-02, -4.68028486e-02,
       -2.94688134e-03, -1.67269371e-02,  1.04232272e-02, -1.72402232e-03,
       -2.66683809e-02, -4.57463898e-02,  9.53027571e-04,  1.87850855e-02,
       -2.90666670e-02,  5.26091903e-02, -2.07366124e-02, -5.53181097e-02,
        4.95259650e-03, -6.72045629e-03, -3.00230389e-03, -3.52190547e-02,
       -3.30689363e-02, -2.45812885e-03, -9.58414967e-05, -2.52529737e-02,
       -1.85729228e-02, -2.39392766e-03,  2.59493999e-02, -3.50509658e-02,
        1.96128478e-03,  4.51695453e-03,  1.91025641e-02, -1.02881892e-02,
       -3.74554172e-02,  3.63993682e-02,  1.01125976e-02,  2.15602219e-02,
        1.94225404e-02, -2.48774048e-02,  5.61326649e-03,  2.72504315e-02,
        2.52948757e-02,  6.23046421e-03, -8.80700827e-04,  2.02162303e-02,
        1.73226893e-02,  2.80428119e-02,  2.74867918e-02,  1.13015091e-02,
        1.65752005e-02,  2.53937133e-02,  2.94369739e-02,  3.63579802e-02,
        2.51296405e-02, -1.91828795e-02, -1.43275140e-02,  7.90927187e-03,
        1.24312202e-02, -9.34778992e-03,  1.19214607e-02,  2.25452352e-02,
       -1.73702408e-02,  9.00155026e-03,  1.73661038e-02,  4.49743960e-03,
        3.26541103e-02, -5.82720935e-02,  2.44890004e-02, -6.02007471e-02,
       -5.58689586e-04, -3.71227860e-02, -2.96593849e-02, -2.32600030e-02,
        1.97718572e-02,  8.28687847e-03, -2.77673565e-02, -3.06195207e-02,
        3.22251581e-02,  9.43601597e-03, -6.40281057e-03,  5.87138580e-03,
       -1.19301574e-02,  1.37459598e-02,  1.39934458e-02,  3.11155990e-02,
       -2.12531313e-02, -1.82093086e-03, -6.78056153e-03, -4.45873179e-02,
        1.90395359e-02, -2.51145177e-02, -4.11450900e-02,  2.39566751e-02,
       -3.81215326e-02,  1.26729310e-02, -1.25898784e-02,  6.39848039e-03,
        2.29689498e-02, -7.96226040e-03,  8.00723489e-03, -8.41295533e-03,
        1.83163006e-02, -2.67484039e-02,  4.33124155e-02,  3.74710634e-02,
       -5.75557090e-02, -2.12004152e-03,  1.45020650e-03, -1.96529087e-02,
        1.41813876e-02, -2.23899912e-02, -2.88676992e-02,  9.52442363e-03,
        1.46831712e-02,  1.74187757e-02,  5.20570530e-03,  2.74692196e-02,
       -4.07708772e-02, -2.76059434e-02,  6.62086485e-03,  2.09480170e-02,
        1.75208431e-02, -9.95162688e-03,  3.60399694e-03, -5.27942739e-02,
       -9.67712328e-03,  3.80140208e-02,  2.17023939e-02, -4.70630405e-03,
       -3.16706896e-02,  1.81082990e-02,  1.82382632e-02,  4.01123725e-02,
        3.21830846e-02, -1.11674685e-02,  3.42375669e-03, -4.89708222e-03,
       -1.50026325e-02, -3.18537541e-02, -2.66618486e-02,  6.66731177e-03,
        1.36776897e-03,  1.96686611e-02,  8.80742911e-03, -6.12638742e-02,
       -1.34284794e-02, -2.15517469e-02, -2.48394720e-02, -4.60142130e-03,
        5.49095171e-03, -1.05977794e-02,  1.10917480e-03,  9.34762787e-03,
        3.40857916e-02, -5.46805933e-03,  1.65020842e-02,  1.40935095e-04,
        3.66632491e-02,  3.75188813e-02, -2.19150707e-02,  3.33293602e-02,
        3.42566743e-02,  2.28914712e-02,  1.78068795e-03,  5.58955688e-03,
       -1.48509759e-02, -1.40144946e-02, -2.31202636e-02, -6.79163681e-03,
       -1.07192313e-02,  1.81197207e-02, -1.86491963e-02, -7.62439240e-03,
       -3.09205391e-02,  3.85406874e-02, -3.16019692e-02,  2.82328911e-02,
       -2.04730872e-02, -1.24189099e-02, -1.50123090e-02, -1.62513833e-02,
        8.97634216e-03,  4.29612882e-02,  7.05520157e-03, -2.11257208e-02,
       -2.22422387e-02, -1.61761213e-02,  2.38122810e-02, -1.99680086e-02,
       -4.69129421e-02,  3.20823453e-02,  1.63592640e-02, -3.21509852e-03,
       -2.50525605e-02, -3.04661747e-02, -1.43233954e-03,  1.80509090e-02,
       -3.01606338e-02, -1.64605994e-02,  6.51562912e-03,  2.56285490e-03,
       -2.95922961e-02,  5.60862804e-03, -1.39255142e-02, -1.59423370e-02,
        2.41635498e-02, -1.60279926e-02,  1.16037782e-02, -3.27083841e-02,
       -1.74916573e-02,  3.18991058e-02,  1.72229465e-02, -3.56459171e-02,
        1.48797408e-02, -6.92359079e-03,  3.01940069e-02, -1.53230885e-02,
       -4.91727516e-03,  1.01801632e-02,  3.28135677e-02, -3.12064067e-02,
       -4.74893674e-03,  1.36315534e-02, -3.11930068e-02, -3.56939733e-02,
        2.50525456e-02, -1.33574689e-02, -3.22291851e-02,  6.34575123e-03,
        5.61540760e-03, -4.75431085e-02, -2.19518766e-02,  2.80837100e-02,
       -1.73488874e-02, -2.17257366e-02, -1.50387024e-03,  1.67283490e-02,
       -1.71363838e-02, -7.79055199e-03,  4.07363474e-02, -9.02193319e-03,
        1.17503861e-02, -2.23227721e-02, -3.26251388e-02,  2.65765917e-02,
       -2.86444537e-02, -6.38691359e-04,  2.72170808e-02, -4.92861457e-02,
       -5.12991659e-03, -1.06576858e-02,  8.14786274e-03,  3.30450572e-02,
       -1.53599335e-02, -1.00309085e-02,  3.89378257e-02, -3.32022421e-02,
        7.53887556e-03, -1.77898705e-02, -1.00144204e-02, -1.34458514e-02,
        1.55696599e-02, -1.76923501e-03,  1.34771448e-02, -9.93288006e-04,
       -3.96950692e-02,  2.34951861e-02,  2.71511506e-02,  4.41238098e-02,
        2.67065316e-02, -3.04131694e-02,  3.27675752e-02, -2.64701303e-02],
      dtype=float32), array([0.00828611, 0.00769023, 0.00836201, 0.0069663 , 0.00831126,
       0.00740955, 0.0097757 , 0.01537489, 0.00783465, 0.01065157,
       0.01123372, 0.00820336, 0.00817345, 0.01107584, 0.00837092,
       0.0089539 , 0.00956657, 0.00845438, 0.0085388 , 0.00749588,
       0.00952539, 0.0085557 , 0.00774132, 0.00796101, 0.00770173,
       0.00820956, 0.00798443, 0.01040614, 0.01159857, 0.00952684,
       0.00728508, 0.00895628, 0.01031491, 0.01019821, 0.00957005,
       0.00814632, 0.01093563, 0.01089226, 0.00811242, 0.00810377,
       0.00785824, 0.00878432, 0.0086183 , 0.00819309, 0.01242353,
       0.00869324, 0.00743805, 0.0142585 , 0.00769412, 0.00832259,
       0.00766011, 0.00780646, 0.00801338, 0.00774811, 0.00967846,
       0.00931324, 0.00843473, 0.00792277, 0.00891025, 0.00777005,
       0.00802343, 0.00883724, 0.00789046, 0.01066731, 0.00802159,
       0.01385731, 0.00739261, 0.00809441, 0.0085453 , 0.01059466,
       0.00787374, 0.00778958, 0.01182726, 0.00742969, 0.00852156,
       0.01259586, 0.00895508, 0.00781747, 0.00808622, 0.00963154,
       0.00771848, 0.00874822, 0.01061056, 0.01071164, 0.00809145,
       0.00745854, 0.01299126, 0.00776541, 0.0074981 , 0.00826115,
       0.01263209, 0.00778385, 0.00771864, 0.00758498, 0.00785436,
       0.0123813 , 0.00822309, 0.00787217, 0.00934626, 0.00788358,
       0.00797489, 0.0131524 , 0.01153079, 0.00812666, 0.01073769,
       0.00816455, 0.00792941, 0.00767258, 0.00921166, 0.0097196 ,
       0.00826129, 0.0089122 , 0.00879294, 0.00848476, 0.01193915,
       0.00793365, 0.01113338, 0.00785939, 0.01842734, 0.00858615,
       0.01064847, 0.00805758, 0.01248678, 0.00855756, 0.00969204,
       0.00783836, 0.00818218, 0.00726752, 0.00888719, 0.00844597,
       0.00810223, 0.01071852, 0.00928043, 0.00802271, 0.01447335,
       0.0085255 , 0.00905494, 0.00893267, 0.00842593, 0.00796378,
       0.00794225, 0.00854415, 0.00977115, 0.00993089, 0.00876865,
       0.00769831, 0.00791787, 0.00889072, 0.00792406, 0.01068868,
       0.00823467, 0.00997818, 0.01136796, 0.00739238, 0.00975669,
       0.00812114, 0.00853785, 0.00765911, 0.00720277, 0.00748541,
       0.01022726, 0.00835034, 0.00840847, 0.00818199, 0.01280583,
       0.00855936, 0.00768483, 0.00715605, 0.00934678, 0.00857001,
       0.00728179, 0.00786752, 0.00938067, 0.00796544, 0.00785339,
       0.01138651, 0.00904329, 0.01437597, 0.00941552, 0.01244669,
       0.00751133, 0.0089154 , 0.00790007, 0.00942686, 0.01685919,
       0.00798033, 0.0080368 , 0.00942949, 0.01044262, 0.00715846,
       0.00985716, 0.00892816, 0.01243739, 0.00879208, 0.00996431,
       0.0106825 , 0.00818409, 0.01552827, 0.00807405, 0.00863181,
       0.00719838, 0.00742754, 0.01100885, 0.00843923, 0.00931767,
       0.00761024, 0.00780998, 0.00820736, 0.012438  , 0.00774809,
       0.01290684, 0.00998044, 0.00902326, 0.00784871, 0.00817914,
       0.00788803, 0.00876075, 0.01071502, 0.01142334, 0.00936753,
       0.00832976, 0.01275089, 0.00731212, 0.01449798, 0.00815869,
       0.00729828, 0.00795472, 0.01153211, 0.00776183, 0.0125893 ,
       0.0158195 , 0.0089131 , 0.00808255, 0.00876903, 0.00857635,
       0.01054929, 0.00934819, 0.010859  , 0.0082799 , 0.00736407,
       0.0115748 , 0.00959347, 0.00976678, 0.01158857, 0.00762204,
       0.00789473, 0.00807257, 0.00815865, 0.01484042, 0.01293086,
       0.00721848, 0.00899359, 0.00791761, 0.01982379, 0.00744056,
       0.02264044, 0.00730928, 0.00716006, 0.00812671, 0.00918811,
       0.00805299, 0.00812754, 0.00756478, 0.00787961, 0.00749934,
       0.00895644, 0.01062361, 0.01064369, 0.00817313, 0.00754929,
       0.00886395, 0.00761076, 0.00901279, 0.01163295, 0.00846476,
       0.00877889, 0.00841555, 0.00857024, 0.00779016, 0.00785495,
       0.0075481 , 0.00851117, 0.0084649 , 0.00783233, 0.00831073,
       0.00838103, 0.00788646, 0.00975115, 0.00925636, 0.00895083,
       0.00929394, 0.00858581, 0.01187797, 0.00910918, 0.00824856,
       0.00917157, 0.00784699, 0.00822988, 0.00854684, 0.00849288,
       0.00865788, 0.00926006, 0.0137931 , 0.01025965, 0.00819746,
       0.01031466, 0.01280962, 0.01278747, 0.0087388 , 0.00882482,
       0.01253586, 0.00871029, 0.00978045, 0.00936465, 0.00848756,
       0.00960043, 0.00934799, 0.0084357 , 0.00794276, 0.00819291,
       0.00781821, 0.00840096, 0.00817653, 0.01138438, 0.00816952,
       0.00923602, 0.00898162, 0.01262688, 0.00768788, 0.00882478,
       0.01069506, 0.01123992, 0.01111331, 0.0080676 , 0.00812516,
       0.01217804, 0.00851137, 0.00979624, 0.00759095, 0.00816173,
       0.00909538, 0.00849648, 0.00961434, 0.00901922, 0.01199043,
       0.00943738, 0.0080153 , 0.01112473, 0.01190471, 0.00836486,
       0.01096561, 0.00726385, 0.00751628, 0.00737796, 0.00890571,
       0.00986945, 0.01624649, 0.01011334, 0.00758344, 0.01044416,
       0.00791066, 0.00887428, 0.00758359, 0.00971783, 0.008466  ,
       0.01283345, 0.00846391, 0.00825956, 0.01099388, 0.00935409,
       0.00820899, 0.01349351, 0.0088791 , 0.00700585, 0.0073708 ,
       0.00967913, 0.00792447, 0.00809156, 0.0087485 , 0.00819361,
       0.00763178, 0.00831218, 0.008025  , 0.01009243, 0.00815043,
       0.0085866 , 0.00767959, 0.01140224, 0.00742888, 0.00818147,
       0.00777965, 0.00765355, 0.01256022, 0.00824216, 0.00911334,
       0.00811856, 0.0091326 , 0.01182119, 0.00889873, 0.00861875,
       0.01392098, 0.01101958, 0.00760997, 0.00882033, 0.00745767,
       0.00800925, 0.00794657, 0.00967074, 0.00726181, 0.00752729,
       0.00825037, 0.00898253, 0.00887766, 0.01298794, 0.00841378,
       0.00803383, 0.00943875, 0.00859109, 0.00798919, 0.00812142,
       0.00753832, 0.01399622, 0.00741933, 0.0078491 , 0.00898938,
       0.01074009, 0.01132219, 0.00779057, 0.0130716 , 0.01584488,
       0.00817834, 0.00763288, 0.00834999, 0.00839461, 0.00758055,
       0.00792905, 0.01189958, 0.00730244, 0.008278  , 0.00989877,
       0.01237122, 0.00833404, 0.00769599, 0.00826852, 0.00900858,
       0.00852592, 0.00853795, 0.00794728, 0.00782045, 0.01063989,
       0.01085401, 0.01040229, 0.01014202, 0.00931782, 0.01102347,
       0.0081864 , 0.00784064, 0.00852815, 0.01143902, 0.01198228,
       0.00728004, 0.00929131, 0.00792108, 0.01143321, 0.00977856,
       0.00724172, 0.01040764, 0.00815671, 0.00798987, 0.00962425,
       0.00806255, 0.0090372 , 0.00790554, 0.00819932, 0.00793741,
       0.00791358, 0.00939109, 0.01128693, 0.00885198, 0.00900701,
       0.00805011, 0.00819684, 0.00804205, 0.01175617, 0.00756338,
       0.00818007, 0.00819002, 0.01012858, 0.00833205, 0.00792692,
       0.00929996, 0.01103736, 0.00741455, 0.00760957, 0.01587942,
       0.01151089, 0.0089993 , 0.00800772, 0.00864711, 0.00837063,
       0.01258505, 0.00879086, 0.0076587 , 0.00775657, 0.00963065,
       0.0082615 , 0.00892398, 0.0110407 , 0.00847332, 0.00961416,
       0.01190874, 0.00833469], dtype=float32), array([[[[-0.069036  , -0.0019045 ,  0.00416704, ...,  0.05283533,
          -0.01017446, -0.0701032 ],
         [-0.06945492,  0.013865  , -0.08328269, ..., -0.02393481,
          -0.07736504, -0.08452337],
         [-0.00887253,  0.04832292, -0.05009081, ..., -0.03496484,
          -0.00880177,  0.00400278],
         ...,
         [-0.00482053,  0.07198201, -0.00746208, ..., -0.01702555,
           0.05707086, -0.04567443],
         [ 0.09476382,  0.04660838,  0.00508846, ...,  0.06986851,
           0.04259507, -0.07966567],
         [ 0.03239126,  0.03649322,  0.00283662, ...,  0.10915889,
           0.03505563, -0.07866585]]]], dtype=float32), array([1.0336823 , 1.0124831 , 1.0194771 , 0.9898928 , 0.99232477,
       1.0526038 , 0.9755804 , 0.9723187 , 0.9883805 , 1.025737  ,
       0.9922865 , 0.96883625, 0.9862484 , 1.0172912 , 1.0117698 ,
       0.97571   , 1.0208937 , 1.0426313 , 0.9964288 , 1.0169432 ,
       1.0019598 , 1.0165184 , 0.9641736 , 0.9757255 , 1.0161663 ,
       1.0481694 , 1.0171188 , 1.00058   , 0.9963466 , 1.0173408 ,
       1.0553235 , 0.982602  , 1.0333183 , 0.991485  , 1.023302  ,
       0.9928398 , 0.9973816 , 0.9924042 , 1.0142156 , 0.9887432 ,
       0.98687035, 1.0042677 , 1.0038339 , 1.0202883 , 1.0006317 ,
       0.9844283 , 0.9950589 , 0.99452996, 1.0036626 , 1.011238  ,
       0.9871012 , 0.99145985, 1.0154753 , 0.9922841 , 0.97288877,
       1.0012444 , 0.96172976, 0.9499896 , 1.0099427 , 1.007924  ,
       0.9886608 , 1.0042691 , 0.99052465, 1.0148821 , 0.99080694,
       1.0137728 , 1.0147145 , 0.99833447, 1.0140911 , 1.010187  ,
       1.0063653 , 0.9795181 , 1.0135535 , 0.9947343 , 1.0162119 ,
       1.0213046 , 1.027074  , 0.974667  , 1.0084065 , 1.0193555 ,
       1.0234016 , 1.0129579 , 0.97882086, 1.025456  , 0.9852909 ,
       1.0231164 , 1.0169442 , 0.9709947 , 1.001574  , 1.030971  ,
       0.9782297 , 0.97719693, 1.0129458 , 1.0533924 , 1.0277125 ,
       1.0100764 , 1.0304154 , 1.0032197 , 0.99237955, 0.9736715 ,
       1.0026226 , 1.0200585 , 0.97015685, 1.0229217 , 0.9787368 ,
       1.0214947 , 0.9723071 , 0.98111844, 0.98910636, 1.0218318 ,
       1.0095758 , 1.0109633 , 0.98881227, 1.0363092 , 0.9918276 ,
       1.0172958 , 0.9907688 , 0.97084725, 1.0390358 , 1.007393  ,
       1.0140826 , 0.9901293 , 1.0349929 , 1.0331013 , 0.9978363 ,
       1.0353097 , 0.99669677, 1.0410831 , 1.0327668 , 1.0245208 ,
       0.99478865, 0.96354926, 0.991799  , 0.9890942 , 0.9669834 ,
       0.97702146, 1.0359832 , 1.011414  , 0.9915981 , 1.0047889 ,
       0.99026966, 1.0388842 , 0.98918986, 1.0259081 , 1.027272  ,
       0.95780754, 1.0089866 , 1.0065528 , 1.0491636 , 1.0009347 ,
       1.004648  , 0.97429377, 1.0235034 , 1.03095   , 0.9851203 ,
       1.0443637 , 0.98396397, 0.99140877, 1.0114334 , 1.0624273 ,
       1.0184318 , 0.9866106 , 0.9995018 , 0.9930204 , 1.036767  ,
       0.9639534 , 1.0160602 , 1.0293229 , 1.0028429 , 0.98685414,
       0.99925077, 1.0325189 , 0.9524477 , 1.0003144 , 1.0120093 ,
       0.9892869 , 1.0263705 , 1.0063871 , 1.0246996 , 1.0437633 ,
       1.0094639 , 0.998554  , 1.0061274 , 1.0079614 , 1.0049815 ,
       1.0356791 , 1.0193716 , 0.98724264, 1.0042362 , 0.9987016 ,
       1.003415  , 1.0063684 , 1.0255202 , 0.9874146 , 0.97863173,
       0.97496784, 1.041586  , 0.9694371 , 0.99933046, 0.98707587,
       0.99606186, 0.99606943, 1.0059881 , 1.070373  , 1.0041771 ,
       1.0211929 , 0.99649495, 1.0361806 , 0.98740643, 1.0066637 ,
       0.9987167 , 0.9894531 , 0.9825073 , 1.012952  , 1.0167323 ,
       0.99243677, 0.96884686, 0.9926533 , 1.028245  , 0.9999485 ,
       1.0652466 , 1.0157771 , 0.9740133 , 1.0002124 , 1.0380136 ,
       0.9913096 , 0.9983697 , 0.9870618 , 1.0121896 , 0.9741576 ,
       1.0183002 , 1.0514007 , 1.0250212 , 0.99229866, 1.0089972 ,
       1.0324379 , 1.016477  , 0.97823554, 1.0102227 , 1.0006541 ,
       0.95589787, 0.9929927 , 0.95390034, 1.0235693 , 0.9793188 ,
       1.0333899 , 1.0304538 , 1.0217129 , 0.9860241 , 1.0080702 ,
       1.0445436 , 0.9602914 , 0.9857442 , 1.0102863 , 1.0024589 ,
       1.0050853 , 1.0010002 , 1.0092963 , 0.96724004, 1.0050144 ,
       0.9670857 , 1.0262368 , 0.9767993 , 1.014067  , 1.0220222 ,
       0.98865026, 1.0163151 , 0.9994555 , 0.9938678 , 1.0226233 ,
       0.98270935, 1.0024172 , 0.9800384 , 1.0042325 , 0.9860085 ,
       0.98923135, 0.99673325, 0.99602175, 0.9996556 , 0.9978677 ,
       0.9988635 , 0.9982321 , 1.0031188 , 1.0037236 , 0.98278433,
       1.0335736 , 1.0217322 , 0.9893224 , 1.0409479 , 1.0287919 ,
       1.006882  , 1.0255682 , 0.9779509 , 0.947538  , 0.9995429 ,
       0.9965136 , 0.97400576, 1.0014335 , 1.0026829 , 1.0033154 ,
       1.0344    , 1.0417206 , 1.0207384 , 0.98873395, 0.9754964 ,
       0.9701613 , 0.9925562 , 1.0002685 , 0.9909507 , 1.0429548 ,
       0.998306  , 1.0074567 , 1.0008291 , 1.0066667 , 1.0267774 ,
       1.0145932 , 0.9990101 , 1.064494  , 0.96242505, 1.022314  ,
       1.005674  , 1.0179709 , 1.0127069 , 0.9969815 , 0.96452045,
       1.0209239 , 0.99230367, 0.9867853 , 0.9934719 , 0.99695575,
       1.007803  , 1.0715445 , 1.0062444 , 1.005987  , 0.9863854 ,
       0.97923964, 1.0396096 , 0.95972556, 1.0285221 , 0.9899055 ,
       1.0069627 , 0.97412604, 1.025304  , 1.0249162 , 1.0226314 ,
       1.012182  , 1.0014307 , 1.0394932 , 0.97909963, 0.98603535,
       0.9914998 , 0.99649173, 0.985419  , 0.9931202 , 0.9835674 ,
       1.0013334 , 1.0051107 , 1.0108479 , 0.98698753, 0.97962993,
       0.98731023, 1.0057517 , 1.0239549 , 0.98520976, 1.0246317 ,
       1.025805  , 0.99653816, 1.0012777 , 0.9786228 , 0.99685377,
       0.9800402 , 1.0306299 , 0.99523354, 0.99218184, 0.98567885,
       1.002097  , 0.99593216, 1.0121008 , 1.0368171 , 1.0082737 ,
       1.0053945 , 1.0125724 , 1.0079018 , 0.9923943 , 0.9926869 ,
       0.9943456 , 1.0045754 , 0.9917377 , 1.0179358 , 0.9844471 ,
       1.0071772 , 1.0254622 , 0.97962296, 1.009703  , 0.99131674,
       1.007869  , 1.0375026 , 1.0283363 , 0.9923662 , 0.97852224,
       0.9881906 , 1.011541  , 1.028366  , 0.9697316 , 1.0164546 ,
       0.982244  , 0.9534855 , 0.9962101 , 1.0076315 , 1.0030745 ,
       0.9907739 , 1.0389961 , 1.0488583 , 1.0044196 , 0.99619055,
       0.97799176, 0.992659  , 0.9897903 , 0.9765398 , 1.00355   ,
       0.9949891 , 0.9702893 , 1.0518602 , 0.9749086 , 0.9844976 ,
       0.99409115, 1.0003672 , 0.99768275, 0.9826239 , 0.9844354 ,
       1.0284021 , 0.9905156 , 0.9890072 , 1.0101733 , 1.0219053 ,
       1.0066319 , 0.995427  , 1.0104322 , 1.0127838 , 1.0366637 ,
       1.0125493 , 0.97888416, 1.0236675 , 0.99318755, 0.99481153,
       1.0279197 , 0.98604363, 1.0224243 , 0.9884477 , 0.9987971 ,
       0.98852134, 1.0134296 , 0.9565985 , 1.0309217 , 1.0147988 ,
       1.0209073 , 0.9898744 , 1.0326979 , 1.0272424 , 0.94990414,
       0.9778995 , 0.9773878 , 1.0017924 , 1.0261387 , 0.9954978 ,
       0.9888837 , 1.0070918 , 1.0046622 , 1.0456479 , 1.0076272 ,
       1.0191115 , 1.0133296 , 1.0339426 , 1.0058314 , 1.0007553 ,
       0.98473126, 1.0051074 , 1.0427316 , 0.9761447 , 1.0189348 ,
       0.9590389 , 1.0092869 , 0.9708132 , 0.9890132 , 1.0027822 ,
       0.9929985 , 0.9960118 , 1.011924  , 1.0162293 , 1.0454612 ,
       0.990903  , 0.9948912 , 1.0007131 , 1.0221492 , 0.99931335,
       1.0230638 , 1.0641042 , 0.986507  , 1.0127949 , 0.9898659 ,
       1.0029311 , 1.0224334 , 1.0084039 , 1.0026147 , 1.0285443 ,
       1.0104896 , 1.0172855 , 1.0290289 , 0.99124384, 0.98601127,
       0.9981625 , 0.989593  ], dtype=float32), array([ 1.93765927e-02, -1.29422322e-02,  3.94247994e-02,  9.47305001e-03,
        1.03321504e-02,  2.76672654e-02, -1.76121388e-02,  5.49761439e-03,
       -6.14383584e-03,  1.01033160e-02,  1.46847479e-02, -2.68972159e-04,
        1.41703561e-02,  1.84271913e-02,  7.21013127e-03, -2.01430395e-02,
        2.75542066e-02, -3.03973649e-02,  3.15159163e-03, -1.66638885e-02,
        2.65900567e-02, -2.43153777e-02, -4.88775931e-02, -2.47102398e-02,
       -1.41002405e-02,  1.92076918e-02,  1.65300269e-03,  1.28057767e-02,
       -1.47583673e-03, -4.94674314e-03,  4.35394235e-02,  2.06249300e-02,
        7.06758071e-03, -2.28518117e-02, -4.87334095e-04, -5.17761288e-03,
       -1.45569793e-03,  1.48721272e-03, -9.06083453e-03, -2.54243594e-02,
        5.07421559e-03,  5.99075621e-03,  1.61851216e-02, -1.88915972e-02,
       -1.81043788e-03, -3.66350543e-03,  3.59983835e-03, -1.18759982e-02,
       -3.25972363e-02,  9.17519443e-03, -1.44178234e-02, -7.43717840e-03,
       -3.89053002e-02,  5.48871874e-04, -2.96419356e-02,  2.50426102e-02,
       -2.77954545e-02, -1.12923672e-02,  8.19370896e-03,  8.19096313e-05,
       -6.34249393e-03, -2.61957124e-02, -1.01136072e-02, -2.00042315e-02,
       -3.08886822e-02,  2.27541402e-02, -3.14368610e-03,  1.44754807e-02,
       -1.35110701e-02, -2.28136387e-02,  4.39246520e-02, -1.81724150e-02,
       -8.87611881e-03,  5.61663741e-03,  3.65614444e-02, -8.98784399e-03,
        3.37424129e-02, -1.60723589e-02,  4.03268896e-02, -1.68699306e-02,
       -1.48040354e-02,  5.64763770e-02, -2.20842119e-02,  2.44388357e-02,
       -5.73818246e-03,  4.51359414e-02,  2.57294010e-02,  1.62186287e-02,
        1.04269702e-02,  4.29387540e-02,  9.71919298e-03,  9.56066884e-03,
        3.00017092e-02, -1.27196014e-02, -7.78157497e-03,  2.39877030e-02,
       -8.48570932e-03, -1.97304785e-02, -5.66533627e-03, -1.74540293e-03,
       -2.16564871e-02,  1.76272150e-02, -2.13701148e-02,  9.75386146e-03,
       -3.02761924e-02, -8.13778024e-03, -5.39485663e-02,  1.28768468e-02,
       -2.69077923e-02,  2.08052211e-02, -7.70136481e-03,  3.64228874e-03,
       -2.18705162e-02,  3.51876672e-03, -1.22930517e-03,  7.58739770e-04,
        2.49274150e-02, -3.11908368e-02,  2.13783868e-02,  3.34371887e-02,
        2.45254897e-02, -2.12313756e-02,  3.62070426e-02,  1.13515491e-02,
       -1.73247047e-03, -2.76364153e-03, -2.49971990e-02,  2.89347079e-02,
       -2.17899829e-02, -1.19954282e-02, -2.71845255e-02, -1.27653265e-02,
       -2.29114946e-02,  8.70303903e-03, -9.75803100e-03, -3.69127318e-02,
        1.86116956e-02, -7.40111712e-03, -2.17940509e-02,  1.04253320e-02,
       -2.93205511e-02,  4.78218496e-02, -4.97803232e-03, -8.72078817e-03,
        1.88186038e-02,  6.32290589e-03,  8.37051496e-03, -3.25075127e-02,
       -1.16038218e-03, -1.73396543e-02,  4.11623679e-02, -1.44213224e-02,
        1.33344787e-04, -9.44067910e-03, -4.12200717e-03,  1.08440621e-02,
        1.04464788e-03,  1.88785177e-02,  2.43586767e-02, -1.93822989e-03,
        4.52524014e-02,  6.89807814e-04,  2.05188245e-02,  1.07254013e-02,
       -9.70678311e-03, -7.34907622e-03, -1.14392918e-02,  2.83607151e-02,
        1.78700238e-02, -8.02198611e-03, -1.85301788e-02,  2.93360483e-02,
       -1.48310680e-02, -3.42399674e-03,  1.44005008e-03, -1.11230994e-02,
       -2.96765915e-03, -1.12416139e-02, -1.43840117e-02,  5.43559641e-02,
        2.05796324e-02,  2.35094950e-02, -1.64791346e-02, -1.46121299e-02,
       -1.89049952e-02,  4.27185893e-02,  2.32928935e-02, -1.89971831e-02,
        3.14361975e-03,  2.07692869e-02,  1.35821886e-02, -2.30172183e-02,
        2.79100034e-02, -1.02092465e-02, -2.24479754e-02, -1.05288215e-02,
       -4.17503566e-02, -1.30593944e-02, -1.70429032e-02,  1.79899279e-02,
        7.05212820e-04,  3.03983446e-02, -2.51614377e-02, -2.03747749e-02,
        9.32777859e-03,  7.89505616e-03,  2.82415505e-02, -6.15504384e-03,
       -1.64019652e-02, -1.03768706e-02,  4.40094434e-02,  1.33141736e-02,
       -6.65690610e-03,  1.64660700e-02, -1.05090458e-02,  1.12784905e-02,
       -3.19107622e-02,  1.37668215e-02,  6.46411255e-03, -1.66908409e-02,
        6.46269834e-03, -1.51841082e-02, -4.48407279e-03,  2.39887051e-02,
        4.63461969e-03, -1.58187523e-02,  2.78687254e-02,  1.80573307e-03,
        1.27111352e-03, -1.81182735e-02,  2.50600092e-02,  9.19932779e-03,
        1.52329011e-02, -3.33435573e-02, -1.43168145e-03, -9.94800963e-03,
        1.32911010e-02, -1.19028464e-02,  1.57947540e-02, -1.22815734e-02,
       -4.87562194e-02,  7.88464677e-05, -3.89019996e-02,  8.30980670e-03,
       -3.83290350e-02,  4.50539030e-02,  3.88871804e-02,  1.06701916e-02,
       -2.57382309e-03, -3.17147770e-03, -6.75401045e-03, -2.65277401e-02,
       -2.66338605e-02,  2.51556430e-02, -8.86747555e-04,  8.79067089e-03,
       -1.69258472e-02,  8.65272596e-04,  3.53059918e-02, -1.02088880e-02,
        2.06428114e-02,  3.95783000e-02, -5.89669235e-02, -1.65481661e-02,
        1.21441800e-02, -7.89333321e-03, -1.32848846e-03,  6.93095103e-02,
       -3.11089344e-02,  1.20779464e-03,  5.50118415e-03, -1.20707799e-03,
        5.18558780e-03,  1.40155721e-02, -4.49455902e-02,  1.84736587e-02,
       -1.15802586e-02,  2.30095536e-02, -4.81868628e-03,  3.28991301e-02,
       -9.90786962e-03,  1.86974518e-02, -2.54528448e-02,  1.38509581e-02,
        1.90370440e-04, -2.76906881e-02,  5.82344132e-03, -4.04006764e-02,
        1.36753442e-02, -8.81079864e-03,  2.20568646e-02, -1.41817443e-02,
       -4.90855724e-02, -2.03231219e-02, -4.78934497e-02, -3.08036879e-02,
        4.87244828e-03,  1.44270919e-02, -2.63862852e-02,  8.08279216e-03,
        1.00020049e-02,  2.75157690e-02,  3.67719145e-03, -5.81376161e-03,
        2.28181966e-02, -2.86627878e-02,  3.92687647e-03,  4.44740430e-03,
        4.75705042e-03,  2.26702150e-02, -6.96655503e-03, -5.33716241e-03,
        5.08072879e-03, -1.24109266e-02,  5.28419651e-02,  8.77143175e-04,
        2.73464490e-02,  6.77171396e-03, -1.38631267e-02, -1.45645492e-04,
        3.85281630e-02,  1.69455772e-03,  7.79227819e-03,  1.15516437e-02,
       -2.79561561e-02, -1.59578491e-02, -1.05592739e-02,  8.84507131e-03,
        1.55644107e-03, -1.41949495e-02,  1.75233297e-02, -2.36454494e-02,
        3.19416868e-03, -3.44480164e-02,  2.60538701e-02, -1.34800216e-02,
       -3.09048872e-02, -2.43865214e-02,  2.11169068e-02, -2.58847326e-02,
        1.41476840e-02, -5.74782817e-03, -9.55327973e-03,  2.90880837e-02,
       -8.94211605e-03,  5.50549179e-02,  2.55852239e-03,  4.33468372e-02,
       -1.98864508e-02,  4.11007879e-03, -1.71010401e-02,  2.73713544e-02,
       -1.39087895e-02,  2.01931633e-02, -1.24472855e-02, -2.56307400e-03,
        2.33967509e-02,  3.19490843e-02,  8.27511307e-03, -1.90999433e-02,
        6.40833704e-03, -8.83473316e-04,  3.66044119e-02,  7.86442216e-03,
        1.77307241e-02,  7.88339414e-03, -1.89079549e-02,  1.57239623e-02,
        3.05463490e-03,  1.68438368e-02, -1.09280860e-02,  1.90239381e-02,
       -9.96086514e-04,  5.60233882e-03, -3.95677015e-02,  2.14364119e-02,
        1.88967790e-02, -7.51970429e-03,  2.86521744e-02,  4.22604792e-02,
       -3.11409254e-02, -1.50123262e-03, -1.02678384e-03,  2.31798477e-02,
       -1.65672898e-02,  4.76577692e-03, -1.02361580e-02, -1.31392209e-02,
        5.99946454e-03, -1.18377954e-02, -1.71233024e-02,  2.53226515e-02,
       -1.53110176e-02,  3.37117212e-03,  1.89200509e-02, -4.92295735e-02,
       -2.55351439e-02,  1.70198623e-02, -6.53451355e-03, -1.65605489e-02,
       -2.51566675e-02,  7.35905662e-04,  2.62225065e-02,  1.29713826e-02,
        1.99244376e-02,  1.72517402e-03, -4.07412201e-02,  3.67515646e-02,
       -3.22548561e-02,  8.77908524e-03, -2.22630613e-02,  3.08600161e-02,
        2.56185606e-02,  3.39425914e-02, -2.14784164e-02, -4.02558595e-02,
       -1.61507353e-02, -9.83663462e-03, -5.94422333e-02,  4.40281845e-04,
       -1.03461163e-04, -1.45685524e-02,  1.31691080e-02, -3.04669533e-02,
       -1.15738809e-02, -7.24359695e-03,  7.34341517e-03,  4.58654463e-02,
        2.32418422e-02, -1.76462736e-02,  2.45591756e-02, -2.92270612e-02,
       -3.14817578e-02, -1.13209849e-03,  1.62632577e-02,  1.93563588e-02,
        3.89311723e-02, -1.19943125e-02,  1.65216494e-02,  1.69586123e-03,
       -2.31362740e-03, -4.51937784e-03,  2.71553975e-02, -2.61686016e-02,
        7.12449895e-03,  9.64639522e-03, -3.24098486e-03,  3.71587314e-02,
       -2.10345946e-02,  1.83899852e-03, -1.19248927e-02,  4.35829572e-02,
       -4.36764723e-03,  1.06620006e-02,  1.10355420e-02,  6.28854334e-02,
        1.33489007e-02,  2.36138329e-02, -1.28070973e-02,  6.00984844e-04,
       -2.91373618e-02, -1.63668618e-02,  2.88001336e-02, -1.88383162e-02,
       -1.31515530e-03, -3.52738611e-02, -1.12940446e-02, -7.25403614e-03,
        1.83609165e-02, -2.05842946e-02, -2.38171848e-03, -7.87715241e-03,
       -9.60297789e-03,  3.64969894e-02,  6.09005045e-04,  1.18021164e-02,
        3.30146775e-02,  1.92124620e-02, -2.37293113e-02,  4.74945456e-02,
       -3.61098684e-02, -5.06230863e-03, -3.69404480e-02,  4.00545523e-02,
       -1.01984311e-02, -5.04939212e-03,  3.82597893e-02,  9.46542434e-03,
        7.52694812e-03,  3.64301801e-02,  3.93934436e-02,  2.08736509e-02,
       -1.77955125e-02,  1.44980326e-02,  1.84039511e-02,  7.52306776e-03,
       -1.56566706e-02, -9.27471090e-03,  2.64214110e-02, -2.37760018e-03,
       -2.30457336e-02, -1.07854158e-02,  8.91163107e-03,  1.67846568e-02,
        1.78766660e-02, -2.05576606e-02,  1.46877328e-02, -1.35089457e-03,
       -1.78164039e-02, -1.37717267e-02,  4.22661135e-04,  1.96944438e-02],
      dtype=float32), array([ 1.57390207e-01,  1.00495720e+00, -3.00228029e-01, -5.64586818e-01,
        3.83948416e-01, -4.96567100e-01,  2.04824135e-01,  4.23039831e-02,
       -1.93044990e-01, -1.73064187e-01, -3.64242017e-01, -2.42587849e-01,
       -3.53105292e-02, -4.66054767e-01, -3.52508485e-01, -3.36900383e-01,
       -5.25821388e-01, -1.11007616e-01, -4.20154810e-01, -3.41950089e-01,
        3.01176727e-01, -4.07350749e-01, -3.00487667e-01,  2.79945701e-01,
        4.76189494e-01, -2.28855178e-01, -3.31836760e-01, -5.68524897e-01,
        1.68510675e-01,  2.13059977e-01, -2.98020959e-01, -2.82308340e-01,
       -9.98702720e-02,  5.09621263e-01, -1.35106985e-02,  1.18115693e-01,
       -2.14638665e-01, -9.43448208e-03,  1.41521906e-02,  6.55082881e-01,
        1.09083275e-03, -1.25176087e-01,  1.04270600e-01,  1.88798830e-01,
       -1.23884588e-01,  2.89541900e-01, -1.93589509e-01,  4.57714617e-01,
        3.72707367e-01, -1.28847763e-01, -5.76832414e-01, -1.36719700e-02,
       -3.81922513e-01,  3.16677749e-01,  3.92860562e-01,  2.00310592e-02,
       -2.28361696e-01, -1.02625906e-01, -3.29678476e-01, -7.42509425e-01,
        9.69031870e-01, -3.33572179e-01,  6.33002771e-03,  2.09694505e-01,
       -4.41740364e-01, -8.10431764e-02, -4.18951660e-01, -6.28045738e-01,
       -7.03076273e-02, -4.59451050e-01,  5.06915510e-01,  3.18396658e-01,
       -4.73040864e-02,  5.06233089e-02, -5.54330230e-01, -1.76512212e-01,
       -3.42891693e-01, -2.19710201e-01,  1.37285478e-02,  3.15675259e-01,
        2.08966941e-01, -2.52234340e-01, -5.79660870e-02, -2.66037911e-01,
        2.25630254e-02, -2.86276639e-01, -6.02365255e-01, -4.91596311e-01,
       -7.56917655e-01, -4.13910687e-01,  3.54959130e-01,  6.91027939e-01,
       -6.91356897e-01, -2.57505089e-01, -8.60671282e-01,  5.09287357e-01,
        1.46440327e-01,  7.93478549e-01, -4.09780800e-01,  1.73870008e-02,
       -4.72203881e-01,  5.83674908e-01,  6.17976010e-01, -2.06609741e-01,
       -7.70181537e-01, -3.23969722e-01,  8.08208510e-02, -7.88893900e-04,
        1.92072302e-01, -7.17991143e-02, -4.34244812e-01, -2.78377742e-01,
        2.69478649e-01, -4.66277331e-01,  2.41786297e-02,  3.62094253e-01,
       -4.63156313e-01,  3.84150505e-01,  2.23670006e-02,  3.40746045e-01,
        1.02454171e-01,  4.97433126e-01, -2.10046455e-01, -2.13691965e-01,
       -4.50126752e-02,  2.35723332e-01,  3.48223060e-01, -1.11447260e-01,
        3.31939548e-01,  2.27755502e-01,  3.73506576e-01,  1.12956755e-01,
        3.93443972e-01, -1.71617404e-01,  6.13515228e-02, -3.71485651e-01,
       -2.40978643e-01,  4.74867672e-01,  5.28241396e-01, -4.80443537e-01,
        2.32188776e-01,  1.40580505e-01,  1.90417334e-01, -9.88336802e-02,
        5.40919304e-02, -6.56390488e-01, -1.21767499e-01,  2.09615648e-01,
       -5.48383296e-01,  5.71438260e-02, -9.86120030e-02, -5.28892577e-01,
       -3.74074489e-01,  3.11237782e-01, -5.95333934e-01, -1.52944028e-01,
        1.92192376e-01,  3.22290212e-01,  1.45342082e-01,  3.71112786e-02,
       -5.40799618e-01,  9.67782363e-02, -2.80989379e-01, -2.67394662e-01,
       -5.15340924e-01, -1.98778629e-01, -4.49161232e-01, -7.54782259e-01,
       -2.09217668e-01,  3.08829069e-01, -3.20149750e-01, -6.07176483e-01,
        1.29725009e-01, -1.06690034e-01, -5.21487832e-01,  2.38385379e-01,
       -3.97017539e-01,  4.60877493e-02,  5.53320408e-01, -6.97460212e-03,
        1.73650920e-01, -1.00008988e+00, -2.59004273e-02, -1.01724766e-01,
        1.98550373e-02,  3.62413287e-01, -1.79282084e-01,  1.75205708e-01,
        1.25223085e-01,  1.96672510e-02,  4.57554683e-02,  2.38120258e-01,
       -4.93562073e-01,  4.46966887e-02,  3.98071378e-01,  1.57012567e-01,
       -4.77007031e-02, -3.31001490e-01,  4.23030406e-02, -7.77121186e-02,
        6.97655231e-02, -4.53922629e-01, -1.86400935e-02,  3.19690704e-01,
       -6.15498871e-02, -9.98948097e-01, -6.62497044e-01, -4.24727023e-01,
       -7.41584659e-01,  2.67509848e-01, -6.69022024e-01,  8.73269571e-04,
        4.69030440e-02,  2.87397411e-02, -2.20127776e-01, -2.91826308e-01,
       -7.62684107e-01,  4.28433746e-01, -5.19164920e-01, -2.54405923e-02,
       -8.87306407e-02, -2.18479857e-01,  3.37515533e-01, -4.78346497e-01,
       -4.10654008e-01,  5.46929203e-02, -5.89136064e-01,  7.00802803e-02,
       -4.83576767e-03,  1.59559935e-01, -1.81295693e-01, -6.04856253e-01,
       -5.84100902e-01,  6.33310318e-01, -2.00671390e-01, -1.66666810e-03,
       -4.09628510e-01, -3.17520201e-01,  3.08242321e-01,  1.30758867e-01,
       -2.11277857e-01,  7.32667893e-02, -2.45288759e-01,  1.41662285e-01,
        6.95584714e-02, -4.50604707e-01, -2.55818337e-01, -5.25220037e-01,
       -2.66154855e-01,  3.08295935e-01,  4.03495729e-02, -4.05154258e-01,
       -5.58926761e-02,  2.67679036e-01,  5.92695057e-01, -1.52884677e-01,
        3.21744502e-01, -2.76291460e-01, -7.26062596e-01, -8.42448417e-03,
       -9.10379231e-01, -2.20206618e-01,  1.00575840e+00, -2.77345683e-02,
       -3.21210384e-01,  6.06288791e-01, -1.63479701e-01,  6.17280677e-02,
        5.67983091e-01, -3.11507791e-01, -2.05167115e-01, -1.93719112e-03,
        1.89248659e-02,  3.43826860e-01,  4.63677704e-01, -9.33918715e-01,
        2.48048291e-01, -3.07937205e-01,  1.36355877e-01, -1.87441111e-01,
       -2.20686376e-01, -1.18716173e-01,  5.63696206e-01, -7.94582348e-03,
        8.23307097e-01,  2.21052617e-01, -7.83281744e-01,  2.45414227e-01,
       -2.28865936e-01, -2.35719651e-01,  1.17469370e-01, -3.16478997e-01,
       -3.32855791e-01, -5.60089834e-02, -1.13830596e-01,  2.99047232e-01,
        2.91303605e-01,  5.27353048e-01, -8.01359639e-02,  3.70589107e-01,
       -7.40349114e-01, -2.83805847e-01,  3.68620425e-01, -2.00662568e-01,
        2.06878036e-01,  3.59430045e-01, -4.72696304e-01, -5.20587787e-02,
        1.84647679e-01, -7.67576754e-01,  3.14276338e-01,  3.30369882e-02,
       -2.89829403e-01, -5.04404247e-01, -2.82459527e-01, -1.59139574e-01,
       -2.53923506e-01, -4.90085408e-02,  2.07283810e-01, -6.34046793e-02,
        1.15608480e-02, -1.31968185e-01, -4.46800500e-01, -1.18194029e-01,
       -7.59186745e-01,  6.48230791e-01,  2.17362732e-01, -7.57855028e-02,
       -6.97025657e-01,  6.05452538e-01, -4.99517232e-01, -3.96146029e-01,
        2.17520684e-01,  2.56881416e-01, -7.78038725e-02, -3.09449404e-01,
        1.77900404e-01,  3.45624536e-01, -4.23992902e-01, -6.17646798e-02,
        3.44126731e-01, -5.44108927e-01,  3.25085521e-02, -4.45615530e-01,
        2.88339555e-01, -5.48769653e-01,  1.49941398e-03, -5.00595212e-01,
        1.07758611e-01, -9.34083581e-01,  4.44628075e-02, -7.43618965e-01,
        9.43773612e-03, -2.03641266e-01, -4.21629697e-02, -8.56984019e-01,
       -3.53416979e-01, -1.37215659e-01,  2.37562373e-01,  2.22075641e-01,
       -4.47890580e-01, -3.37245166e-01, -4.41710740e-01,  4.07590300e-01,
       -4.29153919e-01,  2.70845443e-01,  6.22353077e-01, -1.88832119e-01,
       -3.70326281e-01,  9.68216285e-02, -1.81429461e-01,  1.43520966e-01,
       -2.26949677e-01,  2.31541142e-01, -1.68212682e-01, -3.40685397e-01,
       -5.51076114e-01, -1.60106614e-01, -3.89059335e-01, -4.66735095e-01,
        2.21342027e-01,  4.33169276e-01,  6.49007499e-01,  9.00622457e-02,
        4.56193805e-01,  1.55155763e-01, -2.08226472e-01, -3.36425402e-03,
       -3.54385436e-01, -2.29431808e-01,  3.75195473e-01, -1.01765022e-01,
       -6.04111910e-01, -1.54354587e-01, -5.16405106e-01,  2.68505305e-01,
       -3.09623718e-01, -3.85360986e-01,  5.49814284e-01, -2.73397177e-01,
        1.32074162e-01,  1.16216533e-01,  3.36495876e-01, -8.11513327e-03,
       -2.72762954e-01, -4.85629141e-01, -1.62442222e-01,  1.93489194e-01,
        4.87006575e-01, -4.97507632e-01, -2.88396686e-01,  4.16803986e-01,
       -2.31376722e-01, -5.07094920e-01,  1.28074124e-01, -3.07945222e-01,
        1.48071378e-01, -4.30116840e-02,  6.07838593e-02,  3.06150336e-02,
       -3.19084644e-01, -3.01885277e-01,  4.98854995e-01,  6.43056870e-01,
        7.13204145e-01,  6.83712140e-02,  2.70359486e-01, -6.04967713e-01,
       -2.10013047e-01, -4.44547012e-02,  1.98176309e-01,  3.78616929e-01,
       -1.81561455e-01,  1.29379436e-01, -1.34630026e-02, -2.06329152e-01,
       -9.43141524e-03, -1.17478333e-01, -3.32899868e-01,  7.89587274e-02,
       -7.09190890e-02, -3.96882147e-01, -5.46655655e-01, -1.59183949e-01,
        2.77427465e-01, -4.50306460e-02, -3.84529352e-01, -8.12325180e-02,
        4.54247802e-01,  5.89317083e-01,  3.03867370e-01, -2.71784782e-01,
       -2.91337252e-01, -5.32101989e-01, -4.53129917e-01, -6.41592383e-01,
       -7.28948534e-01, -5.01964986e-01, -7.61449337e-02, -4.51094300e-01,
        2.05944240e-01, -1.11441910e-01, -9.05503094e-01, -3.92875850e-01,
        5.39160483e-02, -6.32171214e-01, -4.57258523e-01, -4.36547875e-01,
       -4.60060805e-01,  2.55142987e-01, -1.49643660e-01,  2.09646925e-01,
       -8.15974772e-02, -2.95562446e-01, -3.28584433e-01, -4.58650351e-01,
       -6.91880360e-02,  3.50073576e-02, -4.02731031e-01, -5.24495900e-01,
       -8.16937268e-01, -7.93328732e-02, -1.00827046e-01, -6.36134520e-02,
        4.73623633e-01, -3.10529292e-01,  1.56846374e-01,  6.72302127e-01,
        2.96650767e-01, -6.40806496e-01, -4.42018002e-01, -3.23191673e-01,
       -7.25368857e-02, -2.33611569e-01, -9.68134031e-02, -4.62641641e-02,
        1.02689989e-01,  1.16326526e-01, -6.31111741e-01,  2.54917681e-01,
       -1.51661485e-01,  7.62109384e-02, -2.60092229e-01,  2.98398077e-01,
       -6.27944767e-01, -3.52523774e-01,  1.53563619e-01, -2.07943562e-02,
        5.97888947e-01,  3.90152872e-01, -3.51606309e-01, -5.91240406e-01],
      dtype=float32), array([0.35330257, 1.1699038 , 0.41089013, 0.32828784, 0.33638465,
       0.44306257, 0.32806444, 0.42288494, 0.31356812, 0.30263525,
       0.34014603, 0.5415866 , 0.77728164, 0.46732992, 0.40468052,
       0.5247451 , 0.38259456, 0.36576313, 0.533372  , 0.24782896,
       0.27385235, 0.33483723, 0.37083006, 0.7756319 , 0.47834113,
       0.48323444, 0.30290443, 0.5698107 , 0.6532905 , 0.69119275,
       0.3455445 , 0.42533767, 0.27475184, 0.96505505, 0.3309448 ,
       0.32816607, 0.5199502 , 0.36802253, 0.37865448, 1.4034266 ,
       0.49884182, 0.31379312, 0.6044584 , 0.6198131 , 0.6259758 ,
       0.30098632, 0.35843065, 0.3654879 , 0.58168185, 0.58326566,
       0.79009897, 0.3213436 , 0.47760278, 0.5099082 , 0.6113358 ,
       0.3641202 , 0.5477056 , 0.52435714, 0.3448351 , 0.7826837 ,
       0.73881483, 0.29217398, 0.45607385, 0.32762638, 0.35280386,
       0.45757446, 0.311919  , 1.2150369 , 0.65341276, 0.44931802,
       0.31249204, 0.7774954 , 0.3119076 , 0.46176013, 0.47449768,
       0.23223054, 0.29156935, 0.32479626, 0.4216033 , 0.35699284,
       0.29280686, 0.73485756, 0.49282768, 0.37488797, 0.3827437 ,
       0.5194374 , 0.37116346, 0.38593525, 0.42826992, 0.3165546 ,
       0.57531023, 0.53254354, 1.0625187 , 0.74314374, 0.3708762 ,
       0.5728158 , 0.73163337, 0.37739575, 0.37920654, 0.6987359 ,
       0.37229943, 0.42733583, 0.44294375, 0.2856226 , 0.7117653 ,
       0.4645714 , 0.40174994, 0.44423088, 0.7005628 , 0.3580913 ,
       0.4691342 , 0.3212859 , 0.6230959 , 0.42405576, 0.6304541 ,
       0.72534066, 0.661217  , 0.581898  , 0.3448227 , 0.3424445 ,
       0.32502598, 0.80127186, 0.4328197 , 0.28511366, 0.49159154,
       0.80698067, 0.9343856 , 0.5009293 , 0.44605693, 0.606974  ,
       0.4121953 , 0.30953535, 0.6390852 , 0.32379204, 0.41747013,
       0.56059676, 0.58763534, 0.28236526, 0.7019906 , 0.36724517,
       0.3053218 , 0.38026112, 0.5611686 , 0.51010776, 0.5583478 ,
       0.4651596 , 0.46625906, 0.4905391 , 0.36044785, 0.7196847 ,
       0.25043565, 0.7327894 , 0.951037  , 0.26947692, 0.41399413,
       0.33588657, 0.5904454 , 0.62531185, 0.33545497, 0.24400799,
       0.6727546 , 0.31359074, 0.6425408 , 0.38276228, 0.41896662,
       0.33469924, 0.5970024 , 0.61992   , 0.41131377, 0.6890591 ,
       0.54264134, 0.39464283, 0.33423367, 0.28174412, 0.26094204,
       0.47431508, 0.33713257, 0.64974576, 0.42219305, 0.29386055,
       0.3509828 , 0.84933895, 0.5500661 , 0.30153933, 0.36881095,
       0.53085554, 0.4258011 , 0.5539056 , 0.32439816, 0.53991354,
       0.5213169 , 0.63482267, 0.4482768 , 0.39045176, 0.43022567,
       0.27248955, 0.5322092 , 0.4108507 , 0.7828164 , 0.36198184,
       0.25905696, 0.6186709 , 0.34014493, 0.5418563 , 0.34780735,
       0.7604882 , 0.9483258 , 0.40619028, 0.5048781 , 0.6925983 ,
       0.52855074, 0.28238532, 0.5881725 , 0.2812009 , 0.3653314 ,
       0.3852164 , 0.41930127, 0.39786893, 0.3581859 , 0.69387275,
       0.31115386, 0.7200718 , 0.48746312, 0.48263133, 0.26596755,
       0.7256777 , 0.37908077, 0.3282636 , 0.4529184 , 0.47286257,
       0.633896  , 0.32427272, 0.30994686, 0.6775366 , 0.48245728,
       0.4604697 , 0.37154254, 0.3654397 , 0.30123976, 0.4040781 ,
       0.424497  , 0.29052612, 0.362579  , 0.29081553, 0.37880212,
       0.3140816 , 0.39517415, 0.35016745, 0.3372589 , 0.8098783 ,
       0.3976447 , 0.3626569 , 0.71893007, 0.2909439 , 0.5983573 ,
       0.35173392, 0.29005656, 0.2438199 , 0.69680583, 0.5784784 ,
       0.9095075 , 0.48816663, 1.0768747 , 0.6238333 , 0.56867915,
       0.5661415 , 0.33503506, 0.4006375 , 0.4081741 , 0.37629002,
       0.45702338, 0.28906506, 0.41578794, 0.2777636 , 0.770047  ,
       0.4624604 , 0.32277814, 0.4001847 , 0.5688428 , 0.2694487 ,
       0.35508162, 0.43556392, 0.6166197 , 0.4672093 , 0.8702562 ,
       0.47979608, 0.2539916 , 0.75011426, 0.34911463, 0.39221612,
       0.5895296 , 0.2915422 , 0.33980572, 0.35618776, 0.6487093 ,
       0.5112312 , 0.43075362, 0.30912656, 0.29508212, 0.30116117,
       0.2932112 , 0.30002245, 0.37648064, 0.3217424 , 0.37527665,
       0.54478544, 0.62476087, 0.5326422 , 0.4134497 , 0.50975996,
       0.46785986, 0.51577044, 0.27400044, 0.48186797, 0.40143728,
       0.29152164, 0.6353807 , 0.7075084 , 0.70600533, 0.40670764,
       0.67324966, 0.4288628 , 0.37722445, 0.36276466, 0.7121127 ,
       0.67847633, 0.37694684, 0.751532  , 0.6928921 , 0.58238727,
       0.36796373, 0.95193464, 0.34682935, 0.5329958 , 0.32879806,
       0.36362693, 0.26939413, 0.44579095, 0.27673748, 0.4552643 ,
       0.27349782, 0.4632588 , 0.4566889 , 0.44669586, 0.27618656,
       0.6473388 , 0.57071215, 0.29588157, 0.4821431 , 1.1468031 ,
       0.32500193, 0.64180464, 0.86717093, 0.44545865, 0.70281494,
       0.29756677, 0.5149197 , 0.3482504 , 0.49302626, 0.2879999 ,
       0.5623323 , 0.31131366, 0.5094437 , 0.6099974 , 0.46827728,
       0.32209823, 1.0320712 , 0.3413339 , 0.6067216 , 0.40090534,
       0.27235445, 0.8599787 , 0.34845573, 0.36335745, 0.41256964,
       0.3544656 , 0.60597914, 0.35799912, 0.274382  , 0.40036586,
       0.41525093, 0.63891864, 0.96808344, 0.4847402 , 0.9475319 ,
       0.528224  , 0.38709697, 0.27729625, 0.66340774, 0.37940875,
       0.52817446, 0.22844857, 0.4270591 , 0.31989977, 0.22828746,
       0.24283703, 0.3253078 , 0.35648766, 0.9562115 , 0.5630508 ,
       0.47300342, 0.46120602, 0.2934157 , 0.39483115, 0.43482408,
       0.90825367, 0.35620376, 0.27918112, 0.8840544 , 0.39252537,
       0.5029091 , 0.31190553, 0.26312163, 0.4524378 , 0.6891868 ,
       0.30464646, 0.2761789 , 0.2804045 , 0.28654718, 0.29593977,
       0.41008773, 0.4996792 , 0.47475687, 0.42842925, 0.43117112,
       0.4889991 , 0.41316116, 0.7871539 , 0.2976152 , 0.3243508 ,
       0.2974678 , 0.28861427, 0.23786291, 0.5486036 , 0.6820657 ,
       0.3990404 , 0.48481944, 0.48739022, 0.40525326, 0.26891294,
       0.49486527, 0.31766748, 0.43447185, 0.5536482 , 0.32480833,
       0.45085496, 0.9006942 , 0.31536278, 0.739205  , 0.7437251 ,
       0.6554254 , 0.30716178, 0.7501943 , 0.6808854 , 0.31716833,
       0.96761984, 0.47908458, 0.53259903, 0.31669244, 0.72309387,
       0.26990154, 0.4413719 , 0.67372906, 0.26123166, 0.3603956 ,
       0.39621598, 0.4279879 , 0.43347406, 0.30741453, 0.3099777 ,
       0.52944195, 0.4330568 , 0.2787463 , 0.33820626, 0.32474878,
       0.64245325, 0.34919667, 0.39871594, 0.46015978, 0.6307489 ,
       0.43273106, 0.35027567, 0.38588163, 0.29706332, 1.1938199 ,
       0.6213731 , 0.3707341 , 0.90840554, 0.32949895, 0.5007127 ,
       0.7199099 , 0.7660691 , 0.54270273, 0.5902791 , 0.3281783 ,
       0.34894416, 0.30788356, 0.3172597 , 0.28454357, 0.5549314 ,
       0.4054582 , 0.2422859 , 0.4961353 , 0.47911185, 0.27450687,
       0.3977537 , 0.28981885, 0.33602962, 0.67888224, 0.4747832 ,
       0.3196398 , 0.77164626], dtype=float32), array([[[[-1.2420695e-02],
         [ 5.8162826e-05],
         [ 2.2291953e-02],
         ...,
         [ 2.1749532e-02],
         [-1.1364623e-02],
         [-6.2003192e-03]],

        [[-2.7740484e-02],
         [-3.4965917e-03],
         [ 1.5692431e-02],
         ...,
         [-2.8935052e-02],
         [-1.1098565e-02],
         [-1.6710130e-02]],

        [[ 1.5796596e-02],
         [ 1.4375398e-02],
         [-4.5391177e-03],
         ...,
         [ 8.7305373e-03],
         [-2.1604216e-02],
         [ 4.1763806e-03]]],


       [[[ 1.5530554e-02],
         [ 1.2452046e-02],
         [-1.3613091e-02],
         ...,
         [ 2.8750209e-02],
         [-8.1034144e-03],
         [-3.2169200e-02]],

        [[-3.1583512e-03],
         [ 4.3900628e-02],
         [-2.1306297e-02],
         ...,
         [ 2.4362359e-02],
         [-6.5428186e-03],
         [ 4.0638834e-02]],

        [[-3.7875276e-02],
         [ 5.6773394e-02],
         [-7.6509796e-02],
         ...,
         [-2.2309750e-02],
         [ 3.3736397e-02],
         [-1.9194184e-02]]],


       [[[ 6.2338486e-02],
         [-1.7675281e-02],
         [-8.4278313e-03],
         ...,
         [ 1.8028423e-02],
         [ 3.3355545e-02],
         [ 1.1855535e-02]],

        [[-2.7940027e-02],
         [ 4.0281478e-02],
         [ 1.7526198e-02],
         ...,
         [ 3.5717539e-02],
         [-2.9431103e-02],
         [-1.9557273e-02]],

        [[-9.6722525e-03],
         [ 9.9780504e-03],
         [ 2.7627146e-02],
         ...,
         [-1.7008163e-02],
         [ 2.9469574e-02],
         [-1.8504776e-02]]]], dtype=float32), array([1.029156  , 1.0050931 , 1.0247016 , 0.9905753 , 0.991762  ,
       1.0534462 , 0.97652394, 0.9687134 , 0.9882599 , 1.0272099 ,
       0.9890129 , 0.96958804, 0.98449516, 1.0194896 , 1.0114588 ,
       0.9725841 , 1.0193835 , 1.0418099 , 0.9970721 , 1.0140789 ,
       1.0054379 , 1.0143257 , 0.96301556, 0.96989876, 1.0125952 ,
       1.040966  , 1.0195274 , 0.99821156, 0.99259394, 1.0161101 ,
       1.0614011 , 0.9810393 , 1.0320927 , 0.9930268 , 1.0193174 ,
       0.991097  , 0.9919367 , 0.9839073 , 1.0016314 , 0.9811208 ,
       0.982196  , 1.0064174 , 0.99584997, 1.0099446 , 0.9991475 ,
       0.98483956, 0.9889022 , 0.9962955 , 1.018488  , 1.0110991 ,
       0.98749435, 0.9936181 , 1.0185375 , 0.98381364, 0.9575293 ,
       1.0019407 , 0.96403223, 0.96349514, 1.0067177 , 1.0063685 ,
       0.9881837 , 1.0041274 , 0.98904324, 1.0147898 , 0.98917437,
       1.0156491 , 1.0086285 , 0.9969757 , 1.0062835 , 1.0094984 ,
       1.0145947 , 0.96286654, 1.0145882 , 0.99450547, 1.0179695 ,
       1.0241742 , 1.0302657 , 0.97597694, 0.99413735, 1.0169152 ,
       1.0186071 , 1.0126398 , 0.9731374 , 1.0260316 , 0.9794481 ,
       1.0343864 , 1.0158262 , 0.97687906, 1.0036753 , 1.0291502 ,
       0.9693663 , 0.97138584, 1.0146148 , 1.0405294 , 1.0300093 ,
       1.0060023 , 1.0145134 , 1.0031399 , 0.99066937, 0.96695167,
       1.0023503 , 1.020289  , 0.9579783 , 1.0234997 , 0.98143905,
       1.0172971 , 0.97064006, 0.97031635, 0.9812827 , 1.0231142 ,
       1.0097564 , 1.0095466 , 0.983025  , 1.0320268 , 0.9683425 ,
       1.0259095 , 0.9895055 , 0.9647904 , 1.0381284 , 1.0056362 ,
       1.012804  , 0.9873213 , 1.0251015 , 1.0295775 , 0.9943162 ,
       1.007947  , 0.9859147 , 1.0432005 , 1.0361959 , 1.0261216 ,
       0.99450785, 0.96180004, 0.9875134 , 0.9949491 , 0.97423923,
       0.9764904 , 1.0342968 , 1.0067832 , 0.9791675 , 1.0044985 ,
       0.9887256 , 1.0428957 , 0.9922709 , 1.0272791 , 1.0273569 ,
       0.9571601 , 1.0066447 , 1.0094472 , 1.054522  , 0.9935011 ,
       1.0068921 , 0.97301143, 1.0227088 , 1.0312146 , 0.981452  ,
       1.0455359 , 0.9829887 , 0.98913085, 1.0110768 , 1.0695736 ,
       1.0200483 , 0.98759234, 0.9972786 , 0.9872171 , 1.0350429 ,
       0.9687921 , 1.01437   , 1.0293704 , 1.0031682 , 0.9905176 ,
       1.0004163 , 1.0343219 , 0.9496971 , 1.0006348 , 1.010108  ,
       0.9884327 , 1.0247362 , 1.0059919 , 1.0185158 , 1.0487458 ,
       1.0120771 , 0.9989296 , 1.0044974 , 1.0123581 , 1.0049967 ,
       1.0318298 , 1.021986  , 0.98080826, 1.0045199 , 0.99374974,
       0.99679387, 1.0051349 , 1.0269148 , 0.99424064, 0.97273135,
       0.97427833, 1.0259217 , 0.96235466, 1.0038545 , 0.9815016 ,
       0.99197876, 0.994229  , 1.013902  , 1.0231706 , 1.0089058 ,
       1.0224663 , 0.99905765, 1.0364125 , 0.98682886, 0.9969885 ,
       0.9975937 , 0.98785263, 0.9813971 , 1.0119581 , 1.0191963 ,
       0.9872713 , 0.9706326 , 0.9877157 , 1.0180954 , 0.9990874 ,
       1.067549  , 1.0301585 , 0.97420025, 0.9990219 , 1.0418937 ,
       0.9905304 , 0.99792075, 0.9864166 , 1.0169406 , 0.9716939 ,
       1.0153481 , 1.0460393 , 1.0239657 , 0.99780154, 1.0089859 ,
       1.0332893 , 1.0116944 , 0.9761265 , 1.0097821 , 0.9780286 ,
       0.96236825, 0.99229336, 0.9585791 , 1.024061  , 0.97891086,
       1.034814  , 1.0324658 , 1.0202199 , 0.9768242 , 1.0124475 ,
       1.0529844 , 0.9601475 , 0.9833244 , 1.0101767 , 1.0024914 ,
       1.004318  , 1.0057478 , 1.0075595 , 0.97269934, 1.0031762 ,
       0.97316843, 1.0307828 , 0.97112024, 1.0199463 , 1.0172439 ,
       0.98338675, 1.0146277 , 1.0001704 , 0.9904011 , 1.0224303 ,
       0.97898513, 1.0048741 , 0.97759956, 1.0085033 , 0.99307466,
       0.9859103 , 0.99965715, 0.99283165, 0.9978101 , 0.99824274,
       0.99470836, 0.99777174, 1.0024878 , 1.0203626 , 0.9779653 ,
       1.047819  , 1.0233996 , 0.9904381 , 1.0388986 , 1.0460508 ,
       1.0052906 , 1.02528   , 0.9792754 , 0.94747263, 0.98761034,
       0.9947561 , 0.9642462 , 0.99591887, 1.0009972 , 1.0031214 ,
       1.0359838 , 1.043954  , 1.0224756 , 0.9871633 , 0.97398835,
       0.9708887 , 0.9886    , 0.99868846, 0.9886612 , 1.0396276 ,
       0.9933792 , 1.0011497 , 0.9996954 , 1.009319  , 1.0349329 ,
       1.0118735 , 0.9960576 , 1.0100011 , 0.96202505, 1.0207782 ,
       1.0109024 , 1.0160778 , 1.0137206 , 0.98916394, 0.9663597 ,
       1.0243752 , 0.98338675, 0.9849623 , 0.99260294, 0.9926357 ,
       1.0061232 , 1.0450376 , 1.0053314 , 1.0046111 , 0.99019325,
       0.9761391 , 1.0315297 , 0.95253307, 1.0313401 , 0.9872909 ,
       1.0080913 , 0.9679387 , 1.0278975 , 1.0204332 , 1.0198413 ,
       1.0096161 , 1.0019114 , 1.0429653 , 0.97895384, 0.98643035,
       0.9885468 , 0.9968185 , 0.9731265 , 0.9880439 , 0.9881669 ,
       0.99622583, 1.0038416 , 1.013617  , 0.9760403 , 0.98337376,
       0.9897434 , 0.9999723 , 1.0239452 , 0.986669  , 1.025568  ,
       1.0208057 , 0.9907703 , 0.9956891 , 0.9817038 , 0.99260145,
       0.9827588 , 1.0182449 , 0.9965424 , 0.9893647 , 0.9870027 ,
       0.999982  , 0.98058677, 1.0105919 , 1.0426036 , 0.99927217,
       1.0045474 , 1.0141248 , 1.0071812 , 0.99050134, 0.9923204 ,
       0.9937298 , 1.0047988 , 0.9837164 , 1.019092  , 0.98081017,
       0.990328  , 1.0272175 , 0.97430426, 1.0062758 , 0.9960236 ,
       1.0107039 , 1.0359595 , 1.0312537 , 0.990776  , 0.9759175 ,
       0.98604316, 0.9907437 , 1.0229816 , 0.96766824, 1.0148717 ,
       0.98375064, 0.95129305, 0.9998682 , 0.9966276 , 1.0026592 ,
       0.98739177, 1.0369942 , 1.0514429 , 1.001484  , 0.99214345,
       0.9773033 , 0.9921928 , 0.9945563 , 0.9752906 , 1.0003101 ,
       0.9920526 , 0.9638675 , 1.0450238 , 0.9716288 , 0.9911898 ,
       0.99141455, 1.0035249 , 0.99745363, 0.980669  , 0.98501486,
       1.0314503 , 0.99199015, 0.98906904, 1.0080731 , 1.0240252 ,
       1.0119246 , 0.99505275, 1.0069153 , 1.0090214 , 1.0331031 ,
       1.0040156 , 0.9762618 , 1.0241251 , 1.0024966 , 0.9916427 ,
       1.0230322 , 0.98275685, 1.0280743 , 0.9838411 , 0.9914249 ,
       0.98475796, 1.0117321 , 0.9593288 , 1.0294316 , 1.0171099 ,
       1.0231984 , 0.98852783, 1.0343443 , 1.0286775 , 0.9613994 ,
       0.9707289 , 0.9783165 , 0.99813646, 1.0301888 , 0.9969566 ,
       0.99084073, 1.006977  , 1.0021509 , 1.0445125 , 1.0092764 ,
       1.0158534 , 1.0055466 , 1.0412483 , 1.0060738 , 1.0000044 ,
       0.9853326 , 1.0033733 , 1.0342773 , 0.9747461 , 1.0199047 ,
       0.9574278 , 1.0103782 , 0.96590084, 0.98495615, 0.99903643,
       0.9903362 , 0.9929925 , 1.0020529 , 1.0257668 , 1.0469395 ,
       0.9917228 , 0.99098235, 1.0007414 , 1.0203205 , 0.9976415 ,
       1.0165099 , 1.0700845 , 0.9835897 , 1.0142848 , 0.975424  ,
       0.99728215, 1.0273556 , 1.0062225 , 1.0031763 , 1.0301374 ,
       1.0103352 , 1.0194105 , 1.0272154 , 0.98634034, 0.97980535,
       0.9949898 , 0.9874311 ], dtype=float32), array([-0.00469968, -0.03201555,  0.03711094, -0.00743953, -0.00090805,
        0.03186818, -0.01646838, -0.02094885, -0.01122413,  0.01964509,
       -0.0141394 , -0.02042313, -0.00931254,  0.01988521, -0.01179851,
       -0.02657264,  0.00661506,  0.01844108,  0.00445707, -0.01374775,
       -0.00765766, -0.00377913, -0.02892051,  0.00143925, -0.00936054,
        0.0082416 ,  0.02709579,  0.00940696, -0.00383565, -0.00428516,
        0.03884587, -0.00271636,  0.03180609, -0.0125933 , -0.00183386,
       -0.02545038, -0.0269167 , -0.00456326,  0.00754519, -0.01099186,
       -0.03006941, -0.01339971,  0.0221707 , -0.01897853, -0.00076346,
       -0.02590298,  0.00913757,  0.01077786, -0.02981783, -0.00919481,
       -0.02540158,  0.01268539,  0.00212619,  0.00492708, -0.01925771,
        0.00197711, -0.04886334, -0.03813857, -0.00321377, -0.00172209,
       -0.01101959, -0.00293552, -0.00071233,  0.01958083,  0.0160873 ,
       -0.00503344,  0.03334057, -0.01922656, -0.00495218, -0.00320304,
        0.03506958, -0.02168687,  0.00553676, -0.01095774, -0.00286279,
        0.00239688,  0.03990114, -0.00201913,  0.00537652, -0.00487649,
       -0.01205492,  0.02120699, -0.02915838,  0.02457223, -0.02215057,
        0.02273842,  0.0021666 , -0.00878792, -0.00171389,  0.043693  ,
       -0.00290106, -0.0050929 ,  0.01691243,  0.00780461, -0.00491438,
        0.01774754, -0.00263673, -0.01170802, -0.01295791, -0.01611549,
       -0.02563962,  0.02117218, -0.02587317,  0.02379137, -0.01318524,
       -0.02841382, -0.03179184, -0.01784346, -0.02299948,  0.01007127,
        0.014102  , -0.00597851, -0.0161844 ,  0.02200035, -0.02256274,
        0.00198545,  0.00316506, -0.02969579,  0.01679913, -0.0153231 ,
        0.02249442, -0.02017366,  0.00743882,  0.00098345,  0.01447017,
       -0.01075441, -0.01225398,  0.03244043,  0.03834464,  0.00846129,
       -0.01874827, -0.00510347,  0.00210287,  0.00115848, -0.0359062 ,
       -0.03517148,  0.02981944,  0.00942741, -0.01310993, -0.01672749,
        0.01252524,  0.02471961, -0.00576019,  0.02307467, -0.02728723,
       -0.03790819,  0.00617842, -0.03050298,  0.03620232, -0.01548165,
        0.01788391, -0.02960953,  0.01983627,  0.0059353 ,  0.01250077,
        0.02644849, -0.00707287, -0.01501486,  0.02436554,  0.03161739,
        0.00330761,  0.00669569,  0.01039557,  0.00817924,  0.03988566,
        0.00681861,  0.01748153,  0.01603603,  0.00731491,  0.00202363,
        0.01093974,  0.02210192, -0.03180888,  0.04082426,  0.03230758,
       -0.01846464,  0.02492228,  0.00293966,  0.01600885,  0.01862947,
       -0.01007492,  0.01550225,  0.03283106,  0.01076634, -0.01076331,
        0.03503553,  0.02405063, -0.0202324 , -0.00035478,  0.00421971,
        0.00550966, -0.01980222,  0.02050399, -0.01176419,  0.0112076 ,
       -0.03189762, -0.00085238, -0.01893728,  0.01009104, -0.02902035,
        0.02007011, -0.0145543 , -0.01511259,  0.02676442, -0.02109709,
        0.00543874,  0.03136199,  0.04458813, -0.02724098, -0.00885335,
        0.01721746,  0.01072896,  0.00053746,  0.00706421, -0.00118892,
        0.00249849, -0.00902553, -0.02250595,  0.00491593,  0.00144696,
        0.04246225, -0.01627705, -0.04046268,  0.00790265,  0.03570217,
       -0.0094735 , -0.03164819, -0.00364593,  0.0047609 , -0.0176867 ,
        0.00811588,  0.01679688,  0.00154475, -0.00022004,  0.03820868,
        0.00970536,  0.00360466, -0.01591357,  0.02804704, -0.0136851 ,
       -0.05898063, -0.00872325, -0.04345413,  0.02467555, -0.01017492,
        0.00632564,  0.02327817, -0.00425279, -0.02344058, -0.01720631,
        0.04142971, -0.01750006, -0.01138457,  0.00960667,  0.01920441,
        0.00394912, -0.01949765, -0.01228862, -0.01758939, -0.0152682 ,
       -0.01958512,  0.04311136, -0.01425861,  0.03779231, -0.00278593,
       -0.03129562,  0.01707164,  0.02656631, -0.01197007, -0.00177098,
       -0.03622226, -0.01646888, -0.015351  ,  0.00578595,  0.01343215,
       -0.00081124, -0.01367668, -0.01091388,  0.00526644, -0.02271225,
        0.00090939,  0.0062778 , -0.01325719, -0.02340885, -0.02052461,
        0.01165606,  0.01009341, -0.00275519,  0.00598899,  0.03050468,
        0.02312342,  0.02940198, -0.01326214, -0.05689169, -0.03118015,
        0.00706543, -0.02725315, -0.01943961,  0.03588339, -0.00050142,
        0.01296585,  0.01021832,  0.02784501, -0.02389036, -0.01357665,
       -0.0238453 , -0.02272389,  0.00448989,  0.00939509,  0.01763235,
       -0.02498676, -0.00959405,  0.01046577, -0.00144747,  0.01961504,
       -0.00355056,  0.00431421,  0.00070941, -0.03891387,  0.00221876,
        0.00333913,  0.01771676,  0.03502548, -0.01036042, -0.02982305,
        0.04690478,  0.00629829, -0.04701367,  0.00674714, -0.00606258,
        0.01836803, -0.00629558, -0.00071517, -0.00564322,  0.00779892,
       -0.01446337, -0.00418102, -0.0465335 ,  0.03042916, -0.01625901,
       -0.01628326, -0.02783162,  0.03434134,  0.03453176,  0.03209241,
        0.0300677 ,  0.01403765,  0.04296339, -0.02158325, -0.00434303,
       -0.01131748, -0.01337684, -0.02023936,  0.00299731,  0.00585235,
        0.0180721 ,  0.0181656 ,  0.01350192, -0.0053116 , -0.01568863,
        0.00226654,  0.00063605,  0.02415945,  0.0257585 ,  0.01819302,
       -0.00160818, -0.00310912, -0.01621805, -0.01988794, -0.03205296,
       -0.01210776, -0.00153752, -0.01849515,  0.00484695, -0.01386947,
        0.0127544 , -0.01197001, -0.00102219,  0.03164899, -0.00956597,
        0.00828956,  0.02073812, -0.00949459, -0.00412914, -0.0128231 ,
        0.03116549,  0.01179913, -0.00682911,  0.00691452,  0.00498806,
       -0.01994842,  0.02468899, -0.02007939, -0.00478703,  0.00744733,
        0.02543602,  0.0118239 ,  0.00955583,  0.02592817, -0.03203529,
       -0.0159405 ,  0.01096427,  0.01741389, -0.02551876,  0.01433715,
       -0.05494394, -0.04891318, -0.00369025,  0.00532776,  0.02658886,
       -0.01836707,  0.03641533,  0.03952925, -0.01274596,  0.03663853,
       -0.01679061,  0.00083113,  0.02562682, -0.03735254,  0.00826415,
       -0.01053454, -0.02366839,  0.01356373, -0.02349405, -0.00725205,
        0.00435245, -0.00086995,  0.01808369, -0.00137447, -0.02241522,
        0.02843958, -0.00200964, -0.02598884,  0.01074258,  0.02617631,
        0.00391138, -0.02642972,  0.01682122,  0.01560103,  0.02999584,
       -0.01526486, -0.01510255,  0.01026563, -0.0326812 ,  0.01463202,
        0.00286344, -0.01287018,  0.02985319,  0.00256725,  0.01741873,
        0.00118773,  0.03618757, -0.01625196,  0.00833172, -0.00713073,
        0.01686417,  0.01659815,  0.03215673, -0.01140137, -0.03960213,
       -0.03170832,  0.00300448,  0.0130516 ,  0.03369418,  0.0202373 ,
       -0.01090607,  0.00439273,  0.01100444, -0.0185405 ,  0.0013124 ,
        0.00958199, -0.0129293 ,  0.02582192, -0.01740457, -0.04226661,
       -0.03134027, -0.03158827,  0.03015538, -0.02663915,  0.0121769 ,
       -0.02153843, -0.00115905, -0.00205784,  0.02543876, -0.02305793,
       -0.01167194, -0.0012208 , -0.00578074,  0.00704364,  0.05197868,
       -0.00372218, -0.0044294 , -0.00662319,  0.0251871 , -0.00896975,
        0.02249737, -0.00417903, -0.00930474,  0.01514419, -0.02396102,
        0.01600161,  0.01737208,  0.0063892 ,  0.01407433,  0.04505391,
        0.00234722,  0.02443285,  0.03572549, -0.00637555, -0.01360978,
       -0.01402335, -0.01783881], dtype=float32), array([-5.59453946e-03,  4.86641414e-02, -1.29478546e-02, -2.06757430e-02,
       -2.42993589e-02,  3.04579292e-03, -3.43983322e-02, -2.11123154e-02,
       -1.68179739e-02, -9.87507962e-03, -6.34263456e-03,  2.11017719e-03,
        7.76282977e-03,  4.03352955e-04, -3.47056501e-02, -2.42026486e-02,
       -1.12202670e-02,  1.10642379e-02,  7.99806882e-03, -9.12047736e-03,
       -1.88629255e-02,  3.13466042e-03, -9.81586985e-03, -3.02807651e-02,
       -4.95352829e-03, -8.88068322e-03, -4.13918905e-02, -1.14128394e-02,
       -1.05323121e-02,  2.11608857e-02, -2.38120034e-02, -1.43414084e-02,
       -1.51869627e-02,  3.61359157e-02, -5.67848608e-03,  1.77850365e-03,
       -2.83741783e-02, -1.20562511e-02,  1.22689735e-03, -4.31865193e-02,
       -1.49302799e-02, -1.49909230e-02, -2.10793596e-02,  3.08125317e-02,
        1.33657306e-02, -2.71480624e-02, -7.55265728e-03, -1.38917444e-02,
        3.04621514e-02, -3.53391073e-03, -3.64766543e-04, -1.66688673e-02,
        1.17764333e-02, -2.77355127e-02, -3.51551957e-02, -2.17639189e-03,
       -9.00460593e-03, -1.78933609e-02, -2.84300689e-02,  7.42219342e-03,
        3.32420878e-02, -1.13511579e-02, -2.89497096e-02, -9.85345151e-03,
       -2.71063074e-02, -2.31554098e-02, -5.41571947e-03,  8.67721532e-03,
        4.71940525e-02, -2.01822221e-02,  9.23048612e-03,  1.77585334e-02,
       -1.38494540e-02,  2.22287048e-02, -3.36783975e-02,  7.44085154e-03,
       -5.97125059e-03, -1.56167690e-02, -1.89964159e-03, -3.43280262e-03,
       -1.91387739e-02, -1.24230562e-02, -1.73076317e-02, -7.89456256e-03,
        9.51709598e-03,  7.94133916e-03,  3.89374141e-03, -1.74233131e-02,
       -8.98294337e-03, -5.37825143e-03, -2.69435551e-02, -3.15451366e-03,
       -1.51538132e-02,  2.23255027e-02,  3.94970998e-02, -3.63860689e-02,
       -1.53483097e-02,  1.85564831e-02,  2.55620014e-03,  1.86006576e-02,
        1.10628139e-02,  3.13091502e-02,  3.19622904e-02, -1.83184687e-02,
        6.54758047e-03,  1.20297121e-02,  1.76586471e-02, -1.38989650e-02,
        4.61824797e-02, -4.83242283e-03, -1.14905350e-02, -8.50946736e-03,
        3.70590203e-02,  2.64598653e-02,  1.80206895e-02,  3.66687775e-02,
       -1.57234743e-02,  1.51138124e-03, -2.43268013e-02,  9.13294870e-03,
       -1.36268325e-02,  3.19264382e-02, -7.10591860e-03, -2.99691199e-03,
       -1.38607742e-02,  3.35425809e-02, -4.44082804e-02, -8.62270873e-03,
        1.27284201e-02,  2.27670968e-02, -3.50349508e-02, -9.66422353e-03,
       -3.87818888e-02, -5.83583629e-03,  3.44527164e-03,  9.35449637e-03,
       -2.18423679e-02,  6.59288699e-03, -3.64864878e-02, -1.18584260e-02,
       -2.44506774e-03, -2.07606656e-03, -2.19614916e-02, -1.20467832e-03,
       -1.42936287e-02, -2.64743157e-02, -3.19572836e-02,  2.00118776e-02,
        6.47848053e-03,  2.12735701e-02, -1.64874475e-02, -2.01137159e-02,
       -3.12302774e-03, -1.04724653e-02,  6.92528393e-03, -1.52529376e-02,
        1.22473286e-02,  6.06787112e-03, -1.83163360e-02, -1.64168943e-02,
       -1.32847326e-02, -1.26973446e-02, -1.35750463e-02,  4.29514516e-03,
        3.21081048e-03, -1.23166023e-02,  2.35741790e-02, -1.83685198e-02,
       -1.30195292e-02, -3.11983600e-02, -1.50081981e-02,  3.33480281e-03,
       -1.09874783e-02, -1.73793137e-02, -1.28397588e-02, -2.16611158e-02,
       -1.27963116e-02, -7.87096273e-04, -9.34718270e-03,  1.26013125e-03,
       -1.58022810e-02, -1.24250147e-02, -2.44033355e-02, -1.96457338e-02,
       -6.49265153e-03, -1.73961241e-02,  1.59960546e-04,  2.42456933e-03,
       -1.29549121e-02, -3.61223184e-02,  7.81332795e-03,  7.19353743e-03,
       -3.22787501e-02,  6.20671315e-03, -1.42191211e-02, -2.72335205e-02,
        8.43428914e-03, -3.66148241e-02, -1.61263831e-02, -4.40181494e-02,
       -2.91803963e-02, -1.41034024e-02,  6.30911067e-03, -1.29919611e-02,
        1.80990261e-03, -5.84133435e-04, -1.02645718e-02, -2.59696646e-03,
        2.67147645e-02,  4.04603295e-02, -5.77063113e-03,  1.16480526e-03,
       -1.29917050e-02, -2.21397858e-02, -1.80218183e-02, -1.14013087e-02,
       -2.00106613e-02, -3.49536128e-02,  2.51372308e-02,  4.24668659e-03,
       -6.05761679e-03,  2.53050923e-02, -1.27174919e-02, -1.59710720e-02,
       -2.38658860e-02,  1.25432201e-02, -2.28204299e-02, -3.65330116e-03,
        1.03334310e-02,  5.65374689e-03, -4.43122983e-02,  1.05048232e-02,
       -2.29364727e-03, -1.92826614e-02, -2.07404699e-02, -6.48691785e-03,
        9.83850006e-03, -2.09956001e-02, -4.38909838e-03, -5.82422363e-03,
       -1.81376990e-02, -1.79359298e-02, -3.37462537e-02, -6.31527582e-05,
        2.69547757e-03, -4.61872108e-03, -9.27806087e-03, -5.56084560e-03,
       -2.79698111e-02,  1.18794655e-02,  3.01050278e-03,  4.02622903e-03,
       -2.85652522e-02, -2.20479369e-02, -3.13121602e-02, -1.17288651e-02,
       -2.51355153e-02, -1.00022154e-02,  2.50931294e-03,  1.30795883e-02,
       -1.74891967e-02, -9.40782658e-04, -4.57622148e-02, -6.79299561e-03,
       -1.77143216e-02, -6.76900195e-03, -2.11902019e-02,  9.32496972e-03,
       -4.68013473e-02,  1.48350038e-02, -2.50380300e-03, -1.31398737e-02,
       -2.13837530e-02, -6.50005229e-03, -1.71118844e-02,  1.81601651e-03,
        1.84412790e-03, -7.85732362e-03,  3.59667614e-02, -1.03798388e-02,
       -1.72955524e-02, -8.02848488e-03,  1.78094662e-03, -6.41533756e-04,
       -1.00695994e-02, -6.53362134e-03, -2.56682001e-02,  4.91394009e-03,
       -1.63106192e-02,  3.95078864e-03, -4.90162428e-03, -8.29598866e-03,
       -1.94430295e-02, -5.83982933e-03,  2.56064329e-02, -2.97646858e-02,
       -3.41159254e-02, -2.21092887e-02, -1.96624380e-02, -1.41989700e-02,
       -3.28903552e-03,  2.58651841e-03, -1.86272953e-02, -1.56049514e-02,
       -1.05555886e-02, -1.86126418e-02,  3.07630356e-02, -8.59318394e-03,
        8.93109653e-04, -9.63444822e-03, -1.88545045e-03,  3.54410857e-02,
       -1.67883411e-02, -1.76542681e-02, -1.86262392e-02,  1.09416507e-02,
        3.60845239e-03,  4.91105504e-02, -1.28185907e-02, -8.53237603e-03,
       -1.98723674e-02, -1.69723462e-02, -1.23630809e-02, -1.10974070e-02,
       -1.26605062e-02, -3.38325128e-02, -2.31229234e-02, -8.18248000e-03,
       -2.40320377e-02, -4.36071632e-03, -2.27649193e-02,  2.23217383e-02,
       -1.99545026e-02, -2.27209646e-02, -4.50739078e-03, -2.86854673e-02,
        2.58205715e-03, -4.23743054e-02, -2.77736969e-02,  5.62370056e-03,
        9.54652205e-04,  3.47410259e-03, -3.65532674e-02,  8.00771522e-05,
       -1.92259531e-02, -3.06608342e-02, -1.52812386e-02, -5.15038380e-03,
       -1.87655538e-02, -1.25568155e-02, -6.53870637e-03,  2.09599230e-02,
       -2.23228037e-02,  8.20068456e-03, -2.18197834e-02, -1.65177472e-02,
       -1.31217549e-02,  5.32506453e-03, -1.21932290e-02, -4.63054553e-02,
       -1.79475024e-02, -1.35734761e-02,  4.68187733e-03, -3.03936936e-02,
       -1.52672101e-02, -3.57024185e-02, -2.86299195e-02, -4.22738343e-02,
       -7.85571150e-03, -9.56342276e-03, -3.08568403e-02,  2.66321432e-02,
       -3.42626236e-02, -1.59797743e-02, -9.09662712e-03, -2.43617775e-04,
       -2.65357681e-02,  1.49958469e-02,  1.03782834e-02, -2.06465945e-02,
       -2.23301779e-02, -1.57823525e-02,  1.48405749e-02,  2.92436685e-04,
       -2.78322250e-02, -1.39638586e-02, -1.00760954e-03,  8.30828771e-03,
        2.09445376e-02, -2.83086915e-02,  3.10585797e-02,  7.43291690e-04,
       -2.13660728e-02, -1.49306864e-03, -7.25873234e-03,  1.29583490e-03,
       -8.86113849e-03, -2.68170014e-02, -3.80210392e-02,  7.17263465e-05,
        2.11292244e-02, -8.52471869e-03, -1.28662703e-03, -1.17798895e-02,
        3.15361447e-03,  1.07248807e-02,  1.46025522e-02, -1.37733445e-02,
       -3.36626843e-02,  7.32837338e-03, -3.70374694e-02, -8.65208078e-03,
       -2.96520488e-03, -6.34357100e-03, -3.96832265e-02,  2.21835938e-03,
       -1.24958595e-02, -1.10153453e-02, -1.54992449e-03, -1.26941232e-02,
       -2.78038904e-03, -3.29216905e-02,  1.13395310e-03, -3.40894833e-02,
        7.85638054e-04, -2.49594636e-02,  7.97496643e-03,  2.50367951e-02,
       -1.40357185e-02, -2.19089612e-02, -4.85454500e-03, -8.89289845e-03,
        7.21038412e-03, -2.20221933e-02, -2.31796945e-03,  3.07734706e-03,
        9.82059631e-03, -1.36728501e-02,  1.36021925e-02, -1.04526244e-02,
       -1.15099866e-02, -3.87209728e-02, -3.50007713e-02, -2.19740206e-03,
       -1.72841852e-03, -1.69905890e-02, -3.15607972e-02, -1.78846978e-02,
       -2.10586116e-02, -1.46427145e-02, -4.16335836e-02, -5.40963374e-04,
       -2.12562419e-02, -1.82848535e-02,  1.98253663e-03, -1.11477785e-02,
        9.05125868e-03,  1.02602793e-02, -1.44963879e-02,  8.24875478e-03,
       -2.77785622e-02,  4.81604948e-04,  1.70214451e-03, -2.24639867e-02,
       -1.26578836e-02, -2.12364073e-04, -3.42384446e-03, -2.13747611e-03,
        1.99801545e-03,  1.08394502e-02, -1.63101703e-02, -3.32992673e-02,
       -1.08298054e-02, -1.15119731e-02, -1.26004787e-02,  2.91568716e-03,
       -1.48074385e-02, -2.33585089e-02, -5.19977475e-04, -2.91002057e-02,
       -1.73613336e-02,  1.38734793e-03, -3.59786712e-02, -2.47191656e-02,
        2.50864867e-02, -7.65048340e-03, -3.01902425e-02, -3.28650363e-02,
       -1.08058900e-02,  3.85536253e-03,  1.23577500e-02, -2.09407452e-02,
       -2.48444937e-02, -9.57027636e-03, -1.87484380e-02, -2.75301398e-03,
        4.44749510e-03,  2.47527864e-02,  2.43118475e-03,  1.47111528e-02,
       -1.83760133e-02, -5.27711934e-04, -2.15312000e-02, -2.10976670e-03,
       -1.28702875e-02, -1.18396981e-02,  4.61330637e-03, -9.83401388e-03,
       -3.98998596e-02,  2.37207096e-02,  6.46563480e-03, -8.51402897e-03],
      dtype=float32), array([0.00807725, 0.02071358, 0.00807241, 0.00829676, 0.00880717,
       0.00831909, 0.0093494 , 0.00945415, 0.00822079, 0.00795937,
       0.00780116, 0.00703699, 0.00698153, 0.00764436, 0.00862713,
       0.00724785, 0.00783917, 0.00764469, 0.00870876, 0.00829039,
       0.00806148, 0.00780095, 0.0071882 , 0.01088045, 0.00784346,
       0.00791648, 0.00867291, 0.00752218, 0.00867357, 0.01115649,
       0.0095266 , 0.00976621, 0.00849105, 0.01503119, 0.0079635 ,
       0.00863724, 0.00801021, 0.00781396, 0.00803989, 0.01765652,
       0.00746713, 0.00850853, 0.00771624, 0.01267894, 0.00752255,
       0.0112734 , 0.00854892, 0.00817606, 0.01147192, 0.00750424,
       0.00705037, 0.0081328 , 0.00798346, 0.0088298 , 0.01433596,
       0.00771269, 0.00719507, 0.00719739, 0.00905715, 0.00742236,
       0.01277248, 0.00832723, 0.01095867, 0.00770578, 0.009764  ,
       0.00822497, 0.00861943, 0.00715021, 0.01828627, 0.00802535,
       0.00884686, 0.00820401, 0.00870262, 0.01479235, 0.00852307,
       0.00843485, 0.00889951, 0.00770655, 0.00793997, 0.00800029,
       0.0080214 , 0.00757917, 0.00864634, 0.00922492, 0.0085422 ,
       0.00880485, 0.00769567, 0.00769913, 0.00767413, 0.00808271,
       0.00985701, 0.00902368, 0.00748943, 0.01288815, 0.00874125,
       0.01262843, 0.00936457, 0.0084271 , 0.00825561, 0.00903999,
       0.00780608, 0.00926235, 0.0092612 , 0.00852752, 0.00712203,
       0.01605829, 0.00850029, 0.01024956, 0.01846069, 0.0084688 ,
       0.00767984, 0.00766664, 0.01252932, 0.00872321, 0.00861208,
       0.01437414, 0.00730421, 0.00771814, 0.00919025, 0.00756678,
       0.00836427, 0.01139626, 0.00798637, 0.00939254, 0.00757653,
       0.01492729, 0.0181727 , 0.00824413, 0.00920503, 0.01051381,
       0.00959528, 0.0079292 , 0.01715931, 0.00797078, 0.00788675,
       0.00714474, 0.0077522 , 0.00980595, 0.01204733, 0.00801968,
       0.00758096, 0.0079372 , 0.01075905, 0.00774647, 0.00792671,
       0.00771952, 0.00807274, 0.00998886, 0.00855503, 0.01060451,
       0.00840071, 0.00754259, 0.00738024, 0.00842218, 0.00729799,
       0.00814698, 0.00902117, 0.00812312, 0.00835248, 0.00842553,
       0.00753102, 0.00769636, 0.00731478, 0.00842198, 0.00842407,
       0.00779147, 0.00764587, 0.00810695, 0.00884609, 0.01214586,
       0.00816084, 0.00776476, 0.00704783, 0.00820119, 0.00818745,
       0.00765665, 0.00880651, 0.0083814 , 0.00909708, 0.00902415,
       0.00787705, 0.00737379, 0.01035217, 0.00832737, 0.00763412,
       0.00762102, 0.00833626, 0.00747486, 0.00789993, 0.01092103,
       0.01312389, 0.00742328, 0.00917622, 0.00892934, 0.00830894,
       0.00782355, 0.00835123, 0.00807198, 0.01065721, 0.01041231,
       0.00882546, 0.00738577, 0.00762809, 0.01064981, 0.00795996,
       0.0075865 , 0.00721548, 0.00799211, 0.00753408, 0.01455093,
       0.0076775 , 0.00888754, 0.00723547, 0.00843619, 0.00829826,
       0.00854727, 0.00716664, 0.01066028, 0.0086794 , 0.00764287,
       0.00982545, 0.01334709, 0.00922466, 0.00777394, 0.00956267,
       0.00737608, 0.0088769 , 0.00775891, 0.00794947, 0.0073025 ,
       0.00883716, 0.00910816, 0.00911884, 0.00893852, 0.00818701,
       0.00758467, 0.00796993, 0.00734795, 0.00769553, 0.00947724,
       0.00705312, 0.00839652, 0.00794614, 0.0084418 , 0.0074393 ,
       0.00824893, 0.00887902, 0.00907356, 0.00767641, 0.01054911,
       0.00823859, 0.00741191, 0.00755819, 0.00855091, 0.01170802,
       0.00830143, 0.0097787 , 0.00810252, 0.00710806, 0.00946906,
       0.00714872, 0.00767975, 0.01718602, 0.01192938, 0.00782042,
       0.00894811, 0.00866914, 0.0076885 , 0.01120045, 0.00826056,
       0.00805669, 0.00817034, 0.00823539, 0.00792094, 0.00937648,
       0.00738214, 0.00815865, 0.0082386 , 0.01248674, 0.00836741,
       0.00972853, 0.00908229, 0.00822521, 0.0074896 , 0.00816635,
       0.00871519, 0.00883885, 0.00970848, 0.00797972, 0.00864578,
       0.00713288, 0.00849695, 0.00791913, 0.00743812, 0.01080409,
       0.01243902, 0.00991867, 0.00905783, 0.00777652, 0.00966194,
       0.00799009, 0.00777263, 0.01132553, 0.00815598, 0.00758642,
       0.00812298, 0.00741856, 0.00754966, 0.00738663, 0.0079056 ,
       0.01230768, 0.01290805, 0.00813719, 0.00763876, 0.00881195,
       0.00835087, 0.00737798, 0.01962134, 0.00752305, 0.00780701,
       0.00772999, 0.0088222 , 0.00798868, 0.00760618, 0.0069529 ,
       0.0122658 , 0.01068048, 0.00711291, 0.00787221, 0.00786333,
       0.00894483, 0.01505404, 0.00753848, 0.00881885, 0.00745703,
       0.00931264, 0.00855736, 0.01295416, 0.00906543, 0.00850872,
       0.00825234, 0.0118981 , 0.01144888, 0.00793183, 0.00857234,
       0.00820644, 0.01019745, 0.00839841, 0.00797982, 0.00703102,
       0.00730539, 0.00741291, 0.01110577, 0.00716925, 0.0142233 ,
       0.00773229, 0.00767635, 0.00939873, 0.00839813, 0.01253459,
       0.00751376, 0.00785807, 0.00839466, 0.01239021, 0.00840716,
       0.00858193, 0.01098996, 0.01017199, 0.00741768, 0.00862548,
       0.00912243, 0.01133295, 0.00881864, 0.00857515, 0.00868823,
       0.00800162, 0.00811613, 0.00890273, 0.00841654, 0.01126614,
       0.00873422, 0.00854785, 0.01119487, 0.00747513, 0.01088827,
       0.00727407, 0.00800739, 0.00827759, 0.00753748, 0.00799012,
       0.01024119, 0.00883304, 0.00726442, 0.0078189 , 0.00864658,
       0.00798056, 0.00825148, 0.00855438, 0.01366635, 0.00739935,
       0.00897942, 0.01062658, 0.00807266, 0.00751212, 0.00848773,
       0.00713109, 0.0079963 , 0.0081862 , 0.01309017, 0.00797499,
       0.00775523, 0.00837299, 0.00877545, 0.00819767, 0.01408658,
       0.0075314 , 0.00801755, 0.00803292, 0.00809374, 0.00831516,
       0.00728068, 0.01059039, 0.00829746, 0.01113446, 0.00809996,
       0.00851247, 0.00781675, 0.00742136, 0.0078811 , 0.00866418,
       0.00874668, 0.00797489, 0.00813727, 0.00798941, 0.00747209,
       0.01124417, 0.00759678, 0.00791391, 0.0081585 , 0.00928856,
       0.01344906, 0.01027263, 0.00844311, 0.01074155, 0.00805545,
       0.00817494, 0.00758086, 0.0088313 , 0.00902363, 0.0114709 ,
       0.0162549 , 0.00825146, 0.00724   , 0.00760398, 0.00796534,
       0.00772941, 0.00734789, 0.00841843, 0.00802267, 0.00710791,
       0.00840314, 0.00702536, 0.00751288, 0.00925454, 0.00794932,
       0.00772386, 0.00746707, 0.0075838 , 0.00855409, 0.00834427,
       0.0077647 , 0.0109986 , 0.00786694, 0.00848359, 0.00759884,
       0.0075897 , 0.00791729, 0.00807703, 0.00746201, 0.00823038,
       0.00729211, 0.00803213, 0.01215313, 0.0082825 , 0.01207436,
       0.00738653, 0.00959972, 0.01212088, 0.01096011, 0.00777395,
       0.00737763, 0.00726986, 0.01023403, 0.00762609, 0.00793419,
       0.00998204, 0.00889963, 0.00919753, 0.00909304, 0.00903103,
       0.00903345, 0.00869257, 0.00752784, 0.00811869, 0.00819047,
       0.00760656, 0.00824867, 0.008665  , 0.01365715, 0.00921754,
       0.00779298, 0.00692926], dtype=float32), array([[[[-0.09873605,  0.08369397, -0.01378741, ...,  0.10035302,
          -0.01404336,  0.02829582],
         [ 0.01625932, -0.00425865,  0.07257545, ..., -0.03066485,
          -0.05351934, -0.08534622],
         [-0.04852691, -0.00439191,  0.03902211, ..., -0.02562151,
          -0.01056387,  0.01849638],
         ...,
         [ 0.05306219, -0.05247302,  0.03013214, ...,  0.02692844,
          -0.04755503, -0.00145934],
         [ 0.00660946, -0.09190729,  0.0986666 , ..., -0.02536872,
          -0.08858749, -0.00061641],
         [-0.01561864, -0.01078072, -0.02111041, ..., -0.06422694,
           0.06415337,  0.03931661]]]], dtype=float32), array([1.0013621 , 0.96063656, 1.0211922 , 1.0069901 , 1.0320138 ,
       0.97943306, 1.0369709 , 1.0222191 , 0.9931992 , 0.9997658 ,
       1.0046487 , 0.9818006 , 0.9758801 , 1.0005121 , 0.9972372 ,
       0.996804  , 0.99597055, 1.006908  , 0.9956653 , 1.0330858 ,
       1.0451343 , 0.97728014, 1.0039868 , 1.0146401 , 0.9891486 ,
       1.045054  , 1.0147914 , 1.0513474 , 0.9653644 , 1.0059737 ,
       1.0123771 , 1.0179462 , 1.0132009 , 0.9962316 , 1.0224018 ,
       0.9985717 , 0.9945767 , 0.99099684, 0.9960665 , 0.9949231 ,
       1.040291  , 0.98836184, 0.966213  , 1.0035857 , 1.0322772 ,
       0.97013146, 1.0123793 , 1.0066586 , 0.9930776 , 0.9934115 ,
       1.0010178 , 1.0340458 , 1.0107242 , 1.0012023 , 1.0231042 ,
       0.9827034 , 1.001411  , 0.99755836, 0.98623204, 1.0216255 ,
       0.9959182 , 1.0105596 , 1.051416  , 1.00961   , 0.9876612 ,
       1.0062168 , 0.96864605, 0.9942247 , 1.0067335 , 1.0152338 ,
       1.004373  , 1.0012286 , 1.0283991 , 0.9960608 , 1.0272095 ,
       0.9987872 , 1.0133257 , 1.008187  , 0.9995272 , 0.99446386,
       1.026753  , 0.96138364, 0.9667238 , 1.0037773 , 0.99249536,
       1.0060736 , 1.0083461 , 1.0211234 , 0.99900377, 0.98459953,
       0.981348  , 1.0065447 , 0.98129284, 1.0192541 , 1.0391364 ,
       1.0231419 , 1.0165998 , 1.0133457 , 0.9825937 , 1.0114938 ,
       1.0359459 , 0.9947696 , 1.0078192 , 0.99143547, 0.9843643 ,
       0.9959534 , 1.0030285 , 1.0096456 , 1.0080488 , 0.9956179 ,
       0.9747563 , 1.0195723 , 1.0425901 , 0.997479  , 1.0249813 ,
       0.9809676 , 1.0290326 , 0.9934523 , 0.9993571 , 1.0045295 ,
       1.0271008 , 1.0160819 , 1.0190877 , 1.0394062 , 0.96139026,
       0.97219753, 0.97882295, 1.015356  , 0.9938369 , 0.9693099 ,
       1.003506  , 1.0114766 , 1.0047824 , 0.98858386, 1.0232047 ,
       1.0231991 , 0.9940516 , 1.0083649 , 0.9889939 , 1.0188369 ,
       1.0179559 , 0.99020666, 0.9756702 , 1.0176796 , 0.9996691 ,
       1.0337558 , 1.0073949 , 0.9978536 , 1.0071927 , 1.0028547 ,
       0.99886465, 1.0162779 , 0.98284096, 1.037388  , 1.0288212 ,
       1.0261327 , 1.0097126 , 1.0290239 , 1.0033702 , 1.0051147 ,
       1.0091001 , 1.0135951 , 0.9758697 , 1.0135521 , 1.0371221 ,
       0.98376805, 1.0314289 , 1.0310272 , 0.9889632 , 1.0027411 ,
       1.0060515 , 1.0056714 , 1.0372703 , 0.9881788 , 1.0281988 ,
       1.0094132 , 0.9865647 , 1.0360646 , 0.9902266 , 0.9872499 ,
       0.98364085, 1.0242206 , 1.014754  , 1.0027977 , 0.9994251 ,
       0.99372345, 1.0080252 , 1.0111448 , 1.0229852 , 0.9819156 ,
       0.98543507, 1.0020759 , 0.9999194 , 1.0464438 , 1.0106506 ,
       1.0187964 , 1.0236967 , 0.9934301 , 1.0098633 , 1.0471884 ,
       0.99259144, 1.0009838 , 0.9861209 , 0.97083735, 0.99938625,
       1.0255063 , 1.0002745 , 0.9974033 , 1.0345523 , 0.9785239 ,
       1.021416  , 1.056149  , 1.0055612 , 1.017753  , 0.99414027,
       1.014848  , 0.98411024, 0.9787589 , 0.96267635, 1.0389605 ,
       0.9791777 , 0.98967606, 1.086343  , 0.98664635, 0.99241453,
       1.0413827 , 1.0227998 , 1.021156  , 1.0248427 , 1.0429564 ,
       1.0249741 , 0.98568493, 1.0063496 , 0.97753054, 0.99216187,
       0.99846745, 0.99538386, 0.9657104 , 1.0044671 , 1.0041571 ,
       1.0122864 , 0.9911094 , 0.96176624, 1.0220081 , 1.0101182 ,
       1.0209576 , 0.9917216 , 1.0214217 , 1.0176013 , 0.9986749 ,
       1.0128603 , 1.007592  , 0.9997924 , 1.0220906 , 1.0155401 ,
       1.0111033 , 1.052179  , 0.96638566, 1.0050781 , 1.0140493 ,
       1.0241479 , 1.0386897 , 1.0300148 , 0.99277335, 1.0031221 ,
       1.0444585 , 1.0368122 , 1.0149224 , 1.0131131 , 0.9736555 ,
       1.0150833 , 1.0164156 , 1.0018363 , 1.0384767 , 1.000622  ,
       1.0260355 , 1.0126247 , 1.0034969 , 0.9994364 , 1.0522417 ,
       0.9818558 , 0.9819192 , 0.9971024 , 0.9862977 , 1.0179757 ,
       1.0178947 , 1.0624927 , 1.0236849 , 1.0236658 , 0.99346656,
       0.99840385, 0.96896785, 0.98584855, 0.998516  , 1.0156987 ,
       0.9989116 , 1.0147682 , 1.0124781 , 1.0226644 , 0.9856246 ,
       1.033443  , 0.9993228 , 1.0272845 , 1.0365928 , 0.97551   ,
       1.0301087 , 1.024712  , 1.0442863 , 0.99890435, 0.99490714,
       0.97204053, 0.9964249 , 1.0087494 , 1.0446453 , 1.0295193 ,
       1.0120347 , 1.0027411 , 1.0102788 , 1.0220516 , 1.0008657 ,
       0.97989196, 1.0088873 , 0.9825754 , 0.992735  , 0.9830384 ,
       0.9889392 , 1.0060025 , 1.032047  , 0.9981417 , 0.9905284 ,
       1.0058634 , 1.0182664 , 0.98623145, 1.0024809 , 1.0265162 ,
       0.9575604 , 0.9937706 , 1.0026481 , 1.0222862 , 1.0152333 ,
       1.0141137 , 1.0331368 , 1.0025568 , 1.0037988 , 0.98783696,
       0.99984294, 1.0074768 , 1.0084329 , 1.0128654 , 0.9973006 ,
       1.0058348 , 1.0002176 , 0.9889809 , 0.99941427, 0.9904371 ,
       0.966015  , 1.0126916 , 0.9872168 , 0.9919804 , 0.9803617 ,
       1.021008  , 1.0088253 , 1.0066334 , 0.9845927 , 1.0119891 ,
       1.0115359 , 0.9910364 , 1.0211823 , 1.0065206 , 1.0188471 ,
       0.9612621 , 1.0148784 , 1.0061047 , 1.0140715 , 0.95744115,
       0.99799556, 1.0398084 , 0.9846474 , 1.0080769 , 1.0241073 ,
       0.9904732 , 1.0153613 , 1.0387491 , 1.0375149 , 0.9767487 ,
       1.012953  , 1.0029262 , 1.0000913 , 0.9799893 , 1.0141945 ,
       0.9950219 , 1.0295581 , 0.9866127 , 1.0024041 , 1.0066015 ,
       0.96996605, 1.010909  , 1.009538  , 0.9911317 , 1.0212476 ,
       1.0143448 , 1.0007772 , 0.9976769 , 1.0142839 , 0.9882726 ,
       1.0085307 , 1.0175393 , 0.9812645 , 0.9992637 , 0.990302  ,
       1.0578153 , 1.0620036 , 1.0370452 , 1.0151385 , 1.0379151 ,
       1.001037  , 1.025131  , 0.9874098 , 1.0201231 , 1.0185329 ,
       0.9906102 , 0.99679744, 1.0056034 , 1.0025533 , 1.0218288 ,
       1.0248585 , 0.99459976, 1.0178096 , 1.0421225 , 1.0520794 ,
       1.006477  , 0.9990262 , 1.0823131 , 0.9581278 , 0.9995259 ,
       1.0032144 , 0.99010426, 0.9978881 , 0.99133795, 1.0207598 ,
       1.0046802 , 1.0410452 , 1.0045936 , 1.031443  , 1.0698767 ,
       0.9885484 , 1.0286762 , 1.0146544 , 0.9695386 , 1.0129358 ,
       0.9932937 , 1.01378   , 1.0140957 , 1.0404736 , 1.0376289 ,
       1.0026844 , 1.030785  , 1.003438  , 1.0174358 , 1.0319147 ,
       1.0215033 , 1.0125198 , 1.0243657 , 1.0089842 , 0.99686736,
       0.99762696, 0.99884117, 1.0197159 , 0.9859859 , 1.034092  ,
       0.9763277 , 1.0428686 , 0.9933008 , 0.98899657, 1.0516846 ,
       0.9932146 , 0.9857545 , 1.0102453 , 1.0251513 , 0.9888147 ,
       1.0056274 , 1.048409  , 1.0135528 , 1.019328  , 0.97588634,
       1.006264  , 0.9913969 , 1.0234236 , 1.0081316 , 1.0841994 ,
       1.0166445 , 0.9983559 , 0.97873455, 1.0030602 , 1.0243355 ,
       0.99804574, 0.9794017 , 0.99758494, 0.9869137 , 0.9991971 ,
       1.0264217 , 1.0285448 , 0.974039  , 1.0458142 , 1.0111735 ,
       1.0213208 , 1.0196121 , 1.0207317 , 0.9585405 , 1.0208244 ,
       1.0131742 , 0.98295194], dtype=float32), array([ 0.01344112,  0.03295628, -0.0063782 ,  0.00787583,  0.01136376,
       -0.01044771,  0.01539711,  0.02242988, -0.00475591, -0.00770505,
        0.01016982, -0.0301284 ,  0.04236482, -0.02978749, -0.00737921,
       -0.00309541,  0.05776173, -0.02131185,  0.00217919,  0.00215811,
        0.01672183, -0.05350551, -0.0134323 ,  0.00550064, -0.02914852,
       -0.00047371,  0.02759508,  0.03909612,  0.005689  ,  0.00318539,
        0.02819153,  0.0190952 , -0.0246297 ,  0.02026511,  0.02913461,
        0.02473748,  0.0105226 ,  0.02327528,  0.0072019 , -0.03338786,
        0.01556453,  0.00052537, -0.00585872, -0.01927053,  0.00597864,
       -0.03152886, -0.0151167 ,  0.02091877, -0.00415694,  0.00416985,
        0.01553275, -0.01320038, -0.0055781 ,  0.03038023,  0.02193463,
       -0.02732369,  0.00025807, -0.01842414, -0.00252622, -0.00609366,
        0.00420353,  0.01154957, -0.00279878,  0.03747397, -0.00675424,
        0.02460461, -0.03614867,  0.04615599, -0.00423521, -0.02160093,
       -0.00777237,  0.00652698, -0.00412979, -0.01956741,  0.01577754,
        0.01905336, -0.01197737,  0.01208729, -0.00157419,  0.02199644,
       -0.00755118, -0.02772605, -0.05166874,  0.01262353,  0.00713372,
       -0.01926389,  0.00728733,  0.00491818,  0.00392791, -0.03839881,
        0.01448615, -0.00464836,  0.00568867,  0.00932467,  0.01556787,
        0.01021269,  0.01491457,  0.02647797, -0.02810298,  0.03557976,
        0.01548388, -0.00339695,  0.01424374, -0.02216895, -0.01243499,
       -0.03963228, -0.01853729,  0.01674888,  0.00525338,  0.01475024,
        0.01799025,  0.00621468,  0.03083566,  0.01725953,  0.03099487,
       -0.00898761, -0.00793062, -0.0263011 ,  0.00420865, -0.00928745,
       -0.00405319,  0.04339765,  0.00659187,  0.02706097, -0.01362507,
        0.00925932,  0.02029419, -0.01641348,  0.00327453, -0.03348816,
        0.00424888,  0.00094345, -0.00153226, -0.01355699,  0.00490096,
       -0.0131501 ,  0.00117427, -0.00125329, -0.02456582,  0.00423827,
       -0.01152554,  0.01027468, -0.00731381,  0.02207966,  0.01496171,
        0.02566485,  0.01015318, -0.01008633, -0.01167087,  0.03128134,
        0.00229239, -0.0100636 ,  0.00636414,  0.01172738,  0.00180527,
       -0.02087118, -0.00842217,  0.02414258,  0.02744075, -0.02009908,
        0.01974703, -0.00793081, -0.00770028, -0.00292584,  0.01195905,
       -0.01151461,  0.01585505,  0.00703792,  0.00018781, -0.00698987,
        0.01131081,  0.0113174 ,  0.03284607,  0.00563441,  0.03946725,
        0.03004764, -0.02697647,  0.00731034,  0.02883893,  0.00170484,
       -0.02711303,  0.01623812,  0.01590673, -0.02413511,  0.00745715,
        0.01500414,  0.01114679, -0.03047536, -0.02443263, -0.01244992,
       -0.01733043, -0.00293166,  0.00821744,  0.03032758, -0.00263677,
        0.01132068, -0.01444656,  0.00910737, -0.00372471,  0.00267461,
       -0.0278219 ,  0.01422956, -0.01573285, -0.03066115, -0.02405892,
        0.0051283 ,  0.01703984,  0.00198905,  0.01745219, -0.00337729,
        0.01307523, -0.01664988,  0.00176346,  0.02508783, -0.00042277,
        0.01383524,  0.01960391, -0.0232513 , -0.01063699,  0.01852905,
       -0.01689397, -0.00102811, -0.01653082, -0.01462373,  0.01297049,
        0.03243741, -0.0278864 ,  0.01508964,  0.03178753,  0.0011565 ,
       -0.01087124,  0.00104301,  0.00288998,  0.01799086, -0.01975383,
       -0.00735797,  0.02120692, -0.02224068,  0.01139215,  0.00322069,
       -0.02019889,  0.01565886, -0.01316556,  0.00365203, -0.00021434,
        0.02039606,  0.01049646,  0.02734569, -0.00587569,  0.00193617,
        0.00841714,  0.00073667,  0.02081166, -0.00423264,  0.01230075,
        0.02832582,  0.00596515, -0.01945837,  0.01357524, -0.03167022,
       -0.00609299,  0.01058282,  0.00832027,  0.00679581, -0.00945241,
        0.00239332, -0.00522648,  0.00358227,  0.01427617,  0.01452356,
       -0.01752684,  0.04515188,  0.00088362, -0.02602781, -0.00055698,
        0.00220932, -0.0023975 ,  0.02586959, -0.03135144,  0.01135659,
        0.0061635 , -0.01038534,  0.00332153,  0.00777033,  0.03321478,
       -0.01367577,  0.045369  , -0.00359478, -0.00681466, -0.04481535,
        0.0108302 , -0.00368024,  0.0003252 ,  0.00376929,  0.00144478,
        0.01149639, -0.01018372, -0.002381  ,  0.02174414,  0.02324656,
       -0.00283309,  0.00390609,  0.04165665, -0.01962009, -0.03416907,
       -0.01183124,  0.02439085,  0.0203505 ,  0.01873357, -0.00760393,
       -0.01272147, -0.0281196 ,  0.01081401,  0.00208393,  0.01231341,
        0.00674677,  0.00884196,  0.01390281,  0.02790572, -0.024011  ,
       -0.01932194,  0.05016965, -0.01309782,  0.00880037, -0.03426485,
        0.03961397,  0.02929175,  0.0198343 ,  0.02326196, -0.00441233,
       -0.00880446,  0.01770285, -0.01443166,  0.02925007, -0.00454973,
        0.02531487,  0.00098556,  0.00617131,  0.02247829,  0.01126532,
        0.00075925,  0.02580822, -0.0086308 , -0.00075905, -0.03314508,
        0.02703559,  0.01788714,  0.03231857, -0.01742764, -0.01320618,
        0.00489922, -0.03522879,  0.01842269,  0.0230963 , -0.0148477 ,
       -0.04428452, -0.0131729 ,  0.00213637,  0.01316335,  0.02117013,
        0.01352798,  0.01989756, -0.00226885, -0.02292167,  0.01357975,
        0.00015497, -0.02502099,  0.02693142, -0.0090879 ,  0.02436293,
        0.00258898,  0.01099329,  0.02623765, -0.00527584, -0.01657194,
       -0.01144246,  0.02085661, -0.01913629, -0.00689336,  0.04971185,
       -0.00808793,  0.00044866,  0.04398584,  0.04014562,  0.01755266,
        0.01495288,  0.0158189 ,  0.04406786,  0.00230319,  0.00123601,
        0.00571794, -0.00607674, -0.01348248, -0.00403679, -0.01675641,
        0.00699476, -0.01515709,  0.00216252,  0.01970589,  0.01100782,
        0.01281889,  0.01524009,  0.00494065, -0.01446264,  0.01437403,
       -0.01388998, -0.01695323, -0.01674507, -0.00960252, -0.02822799,
        0.00994354,  0.03707331,  0.04596439, -0.00054511,  0.01694702,
        0.04031551, -0.01806105,  0.04203028, -0.00950424,  0.00547802,
        0.01196668,  0.01891789, -0.01210081, -0.00567648, -0.02253222,
       -0.00915455,  0.00950035, -0.01284586,  0.02574449,  0.03710779,
       -0.02702564, -0.00469914,  0.00012865,  0.02718951,  0.00145697,
       -0.00422545,  0.0125742 , -0.0174507 , -0.01203377,  0.02143744,
       -0.00687902,  0.00579463,  0.00707098,  0.00413414,  0.01356654,
        0.00184978, -0.00330274,  0.00977198, -0.01121375,  0.00402843,
        0.01506928,  0.01902206, -0.01307112, -0.0028261 ,  0.02333737,
       -0.01471695,  0.01117107, -0.00376935, -0.01708443, -0.00924709,
       -0.01201568, -0.0037602 , -0.00213557,  0.00396742, -0.01720291,
       -0.00029167, -0.00790332, -0.01282688,  0.00089724,  0.0149393 ,
        0.00458978,  0.02928244, -0.01583552,  0.01724209,  0.01416034,
        0.00196275, -0.00019652,  0.00953977,  0.00434921, -0.02948802,
        0.02051578,  0.00185338,  0.03667118,  0.04252016, -0.02138664,
        0.04190531,  0.04284038,  0.04810815, -0.00546053,  0.03431505,
       -0.01485352,  0.01497179,  0.00156509, -0.02507975,  0.00448959,
       -0.00494225, -0.01770576, -0.00141851, -0.00508876, -0.02347484,
        0.00732499,  0.01474181,  0.02091604, -0.0171437 ,  0.01119018,
        0.00829695,  0.01029407,  0.00649262,  0.02030405,  0.03724983,
        0.04047162,  0.00453801], dtype=float32), array([ 1.37214690e-01, -5.90836167e-01, -1.15056492e-01, -5.43109357e-01,
        4.08151001e-01, -1.18544948e+00, -3.77454162e-01, -4.82219815e-01,
        1.36655584e-01, -1.47303805e-01,  2.70715982e-01,  1.80672228e-01,
       -1.02938311e-02, -2.04580382e-01,  1.10996373e-01,  4.90875036e-01,
       -2.64123529e-01, -6.30355954e-01,  5.13224363e-01, -1.36214346e-01,
        2.96218753e-01,  1.59915499e-02, -5.21028280e-01,  1.29464582e-01,
       -2.56725460e-01, -1.65455505e-01, -7.06485689e-01, -1.74510881e-01,
        2.03715339e-01, -2.81429559e-01, -7.54647329e-03, -1.56341806e-01,
       -3.94731909e-01,  5.62286843e-03,  4.75993678e-02, -8.96703243e-01,
       -1.36611521e-01, -6.55873299e-01, -3.49469572e-01, -3.39191467e-01,
        4.04942214e-01, -2.22183198e-01,  2.96800081e-02,  6.52204752e-02,
       -8.36047828e-02, -4.22520459e-01, -6.02154061e-02, -5.86212158e-01,
       -1.42716974e-01, -2.60680228e-01, -3.17836046e-01,  1.44991428e-01,
       -1.88308626e-01, -1.75459132e-01, -2.93089122e-01,  7.82737732e-01,
       -2.31200323e-01, -7.25735202e-02,  6.32463098e-02, -2.62968630e-01,
        2.45140687e-01, -4.75290090e-01,  3.38366061e-01,  5.81665516e-01,
       -5.36345541e-01, -5.58840454e-01, -1.25529408e-01, -1.08793005e-01,
       -2.33246326e-01, -2.12256417e-01,  6.54630840e-01, -4.07382190e-01,
       -3.02947849e-01, -4.00722772e-02,  8.33050814e-03, -3.82687211e-01,
       -2.81139910e-01, -7.90041089e-01, -4.08340126e-01, -5.71314096e-01,
        4.29689497e-01, -2.87985831e-01,  5.48048615e-01,  2.91664302e-01,
       -3.08267117e-01,  2.36787930e-01,  1.28857270e-01, -1.99234456e-01,
        1.74272452e-02, -1.01792462e-01, -3.33676636e-01, -3.87079507e-01,
        9.74196970e-01, -2.05359563e-01,  2.98519153e-02, -2.50524163e-01,
       -3.60065937e-01, -8.16815197e-01,  1.71162888e-01,  1.63012683e-01,
        4.95278299e-01, -1.04674965e-01, -1.75186187e-01, -1.80965185e-01,
       -4.26358253e-01,  2.93703616e-01,  5.77976465e-01, -1.47980258e-01,
        1.20579258e-01,  5.07742047e-01, -3.52630876e-02, -2.55402595e-01,
       -9.12695751e-02,  4.17510420e-02, -2.97455609e-01, -2.70357847e-01,
        8.56099352e-02,  8.33900422e-02, -3.94027606e-02,  3.04806799e-01,
       -4.76594925e-01, -7.82764554e-01, -4.07521278e-01, -2.41394881e-02,
       -4.61479835e-03, -1.12109549e-01, -1.70475587e-01, -1.40164658e-01,
       -2.89469332e-01, -4.91126895e-01,  2.53223509e-01, -4.97672409e-01,
       -3.81455243e-01,  2.56253988e-01, -7.79179871e-01,  3.11608642e-01,
       -2.54538387e-01, -6.16277814e-01,  6.19835779e-02, -4.61762071e-01,
       -2.65135556e-01,  3.95240635e-01, -9.47954506e-02,  3.13195363e-02,
       -4.82336544e-02,  5.08242607e-01, -3.94652873e-01, -1.26887575e-01,
       -2.10077852e-01, -2.75632292e-01, -7.40879476e-01,  1.71280518e-01,
        5.84655032e-02,  2.97725260e-01, -7.70043254e-01, -4.31460232e-01,
        3.24951291e-01,  5.04719734e-01,  3.54348153e-01,  6.46322072e-02,
       -3.46853197e-01,  1.48680046e-01, -3.19987833e-01, -4.66076970e-01,
       -2.91280508e-01,  6.01588860e-02, -1.56010211e-01, -1.67991146e-01,
       -1.80768281e-01, -1.40539646e-01, -3.54914039e-01, -2.92446285e-01,
       -5.77452958e-01,  4.13142502e-01, -8.72973725e-02, -1.23826146e-01,
        8.09146836e-02, -1.80961102e-01, -5.95774613e-02,  3.81414741e-01,
        4.99335140e-01,  3.25856991e-02, -8.50705951e-02, -2.21782207e-01,
        3.11004311e-01, -1.59042373e-01, -6.09261990e-02, -2.65021306e-02,
       -6.02400959e-01, -1.93334281e-01, -6.13666214e-02, -6.75881088e-01,
       -5.72801530e-01,  3.34765077e-01, -7.31849730e-01,  4.23657894e-01,
       -4.42200564e-02, -4.80023503e-01, -3.61452430e-01, -3.32602096e-04,
       -1.57997757e-01, -6.71140432e-01,  1.37008280e-01,  7.88826793e-02,
        1.09694719e-01,  5.21835506e-01,  2.04502463e-01, -7.36054778e-01,
       -2.81293899e-01, -2.41739780e-01, -2.62930095e-01, -1.60661295e-01,
       -6.34284243e-02,  8.07867870e-02,  2.06879959e-01, -1.83067024e-01,
        4.67929803e-02,  4.08849210e-01,  2.24614486e-01, -2.70404816e-01,
        3.19178760e-01, -3.17227811e-01, -1.96701884e-01,  6.96182191e-01,
       -7.50235021e-02, -5.06447516e-02,  4.18080837e-01, -3.81530911e-01,
       -1.70770198e-01, -2.42653295e-01,  1.42970026e-01,  3.58447134e-01,
       -2.88883690e-02, -3.52183640e-01,  3.31509888e-01, -1.67851135e-01,
       -1.12384267e-01, -4.70291436e-01, -4.67072390e-02, -1.92044139e-01,
        3.82511258e-01,  2.60932744e-01,  2.37532899e-01, -7.86370397e-01,
        6.23600334e-02, -3.58701676e-01, -3.92222881e-01,  2.48510782e-02,
        3.82574767e-01,  2.26949126e-01,  2.31225058e-01,  2.11415738e-01,
       -6.21533871e-01, -3.66403610e-01, -3.74139488e-01, -4.67427015e-01,
       -1.31879151e-01, -2.57024169e-01, -3.96151632e-01,  1.73392922e-01,
       -3.19947824e-02, -4.16536450e-01,  2.37819001e-01,  3.54570150e-01,
        8.03921342e-01, -4.50351417e-01, -3.21829379e-01, -6.50029898e-01,
        1.18587233e-01,  1.00696553e-02,  2.90674329e-01, -3.23075831e-01,
        1.16111510e-01,  3.06913704e-01,  1.24712745e-02, -1.26195773e-01,
        1.13301508e-01, -6.22206032e-01, -3.37203294e-01,  1.92699246e-02,
        1.73154801e-01, -4.87180233e-01, -4.72365767e-01, -4.09207612e-01,
       -2.42017403e-01, -1.16851687e-01, -3.97695303e-01, -3.55633289e-01,
        1.62632301e-01,  6.45668507e-02,  7.79718161e-02,  1.24950454e-01,
       -4.08983320e-01, -3.06680232e-01, -5.20676672e-01, -3.10514629e-01,
        1.20905995e-01, -1.26319438e-01, -7.31470734e-02,  2.46803239e-01,
        2.20303729e-01,  2.84221232e-01, -6.42606378e-01,  1.85590446e-01,
       -4.67979640e-01, -2.46365830e-01,  4.41885442e-01,  1.57461867e-01,
       -4.34606254e-01, -3.03389560e-02,  4.16239321e-01,  1.20696723e-01,
       -1.19780883e-01, -3.12831670e-01, -6.72941625e-01,  2.39680380e-01,
        3.16540636e-02, -6.67556599e-02, -4.53835577e-01, -1.41357362e-01,
        5.55092134e-02, -2.72648245e-01,  1.15637705e-01, -3.69194269e-01,
       -2.46697351e-01, -2.13030607e-01, -5.35916746e-01,  1.22173265e-01,
       -2.26386875e-01,  1.21244952e-01,  2.46608600e-01,  1.14984751e-01,
       -3.38314235e-01, -1.86451554e-01,  1.01037696e-01, -4.63646680e-01,
        3.72002125e-01,  3.57396364e-01, -1.33476779e-01,  3.39640558e-01,
        1.66613132e-01,  3.18085968e-01, -2.23897636e-01, -3.88991803e-01,
        3.25706482e-01,  1.80485070e-01, -7.06845641e-01, -3.14450502e-01,
       -2.99574852e-01, -3.42377454e-01,  3.37020606e-02,  6.33324564e-01,
        3.96425247e-01,  9.57002342e-02, -9.19781998e-03, -1.01162925e-01,
       -1.24752313e-01,  2.16572747e-01, -4.01441574e-01,  2.05238342e-01,
       -2.31176957e-01,  1.74565285e-01,  1.14301808e-01, -4.56711650e-02,
       -1.47148445e-01, -5.47788620e-01,  8.03371489e-01, -1.79063603e-01,
       -3.30505162e-01,  4.52529006e-02, -2.32133031e-01, -1.03061639e-01,
       -3.66753548e-01, -2.67830402e-01, -7.80216873e-01,  1.94708884e-01,
       -2.78978020e-01,  3.68514836e-01, -1.97589234e-01, -6.01612449e-01,
       -8.39308560e-01,  9.09389779e-02, -1.85883775e-01, -4.19929147e-01,
       -2.16230288e-01,  1.59726262e-01, -2.83646047e-01, -4.31024253e-01,
       -5.61656535e-01, -4.58411157e-01, -8.25185776e-01, -8.13963056e-01,
       -9.94023085e-02, -3.87993515e-01,  2.77174443e-01, -5.47208071e-01,
       -4.07609701e-01,  5.99957466e-01, -6.72465935e-02, -1.05910607e-01,
        2.73734540e-01, -6.22414827e-01, -1.89350918e-01,  1.20283753e-01,
       -4.94461805e-01, -4.75006253e-02, -2.05328658e-01, -2.74078041e-01,
        1.27787933e-01,  3.41045141e-01,  1.35159701e-01,  2.74831429e-02,
        1.05416752e-01, -3.22997898e-01, -1.62981972e-01, -4.65426922e-01,
       -4.50913787e-01, -1.53394967e-01, -5.38664341e-01, -2.17683703e-01,
       -3.54512960e-01,  4.27070677e-01, -1.50396138e-01,  1.82398275e-01,
       -2.11658552e-01,  2.96306551e-01, -5.02424896e-01,  1.69271961e-01,
       -1.58109426e-01, -1.47230819e-01, -7.86311403e-02,  4.48902458e-01,
        7.37434328e-02, -1.93051979e-01,  4.22076553e-01,  1.69259802e-01,
        2.69225817e-02,  1.73201889e-01, -2.03502625e-01, -2.84845918e-01,
       -2.11042762e-01,  5.43612009e-03, -1.61834940e-01, -3.71023476e-01,
        2.88119346e-01,  1.62838817e-01, -5.89156628e-01, -5.23166001e-01,
        1.71175361e-01, -1.76744893e-01, -1.04822312e-02,  2.20405802e-01,
        4.19711947e-01,  4.35767144e-01,  1.36741504e-01, -1.94993913e-01,
       -6.72100246e-01, -2.34461054e-01, -3.42008322e-01, -1.38636485e-01,
       -2.81121194e-01,  1.47359535e-01, -2.87768543e-01, -1.44264027e-01,
        1.81511909e-01, -3.34459305e-01, -3.98366690e-01,  2.95538425e-01,
       -4.54735905e-01, -1.53382391e-01, -3.81204367e-01,  1.29017517e-01,
        2.18709916e-01, -6.88370094e-02,  3.67167220e-02, -2.79732585e-01,
       -3.80585372e-01, -4.31413889e-01, -3.52784663e-01,  3.87698531e-01,
        9.47138295e-02,  2.20189750e-01, -2.58784801e-01, -3.46093267e-01,
       -4.14652944e-01, -2.58787513e-01, -3.98010254e-01, -4.95995075e-01,
       -4.47570011e-02, -2.71318406e-01,  3.23093563e-01, -7.60977119e-02,
        3.67811620e-02,  3.98958057e-01,  2.24788323e-01,  3.54979299e-02,
        7.20821261e-01, -4.99057919e-01,  2.04619914e-01,  9.50467587e-02,
        2.18399748e-01,  1.43146157e-01, -2.95208544e-01, -4.54604149e-01,
       -2.02623799e-01, -4.45743799e-01, -2.95156240e-01,  3.94654781e-01,
        5.72584011e-02,  1.35367543e-01, -4.90731537e-01, -4.91390020e-01],
      dtype=float32), array([0.38488978, 0.67093575, 0.28514156, 0.2506373 , 0.25533035,
       0.82591444, 0.32108262, 0.2388716 , 0.49372485, 0.25365284,
       0.2589944 , 0.24496976, 0.3382757 , 0.28219026, 0.18749465,
       0.3209857 , 0.23250653, 0.22832645, 0.25492042, 0.27250734,
       0.37655973, 0.45983443, 0.23790999, 0.23383757, 0.58808184,
       0.26710203, 0.3792174 , 0.54021674, 0.30205113, 0.2807624 ,
       0.29785082, 0.2539619 , 0.5882883 , 0.25398463, 0.25972   ,
       0.54671746, 0.5250746 , 0.40519422, 0.44892353, 0.28726733,
       0.28672615, 0.267437  , 0.3579112 , 0.24016465, 0.34243235,
       0.50572044, 0.4065181 , 0.2608354 , 0.33032623, 0.21209337,
       0.1909683 , 0.29762253, 0.28387728, 0.22478233, 0.289529  ,
       0.43935564, 0.22516434, 0.2714913 , 0.25254118, 0.27376837,
       0.39029688, 0.35865456, 0.52579314, 0.33985358, 0.38356814,
       0.824516  , 0.3440576 , 0.713503  , 0.3060756 , 0.3993766 ,
       0.34714678, 0.34523758, 0.27413812, 0.29294437, 0.33693716,
       0.27067026, 0.2587192 , 0.3317902 , 0.34306502, 0.4524377 ,
       0.865884  , 0.52704173, 0.26936558, 0.81880164, 0.5157328 ,
       0.68082523, 0.2475205 , 0.25013995, 0.31932822, 0.33644927,
       0.49559286, 0.3491055 , 0.29584777, 0.25161508, 0.3647535 ,
       0.49982032, 0.38296682, 0.46331513, 0.39198196, 0.3715143 ,
       0.3507773 , 0.25820276, 0.32295835, 0.30448216, 0.3759487 ,
       0.4466802 , 0.6134835 , 0.23237352, 0.40668926, 0.2774245 ,
       0.3027568 , 0.25778943, 0.27685377, 0.21413913, 0.38834214,
       0.40159875, 0.26303002, 0.27292418, 0.2423691 , 0.73514664,
       0.25190908, 0.47991455, 0.37089422, 0.28714612, 0.60796374,
       0.44017586, 0.5737302 , 0.2647349 , 0.2860508 , 0.22961974,
       0.36855298, 0.43468162, 0.2635023 , 0.48565957, 0.7637051 ,
       0.21752776, 0.27390236, 0.21205747, 0.2462984 , 0.46540532,
       0.21813473, 0.3795211 , 0.6878632 , 0.44887188, 0.22599177,
       1.007806  , 0.30409914, 0.35598832, 0.2549991 , 0.28253195,
       0.6489795 , 0.34605443, 0.47337297, 0.2685795 , 0.26795235,
       0.33494473, 0.41055048, 0.37063235, 0.37356538, 0.2587714 ,
       0.20593101, 0.43227428, 0.2618993 , 0.24576116, 0.29388365,
       0.24436869, 0.3899374 , 0.26763836, 0.30401412, 0.26571366,
       0.40762764, 0.26783052, 0.27143198, 0.5961479 , 0.27702594,
       0.40923923, 0.40778247, 0.26469797, 0.33817327, 0.2573932 ,
       0.5704695 , 0.36456633, 0.24921787, 0.5631954 , 0.33030966,
       0.50232893, 0.4163059 , 0.3139954 , 0.26236674, 0.2696262 ,
       0.5006726 , 0.3660451 , 0.33999345, 0.2253801 , 0.2592145 ,
       0.30609274, 0.3194217 , 0.28132722, 0.6108023 , 0.28021795,
       0.33302784, 0.43389156, 0.32995236, 0.36843663, 0.37818843,
       0.39732495, 0.34627464, 0.28900218, 0.30588004, 0.3721855 ,
       0.26367334, 0.28755248, 0.47182292, 0.2562759 , 0.31799582,
       0.38083252, 0.4195084 , 0.81464046, 0.39845815, 0.320283  ,
       0.4039266 , 0.5103857 , 0.24151248, 0.69146866, 0.34195176,
       0.29600623, 0.52147335, 0.26088262, 0.42586464, 0.37500465,
       0.2819718 , 0.29115376, 0.407715  , 0.35116556, 0.23762722,
       0.33733672, 0.30131596, 0.585611  , 0.27418587, 0.24969861,
       0.26194444, 0.36932576, 0.6183565 , 0.2867484 , 0.35029644,
       0.76022583, 0.64261156, 0.33427066, 0.43169248, 0.42780545,
       0.4409025 , 0.25168103, 0.26985806, 0.3417856 , 0.2409458 ,
       0.39161056, 0.4380448 , 0.37101838, 0.30770788, 0.4410208 ,
       0.31607264, 0.30805838, 0.28343445, 0.43642235, 0.27046287,
       0.31301653, 0.42618155, 0.23834734, 0.5699821 , 0.42318797,
       0.2948993 , 0.3632734 , 0.2275128 , 0.30524382, 0.50117767,
       0.3509364 , 0.22321944, 0.45441616, 0.33978975, 0.34286952,
       0.50796825, 0.39124674, 0.21610321, 0.3331151 , 0.54537684,
       0.38539195, 0.34051615, 0.32586187, 0.26701176, 0.65079355,
       0.31479022, 0.3057124 , 0.34354416, 0.30726132, 0.30180553,
       0.30324855, 0.33397204, 0.25779384, 0.36230153, 0.23581493,
       0.36187068, 0.2922722 , 0.33001563, 0.39527133, 0.5680766 ,
       0.21638723, 0.2435683 , 0.20722745, 0.35013753, 0.24884725,
       0.96884686, 0.72399026, 0.2284644 , 0.41994372, 0.2754057 ,
       0.24651273, 0.21852137, 0.44726253, 0.28164196, 0.26322556,
       0.36248532, 0.75005114, 0.39806595, 0.5417434 , 0.22853585,
       0.43614182, 0.29491282, 0.3557496 , 0.3117732 , 0.21932237,
       0.40214062, 0.27409446, 0.35557353, 0.46928704, 0.19132622,
       0.3448035 , 0.2694663 , 0.40143168, 0.2634354 , 0.3412937 ,
       0.2926402 , 0.24034889, 0.2560278 , 0.18424664, 0.29065546,
       0.29926148, 0.39160234, 0.341572  , 0.41114065, 0.23316005,
       0.30608383, 0.6075231 , 0.2784992 , 0.24814506, 0.2275709 ,
       0.45211738, 0.29148263, 0.36350107, 0.21825315, 0.36174095,
       0.26070574, 0.44001818, 0.2765389 , 0.27683756, 0.25031   ,
       0.3734746 , 0.5192656 , 0.5157384 , 0.26425022, 0.3334853 ,
       0.30650672, 0.26710024, 0.28935504, 0.39582413, 0.36883357,
       0.51977783, 0.4662921 , 0.46572274, 0.20410465, 0.72535896,
       0.24842323, 0.3504343 , 0.29628795, 0.2603049 , 0.29233962,
       0.40623593, 0.2743242 , 0.36836797, 0.20552249, 0.28260487,
       0.32133883, 0.41974518, 0.3886915 , 0.3253871 , 0.2524257 ,
       0.30450907, 0.26891732, 0.21868283, 0.43525028, 0.25206485,
       0.28073418, 0.35324693, 0.27538076, 0.34340653, 0.40897885,
       0.22795084, 0.2660865 , 0.30509612, 0.3645717 , 0.36270615,
       0.37361735, 0.4028159 , 0.3357333 , 0.3369338 , 0.4633101 ,
       0.23348045, 0.27244285, 0.27313942, 0.20517868, 0.33880514,
       0.42490262, 0.31375697, 0.28202945, 0.22923607, 0.23396905,
       0.24487709, 0.34045613, 0.26347515, 0.3716517 , 0.43089387,
       0.2558669 , 0.2980709 , 1.1929787 , 0.4192081 , 0.43059477,
       0.3196831 , 0.26819462, 0.25237542, 0.31989866, 0.33478478,
       0.36224923, 0.28827655, 0.2788511 , 0.41680744, 0.5000156 ,
       0.30928123, 0.46426773, 0.31071445, 0.326456  , 0.47739574,
       0.22884639, 0.22994992, 0.32574138, 0.39177743, 0.26952216,
       0.37853822, 0.32045177, 0.20666713, 0.2947155 , 0.44167197,
       0.2771339 , 0.26839638, 0.34211496, 0.4501797 , 0.27276158,
       0.3840325 , 0.33358315, 0.31172532, 0.5991279 , 0.3103387 ,
       0.380018  , 0.27132028, 0.39750704, 0.32694936, 0.26568705,
       0.31542212, 0.32578716, 0.2586841 , 0.3239156 , 0.536295  ,
       0.31889907, 0.50880563, 0.312414  , 0.3049779 , 0.26157784,
       0.23754361, 0.21579547, 0.298577  , 0.5198406 , 0.310721  ,
       0.24187362, 0.39990464, 0.4495757 , 0.57381195, 0.24398994,
       0.23280561, 0.9701771 , 0.22227786, 0.2868111 , 0.37328714,
       0.24374892, 0.32847455, 0.50761366, 0.2769033 , 0.40949652,
       0.29245988, 0.23261218, 0.24381192, 0.31587175, 0.25315657,
       0.27404973, 0.40105218], dtype=float32), array([[[[-0.00290728],
         [ 0.01649308],
         [ 0.01625865],
         ...,
         [ 0.04722757],
         [ 0.04030608],
         [ 0.01913459]],

        [[-0.00331694],
         [-0.00115124],
         [ 0.01088478],
         ...,
         [-0.02380672],
         [-0.03730589],
         [-0.03937571]],

        [[-0.03246981],
         [-0.02692851],
         [-0.02026857],
         ...,
         [ 0.04271244],
         [-0.02055267],
         [-0.0091521 ]]],


       [[[ 0.03668993],
         [ 0.01128419],
         [-0.05110211],
         ...,
         [-0.00491582],
         [ 0.04837631],
         [ 0.00029524]],

        [[-0.05897994],
         [ 0.01550246],
         [ 0.05085266],
         ...,
         [-0.03311663],
         [ 0.00541059],
         [-0.02957432]],

        [[ 0.02188698],
         [-0.02364876],
         [-0.01691558],
         ...,
         [-0.01353922],
         [ 0.02104338],
         [ 0.01684305]]],


       [[[ 0.01917536],
         [-0.02477565],
         [ 0.00579796],
         ...,
         [-0.01681334],
         [-0.04079222],
         [ 0.01943593]],

        [[-0.01718652],
         [ 0.01948977],
         [-0.02922893],
         ...,
         [-0.00493014],
         [-0.04474013],
         [-0.00747786]],

        [[-0.0438001 ],
         [-0.02377746],
         [-0.02363026],
         ...,
         [-0.04665909],
         [-0.00919401],
         [ 0.03348477]]]], dtype=float32), array([0.99743426, 0.9633481 , 1.0245433 , 1.0036197 , 1.0299203 ,
       0.9810891 , 1.0343232 , 1.0245419 , 0.9912016 , 0.9987451 ,
       1.0034083 , 0.986078  , 0.9778962 , 1.0004205 , 0.9970565 ,
       0.98679817, 1.0012971 , 1.0080029 , 0.9920601 , 1.033608  ,
       1.0465674 , 0.98004293, 0.99955237, 1.0070878 , 0.98789525,
       1.0495749 , 1.0129302 , 1.0506788 , 0.9682177 , 1.0055413 ,
       1.0116762 , 1.017553  , 1.0117685 , 0.99803686, 1.0291244 ,
       0.9998738 , 0.99202   , 0.989903  , 0.99064374, 0.9933505 ,
       1.0414838 , 0.9871487 , 0.9675215 , 0.99712205, 1.0324491 ,
       0.9657406 , 1.0094742 , 1.0062964 , 0.99195963, 0.9919773 ,
       1.0029743 , 1.0338022 , 1.0080255 , 1.0010275 , 1.0269306 ,
       0.9796904 , 1.0024961 , 0.99288774, 0.97856426, 1.0126306 ,
       0.98670393, 1.0128763 , 0.9851712 , 1.008925  , 0.98560375,
       1.0081273 , 0.97045034, 0.9958481 , 1.0007054 , 1.0125015 ,
       0.9985965 , 0.9981582 , 1.031509  , 0.9921419 , 1.0272518 ,
       0.998006  , 1.0131999 , 1.0065717 , 0.98708916, 0.9954806 ,
       0.99958634, 0.9616474 , 0.9683304 , 0.9877495 , 0.98834944,
       0.992978  , 1.002418  , 1.02039   , 0.9938234 , 0.9748123 ,
       0.9858306 , 1.0041351 , 0.97806984, 1.021516  , 1.037055  ,
       1.0203056 , 1.0152589 , 1.0121713 , 0.97739685, 1.0076445 ,
       1.0309254 , 0.98947465, 1.007605  , 0.9893771 , 0.98454475,
       0.9927043 , 0.99343014, 1.017335  , 0.9994433 , 0.9950493 ,
       0.97360086, 1.0164865 , 1.0438213 , 0.99563754, 1.0256165 ,
       0.9785371 , 1.028047  , 0.9921006 , 0.9985855 , 0.9782112 ,
       1.0288112 , 1.0176153 , 1.016745  , 1.0413443 , 0.95850223,
       0.96726954, 0.98177135, 1.0177019 , 0.9931298 , 0.96536714,
       0.99768263, 1.0083286 , 0.99794674, 0.9800475 , 1.0242192 ,
       1.0229622 , 0.9939282 , 1.0085672 , 0.98964584, 1.0186272 ,
       1.0175608 , 0.98844904, 0.971286  , 1.0166905 , 1.004309  ,
       0.9821616 , 1.0091745 , 0.99372673, 1.0021477 , 1.0017288 ,
       0.99737847, 1.024108  , 0.9746585 , 1.0393721 , 1.031143  ,
       1.0265896 , 1.0052574 , 1.0308559 , 0.9751985 , 1.0055722 ,
       1.0046611 , 1.010315  , 0.9700155 , 1.0125601 , 1.039625  ,
       0.97987425, 1.0382854 , 1.0351729 , 0.98818594, 1.0009011 ,
       1.0060087 , 1.0055599 , 1.0158982 , 0.99224824, 1.0257916 ,
       1.0084653 , 0.9883177 , 1.0405391 , 0.9859196 , 0.9846718 ,
       0.9697616 , 1.0258865 , 1.010307  , 1.0001276 , 0.99878544,
       0.9965473 , 1.0058241 , 1.0089194 , 1.0272411 , 0.9794455 ,
       0.9874915 , 0.99986035, 0.99968845, 1.0435516 , 1.0098128 ,
       1.0158236 , 1.0243342 , 0.98948497, 1.0112677 , 1.0465065 ,
       0.990831  , 1.0004848 , 0.98771393, 0.96663177, 0.9873806 ,
       1.0130954 , 0.99697256, 0.9987236 , 1.0369277 , 0.9775582 ,
       1.0199032 , 1.0562942 , 0.99555755, 1.0244547 , 0.9893684 ,
       1.0122584 , 0.98156923, 0.9740156 , 0.9724705 , 1.0397047 ,
       0.9736642 , 0.9881761 , 1.0896984 , 0.9856669 , 0.9925995 ,
       1.0458652 , 1.029126  , 1.0194427 , 1.0279202 , 1.0465906 ,
       1.0110916 , 0.9850499 , 1.0097841 , 0.9770001 , 0.9925347 ,
       1.0005324 , 0.99173814, 0.9728289 , 1.0048758 , 1.0053384 ,
       1.0156009 , 0.98292184, 0.96972495, 1.023169  , 0.99356115,
       1.020669  , 0.990099  , 1.020716  , 0.9943504 , 0.9879417 ,
       1.0103965 , 1.0102208 , 0.99836147, 1.0260837 , 1.0157839 ,
       1.0119224 , 1.0597006 , 0.9691096 , 1.0053924 , 0.98592407,
       1.0230482 , 1.0372397 , 1.0252843 , 0.9862479 , 0.98688394,
       1.0430537 , 1.0352229 , 1.0151747 , 1.0204642 , 0.9705744 ,
       1.009879  , 1.0180798 , 1.0035124 , 1.0408372 , 0.9991252 ,
       1.01206   , 1.009261  , 1.0034062 , 1.0027312 , 1.0711681 ,
       0.97709006, 0.98101324, 0.9964382 , 0.9880155 , 1.0160146 ,
       1.0155251 , 1.0639511 , 1.0240446 , 1.022208  , 0.9970276 ,
       0.99648917, 0.9645891 , 0.9824423 , 0.99652994, 1.0126889 ,
       0.99222916, 1.0182892 , 1.0104889 , 1.0237314 , 0.9857802 ,
       1.035948  , 1.0014853 , 1.0360805 , 1.0205123 , 0.9788506 ,
       1.0293525 , 1.0295527 , 1.0467699 , 0.98801714, 0.99277973,
       0.96577305, 0.98887175, 1.0100476 , 1.0273205 , 1.0254518 ,
       1.0135281 , 1.0032969 , 1.0099928 , 1.0237962 , 0.9972198 ,
       0.9815995 , 1.012541  , 0.97861296, 0.9927925 , 0.975388  ,
       0.9872188 , 1.0062109 , 1.0377845 , 1.0003405 , 0.988707  ,
       0.99291486, 1.0171384 , 0.985293  , 1.0011777 , 1.0257818 ,
       0.9580854 , 0.9897511 , 0.98328716, 1.0125763 , 1.0000954 ,
       1.0102378 , 1.0326356 , 1.0022317 , 1.0049657 , 0.9826612 ,
       0.994602  , 1.009975  , 1.0129787 , 1.0059912 , 1.0015098 ,
       1.009107  , 0.98383284, 0.98939764, 0.9996097 , 0.9872375 ,
       0.9677479 , 1.0079786 , 0.9784874 , 0.9913152 , 0.97858196,
       1.0167865 , 0.9847424 , 1.0049298 , 0.98184943, 1.0133755 ,
       0.9998726 , 0.9869229 , 1.020018  , 1.0077387 , 1.0112413 ,
       0.9597525 , 1.0136548 , 1.008006  , 1.0154867 , 0.95662916,
       0.9971759 , 1.0372611 , 0.97826856, 1.008568  , 1.024507  ,
       0.9914016 , 1.0133578 , 1.0481145 , 1.0408553 , 0.9745255 ,
       1.0048554 , 1.003856  , 1.002427  , 0.97819114, 1.0120958 ,
       0.9896849 , 1.0263581 , 0.9734941 , 0.9993776 , 1.0040785 ,
       0.960991  , 1.006422  , 1.003629  , 0.99047935, 1.020568  ,
       1.0157869 , 1.0027118 , 0.99587625, 1.0114912 , 0.98731416,
       1.0024076 , 1.0127554 , 0.98569584, 0.9973533 , 0.98063046,
       1.0543246 , 1.0205735 , 1.0428623 , 1.0132378 , 1.0362    ,
       1.0017741 , 1.0218847 , 0.99002814, 1.0233139 , 1.0142299 ,
       0.9835278 , 0.99328274, 1.0016675 , 0.99968   , 1.0224339 ,
       1.0271223 , 0.99162793, 1.017254  , 1.0400182 , 1.0576133 ,
       1.0103489 , 1.0026656 , 0.9920177 , 0.9592141 , 0.99489737,
       0.9970855 , 0.9930513 , 0.9969631 , 0.9830577 , 1.0200317 ,
       1.001817  , 1.0414398 , 0.99385643, 1.0300865 , 1.0011232 ,
       0.9835681 , 1.0301763 , 1.0188298 , 0.9642571 , 1.0076811 ,
       0.9881743 , 1.0114514 , 1.0141599 , 1.0526955 , 1.036605  ,
       1.0009921 , 1.026376  , 1.0024049 , 1.013927  , 1.0286149 ,
       1.0229988 , 1.0094763 , 1.0191052 , 1.0067466 , 0.9977674 ,
       0.9967439 , 0.99919575, 1.014765  , 0.9922117 , 1.0278764 ,
       0.9748752 , 1.0450985 , 0.9833625 , 0.9882272 , 1.0515248 ,
       0.99223965, 0.9903601 , 1.010153  , 1.0255264 , 0.98804367,
       1.0033946 , 1.0224335 , 1.0196471 , 1.0196643 , 0.97506607,
       1.007753  , 0.9856521 , 1.0272014 , 1.0043803 , 1.0949228 ,
       1.0202153 , 0.9954317 , 0.9731653 , 0.99483377, 1.0254532 ,
       0.9884675 , 0.97526443, 0.9965288 , 0.96595293, 0.9973555 ,
       1.0266858 , 1.0278329 , 0.9753954 , 1.04347   , 1.010623  ,
       1.0283818 , 1.0192249 , 1.0177828 , 0.9612539 , 1.0172881 ,
       1.013751  , 0.9853944 ], dtype=float32), array([-1.51816681e-02, -2.64720358e-02, -4.44822805e-03, -2.82218470e-03,
        1.88790783e-02, -3.60879004e-02,  4.15098481e-02,  2.13945415e-02,
       -8.80437961e-04,  1.99302807e-02, -3.62954475e-03, -1.40639320e-02,
       -2.53899172e-02, -1.12575153e-02, -3.05080507e-02,  4.63011814e-03,
        3.52757424e-03, -1.05247926e-02, -1.28056975e-02,  3.55741084e-02,
        2.42632106e-02, -1.79552976e-02, -2.88160369e-02,  6.91969600e-03,
       -2.08602659e-02,  4.71795835e-02,  1.83750968e-02,  4.48538996e-02,
       -1.48018319e-02, -8.13094550e-04,  1.25654964e-02,  1.48445535e-02,
        2.27000974e-02, -5.13226213e-03,  3.74658033e-02,  4.77118371e-03,
       -2.40357853e-02, -8.48317612e-03,  1.54132606e-03, -3.49333361e-02,
       -8.19280744e-03, -1.28232259e-02, -4.48840484e-02, -1.96728203e-02,
        1.66351497e-02, -1.13233123e-02,  1.28710419e-02,  1.05154719e-02,
       -1.61842834e-02, -4.28209733e-03, -4.39266703e-04, -6.72568055e-03,
        2.37656180e-02, -3.24151898e-03,  4.66947164e-03, -2.80710515e-02,
        3.75160365e-03, -4.43805493e-02, -1.01918252e-02,  2.56884890e-03,
       -1.53432204e-03,  1.83492489e-02,  1.18163484e-03,  4.00181860e-03,
       -1.78020913e-02, -1.19095377e-03,  6.99581625e-03, -2.23722700e-02,
       -7.65346037e-03, -1.22515177e-02,  7.59230601e-03,  2.32896837e-03,
        1.95177980e-02, -9.47683817e-04,  2.21071579e-02, -1.02665629e-02,
       -7.32834172e-03, -6.24383939e-03, -1.16441613e-02,  2.69682892e-03,
       -9.07071028e-03, -2.89001036e-02, -1.10417521e-02, -1.89842619e-02,
        6.65672997e-04,  4.30852233e-04,  3.89472814e-03, -1.16847483e-02,
        7.78627116e-04, -3.35895596e-03,  6.85255881e-03,  1.98747162e-02,
       -3.33089046e-02,  9.38492548e-03,  3.65070663e-02,  2.55499538e-02,
        2.08441764e-02,  1.16243241e-02, -1.65675767e-02,  2.68902108e-02,
        2.41972338e-02,  3.46616725e-03,  8.83222278e-03, -1.89337675e-02,
       -1.34667372e-02, -3.01886201e-02, -1.70543306e-02,  5.16636111e-03,
       -9.03057214e-03, -3.94931808e-03, -1.85369011e-02,  2.96583679e-02,
        3.15515772e-02,  2.16905796e-03,  4.08264436e-02, -1.34580238e-02,
        1.12204412e-02, -1.02082659e-02, -1.26824351e-02, -2.64504347e-02,
        1.75793171e-02,  2.46095490e-02, -7.13837100e-03,  1.13514010e-02,
       -3.09360288e-02, -4.25469987e-02, -5.92771731e-03,  4.70265336e-02,
        9.41532198e-03, -4.20047268e-02, -2.88578384e-02,  7.15263793e-03,
        2.10667793e-02, -1.57580581e-02, -2.22074892e-02,  1.81064568e-02,
       -1.47611545e-02, -2.07619686e-02, -6.43490488e-03,  3.40927728e-02,
        1.51801035e-02, -3.12077869e-02, -2.49581542e-02,  2.02891082e-02,
       -1.07402671e-02, -3.13604856e-03, -3.98657620e-02, -2.70929616e-02,
        1.84501130e-02,  5.78373950e-03, -1.16722966e-02, -3.80893616e-04,
       -2.37220023e-02,  2.29191612e-02,  4.15938459e-02,  3.18057425e-02,
       -6.68102317e-03,  1.21176690e-02, -1.17125437e-02,  6.17072452e-03,
        1.76207479e-02, -9.11366311e-04, -3.10547035e-02,  3.26990080e-03,
        4.03006822e-02, -2.19401680e-02,  3.92945036e-02,  2.70938780e-02,
       -1.20213833e-02, -6.89810840e-03,  1.90224927e-02,  2.18864046e-02,
        1.44149372e-02, -8.06790777e-03,  1.99373066e-02,  1.18393293e-02,
       -1.80022586e-02,  2.25998815e-02,  6.06185663e-03, -2.14502458e-02,
        8.60185421e-04,  1.90339703e-02,  2.15872284e-02, -7.48155359e-03,
       -1.52926445e-02,  1.17671778e-02, -4.17962158e-03, -1.34439785e-02,
        3.32282148e-02, -1.72862560e-02,  5.18914638e-03, -1.79864059e-03,
       -2.16706172e-02,  1.00100730e-02, -9.30496119e-03,  8.98512173e-03,
        1.53163681e-02,  4.61255520e-04, -2.26829350e-02,  2.08713338e-02,
        1.31796591e-03, -1.72237940e-02, -2.51574628e-02, -2.68333349e-02,
       -1.29192686e-02, -1.22914126e-03,  6.93788985e-03,  1.41349919e-02,
        1.07221967e-02, -2.83865668e-02,  1.32636297e-02,  1.20819909e-02,
       -1.35649759e-02,  1.32288598e-02, -5.24574472e-03,  8.98143742e-03,
       -1.42211262e-02, -2.93595493e-02, -3.32451910e-02,  3.51194292e-02,
       -3.49488705e-02, -2.48530302e-02,  4.30902727e-02, -1.99234933e-02,
       -2.00511422e-02,  4.02695648e-02,  1.03036058e-03,  2.26802193e-02,
        3.79355364e-02,  5.15689217e-02,  1.50392177e-02, -2.11564060e-02,
        3.14224279e-04, -3.35270911e-02,  2.36017257e-03,  9.24120191e-03,
        5.08135324e-03, -2.80161295e-02,  2.81538977e-03, -1.88247915e-02,
       -1.51172862e-03, -2.29498893e-02, -2.00118273e-02,  2.08224822e-02,
       -5.10254782e-03,  9.77704301e-04, -9.75339860e-03,  1.98412314e-02,
       -1.35982754e-02,  9.96791199e-03,  1.74640752e-02, -6.29170449e-04,
       -5.06835338e-03,  3.32213156e-02,  1.74966082e-02, -1.23784663e-02,
        2.79537514e-02, -2.66503580e-02,  1.31827528e-02, -3.85287516e-02,
        3.47653516e-02,  2.68450733e-02,  1.11859031e-02,  1.26022808e-02,
       -1.18718212e-02,  1.88634675e-02,  3.45146842e-02,  2.10960209e-02,
       -6.79794373e-03, -2.28600278e-02, -6.58875040e-04, -5.46309492e-03,
       -1.76437348e-02,  2.33204123e-02,  1.24770561e-02,  1.35489292e-02,
        7.59077072e-03,  1.28464457e-02,  1.47027504e-02,  4.75367978e-02,
       -8.48209113e-03, -1.49060730e-02, -5.38534718e-04, -8.57166573e-03,
        2.55522318e-02,  4.87133814e-03,  4.42248769e-02, -5.88085037e-03,
       -9.90359578e-03, -5.85253164e-03,  1.88833568e-02, -1.83949694e-02,
        1.76938297e-03,  9.42392834e-03, -4.18750074e-04,  1.64407492e-02,
        3.44987251e-02, -5.40604990e-04,  2.87910290e-02, -1.26104504e-02,
        2.78705172e-02, -3.22955544e-03,  5.05964607e-02, -5.83266793e-03,
       -1.84442680e-02, -1.67265665e-02,  2.00679358e-02,  4.57575992e-02,
        2.57817912e-03, -1.87330060e-02, -2.77242120e-02, -2.35432833e-02,
        2.40814947e-02,  1.26581984e-02,  1.52051738e-02,  1.75784770e-02,
        1.45500917e-02,  4.41439683e-03,  1.47965290e-02, -3.13179888e-04,
        1.54690153e-03,  6.00756658e-03, -2.27686949e-02,  8.84095952e-03,
        6.25439221e-04, -1.85777880e-02,  1.15811825e-02,  8.80220439e-03,
        2.73011718e-03,  3.56675964e-03, -9.23878513e-03, -7.79286819e-03,
       -2.41767503e-02,  6.76137768e-03,  1.47339590e-02, -3.93678322e-02,
        7.43366033e-03, -1.27839837e-02,  1.68916595e-04, -1.30159045e-02,
        1.23654827e-02,  2.29350980e-02,  2.08633635e-02, -1.15765829e-03,
       -3.75252180e-02,  1.57431494e-02, -1.15763200e-02,  3.41433473e-02,
        2.64609698e-03,  9.41834878e-03,  1.38645777e-02, -1.32908113e-02,
       -6.55875169e-03,  6.50189235e-04, -1.72922388e-02, -2.75640562e-02,
        3.57580632e-02, -2.29249373e-02, -1.89091880e-02, -1.30196447e-02,
        1.00710224e-02, -2.91742361e-03, -2.44354410e-03,  8.11264012e-03,
        2.21220870e-02, -8.12798180e-03, -1.45710539e-02,  1.76558644e-02,
        3.22708488e-02, -2.32613820e-06, -3.74523848e-02,  1.89346578e-02,
        3.53114493e-02,  2.20491663e-02, -3.41791920e-02,  1.71282433e-03,
        4.17941213e-02, -3.73350009e-02,  4.77171224e-03,  1.14674373e-02,
       -1.65682565e-02, -2.97449110e-03,  4.61584330e-02,  3.95401344e-02,
       -2.70700250e-02, -1.10898362e-02, -1.55122066e-03, -9.13314428e-03,
       -4.14130725e-02,  2.20978763e-02, -7.95066264e-03,  1.51973749e-02,
       -4.59271111e-02, -1.37017639e-02, -1.68278031e-02, -3.39564681e-02,
        1.43561501e-03,  4.15599253e-03,  1.23533076e-02,  8.21656268e-03,
        9.29855928e-03,  1.83152650e-02, -2.06820834e-02,  1.97285190e-02,
       -3.04510887e-03, -1.85430603e-04, -1.44308191e-02,  7.93807860e-03,
       -1.89193133e-02, -1.08062029e-02,  3.43031138e-02, -1.12022394e-02,
        3.76846790e-02,  3.70754264e-02,  3.61258052e-02,  2.43842918e-02,
        4.94708354e-03,  1.85696501e-02,  3.08669191e-02, -6.44879276e-03,
       -1.22726420e-02, -7.98355881e-03, -1.54012190e-02, -5.39157679e-03,
        1.07302461e-02,  3.30210030e-02, -1.72197558e-02, -2.03269138e-03,
        2.01855674e-02,  3.44009958e-02,  1.28199840e-02, -2.88098771e-03,
        1.32401502e-02, -2.49707364e-02, -1.12206545e-02, -2.73233792e-03,
       -1.87001023e-02, -7.58669619e-03, -4.70279716e-03,  2.27632094e-02,
       -3.37954867e-03,  3.89451496e-02, -1.35177211e-03, -9.53619275e-03,
        2.57289619e-03, -9.92387533e-03,  2.14485619e-02,  2.32469011e-02,
       -2.81104166e-02, -2.70878733e-03,  8.03462602e-03, -5.23431983e-04,
       -1.52479708e-02,  2.23905519e-02,  1.29445000e-02,  9.74577293e-03,
        2.20633578e-02,  1.02628535e-02,  2.82907691e-02, -4.53246012e-03,
        2.09849365e-02,  1.29332198e-02,  1.50424261e-02,  2.88698543e-02,
        3.42836906e-03, -3.28865339e-04,  4.83391946e-03,  1.96873322e-02,
        1.89598382e-03,  1.68856774e-02, -1.86561011e-02,  2.15420444e-02,
       -3.35158370e-02,  2.00644066e-03,  2.29807086e-02, -2.58896463e-02,
       -1.60378814e-02,  1.24178380e-02,  2.65493784e-02, -1.28768487e-02,
        1.33223512e-04,  1.70231611e-02,  1.67628396e-02,  2.12654471e-02,
       -7.94568472e-03,  6.13856246e-05,  2.72978854e-04,  2.39017494e-02,
       -1.89897958e-02,  5.60430810e-02,  2.24499591e-02, -3.07556568e-03,
       -2.97361277e-02, -3.68511491e-02,  3.86578254e-02, -9.08013340e-03,
       -2.15733573e-02, -7.82528706e-03, -1.84303764e-02, -1.45568829e-02,
        1.38290050e-02,  5.34350760e-02, -2.91387569e-02,  9.78603121e-03,
        2.59898379e-02,  1.42077897e-02,  1.75735075e-02,  8.76232237e-03,
       -3.72434668e-02,  6.43727183e-03,  1.79432221e-02, -3.49528342e-02],
      dtype=float32), array([-3.38297933e-02, -2.37193797e-03, -2.35623289e-02, -2.12192349e-02,
       -1.05244145e-02,  7.02581136e-04, -1.86846778e-02, -7.99081102e-03,
       -2.58152541e-02,  2.43348419e-03, -7.89010711e-03, -1.23106716e-02,
       -6.13882765e-03, -7.17709959e-03, -8.00624304e-03,  9.96864401e-03,
       -1.18204001e-02, -1.43760657e-02, -8.28544050e-03, -2.24371180e-02,
       -1.67823024e-02, -2.30837036e-02, -2.93431468e-02, -3.81505042e-02,
       -1.79895442e-02, -1.36290994e-02, -1.34628601e-02, -1.91182811e-02,
       -1.85672604e-02, -9.39286873e-03, -1.51656959e-02, -1.72062535e-02,
       -1.67568214e-02, -1.21334558e-02, -2.27029063e-02, -2.44316384e-02,
       -1.55593203e-02, -1.48645686e-02, -2.08645649e-02, -1.05117504e-02,
       -1.74345281e-02, -1.57700852e-02, -1.40617248e-02, -1.94495209e-02,
       -2.43603252e-02, -5.67868724e-03, -1.29859736e-02, -1.80587936e-02,
       -1.95307434e-02, -1.14844609e-02, -1.11942263e-02, -9.75183304e-03,
       -7.49938516e-03, -1.00590996e-02, -1.07157342e-02,  4.40617418e-03,
       -1.04509126e-02, -1.44071383e-02, -1.64001994e-02, -1.08240973e-02,
       -1.68304946e-02, -3.89254955e-03, -2.11872570e-02, -2.30062683e-03,
       -1.60988122e-02, -1.67632382e-02, -1.13295959e-02, -6.09397888e-03,
       -6.06151624e-03,  2.80294497e-03,  5.54074686e-05, -1.72646530e-03,
       -1.24322632e-02,  2.57095858e-03, -1.88815035e-02, -1.17516527e-02,
       -9.84680094e-03, -9.95914638e-03,  4.87372186e-03, -1.22503610e-02,
        2.57038027e-02, -1.85834300e-02, -1.64555982e-02, -3.67648415e-02,
       -9.18071251e-03, -2.21576244e-02, -8.75867717e-03, -1.06778974e-02,
       -1.52629698e-02, -2.06728559e-02, -3.98642430e-03, -1.91812664e-02,
       -1.40892752e-02, -9.41466447e-03, -5.72390016e-03, -1.36813149e-02,
       -1.53007247e-02, -5.46323555e-03, -8.58830288e-03, -8.53494089e-03,
       -7.61038577e-03, -1.50588388e-02, -2.78490502e-02,  8.10196158e-04,
       -5.23262704e-03, -2.11692732e-02, -1.24030160e-02, -1.37552582e-02,
       -2.06472259e-02, -1.34427790e-02, -3.83242732e-03, -2.72741262e-02,
       -7.30110332e-03, -1.79426521e-02, -1.58414654e-02, -1.06600588e-02,
        1.30820891e-03,  6.56836759e-03, -6.68186508e-03,  3.70575562e-02,
       -2.01678202e-02, -9.90177877e-03, -1.11598503e-02, -2.50639096e-02,
       -8.18553194e-03, -1.59998052e-02, -8.55900068e-03, -9.15704481e-03,
       -4.27811639e-03, -2.00127400e-02, -1.96112748e-02, -6.22101035e-03,
       -1.42512759e-02, -3.54552381e-02, -2.82552512e-03, -1.56536959e-02,
       -1.96962208e-02, -5.86841488e-03, -1.70393493e-02, -6.27357978e-03,
       -1.29131833e-02, -4.60669072e-03, -2.26402730e-02, -2.06748098e-02,
       -1.34243071e-02,  1.54324714e-02, -8.81239958e-03, -1.22383945e-02,
       -4.88247117e-03, -7.94080086e-03,  1.82702707e-03,  3.42612877e-03,
        1.91822101e-03, -1.59445852e-02, -8.14393535e-03, -9.18195117e-03,
       -1.04260696e-02, -2.25608815e-02,  2.15382315e-02, -1.54696610e-02,
       -1.00334492e-02, -3.13043268e-03, -2.74145715e-02, -1.62717625e-02,
       -1.65956225e-02, -1.05228154e-02, -2.39816364e-02, -1.63649935e-02,
       -1.16569847e-02, -6.81061763e-03, -7.83016440e-03, -2.43975464e-02,
       -7.40507711e-03, -2.21987925e-02, -2.06247065e-02, -1.10406755e-02,
        1.79914515e-02, -2.13326588e-02, -2.74065789e-02, -9.05740913e-03,
       -9.58837103e-03, -1.92831047e-02, -7.53265899e-03, -2.06565857e-02,
       -8.84180330e-03, -1.56003027e-03, -7.02836411e-03, -1.30922105e-02,
       -5.51977055e-03, -1.58602577e-02, -9.21606086e-03, -9.70339123e-03,
       -1.51526779e-02, -1.39987413e-02, -1.58471446e-02, -9.50451661e-03,
       -1.55399963e-02, -1.47667034e-02, -6.33839518e-03, -7.73605611e-03,
       -9.96507797e-03, -2.37629395e-02, -1.81609322e-03, -1.37600983e-02,
       -1.30103249e-02, -4.26908955e-02, -2.06064712e-02, -1.77165121e-02,
       -2.67473087e-02, -1.55762965e-02, -9.50098690e-03,  3.28045036e-03,
       -1.58930868e-02, -7.47465529e-03, -1.93631612e-02, -1.50246518e-02,
       -1.35143390e-02, -2.94947196e-02,  4.58597345e-03, -1.94076225e-02,
        1.08555565e-02, -2.20600725e-03,  1.77187612e-03, -4.36370773e-03,
       -1.57146975e-02, -5.40491659e-03, -1.15264487e-02, -2.02853978e-02,
       -1.16384579e-02, -1.26348753e-02, -1.50338141e-03, -8.24728422e-03,
       -8.03776924e-03, -1.99945066e-02, -3.43701281e-02, -2.22912412e-02,
       -1.09872306e-02,  6.02489617e-03, -1.91914067e-02, -1.70871411e-02,
       -1.97700877e-02, -3.01084705e-02, -1.83191225e-02, -7.17257336e-03,
       -9.23151150e-03,  4.82924841e-03,  1.09128327e-04, -1.94600727e-02,
        1.11300992e-02, -2.88096536e-03, -9.90168005e-03, -1.51866926e-02,
       -1.37334047e-02, -1.69290323e-02, -1.34545155e-02, -1.30230598e-02,
       -2.97235767e-03, -1.01290541e-02, -1.31842019e-02,  2.01520603e-03,
       -1.14083020e-02, -1.44198854e-02, -9.26092174e-03, -2.06689313e-02,
       -1.66702103e-02, -8.52207653e-03, -2.28388999e-02, -1.10317739e-02,
        6.87209330e-03, -1.86178070e-02, -2.23538689e-02, -1.30693568e-02,
       -2.95922384e-02, -2.32088361e-02, -1.14163244e-02, -2.30235048e-02,
       -2.11856309e-02, -1.03566470e-02, -2.72302609e-02,  9.65558924e-03,
       -2.90980916e-02, -2.45394092e-03, -8.48621689e-03,  1.22249033e-03,
       -1.32554844e-02, -1.90557670e-02, -2.11240519e-02, -2.20971461e-02,
       -2.00443659e-02, -2.26390194e-02, -1.06146969e-02,  8.54180194e-03,
       -1.80903114e-02, -6.61688065e-03, -9.97182634e-03, -2.88145505e-02,
       -2.40174495e-02, -9.60933976e-04, -2.73262728e-02, -1.66375283e-02,
       -4.07875739e-02, -6.08738372e-03, -2.08885968e-02,  2.06683367e-03,
       -1.02008814e-02, -3.08131636e-03, -1.06868399e-02, -2.19413601e-02,
       -3.42666022e-02, -5.96154481e-03, -2.07962077e-02,  2.06023492e-02,
       -1.92149486e-02,  1.15437638e-02, -1.98255982e-02, -1.34674683e-02,
       -1.00565115e-02, -1.86240021e-02, -3.31423315e-03, -1.71765275e-02,
       -1.53838694e-02, -4.36609099e-03, -2.73471773e-02, -1.46407709e-02,
       -2.61865892e-02, -9.67527367e-03, -1.22854887e-02, -4.32810839e-03,
       -7.26190070e-03, -2.00282522e-02, -1.90719776e-02, -1.00218896e-02,
       -1.82162970e-03, -4.39049164e-03, -1.54101662e-02, -3.58305350e-02,
       -2.13697478e-02,  2.18509194e-02,  1.80827512e-03, -1.20740989e-03,
       -1.63093638e-02, -1.60693899e-02, -1.27055803e-02, -1.05176605e-02,
       -3.10461293e-03, -2.11749449e-02, -7.22754607e-03, -3.41497548e-02,
       -1.53621295e-02, -2.65973937e-02, -8.24988075e-03, -1.24942614e-02,
       -9.69562959e-03, -8.96640960e-03, -2.25572076e-04,  1.99111248e-03,
       -2.06734408e-02,  2.40961090e-03, -8.79519619e-03, -4.77481494e-03,
       -1.04335835e-02, -4.29464458e-03, -2.32329667e-02, -2.38249358e-02,
       -1.41809713e-02,  3.46416188e-03, -1.84599441e-02, -1.19966250e-02,
       -4.89769876e-03, -2.50324905e-02, -9.40791238e-03, -3.03284712e-02,
       -2.24709250e-02, -2.36754380e-02, -1.85270782e-03, -1.42496796e-02,
       -3.22871911e-03,  9.72455554e-03, -1.63978264e-02, -1.83097124e-02,
       -1.35598537e-02, -5.31451497e-03, -2.45071799e-02, -1.73172653e-02,
       -3.66805471e-03, -3.75810079e-03, -1.03269117e-02, -1.04968715e-02,
       -5.79984207e-03, -1.17035415e-02, -5.59929525e-03, -1.06128538e-02,
        1.21078826e-03, -2.74178069e-02, -1.74647830e-02, -1.64130311e-02,
        1.17703667e-03, -2.41936091e-02, -1.25347236e-02, -1.20882457e-02,
       -1.76707078e-02, -1.50607005e-02, -1.96712445e-02, -1.04671093e-02,
       -1.83775760e-02, -2.04436183e-02, -1.34320254e-03, -8.38655420e-03,
       -1.79558736e-03, -1.28148459e-02, -2.47034151e-02,  7.64675252e-03,
        1.69518460e-02, -1.31173749e-02, -2.83280816e-02, -1.30580785e-02,
        9.38314013e-03, -4.32838500e-03, -1.13508161e-02, -7.41044944e-03,
       -1.50265982e-02, -1.21769514e-02, -2.17156764e-02, -1.78750847e-02,
       -1.29007129e-02, -1.31369997e-02, -2.00177617e-02, -1.30650392e-02,
       -1.30551001e-02, -1.36869829e-02, -1.53635051e-02, -1.98178720e-02,
        2.14427598e-02, -1.45638799e-02,  3.25510674e-03, -2.01425999e-02,
        5.24690188e-03, -1.59793831e-02, -3.80479917e-02, -1.53241847e-02,
       -2.00842153e-02, -1.40340962e-02, -1.40398592e-02, -1.29592540e-02,
       -4.15669382e-03, -2.12370474e-02, -7.98121467e-03, -2.35409141e-02,
       -1.09590339e-02, -3.09951622e-02, -1.04938075e-02, -2.33391356e-02,
       -1.95763316e-02,  9.39246267e-03, -1.65894926e-02, -1.71244536e-02,
       -1.83207318e-02, -1.83750167e-02, -1.52333034e-02, -1.17057767e-02,
       -1.95423011e-02, -1.96985714e-02,  4.87968326e-03, -1.17346635e-02,
       -3.40416282e-03, -8.73775501e-03, -2.19295193e-02, -9.13392380e-03,
       -1.31834429e-02,  2.67605181e-04, -5.73284505e-03,  4.93470998e-03,
       -2.43214238e-02, -7.63459643e-03, -2.14374415e-03, -1.80964321e-02,
       -4.47110971e-03, -9.27176792e-03, -1.29918149e-02, -1.68035664e-02,
       -7.38029275e-03,  7.77802605e-04, -1.91920809e-02, -9.96711664e-03,
       -1.47435600e-02, -2.50864532e-02, -1.56702753e-02, -2.38369480e-02,
        7.25520402e-03, -7.60930218e-03, -1.09761339e-02, -8.58030253e-05,
        1.54073571e-03,  1.31304003e-02, -1.42036453e-02, -1.68870371e-02,
       -1.73630752e-02, -1.31096225e-02, -5.15009603e-03, -1.82504449e-02,
       -1.95732992e-02, -1.97531693e-02, -5.72340982e-03, -3.92987952e-03,
       -3.11556719e-02,  8.12868495e-03, -1.19419871e-02, -1.68736409e-02,
       -2.22686259e-03, -2.54015345e-02, -1.72876101e-02, -1.44470725e-02],
      dtype=float32), array([0.01070192, 0.00704853, 0.00876155, 0.00835208, 0.00837269,
       0.00708035, 0.00839563, 0.0083184 , 0.00962877, 0.00759301,
       0.0082731 , 0.00755223, 0.00742316, 0.00846596, 0.00803631,
       0.00867997, 0.00877386, 0.00821114, 0.00813471, 0.0085466 ,
       0.00814837, 0.00887686, 0.00943514, 0.01042216, 0.00712607,
       0.00884869, 0.00788517, 0.00882616, 0.00953425, 0.00787377,
       0.00845322, 0.00975208, 0.00749356, 0.00792709, 0.00971246,
       0.00769791, 0.00718404, 0.00776214, 0.0084802 , 0.00743967,
       0.00876642, 0.00759539, 0.00812703, 0.01164832, 0.00951602,
       0.00717517, 0.00835908, 0.00873429, 0.00912572, 0.00832894,
       0.0079803 , 0.00952633, 0.0091339 , 0.00782965, 0.00808298,
       0.00828523, 0.00873658, 0.00840725, 0.00823957, 0.00828792,
       0.00991624, 0.008005  , 0.02177469, 0.00867801, 0.00777495,
       0.00744324, 0.00787202, 0.00731763, 0.00814363, 0.01418158,
       0.00979237, 0.00765687, 0.00877369, 0.00827194, 0.00843254,
       0.00759163, 0.00810645, 0.00795606, 0.01400981, 0.00742019,
       0.01055817, 0.00736174, 0.00779119, 0.01605145, 0.0137411 ,
       0.01160116, 0.00799674, 0.0078567 , 0.00831058, 0.01224923,
       0.00740344, 0.00816065, 0.00783463, 0.00814835, 0.00802913,
       0.0076173 , 0.00906315, 0.00788185, 0.00774461, 0.01009735,
       0.00779353, 0.00802936, 0.01019533, 0.00757362, 0.00717207,
       0.0087027 , 0.00967714, 0.00850492, 0.00807171, 0.00988921,
       0.00791598, 0.00941279, 0.00865681, 0.00872428, 0.00864274,
       0.00731681, 0.00884554, 0.00778203, 0.00773927, 0.02059441,
       0.00967944, 0.00786037, 0.00807437, 0.00872263, 0.00727592,
       0.0071642 , 0.00754409, 0.00858134, 0.00819089, 0.00748143,
       0.00878905, 0.0080457 , 0.00814141, 0.01302321, 0.00755787,
       0.00819368, 0.00959646, 0.00842918, 0.00769409, 0.00860451,
       0.00961563, 0.00762513, 0.01006541, 0.01077715, 0.00803235,
       0.01705278, 0.0077631 , 0.00848432, 0.00836707, 0.00755043,
       0.00726948, 0.00817398, 0.01429254, 0.00897349, 0.00820392,
       0.00797493, 0.01428008, 0.00839472, 0.01222355, 0.00845298,
       0.00846468, 0.00771413, 0.0136444 , 0.00819848, 0.00912213,
       0.00948492, 0.01076052, 0.00882631, 0.00789958, 0.00803904,
       0.00740966, 0.0087412 , 0.01028954, 0.0089863 , 0.00936415,
       0.0079996 , 0.00863595, 0.00879541, 0.00802728, 0.00732302,
       0.01440413, 0.00936321, 0.00820534, 0.00787349, 0.00777468,
       0.00745727, 0.00746274, 0.00796844, 0.00829899, 0.00733165,
       0.00739947, 0.00748883, 0.0082523 , 0.00899759, 0.00818749,
       0.0085432 , 0.00845806, 0.0078319 , 0.00734673, 0.00843414,
       0.00807022, 0.00782261, 0.00907235, 0.0076306 , 0.0113758 ,
       0.01339871, 0.00806215, 0.00793916, 0.00961215, 0.00732091,
       0.00855058, 0.00921346, 0.01100217, 0.00813951, 0.00967354,
       0.00800341, 0.00793107, 0.0126637 , 0.00747606, 0.00876475,
       0.0109405 , 0.00757435, 0.00915198, 0.01021238, 0.00754526,
       0.00879105, 0.00836069, 0.01057035, 0.00816632, 0.00807389,
       0.00820032, 0.01095204, 0.00898378, 0.00754036, 0.00903274,
       0.00976406, 0.00905269, 0.00699221, 0.009349  , 0.0075446 ,
       0.00993417, 0.00801629, 0.00994577, 0.00834422, 0.00959332,
       0.00733929, 0.00735324, 0.00824938, 0.01099711, 0.00854047,
       0.00821547, 0.00781737, 0.00821157, 0.00863577, 0.007992  ,
       0.00790293, 0.00839146, 0.00758337, 0.00855505, 0.01109737,
       0.00914283, 0.00969734, 0.00806434, 0.00949681, 0.00892792,
       0.00828244, 0.00874436, 0.00863214, 0.00888017, 0.0076711 ,
       0.00934753, 0.00775281, 0.00872401, 0.00904982, 0.00797923,
       0.01437691, 0.00871652, 0.00986918, 0.00939742, 0.01522851,
       0.01151624, 0.00793768, 0.00777986, 0.00887553, 0.00787766,
       0.00752654, 0.01347684, 0.00855442, 0.01106226, 0.00880642,
       0.00824135, 0.00815713, 0.00878365, 0.00782546, 0.00859166,
       0.00966555, 0.00947881, 0.00827723, 0.00914911, 0.00864748,
       0.01470814, 0.00803463, 0.01003375, 0.00928078, 0.00708699,
       0.00933026, 0.00956582, 0.0104649 , 0.01208247, 0.0105683 ,
       0.00925349, 0.00959164, 0.00880491, 0.01378373, 0.00899246,
       0.00956089, 0.00833221, 0.00831425, 0.00799893, 0.00897678,
       0.00766801, 0.00796241, 0.01603643, 0.0077577 , 0.00858769,
       0.00946065, 0.00977195, 0.00866478, 0.00814585, 0.00793569,
       0.01121837, 0.0094274 , 0.00775975, 0.00785755, 0.00971042,
       0.00785428, 0.00854115, 0.0118112 , 0.009512  , 0.00916409,
       0.01016655, 0.00835218, 0.00776484, 0.00784082, 0.00852919,
       0.01003312, 0.00768283, 0.00917588, 0.00850396, 0.01013981,
       0.01251629, 0.00841771, 0.00806511, 0.00795169, 0.01008931,
       0.00876252, 0.00996476, 0.00884897, 0.00899742, 0.00854085,
       0.00793746, 0.00858162, 0.00907028, 0.00865716, 0.00833606,
       0.00796449, 0.01116921, 0.00780602, 0.0078909 , 0.00989433,
       0.00808307, 0.00955381, 0.00870904, 0.0086325 , 0.00787405,
       0.00903395, 0.00755285, 0.00904256, 0.00770503, 0.00751445,
       0.00905909, 0.00835975, 0.00900438, 0.00845664, 0.00735289,
       0.0103827 , 0.0082088 , 0.00771399, 0.00807147, 0.00967747,
       0.00757001, 0.00810779, 0.00869368, 0.01102825, 0.0091102 ,
       0.00822395, 0.00819904, 0.00953664, 0.00787323, 0.00839791,
       0.0084051 , 0.00921702, 0.00825039, 0.00858105, 0.00782525,
       0.00870104, 0.00781238, 0.00760855, 0.00780132, 0.01255055,
       0.01091636, 0.01302406, 0.01131622, 0.00856887, 0.00893229,
       0.00993508, 0.0091978 , 0.00771284, 0.00816568, 0.00905984,
       0.00762915, 0.00787914, 0.00813169, 0.00842014, 0.0085725 ,
       0.00830602, 0.01194783, 0.00856804, 0.00799247, 0.00868702,
       0.00797341, 0.00849622, 0.01518454, 0.0073278 , 0.00760447,
       0.0112175 , 0.00874598, 0.00867419, 0.01430043, 0.00806762,
       0.0091572 , 0.0090579 , 0.00946541, 0.00759873, 0.00915873,
       0.00819847, 0.00852236, 0.00961713, 0.00729323, 0.0083267 ,
       0.00896369, 0.0092926 , 0.0081422 , 0.00971915, 0.0085996 ,
       0.00809757, 0.00797176, 0.00825255, 0.00962229, 0.01486686,
       0.00856765, 0.00876653, 0.01147415, 0.0078754 , 0.00865179,
       0.00797894, 0.00828094, 0.01102804, 0.00759684, 0.00880743,
       0.00757819, 0.00905981, 0.01510495, 0.00750841, 0.00876562,
       0.00778996, 0.00732987, 0.00823978, 0.00865997, 0.00888915,
       0.00767695, 0.01121604, 0.00900351, 0.00843115, 0.00792369,
       0.00867893, 0.0086486 , 0.00826034, 0.00949863, 0.00883473,
       0.00872879, 0.00797397, 0.00848726, 0.01151385, 0.0088551 ,
       0.00882482, 0.00819499, 0.00795272, 0.00812627, 0.00778154,
       0.00875907, 0.00853731, 0.00766612, 0.00881946, 0.01353542,
       0.00941258, 0.00925121, 0.00809748, 0.00735595, 0.00958815,
       0.00943913, 0.00786553], dtype=float32), array([[[[-0.04456919,  0.06596047,  0.02734585, ..., -0.05523195,
          -0.03898748, -0.00728486],
         [ 0.00509285,  0.04247482, -0.02245931, ...,  0.00588176,
          -0.06679426,  0.06175307],
         [-0.01685324,  0.06192771,  0.06544229, ..., -0.08070672,
          -0.00550539, -0.05678539],
         ...,
         [-0.02272489,  0.02295626,  0.052332  , ...,  0.02942408,
           0.00715213,  0.01086138],
         [ 0.06788057, -0.01294631, -0.07623819, ...,  0.01952109,
           0.00739784,  0.01527581],
         [-0.01590813,  0.02306282,  0.0146091 , ...,  0.03596197,
           0.03092908, -0.04975187]]]], dtype=float32), array([1.0309896, 1.0283196, 1.0142571, ..., 1.0111216, 1.025539 ,
       1.0041507], dtype=float32), array([ 0.0122693 ,  0.0477717 , -0.00916672, ...,  0.00944795,
        0.00201776,  0.03645141], dtype=float32), array([-0.04489447, -0.34944534, -0.54552025, ..., -0.35823575,
        0.12985046, -0.1941539 ], dtype=float32), array([0.1689419 , 0.2219669 , 0.15729302, ..., 0.25042593, 0.28443798,
       0.3737484 ], dtype=float32), array([[[[-0.04581178],
         [-0.01132456],
         [ 0.0312352 ],
         ...,
         [-0.00960175],
         [-0.03557804],
         [-0.03133814]],

        [[ 0.05271244],
         [-0.04157175],
         [-0.02554474],
         ...,
         [-0.03747858],
         [ 0.02879379],
         [ 0.00645024]],

        [[-0.03809835],
         [ 0.00900023],
         [ 0.0178722 ],
         ...,
         [-0.02148643],
         [ 0.02407349],
         [ 0.0062594 ]]],


       [[[-0.03425085],
         [ 0.02358079],
         [-0.03514521],
         ...,
         [ 0.01491538],
         [-0.01051935],
         [ 0.02245147]],

        [[-0.02009397],
         [-0.00218562],
         [-0.02755472],
         ...,
         [-0.01137833],
         [-0.03324026],
         [-0.02571724]],

        [[ 0.00373313],
         [-0.03747436],
         [-0.00917107],
         ...,
         [-0.02649587],
         [ 0.02930556],
         [ 0.0211284 ]]],


       [[[ 0.03476874],
         [-0.0219488 ],
         [-0.0034703 ],
         ...,
         [ 0.02554175],
         [ 0.01225037],
         [-0.02101663]],

        [[-0.01700578],
         [ 0.02698187],
         [-0.0006611 ],
         ...,
         [-0.00433649],
         [-0.00769731],
         [-0.05178922]],

        [[-0.02123247],
         [-0.01572622],
         [-0.00403504],
         ...,
         [ 0.03079108],
         [-0.0671456 ],
         [ 0.00544255]]]], dtype=float32), array([1.0302479, 1.033273 , 1.012755 , ..., 1.0112175, 1.0270673,
       1.0073359], dtype=float32), array([ 1.0312928e-02, -3.1298667e-03,  1.5235030e-02, ...,
       -8.2091850e-05,  4.6979625e-02,  2.2130530e-02], dtype=float32), array([-0.02313532, -0.02408328, -0.01470176, ..., -0.01560795,
       -0.02234524, -0.02058726], dtype=float32), array([0.00918442, 0.0078933 , 0.00774027, ..., 0.00787406, 0.00968734,
       0.00871806], dtype=float32), array([[[[-0.01376945, -0.0370395 ,  0.00418071, ...,  0.00810318,
          -0.00857445, -0.07651302],
         [ 0.02268407,  0.05404049,  0.0224194 , ..., -0.00962178,
           0.01877457, -0.01554693],
         [ 0.01093589,  0.03494577, -0.06114794, ...,  0.02757071,
          -0.01190057, -0.05982756],
         ...,
         [ 0.03080108,  0.05010536,  0.04055557, ..., -0.05784966,
           0.02721333, -0.02908299],
         [ 0.02846921, -0.01108154, -0.0401443 , ...,  0.02696306,
          -0.00105396, -0.05985061],
         [ 0.00688862, -0.01102976,  0.02746428, ..., -0.04527574,
           0.03127968, -0.05240337]]]], dtype=float32), array([0.99011683, 0.96057004, 0.9925837 , ..., 0.9897202 , 0.9741873 ,
       0.984994  ], dtype=float32), array([-0.00489925, -0.03587189, -0.00314841, ..., -0.00750572,
       -0.02370118, -0.01215337], dtype=float32), array([0.03918162, 0.31611937, 0.1552397 , ..., 0.67580676, 0.0842531 ,
       0.0150525 ], dtype=float32), array([0.32479995, 0.38693807, 0.38293874, ..., 0.46354455, 0.27249575,
       0.47687626], dtype=float32), array([[ 0.00188276, -0.05170051],
       [ 0.03894642,  0.03691233],
       [ 0.01212961, -0.05610387],
       ...,
       [ 0.03789616,  0.0020443 ],
       [-0.00614871, -0.00109564],
       [-0.00230215,  0.05650698]], dtype=float32), array([ 0.00458599, -0.004586  ], dtype=float32)]

weights_of_Inception = members[1].get_weights()
print(weights_of_Inception)

[array([[[[ 0.05001403, -0.08404427, -0.12928762,  0.01997367,
           0.09671957, -0.06124135,  0.04189337, -0.01883661,
          -0.01188476, -0.10634331,  0.07826533,  0.00500879,
          -0.10053271, -0.06170962, -0.14212444, -0.02980095,
          -0.0515077 , -0.12389146,  0.11510424,  0.09058365,
          -0.13225046,  0.070985  , -0.03192156,  0.04066586,
           0.09900218,  0.10432072, -0.07891849,  0.08516747,
          -0.04428835, -0.10583081,  0.0087005 ,  0.07391702],
         [ 0.1253202 ,  0.05151203,  0.0031286 ,  0.10781213,
           0.08362129, -0.14174454, -0.12727389,  0.06948912,
           0.04870854,  0.06740022, -0.12189879,  0.05225517,
           0.05244799,  0.06254877,  0.11858   ,  0.0841798 ,
          -0.14306974,  0.04092298, -0.09082153, -0.07433204,
          -0.0339638 ,  0.0465165 , -0.08232566,  0.13238244,
          -0.10841707,  0.067738  ,  0.10280099,  0.00884002,
           0.11785131,  0.07585137,  0.05809103,  0.00049599],
         [-0.00682301,  0.0696028 , -0.12872848, -0.01884271,
           0.0977573 , -0.02361584, -0.12038442,  0.13308458,
           0.0591577 , -0.09837029, -0.04687099, -0.10833323,
          -0.13169383,  0.03061853, -0.0632454 , -0.07428088,
          -0.08966576,  0.09382155,  0.08271617,  0.07779171,
           0.04821294,  0.07034416, -0.01506209, -0.05013636,
          -0.06850084, -0.0018277 ,  0.13561173, -0.12775773,
          -0.12764639, -0.1007582 ,  0.06632941, -0.14309251]],

        [[ 0.12504207, -0.03901382, -0.02990786, -0.12496476,
           0.08103688, -0.11512125,  0.05397363,  0.02783978,
           0.10647905, -0.06645985, -0.00540708,  0.03761332,
          -0.09198507, -0.07411625,  0.04335581, -0.11243889,
           0.07885464, -0.1156119 ,  0.0905093 ,  0.0715599 ,
          -0.10649067, -0.08208719, -0.06137238,  0.08993849,
           0.12770933,  0.12861478,  0.01908636, -0.14351724,
          -0.03972133, -0.12545018,  0.10601445,  0.07246029],
         [ 0.08848929,  0.06554797, -0.11372914,  0.10219435,
           0.13971929,  0.10297532,  0.0193314 ,  0.01375002,
          -0.02892682,  0.04692043, -0.05833901, -0.04523238,
           0.10217151, -0.08226506, -0.01869557,  0.07077126,
          -0.07364992,  0.08262726, -0.09271599,  0.0695491 ,
          -0.08596362, -0.13587007, -0.11489011,  0.03639224,
           0.12605153, -0.11728331, -0.06594002, -0.03847039,
          -0.11264347,  0.0082049 ,  0.12360984,  0.06554027],
         [ 0.08555238,  0.04122629,  0.07189797, -0.02682104,
           0.07930718,  0.0334197 ,  0.10529389,  0.12111671,
          -0.08918785, -0.02215262, -0.07185916, -0.00979468,
          -0.03241903,  0.01153427, -0.01510578, -0.06511504,
          -0.08696572,  0.00705304, -0.04492279,  0.00687735,
           0.10212443,  0.03990071, -0.01797672,  0.02853043,
          -0.01062384,  0.03529139,  0.06296036,  0.0117858 ,
           0.05267713, -0.06079439,  0.10553421, -0.07484406]],

        [[ 0.1294163 ,  0.13175417, -0.0806832 , -0.13123664,
           0.0142971 ,  0.09435797, -0.04283363, -0.12506911,
           0.09718765,  0.06444521, -0.02586058, -0.07359043,
           0.0930139 ,  0.10195431, -0.0818033 ,  0.12166782,
          -0.11492533,  0.07469942,  0.05574265,  0.1395463 ,
           0.11176679,  0.04256872, -0.05654236,  0.07012526,
          -0.06394782,  0.11579303, -0.03530041, -0.11316463,
          -0.08176446,  0.06244205, -0.00994485,  0.01639265],
         [ 0.04357307,  0.08012231, -0.06968357, -0.09258334,
          -0.02515639,  0.07387807, -0.06736895, -0.09866785,
           0.06021139,  0.06864798, -0.0962012 , -0.02456097,
           0.01621952,  0.04687588, -0.03742072, -0.09065626,
          -0.05628946, -0.09529576,  0.01166561,  0.14460887,
          -0.0255145 , -0.09749985, -0.05052647, -0.07922491,
           0.09904857, -0.00845166, -0.05974889,  0.11339401,
          -0.0597317 , -0.04857253, -0.02814135, -0.0066657 ],
         [ 0.0370184 , -0.08435465, -0.10666618,  0.04145589,
          -0.12995957,  0.0910522 , -0.1088091 ,  0.04580457,
           0.0701194 ,  0.08838973, -0.07307665, -0.09728301,
          -0.05919793, -0.04965879,  0.13566643, -0.10476615,
          -0.11802418,  0.01363418, -0.04030026, -0.0195242 ,
           0.04357117,  0.00394295,  0.09614649, -0.09240172,
           0.11927277,  0.00576859, -0.10853216,  0.10628048,
          -0.09355675, -0.13464408, -0.05191011, -0.04478338]]],


       [[[ 0.11851073, -0.01433491,  0.02145288, -0.05097065,
           0.11817513, -0.01833662, -0.1220135 , -0.14897834,
           0.06472461, -0.10595636, -0.09531742, -0.07039778,
          -0.06020544,  0.11667667,  0.10897597, -0.07846186,
          -0.09667684, -0.0272509 ,  0.11872146, -0.02468745,
           0.03175848, -0.03464798,  0.00792839, -0.12062879,
           0.10937934, -0.03928557, -0.00265233, -0.11040648,
           0.03047329,  0.02649269, -0.00364025, -0.04555824],
         [ 0.07801174, -0.06358051,  0.13298139,  0.03015367,
          -0.08723771,  0.00547336,  0.011322  ,  0.09616121,
           0.14569308, -0.01947507, -0.10341785, -0.11865827,
           0.0587444 ,  0.10065921,  0.02227451,  0.12266727,
          -0.07409732,  0.03866747, -0.11835398, -0.08591336,
           0.10751567, -0.04957941,  0.0900992 , -0.00283721,
           0.1122912 , -0.05111596,  0.13680497,  0.05915523,
           0.01256406,  0.08862475, -0.03332454,  0.02592374],
         [ 0.03340084, -0.12146914,  0.01419715,  0.03134283,
          -0.08623189, -0.07469532, -0.01021453, -0.09689725,
           0.10762037, -0.13740116, -0.02036628,  0.01545909,
          -0.07107921,  0.02215272,  0.0620156 , -0.04129068,
          -0.09355639,  0.11573779,  0.11884553,  0.04807375,
          -0.06762137,  0.07553015,  0.04248201,  0.02123099,
          -0.1187294 , -0.04938892,  0.0763615 , -0.07366257,
          -0.11395562,  0.07440751, -0.04130421,  0.12003183]],

        [[-0.03963758,  0.05655216, -0.09516051,  0.02423759,
          -0.00136426,  0.11633381, -0.11512713, -0.09418183,
          -0.06613422, -0.0505918 ,  0.090978  ,  0.12073413,
          -0.01257824, -0.10745428, -0.03947522, -0.08303154,
           0.03289282,  0.08587422, -0.0314019 ,  0.1086821 ,
           0.08739829, -0.11791797, -0.10970465,  0.07655493,
           0.0758973 , -0.06153626,  0.07121956,  0.01574468,
          -0.01733072, -0.11097372, -0.12918225, -0.00612243],
         [-0.10865701,  0.04034073,  0.01325736, -0.14256155,
           0.09509881, -0.14999141, -0.05420836, -0.03955869,
          -0.11234289,  0.00128913, -0.11533371, -0.08561134,
          -0.03974614, -0.0576    ,  0.07898185, -0.07972597,
          -0.07295804,  0.06965584,  0.00033474, -0.03546578,
           0.10064954,  0.04200601, -0.1453774 , -0.00898084,
          -0.05419182, -0.1112771 ,  0.03346434,  0.11184846,
           0.05679395, -0.05196004,  0.07563701,  0.0691806 ],
         [-0.00483097, -0.04004151, -0.08131947,  0.1062643 ,
           0.06435069, -0.07105462, -0.03935237,  0.05643372,
           0.05643696, -0.06171589, -0.09752154, -0.06487616,
           0.11225019, -0.08110129,  0.01176967,  0.01656505,
          -0.09765282, -0.03140379,  0.10665103,  0.10499387,
           0.07767037, -0.10013589,  0.01748634, -0.1145023 ,
          -0.11978608,  0.02582096, -0.07340986,  0.01337643,
          -0.00412067,  0.11143178,  0.10814013, -0.13817091]],

        [[-0.0208487 ,  0.04361318, -0.11339621,  0.01335377,
           0.08524463,  0.02827386, -0.07614007,  0.03606755,
          -0.13212706,  0.04354361, -0.00454641,  0.02625487,
           0.06798359,  0.04682108, -0.12730455,  0.05176111,
           0.07460231,  0.02350338, -0.06475397,  0.02323592,
          -0.11541384, -0.12772056,  0.01578074,  0.02623277,
           0.00282117,  0.02732955, -0.02693424, -0.06162922,
           0.06552697,  0.11199991, -0.03117683, -0.06416468],
         [-0.05164821, -0.05196841, -0.02930307, -0.12587759,
          -0.0649761 , -0.01043267, -0.03025725,  0.02475434,
           0.05993967, -0.08390343, -0.04306237,  0.1199573 ,
           0.0873168 , -0.12607537, -0.05863185,  0.01868057,
           0.00634141, -0.01987125,  0.13129804, -0.11830647,
           0.0353879 ,  0.02814727, -0.1356759 ,  0.09113882,
           0.01823101, -0.03627988, -0.03255318, -0.10862878,
          -0.04019206,  0.00717618, -0.09177071,  0.10092339],
         [-0.12970506,  0.06090039, -0.12504503,  0.02151985,
          -0.12470898, -0.01501838, -0.05945818,  0.06234842,
          -0.04397056,  0.09695003,  0.05257032, -0.01166748,
          -0.02315489,  0.0837587 ,  0.00792677,  0.10871598,
          -0.04079703,  0.06046341, -0.13741092,  0.09566719,
           0.09283368,  0.10489592, -0.08698503, -0.0876414 ,
          -0.14147948, -0.02362219, -0.11484059, -0.11126536,
           0.01724456, -0.01294118, -0.06975786, -0.10471352]]],


       [[[ 0.08789291,  0.08922455, -0.1126551 ,  0.02879821,
          -0.0067717 , -0.14235152, -0.00886306, -0.0895621 ,
           0.09324379,  0.04451815, -0.04843954, -0.0080316 ,
          -0.08507714,  0.09522298, -0.05395074,  0.03275574,
           0.08604086, -0.06932028,  0.05927048, -0.1331796 ,
          -0.13408765, -0.07462665,  0.10619223, -0.0197846 ,
           0.07725452,  0.0796512 , -0.08424743, -0.00362041,
          -0.1466322 ,  0.07868316, -0.07684171, -0.03357924],
         [ 0.01278129,  0.11627104, -0.0868543 ,  0.06211011,
           0.09835473,  0.08829214, -0.07831953,  0.09602803,
          -0.02893033,  0.04710921,  0.02713989, -0.10346152,
          -0.04787452, -0.11633387, -0.09938373, -0.0475305 ,
          -0.07957095,  0.05987502, -0.02799197,  0.12709951,
           0.11751162,  0.01864255, -0.02341312, -0.06572748,
           0.09052274,  0.06009413, -0.10389657, -0.02951173,
           0.11762066, -0.14730015,  0.1217388 , -0.00900268],
         [ 0.03784908, -0.08689694,  0.06193099,  0.02383016,
           0.02994908, -0.00996604,  0.08147783,  0.00168277,
           0.0163326 ,  0.04789898, -0.08081894,  0.03154204,
          -0.04165625, -0.03811385, -0.07579128,  0.06562308,
          -0.04287677,  0.01954335, -0.00343053, -0.05326658,
           0.05826059,  0.00269578, -0.08102049,  0.01892854,
           0.06677622,  0.09570628,  0.05624372, -0.08404943,
          -0.01431424, -0.02241457,  0.1318327 , -0.00574091]],

        [[ 0.10476302,  0.10620274,  0.05228418, -0.05911895,
           0.10277281, -0.12384868, -0.09213752,  0.11638941,
          -0.08142102, -0.00339308, -0.02228715, -0.13461044,
           0.09892178,  0.01747032, -0.1303867 ,  0.00601556,
          -0.05488828, -0.0843654 , -0.11565366, -0.0870425 ,
           0.12199912, -0.07958546,  0.04458934, -0.10812893,
           0.02981939,  0.09129728,  0.10275705, -0.13591415,
          -0.03877433, -0.10215382, -0.00241455,  0.06566422],
         [ 0.05900553,  0.03388361, -0.04774388, -0.13981982,
           0.01416244,  0.08849406, -0.01037809, -0.01231747,
          -0.00287502, -0.11579601, -0.09673508, -0.08424328,
           0.04758234, -0.02048137,  0.02983267,  0.02550272,
           0.09369179,  0.12170286, -0.03933213, -0.0189699 ,
           0.10401644, -0.07155386, -0.06721299, -0.08279008,
           0.09057745,  0.05754028,  0.04915036,  0.12357706,
           0.03072803,  0.01286643,  0.06523693,  0.09600382],
         [ 0.08013457,  0.07791582,  0.07465822,  0.04739431,
          -0.11192016, -0.06599462, -0.11410002, -0.09639182,
           0.09922852,  0.04793961, -0.089596  ,  0.11463627,
          -0.12513316, -0.0699565 , -0.07072534,  0.01511563,
           0.05449457, -0.04631174,  0.00382845, -0.04895649,
          -0.02155001, -0.08442844,  0.06287252, -0.14043152,
          -0.09703322,  0.01540243, -0.07679939, -0.0194235 ,
           0.00876689, -0.07697229,  0.15804626, -0.04240813]],

        [[ 0.07639272, -0.08842864,  0.02597953,  0.08970809,
           0.11204223,  0.12547553,  0.00756703,  0.08113363,
          -0.00401854,  0.03769845,  0.04290352,  0.07909507,
          -0.04917384, -0.1549064 , -0.07105926, -0.07102694,
          -0.03666889, -0.05756605, -0.13195588,  0.02825028,
          -0.03831824,  0.01959493,  0.02948517,  0.04884614,
           0.06473193,  0.11530261,  0.13610643,  0.10627954,
           0.02557742, -0.10927648,  0.00235815, -0.03734621],
         [-0.07444476,  0.05226946,  0.03420559, -0.12884693,
          -0.11513572,  0.09911779,  0.06483954,  0.02019894,
           0.09041093,  0.06088286, -0.12260681, -0.00739409,
           0.04666419, -0.12957394,  0.07625806, -0.1280362 ,
           0.04391889,  0.10995062, -0.09821996, -0.07994146,
           0.08820988,  0.13246565,  0.10082227,  0.08283088,
           0.02533422,  0.10079698,  0.12893173, -0.03525805,
           0.00743221, -0.06331853,  0.10688555,  0.04064801],
         [ 0.02091762, -0.07289605, -0.01920029, -0.04684537,
           0.12901558, -0.08054394,  0.05022071,  0.05621115,
           0.01327723, -0.10110245,  0.06284061,  0.08918141,
          -0.03268139,  0.08420155,  0.06228698, -0.04905665,
          -0.09594331, -0.03369688, -0.10499082,  0.14235385,
           0.11535899, -0.06728517, -0.12409446, -0.0954809 ,
          -0.03539905,  0.03171616, -0.03964119,  0.06606927,
          -0.10025899,  0.08984909,  0.05596811, -0.08554408]]]],
      dtype=float32), array([ 0.01051294, -0.01628543,  0.00577327,  0.01493218, -0.00407546,
       -0.01063741,  0.00158628,  0.01753806,  0.01899935, -0.00131525,
        0.00038262, -0.00026287,  0.00256455, -0.00203516,  0.01279895,
       -0.00542939,  0.02139459,  0.00966414, -0.01820927,  0.0049124 ,
        0.01049738,  0.01301723,  0.00166706, -0.00193298,  0.00335461,
        0.00585024, -0.00982621, -0.00626677, -0.00521157, -0.0082636 ,
        0.00512624, -0.01991164], dtype=float32), array([ 0.57586783,  0.22839677, -0.51598096, -0.20263591,  0.44136992,
       -0.06635146, -0.47465673,  0.08710928,  0.29403836, -0.11418335,
       -0.56844366, -0.18361111, -0.05936314, -0.1469253 , -0.24922167,
       -0.15718648, -0.5212875 ,  0.1035212 , -0.09665655,  0.26955935,
        0.30193287, -0.2734683 , -0.30193192, -0.10181644,  0.3407237 ,
        0.39776382,  0.10803034, -0.23323303, -0.25572136, -0.29487395,
        0.35121232, -0.00954748], dtype=float32), array([0.09858529, 0.08402656, 0.09664552, 0.08336984, 0.0908092 ,
       0.08160974, 0.09480195, 0.08386146, 0.08831353, 0.08196321,
       0.10912269, 0.08379369, 0.082036  , 0.08309321, 0.08433273,
       0.08254947, 0.10556481, 0.08496137, 0.08257215, 0.08611052,
       0.09340052, 0.08488726, 0.08845404, 0.08423313, 0.08744594,
       0.08911256, 0.08186573, 0.08387981, 0.08546782, 0.08601763,
       0.09541785, 0.082302  ], dtype=float32), array([[[[-5.06845899e-02, -1.14118923e-02,  6.33015633e-02, ...,
           3.69875878e-02, -7.26628006e-02,  7.58002922e-02],
         [-7.03773135e-03, -7.29263052e-02, -1.20465262e-02, ...,
           6.58963174e-02, -3.65934484e-02,  4.06471714e-02],
         [ 3.19482237e-02,  1.86153539e-02,  4.12323996e-02, ...,
           2.79349815e-02, -6.95780739e-02,  8.67953673e-02],
         ...,
         [ 4.43415679e-02,  2.46121287e-02,  2.71848049e-02, ...,
           2.60830354e-02,  9.20256525e-02, -5.32266200e-02],
         [-9.75497649e-04, -9.87667963e-02,  4.11998890e-02, ...,
           2.38984637e-02,  1.46232489e-02,  3.16700339e-02],
         [-5.19050770e-02, -2.47862637e-02, -1.35523248e-02, ...,
          -7.53503963e-02,  2.24487688e-02, -5.04740253e-02]],

        [[-4.46098298e-03, -5.41514205e-03, -1.03581950e-01, ...,
          -7.10948259e-02, -9.26241949e-02,  6.10518642e-02],
         [-4.04901169e-02,  2.59350017e-02,  2.64454633e-02, ...,
          -6.42037690e-02, -6.99324757e-02, -9.25030559e-02],
         [ 1.67528093e-02,  7.79927010e-04, -8.96894336e-02, ...,
          -4.77675460e-02, -5.24045676e-02,  6.11849166e-02],
         ...,
         [-2.07351204e-02,  1.38426814e-02,  1.25060026e-02, ...,
          -7.16118515e-02,  8.41125008e-03,  5.90825975e-02],
         [ 4.23683710e-02, -3.48729938e-02, -7.98445137e-04, ...,
           3.12644169e-02,  4.79476340e-02, -4.35533049e-03],
         [-1.17987670e-01, -5.63551821e-02,  3.25927548e-02, ...,
           1.78327467e-02,  4.23205569e-02, -7.72786066e-02]],

        [[-2.71459818e-02, -8.59334171e-02,  5.94437644e-02, ...,
           7.37371966e-02, -7.22712278e-02, -2.28720661e-02],
         [ 2.35576462e-02, -6.46596355e-03, -1.44898240e-02, ...,
          -6.88465219e-03, -3.73792276e-02, -1.01203248e-01],
         [-1.09624760e-02, -8.49832371e-02,  7.63145015e-02, ...,
          -5.68331107e-02, -5.68761975e-02,  4.04597782e-02],
         ...,
         [-7.64464587e-02,  1.52505897e-02,  2.31871717e-02, ...,
           6.67498708e-02, -8.15108567e-02,  5.08113094e-02],
         [ 5.67370094e-02, -9.85202715e-02, -7.68406987e-02, ...,
           3.00167277e-02, -1.01520747e-01, -6.21649325e-02],
         [ 2.46453732e-02,  2.12926324e-02, -6.42063795e-03, ...,
           1.55501463e-03,  8.93376488e-03, -9.03367549e-02]]],


       [[[-4.23310809e-02,  1.97465438e-02, -4.56039086e-02, ...,
           6.41498938e-02,  2.66529843e-02, -1.15839578e-01],
         [-8.33015740e-02, -3.95850465e-02, -1.82968918e-02, ...,
          -5.90944439e-02, -8.58352557e-02, -2.65183151e-02],
         [ 2.55086850e-02,  4.31596301e-02,  4.04169075e-02, ...,
          -3.10912542e-02, -3.08576841e-02, -8.70271865e-03],
         ...,
         [-1.38619300e-02, -8.48836005e-02,  3.15020159e-02, ...,
           3.53656001e-02,  9.16285068e-02, -3.15428562e-02],
         [-7.43751451e-02, -3.58892381e-02, -2.39982666e-03, ...,
           8.34498405e-02, -1.07529014e-01, -8.29462707e-02],
         [-6.35014251e-02,  9.27440971e-02,  7.65059218e-02, ...,
          -8.61102566e-02, -8.75290185e-02, -2.93078460e-02]],

        [[-4.92458791e-02, -1.01557344e-01, -9.22248363e-02, ...,
           3.39437388e-02, -1.06780164e-01,  8.34668279e-02],
         [ 7.44324401e-02,  6.27830774e-02,  4.69973385e-02, ...,
          -1.03778109e-01,  7.57158101e-02, -1.19725399e-01],
         [ 2.02738084e-02,  4.33913395e-02, -6.01739809e-02, ...,
           2.39554625e-02,  2.57795844e-02, -2.38504577e-02],
         ...,
         [ 6.60227984e-02, -7.43475854e-02,  6.04976639e-02, ...,
           5.52233271e-02,  2.03977264e-02, -7.09467456e-02],
         [-9.57975071e-03,  5.00244349e-02, -6.24610148e-02, ...,
          -9.88137498e-02, -4.18135449e-02, -2.26258114e-02],
         [ 6.63471594e-02, -8.53228495e-02, -2.51704976e-02, ...,
          -2.56186891e-02, -8.42124075e-02,  2.85881590e-02]],

        [[-3.47387493e-02, -6.81385472e-02, -1.23088202e-02, ...,
           2.94842217e-02,  2.66061369e-02,  3.90944481e-02],
         [-5.99384904e-02, -1.03376329e-01,  5.68371005e-02, ...,
          -1.65182278e-02, -2.24175546e-02, -2.80256663e-02],
         [ 5.87471835e-02,  7.67012686e-02,  1.11105867e-01, ...,
           5.43171428e-02, -3.86772603e-02, -4.26495390e-05],
         ...,
         [-8.83089080e-02, -2.26765573e-02, -1.62891317e-02, ...,
           3.14430147e-02,  4.67709452e-02,  2.54028086e-02],
         [-9.22335405e-03,  5.06372750e-02,  1.90618727e-03, ...,
          -4.71329987e-02,  9.44989547e-03,  5.93630411e-02],
         [ 5.45605496e-02,  5.00199236e-02,  6.58484474e-02, ...,
           6.92857802e-02, -6.85910657e-02, -6.69174716e-02]]],


       [[[-8.57234895e-02, -2.68822350e-02,  3.75991315e-02, ...,
           6.75554127e-02,  1.23416483e-02, -5.35251573e-02],
         [ 5.51303253e-02,  2.15659738e-02, -6.14877744e-03, ...,
          -9.84847099e-02,  3.93867381e-02, -3.54825221e-02],
         [-9.29899886e-02, -7.80963376e-02, -8.02541152e-02, ...,
           3.25213671e-02, -2.79819556e-02, -1.74345560e-02],
         ...,
         [ 3.60066630e-02, -4.62648124e-02, -4.96588685e-02, ...,
          -8.37471709e-02,  6.95637167e-02,  1.85809117e-02],
         [ 7.38105774e-02,  4.62341197e-02,  3.75195183e-02, ...,
           8.11599866e-02,  4.95929979e-02, -2.96217501e-02],
         [-5.29164411e-02,  1.04803681e-01,  6.92727715e-02, ...,
          -3.09576578e-02, -5.49685471e-02,  1.01893418e-01]],

        [[-9.80799943e-02,  5.33261523e-02, -6.30255565e-02, ...,
           7.50063881e-02, -2.72360221e-02, -3.49244177e-02],
         [ 6.31059185e-02,  5.81231639e-02, -1.08382218e-01, ...,
          -1.86277460e-02,  3.91011201e-02,  3.76325734e-02],
         [-9.61292610e-02, -6.89835995e-02,  1.87704992e-02, ...,
           5.26700877e-02, -6.23404086e-02, -7.76419267e-02],
         ...,
         [ 3.69327217e-02, -9.47825909e-02,  9.07071587e-03, ...,
          -4.28724997e-02,  7.54722729e-02,  9.37408805e-02],
         [ 1.30172716e-02,  5.92957288e-02, -1.05105631e-01, ...,
          -1.00881316e-01, -7.70924240e-02,  1.01751124e-03],
         [ 5.30079799e-03,  7.25085586e-02,  6.48833290e-02, ...,
          -3.06992815e-03, -2.98058894e-02, -7.01834336e-02]],

        [[ 8.92795846e-02, -5.85217923e-02,  7.44447066e-03, ...,
          -5.87501153e-02, -5.89052141e-02, -1.11981258e-01],
         [-1.98823493e-02, -3.87554951e-02, -7.10126311e-02, ...,
          -4.47902270e-02, -8.52593780e-02,  6.80176541e-02],
         [-5.67192510e-02,  8.24444592e-02, -8.12669694e-02, ...,
          -7.80345798e-02, -8.41991380e-02,  3.38108577e-02],
         ...,
         [ 3.65325212e-02,  1.10467505e-02,  1.05677798e-01, ...,
          -2.70103617e-03, -2.41498686e-02, -4.91008535e-02],
         [ 9.17625949e-02, -3.46836261e-02, -1.00245245e-01, ...,
           3.43736373e-02,  1.64168514e-02,  1.49616636e-02],
         [ 4.85384231e-03,  3.98290455e-02,  3.89085300e-02, ...,
           8.44533965e-02,  1.14230821e-02, -1.27113704e-03]]]],
      dtype=float32), array([ 0.01749056, -0.00440636,  0.00761334,  0.01046253,  0.01187541,
        0.0041736 , -0.00411253, -0.00377131,  0.01847508, -0.02035084,
       -0.00775725, -0.00707506,  0.01408958,  0.00866797,  0.00734674,
       -0.0058778 ,  0.00511613, -0.00290164,  0.01581854,  0.01010557,
        0.00107454, -0.00772215, -0.003059  ,  0.01308992,  0.00520133,
        0.0149211 , -0.0014595 , -0.00092827, -0.02457318, -0.00661597,
       -0.00108726,  0.00487753], dtype=float32), array([-0.6033819 ,  0.04080475,  0.34088683,  0.19346201, -0.8408579 ,
        0.02832554, -0.9455125 , -1.1306661 ,  0.31970543, -0.17509381,
        0.23276046,  0.47907287,  1.1378344 ,  0.22938713, -0.42719662,
       -0.37281403, -0.6729995 , -0.03637679, -0.20909178,  0.26191097,
        0.35937542, -0.14637786,  0.28110304,  0.08325385, -0.49536747,
       -0.2627768 ,  0.68878764, -0.37857556, -0.50014335, -1.0974203 ,
        0.16557491, -0.0030478 ], dtype=float32), array([0.5029681 , 0.9711143 , 0.96178395, 1.5283864 , 0.9975294 ,
       1.0432737 , 0.9246449 , 0.98490554, 1.5590485 , 1.0887115 ,
       0.39179844, 0.55965865, 1.5424109 , 2.0243034 , 0.8575686 ,
       0.6675347 , 0.7728125 , 0.5991742 , 0.7116301 , 0.81349444,
       0.4545921 , 0.6626501 , 0.9646544 , 1.2972608 , 1.2016387 ,
       0.46906376, 0.8885421 , 0.8660668 , 1.3950033 , 1.4966083 ,
       1.249522  , 1.1636529 ], dtype=float32), array([[[[ 0.01616245,  0.07180317, -0.02932638, ...,  0.06624523,
          -0.03144514, -0.01941841],
         [-0.06859587, -0.04625111,  0.08820429, ..., -0.02437857,
           0.01277113, -0.03591841],
         [ 0.03468329,  0.01702216, -0.08047984, ...,  0.08776579,
           0.05155998,  0.03342596],
         ...,
         [-0.00250432, -0.05669026,  0.02494137, ..., -0.03187719,
          -0.05319615, -0.05424339],
         [ 0.07642376,  0.0214439 , -0.04106373, ..., -0.06578378,
           0.01482474,  0.06328386],
         [ 0.03399897,  0.03053517, -0.06142202, ..., -0.01818435,
           0.00539863, -0.03031932]],

        [[ 0.03549534, -0.03177981,  0.07019717, ..., -0.02782037,
          -0.07716783,  0.0315509 ],
         [ 0.00661424,  0.03610351,  0.03816839, ...,  0.01837359,
          -0.01773978,  0.06487324],
         [-0.0482682 , -0.00544833, -0.03119059, ..., -0.01024908,
          -0.02470942, -0.07073247],
         ...,
         [ 0.07216176,  0.09259776, -0.07378338, ..., -0.03664261,
           0.00835857,  0.02278567],
         [ 0.03379634,  0.05109682, -0.02184553, ..., -0.06192052,
          -0.02938922,  0.02534647],
         [ 0.01998968, -0.05193486,  0.01653174, ...,  0.06189662,
           0.06538014, -0.0689617 ]],

        [[ 0.03113966,  0.01414585, -0.08139826, ..., -0.00514555,
          -0.09408946,  0.00925964],
         [ 0.0103138 , -0.03402913, -0.05583003, ...,  0.01539017,
          -0.03287487, -0.03574167],
         [-0.04642507, -0.03383038,  0.03048428, ..., -0.00431359,
          -0.00204423, -0.0094628 ],
         ...,
         [-0.01818146,  0.04874213,  0.07365029, ...,  0.07401262,
          -0.03429428,  0.06137849],
         [-0.02450573,  0.02007211,  0.06152155, ...,  0.0043958 ,
          -0.02663307, -0.02311921],
         [ 0.03358264,  0.01537441, -0.01801194, ...,  0.03257373,
           0.00205042,  0.01398624]]],


       [[[-0.05338809,  0.09962633,  0.02113789, ...,  0.04676424,
          -0.04608515,  0.08436215],
         [-0.06138641,  0.02191578,  0.00165729, ...,  0.02579834,
          -0.09167735,  0.04585061],
         [ 0.02929955,  0.09217455, -0.07983194, ...,  0.05226828,
          -0.01671343,  0.05750101],
         ...,
         [-0.06691285,  0.05844109, -0.02832001, ...,  0.03550165,
           0.04491864,  0.07270312],
         [-0.05535742, -0.01533039, -0.08431885, ...,  0.00482573,
           0.08948997, -0.02947059],
         [ 0.04828234,  0.01326901,  0.07098283, ..., -0.04693635,
          -0.00796457, -0.08460774]],

        [[ 0.01948353, -0.01351102, -0.03451343, ..., -0.04962301,
          -0.06104467, -0.00694591],
         [ 0.07250541, -0.03827009, -0.03908655, ...,  0.06200554,
           0.00702319, -0.00895854],
         [-0.05228547, -0.04115286,  0.00107777, ...,  0.02350092,
          -0.03343815,  0.01966154],
         ...,
         [ 0.06736892, -0.00592307, -0.04546309, ..., -0.0033749 ,
           0.05050909,  0.08079091],
         [ 0.01730445, -0.0754018 , -0.0458332 , ...,  0.01306763,
           0.03741191,  0.0490341 ],
         [ 0.0804734 , -0.07574037,  0.05917944, ...,  0.00991954,
           0.05756711, -0.06611919]],

        [[ 0.07832932, -0.03295712, -0.03280909, ...,  0.04018826,
          -0.10562174, -0.02697244],
         [ 0.07743476,  0.06915724, -0.00273206, ...,  0.04353385,
          -0.05189272,  0.01784781],
         [ 0.0169527 ,  0.07535134, -0.07147104, ...,  0.06051759,
          -0.0282045 ,  0.0651027 ],
         ...,
         [-0.05779515,  0.0428925 ,  0.04231552, ...,  0.01863475,
          -0.05885969,  0.06428977],
         [-0.05738283, -0.08714676,  0.04826094, ..., -0.06679317,
           0.08131407, -0.04802847],
         [ 0.06980525,  0.0251801 ,  0.0633857 , ..., -0.00123051,
          -0.02210655,  0.04964537]]],


       [[[ 0.05852839,  0.09463315, -0.02494355, ..., -0.09159317,
          -0.03756396,  0.03431401],
         [-0.03476391,  0.04885523, -0.01872605, ...,  0.03969171,
          -0.05760307,  0.00034225],
         [-0.02166804, -0.01933803, -0.04498555, ...,  0.0154876 ,
          -0.06092807,  0.0630512 ],
         ...,
         [-0.08931291, -0.02714093,  0.0114939 , ..., -0.06898563,
           0.01405897, -0.0074144 ],
         [ 0.05931441,  0.03570707,  0.01386653, ..., -0.05890171,
          -0.06859072, -0.05476366],
         [ 0.07354373,  0.01140993,  0.0127661 , ..., -0.02492699,
          -0.05302812,  0.07472087]],

        [[ 0.06020653,  0.03754609, -0.08418589, ...,  0.02141286,
          -0.00798594, -0.027976  ],
         [-0.05355558, -0.0149587 ,  0.02886341, ...,  0.08106834,
          -0.02143544, -0.02000127],
         [ 0.0907233 , -0.07775656, -0.04133456, ..., -0.0557407 ,
           0.0062621 ,  0.04160709],
         ...,
         [-0.05716458, -0.03752618, -0.05987885, ...,  0.0401633 ,
          -0.03384484,  0.02404683],
         [ 0.04297006,  0.07646392,  0.00324113, ..., -0.02440565,
          -0.05352378,  0.05239734],
         [-0.02604669, -0.07157977, -0.01130331, ...,  0.00411668,
           0.01174064, -0.04256069]],

        [[ 0.04862153,  0.04346148,  0.00225506, ...,  0.03888059,
          -0.09137533, -0.02595554],
         [ 0.02314643,  0.07122815,  0.06805412, ...,  0.06647559,
           0.0648111 ,  0.01053082],
         [-0.01349365,  0.00533289,  0.01888032, ..., -0.01623486,
          -0.01416868, -0.01452493],
         ...,
         [ 0.02086362,  0.09139357,  0.00358588, ..., -0.02269124,
          -0.00014994,  0.04357588],
         [-0.04389403, -0.03815339, -0.03171891, ..., -0.04649551,
          -0.05791669,  0.0246115 ],
         [ 0.01105452,  0.04763481,  0.04778643, ...,  0.08192701,
          -0.06392705,  0.05664222]]]], dtype=float32), array([-0.00159162, -0.00639912, -0.00257472,  0.00140651, -0.00737757,
       -0.01905286,  0.00687538, -0.01679878,  0.00904271,  0.00931021,
        0.01088255,  0.00706666, -0.00488839,  0.00780014, -0.00232725,
       -0.00643129, -0.00800094,  0.00207476,  0.01369479, -0.00244049,
        0.00603502, -0.01166452, -0.00836922, -0.01532809, -0.00278992,
       -0.01152532, -0.0086579 ,  0.004715  ,  0.01815051, -0.00526942,
       -0.01876804,  0.00121741, -0.0060854 , -0.01511656,  0.00648455,
        0.01269156,  0.00877365,  0.00304278, -0.01105287,  0.0068819 ,
        0.0097328 ,  0.00103437, -0.00751563,  0.01480806,  0.00333449,
       -0.00491315, -0.00305863, -0.0025089 , -0.01679825, -0.01122897,
       -0.00902603, -0.00986423,  0.00504674,  0.0104124 ,  0.01352122,
        0.00613126, -0.00935277,  0.00984356, -0.00472038,  0.01217445,
        0.01087935,  0.00962997,  0.00357605, -0.01605413], dtype=float32), array([ 0.7401041 ,  0.39492038, -0.42988864,  0.00731989,  0.34426808,
        0.63990587, -0.03165934,  0.04562566,  0.02830264, -0.6358806 ,
       -0.323617  , -0.12362154,  0.04716466, -0.10449193,  0.31906712,
        0.11770099,  0.20223173,  0.03542505, -0.2966414 ,  0.0189152 ,
        0.18376449,  0.49065208, -0.76227176,  0.0262911 ,  0.28845304,
        0.37172326, -0.29080924, -0.31288096,  0.11592586, -0.55915093,
       -0.05566189,  0.5169409 , -0.4473308 , -0.04649024, -0.55095345,
       -0.46604434, -0.4502395 , -0.07882734, -0.6324471 ,  0.1912797 ,
        0.6685201 ,  0.27329957, -0.19854337, -0.02409181, -0.25847712,
        0.31324   ,  0.40208495, -0.3151039 ,  0.72708374, -0.3150851 ,
       -0.49359706, -0.09901547,  0.00190206, -0.21858431, -0.33091328,
       -0.07115211, -0.872591  , -0.49526277, -0.34897205, -0.62842375,
       -0.15416326,  0.15153667, -0.7758642 ,  0.00100214], dtype=float32), array([1.066567  , 0.537149  , 1.2126102 , 0.363806  , 0.64730674,
       0.92918646, 0.33518252, 1.0049541 , 1.3961248 , 0.5888528 ,
       0.4854912 , 0.5721896 , 0.45483172, 0.46945247, 0.491828  ,
       0.6155258 , 0.42173323, 1.5464225 , 0.30920932, 1.292191  ,
       0.3909093 , 1.9865205 , 0.8699472 , 0.5341686 , 0.8036637 ,
       1.426572  , 1.2678492 , 1.0087277 , 0.56851304, 1.2325163 ,
       0.6616761 , 1.1532738 , 1.3877765 , 0.95457864, 2.1309679 ,
       0.98638487, 1.4462748 , 0.58667797, 0.90321094, 1.0164775 ,
       1.3237162 , 1.6719861 , 0.9972666 , 0.35428536, 0.85572565,
       0.36705557, 0.85124665, 0.643014  , 0.597443  , 1.0858968 ,
       1.6860026 , 0.49390492, 0.27964556, 0.410963  , 0.30591035,
       0.99369   , 1.2662947 , 0.72625846, 1.3072026 , 0.7501123 ,
       1.0599279 , 0.72335625, 0.9357421 , 0.90727866], dtype=float32), array([[[[ 0.1722294 ,  0.09291741, -0.17098793, ..., -0.09487336,
          -0.17941822,  0.03715719],
         [ 0.13150495, -0.04069666,  0.1548214 , ...,  0.17537232,
          -0.03698212, -0.21437903],
         [-0.06497008, -0.10051077, -0.14121489, ..., -0.1158565 ,
           0.03144418,  0.1776561 ],
         ...,
         [ 0.13097456, -0.15968877,  0.03708652, ...,  0.08713464,
           0.00685493,  0.04538187],
         [ 0.03880443,  0.16282737, -0.19986565, ..., -0.11991053,
          -0.10471676, -0.21282421],
         [ 0.1018115 ,  0.14936537, -0.09825377, ...,  0.02486297,
          -0.06356895,  0.16598146]]]], dtype=float32), array([-8.29358958e-03, -6.52184943e-04, -3.80280078e-04,  9.23013221e-03,
        1.10265380e-02, -6.77485578e-03, -4.81716171e-03, -1.34929526e-03,
        1.22785168e-02,  2.54995748e-03, -2.48594733e-04,  1.96461892e-03,
       -8.78002308e-03, -4.85171657e-03,  4.36750427e-03, -9.93264001e-03,
        6.35825936e-03,  1.33893988e-03, -7.15690432e-03, -2.01482530e-04,
       -1.10112093e-02, -2.78227939e-03, -2.65888823e-03, -4.71453695e-03,
       -1.91341620e-02, -2.09125746e-02, -1.58141963e-02,  1.25679439e-02,
        1.07910661e-02,  1.34325901e-03,  1.66511373e-03, -1.75803863e-02,
        2.85898801e-02,  4.00007889e-03, -4.35192697e-03,  1.33722555e-02,
       -2.98065250e-03,  7.69770890e-03,  3.35447094e-03,  1.48960054e-02,
       -1.81534346e-02, -1.47775293e-03, -6.18661568e-03,  3.29994247e-04,
        1.54941510e-02,  1.36143332e-02, -1.93199994e-05,  7.97965191e-03,
       -1.25845261e-02, -2.24112021e-03, -1.06866723e-02,  1.95113744e-03,
       -1.14162536e-02, -1.43078417e-02,  1.84474175e-03, -1.39696682e-02,
       -3.45266494e-03,  5.94449323e-03,  1.05861618e-04, -2.47495137e-02,
       -8.14781408e-04, -6.49674982e-03, -1.10006435e-02, -1.03436653e-02,
        1.81910507e-02, -4.90128156e-03, -1.83513444e-02, -1.07969753e-02,
       -1.65999727e-03,  5.30534424e-03, -1.71360113e-02,  2.61228764e-03,
       -6.69073546e-03, -1.68756361e-03,  1.63110755e-02, -4.55572095e-04,
        1.08697470e-02,  6.84822851e-04, -1.52699072e-02, -3.20929615e-03],
      dtype=float32), array([ 0.3318313 , -0.35788608,  0.568252  , -0.25618836,  0.2931389 ,
       -0.16813923,  0.21884014, -0.7230482 , -0.09602473, -0.6895416 ,
        0.06098173, -0.13804317, -0.15020159,  0.46866453,  0.03431937,
        0.17634362,  0.5436242 ,  0.3300107 , -0.22368315,  0.62620443,
        0.7385872 ,  0.27500427,  0.08416019,  0.15619834,  0.09661838,
       -0.58384657,  0.43340036, -0.24427445, -0.14686061, -0.29275227,
       -0.08449607, -0.2589088 ,  0.03025842, -0.85043985, -0.08363517,
        0.7378642 , -0.725313  , -0.26530147, -0.6794683 , -0.1874792 ,
        0.06748825, -0.36440343, -0.26370478,  0.37541696, -0.24043219,
       -0.6516096 , -0.46035987,  0.2242661 ,  0.1430966 ,  0.45914385,
       -0.2500875 ,  0.19996406,  0.55326205,  0.25355294, -0.30224782,
        0.16587247,  0.04200233,  0.10127656,  0.1230832 ,  0.16977409,
       -0.10150546, -0.23885335,  0.1996705 ,  0.28694013,  0.06506784,
        0.12689632,  0.8653565 , -0.20840967, -0.12603985,  0.06155925,
        0.10531262, -0.37017977,  0.08406179,  0.48828408,  0.29281256,
        0.2551767 , -0.5522674 , -0.24130487,  0.09495854,  0.9019258 ],
      dtype=float32), array([0.9894484 , 0.40138265, 0.4537862 , 0.35639918, 0.36513677,
       0.5421469 , 0.19569065, 0.672513  , 0.6692421 , 0.28625986,
       0.65254676, 0.6711092 , 0.5458401 , 0.3091953 , 0.37011188,
       0.26850864, 0.5987721 , 1.4057105 , 0.25945982, 0.6543121 ,
       0.29497772, 0.50785863, 0.22049418, 0.24405621, 0.2165366 ,
       0.70917505, 0.42227045, 0.2682883 , 0.47194368, 0.5916636 ,
       0.21934791, 0.2765813 , 0.3408546 , 0.6417075 , 0.91683686,
       0.57032335, 0.30838457, 1.0823565 , 0.5700007 , 0.28008252,
       0.27721116, 0.24071383, 1.4319618 , 0.31738597, 1.5782799 ,
       0.419652  , 1.3034164 , 0.42736077, 0.3004933 , 0.39338344,
       0.8202298 , 0.44333532, 0.45206147, 0.43457437, 0.3707337 ,
       0.6118537 , 0.75718164, 0.26327354, 0.5850593 , 0.3699034 ,
       0.44315442, 0.39530352, 0.67549324, 0.27326345, 0.57979554,
       0.3743429 , 0.31571686, 0.38556367, 0.30341664, 0.6013103 ,
       0.7022544 , 0.28510058, 0.56792575, 0.31075168, 0.31284115,
       0.60236585, 0.51738364, 0.5579375 , 0.32761496, 0.30816525],
      dtype=float32), array([[[[-0.023553  , -0.02347214,  0.01060804, ..., -0.01631841,
          -0.02286558,  0.04422485],
         [-0.02364814, -0.0243223 , -0.02759446, ...,  0.05958426,
          -0.0163719 , -0.03229615],
         [-0.01046614,  0.00973392, -0.00336385, ...,  0.04660837,
           0.03005492,  0.00012028],
         ...,
         [-0.00539512, -0.01417356, -0.04362076, ...,  0.06060963,
          -0.01498423, -0.04852032],
         [-0.00204823, -0.00147148,  0.03167795, ...,  0.02899852,
          -0.02361752,  0.02604842],
         [ 0.00627197,  0.01792236,  0.04766482, ..., -0.04624181,
           0.0189668 ,  0.01905828]],

        [[ 0.05310633,  0.04325386,  0.03786881, ...,  0.00021817,
           0.00683009, -0.03503913],
         [-0.05656197, -0.00885034, -0.02265533, ...,  0.03644732,
           0.03600922,  0.04769364],
         [-0.03903306,  0.05051193,  0.0538323 , ..., -0.01924152,
           0.00306947, -0.00797165],
         ...,
         [ 0.03388521,  0.023528  ,  0.01842968, ..., -0.00244185,
          -0.00951656, -0.03672258],
         [ 0.01816499,  0.02431151, -0.00443735, ..., -0.0210334 ,
          -0.00600168, -0.02772056],
         [ 0.00944807,  0.02722242,  0.03669229, ...,  0.03367371,
           0.00416822, -0.00203338]],

        [[-0.02685449,  0.00450547,  0.02663658, ..., -0.03105398,
          -0.00625761, -0.01831569],
         [-0.06189742,  0.01725571, -0.03448705, ...,  0.04491749,
          -0.04500477, -0.03236842],
         [ 0.00908449, -0.03928294, -0.01592725, ...,  0.00893169,
          -0.00405381,  0.04621873],
         ...,
         [-0.00768799, -0.0295069 ,  0.01412299, ..., -0.01176357,
          -0.0088529 ,  0.02212858],
         [ 0.03671322,  0.0348633 ,  0.02675347, ..., -0.00571493,
           0.01003992, -0.03193476],
         [-0.0507836 ,  0.02054108,  0.05195059, ..., -0.02597548,
          -0.04338881,  0.00496817]]],


       [[[ 0.02010581,  0.00347514,  0.01196989, ..., -0.00261197,
           0.05214246, -0.04398741],
         [-0.03431352,  0.04121177, -0.037978  , ...,  0.06563443,
          -0.02750337,  0.02019747],
         [ 0.04819991,  0.00114031, -0.01878321, ...,  0.04600644,
          -0.01970348,  0.03294437],
         ...,
         [ 0.00922155, -0.04925893,  0.02629181, ..., -0.00330662,
           0.0520158 , -0.04331719],
         [ 0.04426899,  0.03801212, -0.05326691, ...,  0.00412156,
           0.01465291,  0.03103582],
         [-0.03435053,  0.01185557,  0.01624951, ...,  0.03472625,
           0.04042884, -0.03906886]],

        [[-0.00836012, -0.02160403,  0.01300639, ...,  0.03299447,
          -0.03749578, -0.02166007],
         [ 0.01583032,  0.03598913, -0.04092434, ..., -0.02987792,
           0.02808009,  0.00500496],
         [-0.04172641,  0.04289185,  0.00821445, ...,  0.04050514,
          -0.03535917, -0.01458022],
         ...,
         [-0.06460013, -0.04559794,  0.00307657, ..., -0.01519762,
          -0.00689724, -0.05039537],
         [-0.00644235, -0.0128416 , -0.03329797, ..., -0.01548762,
           0.00618739, -0.02485889],
         [ 0.04577968,  0.00625049,  0.01869431, ...,  0.02160591,
          -0.0562015 , -0.02831598]],

        [[ 0.00385435, -0.04315275,  0.03222093, ...,  0.02140513,
           0.03972287, -0.05368974],
         [ 0.00560412, -0.03653625, -0.0179959 , ...,  0.01948652,
          -0.04986784,  0.05014917],
         [-0.01979502, -0.04052869, -0.03565742, ..., -0.04910254,
           0.01410409, -0.04399402],
         ...,
         [ 0.01890453,  0.02985299, -0.00901501, ..., -0.01499028,
          -0.02052688, -0.01904027],
         [-0.02418794,  0.03471074, -0.03588169, ...,  0.01687589,
           0.03810678,  0.01695092],
         [-0.02586451,  0.03433675, -0.00057868, ..., -0.00337101,
          -0.04210649, -0.03606813]]],


       [[[-0.01690611,  0.01568785,  0.05052045, ...,  0.01071257,
          -0.02135543,  0.03917603],
         [-0.00289377, -0.00525356, -0.01006445, ...,  0.05826312,
          -0.02405461,  0.01815772],
         [ 0.00709459,  0.04601271,  0.04869427, ...,  0.01924104,
           0.02706056,  0.01120604],
         ...,
         [ 0.02613515,  0.03331304, -0.00966369, ...,  0.05685275,
          -0.02183677,  0.01774234],
         [-0.04105128,  0.01884132,  0.0272064 , ..., -0.05453565,
           0.01450952, -0.03615098],
         [-0.04907129,  0.00361599, -0.02911031, ...,  0.02276902,
           0.02217604, -0.01097934]],

        [[-0.03294962, -0.02600526,  0.03135256, ..., -0.00643005,
           0.02673892, -0.03672348],
         [-0.04950884, -0.06141799, -0.05939562, ...,  0.04985118,
           0.0380266 , -0.03174539],
         [-0.00890244,  0.05365449, -0.01816862, ...,  0.02461381,
           0.00035675, -0.03308991],
         ...,
         [-0.04556639, -0.04085687,  0.02225384, ...,  0.055576  ,
           0.0464248 ,  0.01339001],
         [ 0.01359878,  0.05522398,  0.02098034, ..., -0.03038528,
          -0.01361901,  0.02774769],
         [ 0.0043416 ,  0.04479714, -0.004773  , ..., -0.02271199,
          -0.01717644, -0.02355521]],

        [[ 0.01617499,  0.04166986, -0.0008294 , ...,  0.02278007,
           0.01955013,  0.02359236],
         [-0.05876644, -0.0126056 , -0.00085624, ...,  0.02198806,
          -0.02849099, -0.04179205],
         [ 0.03571175, -0.01311537, -0.0188619 , ...,  0.03390981,
           0.03826728, -0.00847274],
         ...,
         [-0.06048991, -0.0090309 , -0.0303351 , ...,  0.03404662,
           0.03088114, -0.00711156],
         [ 0.05156388,  0.0342943 , -0.01442948, ..., -0.03623113,
           0.03453802,  0.03376273],
         [ 0.01483541, -0.02262086, -0.01925387, ...,  0.02994097,
          -0.04255498, -0.01788209]]]], dtype=float32), array([-1.1426685e-02, -1.0323850e-02,  5.1636081e-03, -1.6483780e-02,
       -1.5349025e-02, -1.7251069e-02, -4.6445318e-03,  1.3281732e-02,
        4.1492786e-03,  1.0293339e-02, -2.1898312e-02,  8.9013996e-03,
       -9.4939061e-03,  1.5649862e-03,  3.5279572e-03, -7.2325775e-03,
        5.3534424e-04, -1.0915905e-02,  2.0644395e-02,  1.4027627e-03,
        1.1571937e-02,  9.0413010e-03, -2.2226946e-02,  1.1502661e-02,
       -7.5280587e-03,  5.4994393e-03, -2.1398811e-02,  1.2681028e-02,
       -1.1016518e-02, -8.0078347e-03, -1.5392427e-02, -4.5336029e-03,
       -2.1177806e-02,  1.0478873e-03,  1.4366235e-03, -9.7259684e-03,
        1.7364385e-02,  6.4347927e-03,  1.4403101e-02,  2.6622410e-03,
        9.5148683e-03, -6.0532773e-03,  1.1988099e-02, -2.3469051e-02,
       -1.9033246e-02, -7.2511490e-03, -3.3575441e-03, -5.1820385e-03,
        1.7939301e-02, -2.7676443e-02, -1.5528299e-02,  4.9556764e-03,
        1.4823894e-02,  2.4726144e-03, -1.0739800e-02, -5.9775123e-03,
       -6.3421292e-04,  9.6538076e-03, -9.1978535e-04, -1.1302769e-02,
       -1.4975436e-02,  1.1786125e-02, -2.1117192e-03,  1.8449692e-02,
        2.8401858e-03, -6.8737799e-03,  4.7407988e-03, -2.7568804e-03,
       -1.8804171e-03, -3.5644050e-03,  1.7008010e-02,  1.3339646e-02,
        2.5169991e-02, -2.9429756e-04,  1.9924315e-03, -2.3158252e-02,
       -1.5893016e-02,  1.3179630e-02,  2.3118962e-02, -1.7841967e-02,
        5.1787118e-03,  1.2762580e-02, -1.6434249e-02, -7.6517002e-03,
        2.6018467e-02,  1.0048350e-02, -2.0743555e-03,  4.9053319e-03,
        7.1263672e-03,  1.7237974e-03,  1.5442744e-02,  6.4596711e-03,
        1.2522904e-03, -4.9738986e-03,  7.3379804e-03,  1.3629807e-02,
       -4.0588665e-04,  2.1168408e-03,  7.2055594e-03, -9.9840360e-03,
       -1.9370653e-02,  1.2753756e-02, -8.2505569e-03,  1.0393390e-02,
       -1.6712654e-02,  1.3263976e-02, -1.0465457e-03, -1.6328096e-02,
       -5.0058491e-03,  6.7145028e-03, -3.3153375e-03,  3.6352389e-03,
       -1.3540499e-02,  2.8317668e-03, -8.9671258e-03,  1.9345433e-02,
        6.7620110e-03, -1.3975445e-02,  7.0708380e-03, -3.6994868e-03,
        6.6089263e-04,  1.1574505e-02, -1.1829913e-02, -5.8556432e-03,
       -6.4832158e-03,  5.5541983e-03, -2.6374878e-03,  1.4890046e-02,
       -1.0894407e-02,  8.8706566e-03, -4.3950020e-03,  3.4799022e-03,
        2.0588764e-03, -4.0773962e-02, -8.1463093e-03, -1.8555108e-02,
       -5.8574933e-03, -2.2909159e-03,  1.5396179e-02,  3.6132396e-03,
       -1.5843154e-03, -4.5380192e-03,  4.5073903e-03, -1.9737752e-03,
       -9.5511274e-03,  1.3864969e-03, -1.2688165e-02, -1.3241673e-02,
       -1.1928252e-02, -1.7768070e-02,  1.2704444e-02,  5.4230104e-04,
       -1.4656466e-02,  3.3985099e-03,  3.0904964e-03,  5.2681416e-03,
       -5.3995741e-03,  6.4660786e-03, -2.7914015e-03, -1.5536277e-02,
        5.1913960e-03, -1.1319219e-02,  8.6250454e-03, -1.2448829e-02,
       -7.8048423e-04, -8.4427033e-05,  6.6268486e-03, -1.6317133e-02,
        1.4611420e-02,  2.4659284e-03, -1.6563073e-02, -1.1358450e-02,
       -1.3951351e-02, -2.0354828e-02, -1.5228792e-02, -1.0729049e-02,
        6.5269782e-03,  1.0943441e-02, -5.0386316e-03, -1.3199947e-02,
       -4.4352724e-03,  5.0769723e-03, -9.2284998e-04,  1.2686647e-03,
        4.4923332e-03, -1.0226040e-02,  4.1421307e-03,  1.2148318e-02,
       -1.4575064e-02,  4.2662644e-03,  7.7792769e-04, -8.2779154e-03],
      dtype=float32), array([-6.93254769e-01,  6.23391680e-02,  4.07022864e-01,  6.07088566e-01,
        7.26379454e-01,  6.30179167e-01, -4.62384708e-02, -7.53810048e-01,
        4.53195632e-01, -3.95555645e-01, -6.45123482e-01, -4.27871644e-01,
        2.14041322e-01, -3.95984203e-01, -6.61469042e-01,  5.26883662e-01,
       -1.47248805e-01, -2.83454061e-01,  3.27634886e-02, -3.21126819e-01,
        1.25750196e+00, -4.31890070e-01, -7.43722856e-01,  1.97986856e-01,
        6.62152171e-01, -6.52883947e-01,  2.02437490e-01,  3.19556803e-01,
        3.17932338e-01, -7.10798919e-01,  2.09677488e-01,  6.16768420e-01,
        5.86089432e-01, -4.42964911e-01,  8.49225521e-01, -8.40717852e-01,
        2.53378510e-01,  2.26501316e-01, -3.28263730e-01,  6.59721196e-01,
        1.33265376e-01, -5.76851964e-01,  9.12302017e-01,  1.03883231e+00,
       -9.51449722e-02, -3.50030750e-01, -7.70354629e-01, -2.46341765e-01,
        1.25625432e-01, -8.90958965e-01,  3.05290431e-01,  5.00972867e-01,
        3.35998029e-01, -3.17185611e-01, -1.77187473e-01,  8.29030395e-01,
        2.21038640e-01,  7.31122851e-01, -3.16740498e-02, -1.03822875e+00,
        3.38085473e-01, -7.29433477e-01,  7.31540501e-01, -1.16506398e+00,
       -1.33774793e+00,  2.06870392e-01,  1.77405164e-01, -3.11651289e-01,
        6.28007114e-01,  3.92157435e-02,  2.43786827e-01, -3.98716092e-01,
       -7.07262039e-01, -3.04308385e-01, -1.84246466e-01, -6.01786196e-01,
        8.66050065e-01, -2.49840617e-02,  4.76587981e-01,  3.76108676e-01,
        4.63241190e-01, -8.89035821e-01,  2.54702121e-01,  1.72010921e-02,
        2.39103764e-01, -7.12869942e-01,  1.75320357e-01,  2.24743024e-01,
        7.59207904e-01, -7.15134382e-01, -2.36470699e-01,  4.04953063e-01,
       -3.42638135e-01,  5.40908933e-01, -1.00536108e+00, -1.12775576e+00,
        3.07813495e-01, -4.16044861e-01,  4.09936041e-01,  1.32889986e-01,
       -3.78331184e-01, -9.92494941e-01, -1.34136543e-01, -2.67927647e-01,
       -1.91989899e-01,  6.56886041e-01,  1.06203936e-01, -4.88502711e-01,
        7.03330755e-01,  1.45110741e-01, -9.80213061e-02, -4.15201411e-02,
        3.07455093e-01,  1.49628341e-01,  4.40270185e-01, -5.02703905e-01,
        6.71033680e-01, -2.12778166e-01,  8.35454583e-01,  5.31169415e-01,
       -1.38074422e+00,  6.54305279e-01, -3.80373687e-01, -1.25505164e-01,
        1.04815888e+00,  2.76342571e-01,  2.39473149e-01, -3.85990143e-01,
       -7.89739966e-01,  3.77588928e-01, -1.43084284e-02, -4.30545777e-01,
        2.60681003e-01, -7.38386661e-02, -5.90242088e-01,  1.99575782e-01,
        7.52359986e-01,  2.38543853e-01, -7.59754300e-01, -3.58226448e-01,
        7.62499213e-01,  3.01041275e-01,  5.31465150e-02, -2.43115485e-01,
        3.71124119e-01, -8.55034217e-02,  1.84875146e-01, -9.90554631e-01,
       -1.41626787e+00, -1.08097041e+00,  1.24690808e-01,  3.68873000e-01,
        3.79251987e-01, -1.74615547e-01,  6.77397013e-01,  3.98704320e-01,
       -8.12374473e-01,  6.64812177e-02,  9.93129760e-02, -1.79375008e-01,
        6.68392777e-01,  6.35855496e-01,  2.20135346e-01,  4.26480830e-01,
       -6.88609838e-01, -1.94907621e-01, -7.24707425e-01, -5.99669755e-01,
       -7.74622619e-01,  5.26530147e-01,  5.02708197e-01, -1.33443046e-02,
        5.91160282e-02,  7.89675653e-01,  1.18953967e+00, -4.22360510e-01,
        4.46017943e-02,  4.28507715e-01, -1.27731800e-01,  7.49821141e-02,
        7.49609917e-02, -6.09291494e-01,  1.18407421e-03,  1.58777639e-01,
        1.74846098e-01,  8.16732273e-02, -1.01476264e+00,  6.34566486e-01,
        1.20429742e+00,  6.17295623e-01, -3.86425108e-01, -8.41736019e-01],
      dtype=float32), array([1.5258913 , 0.9525019 , 1.9059925 , 1.1790905 , 1.6005192 ,
       2.1098495 , 2.3286397 , 4.09673   , 1.8187196 , 1.8890003 ,
       1.0253322 , 1.6651151 , 0.6824116 , 1.2773381 , 2.0969863 ,
       1.5242143 , 0.6070837 , 0.8793832 , 2.520953  , 0.5961634 ,
       2.5810008 , 1.8383474 , 0.7400097 , 1.3840629 , 1.1347095 ,
       1.0408404 , 0.7363681 , 0.68653613, 2.078118  , 0.7443214 ,
       1.4883596 , 1.0840216 , 1.583851  , 1.6973153 , 1.4381227 ,
       1.36612   , 0.684369  , 0.50050485, 0.9833383 , 1.5295271 ,
       0.5740561 , 1.5019219 , 1.3368665 , 1.4124434 , 1.4052299 ,
       1.0398092 , 2.0201807 , 2.2376058 , 1.5266013 , 1.4357637 ,
       0.80409294, 0.9596262 , 1.9564178 , 1.0678579 , 2.025943  ,
       2.3672621 , 0.9455071 , 1.0260818 , 0.7952289 , 1.5077928 ,
       0.65816134, 0.7276689 , 1.1741681 , 2.0310314 , 1.6935552 ,
       1.4191823 , 1.2487799 , 1.1426551 , 1.5273337 , 1.3478397 ,
       2.76041   , 1.2118169 , 1.1811525 , 0.71982193, 1.4004017 ,
       0.9469442 , 1.5126947 , 0.78872365, 1.3456875 , 0.93109477,
       1.4373721 , 2.0031056 , 0.8116957 , 1.4464449 , 1.3304981 ,
       1.9385505 , 1.1644303 , 1.600237  , 0.987401  , 0.85224956,
       1.118507  , 1.1643332 , 1.3773019 , 1.0524002 , 3.8763356 ,
       1.7486513 , 0.979838  , 2.5753605 , 1.4540719 , 1.0762285 ,
       0.82711893, 1.1433661 , 1.1045368 , 0.92007905, 0.7635821 ,
       0.9011698 , 0.9917409 , 1.0965776 , 1.9442059 , 1.0323914 ,
       0.84225035, 1.4285514 , 0.66866064, 0.89886564, 0.8017757 ,
       1.0304562 , 1.1491501 , 1.1763153 , 0.8801413 , 0.9109355 ,
       2.0424013 , 1.1630019 , 0.78379226, 1.1376783 , 0.9817335 ,
       1.4094467 , 1.9898871 , 2.3472552 , 1.8017678 , 1.9589218 ,
       0.88908446, 0.87921697, 0.7756291 , 0.58409214, 1.4620321 ,
       0.4640045 , 1.1904356 , 0.8568353 , 2.577426  , 0.71503407,
       2.2627406 , 0.9701614 , 0.9697685 , 0.76605046, 2.340695  ,
       0.6872256 , 1.4927152 , 1.0001038 , 2.5426407 , 1.9622337 ,
       1.10579   , 0.7002638 , 1.2002956 , 0.74791104, 1.1569629 ,
       0.8820443 , 0.9657204 , 1.4780594 , 1.0153769 , 1.5204618 ,
       1.8510286 , 1.5773579 , 0.9982553 , 0.8237752 , 2.4939175 ,
       1.4815235 , 1.3391892 , 0.9648374 , 1.8235296 , 1.6248219 ,
       2.461107  , 1.026025  , 1.3235284 , 2.2136507 , 2.1182373 ,
       2.8096137 , 0.8269894 , 1.0602424 , 1.6274673 , 0.8436667 ,
       1.2738976 , 1.709954  , 1.09913   , 1.2538625 , 1.6297932 ,
       0.7259535 , 1.6297642 , 1.2710505 , 2.0531354 , 0.96046084,
       1.888154  , 1.5988786 ], dtype=float32), array([[[[-0.00174994, -0.02077402, -0.08990444, ..., -0.10389641,
          -0.07724711, -0.04244774],
         [-0.1223864 ,  0.12966649, -0.13665685, ..., -0.14089821,
           0.0229838 , -0.07310337],
         [-0.02826863,  0.04544844,  0.13114457, ..., -0.04109905,
          -0.07353026, -0.00234619],
         ...,
         [-0.06352071,  0.01757231, -0.10358886, ..., -0.00182514,
          -0.0896966 ,  0.05173685],
         [ 0.01785809,  0.12518737, -0.11428677, ...,  0.04703457,
          -0.03531681,  0.10519907],
         [ 0.07370971,  0.0863717 , -0.0636995 , ..., -0.03657261,
          -0.05106504, -0.1136083 ]]]], dtype=float32), array([-0.0090093 , -0.0096586 ,  0.00326798,  0.0043256 , -0.00300224,
        0.00217911, -0.00155314,  0.00893018,  0.00477358, -0.00405314,
        0.0115742 ,  0.00139729,  0.00021723, -0.00375613, -0.00391791,
       -0.00467778,  0.00487644, -0.00383386, -0.01223712,  0.0032487 ,
       -0.0003931 ,  0.00089988,  0.00385493, -0.01087545,  0.0014636 ,
        0.01358644,  0.02580289,  0.00573262, -0.00794573, -0.00931195,
       -0.00981407, -0.00196794, -0.00478921, -0.02255113,  0.00704303,
        0.00322715, -0.02320541, -0.00214803,  0.00126053,  0.01008333,
       -0.00335565, -0.00388351,  0.01632844,  0.01188433, -0.00777338,
        0.01685664,  0.00472987, -0.01174204,  0.00607673,  0.01773796,
        0.0078021 , -0.00785663,  0.00958761, -0.01072423, -0.01857361,
        0.01515694, -0.00979264,  0.00604995, -0.01120724,  0.00250533,
       -0.00059415,  0.01322847, -0.0031809 ,  0.007303  ], dtype=float32), array([-0.20216912, -0.03044292, -0.31532577, -0.0409354 ,  0.2735178 ,
       -0.01025292, -0.5023601 , -0.19576408,  0.18867344,  0.04125151,
        0.53134656,  0.48506448,  0.28373313, -0.2547822 , -0.60448927,
       -0.60664976,  0.6198374 , -0.3318028 ,  0.40717205,  0.47225374,
        0.7858562 ,  0.6363815 , -0.2022712 ,  0.35961375, -0.7417623 ,
        0.50561595, -0.3884014 ,  0.13351859,  0.07824607, -0.22626986,
       -0.4246773 , -0.6423942 ,  0.28608364,  0.59153974, -0.38233608,
       -0.37489277, -0.6283063 ,  0.80429375, -0.49370202,  0.9183315 ,
        0.7277286 ,  0.33182302, -0.21628922, -1.0385027 ,  0.93461037,
        0.5202876 ,  0.41369167, -0.7904901 ,  0.17563014, -0.37411582,
        1.31692   ,  0.985711  ,  0.02264384,  0.14739412,  0.21526818,
       -0.74907684, -0.48774928,  0.8065215 ,  0.00269237,  0.5346485 ,
       -0.4010602 ,  0.8825593 ,  0.14692941, -1.2273142 ], dtype=float32), array([0.8705349 , 0.81009763, 0.82028323, 2.2729902 , 1.3671665 ,
       1.0815579 , 1.4288301 , 1.0519255 , 2.284768  , 1.2547054 ,
       0.95852125, 1.0718696 , 1.2488414 , 1.1879227 , 1.4845788 ,
       1.7293832 , 1.0380099 , 0.95151603, 1.8122535 , 1.7525625 ,
       0.9372951 , 1.4299293 , 0.92763436, 0.7571234 , 1.1160624 ,
       1.6757046 , 1.0631148 , 0.80559933, 2.6714947 , 1.5838805 ,
       1.1989349 , 2.1771464 , 0.5582677 , 0.8726791 , 1.0724901 ,
       1.3361117 , 1.4814259 , 1.5080055 , 1.5286276 , 1.6774383 ,
       1.2410156 , 0.85706586, 1.2596862 , 1.1055802 , 0.9273138 ,
       0.9889752 , 1.2338426 , 1.2646525 , 1.1918108 , 1.0629004 ,
       2.3448365 , 0.8165306 , 1.9875795 , 0.65342724, 1.990636  ,
       2.0981188 , 1.2614069 , 1.6591183 , 1.0987301 , 0.8373391 ,
       1.5098959 , 1.7973394 , 0.9531049 , 2.4576404 ], dtype=float32), array([[[[-0.0062662 ,  0.08731502, -0.13799454, ..., -0.0572334 ,
          -0.03055692,  0.08981111],
         [ 0.13675655, -0.15337528, -0.12989612, ..., -0.00902565,
          -0.05375974,  0.07555696],
         [ 0.14528434,  0.14931647,  0.14937142, ...,  0.1206786 ,
           0.02888592, -0.09743568],
         ...,
         [-0.06119655, -0.08806603,  0.14400327, ...,  0.11693732,
          -0.01355311, -0.13715017],
         [-0.14050376,  0.03523602, -0.11951368, ..., -0.10315738,
           0.00677658,  0.16588001],
         [-0.12761652, -0.14588252, -0.01550961, ...,  0.15901597,
          -0.11000101, -0.07505356]]]], dtype=float32), array([[[[ 0.05875852, -0.02368799, -0.01934705, ...,  0.00478107,
           0.00829528, -0.03763717],
         [-0.02221536,  0.04373951, -0.04323851, ..., -0.05801564,
          -0.0548587 , -0.05792918],
         [-0.02123541,  0.01551444, -0.03305597, ...,  0.06144784,
           0.02851605, -0.01754546],
         ...,
         [-0.05560146,  0.04806308, -0.00959076, ...,  0.01863008,
           0.03473581,  0.03759416],
         [ 0.05536852,  0.03090284, -0.00455972, ..., -0.04867153,
          -0.04026996,  0.03959526],
         [ 0.03232472,  0.04103415, -0.04920789, ..., -0.02389194,
           0.00146728, -0.03545061]],

        [[-0.03124356, -0.05112184,  0.02899338, ..., -0.04045129,
          -0.06666243, -0.05923742],
         [-0.01509822,  0.01603299, -0.02986675, ...,  0.00747819,
           0.01031041, -0.01561219],
         [ 0.00506473,  0.01474863,  0.03095078, ..., -0.01714091,
           0.03097096, -0.04861555],
         ...,
         [-0.00878163, -0.00749083, -0.05470997, ..., -0.06269198,
           0.05724655,  0.05076545],
         [ 0.05689324, -0.02575936, -0.02238772, ...,  0.05157059,
          -0.03079625,  0.02442488],
         [ 0.04461277, -0.05626639, -0.03890077, ..., -0.0317648 ,
           0.02604338,  0.03063676]],

        [[ 0.04815874, -0.00754243,  0.06414981, ...,  0.0529996 ,
          -0.05135956,  0.03341335],
         [ 0.00436393,  0.03064366,  0.04458646, ...,  0.05373255,
           0.02934948,  0.04049824],
         [ 0.06355841,  0.0417129 , -0.01999502, ..., -0.02140066,
          -0.07677749,  0.00126633],
         ...,
         [-0.01468699,  0.06312216,  0.07661526, ...,  0.03932112,
          -0.01219312, -0.05032389],
         [ 0.06804056,  0.00941288,  0.04861818, ..., -0.00351705,
          -0.04679286,  0.05555672],
         [-0.05158657,  0.04370295,  0.05286275, ..., -0.04022775,
          -0.06178313, -0.04292147]]],


       [[[ 0.05494109,  0.01620139,  0.03029749, ..., -0.0112492 ,
           0.04247785,  0.02655284],
         [-0.05117793,  0.02376555,  0.04291978, ..., -0.02334841,
           0.00575357,  0.03708675],
         [-0.03587228,  0.04655474,  0.02784652, ...,  0.04921586,
           0.00669978, -0.01342084],
         ...,
         [-0.031272  , -0.00819779,  0.04734235, ..., -0.02186048,
           0.03429283, -0.06085661],
         [-0.05208115,  0.00048078,  0.01691408, ...,  0.02618483,
           0.06430364,  0.00022199],
         [ 0.03613111, -0.05252246,  0.07336531, ...,  0.01986354,
           0.06116404, -0.05188882]],

        [[-0.0147811 , -0.02457596,  0.07247256, ...,  0.05458339,
          -0.05214138, -0.03240107],
         [ 0.01204737,  0.05635765, -0.04228342, ..., -0.03330992,
          -0.05796546,  0.03789876],
         [ 0.05004261,  0.06126299, -0.04902439, ...,  0.03599916,
          -0.01371751, -0.03736677],
         ...,
         [ 0.05733849, -0.04906272,  0.07275748, ...,  0.04773162,
           0.04060126,  0.02649196],
         [ 0.00946173,  0.0569525 ,  0.0335175 , ..., -0.03427492,
          -0.04425353, -0.05085527],
         [-0.0383004 ,  0.06717878,  0.00933695, ..., -0.05739511,
           0.0037016 ,  0.0290094 ]],

        [[-0.00241163,  0.02489349,  0.01528847, ..., -0.02043718,
           0.0351884 , -0.05491884],
         [ 0.053148  ,  0.04611893, -0.06816381, ...,  0.02790187,
          -0.03940848, -0.06781618],
         [ 0.04024241, -0.03926692,  0.04457527, ...,  0.04507553,
          -0.0425503 , -0.03478021],
         ...,
         [ 0.04479579, -0.0380079 , -0.0014773 , ...,  0.01868752,
           0.05769926, -0.00094549],
         [-0.01639587, -0.00323624, -0.02058808, ...,  0.03145025,
           0.03818634, -0.03960627],
         [ 0.02349539,  0.06364504, -0.00889523, ..., -0.05598643,
           0.01661538,  0.01228662]]],


       [[[ 0.01068561,  0.05194796, -0.02178267, ...,  0.0578224 ,
          -0.02767438, -0.03638164],
         [ 0.03260955,  0.04201025, -0.02168554, ..., -0.00738851,
           0.04981044, -0.07830361],
         [-0.03843275,  0.04699084, -0.06139692, ...,  0.0405448 ,
           0.03039797, -0.04086862],
         ...,
         [ 0.06280899,  0.04990889,  0.02607316, ..., -0.06360812,
           0.07516078, -0.02804391],
         [-0.01260885, -0.04139749, -0.04559671, ...,  0.07511674,
          -0.016697  , -0.04736171],
         [ 0.01908968,  0.04566715,  0.02549507, ...,  0.04721119,
          -0.03933832, -0.03979019]],

        [[ 0.00501826, -0.02261663, -0.00952127, ...,  0.06713331,
           0.00341407,  0.03054764],
         [ 0.02115376, -0.04344072, -0.02299659, ..., -0.0227616 ,
           0.00136522,  0.02819551],
         [ 0.04327212, -0.02506413,  0.03342043, ..., -0.00805342,
          -0.03013022, -0.04560591],
         ...,
         [ 0.03803362,  0.05072358, -0.04146674, ..., -0.02218191,
           0.00280718,  0.02743961],
         [ 0.02976928,  0.07156712,  0.03073343, ..., -0.01368442,
           0.05930062, -0.03457824],
         [-0.00530881, -0.04373293,  0.03864986, ..., -0.05987791,
           0.04563067, -0.04184739]],

        [[-0.04371291,  0.0086881 , -0.01106149, ..., -0.04025014,
          -0.05504646,  0.02226315],
         [-0.00616754, -0.03510188,  0.00319079, ..., -0.06035907,
           0.01844395,  0.01933367],
         [ 0.04018357,  0.02709751,  0.0508442 , ...,  0.04812078,
          -0.01169256, -0.0201553 ],
         ...,
         [-0.00233911,  0.04832716, -0.04516945, ..., -0.0535378 ,
           0.01279867,  0.03824054],
         [-0.01084688,  0.02434646, -0.03069369, ..., -0.00970737,
           0.04938183, -0.05426631],
         [-0.00942226,  0.00028819,  0.00150998, ...,  0.02716126,
          -0.05136415,  0.06340423]]]], dtype=float32), array([ 0.02327016,  0.00106779,  0.00477299, -0.01455496,  0.01265169,
       -0.01330131, -0.0119441 , -0.01372493, -0.01304917,  0.02213102,
        0.00168471, -0.00275332, -0.00424139, -0.00785542, -0.00410217,
       -0.01826711, -0.01918958, -0.01569192,  0.00568281,  0.01959914,
        0.0031966 ,  0.01354972, -0.02539795, -0.00068014, -0.00974265,
       -0.00941087,  0.01187235, -0.00262184,  0.00443864,  0.01167439,
        0.0175337 , -0.01663817,  0.00102282,  0.01373519, -0.00863344,
       -0.00687034,  0.00616827, -0.01526707,  0.01287308, -0.01708789,
        0.01316724, -0.00216361,  0.00167288,  0.0050805 , -0.01127985,
       -0.00079543, -0.0121278 ,  0.02201018], dtype=float32), array([-0.00710903, -0.01414737, -0.68619955,  0.54659164, -0.5749124 ,
        1.4273384 ,  0.74446046, -0.77206457,  0.1261303 , -0.17624623,
       -0.9831663 , -0.5655522 ,  0.3053058 ,  1.2801557 ,  0.18938468,
        0.19567749,  0.39053923, -0.52806103, -1.0187292 , -0.6305515 ,
        0.24909203, -0.27740052, -0.9853814 , -0.03646205, -1.131045  ,
        0.9398975 ,  0.12838383,  0.6575864 ,  0.7389868 ,  0.8786336 ,
       -0.06352576,  0.32598585, -0.57410616, -0.22118725,  0.32604358,
       -0.44610623, -0.30185857, -0.26768342, -0.40891284,  0.5420028 ,
       -0.05078534,  1.4455043 ,  0.5879654 , -0.39180768,  0.7726375 ,
        1.5104704 , -0.16771545,  0.22311883], dtype=float32), array([1.4981369 , 0.7402698 , 1.3977952 , 1.2110083 , 0.90996176,
       1.4976445 , 0.4506882 , 1.5568699 , 2.8590472 , 1.3935403 ,
       2.0081553 , 1.6426221 , 0.9986498 , 1.2885273 , 1.2237432 ,
       0.78691274, 1.1066649 , 0.8143046 , 1.1666651 , 1.2019812 ,
       0.8540654 , 1.3179231 , 0.7426297 , 1.2356724 , 1.6020664 ,
       1.1141021 , 0.97511816, 1.591081  , 2.1292067 , 1.3440856 ,
       0.85482347, 0.72787726, 1.2128806 , 0.937665  , 1.6493163 ,
       1.3345605 , 0.85017985, 1.2900532 , 0.63539785, 0.86776936,
       0.89335746, 1.5593488 , 2.5298574 , 0.9120734 , 1.8471016 ,
       1.4203904 , 0.7412362 , 2.9609675 ], dtype=float32), array([-0.00299604, -0.00894827, -0.01423976, -0.00248717,  0.00629878,
        0.01108306, -0.00293747,  0.01595952, -0.00624394, -0.00779178,
        0.00120762,  0.00125522, -0.01934774, -0.00325216, -0.01821321,
       -0.01296069,  0.00236154,  0.00916089,  0.00744449,  0.00928492,
        0.00547075,  0.00838395, -0.01307934,  0.01865281, -0.01473262,
        0.0105143 , -0.00063928, -0.00697588, -0.00123657,  0.01063906,
        0.00464969,  0.00159907, -0.00108598, -0.01035666, -0.00614987,
       -0.00224114, -0.01962688,  0.01662128,  0.00235284, -0.00706952,
        0.01804758, -0.00303342, -0.01590586,  0.01643525,  0.00123069,
       -0.00327134, -0.0035202 ,  0.01424996,  0.00065104,  0.00773929,
        0.01549538,  0.01610321, -0.01180954,  0.01603807, -0.01428567,
        0.00326618, -0.0236201 , -0.00396272,  0.00206304, -0.00255786,
        0.00197004, -0.00627977, -0.0047197 ,  0.00744194,  0.00864058,
        0.01088321,  0.00953526,  0.01722319, -0.00583205,  0.00136356,
       -0.0148748 , -0.01108224,  0.00165604, -0.00653425,  0.01314541,
        0.00126131, -0.00998063,  0.00708719,  0.01213577, -0.00371595,
       -0.00694822, -0.01735762,  0.00431687,  0.00342046, -0.01045119,
        0.00097155, -0.00726656,  0.01169472,  0.00469396, -0.00590324,
       -0.01792057,  0.00918309,  0.01654255, -0.01163935, -0.00816383,
        0.00185162], dtype=float32), array([ 0.44816568,  0.90614265,  0.32066435,  0.20150739,  0.43471268,
        0.171418  ,  0.30965966,  0.3559864 , -0.32349098, -1.0514606 ,
       -0.09268896,  0.26214993, -0.01873854, -0.10846569, -0.5079538 ,
        0.7455141 ,  0.7089196 , -0.6263356 ,  0.47681242,  0.6390549 ,
       -0.11062757, -0.29573968, -0.55856025,  0.2913758 ,  0.17245209,
       -0.12085241,  0.40633404,  0.95284575, -0.0410277 , -0.6274401 ,
       -0.9183586 , -0.1493142 , -0.01710363, -0.31717235, -0.6027529 ,
       -0.3028688 ,  0.8342624 , -0.74235266, -0.17325437, -0.35112125,
        0.08984098, -0.4971605 ,  0.5107497 ,  0.556516  ,  0.36974326,
        0.16972554,  1.1076841 ,  0.6499734 , -0.24497166,  0.33041033,
        0.57092893,  0.02967553, -0.9858656 ,  0.24797669,  0.40040886,
       -0.02532657,  0.31278625, -0.5451217 ,  0.6771036 ,  0.42209753,
        0.21196838, -0.68480176, -0.10369661, -0.30140436,  0.25853705,
       -0.58881277,  0.5543737 ,  0.0186239 ,  0.05786315, -0.04249879,
        0.14503883,  0.4569842 ,  0.16297443,  0.39156395,  0.8702262 ,
        0.5277964 , -0.31974754,  0.30295274, -1.6341968 , -0.11699333,
       -0.78928936,  0.17363673, -0.8371394 ,  0.14334185,  0.20046094,
        0.6974041 , -0.308724  , -0.01034344,  0.21048264,  0.17231645,
       -0.4211122 ,  0.26950124, -0.5581238 ,  0.40100843,  0.54237497,
       -0.34791866], dtype=float32), array([0.9350095 , 1.4791954 , 0.7759427 , 0.7802584 , 0.94489574,
       0.93882644, 0.6497915 , 1.1211655 , 0.8623233 , 1.216315  ,
       1.0961084 , 0.9790078 , 0.47775668, 0.57348484, 0.89392096,
       2.2737074 , 1.4623017 , 1.0956029 , 0.67948717, 3.2156265 ,
       0.89026296, 2.443752  , 1.2341661 , 1.1539257 , 1.2062222 ,
       1.5733938 , 0.8256904 , 1.5419964 , 0.8570684 , 1.358281  ,
       0.8502533 , 0.7365021 , 0.8220714 , 0.86697465, 0.7896865 ,
       0.6871627 , 0.7079534 , 0.8058314 , 1.1569835 , 0.46643308,
       0.85708606, 1.4191053 , 1.1436452 , 0.92722636, 1.4197873 ,
       1.0091767 , 1.1569793 , 1.8404201 , 2.6035538 , 1.860234  ,
       1.0545846 , 1.1657488 , 1.0018855 , 1.8397824 , 1.3793176 ,
       1.4365902 , 0.659604  , 0.92905754, 0.99516064, 1.3612772 ,
       1.1435384 , 0.8741642 , 0.70632815, 0.7720804 , 1.594885  ,
       0.9243983 , 1.2704896 , 1.5229548 , 0.65754455, 0.9250141 ,
       0.71636283, 0.7681394 , 1.8995346 , 0.46849787, 1.0844193 ,
       1.291489  , 1.0582277 , 1.089536  , 2.412196  , 0.54405534,
       1.3102432 , 0.8749895 , 1.6935232 , 0.8953404 , 1.3613654 ,
       1.0046177 , 1.1843411 , 0.7647007 , 1.036977  , 1.5453972 ,
       1.2459859 , 0.90605587, 1.2944098 , 2.5676658 , 0.7918164 ,
       1.2221481 ], dtype=float32), array([[[[-0.12795042, -0.13194144, -0.1405378 , ...,  0.09071478,
           0.07234432, -0.06740692],
         [ 0.12611903,  0.09175652,  0.08766027, ...,  0.02417092,
          -0.02410546,  0.00878333],
         [ 0.12052455,  0.00803861, -0.02868477, ...,  0.04329333,
          -0.03215345, -0.05614483],
         ...,
         [-0.0892183 ,  0.00672544, -0.09695727, ..., -0.09392905,
          -0.11155165,  0.02414759],
         [-0.01830737,  0.14730489, -0.05573134, ...,  0.09743317,
          -0.04998834,  0.12160982],
         [-0.13543607,  0.00430483,  0.09906893, ..., -0.1461514 ,
          -0.04648994, -0.0854889 ]]]], dtype=float32), array([[[[-1.38266431e-03, -4.59528565e-02, -4.58024852e-02, ...,
           1.36199426e-02, -1.37348929e-02,  2.28035673e-02],
         [ 1.87294930e-02, -1.89563148e-02,  1.59048866e-02, ...,
           2.41132174e-02, -6.25106832e-03,  3.20612006e-02],
         [ 4.32355478e-02, -2.77424362e-02,  5.10217957e-02, ...,
           1.20662693e-02,  5.99185238e-03, -7.35599268e-03],
         ...,
         [-5.32334968e-02,  4.47714813e-02, -6.97841728e-03, ...,
          -2.66664717e-02,  6.47272076e-03,  2.21634260e-03],
         [ 3.44830938e-02,  5.80015220e-03, -6.17282558e-03, ...,
          -3.00138518e-02, -3.16482075e-02,  3.03469412e-02],
         [-4.08616997e-02, -3.04246992e-02, -2.30170619e-02, ...,
          -4.10354212e-02,  2.96609700e-02,  3.37221250e-02]],

        [[-4.63750511e-02, -7.72020640e-03, -1.68639030e-02, ...,
           1.39178103e-02,  4.33431007e-02,  5.52080423e-02],
         [-3.35050486e-02,  3.20385359e-02,  2.00503338e-02, ...,
           5.90072421e-04, -8.32944456e-03,  4.05901372e-02],
         [ 3.65970954e-02, -7.83390552e-03,  1.71035584e-02, ...,
          -2.10565003e-03, -7.79043697e-03,  4.54973653e-02],
         ...,
         [-3.74644548e-02,  2.79574636e-02, -3.38908397e-02, ...,
           3.24692652e-02, -2.54554134e-02, -2.33509969e-02],
         [-2.17131749e-02, -1.44037725e-02,  1.29033364e-02, ...,
           3.61826085e-02, -4.45969310e-03, -4.17264923e-02],
         [-3.17025296e-02,  4.19902690e-02, -6.54599816e-02, ...,
          -4.94310632e-02,  1.18275136e-02, -3.51524204e-02]],

        [[ 1.43682547e-02,  3.18210199e-02,  1.95831880e-02, ...,
           3.13004479e-02,  5.15221506e-02,  2.23122966e-02],
         [ 2.44141407e-02,  1.42023051e-02, -6.48988818e-04, ...,
          -4.68998291e-02,  1.83382016e-02,  2.58667301e-02],
         [ 4.46068496e-02, -6.79022772e-03,  1.04820058e-02, ...,
           5.63701056e-02,  4.05232236e-03, -1.74935348e-02],
         ...,
         [ 1.61296949e-02,  4.36526127e-02,  2.47397758e-02, ...,
           1.04026413e-02,  2.48817950e-02, -4.27917168e-02],
         [-1.79714721e-03, -3.51838730e-02, -3.22507210e-02, ...,
          -5.84505871e-03,  1.22234402e-02,  3.91070824e-03],
         [ 3.87518667e-02, -2.14844812e-02, -4.41127364e-03, ...,
           2.10942943e-02,  5.90267256e-02, -1.47750704e-02]],

        [[-2.59917863e-02,  6.24319911e-03,  6.31961413e-03, ...,
           4.30996530e-02, -2.98279319e-02,  1.95225906e-02],
         [ 2.28936803e-02, -2.32934840e-02,  1.68320853e-02, ...,
          -2.90400051e-02, -2.28103679e-02,  4.00070287e-02],
         [-3.93229350e-02, -4.71504293e-02,  3.52163613e-02, ...,
           3.79620353e-03, -3.50990035e-02,  1.21132433e-02],
         ...,
         [-2.13761330e-02,  5.72045008e-03, -4.58576232e-02, ...,
          -2.99951136e-02, -3.11649162e-02, -8.04075692e-03],
         [-2.23231893e-02, -2.57003400e-02, -4.50313799e-02, ...,
          -2.61210985e-02,  2.43848208e-02, -1.65017974e-02],
         [ 1.03733118e-03,  1.58287287e-02, -2.39665117e-02, ...,
           2.82705780e-02,  7.30942339e-02, -2.29777545e-02]],

        [[ 2.24290602e-02,  3.16233598e-02, -4.39829826e-02, ...,
          -4.28321213e-02, -3.39015648e-02,  3.44706140e-02],
         [ 3.51017267e-02,  3.77072133e-02,  6.44594850e-03, ...,
           4.36589308e-02,  3.16014625e-02,  1.35167281e-03],
         [-2.69782245e-02, -2.33958066e-02,  5.81218340e-02, ...,
          -3.16381734e-03,  2.96939183e-02,  1.83266494e-02],
         ...,
         [ 1.34820109e-02,  5.65508939e-02, -1.58204585e-02, ...,
          -2.52403263e-02, -1.09752575e-02, -3.90934478e-03],
         [-1.60084609e-02, -4.50993516e-02, -3.28332819e-02, ...,
           3.83309200e-02, -2.82854345e-02,  2.44062021e-02],
         [-5.42186238e-02,  4.01228681e-05,  3.30873020e-02, ...,
          -5.66018187e-03,  5.16250320e-02,  2.82569462e-03]]],


       [[[ 8.90973210e-03, -4.17695977e-02, -2.79160161e-02, ...,
           3.30036730e-02, -3.80443186e-02, -2.59605492e-03],
         [ 3.37321497e-02,  3.76336388e-02, -1.91156808e-02, ...,
          -2.83556040e-02,  1.16218971e-02, -2.09527574e-02],
         [-2.85708588e-02,  3.96783650e-02,  3.07012927e-02, ...,
          -2.20899303e-02, -2.85189617e-02,  4.88177873e-02],
         ...,
         [-3.65528986e-02, -2.66040824e-02,  2.29346231e-02, ...,
           2.47204956e-02,  1.61489919e-02,  3.80737968e-02],
         [ 2.12974586e-02, -4.26460095e-02, -4.21811678e-02, ...,
           3.45419310e-02, -1.52427908e-02,  2.57596490e-03],
         [-2.83061992e-02, -2.79203895e-02, -2.79824790e-02, ...,
           1.10349655e-02, -1.04313614e-02, -2.71272771e-02]],

        [[-4.22355011e-02, -1.90468486e-02, -6.15905263e-02, ...,
          -1.43695232e-02, -1.72954460e-03,  5.47245927e-02],
         [-1.92762334e-02,  1.41690308e-02, -5.09135388e-02, ...,
           9.12108459e-04,  2.01388784e-02,  3.55729200e-02],
         [-7.41671212e-03,  2.21353341e-02, -3.65237035e-02, ...,
           3.40270028e-02,  1.33686548e-03,  3.26625966e-02],
         ...,
         [-8.94791633e-03,  4.46913280e-02,  2.21765935e-02, ...,
           2.75415964e-02,  4.87331524e-02,  2.46505644e-02],
         [ 1.72000006e-02,  3.65430862e-02,  7.96443503e-03, ...,
           5.03734052e-02,  3.67473364e-02,  3.56532284e-03],
         [ 2.01464910e-02,  1.26451040e-02, -1.48901285e-03, ...,
           3.66117078e-04,  5.04819974e-02,  2.68455241e-02]],

        [[ 2.43132561e-02,  1.26359398e-02, -1.95112489e-02, ...,
          -5.15926396e-03, -3.28196166e-03,  4.51977029e-02],
         [-1.54364817e-02,  5.41476756e-02, -2.47165989e-02, ...,
          -7.48573337e-03,  3.34991179e-02,  3.82715501e-02],
         [-3.42027023e-02,  3.30473669e-02, -2.58891061e-02, ...,
           2.58005541e-02, -3.40983123e-02,  2.57543661e-02],
         ...,
         [-2.82692928e-02,  3.44263464e-02,  3.29966508e-02, ...,
          -3.92334089e-02,  5.18134311e-02, -8.49638507e-03],
         [ 3.22538503e-02, -5.43079246e-03, -5.35030402e-02, ...,
           3.69097255e-02, -5.10071106e-02,  2.08656006e-02],
         [-9.63113084e-03,  1.29238274e-02, -5.22659998e-03, ...,
          -7.64214061e-03,  2.30687466e-02,  3.28226388e-02]],

        [[-1.91690382e-02,  2.80876234e-02,  1.54768405e-02, ...,
           3.09268720e-02,  4.84343991e-02,  4.47132997e-02],
         [ 5.05032949e-02, -2.04708055e-03,  2.15886869e-02, ...,
           1.95062440e-02, -9.93986707e-03,  3.02969459e-02],
         [-2.39026491e-02, -3.24588642e-02, -1.08420802e-02, ...,
          -8.90943781e-03,  2.32488359e-03,  3.84698026e-02],
         ...,
         [-2.86247414e-02,  1.22156367e-02, -7.69726979e-03, ...,
          -9.42949031e-04,  5.17665669e-02, -1.48487091e-02],
         [ 2.39938144e-02, -4.70744893e-02,  1.34074427e-02, ...,
           1.70769263e-02,  1.99835710e-02,  4.90993820e-03],
         [ 3.20344493e-02, -3.25065968e-03, -6.72061171e-04, ...,
          -3.84615362e-02,  1.19646573e-02,  2.60274410e-02]],

        [[-5.28521985e-02,  6.96639298e-03,  2.27640159e-02, ...,
          -4.54722345e-03,  3.39436233e-02,  2.62682997e-02],
         [-3.39609338e-03,  4.70385607e-03, -4.33540978e-02, ...,
          -2.84412578e-02, -2.32951697e-02,  4.13097702e-02],
         [-3.23388539e-02,  1.85528852e-03,  6.93250401e-03, ...,
           1.96947940e-02,  3.72258313e-02,  2.14936081e-02],
         ...,
         [ 3.70013379e-02, -2.82747708e-02, -4.35929606e-03, ...,
           7.95051176e-03,  4.47512157e-02, -5.98717295e-03],
         [-4.50825579e-02,  1.79018918e-03,  1.90526973e-02, ...,
           4.41726334e-02, -4.83048521e-02,  2.82986630e-02],
         [-2.85064075e-02,  1.66446511e-02,  1.69950221e-02, ...,
           1.16789890e-02,  4.89810407e-02,  1.00302035e-02]]],


       [[[-2.41091028e-02, -4.27230224e-02, -4.94996645e-02, ...,
           2.00684164e-02, -1.87834376e-03,  7.29376334e-05],
         [-2.70905029e-02, -1.80434249e-02,  8.74568429e-03, ...,
          -3.15285288e-02,  3.97131853e-02,  1.88049451e-02],
         [-3.46778594e-02,  3.68833058e-02,  3.56427096e-02, ...,
           2.22925283e-02,  1.54283512e-02, -2.85742898e-02],
         ...,
         [ 1.88216695e-03,  5.57101518e-02, -2.41710013e-03, ...,
          -4.19268236e-02, -3.35056223e-02, -9.72692110e-03],
         [ 5.84817827e-02,  1.29078506e-02,  1.77684594e-02, ...,
          -1.36979017e-02, -2.19993759e-02,  2.05668677e-02],
         [-5.15725687e-02, -1.07253920e-02, -4.74896207e-02, ...,
          -2.66500805e-02,  3.02993376e-02,  3.46421786e-02]],

        [[ 2.35172417e-02, -2.17042919e-02,  9.91461985e-03, ...,
           4.87101562e-02,  2.14097835e-02, -2.44943444e-02],
         [ 2.17370298e-02, -1.97417662e-03,  5.07930946e-03, ...,
           2.57412847e-02,  1.36223398e-02,  4.73931851e-03],
         [ 3.03769466e-02,  3.99896577e-02, -3.17287743e-02, ...,
           5.10581210e-02,  2.14534383e-02,  1.85183212e-02],
         ...,
         [ 2.46809218e-02,  1.64191667e-02, -3.22743021e-02, ...,
          -5.35512827e-02, -1.01871723e-02, -3.00112255e-02],
         [-2.52034348e-02,  2.82301456e-02,  3.27148885e-02, ...,
           2.41259299e-02,  1.49533963e-02,  2.15915758e-02],
         [-1.82850438e-03, -2.65954640e-02, -1.67404935e-02, ...,
          -8.23980104e-03,  7.08804876e-02,  1.21587552e-02]],

        [[-2.63827089e-02,  1.24252355e-02, -5.96540086e-02, ...,
          -1.79002229e-02,  5.31691574e-02, -2.31994297e-02],
         [-3.37147042e-02,  2.24597119e-02,  2.94953659e-02, ...,
           1.94397084e-02,  2.21643783e-02, -1.30236680e-02],
         [-3.54927890e-02,  3.90748158e-02, -6.55455515e-05, ...,
          -1.69728640e-02, -2.31291633e-02, -2.72844061e-02],
         ...,
         [-2.98358995e-04,  3.45493816e-02, -4.33273241e-03, ...,
           2.53860876e-02,  4.04293276e-02,  3.75797302e-02],
         [-1.53346164e-02, -2.46325359e-02, -5.32305576e-02, ...,
          -2.51709670e-02, -2.64138300e-02,  3.76363881e-02],
         [-3.01565155e-02,  2.65852418e-02,  1.93667319e-02, ...,
          -2.74543022e-03,  3.20225023e-02, -7.94895552e-03]],

        [[-1.26132853e-02,  3.67147732e-03, -6.20091967e-02, ...,
          -2.46553402e-02,  2.72378996e-02,  7.68312020e-03],
         [-4.76761349e-03,  7.81580620e-03,  3.28698684e-03, ...,
          -2.50636432e-02,  2.18232628e-02,  2.28512622e-02],
         [-5.53319650e-03, -1.62945818e-02,  1.43465837e-02, ...,
           1.55867906e-02, -3.50260139e-02,  2.63079405e-02],
         ...,
         [ 1.84568036e-02,  4.59048524e-02,  5.74626308e-03, ...,
          -5.36717623e-02,  1.21156136e-02, -4.38740775e-02],
         [-3.64551693e-02, -2.34034061e-02,  3.10019962e-03, ...,
           5.63160293e-02, -4.61451411e-02, -2.55579576e-02],
         [-7.29310839e-03, -3.68398651e-02, -2.69432627e-02, ...,
          -4.40733470e-02,  2.64031906e-02,  2.82713883e-02]],

        [[ 2.36297818e-03,  3.78526933e-02,  5.97156817e-03, ...,
          -2.73254234e-02,  4.87474352e-02,  2.51895539e-03],
         [ 6.85093412e-03, -2.17819046e-02, -4.08292413e-02, ...,
          -4.50691320e-02, -2.78366785e-02,  9.62808356e-03],
         [ 4.71900625e-04,  5.62427118e-02,  5.61489258e-03, ...,
          -2.98547912e-02, -4.41355035e-02,  3.60110477e-02],
         ...,
         [ 3.24289761e-02, -3.86412465e-03, -1.60069987e-02, ...,
           2.84791756e-02,  3.57683152e-02, -1.29084345e-02],
         [ 2.98195295e-02,  1.78098306e-02, -1.78892016e-02, ...,
           5.60911447e-02, -1.82253625e-02, -2.02948432e-02],
         [ 2.23846715e-02, -3.94554138e-02, -4.11713161e-02, ...,
          -3.15935351e-02,  6.60145190e-03,  2.55721863e-02]]],


       [[[ 6.32716529e-03, -3.37811336e-02, -5.59954233e-02, ...,
          -3.01229469e-02,  4.18040417e-02,  7.96334993e-04],
         [-2.68464945e-02,  3.39755730e-04, -2.57393755e-02, ...,
          -2.32946407e-02, -1.93833504e-02,  4.80246934e-04],
         [-3.42180245e-02, -1.49939526e-02,  8.55787541e-04, ...,
           1.26363076e-02,  1.04789957e-02, -3.27991806e-02],
         ...,
         [ 3.78333926e-02, -5.31947287e-03, -4.13114615e-02, ...,
           3.59444022e-02,  2.80226860e-02, -5.33352513e-03],
         [-1.31992232e-02, -3.70135121e-02,  2.66980845e-02, ...,
           2.82547846e-02, -5.22568226e-02,  3.70206311e-02],
         [-4.54533584e-02,  4.94553484e-02, -3.45097184e-02, ...,
           1.25820003e-02, -1.32546332e-02, -2.93599237e-02]],

        [[ 2.20926050e-02,  4.53540049e-02,  1.79250743e-02, ...,
           2.31732801e-02, -3.04802861e-02, -1.99529584e-02],
         [-6.63257483e-03,  4.73086424e-02,  8.34054686e-03, ...,
           1.37454309e-02,  2.15244088e-02,  3.85867096e-02],
         [ 7.25151738e-03,  9.27007850e-03,  2.58944184e-02, ...,
          -2.05120649e-02, -3.88201438e-02,  5.10463342e-02],
         ...,
         [-3.30983400e-02,  2.90582608e-02, -4.07124981e-02, ...,
           5.10908710e-03,  3.85308042e-02, -2.42849775e-02],
         [-9.51773021e-03, -1.81155782e-02,  2.40285769e-02, ...,
           4.93663289e-02, -1.61240827e-02,  1.60760004e-02],
         [ 2.75835879e-02,  3.41640189e-02,  1.14639960e-02, ...,
          -9.40728746e-03,  6.18007481e-02,  1.76876318e-03]],

        [[ 3.17846574e-02, -3.03540137e-02, -1.75153371e-03, ...,
          -3.93297896e-02,  4.32162546e-02, -2.20799129e-02],
         [ 4.42683734e-02,  8.48371722e-03, -3.50787789e-02, ...,
          -2.13408675e-02, -3.42601277e-02,  1.43403150e-02],
         [-3.16765383e-02, -8.39699246e-03,  3.14762779e-02, ...,
           2.13257428e-02, -5.14987037e-02,  2.62332894e-02],
         ...,
         [ 3.43092047e-02, -2.69628987e-02, -2.09671203e-02, ...,
          -1.35783684e-02,  3.17919068e-02,  3.55757563e-03],
         [ 4.18200885e-04,  4.62372508e-03,  5.31273708e-03, ...,
           1.03873899e-02, -3.37573253e-02, -3.26497592e-02],
         [ 2.61237919e-02,  2.62445770e-03,  2.42138263e-02, ...,
          -4.22858186e-02, -1.65397562e-02,  2.29628314e-03]],

        [[-1.37767871e-03,  1.17339762e-02,  1.23532992e-02, ...,
          -1.40498225e-02, -2.46766284e-02, -3.81547734e-02],
         [-1.00028394e-02, -1.68782603e-02,  1.25414843e-03, ...,
           4.53803781e-03,  1.37491217e-02,  2.82467976e-02],
         [ 6.59249630e-03, -4.08641947e-03,  1.71468891e-02, ...,
          -9.87252407e-03,  3.60677093e-02,  5.30919880e-02],
         ...,
         [-4.29806300e-02,  1.63661502e-02, -2.12321468e-02, ...,
           1.80934258e-02, -1.88180450e-02,  1.85591560e-02],
         [ 2.74939090e-02, -4.02964791e-03,  1.30388862e-03, ...,
          -1.77378077e-02,  9.04264953e-03,  3.37336585e-02],
         [ 1.70412008e-02, -6.54573599e-03,  2.72149518e-02, ...,
           3.48582342e-02,  4.84327525e-02,  2.48532426e-02]],

        [[-4.36021201e-02,  3.59861962e-02,  1.12617109e-02, ...,
          -3.69179919e-02,  1.61555167e-02,  4.32853907e-04],
         [ 3.36171687e-02,  1.41215837e-02, -5.87745495e-02, ...,
          -6.21374696e-03,  1.20189805e-02,  1.51418485e-02],
         [-2.99004689e-02,  2.91638225e-02, -1.79939736e-02, ...,
          -1.90811288e-02, -3.40484492e-02,  7.16973515e-03],
         ...,
         [-1.51385963e-02,  5.10917418e-03,  3.62064131e-02, ...,
           3.71442479e-03,  2.29028445e-02,  2.56279614e-02],
         [ 3.71807665e-02, -1.43403895e-02, -1.42772822e-02, ...,
          -2.69833729e-02, -4.63527031e-02, -3.71992961e-02],
         [ 2.93505173e-02,  1.08035794e-02, -4.60676700e-02, ...,
           4.32907138e-03,  2.36323127e-03, -2.80303950e-03]]],


       [[[ 1.03160292e-02,  4.08928730e-02, -4.23249155e-02, ...,
          -1.17498273e-02,  2.75432449e-02,  3.34227196e-04],
         [ 9.18590836e-03,  2.30779964e-02, -4.88369465e-02, ...,
           1.79232918e-02,  1.61827374e-02, -2.88202371e-02],
         [ 4.20059711e-02, -4.60770121e-03, -3.77558954e-02, ...,
           2.11578514e-02, -2.66409107e-02,  1.55134508e-02],
         ...,
         [ 9.19865072e-03, -4.27510031e-02, -3.12339496e-02, ...,
          -2.26053242e-02,  5.49976598e-04,  3.96152176e-02],
         [ 5.59632368e-02, -2.72199567e-02, -2.01156419e-02, ...,
           2.23351531e-02,  1.37829017e-02,  2.78591830e-02],
         [-2.96444800e-02, -1.31602176e-02, -4.59527150e-02, ...,
          -4.96286899e-02,  2.26412136e-02,  1.10731153e-02]],

        [[-7.47295329e-04, -3.66482101e-02, -6.14544861e-02, ...,
           1.59461256e-02, -2.90488768e-02,  2.66606081e-02],
         [ 4.89417091e-03,  1.35365110e-02, -4.65929396e-02, ...,
           2.62017641e-02,  9.44965519e-03,  2.36272477e-02],
         [ 3.15390378e-02, -1.37459869e-02, -2.54077429e-04, ...,
          -7.39065558e-03, -5.25180064e-03, -2.92580277e-02],
         ...,
         [-7.96290208e-03,  3.95779721e-02, -3.41178812e-02, ...,
          -3.27580087e-02,  3.88955101e-02, -2.42645144e-02],
         [-2.36635897e-02,  1.77996606e-02, -3.19552794e-02, ...,
          -1.70497391e-02,  1.40238265e-02,  1.72679573e-02],
         [ 5.41320024e-03, -1.15732420e-02,  1.31556578e-02, ...,
           2.06811093e-02,  6.91815615e-02, -3.67210172e-02]],

        [[-3.74294706e-02,  8.14184826e-03,  9.62343905e-03, ...,
           4.02408913e-02,  4.25766921e-03, -3.16334330e-02],
         [ 1.76131539e-02,  4.08322066e-02,  1.47583932e-02, ...,
          -2.64803530e-03, -8.81962664e-03, -2.92400438e-02],
         [ 1.79051813e-02,  2.76566707e-02,  3.86326723e-02, ...,
           2.72765383e-02, -3.15827839e-02,  4.48769927e-02],
         ...,
         [-1.60653691e-03,  9.58381128e-03,  1.39614511e-02, ...,
          -4.91948193e-03, -4.54228651e-03,  1.93948336e-02],
         [ 2.88364813e-02,  4.24126089e-02, -2.11457489e-03, ...,
          -2.78157163e-02, -2.92233005e-02, -5.35374833e-03],
         [ 1.66025534e-02,  3.83773074e-02, -3.08928415e-02, ...,
           3.61317135e-02, -2.14292295e-03,  9.63366032e-03]],

        [[ 2.70050652e-02, -2.24720147e-02, -2.76192762e-02, ...,
           2.32835859e-02,  4.79219891e-02,  6.46018144e-03],
         [ 3.90003994e-03,  5.23535535e-02,  4.26730365e-02, ...,
          -1.06230164e-02, -1.19633321e-02,  1.16764056e-02],
         [ 3.61097716e-02,  3.74072529e-02,  3.17704901e-02, ...,
           4.91588935e-02,  1.49690546e-03,  3.08335107e-02],
         ...,
         [-2.20133308e-02,  2.31390428e-02, -3.17200348e-02, ...,
           1.05655361e-02,  2.64576301e-02, -2.10712906e-02],
         [ 3.64547335e-02, -2.87808664e-02, -2.17943564e-02, ...,
           7.59089319e-03,  1.95240024e-02,  3.56413424e-02],
         [ 3.72630497e-03, -2.64230426e-02,  1.60548519e-02, ...,
           2.56010983e-03, -1.44496886e-03, -5.95130399e-03]],

        [[-4.74138670e-02, -3.56496051e-02, -2.42292695e-02, ...,
           1.16393175e-02,  4.77449447e-02,  8.69384781e-03],
         [ 7.70734763e-03, -8.08607694e-03,  2.64599770e-02, ...,
          -1.71727818e-02,  2.17798515e-03,  6.80677220e-03],
         [ 4.00633411e-03, -3.62590216e-02,  3.14261913e-02, ...,
          -3.73142608e-03, -6.63208216e-03, -2.28377003e-02],
         ...,
         [ 1.25371935e-02,  1.07996387e-03,  1.61078759e-02, ...,
          -2.52831113e-02, -7.09195156e-03, -4.10946459e-02],
         [-9.47709940e-03, -5.17145842e-02, -2.08339132e-02, ...,
           3.56730260e-02,  1.84160061e-02,  9.16283857e-03],
         [ 1.48524605e-02, -3.44939576e-03,  6.46646600e-04, ...,
          -5.96936420e-03,  3.47136036e-02,  2.04637479e-02]]]],
      dtype=float32), array([[[[ 0.03569528,  0.00599798, -0.01208877, ..., -0.01052316,
           0.00625356, -0.05291702],
         [-0.05051337, -0.0031446 ,  0.03910901, ..., -0.00942992,
          -0.01268363, -0.00025128],
         [ 0.01654681,  0.05019411, -0.05194144, ...,  0.03294327,
           0.0470256 ,  0.02339077],
         ...,
         [ 0.01035054,  0.04443417,  0.02453854, ...,  0.0021675 ,
          -0.02601975, -0.02959121],
         [-0.04826697,  0.01302335, -0.03381507, ..., -0.05276414,
          -0.0369053 ,  0.06472806],
         [ 0.01288942, -0.03178577, -0.02515705, ..., -0.03792117,
           0.01042112,  0.02358293]],

        [[ 0.00656112,  0.04646203, -0.01035242, ...,  0.00263848,
          -0.04258174, -0.05656242],
         [-0.00196126, -0.02711066, -0.01370587, ...,  0.04500613,
           0.0315074 ,  0.03836603],
         [-0.04716164, -0.03826736,  0.02140307, ..., -0.00168641,
          -0.04211354,  0.01769735],
         ...,
         [ 0.02026028, -0.03549414,  0.0032314 , ...,  0.02722771,
          -0.01935783,  0.02945215],
         [ 0.02023894,  0.04931192, -0.042367  , ...,  0.00064744,
           0.06234338,  0.02132752],
         [-0.0050248 , -0.02410178, -0.02265207, ..., -0.05058782,
           0.00354983,  0.0081796 ]],

        [[-0.02911148, -0.03806764,  0.03369735, ..., -0.00096514,
           0.01708277, -0.03527286],
         [-0.02560194,  0.01036187, -0.00306503, ..., -0.04405127,
           0.04327932,  0.02356477],
         [-0.04751887, -0.05480273,  0.02221698, ..., -0.02879991,
          -0.00278001, -0.01532693],
         ...,
         [ 0.01133777,  0.01602861,  0.06667294, ..., -0.03496525,
          -0.04204306, -0.01283201],
         [-0.02723882, -0.04263787,  0.05365186, ...,  0.01687388,
           0.02338968, -0.0133163 ],
         [-0.01775494, -0.04330248, -0.00461674, ..., -0.04251019,
           0.02686266, -0.02850585]]],


       [[[-0.01367791, -0.04102659, -0.03076164, ..., -0.04262973,
          -0.01876509,  0.00216089],
         [ 0.01328183, -0.04633389,  0.04142953, ..., -0.04965787,
           0.00134507,  0.05287326],
         [-0.00076002,  0.03340055, -0.04539203, ...,  0.06329235,
          -0.03418715,  0.00519068],
         ...,
         [-0.00636855, -0.0298739 ,  0.01686325, ...,  0.04018028,
           0.05617147, -0.03791073],
         [ 0.01416348,  0.04396275,  0.01227813, ..., -0.06707998,
           0.03456113, -0.01950287],
         [ 0.02319758,  0.03903003,  0.03912112, ..., -0.01367308,
          -0.03159554, -0.01293018]],

        [[ 0.02546258, -0.01791082,  0.04016642, ..., -0.02057089,
           0.01098815,  0.05773333],
         [-0.05549055,  0.01704582, -0.04065316, ..., -0.03377946,
          -0.05157889, -0.04322371],
         [-0.0286621 ,  0.04929821,  0.04305716, ..., -0.02378587,
           0.03102859,  0.02698371],
         ...,
         [ 0.00638784,  0.03003334,  0.0290729 , ...,  0.03684635,
           0.04502111,  0.04057172],
         [-0.04719729, -0.01272553, -0.05108965, ..., -0.00999121,
           0.02567012,  0.01378828],
         [-0.04967823, -0.01142253, -0.02687829, ..., -0.03009933,
           0.05019362, -0.05081313]],

        [[-0.03475704,  0.0583602 ,  0.01422191, ...,  0.02684134,
          -0.01988861,  0.01592269],
         [ 0.04810799, -0.01560856, -0.00504338, ...,  0.02810745,
           0.03186904,  0.02185631],
         [ 0.01014714, -0.0066585 , -0.02040484, ...,  0.01781263,
          -0.01405611,  0.00212662],
         ...,
         [ 0.0422448 ,  0.04771367,  0.00677522, ..., -0.00049419,
           0.01066366,  0.04409418],
         [ 0.05607716, -0.02520824,  0.03570402, ...,  0.05364089,
           0.01802463,  0.03754137],
         [-0.03664602,  0.04942584, -0.03649025, ...,  0.05096291,
           0.02799478,  0.00016029]]],


       [[[ 0.01681555,  0.02949996,  0.04822898, ...,  0.03549778,
          -0.00619368, -0.02549451],
         [-0.03299786,  0.03474787,  0.05633092, ..., -0.00385733,
           0.00744313, -0.02521098],
         [ 0.04559501,  0.01377276, -0.03559854, ...,  0.00126307,
           0.02392196, -0.02249835],
         ...,
         [-0.06618809,  0.04302332,  0.00030228, ...,  0.01592774,
           0.04517945,  0.0665526 ],
         [-0.03648275, -0.0146176 ,  0.04974697, ...,  0.02973073,
          -0.02414483, -0.03844959],
         [-0.04839186, -0.05407049, -0.06124583, ...,  0.02864582,
           0.05843743, -0.02127546]],

        [[-0.03937468, -0.0024385 ,  0.06390733, ..., -0.04074541,
          -0.04125958,  0.02467998],
         [-0.03481168,  0.0381797 , -0.04419084, ..., -0.01582823,
          -0.05034019,  0.03111775],
         [ 0.02650201,  0.00673406,  0.03168148, ..., -0.0306402 ,
           0.03082523, -0.03249605],
         ...,
         [ 0.04570438, -0.01694177, -0.04205665, ...,  0.00505269,
          -0.00330201,  0.01249706],
         [ 0.01793852, -0.03552977,  0.05067837, ..., -0.03496446,
          -0.00553028,  0.03022115],
         [-0.04031032, -0.00347286, -0.03238755, ..., -0.01190431,
           0.04283943, -0.01862264]],

        [[-0.0102293 ,  0.00049509, -0.02441975, ..., -0.04240061,
          -0.02345212,  0.02602485],
         [ 0.04351303,  0.01445156, -0.04191443, ...,  0.00309163,
           0.04573708,  0.01849455],
         [-0.00064147,  0.01355215, -0.0303409 , ...,  0.0590044 ,
          -0.05428338, -0.01958408],
         ...,
         [-0.00848073, -0.01118291,  0.03363115, ..., -0.00257292,
           0.03773289, -0.0357537 ],
         [-0.05634446,  0.05027674,  0.05042326, ..., -0.01690795,
           0.02868121, -0.03609959],
         [-0.01870586, -0.03208849,  0.0039951 , ...,  0.04858397,
          -0.051169  ,  0.00304887]]]], dtype=float32), array([[[[ 0.08782357, -0.08282118, -0.12064643, ..., -0.02875743,
          -0.01128822,  0.02305628],
         [ 0.1638488 , -0.14442913, -0.11330618, ..., -0.15757786,
           0.14454204,  0.14648922],
         [-0.09584942,  0.01371382,  0.166186  , ..., -0.09638965,
           0.01050827, -0.13885121],
         ...,
         [ 0.08595299,  0.13656172,  0.1890997 , ..., -0.00952286,
          -0.14397717,  0.08912317],
         [-0.07908018,  0.02168793,  0.04156555, ..., -0.00270125,
          -0.05659181,  0.09574688],
         [-0.12580295, -0.16351554, -0.02559803, ...,  0.07220466,
           0.03396586,  0.05665755]]]], dtype=float32), array([ 0.01094159,  0.01290868,  0.0042733 ,  0.00318004, -0.02286652,
        0.00493824,  0.00408125, -0.00878839, -0.00633447,  0.00350686,
        0.01131516, -0.00934639, -0.00705651,  0.00223636, -0.00767137,
       -0.02846079,  0.00571984, -0.00445036,  0.00334999, -0.0077025 ,
       -0.00085156,  0.01728645,  0.01655452, -0.01634691,  0.01034738,
       -0.00095232,  0.00093137, -0.00704026, -0.01628157, -0.00344185,
        0.01174547, -0.01975971, -0.00083328,  0.00183671,  0.01212783,
       -0.00259015, -0.02241936,  0.0038827 , -0.00581082,  0.0129277 ,
       -0.00471162, -0.01061762,  0.02326518, -0.0049043 , -0.01414366,
       -0.02070558,  0.00706983,  0.00728325, -0.00091151, -0.00264756,
        0.00874383,  0.00922093,  0.01683396,  0.00016767,  0.01217845,
       -0.00599127,  0.00322153,  0.00672231, -0.01226931, -0.00940035,
        0.01155823,  0.00762865, -0.001609  ,  0.00610475], dtype=float32), array([-0.33872682, -0.21847571, -0.81987154, -0.84424615, -1.1620749 ,
        0.32668877, -0.24532211, -1.1029618 ,  0.35799855, -0.63998806,
       -1.1999367 ,  0.52832663, -0.06419829,  0.5392223 ,  0.26133227,
       -0.00963716,  0.2731329 , -1.1627831 ,  0.19960262, -0.30684915,
       -0.01903588,  0.5429761 , -1.1994294 ,  1.0615597 , -0.7941162 ,
       -0.1320338 , -0.34405622,  0.23041907,  0.18115275, -0.2892765 ,
        0.21694598,  0.98966455,  0.8761992 ,  0.46622172,  0.24277712,
        0.8419192 ,  0.40537784,  0.5358472 , -0.63851446, -0.35710058,
       -0.76873404,  1.3931855 ,  0.08062592, -0.6683002 ,  0.7200634 ,
        0.21760394, -0.8082375 ,  1.0650935 ,  0.14924575, -1.1020619 ,
        0.60398936,  1.4401644 ,  0.07468671,  0.69761074,  0.77508307,
        0.83449334,  0.21049806,  0.32735702,  1.158946  , -0.7132087 ,
        0.5239324 , -0.23385061, -0.18945466,  0.07285908], dtype=float32), array([0.962039  , 1.0736516 , 1.0113649 , 1.2127562 , 1.716106  ,
       1.1430745 , 0.7722485 , 1.3037333 , 0.80180734, 0.8064386 ,
       2.29817   , 1.0128781 , 0.449103  , 0.9792804 , 1.5757511 ,
       0.9262881 , 0.98331344, 0.77941364, 0.76391983, 0.58764315,
       1.2997601 , 0.80915725, 0.652058  , 3.2275884 , 1.0290947 ,
       0.7871399 , 0.55528516, 1.5320694 , 1.4710455 , 0.80910844,
       0.7328934 , 1.415511  , 2.3253963 , 1.4375293 , 1.9431152 ,
       1.9461544 , 1.7017119 , 1.9933062 , 0.75237995, 1.0404856 ,
       0.95007753, 2.0766478 , 0.48771214, 1.2407066 , 1.2047584 ,
       4.2365093 , 1.2342027 , 1.6761479 , 2.2604363 , 1.0294356 ,
       0.83357644, 1.887533  , 0.7001124 , 0.49013984, 0.8797233 ,
       0.75955176, 1.1237214 , 0.6271076 , 1.0664544 , 1.685539  ,
       0.8087435 , 1.901032  , 1.0199088 , 0.90822667], dtype=float32), array([-8.87077488e-03,  5.84828015e-03,  4.01348807e-03,  1.73741095e-02,
       -2.91048773e-02,  1.41969626e-03, -4.45110491e-03,  5.58379514e-04,
        2.48903502e-02,  5.26032643e-03, -2.19150446e-02, -5.45547437e-03,
        3.57887312e-03,  1.10310211e-03,  1.06853880e-02, -2.91704223e-03,
        1.48890046e-02,  4.31706430e-03, -1.94962602e-02,  5.27994055e-03,
        1.12237129e-02,  9.34236962e-03, -1.18980296e-02,  3.98874935e-03,
        3.95633560e-03, -1.30191781e-02, -1.31876394e-02, -8.24392308e-03,
       -9.50695761e-03, -2.63249403e-05,  6.23120554e-03, -1.28828026e-02,
       -7.76548171e-03,  8.08505528e-03, -2.52037682e-03,  2.25340314e-02,
        2.41748616e-02,  6.30463799e-03, -7.88017933e-04,  9.45930555e-03,
       -3.32022808e-03, -1.67957915e-03, -5.22595132e-03, -4.82865144e-03,
        6.61858218e-03, -1.78637616e-02,  2.42604893e-02,  1.16066709e-02,
       -3.76606430e-03, -1.63133685e-02, -7.19709415e-03, -9.12474561e-03,
       -1.52624939e-02,  1.04702124e-03,  1.55030675e-02, -5.23319794e-03,
       -1.86956092e-03,  5.50087821e-03, -9.78525635e-03,  1.53942071e-02,
       -6.70751184e-03,  5.92073938e-03,  7.56177772e-03,  9.06833727e-03],
      dtype=float32), array([-0.3742567 ,  1.0946753 , -1.0859125 , -0.22339424, -0.78474104,
        0.42585203, -0.36109996, -0.40538782,  0.17515503, -0.32289845,
        0.62559307,  0.30058017, -0.19414698,  0.557047  , -0.53673863,
        0.03649635,  0.19212198, -0.22275092, -0.52999216,  0.0287788 ,
       -0.78752166, -0.10794039,  1.4544551 , -0.9187975 ,  0.26707414,
        1.9061642 , -0.8609087 ,  0.45194745, -0.01472078, -0.42494163,
        0.25072554, -0.61290157,  1.4083049 ,  0.07588157,  0.7129993 ,
        0.8638027 ,  0.3146558 , -0.17917334,  1.1147873 , -0.08483746,
        0.9875475 ,  0.83307993, -0.5331484 , -1.1606771 , -0.24397597,
       -1.0259336 , -0.14936647, -1.2361737 , -0.2191594 , -0.15771037,
       -1.3652436 ,  0.8095283 ,  0.05814042, -0.8922693 , -0.75461835,
       -1.4229337 ,  0.895259  , -0.7424283 ,  1.0388619 , -0.9293757 ,
       -0.78839517, -0.24511983,  0.5412401 ,  0.6939706 ], dtype=float32), array([1.4568433, 3.0972347, 1.6743501, 2.2613337, 2.7683678, 3.985018 ,
       2.6602283, 2.647184 , 2.6325748, 2.4000087, 2.2155504, 1.6206949,
       2.5223982, 1.5732076, 1.976293 , 3.8055692, 3.297247 , 3.1294389,
       2.3268056, 2.7222366, 2.8037612, 3.1055353, 3.1826446, 2.5524786,
       2.9032977, 4.5118484, 2.6118202, 4.8034725, 2.3156142, 1.7530864,
       2.1126683, 1.5173818, 5.1105957, 4.5861654, 1.8303947, 1.9284627,
       2.8020198, 3.434366 , 2.2706523, 2.2735462, 2.4608   , 6.011382 ,
       2.0068836, 5.4207315, 2.582288 , 4.9887433, 2.8148782, 2.662744 ,
       1.4469848, 0.778804 , 4.2717476, 2.0752134, 3.7974255, 4.6515245,
       1.9531317, 3.1402907, 3.8961015, 1.9785044, 3.003282 , 3.0277631,
       1.4806596, 3.7044046, 4.206422 , 2.470916 ], dtype=float32), array([ 2.64298450e-03,  3.07319948e-04, -4.05455148e-03,  1.74659844e-02,
        5.15494682e-03, -1.30144577e-03, -1.68758407e-02, -1.70207992e-02,
       -1.06101623e-02, -1.14496332e-03,  2.34608678e-03, -1.05609847e-02,
       -6.95127854e-03, -1.90374125e-02, -1.12822177e-02,  3.86560056e-03,
       -7.79978838e-03,  1.39149095e-04,  5.72168780e-03, -7.33346213e-04,
        5.12056472e-03, -5.06940810e-03, -3.73941637e-03,  1.83725439e-03,
        1.05942059e-02, -1.65749516e-03, -1.18063660e-02, -1.33063877e-02,
        1.97596066e-02,  1.04493247e-02, -1.63232852e-02,  1.02165341e-03,
       -1.32124675e-02,  6.14568731e-03,  2.11597793e-02, -1.97137017e-02,
        2.58071162e-02,  3.96468851e-04, -6.30958285e-03,  8.71315133e-03,
       -1.24859698e-02, -4.58627800e-03, -1.68729145e-02,  1.11129405e-02,
        2.31174659e-02, -4.92749736e-03,  1.32745421e-02,  9.88583826e-03,
       -1.74556822e-02,  7.13663455e-03, -7.69760506e-03,  1.29867774e-02,
        1.45353181e-02,  2.26664618e-02,  4.08274587e-03,  6.17819931e-03,
        2.14874204e-02, -2.39525829e-02,  1.47537626e-02, -1.46936262e-02,
       -1.27800414e-03,  4.03130573e-04, -2.32468569e-03,  2.34785723e-03,
       -3.80118610e-03, -8.04770272e-03,  1.57092288e-02,  2.37645190e-02,
       -9.81659442e-03,  9.17855836e-03, -5.12344996e-03, -7.07755331e-03,
        1.29104070e-02,  9.36874095e-03, -2.64709350e-02,  1.57956555e-02,
        1.73834246e-02,  6.47249166e-03,  6.03770750e-05, -3.42159742e-03,
       -1.73615944e-02,  1.25452345e-02,  9.17024538e-03, -7.43759610e-03,
        4.21562605e-03,  1.33688503e-03,  2.26285029e-02, -1.07380673e-02,
        4.67387901e-04, -1.24562420e-02, -4.39719850e-04, -9.46590770e-03,
       -7.66750006e-03, -1.12350006e-02,  2.13132153e-04, -1.24805665e-04],
      dtype=float32), array([-1.2491874 ,  0.39099088,  0.9118196 , -0.15353097,  0.60283285,
       -0.1697351 ,  0.5390908 ,  0.664287  , -0.7408721 , -1.0033126 ,
        1.180296  ,  0.9943928 , -0.85526913, -0.6675077 , -0.7328624 ,
        1.0274999 , -0.975333  ,  0.31500766, -0.6383482 , -0.15012132,
        0.6442663 ,  0.00267519, -0.38865438, -1.3614804 , -0.32549155,
        1.3064233 , -1.3907932 , -0.7832797 ,  1.0878284 , -0.8172778 ,
        0.09097283,  0.8242727 ,  0.9366766 , -0.6179701 ,  1.2042947 ,
        0.06521765,  0.32100874,  0.31440285,  1.3998475 , -1.1549044 ,
        0.4203607 , -1.0356739 , -0.1321293 ,  0.9111136 , -0.8034579 ,
        0.16966973,  0.5652784 ,  0.11221825,  1.1334457 ,  0.18600091,
        0.7421951 ,  0.9470607 ,  0.7508382 , -0.569368  ,  1.0320612 ,
        0.46192536,  0.46291107,  1.2125865 ,  0.320616  ,  1.4832476 ,
       -0.97933716, -0.26257318, -1.1303471 , -0.81859124,  0.1078432 ,
        1.2255874 , -1.4343951 ,  0.93760586,  0.8364112 ,  0.07732501,
        0.9653611 ,  1.4607134 , -0.27067393, -0.32228622, -0.7568006 ,
        1.0814809 ,  0.38523662, -0.94891447, -0.80071837, -0.49912754,
        0.58194315, -0.47308394,  0.71872205, -0.16887303, -0.03455655,
       -1.1347129 ,  1.9295762 ,  0.5906981 ,  1.2893    , -0.2995407 ,
        0.8510317 , -0.6493679 ,  0.3723039 , -1.2226421 , -0.38107848,
        0.5622623 ], dtype=float32), array([3.6009622, 1.5442879, 2.8876975, 1.8131865, 1.7484242, 2.3013089,
       1.0927784, 2.1053114, 2.3084013, 1.7753314, 2.504389 , 2.554539 ,
       2.4795604, 3.2732363, 2.7469697, 3.3909338, 1.7573792, 1.4441811,
       3.0909324, 2.4075067, 2.5658002, 2.4431217, 2.214643 , 4.2365236,
       1.9024659, 2.5636184, 4.1556654, 2.3018317, 2.4457555, 2.0291061,
       2.2720125, 2.9439318, 2.0561683, 2.2351837, 3.2166722, 1.883091 ,
       3.0639079, 3.4146876, 3.196459 , 1.9491283, 2.1036305, 3.0149915,
       1.7406826, 3.0751998, 1.9002625, 1.4562188, 3.2228503, 2.4633486,
       3.5305371, 3.2580998, 3.4334888, 1.6126927, 3.049053 , 3.5230482,
       2.4167829, 3.0068343, 1.7843963, 6.324427 , 1.0081675, 3.760389 ,
       1.1458913, 1.0499079, 3.4262059, 3.3835042, 1.5841829, 2.8043642,
       2.303041 , 1.8066409, 2.3204088, 2.9314275, 3.612543 , 4.764151 ,
       1.8273015, 1.2678609, 2.41182  , 3.0048733, 1.7336135, 2.2950885,
       2.8365514, 2.0535212, 2.5375245, 3.322919 , 3.1419597, 2.099541 ,
       1.0709789, 3.492847 , 3.459754 , 1.5984124, 2.4639816, 2.15624  ,
       1.8824834, 3.5008163, 2.4459658, 2.123041 , 2.8036175, 1.9950314],
      dtype=float32), array([-1.1956049e-02, -7.5927125e-03,  1.0764536e-03,  4.8639462e-03,
        1.3103095e-03,  1.3628659e-02, -1.1189722e-03, -9.2120789e-04,
       -1.0163886e-02,  1.0223418e-02,  8.8889180e-03,  2.6522437e-03,
        5.3105322e-03, -8.4596599e-05, -3.0356646e-03,  2.4374421e-03,
        1.2849035e-02, -2.8608911e-04,  7.9255421e-03, -1.2359809e-02,
       -3.8430872e-04, -1.7872846e-03,  8.2913013e-03, -9.1987373e-03,
       -1.0747193e-04, -2.5409632e-04,  2.2466965e-03, -1.2330201e-02,
        1.0370801e-03, -2.6939032e-03, -1.6006541e-02, -2.4675101e-03],
      dtype=float32), array([ 0.37953725,  1.0678345 ,  0.86735445,  0.90953505,  0.14943424,
       -0.30571702,  0.44591317, -0.22257169, -0.8192829 ,  0.06846908,
        0.79247904, -0.5777422 ,  0.7453857 , -0.89749455,  0.26828492,
       -0.22062036, -0.4687334 ,  0.11205209, -0.07048013, -0.18394814,
        0.35847414,  0.31769025,  0.4827368 ,  1.1418316 , -0.43659616,
       -0.59139663, -0.9550913 , -0.18660861, -0.58739775, -0.500978  ,
        1.2909157 ,  0.88215816], dtype=float32), array([1.0733352 , 1.5103297 , 1.1354581 , 0.93533385, 1.7045778 ,
       0.78448224, 1.29396   , 1.276848  , 0.75220424, 1.1151195 ,
       1.7210429 , 1.4224981 , 1.9278158 , 0.5871145 , 1.555046  ,
       1.0560083 , 1.2713894 , 0.72150296, 1.0010095 , 0.8953055 ,
       0.8971259 , 1.2444687 , 1.2501582 , 2.144216  , 0.7363168 ,
       0.6384665 , 1.1345698 , 0.8599504 , 0.7987603 , 1.4942675 ,
       0.67080146, 0.88053846], dtype=float32), array([[[[ 0.06507432,  0.0383587 , -0.06440162, ...,  0.06466664,
           0.06150343,  0.04837596],
         [-0.04819155, -0.06269171,  0.03362129, ..., -0.15001452,
           0.05864799,  0.12676632],
         [-0.09013493,  0.10472555, -0.08842189, ...,  0.00987452,
          -0.12368397,  0.09336796],
         ...,
         [-0.03528207, -0.08723415,  0.0824047 , ...,  0.08500316,
          -0.01513879, -0.13432552],
         [-0.06610287, -0.04161235,  0.1064803 , ...,  0.02870646,
           0.1218593 , -0.11441378],
         [ 0.0562751 ,  0.1322382 ,  0.12727398, ...,  0.09414248,
           0.1362669 , -0.07149317]]]], dtype=float32), array([-1.14845159e-02,  1.43743502e-02,  1.30261655e-03,  7.99506065e-03,
       -9.60562192e-03, -3.47878970e-03, -4.89836466e-03, -1.52271828e-02,
       -5.55264996e-03,  4.65925317e-03,  1.70065206e-03,  2.15407293e-02,
        8.51229066e-04,  1.06491158e-02, -5.06213401e-03, -4.64764526e-06,
        4.58315760e-03, -1.49775762e-02, -8.03068560e-03, -1.10948756e-02,
        4.18097829e-04,  5.50849317e-03,  1.69579051e-02, -4.18869359e-03,
       -6.50519133e-03,  3.47564858e-03, -1.18108438e-02, -5.67914266e-03,
       -4.82755993e-03, -6.91726850e-03,  1.43541172e-02, -2.86567141e-03,
        9.95810702e-03,  2.04157252e-02,  5.35385543e-03,  6.14756020e-03,
       -1.03188888e-03, -1.44243399e-02, -1.45259798e-02, -3.40173161e-03,
        6.70286641e-03,  4.24974225e-03, -8.56624858e-04,  1.46818105e-02,
       -4.28477954e-03,  1.68857109e-02, -5.13248006e-03,  7.55055714e-03,
        8.44047125e-03, -1.63520016e-02, -8.82443693e-03, -1.58597548e-02,
       -1.56202381e-02, -1.86975244e-02, -1.10746464e-02, -9.21595097e-03,
       -4.20378661e-03, -1.94386933e-02, -6.22466393e-03,  7.41483970e-03,
       -2.27329438e-03, -7.54953269e-03, -9.23344679e-03, -1.76737960e-02],
      dtype=float32), array([-0.32895243,  0.16416787,  0.627408  , -1.0634912 , -0.0998093 ,
       -1.0209225 , -0.56822497,  0.02810815,  0.35051388,  0.14471975,
       -0.6020823 ,  0.14158757, -0.8009144 ,  0.5500145 , -0.21380553,
        0.3776087 ,  0.15579614,  0.60216737,  1.4067956 , -0.12194066,
       -0.35621083, -0.08289383, -0.34060022,  0.71146953, -0.30938366,
        0.10667728, -0.00256783, -0.67139137,  0.07897648, -0.52061844,
        0.39056084,  0.18650544, -0.45465288, -0.6479144 , -0.67434555,
        0.5788708 , -0.37470448,  0.5341623 ,  0.171688  ,  0.31358144,
       -0.07459178, -0.65378815, -0.00662804, -0.2962172 , -0.43356574,
        0.16649938,  0.8519778 ,  0.4600515 ,  0.6733794 , -0.5108025 ,
        1.971817  , -0.5146569 , -0.01741064, -0.06282938,  1.0544134 ,
        0.42015535,  0.22878894, -0.12171281,  1.1174731 , -0.18241216,
        0.72790843, -0.06563359, -0.01205227, -0.3569536 ], dtype=float32), array([0.91115046, 1.0522578 , 1.3254477 , 2.207954  , 1.0601317 ,
       0.77888376, 1.4989189 , 1.9631648 , 0.994376  , 0.8616312 ,
       0.7214611 , 1.0254909 , 0.8961819 , 1.1652666 , 0.72447264,
       3.3578682 , 1.3762897 , 1.2011967 , 1.0085388 , 1.1060629 ,
       0.8576761 , 0.6180251 , 1.7450011 , 0.73651856, 0.55720216,
       1.1742257 , 2.094357  , 0.8111697 , 0.4709465 , 0.87793535,
       0.815082  , 0.7902744 , 0.49682093, 0.82506096, 1.0320913 ,
       0.62639976, 1.1450522 , 2.147753  , 0.5871965 , 1.0033698 ,
       0.711926  , 0.45798752, 1.2662008 , 1.5041811 , 2.3704696 ,
       0.7803418 , 0.8751745 , 1.3148959 , 0.73951703, 0.63207483,
       2.178584  , 0.8057432 , 1.47822   , 0.5900784 , 1.5530417 ,
       0.3850553 , 0.7301186 , 0.70786834, 0.7223259 , 1.344597  ,
       1.180997  , 1.5028636 , 0.79831606, 0.847071  ], dtype=float32), array([[[[-0.01654756, -0.03631701, -0.08596489, ...,  0.00382374,
          -0.06993192, -0.08818601],
         [ 0.07720728,  0.11977152, -0.09232634, ..., -0.08676048,
          -0.07154666, -0.04917926],
         [ 0.088413  , -0.11460901,  0.1265075 , ...,  0.05250334,
          -0.08796811, -0.06389531],
         ...,
         [ 0.08213137,  0.02020485,  0.00646137, ..., -0.09193543,
           0.10736682, -0.04212389],
         [ 0.11628717,  0.13040283,  0.06743199, ...,  0.03228441,
          -0.01502425, -0.10942216],
         [-0.10136038,  0.06527378, -0.10150036, ..., -0.02843908,
          -0.02518097,  0.04766123]]]], dtype=float32), array([[[[ 0.01424468,  0.00089255,  0.03767028, ...,  0.04319654,
           0.03352284, -0.02330706],
         [-0.06010389,  0.05150537, -0.04724663, ...,  0.00563768,
          -0.01206502, -0.04117114],
         [-0.02446158,  0.00474853,  0.05274703, ...,  0.02437192,
           0.01011605,  0.01452769],
         ...,
         [ 0.05688737,  0.07369936,  0.01417567, ...,  0.07779109,
          -0.03025602,  0.01625868],
         [-0.01665995,  0.00278476, -0.06263547, ..., -0.04683628,
           0.00896382, -0.01934298],
         [-0.03549866,  0.05745432,  0.05014408, ...,  0.01063601,
          -0.06867446, -0.02843986]],

        [[-0.01505903, -0.01268786,  0.06367105, ...,  0.03136326,
          -0.07482509, -0.00218799],
         [ 0.05709371, -0.00841127, -0.00456315, ..., -0.00100391,
           0.02426302, -0.05657378],
         [ 0.0280451 , -0.00784459,  0.02866014, ..., -0.05034392,
          -0.00175753, -0.02255429],
         ...,
         [ 0.02549586,  0.00288622, -0.05872396, ...,  0.07262198,
          -0.0008494 , -0.02417135],
         [-0.05514593,  0.06456313,  0.02900693, ...,  0.00227031,
          -0.04115798, -0.04575283],
         [-0.00303905, -0.01884527,  0.04034723, ...,  0.06016772,
          -0.02758593, -0.00833876]],

        [[-0.03666319,  0.03762932, -0.06215709, ..., -0.01519814,
           0.05037627,  0.03635603],
         [-0.00410885,  0.00290798,  0.00148262, ...,  0.02800655,
          -0.0134926 , -0.04024334],
         [-0.04682567,  0.03052453, -0.08149172, ...,  0.06718212,
          -0.02372018,  0.06399991],
         ...,
         [-0.00461128,  0.05143045, -0.02333953, ..., -0.00874203,
          -0.01452109, -0.01434116],
         [ 0.00745566, -0.01365046,  0.03793692, ..., -0.0516449 ,
           0.04239563, -0.04050361],
         [ 0.03545383,  0.00193113,  0.0063471 , ...,  0.00667082,
           0.03304246,  0.03001925]]],


       [[[-0.00482868, -0.03481042, -0.03118956, ...,  0.05304744,
          -0.00095057, -0.01831236],
         [ 0.06544004,  0.03192688, -0.05420363, ...,  0.01673234,
          -0.03075669,  0.00598879],
         [-0.03278545,  0.0377486 , -0.07561447, ..., -0.01341267,
           0.0575869 ,  0.05352687],
         ...,
         [-0.01073439, -0.02528746, -0.00937355, ...,  0.02307961,
           0.0496835 ,  0.02996158],
         [-0.00629604,  0.05266036, -0.01088189, ...,  0.01972579,
           0.03910283,  0.04159505],
         [ 0.02722536, -0.00743442,  0.0182029 , ...,  0.02146261,
          -0.04335878, -0.05155716]],

        [[ 0.04491744,  0.00896094, -0.00643302, ...,  0.04075677,
          -0.0581595 ,  0.00026463],
         [-0.05018152, -0.01271485, -0.0001596 , ..., -0.03946308,
          -0.01596229, -0.02102491],
         [ 0.02437523,  0.02545315,  0.03214822, ...,  0.06955669,
           0.06206647,  0.0195378 ],
         ...,
         [-0.05742346, -0.01548006,  0.04951104, ...,  0.01742573,
          -0.02753516, -0.02632523],
         [ 0.03662084,  0.07691588, -0.02733183, ...,  0.00642068,
           0.05835101,  0.02730932],
         [ 0.0799595 , -0.03675076,  0.05919283, ..., -0.03359783,
          -0.05276621,  0.01958466]],

        [[ 0.02430791,  0.05693762, -0.03017052, ...,  0.03996372,
          -0.02764536, -0.06260277],
         [ 0.04820496,  0.01904309, -0.0265593 , ...,  0.060046  ,
          -0.01232135,  0.01758953],
         [ 0.04946434, -0.04217432,  0.05451572, ...,  0.02101783,
           0.01873767,  0.04168094],
         ...,
         [-0.0300589 ,  0.08319014,  0.05088941, ..., -0.02097444,
           0.05800254, -0.0126657 ],
         [ 0.06332973, -0.00872204,  0.03770545, ...,  0.01066931,
          -0.0642512 ,  0.05235235],
         [ 0.006797  , -0.05178362, -0.00471833, ...,  0.0691426 ,
           0.02470934,  0.01587686]]],


       [[[-0.02448616, -0.00833633,  0.05355173, ..., -0.03258884,
          -0.04772674,  0.04841507],
         [-0.04173645,  0.03539318, -0.04062972, ...,  0.00916653,
           0.04746039,  0.02305111],
         [ 0.02130703,  0.08100215, -0.04340016, ...,  0.02194587,
          -0.0063732 ,  0.01416013],
         ...,
         [-0.0546542 ,  0.03045026, -0.02519258, ...,  0.0743622 ,
          -0.0508408 , -0.03454842],
         [-0.05186157,  0.06772699,  0.04036741, ...,  0.0731861 ,
          -0.01784851, -0.05903432],
         [ 0.04367395,  0.04937586,  0.01069391, ...,  0.04837349,
           0.03177476, -0.04837797]],

        [[-0.06895938, -0.00503877,  0.04070608, ...,  0.0616184 ,
          -0.06749316, -0.03705233],
         [-0.04697865, -0.0071683 ,  0.01244586, ...,  0.00185364,
          -0.02985797,  0.0462677 ],
         [ 0.06556716,  0.03142031, -0.0183294 , ..., -0.0568024 ,
          -0.03447368, -0.0311856 ],
         ...,
         [-0.03003608,  0.04892425,  0.01637825, ..., -0.02477418,
          -0.04168371, -0.03216997],
         [-0.00502437,  0.07185619,  0.01954871, ...,  0.00328605,
           0.00542415, -0.0643727 ],
         [-0.00627904,  0.00525586,  0.05953315, ...,  0.02608552,
           0.02524812,  0.03089483]],

        [[-0.0120166 ,  0.03092097, -0.02532151, ..., -0.01139548,
          -0.01715911, -0.01942086],
         [ 0.03194041, -0.00687411,  0.04732445, ...,  0.05617454,
           0.04179855,  0.04154376],
         [ 0.0383399 ,  0.00558312, -0.02651033, ..., -0.00605279,
           0.05787095,  0.0075128 ],
         ...,
         [ 0.05303428, -0.02663224, -0.03361264, ...,  0.04328621,
           0.00799708,  0.03265782],
         [ 0.01138439,  0.02606473,  0.00712641, ..., -0.00036596,
          -0.03678272, -0.05564217],
         [-0.0020071 ,  0.00537953, -0.0058859 , ...,  0.02652507,
          -0.01878122, -0.04657112]]]], dtype=float32), array([-0.00866781,  0.00043175, -0.02267546, -0.00588249, -0.01619428,
        0.00693679, -0.01642577, -0.00894962, -0.00756589,  0.00048551,
        0.01235039, -0.00975456, -0.01609016,  0.01177189,  0.00511571,
       -0.01085061,  0.01821009,  0.00267694,  0.00745658,  0.00305827,
        0.01172034,  0.00486639,  0.0062416 ,  0.00820197, -0.00067913,
       -0.01793715, -0.00536067,  0.01056727, -0.0043758 , -0.00905693,
       -0.00557253, -0.01356328,  0.0079039 , -0.01937935, -0.0031044 ,
       -0.00283815, -0.00195969,  0.01152973,  0.00228051, -0.00235514,
       -0.02325517,  0.00984983, -0.0026623 ,  0.01147717,  0.01310346,
       -0.00265784, -0.00203484, -0.01597126], dtype=float32), array([-0.4523802 , -0.60680586, -0.41664672,  0.77265286, -0.3204705 ,
        0.44871926,  1.1570328 ,  0.59436834,  0.35309568,  0.22541887,
        0.09421613,  0.05400243,  0.21266088, -0.15351766,  0.35699934,
        1.0045456 , -0.22318809,  1.2076346 ,  0.8425185 ,  0.20759466,
       -0.19605502, -0.87783766,  0.01027289, -0.18456782,  0.6263518 ,
       -0.44506136,  0.3416903 , -0.05929903, -0.5774805 ,  0.35518736,
        0.35955787, -0.21088879,  0.42505938,  0.11832245, -0.20116596,
        0.57543004,  0.18427886,  0.3820941 ,  0.50097895,  0.99678814,
        0.62075186, -0.7967887 , -0.3443132 , -0.0424087 ,  0.12077957,
        0.01139039,  0.5488557 , -0.32392123], dtype=float32), array([1.2769285 , 0.8672683 , 1.1520338 , 1.9359312 , 0.681412  ,
       1.690948  , 0.6964476 , 2.8513124 , 0.5719428 , 1.0068662 ,
       0.73740697, 0.5087516 , 0.94670933, 1.0798539 , 0.38758597,
       1.7011607 , 0.7666165 , 2.2287548 , 1.7233771 , 1.2908752 ,
       0.6585587 , 0.5000036 , 0.9224162 , 0.5120623 , 1.5520793 ,
       0.736293  , 1.3603108 , 0.8438097 , 1.0782831 , 0.7135426 ,
       1.6725116 , 0.8495336 , 2.4820662 , 1.390289  , 1.0109596 ,
       0.7452014 , 1.0414575 , 1.3297905 , 1.4442374 , 2.069977  ,
       0.9525252 , 1.5704628 , 0.6123756 , 1.1719683 , 0.9205703 ,
       0.6431648 , 1.0096809 , 1.09717   ], dtype=float32), array([ 0.00228857,  0.01091637, -0.00245024,  0.02292728, -0.00496703,
       -0.00167608,  0.01327716, -0.02139147,  0.00154317,  0.01084907,
        0.00443674, -0.00674172, -0.0098298 , -0.0075757 , -0.00419581,
        0.00048616, -0.00158333, -0.00646562, -0.01222695,  0.00937317,
        0.00999575,  0.00999673,  0.00153453, -0.01828601,  0.00388268,
        0.00034817,  0.01499779,  0.00234583,  0.00953003, -0.00660941,
       -0.00950413, -0.01767196, -0.02248643,  0.01670921, -0.0012656 ,
       -0.01613794, -0.00213578, -0.00055623, -0.00487272, -0.00327535,
       -0.01172588, -0.01476036, -0.01024483,  0.00047967,  0.00777391,
       -0.01761294,  0.0208077 ,  0.00217372,  0.01025014, -0.01017588,
       -0.01335327, -0.00292875, -0.00737939,  0.00355836, -0.01412836,
       -0.01415148, -0.00764421,  0.01338087, -0.00089274,  0.0056806 ,
       -0.00994402,  0.02802108, -0.00440288, -0.02296424, -0.00637628,
       -0.01615303, -0.0063987 , -0.01696983,  0.00089672,  0.01490522,
       -0.01038628, -0.01580765, -0.01976098,  0.01033782, -0.00414826,
        0.00136271, -0.01546738,  0.00619381,  0.01288   , -0.00974526,
       -0.00940752,  0.00198802, -0.02256178,  0.00797859,  0.00996567,
       -0.00185325,  0.02106457,  0.00409162, -0.01785318,  0.01191115,
        0.00463185,  0.003539  ,  0.00173764, -0.01351528, -0.01626516,
       -0.02624131], dtype=float32), array([ 0.985958  ,  0.66397125,  0.3648341 ,  0.03866111,  0.5237321 ,
        0.08792207,  0.02250199,  0.29566863,  0.50003964,  0.3594028 ,
        0.4146438 ,  0.8862974 ,  0.4463598 ,  0.7006603 ,  0.56837296,
       -0.49085197,  0.9128856 ,  0.21492614, -0.04248423, -0.21518122,
        0.15902331, -0.5294282 , -0.9790625 , -0.20738812,  0.93693125,
        0.07247251, -0.36960068,  0.6393555 , -0.33116812, -0.38565722,
        0.54171586,  0.70032316, -0.90870994, -0.5706147 ,  0.26214972,
        0.28691596, -0.152336  ,  0.7176674 ,  0.7589033 ,  0.31378192,
        0.706182  ,  0.5607514 ,  1.0099962 ,  0.15207773, -0.57929987,
        1.0507978 , -0.0426368 ,  0.08614478,  0.9041456 ,  0.69114906,
       -1.1321106 ,  0.7371079 , -0.13887398,  0.1407833 ,  0.277026  ,
       -0.5609014 , -0.79077435, -0.7544568 , -0.56432414, -0.71577084,
        0.84213   , -0.57359076, -0.92518497,  0.86351913, -0.12643707,
       -0.5857523 , -0.17366746,  0.04894947, -0.8741022 ,  0.48714158,
        0.6216841 ,  1.2663509 ,  0.6522979 , -0.35830343, -0.37700796,
        0.1298799 ,  1.1595551 ,  0.4199368 , -0.8432106 ,  0.5900971 ,
       -0.7011863 , -0.6525235 ,  0.6310454 , -0.31903562,  0.43469638,
       -0.12094188, -0.15814607,  0.27484968,  0.5786752 , -0.6769456 ,
        0.3006247 , -0.5059049 ,  0.6843295 ,  1.1959534 ,  0.44700563,
        0.16415223], dtype=float32), array([1.982301  , 2.5074077 , 1.1441717 , 1.3039062 , 1.0328743 ,
       1.4165201 , 1.396686  , 0.9933113 , 1.1109036 , 1.9334276 ,
       0.6550435 , 1.3614366 , 1.6910104 , 1.1229936 , 1.0614688 ,
       1.1781927 , 2.1210802 , 1.1622757 , 0.8822355 , 1.0629854 ,
       2.4265873 , 0.6972003 , 3.2307863 , 0.6870672 , 1.4788778 ,
       1.2217348 , 0.35033584, 1.70361   , 0.9531388 , 1.007478  ,
       0.8678845 , 1.2934614 , 1.1327065 , 1.794137  , 1.8909687 ,
       0.64832675, 0.9090972 , 1.1213868 , 1.4883603 , 0.67260206,
       1.1252917 , 0.59597504, 1.2327485 , 0.9121869 , 1.1190988 ,
       1.7323459 , 1.2849253 , 1.7384158 , 1.5257198 , 1.7029828 ,
       2.0423148 , 1.6071029 , 0.62932515, 0.4703962 , 0.7561092 ,
       0.76377183, 1.0648887 , 1.2469667 , 1.4984347 , 1.5955168 ,
       1.8760766 , 0.9472722 , 1.4235092 , 2.0375104 , 1.5091596 ,
       1.7500669 , 0.44917896, 1.0869423 , 1.571988  , 1.4871243 ,
       1.4280245 , 1.2310162 , 1.7390355 , 0.89303774, 1.378424  ,
       1.5123838 , 1.4564625 , 1.1718137 , 2.2375252 , 1.4414709 ,
       1.8446896 , 1.7561446 , 1.1922575 , 1.1377491 , 1.2848117 ,
       1.1594918 , 0.55110836, 1.1635746 , 1.1122924 , 0.92210114,
       0.78365594, 1.1541913 , 1.2811153 , 1.2993569 , 1.2496419 ,
       0.99677694], dtype=float32), array([[[[-0.08707796, -0.1075462 ,  0.01410485, ..., -0.06986219,
          -0.11953679, -0.11077838],
         [-0.10750756,  0.09314348, -0.08155455, ...,  0.06619992,
          -0.07760353,  0.12076144],
         [-0.02245939, -0.13548824,  0.04270321, ..., -0.03768387,
           0.12426151,  0.05841692],
         ...,
         [ 0.02918876, -0.00607065,  0.04934244, ..., -0.05262392,
           0.01503464,  0.05496414],
         [ 0.04504389, -0.09162986, -0.10735276, ..., -0.05936322,
          -0.09740696, -0.06607591],
         [ 0.07297454, -0.10304959,  0.10476777, ...,  0.02192977,
          -0.02067645, -0.00312275]]]], dtype=float32), array([[[[ 9.39800963e-03, -2.33453624e-02, -1.43713122e-02, ...,
           7.82818708e-04, -2.12382749e-02, -2.08279788e-02],
         [ 1.58710610e-02,  2.17808522e-02,  2.86057089e-02, ...,
           5.55738993e-03, -9.92181897e-03,  3.98993753e-02],
         [ 4.15235423e-02,  2.35603447e-03, -1.53265353e-02, ...,
          -3.37293260e-02,  6.80001732e-03, -2.57988777e-02],
         ...,
         [ 2.29237191e-02,  4.24136296e-02, -1.43876672e-02, ...,
           7.17004854e-03,  2.33130530e-02,  4.50129574e-03],
         [ 3.44656594e-02, -3.51470038e-02, -2.29315907e-02, ...,
          -2.82732658e-02,  4.94784899e-02,  3.97968739e-02],
         [ 3.32254395e-02,  2.92437319e-02, -2.63510700e-02, ...,
          -3.11574489e-02,  1.13532674e-02,  2.91266236e-02]],

        [[ 4.04983796e-02, -1.08478395e-02, -1.64786205e-02, ...,
          -3.39859389e-02, -4.30794607e-04,  2.01915726e-02],
         [-7.63708819e-03, -4.96905595e-02, -3.66185978e-02, ...,
          -4.40131463e-02,  3.01796179e-02,  1.53617514e-02],
         [-4.89636464e-03,  1.07585108e-02, -1.89842749e-02, ...,
          -4.43124883e-02, -1.65439602e-02, -2.37529213e-03],
         ...,
         [-4.40392420e-02,  4.64672409e-02,  2.03561019e-02, ...,
          -3.73294391e-02, -4.23473306e-03,  2.64613517e-02],
         [ 2.31654290e-03,  1.99098252e-02,  1.00793382e-02, ...,
          -3.06972489e-02,  3.10822409e-02,  3.95127237e-02],
         [-4.75974530e-02, -1.67836361e-02,  3.18646468e-02, ...,
           3.00462055e-03,  1.78123116e-02, -4.53438871e-02]],

        [[ 1.30904298e-02,  4.36252318e-02,  2.13435595e-03, ...,
          -4.83312793e-02,  1.60680264e-02,  4.37258333e-02],
         [-3.76844145e-02,  1.03052927e-03,  1.27174612e-03, ...,
           1.69270709e-02,  1.42401820e-02,  2.75351899e-03],
         [-4.60926816e-03, -2.46526785e-02,  2.83267889e-02, ...,
           1.92642435e-02,  3.50464359e-02,  2.99070049e-02],
         ...,
         [ 1.66233983e-02, -1.85224544e-02,  1.14066182e-02, ...,
           1.33741077e-03,  1.08914422e-02, -1.98564064e-02],
         [-2.84437798e-02, -2.75446288e-03,  1.65821183e-02, ...,
          -9.65031609e-03, -2.30671223e-02,  3.44658247e-03],
         [ 1.28197856e-02, -9.26122162e-03, -7.50877755e-03, ...,
          -4.40200232e-02, -6.48518465e-03, -1.88974757e-02]],

        [[ 1.95132904e-02,  1.70571767e-02,  5.15281595e-02, ...,
          -4.08027284e-02, -4.26746160e-02, -4.51733768e-02],
         [ 3.66906897e-04, -1.92350056e-02, -1.01680374e-02, ...,
          -6.76758762e-04,  1.12593388e-02, -4.56443951e-02],
         [ 1.77048333e-02, -2.97307726e-02,  2.99474113e-02, ...,
           2.89791971e-02, -1.53568843e-02,  2.30498593e-02],
         ...,
         [-1.53896660e-02, -2.41195709e-02,  8.70559888e-04, ...,
          -2.99209356e-02,  9.33271274e-03, -3.15362238e-03],
         [ 7.16402149e-03,  4.69111800e-02,  2.96355039e-02, ...,
          -1.43102547e-02, -3.22265141e-02,  4.49990556e-02],
         [-3.94344293e-02, -1.63918380e-02,  9.50811058e-03, ...,
           3.75813544e-02, -2.57205348e-02, -5.51035907e-03]],

        [[ 3.64404768e-02,  4.20697927e-02,  2.25444883e-02, ...,
          -2.73863394e-02, -1.66027329e-03,  1.08565371e-02],
         [-1.61961429e-02,  3.83247323e-02,  1.34648038e-02, ...,
           4.52149808e-02,  1.01356935e-02, -4.28545587e-02],
         [-1.75097752e-02,  4.46826816e-02,  2.93189362e-02, ...,
          -4.46393266e-02, -2.05310136e-02, -3.32263149e-02],
         ...,
         [ 4.13087830e-02, -4.96722758e-03,  1.14724822e-02, ...,
          -1.47077711e-02,  2.92380806e-02,  8.39405414e-03],
         [-4.66568358e-02, -2.63425242e-03,  4.19786014e-03, ...,
          -2.33113039e-02, -1.71483215e-02,  1.96546242e-02],
         [-3.79108563e-02,  2.52747610e-02, -1.57976244e-03, ...,
          -1.44355819e-02, -3.89069021e-02,  3.19384746e-02]]],


       [[[-3.24457586e-02, -4.33347225e-02, -1.77302323e-02, ...,
           3.49842720e-02, -1.70608442e-02, -2.47400459e-02],
         [-4.62391265e-02, -5.72244608e-05, -1.93055402e-02, ...,
          -4.15121801e-02, -3.19358855e-02, -2.53850943e-03],
         [-1.91468634e-02, -3.51844020e-02, -3.04093622e-02, ...,
           1.53572038e-02,  1.98731814e-02,  2.96312682e-02],
         ...,
         [-1.44839995e-02, -3.11992746e-02, -4.63080183e-02, ...,
          -4.40149978e-02, -3.52691412e-02,  4.54568975e-02],
         [-4.57481928e-02,  1.02078579e-02, -4.59522791e-02, ...,
          -5.62101509e-03,  2.22023744e-02,  3.39684822e-02],
         [ 2.46405583e-02, -2.12257728e-02, -1.62187424e-02, ...,
           1.00037912e-02, -5.71648329e-02, -2.56667323e-02]],

        [[-3.50555070e-02, -4.44249958e-02,  1.19687021e-02, ...,
          -3.23674851e-03, -1.90093946e-02, -2.74389666e-02],
         [ 1.84081625e-02, -3.72323506e-02,  1.35047697e-02, ...,
           3.30350362e-02,  2.59900708e-02, -2.77471058e-02],
         [ 1.77526847e-02,  2.01343149e-02,  4.01921906e-02, ...,
          -3.83822285e-02, -3.50655951e-02,  1.64339948e-03],
         ...,
         [-4.25099395e-02,  2.48196418e-04, -8.22042115e-03, ...,
          -2.07038540e-02,  2.01903004e-02, -4.05731685e-02],
         [ 3.99073362e-02,  3.00045162e-02, -4.76091094e-02, ...,
          -3.74133252e-02,  4.19255309e-02, -2.29447298e-02],
         [-6.78190123e-03,  1.88501459e-02, -1.79172624e-04, ...,
          -3.76389958e-02, -4.80053499e-02,  7.67785357e-03]],

        [[-2.49061026e-02,  2.13914067e-02, -1.46297775e-02, ...,
           3.19765061e-02,  3.07623837e-02,  2.80854329e-02],
         [-2.83684880e-02, -1.36843110e-02, -1.03921909e-02, ...,
          -3.89615819e-02,  4.75941338e-02,  2.83242520e-02],
         [-1.40963038e-02, -3.71280164e-02, -2.25495342e-02, ...,
           2.35698409e-02, -2.95131691e-02,  4.43154983e-02],
         ...,
         [ 1.89473536e-02, -3.20204236e-02, -4.46238965e-02, ...,
           2.51568183e-02,  1.71150807e-02,  2.88020801e-02],
         [ 8.86083674e-03,  4.33280207e-02, -3.27560119e-02, ...,
           2.99114529e-02,  4.74263057e-02,  4.82666977e-02],
         [ 1.26985356e-03,  1.33627346e-02, -4.79906835e-02, ...,
          -1.85981300e-03, -2.76873298e-02, -3.38510163e-02]],

        [[-3.35961543e-02,  1.71529353e-02,  1.66185256e-02, ...,
           3.02393306e-02,  3.65176350e-02,  2.99649481e-02],
         [-9.15693212e-03, -3.79754193e-02,  2.97930203e-02, ...,
           3.30710672e-02, -4.17903215e-02,  1.91474496e-03],
         [ 1.01083713e-02, -1.99192297e-03,  2.89081540e-02, ...,
          -1.84910242e-02, -1.27246063e-02, -1.75826065e-02],
         ...,
         [-8.33210628e-03, -3.47139016e-02,  2.88800709e-02, ...,
          -2.30191387e-02, -8.66189227e-03, -1.93524826e-02],
         [ 9.52439662e-03, -3.50931771e-02, -5.03624007e-02, ...,
           2.09861696e-02,  2.15055030e-02, -2.87697259e-02],
         [ 2.36796550e-02,  2.30422076e-02,  2.08956655e-02, ...,
          -4.22094651e-02, -1.68934874e-02, -2.19097566e-02]],

        [[ 2.42332369e-02, -1.98405236e-02,  3.59833166e-02, ...,
           1.60624590e-02,  3.08506191e-02,  3.30454409e-02],
         [-2.39926726e-02, -2.27578506e-02,  1.43354828e-03, ...,
           1.32427728e-02,  4.56948467e-02, -3.42214331e-02],
         [-3.42131592e-02,  2.92122345e-02,  3.98397446e-02, ...,
          -2.37636305e-02,  2.48220842e-03, -3.78500596e-02],
         ...,
         [-4.28108089e-02, -2.68946495e-02,  6.00338448e-03, ...,
           1.93082145e-03,  1.15018273e-02, -1.67203657e-02],
         [-3.52105349e-02,  1.45453997e-02, -4.86312211e-02, ...,
          -2.30938550e-02,  3.85437650e-03,  1.76043008e-02],
         [-1.67900901e-02,  1.33221997e-02, -3.93338799e-02, ...,
          -3.78068015e-02, -2.86279079e-02, -4.44234069e-03]]],


       [[[-7.39720697e-03, -1.94516871e-02, -2.32295808e-03, ...,
           2.28732582e-02, -2.87717078e-02,  1.36269974e-02],
         [-2.11946797e-02, -1.59302074e-02, -2.43196078e-02, ...,
           3.77815589e-02, -1.25665665e-02, -4.81139123e-02],
         [ 1.50431022e-02, -2.98095290e-02,  2.18846314e-02, ...,
          -2.48098318e-02,  1.31497597e-02,  2.91039310e-02],
         ...,
         [ 1.00665288e-02,  3.74810770e-02, -5.94704878e-03, ...,
          -3.36038731e-02,  6.19405927e-03,  5.81832277e-03],
         [ 2.34112446e-03, -1.05358632e-02,  1.63721584e-03, ...,
           2.67308112e-02,  4.58465517e-02,  2.24694908e-02],
         [-1.83711499e-02, -1.63297169e-02,  4.16077264e-02, ...,
           4.58240584e-02,  2.00935435e-02, -4.15118672e-02]],

        [[ 2.06819121e-02,  5.87611133e-03, -9.36767552e-03, ...,
           3.39281373e-02,  1.62598938e-02,  1.29874609e-02],
         [ 1.16429981e-02,  1.41137466e-02, -2.59583220e-02, ...,
           3.25354896e-02,  2.20385548e-02, -4.56187315e-02],
         [ 4.54919748e-02,  2.40489766e-02, -3.86225316e-03, ...,
          -2.03671250e-02, -4.28145118e-02,  1.30115869e-02],
         ...,
         [ 3.90777774e-02,  2.45126057e-02, -1.12078702e-02, ...,
          -3.70942429e-02, -3.96874845e-02, -4.01439033e-02],
         [-3.57786678e-02,  1.34095950e-02,  1.49729857e-02, ...,
          -2.43587513e-02,  3.68087962e-02,  3.72885503e-02],
         [-2.82577127e-02, -1.02655580e-02,  2.06400733e-02, ...,
          -5.08516049e-03,  2.79782582e-02, -5.30509874e-02]],

        [[-7.59006536e-04, -2.45325305e-02,  4.77914959e-02, ...,
           6.32492406e-03, -4.42054160e-02, -3.29070464e-02],
         [-3.28497961e-02, -5.69112226e-03,  2.61586029e-02, ...,
           2.32282523e-02, -4.14381176e-02, -3.63583937e-02],
         [-7.47035374e-05, -3.49332113e-03,  3.53076458e-02, ...,
           2.26859804e-02,  1.46898860e-02, -4.84472401e-02],
         ...,
         [-3.57735455e-02,  2.86526736e-02,  2.67770229e-04, ...,
          -6.10719770e-02,  3.00086457e-02,  4.54747006e-02],
         [ 2.01421604e-02,  4.54875194e-02,  2.35545263e-02, ...,
          -2.26423424e-03, -2.36153137e-02,  4.47486266e-02],
         [-3.83170247e-02, -3.03370710e-02,  8.95459019e-03, ...,
           1.09117627e-02,  1.11033330e-02,  2.80249007e-02]],

        [[-1.53730847e-02, -2.46905442e-02,  5.70133589e-02, ...,
          -1.77951362e-02,  3.30916420e-02, -1.40536577e-02],
         [-1.79887954e-02,  4.38691117e-02,  4.31126542e-02, ...,
           3.58376466e-02, -5.87260090e-02, -3.02123502e-02],
         [-6.10456197e-03, -1.96481217e-02, -2.80847866e-02, ...,
           3.23423930e-02,  8.22995696e-03, -2.46360153e-02],
         ...,
         [-1.87199581e-02, -3.75239328e-02,  1.13222124e-02, ...,
          -1.41101622e-03,  5.01614437e-03, -3.51174781e-03],
         [ 3.67740840e-02,  4.48973514e-02, -3.60258706e-02, ...,
           1.55806290e-02,  9.12820362e-03, -4.05599624e-02],
         [-2.33425014e-02,  1.56824365e-02, -7.74761802e-03, ...,
           4.18690033e-02, -1.17141823e-03, -4.39169025e-03]],

        [[ 1.66128613e-02,  2.12353207e-02,  1.93549525e-02, ...,
          -5.47727533e-02, -1.69110149e-02, -1.76782887e-02],
         [-5.68509214e-02, -4.43395460e-03,  4.34518605e-03, ...,
          -3.32901254e-02, -7.06658792e-03,  2.04470623e-02],
         [-6.93739334e-04, -2.40633655e-02,  4.31761742e-02, ...,
          -5.02444841e-02, -3.16515118e-02, -3.85352373e-02],
         ...,
         [-5.75645408e-03, -1.43984507e-03,  2.03404035e-02, ...,
          -4.78317700e-02, -2.31109541e-02,  5.03633032e-03],
         [-2.45599300e-02,  4.02975753e-02, -2.93684267e-02, ...,
           2.44764350e-02, -2.04211064e-02,  4.33304422e-02],
         [-1.43217985e-02, -9.68942698e-03,  3.21217999e-02, ...,
          -2.41951887e-02, -4.54646051e-02,  2.69609448e-02]]],


       [[[ 1.30786141e-02, -1.36102801e-02, -1.56459922e-03, ...,
          -2.63147969e-02,  2.61923694e-03,  4.28854525e-02],
         [-8.46563559e-03,  9.38569102e-03,  2.76352689e-02, ...,
           4.29869406e-02, -2.56688371e-02, -1.24253957e-02],
         [-1.35685876e-02,  2.71920599e-02, -2.25139246e-03, ...,
          -1.01479935e-02,  2.86109615e-02, -3.43095697e-02],
         ...,
         [-2.50990707e-02,  4.91323061e-02, -2.36395225e-02, ...,
           1.53486179e-02, -8.26350320e-03,  1.74927097e-02],
         [-2.13546604e-02,  5.10291159e-02,  9.18162521e-03, ...,
           1.23883772e-03, -2.18131822e-02, -3.38033587e-02],
         [ 1.16566233e-02, -4.03244942e-02,  4.35954370e-02, ...,
           4.86228243e-02, -6.31286800e-02, -2.15400234e-02]],

        [[-3.11750602e-02,  1.80900842e-02,  3.88454534e-02, ...,
           2.74938904e-02, -4.19258792e-03,  3.79342362e-02],
         [ 2.45964713e-02,  8.63566995e-03,  2.02425271e-02, ...,
          -4.16018218e-02,  2.66499911e-02,  1.05168251e-02],
         [-1.13887042e-02,  3.07048280e-02, -9.90593061e-03, ...,
           4.94393818e-02,  5.81353949e-03, -4.01373506e-02],
         ...,
         [ 4.86974902e-02, -1.85862780e-02,  1.94532704e-02, ...,
           2.48783249e-02, -7.60494499e-03, -5.14725521e-02],
         [-4.46440727e-02, -4.22860198e-02,  1.29204364e-02, ...,
           8.39343108e-03,  6.20447658e-02, -2.92182583e-02],
         [ 5.67407906e-03, -4.97814780e-03, -1.42042106e-02, ...,
          -1.81321874e-02, -1.45749254e-02,  1.32366456e-02]],

        [[ 4.70421799e-02, -5.05779982e-02, -1.48001444e-02, ...,
           3.05282921e-02,  2.42352150e-02, -2.03637015e-02],
         [ 1.54588455e-02, -1.17116449e-02, -7.07234535e-03, ...,
           2.04052180e-02,  1.50308758e-02,  6.45917188e-03],
         [-2.01627761e-02,  6.31175516e-03,  3.69933061e-02, ...,
           1.42326253e-02, -4.87900898e-02,  3.28617916e-02],
         ...,
         [-2.51458790e-02,  2.19389871e-02, -2.18646340e-02, ...,
          -3.14537175e-02,  5.03629772e-03,  4.28065769e-02],
         [ 2.81897932e-02, -8.58900044e-03,  2.11912561e-02, ...,
          -1.44745354e-02, -1.73727684e-02,  7.57394079e-03],
         [-1.82700865e-02, -5.28481789e-02, -9.05194040e-03, ...,
           2.50879284e-02, -5.75885586e-02, -4.10276465e-02]],

        [[-2.72940006e-02,  1.56631414e-02, -3.15485150e-02, ...,
           1.89664736e-02,  1.65876914e-02,  2.66889427e-02],
         [-6.47440972e-03,  3.35202478e-02,  1.85114983e-02, ...,
          -4.36888784e-02, -1.17434496e-02,  7.65817892e-03],
         [-7.38788396e-03,  2.19820701e-02,  2.07427014e-02, ...,
           3.09191775e-02, -1.30142337e-02,  4.60328069e-03],
         ...,
         [ 3.63871604e-02, -2.53115986e-02,  4.45168989e-04, ...,
           3.74800786e-02, -9.17225610e-03,  3.64885293e-02],
         [ 3.66043225e-02,  4.13866481e-03,  5.27518336e-03, ...,
           4.75670286e-02,  3.80869620e-02, -4.96203499e-03],
         [ 2.20883880e-02, -4.53457274e-02, -1.51984300e-02, ...,
           1.47290314e-02, -4.24387213e-03,  1.11561082e-02]],

        [[ 1.52461650e-02, -1.38657726e-02,  1.65762063e-02, ...,
          -4.12935168e-02,  6.47571264e-03, -3.67745683e-02],
         [-5.03118038e-02, -1.64246000e-03, -2.46127285e-02, ...,
          -1.85847264e-02, -4.10351194e-02,  7.03652017e-03],
         [ 1.77157111e-02, -2.35778652e-02,  3.95880034e-03, ...,
           3.88545590e-03,  3.87413451e-03, -4.98019792e-02],
         ...,
         [ 2.81911474e-02,  1.05845844e-02,  2.54567210e-02, ...,
           2.28061993e-02,  1.41809331e-02, -2.87360959e-02],
         [ 3.77062745e-02,  4.34562005e-02,  5.90607384e-03, ...,
           2.97006052e-02, -5.40559553e-03, -1.12716854e-02],
         [-1.96253378e-02, -5.46718389e-02, -4.28233668e-02, ...,
          -2.74175406e-02, -3.21521796e-02,  2.92431209e-02]]],


       [[[ 6.69203280e-03, -1.44917686e-02,  5.11608720e-02, ...,
          -3.38281356e-02,  5.56523073e-03, -8.87893420e-03],
         [ 1.31618138e-02, -4.23447713e-02,  1.04129938e-02, ...,
           3.51062939e-02, -5.22696925e-03,  1.56292617e-02],
         [ 9.18510929e-03, -8.52110051e-03, -7.42146606e-03, ...,
           2.91791726e-02, -4.16873489e-03,  2.60934196e-02],
         ...,
         [ 1.99212451e-02, -3.72419208e-02, -5.54905385e-02, ...,
          -1.86402425e-02,  2.95823514e-02, -3.17307040e-02],
         [ 1.01657026e-02,  3.36455391e-03, -4.02490515e-03, ...,
          -1.51748033e-02,  4.18763086e-02,  2.63323803e-02],
         [-4.02881578e-03, -4.40976117e-03, -2.78347135e-02, ...,
          -7.55423331e-04,  1.67862307e-02, -3.72226909e-02]],

        [[ 5.38613908e-02, -2.52936780e-03,  9.21611115e-03, ...,
          -4.56142090e-02,  2.15342902e-02,  1.94941889e-02],
         [ 5.19775692e-03, -2.62527633e-02,  3.83647941e-02, ...,
           2.04327386e-02,  3.63558605e-02,  1.90880476e-03],
         [ 3.06501072e-02, -1.72189865e-02,  2.92256493e-02, ...,
          -4.10303883e-02,  1.40237026e-02, -3.36681958e-03],
         ...,
         [ 3.81183513e-02, -3.44552770e-02,  1.70008338e-03, ...,
           1.55699700e-02,  2.20922288e-02, -4.60680090e-02],
         [-2.54593114e-03, -1.07985537e-03,  2.30717938e-02, ...,
          -1.23841297e-02,  5.34436740e-02,  7.42694549e-03],
         [ 1.47800976e-02, -2.32020430e-02,  3.78062553e-03, ...,
          -2.38555633e-02, -2.55744867e-02, -1.89374443e-02]],

        [[ 4.90472913e-02,  2.10406575e-02, -7.18772085e-03, ...,
           2.61806380e-02, -1.67339034e-02,  4.62954491e-02],
         [-2.51764506e-02, -5.30441105e-02, -1.31016970e-02, ...,
          -1.27681380e-03,  9.59973317e-03,  2.77066883e-02],
         [-3.73428091e-02,  4.55022529e-02,  7.88254570e-03, ...,
          -3.21596414e-02,  1.15982606e-03,  2.31214594e-02],
         ...,
         [ 5.64392395e-02,  3.56924924e-04,  2.33713109e-02, ...,
          -2.18057334e-02,  3.84289101e-02,  4.68692072e-02],
         [ 2.45767906e-02,  4.43094689e-03,  2.40987237e-03, ...,
          -2.92298254e-02,  1.87085140e-02,  1.30477818e-02],
         [-1.26158325e-02,  1.28021678e-02,  2.82371752e-02, ...,
           3.76945771e-02, -3.47708948e-02, -3.01819853e-02]],

        [[-1.73240192e-02,  5.64830936e-03,  2.99729798e-02, ...,
          -3.51217352e-02, -3.28681655e-02,  3.07108387e-02],
         [ 3.31814513e-02, -3.70831788e-02,  7.95910228e-03, ...,
          -1.14978049e-02,  7.21378950e-03,  5.04468121e-02],
         [ 3.00482903e-02,  3.80632058e-02,  3.72809358e-02, ...,
           3.29330377e-02,  2.28805147e-04,  3.62481028e-02],
         ...,
         [-2.21101139e-02, -2.27671210e-02, -5.50067350e-02, ...,
          -4.07102592e-02, -1.15748299e-02, -1.75138358e-02],
         [ 1.10511240e-02, -1.56250466e-02, -2.19363607e-02, ...,
          -1.99287571e-02,  4.21607867e-02,  1.79454405e-02],
         [-2.64360458e-02, -5.41322902e-02,  2.51096934e-02, ...,
           3.24144699e-02, -1.16955135e-02, -1.61544718e-02]],

        [[-4.47535999e-02, -2.23604906e-02,  4.19686437e-02, ...,
          -3.50131956e-03, -2.47683730e-02, -3.37492824e-02],
         [ 3.01012769e-02, -4.10454385e-02,  1.86773017e-02, ...,
           2.78144572e-02,  8.14894494e-03,  1.09057724e-02],
         [ 1.36719197e-02,  1.14235347e-02,  1.37261786e-02, ...,
          -1.02628516e-02,  1.74584743e-02,  1.46757765e-02],
         ...,
         [ 2.91786832e-03, -1.62006076e-02, -8.59217253e-04, ...,
           2.97963060e-02,  2.41493229e-02,  3.74607258e-02],
         [-3.37425284e-02,  9.35058482e-03, -4.97776903e-02, ...,
          -2.32305583e-02,  5.04754893e-02, -2.03006864e-02],
         [ 1.73393786e-02,  1.97558315e-03,  1.36091020e-02, ...,
           4.94927317e-02, -2.67765988e-02,  7.18587637e-03]]]],
      dtype=float32), array([[[[-9.52081196e-03,  8.26801732e-03,  6.00045500e-03, ...,
          -1.82406083e-02, -4.13968675e-02,  1.70781799e-02],
         [ 6.29068464e-02, -1.98459551e-02, -6.18472882e-02, ...,
          -2.84208190e-02,  7.33274370e-02,  2.90742796e-02],
         [-4.21718545e-02, -4.30155657e-02,  6.34044409e-02, ...,
          -5.73269427e-02, -1.77303273e-02,  2.91094696e-03],
         ...,
         [-3.15778628e-02,  7.37906946e-03, -5.55096529e-02, ...,
          -5.21995034e-03, -2.80752946e-02,  1.81950815e-02],
         [ 5.23881130e-02,  3.42121418e-03,  7.27736903e-03, ...,
          -2.84010451e-02,  2.99191661e-02,  6.38680160e-02],
         [-2.56351363e-02,  4.82285060e-02,  1.59610175e-02, ...,
           5.58155179e-02, -6.71083853e-02, -1.31441494e-02]],

        [[-4.58065346e-02,  2.77094114e-05,  6.21708706e-02, ...,
           2.91635450e-02, -9.39025357e-03,  3.19925323e-02],
         [ 3.89060490e-02,  2.02480834e-02,  1.95710789e-02, ...,
           2.75029447e-02,  1.66831110e-02, -6.58052266e-02],
         [ 1.62089721e-03, -1.06302258e-02,  5.10208420e-02, ...,
           1.20900683e-02, -1.68778133e-02, -2.00702976e-02],
         ...,
         [ 3.52701917e-02, -2.32332349e-02,  2.15637144e-02, ...,
           7.52046565e-03, -5.17121777e-02, -1.25609618e-02],
         [ 5.94049357e-02, -4.69723567e-02,  4.30062413e-02, ...,
           7.82746635e-03, -2.33213492e-02, -5.44253290e-02],
         [ 3.59411091e-02,  2.52719764e-02, -3.98942195e-02, ...,
          -3.46864089e-02, -1.88346468e-02, -7.91695621e-03]],

        [[-7.15118721e-02,  5.44695631e-02, -2.92208754e-02, ...,
           4.64865901e-02,  5.23358546e-02,  6.61645830e-02],
         [-3.74570899e-02, -7.08604380e-02, -1.37579348e-02, ...,
           1.95917338e-02,  3.41651253e-02,  3.91012207e-02],
         [ 2.62872558e-02,  2.12506820e-02, -2.44559012e-02, ...,
           3.40749300e-03,  3.77555862e-02,  5.46685420e-02],
         ...,
         [ 3.73399071e-02, -2.85915863e-02,  8.25689360e-03, ...,
          -2.98779383e-02,  2.78610103e-02, -1.22772427e-02],
         [-4.95667234e-02,  4.66338685e-03,  8.40453990e-03, ...,
          -2.51373518e-02,  3.65209468e-02,  1.48890428e-02],
         [ 3.80227007e-02, -3.24459970e-02, -5.93220396e-03, ...,
          -5.91501333e-02, -8.90563801e-03, -2.01010574e-02]]],


       [[[-1.73016209e-02, -4.20384342e-03,  2.12101191e-02, ...,
          -4.61068451e-02, -1.41608203e-02,  3.13695297e-02],
         [-6.52730558e-03,  1.28252618e-03, -5.88332005e-02, ...,
           1.26005039e-02,  4.72002588e-02,  1.46586904e-02],
         [-1.49796763e-02,  6.27125576e-02,  7.63076395e-02, ...,
          -6.02612272e-02,  3.89478616e-02,  5.49158752e-02],
         ...,
         [-3.12677175e-02, -4.53891531e-02, -5.47048822e-02, ...,
          -1.42049714e-04, -2.68158149e-02, -5.76007962e-02],
         [-9.41529125e-03, -6.83833584e-02,  2.42668688e-02, ...,
          -4.63743648e-03, -3.35162804e-02,  4.93339971e-02],
         [-2.80490499e-02,  4.37914692e-02, -2.61962488e-02, ...,
          -4.54530679e-02, -4.99078259e-02,  2.90774181e-02]],

        [[-4.57430258e-02,  3.32796052e-02,  2.30415650e-02, ...,
          -7.28467596e-04,  2.48156320e-02, -3.28849889e-02],
         [ 1.05793951e-02, -6.91614449e-02,  3.75915202e-03, ...,
          -6.95742890e-02,  6.12139851e-02, -5.63501306e-02],
         [-5.90546243e-02, -1.68610383e-02, -1.86091487e-03, ...,
          -2.36413237e-02, -2.60738861e-02, -9.73314047e-03],
         ...,
         [ 4.45922501e-02,  4.50310186e-02, -4.12384570e-02, ...,
          -5.23609901e-03, -2.83874813e-02, -1.34949405e-02],
         [ 3.55510972e-02, -1.97989326e-02, -3.60406078e-02, ...,
          -2.84386557e-02,  1.52574684e-02,  5.82837907e-04],
         [ 4.54573054e-03, -1.97612420e-02, -6.52094558e-02, ...,
          -3.30577530e-02, -5.30101657e-02, -3.77980247e-02]],

        [[-7.20675811e-02,  5.32772802e-02,  8.16255156e-03, ...,
           1.88779775e-02,  2.12606248e-02, -1.34471552e-02],
         [ 4.43253741e-02,  1.69991925e-02,  9.83628072e-03, ...,
          -2.96506882e-02, -2.61443872e-02, -6.27575964e-02],
         [ 7.94721860e-03,  4.14173380e-02,  5.45861982e-02, ...,
           4.48509790e-02,  5.10872602e-02, -6.48927968e-03],
         ...,
         [-3.24430689e-02, -4.55938019e-02,  1.19067531e-03, ...,
          -3.41354422e-02,  2.86302641e-02, -2.05757115e-02],
         [ 5.85169941e-02, -1.76199637e-02,  1.61163956e-02, ...,
          -7.81415869e-03,  5.36577078e-03, -2.42290962e-02],
         [-3.31159681e-02,  1.44710960e-02,  7.15196831e-03, ...,
          -5.32206818e-02,  6.03904063e-03, -2.97848657e-02]]],


       [[[-2.06979010e-02,  4.84083369e-02, -1.13947596e-02, ...,
          -5.47845848e-03, -1.66856032e-02, -7.66674115e-04],
         [-1.63653214e-02, -4.82102484e-02, -3.58593315e-02, ...,
          -5.01549505e-02, -1.36607829e-02, -4.93649170e-02],
         [-4.83491868e-02,  6.02684394e-02, -2.62980722e-02, ...,
          -1.43697727e-02, -4.59328443e-02,  2.50897761e-02],
         ...,
         [-5.28271236e-02,  4.08995040e-02,  3.71398255e-02, ...,
          -3.67336906e-03,  3.30570638e-02, -4.90236878e-02],
         [ 1.60628352e-02, -8.05468392e-03, -2.60120425e-02, ...,
           7.62462616e-03, -7.44982734e-02,  7.63798133e-04],
         [ 1.10794120e-02,  1.23015558e-02, -3.64954881e-02, ...,
          -2.38922220e-02, -5.51668294e-02,  1.97977619e-03]],

        [[ 5.84072666e-03,  1.70866344e-02, -3.08984779e-02, ...,
           4.12873290e-02,  2.08653715e-02,  1.88162271e-02],
         [-1.35694956e-02, -2.32336912e-02,  2.77549773e-03, ...,
          -1.58516094e-02,  3.19156870e-02, -8.49321019e-04],
         [ 3.77693237e-03,  2.86709405e-02, -2.86735967e-02, ...,
           5.10301143e-02,  4.70298789e-02,  1.42183686e-02],
         ...,
         [-6.29958212e-02,  1.42511977e-02, -1.00941909e-02, ...,
          -7.52599165e-03,  1.56392362e-02, -6.27338588e-02],
         [ 1.99467372e-02, -5.74631244e-02, -2.92554535e-02, ...,
           5.18711656e-02, -6.01579547e-02,  3.22947651e-02],
         [-2.22219024e-02,  1.03943106e-02, -6.29018247e-02, ...,
           5.37658185e-02, -3.99260893e-02,  2.08086264e-03]],

        [[-6.18302776e-03, -1.43601447e-02,  2.14263871e-02, ...,
           5.41807199e-03,  2.96818428e-02,  5.64225465e-02],
         [ 5.15155233e-02, -1.26845874e-02, -6.42548129e-02, ...,
          -2.13144422e-02,  7.44160116e-02, -6.95015788e-02],
         [-3.97026613e-02,  5.19864634e-02,  4.66804355e-02, ...,
           5.13556562e-02, -3.34707126e-02, -4.36516181e-02],
         ...,
         [-2.31549833e-02, -3.95214632e-02, -1.97834633e-02, ...,
           4.72207740e-02,  5.22748986e-03,  4.82805222e-02],
         [ 3.01073585e-02, -3.59937549e-02,  1.50928842e-02, ...,
           1.35445260e-02, -3.40438597e-02,  3.47096361e-02],
         [ 2.20809411e-02, -1.84915792e-02, -5.45556806e-02, ...,
          -4.46601845e-02, -5.53472713e-02, -3.60698067e-02]]]],
      dtype=float32), array([[[[ 0.12638901,  0.08278713, -0.05288061, ..., -0.03346991,
          -0.12055292, -0.01002239],
         [ 0.14400685,  0.01339518, -0.09304351, ..., -0.08871158,
          -0.02237707, -0.05519647],
         [-0.08954636,  0.00025307,  0.01300872, ..., -0.02308965,
           0.07312483, -0.08782   ],
         ...,
         [ 0.01574167, -0.12940046,  0.04634029, ...,  0.00832403,
          -0.05203124, -0.07926872],
         [ 0.0189287 ,  0.05171664, -0.00401747, ..., -0.11949746,
          -0.00336443,  0.11357749],
         [-0.05013129, -0.11105043, -0.06227851, ..., -0.02174212,
           0.001661  ,  0.10086297]]]], dtype=float32), array([ 0.01488045,  0.00309379,  0.01131141,  0.01912007, -0.00048476,
       -0.01004308,  0.00722859, -0.01179169, -0.00135006,  0.00701265,
        0.00790805, -0.00211727, -0.01342337, -0.01326692, -0.00501932,
        0.00154262, -0.00124299, -0.00274784, -0.0079072 ,  0.0031628 ,
       -0.01694634,  0.0124876 , -0.01113864, -0.00067953,  0.00146477,
       -0.00989718, -0.01298434, -0.01727626,  0.00549752, -0.00113568,
       -0.00315687,  0.00409093,  0.01182476, -0.01424825, -0.00334385,
        0.00213958, -0.00201524,  0.00044546,  0.00838858,  0.00082356,
       -0.00542879, -0.00211324,  0.01574268, -0.01817031,  0.01105316,
        0.0020214 , -0.00272095, -0.00794042,  0.00037836, -0.00446434,
       -0.01103386, -0.01112097, -0.00972466,  0.0060716 ,  0.02031785,
       -0.02669952, -0.00130192,  0.0063237 ,  0.01600126, -0.00357852,
        0.00789494, -0.00352093,  0.00350494,  0.00875565], dtype=float32), array([-2.5253725e-01, -5.5691785e-01,  1.4739563e-01, -1.2478694e-01,
       -2.1758944e-01,  1.2294303e-01, -6.2961853e-01,  6.4079916e-01,
       -2.1430220e-01,  2.0882504e-02,  1.4864235e-01,  3.5962957e-01,
        1.2278764e+00, -4.3682247e-01,  3.2988912e-01,  4.2045557e-01,
       -3.7394652e-01,  2.5672287e-01,  8.0595404e-01,  3.8104340e-01,
        4.7299922e-02, -3.5057920e-01, -2.2331913e-01, -6.9985658e-01,
        8.2185590e-01,  6.6460639e-01,  2.8751335e-01,  1.0622090e-03,
       -8.8279799e-02,  4.2643076e-01, -3.8245562e-01,  5.8659381e-01,
        1.2823202e-01,  9.2434043e-01,  4.4278818e-01, -3.8655274e-02,
        7.8304493e-01,  4.3692055e-01,  1.5297274e-01, -1.0141964e+00,
       -3.4779671e-01, -1.0850772e+00, -2.0096299e-01,  6.2462157e-01,
        4.0548494e-01,  3.3469158e-01, -1.4911066e-01, -1.0024933e-01,
       -3.3404300e-01,  5.0558454e-01, -5.5437982e-01, -2.5641978e-01,
       -4.2540374e-01,  2.4617344e-01,  5.7470642e-02,  7.3836523e-01,
       -1.6612098e-01,  1.4201286e+00, -1.2692907e-02,  8.9648567e-02,
        8.0393635e-02,  4.6528453e-01,  2.0362589e-01, -7.0678723e-01],
      dtype=float32), array([1.1108272 , 1.1929108 , 1.1813279 , 0.7862308 , 2.1921544 ,
       0.968306  , 1.8684299 , 1.3287425 , 0.78119516, 1.0926495 ,
       1.8418069 , 1.2917013 , 1.3055527 , 0.41248694, 1.0587866 ,
       1.3383135 , 0.8423614 , 1.4537824 , 0.95139956, 1.1823679 ,
       0.96802926, 1.120507  , 0.90572584, 0.64575756, 1.2277693 ,
       0.9526047 , 0.87652695, 1.0365295 , 0.7860091 , 2.2908192 ,
       0.54917294, 1.2498482 , 0.91400874, 2.209525  , 0.9720725 ,
       0.60170007, 1.3647207 , 0.75241876, 1.4538103 , 1.3442793 ,
       0.6303922 , 1.1955496 , 0.89357066, 1.3119789 , 1.3818393 ,
       1.036211  , 1.4282721 , 0.61062306, 0.541077  , 2.3939424 ,
       0.7473474 , 0.61808074, 0.80743724, 1.2459325 , 0.72193134,
       1.3376019 , 0.7044717 , 1.2478901 , 0.6056467 , 1.5937525 ,
       1.1599002 , 1.7067533 , 0.7038634 , 1.5168113 ], dtype=float32), array([-0.00722733, -0.00554084,  0.00940467, -0.00378934, -0.00677965,
        0.00017874, -0.01776645,  0.00212995, -0.00178991, -0.01021492,
        0.01198696, -0.00547515,  0.00094278,  0.00223764,  0.00756892,
       -0.00266338, -0.01594997,  0.01748425,  0.00875255,  0.02111607,
       -0.00272364, -0.00501792,  0.01497484, -0.00478177, -0.01412458,
       -0.00251933, -0.01256213, -0.00143381,  0.00807221, -0.00147566,
       -0.00482014,  0.01210519,  0.00600746, -0.00265146,  0.01012189,
       -0.02761186, -0.0016182 , -0.00790102,  0.01626847, -0.0100522 ,
        0.0084833 ,  0.02913709,  0.00516221,  0.01310917,  0.00526377,
       -0.00540539, -0.01234125,  0.00357821,  0.01210433,  0.00479775,
       -0.01032856,  0.00228914, -0.00686974, -0.00176685,  0.0001784 ,
       -0.00203001, -0.00659671, -0.00817087, -0.00666853, -0.02096973,
        0.0160341 ,  0.02153973, -0.00444048,  0.00039672], dtype=float32), array([-1.3505672 ,  0.6568613 , -1.581635  , -0.34790477, -0.10268632,
        0.31618795, -1.1937424 ,  1.6989102 ,  0.37455636, -2.2768936 ,
        0.77826536,  1.7640195 ,  0.74682975, -0.47902107,  0.10523523,
       -1.1718755 ,  0.4317425 ,  1.0489    ,  1.0910424 , -1.1054479 ,
       -0.63402635,  1.4702103 ,  0.66637486,  0.51793677, -1.1895754 ,
       -0.07342625,  0.29947278,  0.91517603, -0.6113281 , -0.07573622,
        1.0164506 , -2.514706  , -0.84482306, -1.1085439 ,  1.1908716 ,
        1.2259294 ,  0.28985754,  1.0698891 ,  0.37851846, -1.2022343 ,
        1.2054989 , -1.1745348 ,  0.510786  ,  0.39886028, -1.2541382 ,
       -1.2491407 ,  1.7751034 ,  1.4792285 , -0.23210916,  0.4635776 ,
       -1.2060146 ,  0.8621446 ,  0.02634254, -1.4929761 ,  1.0378169 ,
        0.56462723, -1.7749509 ,  1.9376491 , -2.048039  ,  0.9171035 ,
        0.3933166 , -1.1107628 ,  0.9850415 ,  0.6335898 ], dtype=float32), array([4.0324225, 2.145726 , 5.800053 , 2.6544154, 2.6739495, 3.9168282,
       3.4617817, 4.7769995, 3.6839082, 7.4127526, 1.6528922, 2.5039203,
       2.3018177, 1.9613467, 1.3926835, 2.9544916, 2.9288359, 2.4776585,
       2.3556128, 3.1626225, 2.8827407, 3.6537282, 5.718974 , 2.3245602,
       2.9186187, 1.3182737, 3.3171782, 3.3392766, 4.8363247, 1.7154773,
       2.316615 , 4.172863 , 2.1405566, 2.7522416, 3.3204327, 5.564204 ,
       3.9756253, 3.0846894, 2.0569265, 4.104618 , 3.6184778, 1.8987192,
       3.9624107, 2.9978285, 2.7079666, 2.6695673, 3.0511217, 3.436073 ,
       2.3525074, 2.8945663, 6.607631 , 1.5731308, 4.6383443, 5.102168 ,
       2.8775067, 3.6640232, 4.6712637, 3.4928129, 7.1328516, 2.2614136,
       4.3516736, 3.7733335, 2.3801372, 3.6024427], dtype=float32), array([ 0.00153806,  0.00933933,  0.00560339, -0.00181371, -0.00397309,
        0.00982707,  0.00183517,  0.00947577, -0.0015751 , -0.00194299,
       -0.00458046, -0.00809664,  0.01629603,  0.00052118, -0.00508192,
        0.01403878,  0.01152206,  0.01377002,  0.01128756,  0.00438838,
       -0.01246218,  0.0157262 , -0.00656288, -0.00737786,  0.01411404,
        0.0086059 ,  0.02798407,  0.01310564,  0.01063345, -0.01963525,
        0.00896326, -0.00915505, -0.00831761, -0.00961141,  0.00398905,
        0.00908884,  0.01962581,  0.01054517,  0.01537697,  0.00140244,
        0.01675735, -0.01659342, -0.00400468, -0.00979806, -0.02559764,
       -0.00508836, -0.00182817, -0.0029615 ,  0.01853959, -0.00412122,
        0.00077232,  0.01836357,  0.00591183,  0.01434183,  0.01080238,
        0.01118194,  0.01179729,  0.00478086, -0.00084324,  0.01075686,
       -0.01022608, -0.00614704,  0.01187756,  0.00589056,  0.00042446,
        0.01097405, -0.01240253,  0.00289479, -0.01621856, -0.00517597,
       -0.02307903,  0.01334742,  0.00755276, -0.0074879 ,  0.00332259,
       -0.03312636, -0.01388904, -0.01143727, -0.00201036, -0.00113575,
       -0.01016982,  0.00195642,  0.03321679, -0.01842018, -0.00706203,
        0.00488613,  0.01909155, -0.00309989,  0.0117323 ,  0.00440856,
        0.00669447, -0.02263082, -0.00668521,  0.01555274, -0.00304589,
       -0.00653293], dtype=float32), array([-0.9580608 , -0.40623108,  0.41175523,  0.856427  ,  1.5888927 ,
       -1.4055007 , -0.44825456,  0.7350334 , -1.4981889 ,  0.6908544 ,
       -0.3278874 ,  0.8182173 , -1.4954742 , -0.6907555 ,  0.8708924 ,
       -0.5199488 , -1.4547602 ,  0.00813455, -1.0767707 , -0.50187004,
        0.6133289 , -0.72262746,  0.11027349,  0.48696926,  0.34467977,
       -0.08840107, -0.9643394 ,  0.33409268,  0.50765496, -0.52809936,
        0.12919794,  0.17482008, -0.07929652,  0.72961724,  1.0393035 ,
        0.29544833, -0.04812159,  0.65721995, -0.41387117,  0.18152753,
       -1.0360997 , -0.13868304, -0.54395527,  0.11351533,  0.17577313,
        0.09940015, -0.96969885, -0.61758196, -1.3139514 ,  0.46440834,
       -0.5809383 , -0.04176372, -0.6954375 , -0.58988744, -0.9546077 ,
        0.46152997, -0.3137837 , -1.2825534 , -0.9625601 ,  0.3415887 ,
        0.21296792, -1.2582027 ,  1.0772552 , -1.3881307 ,  0.4745825 ,
       -0.2614351 , -1.1322451 ,  0.17988962,  0.3495516 ,  0.40673223,
        1.1830956 , -0.29601142, -0.90919477,  0.45351383, -0.5312143 ,
       -0.3797036 ,  0.9456234 , -0.2757061 ,  0.12495768,  0.5251129 ,
       -0.43315884, -0.97142386, -0.90812635, -0.922795  ,  1.053499  ,
        1.015932  , -1.7182225 , -0.7538738 ,  0.4751967 ,  0.56045425,
       -0.84911937, -0.44503117,  1.2320447 , -0.50596654, -0.62644553,
        0.5746785 ], dtype=float32), array([3.0810602, 1.6727648, 3.2871501, 2.6631093, 4.5667176, 3.49064  ,
       3.0248268, 1.2281194, 6.297634 , 1.7958399, 2.8235285, 3.1503878,
       1.8186884, 1.1669122, 2.947576 , 4.045572 , 4.5680537, 2.2966776,
       1.6676362, 2.8895452, 3.2728927, 1.8207846, 2.2875514, 3.071289 ,
       1.2311167, 2.3934803, 3.246254 , 2.286227 , 1.4307461, 1.9112239,
       1.5204755, 1.7231327, 1.4265672, 1.6626512, 2.5822694, 3.0538645,
       2.2703524, 1.9409871, 3.2713528, 2.2886698, 2.3727977, 3.5576282,
       2.4052079, 2.0243306, 2.2301419, 3.885793 , 2.4184008, 2.2526672,
       4.815644 , 2.092349 , 2.228569 , 3.0741057, 2.1405644, 2.7923062,
       2.132222 , 3.2668183, 1.5277747, 5.1474757, 1.0039538, 1.8749744,
       1.3707685, 3.023023 , 5.1071815, 6.477687 , 2.0418286, 2.2998657,
       3.4247754, 1.474275 , 1.4689525, 1.8440586, 2.6491823, 2.0358324,
       4.612796 , 1.6305641, 3.219124 , 0.9209684, 2.82776  , 1.5127481,
       1.1534402, 3.2790434, 3.3373065, 2.774658 , 3.2695346, 2.4321213,
       4.1874905, 2.7130027, 5.326851 , 2.0769148, 4.2148576, 2.247161 ,
       2.022913 , 3.8773816, 3.6933753, 1.9971237, 2.9660475, 3.1340685],
      dtype=float32), array([-0.00078388,  0.01080384, -0.00082887, -0.00580466,  0.00197834,
        0.00388366, -0.00608007,  0.00102937,  0.00521214,  0.00775028,
       -0.01599124,  0.01825891,  0.00405621, -0.00018206,  0.00627375,
        0.00222379, -0.00117633,  0.00378316, -0.01160683, -0.00846104,
        0.00198081, -0.00181324, -0.008193  ,  0.00818287, -0.01042478,
        0.00711168,  0.00259362, -0.01906691, -0.00422728, -0.00144107,
        0.00830406,  0.02226114,  0.01223194,  0.00712822, -0.00957373,
       -0.00364366,  0.01046067, -0.01198027,  0.00341325, -0.00844843,
       -0.00140493, -0.00461359, -0.0026786 , -0.02214022, -0.00977383,
        0.00769133, -0.01492216, -0.03189167,  0.00110776, -0.0008025 ,
       -0.00855486,  0.02141154,  0.00373626, -0.01878112,  0.02313099,
       -0.00018144, -0.00057426, -0.00414296, -0.00326148, -0.00710818,
       -0.0008817 , -0.00665455, -0.01419123,  0.00325443], dtype=float32), array([-0.00904519,  0.39869025,  0.44524094,  0.46423852,  0.3610732 ,
        0.22036478,  1.1011746 , -0.06417393,  0.06900637, -0.01042785,
       -0.55871075,  0.6904671 , -0.07217358, -0.01002158,  0.18033884,
        0.26109654,  0.21006608,  0.7823261 ,  0.09723539, -0.19738898,
        0.636862  ,  0.34717804, -0.14133058, -0.4100217 ,  0.7211495 ,
        0.04712128, -0.10142361,  0.19625303,  0.78837556,  0.02709152,
        0.4934382 ,  0.13651106, -0.608015  ,  1.0742614 ,  0.79590434,
        0.30048218, -0.3622903 ,  0.50197065, -0.15836054, -0.06962064,
        0.3927592 ,  0.3303341 ,  0.3128328 , -0.25539044, -0.2534367 ,
       -0.7138014 ,  0.7124401 ,  0.9625728 , -0.63508636,  0.4783315 ,
       -0.4807872 ,  0.21494232,  0.39531013, -0.2337423 , -0.13513754,
       -0.65075916,  0.0600479 , -0.51017165, -0.38630548, -0.37758076,
        0.1115677 , -0.0877964 ,  0.11954418,  0.02213395], dtype=float32), array([0.63396347, 0.92419916, 0.91362697, 0.73524404, 0.85637414,
       0.57945514, 1.2350476 , 0.6496903 , 1.1496814 , 0.93185693,
       1.0305233 , 1.0777501 , 0.7828051 , 1.8748796 , 0.7272705 ,
       1.1935514 , 0.6860487 , 0.88493633, 1.2785965 , 0.8499353 ,
       0.67149323, 0.5599704 , 1.6028438 , 0.8787406 , 1.1300497 ,
       0.8113383 , 0.94450027, 2.1404076 , 3.549455  , 0.9299505 ,
       1.0313036 , 1.0373147 , 1.2088181 , 1.4706    , 1.2259188 ,
       0.9286179 , 1.0565661 , 1.4586363 , 0.82501084, 0.8956916 ,
       0.89389837, 1.6094292 , 2.135452  , 0.44589168, 1.2472216 ,
       0.6546125 , 1.0264504 , 1.1370133 , 1.0855795 , 2.1142552 ,
       1.3237376 , 1.0485225 , 0.95123655, 0.7235829 , 1.6715236 ,
       1.0419015 , 1.3879665 , 0.42692834, 0.37827146, 0.9164849 ,
       0.5705684 , 1.6556025 , 0.51602423, 0.93488425], dtype=float32), array([[[[-0.05381145,  0.07593578,  0.10045889, ..., -0.08520164,
           0.03141291,  0.13359657],
         [ 0.04904911,  0.11719064, -0.06607068, ..., -0.00619545,
          -0.02521892,  0.10551534],
         [ 0.05355605,  0.08030677, -0.02507797, ...,  0.09854757,
           0.05322963, -0.1045491 ],
         ...,
         [-0.05581024,  0.06369302,  0.03979419, ...,  0.12698378,
          -0.02678489, -0.06967616],
         [-0.00724335,  0.04411307,  0.06380416, ..., -0.12020293,
           0.00913785, -0.11618991],
         [ 0.10713967,  0.01298264,  0.09904962, ...,  0.09492885,
          -0.05836711, -0.06940843]]]], dtype=float32), array([-1.04653481e-02, -3.92296817e-03,  4.69095467e-05, -2.66499110e-02,
       -9.13044997e-03, -1.15746530e-02, -2.69782376e-02,  1.29625099e-02,
        1.11703118e-02,  6.24898262e-03,  1.32866725e-02, -9.68922488e-03,
       -2.10896190e-02,  1.08187096e-02,  2.51195468e-02, -1.26335593e-02,
        1.26420206e-03,  1.22827124e-02,  8.77971202e-03,  3.68748815e-03,
       -2.97815818e-03,  2.14109686e-03, -4.76402557e-03, -1.40024191e-02,
        2.53599733e-02, -8.01524427e-03, -1.29476562e-03, -6.60443585e-03,
       -2.10387725e-03,  1.73836350e-02, -6.50096824e-03,  5.90821169e-03,
       -2.46805581e-03,  7.67663354e-04,  1.43245533e-02,  3.34961107e-03,
        9.80537334e-06, -5.22071845e-04, -1.90202333e-02,  1.41943963e-02,
        1.05582876e-02,  5.33769140e-04, -1.77909015e-03, -8.89860000e-03,
        1.89099996e-03,  7.85422698e-03, -1.64026562e-02,  1.37179568e-02,
        9.43718292e-03, -5.08333603e-03,  1.01841651e-02, -3.79742170e-03,
       -1.98175339e-03, -1.06038386e-02,  1.19427210e-02, -2.77495459e-02,
       -7.19574094e-03,  5.67084062e-04, -5.83619159e-03,  7.43214227e-03,
       -1.20699434e-02, -2.38493411e-03, -1.03992838e-02, -3.91018251e-03],
      dtype=float32), array([ 2.05753252e-01, -3.13617349e-01, -2.48455837e-01,  3.48544300e-01,
       -7.10135281e-01,  1.38565850e+00,  5.80846906e-01, -6.09808080e-02,
        9.27194417e-01,  8.80215645e-01,  1.53467387e-01,  1.26012433e-02,
        2.19167426e-01, -1.45086110e-01,  1.30166277e-01, -2.27207914e-02,
        5.00632226e-01, -2.16808721e-01,  3.68482560e-01,  2.65048206e-01,
       -5.06742656e-01,  2.65513122e-01,  5.79635352e-02,  9.78914648e-02,
       -3.93641442e-02,  3.43309522e-01,  1.54724956e-01,  3.64216775e-01,
        1.44039229e-01, -5.18785834e-01, -4.39760759e-02,  1.11212306e-01,
        6.84075177e-01, -1.71845901e+00, -7.46332049e-01,  3.45066946e-04,
        4.30972517e-01, -2.64184505e-01,  1.08703864e+00, -3.05539697e-01,
        6.50345564e-01,  3.09402943e-01,  1.33584052e-01,  3.37175190e-01,
       -7.43621051e-01, -5.12415804e-02,  8.94486368e-01, -1.83220476e-01,
        5.23866355e-01,  9.60581779e-01, -1.04170062e-01, -3.60923409e-02,
       -3.17785025e-01,  5.83935790e-02, -1.31512552e-01, -3.20608914e-02,
        2.72583276e-01,  6.01122439e-01, -1.30438256e+00,  6.60591945e-02,
        4.56149340e-01, -2.76307374e-01,  1.09924948e+00,  1.10055760e-01],
      dtype=float32), array([2.0224702 , 1.0637321 , 1.4084623 , 1.5192765 , 0.95368075,
       1.6331403 , 1.1471095 , 0.75467956, 3.8522282 , 3.1471343 ,
       1.7556146 , 0.8112591 , 1.3791201 , 1.6549481 , 0.9530972 ,
       1.8199552 , 1.0712496 , 0.9337101 , 2.2214248 , 0.8083399 ,
       2.5020099 , 2.2922282 , 1.3178971 , 1.1277313 , 1.1067271 ,
       1.6421522 , 0.88602996, 1.1357838 , 1.4465729 , 1.8527182 ,
       1.4172227 , 0.7698957 , 0.8561842 , 3.1078987 , 1.5371435 ,
       0.590958  , 1.5121586 , 1.1304269 , 1.7945629 , 1.1298265 ,
       1.3145807 , 1.4654754 , 0.9445628 , 2.445964  , 0.9507532 ,
       2.4617114 , 1.0694724 , 1.4312702 , 1.8609734 , 1.2385806 ,
       1.7706261 , 0.66196436, 1.2188025 , 1.3224788 , 0.4622312 ,
       1.6092125 , 0.7288029 , 1.3520341 , 1.7157383 , 2.322959  ,
       1.5085614 , 1.1506556 , 1.5979037 , 1.383304  ], dtype=float32), array([[[[ 0.11380679, -0.03039099, -0.03365157, ...,  0.03752302,
           0.10376433, -0.08357098],
         [-0.08857962, -0.01153788, -0.07589161, ...,  0.11303903,
           0.08597912, -0.04236776],
         [-0.10555932, -0.00202676, -0.02938136, ..., -0.04773821,
          -0.019972  , -0.05438723],
         ...,
         [-0.12631243, -0.0232346 , -0.04951085, ..., -0.10478799,
          -0.10288164,  0.10927853],
         [ 0.02101122,  0.00696224,  0.03543152, ..., -0.05811374,
           0.12043907,  0.10123482],
         [ 0.0103556 ,  0.05532002,  0.04115834, ..., -0.12506235,
          -0.01676116,  0.08499466]]]], dtype=float32), array([[[[-0.0284653 ,  0.01801787,  0.01450327, ...,  0.06715184,
           0.06342374, -0.03950668],
         [-0.05466099,  0.00096975, -0.03647104, ..., -0.01354652,
           0.00527045, -0.0204065 ],
         [-0.02095382, -0.01049839,  0.03643268, ..., -0.03985433,
          -0.02468675, -0.01653404],
         ...,
         [-0.05295649,  0.0012778 ,  0.00838531, ..., -0.04332983,
           0.03189571, -0.05842626],
         [ 0.02696506, -0.0267421 , -0.01811585, ..., -0.02779001,
          -0.02897331, -0.02525569],
         [-0.05620343,  0.03730746,  0.03815629, ..., -0.00824841,
          -0.03259083, -0.03245131]],

        [[ 0.04028843, -0.02105063, -0.05578239, ...,  0.04472777,
          -0.04364466,  0.00802179],
         [-0.00100919,  0.05580523, -0.01308148, ...,  0.02942328,
           0.03789023,  0.03012861],
         [ 0.01038219,  0.02235317, -0.00436286, ..., -0.010547  ,
          -0.04072918,  0.01264537],
         ...,
         [-0.02752145, -0.04209537,  0.03730357, ...,  0.02819446,
          -0.04097013,  0.00968672],
         [-0.07014041,  0.05913182,  0.05271152, ..., -0.04705771,
           0.00629851,  0.07456385],
         [ 0.03765187,  0.06454602, -0.01566962, ...,  0.00545401,
          -0.01746726, -0.01135377]],

        [[-0.0028362 , -0.0424536 , -0.01971885, ..., -0.01571463,
           0.00235792, -0.01585463],
         [-0.01248934,  0.05708652,  0.04636563, ..., -0.01262103,
          -0.02208886,  0.0058311 ],
         [ 0.06312691, -0.00171427, -0.00511201, ...,  0.03177603,
          -0.06091533, -0.00615676],
         ...,
         [ 0.04830566,  0.02874126, -0.0369381 , ...,  0.00610475,
           0.05600393, -0.02064207],
         [-0.02154298, -0.04347924,  0.07336088, ..., -0.04190672,
          -0.04589409,  0.01983038],
         [-0.0293865 ,  0.0669558 ,  0.01759022, ..., -0.05849978,
           0.00027577, -0.0663875 ]]],


       [[[-0.03253476,  0.02111439, -0.00511131, ...,  0.04511383,
           0.03855122,  0.02607272],
         [-0.02502438, -0.05224461,  0.00920574, ...,  0.01947673,
           0.01000174, -0.06036883],
         [ 0.00106582, -0.05296654,  0.02095845, ..., -0.00768153,
          -0.0202639 ,  0.0679717 ],
         ...,
         [ 0.04812427, -0.01348958, -0.03328561, ...,  0.05694408,
          -0.04201355,  0.03781092],
         [ 0.05876762,  0.0456203 , -0.02548007, ..., -0.00171712,
          -0.06939576, -0.05192274],
         [ 0.06036182,  0.0004535 , -0.01523932, ..., -0.06869578,
           0.01582788, -0.04043262]],

        [[ 0.02437562, -0.0255726 ,  0.02552791, ...,  0.03737896,
           0.04594853, -0.01299049],
         [ 0.05630837, -0.01973841, -0.04447452, ..., -0.01061426,
          -0.0244555 , -0.02832522],
         [-0.05678434,  0.06570374,  0.02045142, ..., -0.04511744,
           0.03441288,  0.00754999],
         ...,
         [ 0.05288151,  0.00360876,  0.0498784 , ..., -0.03446778,
          -0.04720448, -0.05213705],
         [-0.06106275,  0.01255883, -0.01084235, ...,  0.00703317,
           0.02596064,  0.02581263],
         [ 0.06153099, -0.0305757 ,  0.01463619, ..., -0.05393856,
          -0.02475054, -0.05648311]],

        [[-0.05036062, -0.00311799,  0.0814116 , ..., -0.02619154,
           0.03214382, -0.04748358],
         [-0.0711583 ,  0.038144  , -0.03145055, ...,  0.06392017,
           0.06155721,  0.05546157],
         [ 0.00608171,  0.03231883,  0.05616094, ..., -0.05474142,
          -0.01238178, -0.00477556],
         ...,
         [ 0.03776604,  0.03498788, -0.05166741, ...,  0.01053604,
           0.06268985, -0.01097747],
         [-0.00084392, -0.04273295,  0.051192  , ..., -0.06027091,
          -0.05085286,  0.00404909],
         [-0.02738349,  0.02804944, -0.0141559 , ..., -0.01279319,
          -0.05069708, -0.00659757]]],


       [[[-0.07373498,  0.02742117, -0.04228059, ...,  0.07094929,
           0.02332081,  0.01384969],
         [-0.04195402,  0.01498914,  0.00214288, ..., -0.02780719,
          -0.00498001, -0.04671153],
         [-0.05089724, -0.03410238, -0.0119698 , ..., -0.06377119,
           0.00521885, -0.05613266],
         ...,
         [ 0.03603171,  0.01812592, -0.03273587, ..., -0.04110068,
          -0.06942146, -0.00160523],
         [-0.06149164, -0.0408956 ,  0.01903049, ..., -0.02693875,
          -0.04440722, -0.02699561],
         [-0.03031024,  0.01329608, -0.04028571, ...,  0.04184524,
          -0.05201651, -0.06169949]],

        [[-0.06246179,  0.05617453,  0.07014642, ...,  0.04676811,
           0.00959652,  0.04178983],
         [-0.00718504,  0.01040882, -0.02152939, ...,  0.02426557,
           0.02985897,  0.05558902],
         [-0.02804884,  0.02521717, -0.00865649, ..., -0.05987101,
           0.02117992, -0.04016929],
         ...,
         [-0.05886745, -0.00877305, -0.01489735, ...,  0.03442956,
           0.0135875 , -0.04546682],
         [ 0.05345482,  0.05044232, -0.03256128, ..., -0.03796203,
           0.01529496,  0.00304561],
         [ 0.0108878 , -0.0044126 , -0.04979804, ..., -0.03050195,
          -0.04545376,  0.04814197]],

        [[-0.04413813,  0.01075858, -0.03264883, ...,  0.04283842,
          -0.0542336 ,  0.04180442],
         [ 0.03538573, -0.01096413,  0.01110335, ...,  0.06624984,
          -0.03553622, -0.04058286],
         [ 0.00136042, -0.03582755, -0.0063357 , ...,  0.00254536,
          -0.0672347 , -0.01019687],
         ...,
         [-0.05251132, -0.0035332 , -0.04405038, ..., -0.02515376,
           0.00056839,  0.02022022],
         [-0.05478901, -0.00706932, -0.04510396, ...,  0.00316311,
           0.02915467,  0.06440974],
         [-0.00202012,  0.01001761, -0.0692215 , ...,  0.06995457,
          -0.03760136,  0.00594684]]]], dtype=float32), array([ 1.12600671e-02, -2.68014637e-03,  1.23621395e-03,  8.35280027e-03,
       -8.12724140e-03, -7.37299072e-03,  8.37658648e-04,  6.21639751e-03,
       -2.49269158e-02, -2.19141111e-05, -2.03752108e-02, -2.39075650e-03,
       -2.69755954e-03,  5.62904030e-03,  4.26359056e-03,  6.36928435e-03,
       -1.86374728e-02,  1.21942284e-02, -1.56693831e-02,  1.70714885e-03,
       -8.02155584e-03, -9.06067376e-04, -2.13503139e-03,  1.61803588e-02,
        6.74769617e-05,  1.51272062e-02,  1.28516322e-02, -9.10331868e-03,
        3.82020790e-03,  3.01488931e-03,  3.00451589e-04,  2.07800288e-02,
       -5.16820280e-03, -1.27798552e-02, -1.37201569e-03,  5.75113529e-03,
       -6.60823286e-03, -1.57502797e-02,  1.15392851e-02,  1.60957500e-02,
        1.39663825e-02, -1.21078975e-02, -2.41479874e-02, -8.46313871e-03,
        1.20917140e-02,  1.81173552e-02, -3.88484308e-03,  4.91877692e-03],
      dtype=float32), array([ 0.01585699,  0.20021251, -0.9514426 , -0.04637419,  0.40713137,
       -0.8661814 ,  0.03125248, -0.83968467, -1.2257231 , -0.06739035,
        0.21060117, -0.02708617,  0.02348306, -0.2920153 , -0.2933043 ,
        0.6889892 ,  0.14175816, -0.10243574,  0.6109196 ,  0.70829594,
        0.16018713, -0.60674626, -0.38049075,  0.31791544, -0.70633495,
       -0.11714807, -0.35992193,  0.03164398,  0.23454267, -0.37897623,
       -0.30168065,  0.05893605, -0.5817766 , -0.22419626,  0.4302457 ,
        0.28811362,  0.36438432, -0.2372568 , -0.30590567,  0.81626   ,
        0.10624566, -0.86105597,  0.0971076 , -0.03359209,  0.09861335,
       -0.11272763,  0.59189004,  0.21190183], dtype=float32), array([0.5531409 , 0.6727783 , 3.0827959 , 0.87776494, 1.2631387 ,
       2.4888914 , 2.3019624 , 1.8714703 , 2.2857442 , 1.8466884 ,
       1.7391992 , 0.5820997 , 0.9744468 , 1.5863681 , 1.3012456 ,
       1.423714  , 1.4684037 , 2.0617037 , 2.3651233 , 0.778117  ,
       0.30836672, 2.0637882 , 1.2159175 , 1.012754  , 1.9120969 ,
       1.3138732 , 1.1107421 , 2.0091586 , 1.993509  , 1.7065656 ,
       0.42095786, 1.1014445 , 1.2404208 , 1.3834574 , 2.2731154 ,
       1.7641735 , 0.61536914, 0.69639915, 0.9326193 , 1.017904  ,
       2.2236407 , 1.4700053 , 1.148869  , 1.1422528 , 1.1449579 ,
       1.2223328 , 2.4507217 , 0.9687863 ], dtype=float32), array([-2.15699263e-02,  1.47492429e-02, -1.47355786e-02, -1.16378367e-02,
       -1.06690433e-02, -5.34617156e-03,  2.48746248e-03, -6.93574315e-03,
       -5.04083233e-04,  4.05328628e-03,  5.24897780e-03, -9.91899706e-03,
       -8.21327604e-03,  2.97115021e-03, -5.47740189e-03, -8.69733375e-03,
        1.52652196e-04, -3.01531400e-03,  1.28845377e-02,  7.60533242e-03,
       -4.48172633e-03, -1.56129282e-02,  9.90442466e-03, -5.05542539e-06,
        1.50782773e-02, -6.95222057e-03,  1.12291370e-02, -1.13018434e-02,
        5.35632810e-03, -1.70923606e-03,  2.39519213e-04,  2.17777081e-02,
       -1.32280746e-02, -4.97633917e-03,  7.61226891e-03, -1.12971189e-02,
       -1.14214588e-02,  1.00665884e-02, -1.95505079e-02,  2.09028344e-03,
       -1.20584248e-02,  7.53875449e-03, -8.06431472e-03,  1.76604912e-02,
       -3.30959656e-03,  1.62724387e-02, -2.66331062e-02,  8.33657477e-03,
        1.98089294e-02, -1.04710357e-02, -8.09646118e-03,  2.30275746e-03,
       -2.96220672e-03,  3.70885246e-03, -8.21708981e-03,  5.41329663e-03,
       -2.20146440e-02, -1.41387265e-02,  1.32337473e-02,  2.14259159e-02,
       -8.49795062e-03, -8.85650329e-03,  1.09954104e-02,  1.51901543e-02,
       -6.77307881e-03, -1.24648074e-02,  1.63459610e-02, -1.42949875e-02,
       -5.80023834e-03,  7.79033871e-03, -6.15170132e-03,  2.38544354e-03,
       -1.07005890e-02, -1.83743332e-02,  3.31394672e-02,  6.59437571e-03,
       -1.62034128e-02,  1.90367457e-02,  2.48455396e-03,  1.93987098e-02,
       -1.79147795e-02, -2.53636185e-02, -3.51358694e-03, -3.43667157e-03,
        2.29082583e-03, -2.23854859e-03,  6.64070807e-03, -1.05386367e-02,
       -1.85523834e-02, -1.33392876e-02, -5.27645694e-03,  1.80092454e-02,
       -6.93332055e-04, -6.55702082e-04,  6.71308348e-03, -6.22600038e-03],
      dtype=float32), array([-0.67073077,  0.27721453,  1.1137145 ,  0.89583075, -0.12834248,
       -0.8940735 , -0.55815834, -0.13475208, -0.4302206 , -0.120129  ,
        0.09280766, -0.01089568,  0.28849772,  0.24998273, -0.5718004 ,
        0.8724493 , -0.61312616,  0.02289733,  0.27263835, -0.23614305,
        0.30635864, -0.22649789, -0.5540181 , -0.87000644, -0.39233187,
       -0.12865222, -0.8346498 ,  0.19972718, -0.09242587, -0.38074014,
        1.0882553 ,  0.15654598,  0.70235074, -0.32177272, -0.25104052,
       -0.22192869,  0.04703977, -0.47635737,  0.58117396,  0.14864591,
        1.0239685 ,  0.36099592, -0.07273634, -0.96664673,  0.19854777,
        0.47968617,  0.25176188,  0.18808497, -0.43041545, -0.40389648,
       -0.3143875 ,  0.66970056, -0.8026409 ,  0.3307287 , -0.39329183,
       -0.28768644,  0.16841643,  0.04782731, -0.7239171 , -0.60617596,
        0.09192287,  0.39723432, -0.12826207, -0.21379834,  0.8060896 ,
        0.77839535, -0.9907256 , -0.39979976,  0.00248405, -0.3429105 ,
       -0.15012337, -0.32094303,  0.3246187 , -0.11169522, -0.58378315,
       -0.20173348,  1.0637252 , -0.4921868 , -0.3789445 , -0.72153056,
        0.34436297,  0.5753115 ,  0.1384059 , -0.84289604, -0.8512164 ,
       -0.14847572, -0.52941525,  0.25099197,  0.4206338 ,  0.20772134,
        0.39879224,  0.2819187 ,  0.23495756, -0.05451597, -0.5358472 ,
       -0.06676961], dtype=float32), array([1.0557836 , 1.3963746 , 2.434844  , 1.3846407 , 1.3368514 ,
       1.9272575 , 0.65838224, 2.0860798 , 0.83702904, 0.6054961 ,
       1.6748867 , 0.810861  , 0.4384126 , 1.1352085 , 1.0751398 ,
       2.3981164 , 0.69952273, 1.0654106 , 1.6215    , 1.0561906 ,
       1.3541121 , 1.244415  , 4.3155026 , 0.8031191 , 0.6410043 ,
       0.86470795, 1.8322972 , 1.9489536 , 0.96327347, 0.91964626,
       1.7278701 , 0.93252826, 1.4605263 , 0.8089879 , 1.3751959 ,
       0.88259715, 1.2352188 , 1.3667587 , 1.5352614 , 0.8045789 ,
       1.3128059 , 0.6850227 , 1.1674021 , 1.147012  , 0.59179974,
       1.2176628 , 1.1100749 , 1.1270332 , 1.8682996 , 0.79603505,
       0.54794973, 1.0197959 , 1.772918  , 1.9348195 , 0.8015209 ,
       1.9482377 , 0.5391678 , 1.1725483 , 1.734326  , 1.0111525 ,
       1.6221824 , 0.789432  , 1.2850332 , 1.7388158 , 0.9077996 ,
       1.7914487 , 2.0344906 , 0.64237595, 1.38001   , 1.2294997 ,
       1.9773093 , 1.4464371 , 1.089132  , 0.6923738 , 1.0916132 ,
       1.374377  , 3.238881  , 1.7344842 , 1.9322634 , 1.3250192 ,
       1.0293883 , 0.91334146, 0.7733104 , 2.3884645 , 1.9868829 ,
       1.7139127 , 1.5499634 , 0.95069075, 2.4380577 , 1.8158863 ,
       1.1931359 , 1.4121925 , 0.55045676, 1.1411011 , 0.8674665 ,
       1.0486891 ], dtype=float32), array([[[[-0.06380302,  0.00184075,  0.03032494, ..., -0.00783665,
          -0.01335418,  0.00029231],
         [-0.10563863,  0.08060478, -0.12007315, ..., -0.0698345 ,
           0.0483918 , -0.02106535],
         [-0.05837553, -0.12908229, -0.09258375, ...,  0.04970656,
           0.09848713,  0.09070557],
         ...,
         [ 0.09406982,  0.08718684, -0.10860103, ...,  0.12356357,
          -0.02859766, -0.12153558],
         [ 0.02721598,  0.0997482 , -0.06582767, ...,  0.01191259,
           0.1066656 , -0.01279574],
         [ 0.08115087, -0.05223768, -0.03704285, ..., -0.0862627 ,
           0.02381632,  0.09799626]]]], dtype=float32), array([[[[-3.37064788e-02,  2.07595155e-02, -2.55084354e-02, ...,
          -2.38491837e-02,  2.12187078e-02,  3.84310856e-02],
         [-2.63131596e-02, -4.48045991e-02,  2.98395660e-03, ...,
          -4.32448499e-02, -6.09868672e-03,  4.13965527e-03],
         [ 3.47945988e-02, -2.90416665e-02,  1.38596306e-02, ...,
          -1.58192329e-02, -1.71571299e-02, -7.98827689e-03],
         ...,
         [-1.53715862e-02, -1.89192854e-02,  4.60108258e-02, ...,
          -1.46068037e-02, -5.14259785e-02,  1.00684643e-03],
         [ 1.28276637e-02, -3.89803760e-02, -6.85508421e-04, ...,
           1.25723034e-02, -3.26754451e-02, -5.65082440e-03],
         [ 5.64500913e-02,  6.28799200e-03,  1.57270990e-02, ...,
          -4.61190343e-02,  5.29237650e-03, -5.26609421e-02]],

        [[ 2.51116138e-02, -4.37538475e-02,  1.36387432e-02, ...,
           2.18717251e-02, -1.58354118e-02, -1.91257801e-02],
         [ 2.40343139e-02,  1.32105706e-04, -3.19395661e-02, ...,
          -5.09099476e-02,  4.91451891e-03,  1.11080296e-02],
         [ 7.19230808e-03, -2.09344290e-02,  2.30098236e-02, ...,
          -2.09730603e-02, -2.04520188e-02, -5.28672419e-04],
         ...,
         [ 2.42727827e-02,  3.98277417e-02, -3.61367734e-03, ...,
          -1.97165404e-02,  8.00833851e-03, -3.85763310e-02],
         [-3.81839685e-02,  1.17359916e-02,  1.97408162e-02, ...,
           6.75996812e-03, -2.41661984e-02, -2.14121956e-03],
         [-2.13176291e-02, -6.72632735e-03, -3.07788868e-02, ...,
          -2.52753105e-02, -4.31674831e-02, -3.21429521e-02]],

        [[ 1.83990058e-02,  3.87459435e-02,  9.69114155e-03, ...,
           7.67071918e-03,  2.90022604e-02,  3.60198156e-03],
         [-3.46440189e-02,  8.51299334e-03, -4.14167251e-03, ...,
          -3.81044894e-02,  4.21443880e-02,  3.18165869e-02],
         [-2.47167163e-02,  2.05756724e-03, -2.45111585e-02, ...,
           1.81970857e-02, -1.25259142e-02,  3.72412167e-02],
         ...,
         [-7.94143043e-03, -4.48416956e-02, -3.73567082e-02, ...,
          -3.99616510e-02, -5.25126187e-03, -2.77607143e-02],
         [ 5.16366549e-02,  2.19868384e-02, -2.52037309e-02, ...,
           1.64415371e-02,  3.06164473e-03, -4.40833485e-03],
         [-6.52404502e-03,  4.29573143e-03, -1.72487963e-02, ...,
           2.16450728e-02,  4.49886732e-02,  1.12151224e-02]],

        [[ 4.24104631e-02,  3.05262357e-02, -2.57697441e-02, ...,
           4.44470003e-04, -4.68293380e-04, -1.29643846e-02],
         [ 4.89200912e-02,  1.37510486e-02, -4.66394471e-03, ...,
          -3.11266873e-02, -1.91869363e-02, -3.24777253e-02],
         [-1.12193665e-02, -8.97285994e-03,  1.04127042e-02, ...,
          -2.28142012e-02,  1.27221327e-02, -3.41800600e-02],
         ...,
         [-1.89320091e-03,  5.54583920e-03, -4.40072175e-03, ...,
           3.86454985e-02, -8.11551325e-03, -3.24491374e-02],
         [ 3.91215598e-03, -5.06877042e-02,  1.39388943e-03, ...,
          -2.34063324e-02, -5.76048438e-03,  1.80053394e-02],
         [ 1.84462918e-03, -2.45894846e-02, -5.12685627e-02, ...,
          -3.69791873e-02, -2.19552591e-02, -3.62180099e-02]],

        [[-3.51891518e-02,  4.17298861e-02, -6.19154684e-02, ...,
           3.39261927e-02, -3.92225794e-02, -1.37320273e-02],
         [ 3.48379761e-02, -4.10851091e-02, -1.08341910e-02, ...,
          -4.59552370e-02,  4.62705642e-02, -6.27042120e-03],
         [ 1.59161258e-02, -2.41157133e-02,  4.02762182e-02, ...,
          -1.74004456e-03,  3.58041190e-02,  6.99926633e-04],
         ...,
         [ 6.70630671e-03,  8.92296992e-03,  1.99320652e-02, ...,
           3.00582573e-02,  1.64487632e-03, -2.19767559e-02],
         [ 6.99472008e-03, -1.23186111e-02,  1.88495927e-02, ...,
          -4.98467758e-02,  1.33707356e-02, -3.11395694e-02],
         [ 2.26141140e-02,  3.56831662e-02, -2.57726554e-02, ...,
           1.13529284e-02, -1.83504485e-02, -1.05333785e-02]]],


       [[[ 5.06485766e-03,  1.81154441e-02, -2.49040988e-03, ...,
          -2.39919331e-02,  4.39045811e-03,  8.80316645e-03],
         [-1.57954264e-02, -3.56998742e-02,  1.84967220e-02, ...,
          -1.99705083e-02,  8.41271784e-03,  2.39088666e-02],
         [-1.23869181e-02,  3.96081470e-02, -2.54183579e-02, ...,
          -5.35627417e-02,  3.14896442e-02, -4.86423373e-02],
         ...,
         [ 3.00909374e-02, -1.43046435e-02, -3.05118924e-03, ...,
          -1.28695173e-02, -6.68024644e-02, -1.60509739e-02],
         [-7.37808691e-03, -3.53632867e-02, -1.39397718e-02, ...,
           2.62458832e-03,  2.72778496e-02,  1.74481682e-02],
         [ 1.88633036e-02, -1.91487409e-02, -4.13499810e-02, ...,
           3.83166000e-02,  3.64745148e-02, -4.55274954e-02]],

        [[ 4.80522737e-02, -2.30397983e-03,  2.72550248e-02, ...,
           4.08479385e-02,  3.54815610e-02, -1.54604511e-02],
         [ 2.73524653e-02,  1.92367472e-02, -2.26039253e-02, ...,
           3.43309827e-02, -5.26840240e-03, -3.10119183e-04],
         [-1.33742169e-02,  1.63653698e-02,  1.29707726e-02, ...,
          -2.97715683e-02, -4.69121411e-02,  3.13350558e-02],
         ...,
         [-2.05983762e-02, -4.44115475e-02, -3.49662378e-02, ...,
          -2.29143556e-02,  2.77578328e-02, -4.82127890e-02],
         [-3.55228893e-02, -2.95791533e-02, -3.58186737e-02, ...,
          -1.95136387e-02, -4.29093800e-02, -3.78630566e-03],
         [-4.54761880e-03, -2.81136669e-02,  8.00115615e-03, ...,
           2.08487678e-02, -6.74246764e-03, -4.33238819e-02]],

        [[ 1.32843386e-02, -3.99520807e-03, -4.39493023e-02, ...,
           1.22850426e-02,  2.54893154e-02,  4.20938022e-02],
         [ 1.15942943e-03,  2.32613217e-02, -4.29993719e-02, ...,
          -2.84482539e-02,  2.09337026e-02,  2.44252738e-02],
         [ 7.87922833e-03,  4.37011421e-02,  3.14077064e-02, ...,
          -2.65186988e-02, -4.92934883e-02,  3.11335679e-02],
         ...,
         [-2.51960978e-02,  4.20440733e-02,  2.59633381e-02, ...,
          -3.46403867e-02, -3.38259749e-02, -1.42171290e-02],
         [ 3.65180410e-02,  1.31416870e-02, -2.38810405e-02, ...,
           2.22418760e-03,  4.23060134e-02, -6.88553322e-03],
         [ 7.42585165e-03, -1.36647485e-02,  6.56184927e-03, ...,
          -3.46439146e-02,  3.76323611e-02,  3.60917784e-02]],

        [[ 3.98227423e-02,  2.85539515e-02, -2.67754216e-03, ...,
           1.71041768e-02,  9.97662311e-04, -2.63845287e-02],
         [-1.79849211e-02,  8.64699949e-03,  5.04162610e-02, ...,
           1.99234765e-02,  1.64409410e-02,  3.78353782e-02],
         [-2.82572815e-03,  3.83741222e-02,  2.37906314e-02, ...,
           3.32388505e-02,  5.45298215e-03, -4.12200391e-03],
         ...,
         [ 2.68475655e-02,  3.06076673e-03,  2.41802111e-02, ...,
          -1.82800721e-02,  2.36849859e-02,  4.43907790e-02],
         [-3.90795842e-02, -1.36692403e-02, -4.11238447e-02, ...,
           4.64057690e-03, -1.31797453e-03, -2.20921133e-02],
         [ 5.30690141e-02, -3.51160914e-02, -4.90937904e-02, ...,
           4.73728664e-02,  1.56265050e-02, -2.29831953e-02]],

        [[ 1.69080794e-02, -8.75212811e-03,  1.39741302e-02, ...,
           6.20784517e-03, -1.35705471e-02, -1.49322497e-02],
         [ 3.89619544e-02, -2.29554866e-02,  2.66469605e-02, ...,
          -4.28865515e-02,  4.36366126e-02, -5.06417975e-02],
         [-2.29676291e-02, -5.67336055e-03,  9.70806181e-03, ...,
          -2.89295241e-02,  3.45860608e-02,  3.25778052e-02],
         ...,
         [-3.78423668e-02, -3.42070647e-02,  4.37171571e-02, ...,
          -4.98423725e-02, -3.41324694e-03, -3.38480249e-03],
         [-4.42718714e-02,  1.80771761e-02, -1.81254596e-02, ...,
           4.95384960e-03,  2.30055675e-02,  4.05678861e-02],
         [-2.49727946e-02, -2.38794126e-02, -6.36631474e-02, ...,
          -1.22594330e-02, -5.16248047e-02, -1.45599088e-02]]],


       [[[ 2.77299285e-02, -3.51079367e-02, -5.33241546e-03, ...,
           2.04842556e-02, -3.65010975e-03, -4.68273461e-02],
         [ 1.02981310e-02, -2.39492971e-02,  1.34688085e-02, ...,
          -2.56987084e-02, -7.98216276e-03, -4.75725941e-02],
         [-3.70503888e-02,  1.12369740e-02,  4.28051800e-02, ...,
           1.54643646e-02, -2.64508706e-02, -1.74794663e-02],
         ...,
         [-2.24846713e-02, -4.11045924e-02,  4.34685120e-04, ...,
          -2.56589726e-02, -3.14562544e-02, -2.52395663e-02],
         [-2.39708181e-02, -5.49744815e-02,  9.32919700e-03, ...,
           2.73514222e-02, -2.28792476e-03, -1.35064824e-02],
         [ 2.82794107e-02, -8.04773625e-03, -6.47973130e-03, ...,
           3.92252587e-05,  1.37577113e-02, -2.14618575e-02]],

        [[-3.17523582e-03,  2.79654451e-02, -1.80122741e-02, ...,
           1.31466389e-02,  2.16854569e-02,  1.90348104e-02],
         [ 2.46145613e-02,  1.96673088e-02, -3.69335562e-02, ...,
          -4.52958457e-02,  2.49024704e-02,  6.59818947e-03],
         [ 3.94158214e-02, -1.57302211e-03,  1.27845434e-02, ...,
           7.26003526e-03,  2.22697929e-02,  1.59337148e-02],
         ...,
         [ 3.12434435e-02, -1.00670347e-03, -1.94825642e-02, ...,
          -2.35885736e-02,  3.93827679e-03,  6.11478789e-03],
         [-5.58631169e-03, -9.55511816e-03, -5.91319576e-02, ...,
           6.31839561e-04, -1.81744471e-02,  4.20061797e-02],
         [-2.74639707e-02, -3.60006057e-02,  1.32352943e-02, ...,
           2.31149942e-02, -3.80126722e-02,  9.64939967e-03]],

        [[ 2.19207108e-02,  2.19619065e-03,  1.11967167e-02, ...,
           2.22718865e-02, -2.04731338e-02,  1.03668170e-02],
         [-3.29059884e-02, -3.32678072e-02, -7.41325039e-03, ...,
           1.60688795e-02,  4.38033566e-02,  4.57469746e-02],
         [-3.33565101e-02,  4.96677086e-02, -7.42027396e-03, ...,
          -4.68998477e-02, -3.74865197e-02,  3.13370861e-02],
         ...,
         [-3.69241498e-02, -1.99956838e-02,  4.23209108e-02, ...,
          -3.46513651e-02, -2.62022186e-02,  4.10685129e-02],
         [ 3.87867796e-03,  2.71835588e-02,  2.00306792e-02, ...,
           1.75148118e-02,  3.00700888e-02,  3.95426154e-02],
         [ 7.36910291e-03, -7.48466514e-03, -2.04028022e-02, ...,
          -3.55448350e-02,  3.90026160e-02, -3.88655104e-02]],

        [[ 2.29638070e-02,  3.98402773e-02, -1.69249438e-02, ...,
           4.29517813e-02,  4.27153930e-02, -1.53701566e-02],
         [-1.51761742e-02, -6.16812818e-02, -2.23627985e-02, ...,
          -1.01610422e-02,  3.51466215e-03,  2.93047843e-03],
         [-3.89838070e-02,  1.64619479e-02, -4.28264495e-03, ...,
          -5.60235083e-02, -1.58630908e-02, -3.77268158e-02],
         ...,
         [-2.81325560e-02,  4.23634015e-02, -2.52707619e-02, ...,
          -4.12566811e-02, -3.23355757e-02, -2.66975723e-02],
         [ 2.21167505e-02,  2.00241413e-02, -4.97071072e-02, ...,
           2.44322489e-03, -2.06867736e-02, -1.01680895e-02],
         [ 3.94265689e-02, -1.11885360e-02, -4.02699709e-02, ...,
          -2.35887151e-02,  2.19871141e-02, -2.79141553e-02]],

        [[ 3.13378386e-02, -2.86770109e-02, -1.46431578e-02, ...,
           4.27936912e-02, -4.43020510e-03, -3.85570253e-04],
         [ 2.32516713e-02,  1.69147812e-02, -2.40768883e-02, ...,
           1.47077339e-02,  1.82994194e-02,  2.06011590e-02],
         [ 1.31323263e-02, -3.82185361e-04,  4.35632840e-02, ...,
           8.37553293e-03,  1.64638944e-02, -2.87083164e-02],
         ...,
         [ 4.01473232e-02,  1.78321954e-02,  3.34198326e-02, ...,
          -8.74195434e-03, -4.27058004e-02,  2.20930669e-02],
         [ 4.88571003e-02, -5.97451404e-02, -3.11626103e-02, ...,
           4.35966474e-04, -2.47155111e-02, -1.83649305e-02],
         [ 3.78854126e-02,  1.01971533e-02, -4.17929702e-02, ...,
          -3.42926458e-02, -3.12211234e-02,  3.02888639e-03]]],


       [[[ 1.20664015e-03, -4.15611779e-03, -5.20385653e-02, ...,
           3.34217548e-02,  5.51242307e-02, -3.06504332e-02],
         [ 4.91377618e-03, -5.13235405e-02,  3.04486286e-02, ...,
           1.30512519e-02, -2.29704883e-02, -2.43706554e-02],
         [-3.23607922e-02,  2.93780696e-02,  4.36764583e-02, ...,
           2.01399140e-02, -4.90103625e-02,  2.39844378e-02],
         ...,
         [-1.54880537e-02, -6.26316480e-03, -3.04051824e-02, ...,
          -1.17099127e-02, -3.10501233e-02,  3.72402486e-03],
         [-4.36039902e-02, -1.58859428e-03, -5.70483543e-02, ...,
          -3.31682116e-02,  3.55958752e-02, -3.48991342e-02],
         [ 1.20701676e-03,  1.14605008e-02,  7.37628783e-04, ...,
           2.66584363e-02, -4.26166095e-02, -3.41038220e-02]],

        [[ 7.01101031e-03, -3.27452794e-02,  1.77387670e-02, ...,
           1.23008201e-02,  1.72625519e-02,  5.13232127e-03],
         [ 3.34243216e-02, -1.42818328e-03,  3.77325565e-02, ...,
          -4.30239923e-02,  3.01096030e-02, -4.57591563e-02],
         [ 1.94069929e-02,  1.46690309e-02,  4.30345535e-02, ...,
          -2.50114072e-02, -2.41605546e-02, -2.75397561e-02],
         ...,
         [ 2.28364598e-02, -9.14779212e-03,  2.49816459e-02, ...,
           2.07152013e-02, -1.61161125e-02,  1.90236699e-02],
         [-2.90166754e-02, -1.80153586e-02, -5.88090792e-02, ...,
          -8.15026741e-03,  3.62978242e-02,  2.76349392e-02],
         [ 6.96685165e-03,  7.90848676e-03, -4.76761581e-03, ...,
           1.03254328e-02, -2.99270847e-03,  2.17563007e-02]],

        [[ 2.87624858e-02,  1.75254643e-02, -1.20995436e-02, ...,
           5.63869765e-03,  3.38967587e-03,  1.74080245e-02],
         [-9.29729547e-03,  2.55176034e-02,  2.82855053e-02, ...,
          -4.18154858e-02,  2.53336839e-02, -2.74970047e-02],
         [-1.64244398e-02, -7.93271884e-03,  2.40046885e-02, ...,
          -4.73201312e-02, -2.24696398e-02, -2.41908804e-02],
         ...,
         [-5.24348067e-03,  2.95759961e-02,  4.89886440e-02, ...,
           3.46590728e-02,  2.32733227e-02,  7.16414116e-03],
         [ 2.67093629e-02,  1.97031982e-02, -2.09878944e-02, ...,
           2.22503468e-02,  1.16105592e-02,  3.10666598e-02],
         [-9.52884182e-03, -1.13260895e-02, -1.10577866e-02, ...,
           2.43256576e-02,  1.88256912e-02, -2.83884015e-02]],

        [[ 2.16864087e-02,  2.86757406e-02,  1.70620997e-02, ...,
           3.15887071e-02,  4.26313579e-02, -2.14493368e-02],
         [ 1.11251865e-02,  1.11956382e-03, -2.24658139e-02, ...,
           6.51905872e-03,  2.25196853e-02, -1.87775735e-02],
         [-5.13564004e-03, -4.51170020e-02,  4.48314706e-04, ...,
           9.82165057e-03,  3.45783271e-02, -3.06159593e-02],
         ...,
         [ 1.08366413e-02, -3.19622904e-02, -2.82066711e-03, ...,
          -1.02455413e-03, -6.17606379e-02,  3.36515978e-02],
         [-3.01616471e-02,  2.33502015e-02, -4.38920893e-02, ...,
           1.87135041e-02,  2.17296071e-02,  1.88426320e-02],
         [-3.16988491e-02, -6.33149222e-03, -5.81065640e-02, ...,
           4.89979498e-02, -5.12960479e-02, -2.88055297e-02]],

        [[ 3.58687043e-02, -3.41066755e-02,  2.44474113e-02, ...,
           5.21705970e-02, -9.59330611e-03, -3.71454954e-02],
         [ 4.38393578e-02, -7.87789654e-03, -3.21995988e-02, ...,
          -3.58720981e-02,  1.10670570e-02, -2.06690580e-02],
         [-4.26218845e-02, -2.98735388e-02,  2.93741338e-02, ...,
          -4.01434265e-02,  4.19359729e-02, -1.34528736e-02],
         ...,
         [-1.19901104e-02, -2.36788280e-02,  2.56820805e-02, ...,
          -2.82554701e-02, -4.93142344e-02,  3.81649546e-02],
         [-2.11023148e-02,  3.00988369e-02, -2.54096445e-02, ...,
          -1.18895629e-02,  5.05110854e-03, -4.65975441e-02],
         [ 2.60894969e-02, -4.44890857e-02,  7.20352214e-03, ...,
           8.62746872e-03,  2.61032600e-02,  2.94165891e-02]]],


       [[[-8.23470857e-03,  2.66973451e-02,  2.46494841e-02, ...,
          -7.95344356e-03,  5.41901477e-02,  3.80892376e-03],
         [ 3.46896946e-02, -3.56616527e-02,  1.76680516e-02, ...,
          -2.58594397e-02, -1.63248088e-02, -2.75265076e-03],
         [ 2.10387260e-03,  2.85851434e-02,  4.26178649e-02, ...,
           2.24570371e-02, -5.67111420e-03,  1.57224927e-02],
         ...,
         [-8.50075856e-03, -1.04381125e-02,  3.67088802e-02, ...,
          -3.87348421e-02, -3.09971347e-02,  2.06953976e-02],
         [-4.28556986e-02, -1.91741865e-02, -5.00398353e-02, ...,
          -2.86979452e-02, -1.85708124e-02,  4.07203054e-03],
         [-2.17487291e-03,  1.17763150e-02, -2.43056864e-02, ...,
          -3.16434130e-02, -6.29072264e-03, -3.70692536e-02]],

        [[-1.47991357e-02,  3.81535664e-02, -4.52017449e-02, ...,
           3.27082165e-02,  3.72239798e-02,  6.24171365e-03],
         [-4.94916327e-02,  1.66965965e-02,  2.75296494e-02, ...,
          -3.60563658e-02,  2.53073815e-02,  4.03792970e-02],
         [-2.83768233e-02,  1.32137316e-03,  4.29472178e-02, ...,
           3.02893501e-02,  1.44144204e-02,  3.09402365e-02],
         ...,
         [ 3.51103172e-02,  9.58061498e-03,  5.19294888e-02, ...,
          -3.29096280e-02, -2.68523265e-02,  4.37065354e-03],
         [-3.90499122e-02, -1.18175652e-02, -1.71098439e-03, ...,
          -4.21404541e-02, -3.11733391e-02, -2.61477288e-02],
         [-1.30414935e-02,  1.25428885e-02, -1.16590075e-02, ...,
           1.07277604e-02,  2.99695712e-02, -5.84134795e-02]],

        [[ 3.96039002e-02,  3.61394603e-03,  3.45684811e-02, ...,
           2.16922374e-03, -3.78693528e-02, -5.05634770e-03],
         [ 3.15429792e-02, -3.78403366e-02, -2.94523314e-02, ...,
           9.06615797e-03,  2.79341061e-02, -8.49829800e-03],
         [ 3.62972766e-02,  1.00066047e-02,  2.49363370e-02, ...,
           1.27204480e-02, -4.54551280e-02,  3.94800864e-02],
         ...,
         [ 3.93683128e-02,  2.03894023e-02, -9.38774832e-03, ...,
          -2.21174005e-02,  2.98597496e-02,  3.87130789e-02],
         [-3.39044854e-02,  2.29387097e-02, -1.68719166e-03, ...,
          -4.69814800e-02, -1.44800320e-02,  2.67530791e-02],
         [ 4.17313613e-02, -3.34071591e-02, -1.22960368e-02, ...,
           4.66541238e-02,  3.38419154e-02, -2.23648511e-02]],

        [[-2.56456919e-02, -1.84572041e-02, -4.72112894e-02, ...,
          -2.46840324e-02, -3.88497338e-02,  3.23555283e-02],
         [ 3.61141041e-02,  2.86871120e-02, -2.30029244e-02, ...,
           8.65036622e-03, -3.64613882e-03, -2.83704177e-02],
         [-2.44418085e-02, -8.83141346e-03, -2.62596905e-02, ...,
           4.93694237e-03, -2.55395547e-02,  4.43419628e-02],
         ...,
         [ 2.10360568e-02,  3.51965949e-02,  8.65049288e-03, ...,
           6.32018037e-03, -6.37807548e-02,  6.69736974e-03],
         [ 7.79788755e-03, -5.03527373e-02,  1.30178984e-02, ...,
          -2.33074073e-02,  4.11761887e-02, -1.95072289e-03],
         [-2.06605569e-02,  3.78227420e-02, -3.61567736e-02, ...,
           1.37477517e-02, -2.79867705e-02, -2.28245538e-02]],

        [[ 1.03193903e-02,  1.78605523e-02, -7.63170980e-03, ...,
           1.39986947e-02, -1.38641875e-02, -3.70460264e-02],
         [ 3.04851197e-02,  1.22348517e-02, -6.54431479e-03, ...,
          -3.45610939e-02,  1.79517083e-02, -2.73510329e-02],
         [ 4.41939794e-02,  3.54783684e-02,  3.78013365e-02, ...,
           1.33813191e-02, -4.83437032e-02,  1.03076715e-02],
         ...,
         [ 1.25785396e-02,  4.29520430e-03,  3.98713984e-02, ...,
           9.86505486e-03, -4.43795770e-02, -4.15943302e-02],
         [-4.27745208e-02,  8.58645246e-04, -1.98522843e-02, ...,
           6.92752097e-03, -3.40285420e-04, -1.10307103e-02],
         [ 6.04993943e-03, -1.53091457e-02,  3.61494557e-03, ...,
          -2.87047513e-02, -3.53954062e-02,  3.72418649e-02]]]],
      dtype=float32), array([[[[-1.98909380e-02, -1.80047064e-04,  4.72355932e-02, ...,
          -4.14696857e-02,  1.44405756e-02,  3.51218358e-02],
         [-7.17394659e-03,  3.15847583e-02,  2.98160501e-02, ...,
          -3.99501808e-02,  2.82684453e-02,  2.60957424e-03],
         [ 5.41317835e-02, -5.84085379e-03, -7.33989582e-04, ...,
           1.72938071e-02,  4.56399284e-02,  2.76395474e-02],
         ...,
         [ 4.21187952e-02, -4.09412049e-02, -1.94266979e-02, ...,
           1.18776150e-02, -2.63784863e-02, -1.58770792e-02],
         [ 1.73143670e-02,  4.27468792e-02, -4.48977649e-02, ...,
           3.70152369e-02,  2.72487774e-02, -3.76335941e-02],
         [-1.69921964e-02,  2.89508160e-02,  2.37151701e-02, ...,
          -4.21471633e-02, -8.70842859e-03,  3.44260633e-02]],

        [[-5.93789816e-02,  3.07621006e-02, -3.78356948e-02, ...,
           1.13152282e-03,  5.36030903e-02, -3.42059135e-02],
         [ 4.55909874e-03, -1.39723206e-02, -2.47065356e-04, ...,
          -2.75852401e-02,  4.39488795e-04,  3.80431972e-02],
         [-2.00720355e-02,  3.39165819e-03, -2.52663400e-02, ...,
          -6.20161509e-03, -1.94459483e-02,  9.67987441e-03],
         ...,
         [ 1.90380178e-02,  5.12827598e-02, -3.03707551e-02, ...,
           1.86849572e-02, -5.89161143e-02, -3.94641943e-02],
         [ 3.98520846e-04,  1.51753612e-03,  5.02604991e-04, ...,
           4.99363765e-02, -4.19152947e-03, -1.98848266e-02],
         [ 4.10230905e-02,  4.62467708e-02, -4.37979139e-02, ...,
           6.19215332e-02,  4.85606827e-02,  2.69372351e-02]],

        [[-3.96527164e-02, -2.75827441e-02, -2.63769478e-02, ...,
           6.25616983e-02, -4.05812673e-02,  2.10207663e-02],
         [-2.48464141e-02, -3.88870388e-03,  4.64868061e-02, ...,
           2.20956616e-02, -1.43362267e-03,  4.35881084e-03],
         [ 1.94299128e-02, -4.91314605e-02,  3.52637880e-02, ...,
          -6.89371377e-02,  2.82781515e-02,  1.73540041e-02],
         ...,
         [ 9.67488741e-04,  3.96557450e-02,  1.56303700e-02, ...,
           5.61511493e-04, -3.12913992e-02,  4.28543426e-02],
         [-5.89450859e-02,  5.41233309e-02, -5.91651397e-03, ...,
          -1.47725716e-02,  4.10272600e-03, -4.78372313e-02],
         [-2.93753985e-02, -3.55163403e-02,  3.48611958e-02, ...,
           3.45498463e-03,  5.65605350e-02,  5.81964701e-02]]],


       [[[ 2.09755241e-03, -5.89955598e-02,  4.46604155e-02, ...,
          -3.84283699e-02, -1.23002278e-02,  3.24470387e-03],
         [-1.62787288e-02,  2.79567298e-02, -9.42407362e-03, ...,
           6.85243160e-02, -5.65537177e-02,  9.76368692e-03],
         [ 3.45676914e-02, -5.66379763e-02, -9.19349957e-03, ...,
          -6.18588664e-02, -3.44751850e-02,  6.04039803e-03],
         ...,
         [-9.71409772e-03,  5.20917810e-02,  2.29478069e-02, ...,
          -7.01430663e-02, -5.75480238e-02, -5.38850799e-02],
         [-5.27025620e-03, -1.66598391e-02,  5.62909357e-02, ...,
          -4.50549573e-02,  8.43286328e-03, -2.75040586e-02],
         [-3.19885761e-02, -2.63189897e-02, -4.92050834e-02, ...,
          -4.78680208e-02, -5.55602200e-02,  1.07187442e-02]],

        [[-4.50192066e-03,  1.65353585e-02, -4.28267345e-02, ...,
           5.14325360e-03, -3.45459729e-02, -5.63805886e-02],
         [ 3.73531058e-02, -3.66620235e-02,  4.51980680e-02, ...,
           1.20101888e-02, -6.17008619e-02, -5.20470962e-02],
         [ 5.22755384e-02, -3.48363891e-02, -3.03864703e-02, ...,
           3.67545988e-03,  3.13612074e-02, -1.70232467e-02],
         ...,
         [-2.59413142e-02, -1.98240057e-02,  2.36986410e-02, ...,
          -1.67096928e-02, -4.80667576e-02,  5.88830076e-02],
         [-6.53897319e-03, -4.31006221e-04,  1.30492067e-02, ...,
          -5.37904445e-03,  5.38870208e-02,  3.19856741e-02],
         [-4.96304706e-02, -3.16329747e-02, -3.40614878e-02, ...,
           5.00321910e-02,  5.02669103e-02,  6.03158362e-02]],

        [[ 9.57970042e-03, -2.18996871e-02,  1.74980983e-03, ...,
          -3.07992045e-02, -3.73230465e-02, -1.61242783e-02],
         [ 4.88855094e-02,  1.19241923e-02,  4.53389157e-03, ...,
           2.85488050e-02, -4.40953337e-02, -1.12416409e-02],
         [-1.70512348e-02, -3.49982642e-02,  1.80063192e-02, ...,
          -5.53497039e-02,  1.03539578e-03,  3.45996730e-02],
         ...,
         [-3.57213430e-03, -9.24368389e-03, -2.33879425e-02, ...,
           1.38109345e-02,  2.17157211e-02,  5.67344464e-02],
         [ 5.33944070e-02,  1.41196987e-02,  1.39140831e-02, ...,
          -4.31046002e-02,  4.42354120e-02,  4.42322157e-02],
         [-2.28648689e-02, -5.11502586e-02,  3.63884494e-02, ...,
           5.22942096e-02, -3.38046663e-02,  2.22865678e-02]]],


       [[[-6.45904541e-02,  3.00288070e-02,  4.65780012e-02, ...,
          -3.12591083e-02, -1.69184003e-02,  4.65640239e-02],
         [-4.27438207e-02, -3.77776064e-02,  1.34174004e-02, ...,
          -5.15189022e-02, -2.90371887e-02, -3.50668823e-04],
         [-4.89144176e-02, -2.27959757e-03, -1.18840449e-02, ...,
          -6.70819730e-02,  3.72282043e-02, -3.87861505e-02],
         ...,
         [ 5.33640981e-02,  6.73143119e-02,  3.99159230e-02, ...,
          -4.04526368e-02,  2.96328235e-02,  2.69461758e-02],
         [-3.49036157e-02,  1.17405569e-02,  1.82437338e-02, ...,
           6.56674132e-02, -1.11499028e-02,  4.88374643e-02],
         [-4.79791090e-02, -1.68833006e-02,  5.11847250e-02, ...,
           6.93305135e-02,  1.80206969e-02, -1.44498525e-02]],

        [[ 1.47906551e-02,  1.10713416e-03, -1.89451911e-02, ...,
           7.17598572e-02, -3.93776558e-02,  3.71221825e-02],
         [-2.23718733e-02,  4.20468859e-02, -2.58339383e-02, ...,
           2.13782750e-02, -2.28319075e-02, -1.71335917e-02],
         [ 4.06771861e-02,  2.35889312e-02,  5.06635644e-02, ...,
          -7.02520162e-02, -5.23255765e-02, -3.38586839e-03],
         ...,
         [-3.51819135e-02, -1.89566780e-02, -1.14993192e-02, ...,
          -4.45526876e-02,  2.00367738e-02,  5.26400879e-02],
         [ 3.18813026e-02,  5.40780053e-02,  5.09168319e-02, ...,
          -3.02245561e-03,  5.06765023e-03, -5.29017486e-02],
         [-3.02703306e-02,  6.33812684e-04,  3.79615985e-02, ...,
           2.72743055e-03,  4.43006530e-02, -2.97516715e-02]],

        [[-4.83231097e-02,  8.75104964e-03,  5.71950153e-02, ...,
          -2.05792412e-02, -1.78971048e-02, -3.43435677e-05],
         [-5.27733229e-02,  2.55833799e-03,  4.94596884e-02, ...,
          -6.28357660e-03, -2.56958362e-02, -4.32528630e-02],
         [-5.20776175e-02,  4.03480493e-02,  2.27838326e-02, ...,
           2.09196135e-02, -3.29203084e-02, -5.67158358e-03],
         ...,
         [ 3.63735668e-02,  6.89681545e-02,  1.88084152e-02, ...,
           2.80158184e-02, -5.43648889e-03,  1.95571221e-02],
         [ 1.64190512e-02,  5.59380911e-02,  2.31958423e-02, ...,
          -1.30920112e-02,  2.91149057e-02,  3.15916650e-02],
         [ 2.58776005e-02,  1.96779296e-02,  2.45688972e-03, ...,
          -3.51701602e-02, -3.86025012e-02,  6.22677281e-02]]]],
      dtype=float32), array([[[[-0.0430833 , -0.11877066,  0.00081862, ..., -0.01845194,
          -0.04459433,  0.03811286],
         [ 0.07448353, -0.12221871, -0.09948217, ...,  0.06055006,
          -0.07019386,  0.14520243],
         [-0.14569905,  0.10570973,  0.11516461, ...,  0.12171858,
           0.01043564,  0.09851217],
         ...,
         [ 0.00299264, -0.13790359, -0.0445714 , ...,  0.00723001,
           0.00846856,  0.03392572],
         [-0.0732687 , -0.04407511, -0.08839811, ..., -0.07500323,
          -0.06168791, -0.03830284],
         [ 0.05872402,  0.0421357 ,  0.09151734, ...,  0.01657021,
          -0.11957   , -0.10203876]]]], dtype=float32), array([ 0.00148582,  0.00294928,  0.00167977,  0.00275532,  0.02134343,
        0.02858836, -0.00251403, -0.01592836,  0.00088463,  0.01722807,
        0.00362963, -0.01723312,  0.00098141,  0.00773894, -0.00975452,
        0.00317728, -0.00315098, -0.01199997,  0.00920534,  0.00556232,
        0.00599895, -0.00522346, -0.00793396, -0.00356814,  0.0021279 ,
        0.01035917, -0.00763726,  0.0152434 , -0.02122624, -0.02190549,
       -0.02254295, -0.00895582,  0.00410244, -0.00200712,  0.01955419,
       -0.00050452,  0.00566273, -0.00588304,  0.01426718, -0.00460164,
        0.01283337, -0.00934881, -0.00515052, -0.00982433,  0.01488583,
        0.01049571, -0.00070711,  0.02321461,  0.00188623,  0.00088365,
        0.01530499, -0.01823302,  0.01036883,  0.0035844 ,  0.00399981,
        0.01594122, -0.01063416, -0.00428415,  0.00250607, -0.0062176 ,
       -0.00955432, -0.00793714, -0.00166166, -0.00392186], dtype=float32), array([ 0.28473517,  0.30959478, -0.02425075, -0.13303006,  0.17931296,
        0.07318373,  0.48919383, -0.35438845,  0.50677645,  0.13103314,
       -0.4100697 ,  0.801715  , -0.12110145, -0.02361211,  0.45280144,
       -0.12634468,  0.42302087,  0.69782186,  0.05812762,  0.4973396 ,
        0.03988586,  0.31447557, -0.16004027,  0.05549767, -0.3767042 ,
       -0.78040326,  0.15541422, -0.08536177,  0.72935647,  0.32496247,
        0.177654  , -0.31858462,  0.4451415 ,  0.6449011 , -0.42786852,
       -0.45382094,  0.26903003, -0.16426894,  0.5192204 , -0.4824501 ,
       -0.16276172,  0.35308155,  0.37008923, -0.20290776, -0.8292112 ,
        0.24297582,  0.04600535, -0.08428032, -0.18786617,  0.3206019 ,
       -0.96596414,  0.12631457,  0.22404848, -0.06887545,  0.06681481,
       -0.6450774 ,  0.42755818,  0.76926064,  0.26414987,  0.15043098,
       -0.15844734,  0.24284355,  0.34548116, -0.25021788], dtype=float32), array([0.42356488, 1.4953301 , 1.3535368 , 1.0128679 , 0.9331028 ,
       1.2878678 , 1.3688457 , 0.429051  , 1.0360124 , 1.0481533 ,
       0.7099054 , 1.6734527 , 0.6093956 , 0.83248806, 1.1963061 ,
       1.067573  , 0.949646  , 0.95529896, 0.96514714, 1.0706272 ,
       1.535489  , 0.9979876 , 0.7846886 , 1.1856915 , 1.7129393 ,
       0.6996842 , 1.0356517 , 0.7338752 , 1.1890672 , 0.8008963 ,
       0.9391702 , 1.2659181 , 0.8558339 , 0.61226726, 0.8019232 ,
       1.8396126 , 1.3222084 , 1.8194422 , 0.87259555, 2.4492874 ,
       2.2274046 , 1.4429512 , 0.44875193, 0.8842819 , 1.1658063 ,
       1.5390213 , 0.6043359 , 0.8646048 , 0.928761  , 2.29963   ,
       1.3075273 , 0.8589029 , 1.1289916 , 1.6432389 , 1.420095  ,
       1.2536491 , 1.1136138 , 2.0606241 , 0.53630483, 1.2829331 ,
       0.9614067 , 1.0029795 , 1.1186644 , 0.8630453 ], dtype=float32), array([-0.00338317,  0.01022339,  0.00628947, -0.00925033, -0.01255817,
        0.00165147, -0.00465295, -0.02138012,  0.00543889, -0.01245108,
       -0.00224831,  0.00354633, -0.00446614,  0.00453575, -0.01326828,
        0.00654633,  0.01625215,  0.02854089,  0.00751312,  0.00214786,
        0.01490451,  0.00044958, -0.02273728, -0.00568943, -0.02293508,
        0.01125487, -0.00707071, -0.01321719,  0.00672049,  0.0044641 ,
       -0.00646979,  0.00776729, -0.00285222,  0.00126009,  0.02685337,
       -0.00088306,  0.01048426, -0.01221133, -0.01185581, -0.00164505,
        0.00951269,  0.00031704, -0.01509023, -0.00765862,  0.00274883,
        0.01390334, -0.00606136,  0.0167812 , -0.00813173,  0.01353831,
        0.0147455 ,  0.01091216,  0.00409509,  0.01828693, -0.00325539,
       -0.00733857, -0.00170513, -0.00233724, -0.00447137,  0.00447571,
       -0.00453165, -0.00034215,  0.01174302, -0.00603974], dtype=float32), array([ 0.61511165, -1.3866197 , -0.4781863 ,  1.0044324 , -0.8707199 ,
        0.5965616 ,  0.9196473 ,  1.3185854 , -1.5689735 ,  0.36723024,
        0.92877775, -0.5220803 ,  0.19736955,  1.3176025 ,  0.1504119 ,
        0.36471665,  0.3742338 , -1.3219111 ,  0.47366208, -0.18767412,
       -0.64513963,  0.19886175, -1.1957637 ,  0.94519436,  0.20760195,
       -1.4600103 , -1.0813236 , -0.12895432, -0.75975543,  0.35055837,
       -0.36763442, -0.24566609,  0.29726353,  0.30820662, -1.5642563 ,
        0.5753731 , -1.3979107 , -0.5994705 ,  1.0815922 , -1.5406842 ,
        0.7291534 ,  0.6366472 , -1.6085199 , -1.8416916 , -0.5195091 ,
       -1.413737  ,  0.65441585,  0.7271651 , -1.4028515 , -1.0897118 ,
        1.1322947 ,  0.3958199 ,  0.31016138, -1.3163526 ,  0.7098495 ,
        0.45931298,  0.4786757 ,  0.536489  ,  0.07138951,  0.76811564,
        0.9489831 , -0.2972466 , -0.59075534, -0.08189463], dtype=float32), array([1.9586321, 5.2226243, 4.945185 , 2.1610527, 2.3617902, 1.851484 ,
       2.5105116, 2.329159 , 3.7783566, 4.635299 , 3.245661 , 3.3853512,
       1.4792689, 3.5359113, 2.6496713, 2.336672 , 3.5227628, 1.9827336,
       4.6530766, 2.797612 , 2.4774754, 4.806951 , 1.3972918, 2.6972914,
       3.2393808, 5.211429 , 2.1405072, 2.1449225, 2.2521958, 3.5224547,
       2.1218748, 5.8062377, 1.4750384, 1.8564557, 4.0268865, 4.007453 ,
       4.642297 , 1.9286926, 2.7301743, 3.3569999, 1.8833092, 3.3999465,
       2.752543 , 1.0843037, 3.364618 , 3.370063 , 1.931693 , 3.3646684,
       2.3896654, 3.8831105, 3.8603804, 3.7616951, 1.5099968, 6.4355693,
       2.432975 , 1.9481606, 3.1453576, 2.1699104, 1.206722 , 2.809099 ,
       2.4094512, 1.7252904, 1.5361297, 2.0435002], dtype=float32), array([ 0.02876124,  0.02114712,  0.0049425 ,  0.01030785, -0.01300777,
       -0.00195071,  0.00386528,  0.01042137,  0.00541227,  0.00087108,
       -0.00119529, -0.00819969,  0.01540977, -0.00171013, -0.00723124,
       -0.00301497, -0.0127731 ,  0.00611785,  0.00225558,  0.01695388,
        0.01004591, -0.01851012, -0.01161519, -0.00816128,  0.01373558,
        0.02386051, -0.0150312 , -0.01122927,  0.01884193,  0.01228172,
        0.01112648, -0.00475411,  0.00686681,  0.01009731,  0.00316548,
        0.00754706, -0.00710044,  0.03250728,  0.01373519, -0.01161546,
       -0.00281947, -0.00696622,  0.00549475,  0.00023808,  0.00950846,
       -0.01273366, -0.00832511,  0.0039917 , -0.00715789, -0.0023797 ,
       -0.01226023, -0.00937915,  0.00860606,  0.00154042,  0.02189071,
       -0.01849223, -0.00889952,  0.00514544, -0.00543745, -0.0133687 ,
       -0.00121743,  0.01821359,  0.00739872, -0.00887358, -0.00717647,
       -0.00257894, -0.01750462,  0.00880075,  0.00799865,  0.030578  ,
       -0.00875361,  0.01909636,  0.00048719,  0.02947868,  0.00445982,
        0.00233326, -0.00382218,  0.00670057, -0.00940877, -0.0062393 ,
        0.00885225,  0.00908025, -0.01628164,  0.00020858,  0.00305554,
        0.02030138, -0.01782057, -0.00453273, -0.00892434,  0.006044  ,
        0.02370294,  0.02076366, -0.01116263, -0.00684532, -0.00758838,
       -0.00373491], dtype=float32), array([-0.7621584 ,  0.8819892 ,  1.4332168 , -0.09068725,  0.49046138,
        0.45625636,  0.18419276, -0.16190398,  0.02171006, -0.14744668,
       -0.16321158,  0.2399145 ,  0.26098707,  0.17471366,  0.37138683,
        0.745955  , -0.3397959 ,  0.41403347,  0.59239525, -0.33558252,
        0.71465105,  0.07997517,  0.37513423, -0.6800561 , -0.32527214,
       -0.7778177 , -0.30418354,  0.65372074, -0.30050012, -0.32682604,
        0.22078492, -0.86885417, -0.38953322, -0.8348285 ,  0.09039663,
        0.4659264 , -0.4182229 ,  0.378023  , -0.7930992 , -0.15991014,
        0.0604055 ,  0.06204773,  0.12916736, -0.0030452 , -0.31924963,
        0.33600545,  0.10673278,  0.6667871 ,  0.43573803, -0.43874148,
        0.4039935 ,  0.7755573 , -0.43227938, -1.0441681 , -0.5050293 ,
        0.6184703 ,  0.27125165,  0.510329  ,  0.20781922,  0.05971966,
        0.39510086, -0.74212223,  0.27786785, -1.2096884 ,  0.38874152,
       -0.03583342,  0.4155178 ,  0.38965514, -0.9325242 , -0.5896596 ,
        0.09896225, -1.3951143 ,  0.69786155, -0.25417477,  0.17661233,
        0.13319235,  0.22064634,  0.42769855, -1.4424895 , -0.25495872,
       -0.7120382 , -0.76883113,  0.45525953, -0.69404054, -0.99198776,
        0.4858618 ,  0.05840486,  0.36451793,  0.09761202, -0.6198892 ,
       -0.47391453, -0.8649888 ,  1.4273984 , -0.6771517 , -0.637103  ,
        0.5571284 ], dtype=float32), array([1.9513735 , 2.1190186 , 2.7945251 , 1.1908646 , 1.7136406 ,
       1.653734  , 1.8761683 , 1.4539707 , 2.2868576 , 2.3470402 ,
       1.5244259 , 2.2165115 , 2.7134004 , 1.2247854 , 2.0913596 ,
       1.7419722 , 2.2669802 , 1.437141  , 2.1679819 , 2.0566382 ,
       2.0898457 , 0.99765503, 1.8468812 , 2.359772  , 1.5449504 ,
       2.526917  , 1.5375137 , 1.9614818 , 2.0003755 , 2.0976822 ,
       1.2002537 , 1.5986819 , 1.6760037 , 1.3214904 , 1.1180117 ,
       2.015919  , 2.4965818 , 2.6410837 , 2.1605814 , 1.7730833 ,
       2.1422324 , 1.6705772 , 1.5772784 , 1.6043602 , 1.0579451 ,
       0.94921005, 1.4457451 , 1.3006954 , 0.7273469 , 1.8164219 ,
       1.9332669 , 3.1348486 , 2.0641356 , 1.9397603 , 2.4086225 ,
       1.5186228 , 1.7952666 , 3.6946783 , 1.788139  , 1.6478876 ,
       2.4212873 , 1.9451368 , 1.3250583 , 0.74563164, 2.7646115 ,
       0.8459063 , 1.5776109 , 1.1880226 , 1.2973119 , 1.5696733 ,
       3.0932784 , 3.3523033 , 1.9447048 , 1.3482971 , 1.9859921 ,
       2.6944685 , 1.4686375 , 1.0440781 , 3.4340203 , 3.3937497 ,
       2.475805  , 1.5930823 , 3.3828785 , 2.6772616 , 2.1112313 ,
       2.2316215 , 2.6739407 , 1.9083773 , 2.2469683 , 1.3671488 ,
       1.856328  , 2.6022215 , 3.1971014 , 2.4931087 , 1.9824104 ,
       3.0566366 ], dtype=float32), array([ 2.1607371e-02,  1.0555429e-02, -1.5861558e-02,  7.8240531e-03,
       -1.3441882e-02, -1.5987895e-02, -1.6727718e-02, -8.6717363e-03,
        9.4686029e-03, -1.9586144e-02, -1.5249385e-02,  7.3671890e-03,
        7.5184694e-04, -1.4675222e-03, -1.2616176e-02, -8.0206618e-03,
        8.2482183e-03,  1.4374494e-02,  6.5626167e-03, -2.2757925e-02,
        3.1465434e-03, -2.1327343e-02,  1.2855076e-03,  1.9371793e-02,
       -1.1088750e-02,  3.1014783e-03,  3.9893617e-03, -2.1428028e-03,
        2.0384831e-02, -1.4035987e-02, -1.0482939e-02, -1.2977506e-02,
        9.5221549e-03,  2.9662396e-03, -1.8112615e-02, -1.4395249e-03,
        2.1958936e-03, -1.0957516e-02, -1.2654126e-02,  8.8823298e-03,
        8.9340471e-03, -8.0325855e-03, -1.4140952e-02, -4.8804958e-03,
        2.8068418e-05,  2.4760017e-04,  1.7312514e-02,  5.7954309e-03,
        2.2616249e-02,  2.9413265e-03, -1.9766128e-02, -1.6654974e-02,
       -1.0888918e-03,  2.2310605e-03,  2.6364697e-03,  7.5671799e-03,
        1.8830530e-03,  1.6262357e-03, -1.3141356e-04,  3.9880448e-03,
        5.1714381e-04, -4.6649417e-03, -8.7331096e-03, -1.0121225e-02],
      dtype=float32), array([-0.5995992 , -0.49934   ,  0.16482699,  0.00206883, -0.76498735,
       -0.52618825, -0.03756324,  0.11265004, -0.12848258,  0.45385453,
        0.20576334, -0.7195314 , -0.11637125, -0.38447303,  0.20740473,
        0.63771355,  0.3167855 , -0.12337277,  0.53213537,  0.9678044 ,
        0.14190328,  0.28546402, -0.06561226, -0.02164191,  0.13900816,
       -0.47134164, -0.38261357,  0.5612895 ,  0.5860574 ,  0.11064066,
        0.10550931, -0.65772015, -0.13275385,  0.02615536,  0.19703946,
       -0.06846655,  0.16268525,  0.270592  , -0.3679421 ,  0.6894984 ,
       -0.04308365,  0.1767145 , -0.5746932 , -0.6129269 ,  0.1392328 ,
       -0.2956512 ,  0.0680598 ,  0.36315504, -0.3349959 ,  0.5168158 ,
        0.36064532,  0.6552683 , -0.00435834,  0.48676667, -0.28852195,
        0.5236411 , -0.58931476,  0.70073444,  0.22598962,  0.184996  ,
       -0.19039167,  0.04096036, -0.59986   ,  0.5847987 ], dtype=float32), array([1.2650595 , 0.5717748 , 1.3535234 , 0.72138345, 1.9558121 ,
       1.2971023 , 0.9639006 , 1.2316445 , 0.5791657 , 2.82078   ,
       1.1853784 , 2.4773192 , 1.2720821 , 1.0174254 , 0.92951185,
       0.7891164 , 2.03096   , 1.6264191 , 1.2991654 , 1.785808  ,
       1.5980057 , 1.8523287 , 0.9457342 , 1.2786244 , 1.1445029 ,
       1.0094925 , 1.6114091 , 0.8018832 , 1.39991   , 0.9337671 ,
       1.7116165 , 1.7288866 , 0.67208415, 1.2408005 , 1.0410593 ,
       0.8902189 , 0.7077116 , 1.0067259 , 1.0966817 , 1.0261099 ,
       0.9372352 , 2.2652943 , 1.4582208 , 0.7945298 , 1.6059753 ,
       0.983807  , 0.7526069 , 0.8891337 , 0.48989317, 0.86470854,
       1.294999  , 1.0224994 , 1.5882628 , 1.1943606 , 0.94154596,
       2.6506348 , 2.116779  , 0.60277873, 1.0433196 , 1.001818  ,
       1.1728245 , 1.0790389 , 0.86064607, 2.9593322 ], dtype=float32), array([[[[ 0.02950918,  0.01395673,  0.07725007, ..., -0.11509214,
           0.09931953,  0.12517866],
         [ 0.11568915,  0.11602756,  0.06872459, ...,  0.07799817,
          -0.09263414,  0.00436637],
         [-0.07252418, -0.11848972,  0.02832041, ..., -0.03655756,
           0.07687476,  0.04376011],
         ...,
         [ 0.0693319 , -0.04712925,  0.05084507, ..., -0.02003565,
           0.04456263, -0.09702381],
         [-0.0171515 ,  0.07100862,  0.0370012 , ...,  0.02464295,
          -0.08143131, -0.08814685],
         [ 0.13388193, -0.02863447, -0.04058686, ...,  0.07745648,
           0.06940912, -0.06246401]]]], dtype=float32), array([ 1.09714735e-02, -1.99621730e-03, -1.91147234e-02, -8.04688875e-03,
       -1.69150420e-02, -6.03750988e-04,  4.62157186e-03,  4.66606952e-03,
       -9.16872919e-03, -1.53273232e-02,  9.10500181e-04, -3.83518636e-03,
        8.04042630e-03,  1.67878869e-04, -9.64336656e-03, -6.42906316e-03,
        7.33008003e-03,  7.25040352e-03, -9.89265088e-03,  5.93985256e-04,
       -6.11237390e-03, -8.38741940e-03,  5.85942576e-03,  7.45046698e-03,
        1.19839888e-03,  9.31056682e-03, -1.53174084e-02,  2.85571115e-03,
        2.25474294e-02,  4.06440115e-03, -5.79051720e-03, -2.46346463e-02,
       -7.25408038e-03,  4.01137676e-03,  5.13920095e-03,  5.32651180e-03,
       -6.71273703e-03, -4.54020593e-03,  1.40619371e-03, -4.54866840e-03,
        9.39102750e-03,  1.43425884e-02, -5.00546582e-03,  1.32882120e-02,
       -8.83831363e-03,  5.21960028e-05,  8.11746810e-03, -1.55812278e-02,
       -9.73775797e-03,  1.70018729e-02,  6.16125064e-03,  5.70520712e-03,
       -1.33263224e-04,  6.51781820e-03,  5.59236435e-03, -9.40345321e-03,
        2.70104166e-02,  7.47214712e-04, -9.55849973e-05, -1.57415215e-03,
       -1.27223518e-03, -4.25283704e-03, -1.18215950e-02, -6.95218984e-03],
      dtype=float32), array([ 0.46126345, -0.8363404 , -0.13432409, -0.2852264 ,  0.26125887,
       -0.3716352 , -0.7628613 , -0.47574964,  0.32555324,  0.40318257,
       -0.46045938,  0.2779501 , -0.46368748, -0.46387026, -0.2570294 ,
        0.634427  , -0.21194717, -0.5908992 , -0.46731746,  0.26011118,
        0.41692764,  0.18056197, -0.00308995, -0.10525098, -0.44788378,
        0.41785377,  0.78138375, -1.1422032 , -1.140762  , -0.33541802,
        0.4144346 , -0.259519  ,  0.6610445 ,  0.2631139 ,  0.47455442,
       -0.5594504 ,  0.79055417, -0.10522727,  0.63956726,  0.5922866 ,
        0.17156503, -0.65654224,  0.49156976, -0.76721865,  0.18064854,
       -0.37675866,  0.49630627, -0.34751812,  1.029739  , -0.34516475,
       -0.50164056,  0.13260114,  0.08250711, -0.7323554 ,  0.24974334,
        0.3463368 , -0.364214  , -1.1191838 ,  0.7421873 , -0.7757383 ,
       -0.16505907,  0.03412478,  0.18569255, -0.05048301], dtype=float32), array([0.78793985, 1.4747063 , 1.0057929 , 1.1653696 , 1.1761297 ,
       0.58192337, 2.0383956 , 0.66878265, 0.54796875, 1.343459  ,
       1.8980585 , 0.99400365, 0.6172219 , 0.7527294 , 1.1989216 ,
       0.9222945 , 1.0517782 , 0.93615735, 0.7485855 , 0.6659113 ,
       1.5146765 , 0.8138495 , 0.570861  , 0.96884084, 1.571504  ,
       0.6503965 , 0.9560602 , 0.7405609 , 1.4150314 , 1.679139  ,
       1.4962549 , 1.1980351 , 1.3639793 , 1.0963535 , 1.1123952 ,
       0.6155332 , 0.9887459 , 0.8339611 , 0.9446217 , 1.2619629 ,
       1.1899372 , 2.0130029 , 1.7765311 , 1.1404179 , 1.0070684 ,
       1.290231  , 0.7708222 , 0.72099996, 1.2729275 , 1.0431309 ,
       1.1974111 , 1.6960485 , 0.8849628 , 1.1346227 , 1.5954119 ,
       0.7381458 , 1.6157192 , 1.2820495 , 1.3958801 , 1.0737844 ,
       0.46249998, 1.5684938 , 1.3070273 , 0.56249946], dtype=float32), array([[[[-5.02028279e-02,  1.18299518e-02, -9.19034879e-04, ...,
           1.32283820e-02, -5.87000251e-02,  4.51686978e-02],
         [ 2.40822677e-02,  5.37170172e-02, -1.05273938e-02, ...,
           4.19180803e-02,  2.05338523e-02, -3.85760851e-02],
         [ 9.46934056e-03, -6.68034479e-02, -5.20109199e-02, ...,
           8.11026022e-02,  5.73781505e-02,  4.31344286e-02],
         ...,
         [-4.94838022e-02,  4.49380763e-02,  4.69534323e-02, ...,
           3.02902590e-02,  3.59997973e-02, -5.95627204e-02],
         [-5.39151058e-02, -6.24865629e-02,  5.67911230e-02, ...,
           6.94974288e-02,  1.35853048e-02, -7.61328638e-03],
         [-1.81501620e-02, -2.69775093e-02, -6.17901608e-02, ...,
           5.68664353e-03, -4.69289813e-03, -7.50924945e-02]],

        [[-4.38309349e-02, -5.94867021e-03,  7.02557061e-03, ...,
           2.10368130e-02, -6.58865198e-02,  3.52872498e-02],
         [ 2.11738441e-02,  9.13995970e-03,  6.11461997e-02, ...,
          -4.06574458e-02, -2.27949233e-03, -4.91673546e-03],
         [ 1.80561505e-02, -1.05991093e-02, -5.48554622e-02, ...,
          -1.87127031e-02,  8.96135159e-03,  4.64732237e-02],
         ...,
         [-1.13878343e-02, -1.13263996e-02,  6.47997186e-02, ...,
          -4.64656688e-02, -1.27100050e-02,  6.34998381e-02],
         [ 1.61013138e-02,  1.39359999e-02,  4.50643562e-02, ...,
           4.54354845e-02, -4.40549105e-02, -2.74049770e-02],
         [-2.92919651e-02, -4.12687175e-02, -1.82968210e-02, ...,
          -6.07647114e-02,  2.36992631e-02, -2.56005442e-03]],

        [[ 3.90118994e-02,  2.69545745e-02, -3.90157960e-02, ...,
           5.96632399e-02, -5.93312941e-02, -5.45187145e-02],
         [ 1.09428782e-02,  1.87332332e-02,  2.34603006e-02, ...,
          -1.59424786e-02,  4.75779288e-02, -3.77236940e-02],
         [ 4.68614651e-03,  1.08769070e-02, -2.59497631e-02, ...,
           2.35830490e-02, -2.75720041e-02,  4.37417962e-02],
         ...,
         [ 4.97912802e-02, -5.00002168e-02,  5.11064194e-02, ...,
           3.32998671e-02, -3.49332392e-02, -4.82546240e-02],
         [ 2.37856042e-02,  2.47909762e-02,  1.40171200e-02, ...,
          -7.01137632e-03,  2.92514209e-02, -4.67273071e-02],
         [-2.49158423e-02,  6.60660267e-02,  2.17209365e-02, ...,
          -1.25744157e-02, -6.03392497e-02,  3.68907489e-02]]],


       [[[-4.94480655e-02, -4.22333740e-03, -5.37954122e-02, ...,
           3.25580165e-02,  4.21771593e-02,  2.42259707e-02],
         [ 3.10057234e-02, -8.01821984e-03,  6.54579997e-02, ...,
          -5.38269170e-02, -4.27691191e-02, -4.89185825e-02],
         [ 1.67546589e-02, -2.22323965e-02, -2.22818460e-02, ...,
           3.84747423e-02, -2.52279174e-03,  2.77650543e-03],
         ...,
         [-1.04992429e-03,  4.51190285e-02,  6.91765398e-02, ...,
          -3.43577866e-03, -3.26711647e-02,  1.99203417e-02],
         [-3.24961990e-02, -3.99430059e-02, -5.31208664e-02, ...,
           1.85118131e-02,  5.56212179e-02,  3.80202271e-02],
         [-3.52697372e-02, -3.60796638e-02, -1.75643973e-02, ...,
           1.91879012e-02, -4.62142192e-02,  5.46904989e-02]],

        [[ 2.95025185e-02,  5.87880909e-02, -5.11526465e-02, ...,
          -2.27225218e-02, -5.76218814e-02, -5.91070279e-02],
         [ 6.01263642e-02, -1.38560720e-02,  4.79755886e-02, ...,
          -1.79368053e-02,  4.35639359e-02,  4.85413149e-02],
         [-2.95463391e-02,  3.69555280e-02, -1.84126683e-02, ...,
          -2.31086719e-03, -3.00888456e-02, -1.12106185e-02],
         ...,
         [-3.02620474e-02, -4.74432372e-02,  3.35319042e-02, ...,
          -2.13002451e-02,  2.11613700e-02,  9.28283297e-03],
         [-9.29993577e-03,  5.18327765e-02,  3.09682079e-03, ...,
          -1.73026249e-02, -2.16287374e-02, -1.25497160e-02],
         [-2.64544127e-04,  6.60013258e-02,  2.98559330e-02, ...,
          -4.00354341e-02, -2.76871510e-02, -2.55092941e-02]],

        [[-2.21804865e-02,  4.00335935e-04, -3.35214362e-02, ...,
           3.12642716e-02, -4.95039262e-02,  2.61407141e-02],
         [-1.66581888e-02, -4.22465540e-02,  1.34842945e-02, ...,
          -7.72989541e-02, -9.49014165e-03,  8.56784452e-03],
         [-3.03369742e-02,  3.89132723e-02,  3.13882679e-02, ...,
          -2.11582482e-02,  3.94490883e-02,  4.37143482e-02],
         ...,
         [-4.15507257e-02, -5.65883284e-03,  5.43454150e-03, ...,
           7.58853853e-02,  4.41304743e-02,  5.08046150e-03],
         [ 2.95845997e-02,  6.22615255e-02, -2.91023292e-02, ...,
           9.47849546e-03,  3.44619714e-03,  5.48918396e-02],
         [-1.73155311e-02,  5.16636930e-02, -5.96407428e-03, ...,
           5.97079061e-02, -5.96719682e-02, -7.90709183e-02]]],


       [[[ 6.12236261e-02,  2.40507163e-02,  1.81000717e-02, ...,
          -3.36343609e-02,  3.37031484e-02,  4.47311513e-02],
         [ 3.81330959e-02, -6.86478391e-02,  6.56032413e-02, ...,
           3.04411668e-02,  4.13749255e-02, -5.94428182e-02],
         [ 3.36992294e-02,  4.32860665e-02, -5.77278249e-02, ...,
           6.62203674e-05,  3.06902863e-02,  5.24295606e-02],
         ...,
         [-4.84297797e-02, -3.36651132e-02,  2.40009632e-02, ...,
           2.92016435e-02, -2.20935401e-02,  6.14606440e-02],
         [-2.29401346e-02, -1.40063409e-02, -3.76066752e-02, ...,
          -6.71120584e-02, -2.93981843e-02, -8.33436567e-03],
         [ 5.62730469e-02,  4.17957194e-02, -5.39644398e-02, ...,
           1.78507790e-02,  3.84804630e-03,  5.02026752e-02]],

        [[ 2.36631036e-02, -2.70783622e-02,  3.71252708e-02, ...,
           4.65550348e-02, -1.89733915e-02,  3.64322923e-02],
         [-4.67019761e-03,  5.03123179e-02,  6.48181746e-03, ...,
          -6.48592189e-02, -6.63839132e-02, -5.40989190e-02],
         [-5.26184030e-02,  1.82194617e-02, -4.22346964e-02, ...,
           2.60803103e-02,  1.70125868e-02, -2.72945352e-02],
         ...,
         [-2.41651554e-02, -4.39626575e-02,  2.05215495e-02, ...,
          -3.01623195e-02, -1.17921922e-02,  1.82504822e-02],
         [-4.77354974e-02,  4.86617722e-02,  6.13554083e-02, ...,
          -1.77080352e-02, -2.41116434e-02,  4.73576970e-03],
         [ 4.52336110e-03, -7.26735359e-03,  4.25215662e-02, ...,
          -5.10507300e-02,  1.92500127e-03, -6.79922923e-02]],

        [[-5.58893345e-02, -6.04577921e-02,  4.21553925e-02, ...,
           5.12184054e-02,  3.06696240e-02,  6.24560416e-02],
         [ 6.72664121e-02, -3.61302085e-02,  2.12544692e-03, ...,
           6.32960210e-03,  8.52242392e-03, -7.58096054e-02],
         [ 1.51438154e-02, -6.96408749e-03, -4.68266122e-02, ...,
           3.33183655e-03, -9.95058566e-03, -9.50042158e-03],
         ...,
         [ 5.69294579e-02, -6.39759153e-02,  8.37178342e-03, ...,
           1.23736132e-02, -7.70441536e-03, -2.49232370e-02],
         [-3.09770107e-02, -1.74299106e-02,  1.64453723e-02, ...,
           1.23338196e-02,  6.06700918e-03, -4.71974686e-02],
         [ 2.16348097e-02,  1.18333595e-02,  3.32373716e-02, ...,
          -2.59659830e-02, -2.55124159e-02, -6.47480115e-02]]]],
      dtype=float32), array([-5.64293098e-03,  3.98789160e-03, -5.22534037e-03,  9.31878481e-03,
        1.34812314e-02, -6.78219181e-03,  1.80307555e-03, -1.70905638e-04,
        1.12896888e-02,  7.32443342e-03,  1.33300358e-02, -9.57429688e-03,
       -1.69313874e-03,  2.23507010e-03,  2.77147014e-02, -1.25803370e-02,
       -5.76320896e-03, -3.69112776e-03, -1.52220652e-02, -3.11168726e-03,
       -5.33278566e-04, -1.52241311e-03, -1.04271788e-02, -8.01806618e-03,
       -3.24144983e-03, -5.70087042e-03, -5.04290359e-03, -1.05083650e-02,
       -1.61721036e-02,  2.03247560e-04,  5.98837808e-03, -1.29439235e-02,
       -2.67018424e-03, -4.99401474e-03,  5.51783014e-03, -1.06911808e-02,
       -2.99930619e-03, -1.13494871e-02,  1.06008546e-02, -1.95318405e-02,
       -1.59043749e-03, -4.04269155e-03,  2.35576984e-02, -6.55101240e-03,
        5.17484965e-03, -1.15296636e-02, -1.69731099e-02,  1.75965279e-02,
        1.43857831e-02,  1.12006674e-02, -1.39360279e-02,  7.09756976e-03,
       -1.77683064e-03,  1.70352999e-02,  5.91329765e-04,  1.82386506e-02,
        1.25106080e-02,  2.16872757e-03, -2.87021417e-02, -2.93809664e-03,
        6.72501326e-03,  1.65354542e-03,  5.83650498e-03,  4.30355361e-03,
       -9.64833889e-03, -6.10564835e-03,  1.00506404e-02, -6.09456236e-03,
        9.80844907e-03,  1.06744459e-02, -3.06522381e-03,  7.86715560e-03,
       -5.14399074e-03, -4.64061653e-04,  2.43223291e-02,  6.57771155e-03,
       -2.08265055e-02, -3.72553011e-03,  2.63620410e-02, -1.16437627e-03,
       -4.23119077e-03,  9.15689487e-03,  3.28798383e-03,  9.46692162e-05,
        5.56015968e-03,  6.13841182e-03,  5.60122076e-03,  3.86649952e-03,
       -4.86543449e-03,  1.28643420e-02, -4.31316299e-03, -1.03789195e-03,
       -1.37991803e-02,  1.65267345e-02, -1.91764180e-02,  1.59626361e-02],
      dtype=float32), array([ 0.5610065 ,  0.08486335,  0.13977638,  0.05780849,  0.1838506 ,
        0.95435953, -0.24406007, -0.083914  ,  1.2607992 ,  0.5729026 ,
       -0.43383235,  0.66115034,  0.04946055, -0.3354032 ,  0.15273438,
        0.62724304,  0.5903187 , -0.6909706 ,  0.43920374,  0.17524484,
        0.1036484 ,  0.03649583,  0.61458063,  0.38833338, -0.5713763 ,
        0.12259832,  0.16051368,  0.7014417 ,  0.43998143,  0.03117654,
        0.33815777, -0.51874155,  0.09776236, -0.8000702 ,  0.3618537 ,
        0.21835825,  0.4747478 ,  0.48506117,  0.24660802,  0.752026  ,
       -0.27293786, -0.78041273,  0.4097773 , -0.48380324,  0.5229451 ,
        0.55237263, -0.4448581 ,  0.39226106, -0.27127224, -0.6453599 ,
       -0.9213849 , -0.24806747,  0.72216845,  0.01892036, -0.7005477 ,
       -0.01467154, -0.5255002 ,  0.65427315,  0.22685738, -0.14844461,
        0.18801467,  0.20351179,  0.4202221 , -0.27244014, -0.60209256,
        0.1342285 ,  0.4315374 , -0.33659226,  0.09129057, -0.6894573 ,
        0.05608778, -0.52991205, -0.13406068, -0.38296282,  0.09594984,
       -0.06384955,  0.4767789 ,  0.7686473 ,  0.3819877 ,  0.3076097 ,
       -0.3455461 , -0.41186035,  0.07749324,  0.576323  , -0.255298  ,
        0.31225622, -0.61815125, -0.2923877 , -0.01796887,  0.24646372,
        0.6985714 ,  0.67349255,  0.40968424, -0.20051955, -0.92810124,
       -0.11259931], dtype=float32), array([0.7689797 , 0.715789  , 0.9874694 , 1.0334455 , 0.41336787,
       0.9002933 , 1.026741  , 0.5789345 , 1.5053108 , 0.8152259 ,
       1.2232186 , 1.0811731 , 0.775029  , 0.73038775, 0.8007245 ,
       1.3762537 , 0.8258046 , 1.1791894 , 1.2086213 , 0.7234062 ,
       0.7670188 , 1.024567  , 1.1793987 , 0.7010966 , 0.8912057 ,
       0.86952466, 0.61815506, 0.78119856, 0.4560816 , 0.551754  ,
       1.2189596 , 1.0141315 , 1.2597122 , 1.2389398 , 0.68624634,
       1.1442599 , 0.7223328 , 1.0326495 , 1.1556541 , 1.1405724 ,
       1.1032143 , 0.55937576, 1.2543548 , 1.0039363 , 0.8068088 ,
       1.0592706 , 0.74379   , 1.0457823 , 1.0073335 , 1.5060859 ,
       1.7879611 , 0.7291889 , 1.1868376 , 1.2037975 , 1.3623149 ,
       1.7599642 , 1.3626517 , 1.0527519 , 0.7183671 , 0.84412974,
       0.654523  , 1.0391796 , 0.79072684, 0.8935667 , 0.77334744,
       0.8652694 , 0.7085409 , 0.85986114, 1.0246565 , 1.0839936 ,
       0.9956594 , 1.1020756 , 0.8350915 , 0.7691784 , 1.5381179 ,
       0.7803947 , 1.2501556 , 1.1430062 , 0.8326049 , 0.5213467 ,
       0.7532451 , 0.8470302 , 1.3466147 , 1.140171  , 0.48460087,
       0.6435343 , 1.2716677 , 0.6250815 , 1.3462197 , 1.8324044 ,
       1.0645819 , 0.8690241 , 0.54412335, 1.1352843 , 0.7328449 ,
       0.4925671 ], dtype=float32), array([[[[-0.00558161, -0.02009408, -0.02714945, ...,  0.00144845,
           0.009527  , -0.02364507],
         [-0.02138632, -0.00220323,  0.00587802, ..., -0.01475958,
          -0.00520112, -0.00624549],
         [ 0.02436231,  0.00502958, -0.00180939, ..., -0.02179094,
           0.01811269, -0.02299737],
         ...,
         [-0.00471751,  0.02242189,  0.00590124, ...,  0.01379823,
           0.02022305, -0.01536536],
         [ 0.01429904,  0.02025164, -0.01190627, ..., -0.01396483,
           0.02352393, -0.02353778],
         [-0.01763762,  0.02667326, -0.01258377, ...,  0.01291154,
          -0.02008531,  0.01627806]],

        [[ 0.00845859, -0.02910952, -0.01857946, ..., -0.01843816,
           0.02346899,  0.01244441],
         [-0.00030637,  0.0136734 ,  0.04093247, ..., -0.022397  ,
           0.00231853,  0.03191013],
         [ 0.02205964,  0.01839274, -0.01774514, ...,  0.00374461,
          -0.01015795,  0.00498956],
         ...,
         [ 0.00740676,  0.00659326, -0.02203169, ...,  0.01114077,
          -0.00339169, -0.01824478],
         [-0.00617656,  0.00197597,  0.01261425, ...,  0.01573722,
           0.03821   , -0.02567165],
         [-0.00877698, -0.00920458,  0.02249649, ...,  0.01004951,
           0.01312768,  0.01074435]],

        [[ 0.0172987 , -0.03508626,  0.02447511, ...,  0.02387019,
          -0.00711073,  0.0113172 ],
         [-0.00776104, -0.02108294,  0.01660579, ..., -0.00060206,
          -0.01371308, -0.01653042],
         [ 0.00998804,  0.01467589,  0.00893884, ...,  0.03844512,
          -0.01849804,  0.00804402],
         ...,
         [ 0.01052312,  0.00536108,  0.00047838, ..., -0.01851343,
          -0.01623164, -0.02250085],
         [-0.00100921,  0.01102446,  0.00562673, ..., -0.01090275,
          -0.02137217,  0.00057455],
         [-0.0053916 , -0.01057258,  0.00862344, ...,  0.02949748,
          -0.02152918,  0.01929711]]],


       [[[ 0.01578402, -0.02992816, -0.02464562, ...,  0.00589432,
           0.03745589, -0.00772481],
         [ 0.0138915 ,  0.01476344,  0.01272283, ..., -0.00947484,
           0.00556462, -0.02502347],
         [ 0.02408185, -0.01147669, -0.00108966, ...,  0.00846082,
           0.02261339, -0.02504697],
         ...,
         [-0.01787937,  0.02805911, -0.00592442, ...,  0.01598028,
           0.03938833,  0.01362239],
         [ 0.02596263, -0.00530091,  0.00129986, ...,  0.00901413,
           0.0077497 ,  0.0199758 ],
         [-0.00962388, -0.02363396, -0.02298915, ..., -0.01711737,
           0.03280997,  0.00259852]],

        [[ 0.0174547 , -0.0261407 , -0.02846796, ...,  0.00548291,
           0.04297898, -0.04064183],
         [-0.03080351,  0.01707629,  0.02028364, ..., -0.0243793 ,
           0.03196421,  0.0304453 ],
         [-0.00031652, -0.00339836,  0.0354045 , ...,  0.01075607,
           0.02164912,  0.00351674],
         ...,
         [-0.02927372,  0.01263789,  0.01031071, ...,  0.01601613,
           0.03609174,  0.00424188],
         [-0.00167871,  0.02077049, -0.02523705, ...,  0.02523606,
           0.03554157, -0.03221971],
         [-0.00696668, -0.0293811 , -0.02122913, ..., -0.00473286,
           0.02343542, -0.01833576]],

        [[ 0.0295163 ,  0.01322512,  0.02078523, ..., -0.01056343,
           0.02942578,  0.0155662 ],
         [ 0.01815029,  0.01023019,  0.01409008, ...,  0.01256532,
           0.01851793,  0.00365288],
         [ 0.01530614, -0.00027606,  0.04006629, ...,  0.02004095,
           0.00816021,  0.03015297],
         ...,
         [-0.02421366, -0.01280268,  0.01476781, ...,  0.02134494,
           0.01424967, -0.03642851],
         [ 0.02563032,  0.01038126, -0.01695376, ..., -0.01454842,
          -0.01445163, -0.00817543],
         [ 0.00986008,  0.01971743,  0.00883795, ..., -0.00835333,
          -0.00358226, -0.02671115]]],


       [[[ 0.00841168,  0.00670804,  0.02469712, ...,  0.00073979,
           0.03790791, -0.00802061],
         [-0.02260221, -0.01154088, -0.00879783, ..., -0.00479167,
          -0.02838376, -0.00130663],
         [-0.01980479, -0.02037951,  0.00684156, ..., -0.00408419,
           0.03502192, -0.02133949],
         ...,
         [-0.00808894, -0.00810898,  0.01563997, ..., -0.01886226,
           0.02897942, -0.00838858],
         [ 0.02916702,  0.01874658,  0.01786195, ...,  0.00226701,
           0.02113346,  0.01343839],
         [-0.02903486, -0.01929839, -0.02080423, ..., -0.02507808,
           0.00885726,  0.01110201]],

        [[-0.00490055,  0.02626592,  0.02321653, ...,  0.01070769,
           0.02664326, -0.01657055],
         [-0.01625521, -0.00733997, -0.01268316, ...,  0.0268082 ,
          -0.02224296,  0.02182036],
         [ 0.00422178,  0.01665868,  0.040572  , ..., -0.0030902 ,
           0.03138179,  0.02539352],
         ...,
         [-0.02948203, -0.0149777 ,  0.00839476, ...,  0.0152886 ,
           0.03215031, -0.02011378],
         [ 0.00184574,  0.0162096 ,  0.01363705, ...,  0.02935038,
           0.03336784, -0.03866517],
         [-0.02033496, -0.02731223, -0.00157763, ..., -0.01301653,
          -0.00796057, -0.03013053]],

        [[ 0.02887853,  0.00752777, -0.03730222, ...,  0.02570993,
           0.0136647 ,  0.0006712 ],
         [-0.02488539, -0.00295313,  0.00633496, ..., -0.01446194,
          -0.03247271, -0.01128902],
         [-0.01642152, -0.00308559, -0.02457777, ..., -0.00797323,
           0.00166924, -0.00783991],
         ...,
         [ 0.01355895,  0.0271819 ,  0.01336623, ..., -0.00275084,
           0.02149774, -0.03976374],
         [ 0.00659021, -0.01501509,  0.01813291, ..., -0.00480868,
          -0.01639771, -0.00924282],
         [-0.02726   ,  0.02499711, -0.02525433, ...,  0.01788586,
           0.01462646,  0.00821311]]]], dtype=float32), array([[[[-0.01400788, -0.04058649,  0.02830433, ..., -0.01200067,
          -0.0557965 , -0.04092402],
         [-0.01065317, -0.04413939,  0.02729042, ...,  0.04143525,
          -0.0560163 ,  0.00534293],
         [-0.04917545, -0.00625338, -0.03209439, ..., -0.00375811,
           0.05795545,  0.01324347],
         ...,
         [-0.04229047,  0.0450551 , -0.01915828, ...,  0.06065937,
          -0.04687533,  0.05074398],
         [-0.04883115,  0.0129462 , -0.05058264, ..., -0.04336728,
           0.04324631,  0.02689221],
         [-0.04569118, -0.05836412,  0.02851111, ..., -0.00785796,
           0.04962982, -0.04412704]],

        [[-0.02498452,  0.05424126, -0.0352068 , ...,  0.0584287 ,
          -0.01484589,  0.00060466],
         [-0.01443715, -0.00399202, -0.0219411 , ...,  0.00962228,
           0.00225535,  0.01470664],
         [ 0.02229881, -0.00652322, -0.0204968 , ..., -0.00628832,
           0.01203596, -0.07052579],
         ...,
         [ 0.02814794, -0.02911411,  0.04654876, ..., -0.02113956,
          -0.05925681, -0.06433856],
         [ 0.01533133, -0.05398788, -0.00010876, ...,  0.04575786,
           0.03193919,  0.01115513],
         [-0.05253092,  0.04640874, -0.02352641, ..., -0.0466536 ,
           0.00107486,  0.00863313]],

        [[-0.00915786, -0.0371561 ,  0.00706343, ...,  0.05896951,
           0.05188693,  0.01670865],
         [ 0.03975248, -0.01067511, -0.02680717, ..., -0.03668462,
          -0.0433154 , -0.02023663],
         [-0.00285632,  0.02174525,  0.03115193, ...,  0.01311468,
          -0.032242  , -0.04974137],
         ...,
         [-0.04751919, -0.00531161,  0.00414855, ..., -0.02896198,
          -0.0075504 ,  0.03164561],
         [ 0.00528007, -0.01647675,  0.0404273 , ..., -0.02446456,
           0.00310195,  0.02817044],
         [ 0.02705903,  0.02105839,  0.04388998, ...,  0.04708124,
           0.00272141,  0.05952964]]],


       [[[-0.0177409 ,  0.01748754, -0.02708626, ...,  0.00981708,
           0.03177169,  0.03256564],
         [-0.05634489, -0.05032443, -0.04247295, ..., -0.03711719,
           0.05374225, -0.04092116],
         [ 0.00170176, -0.03962171, -0.05204409, ...,  0.00820481,
          -0.01443484,  0.01058928],
         ...,
         [-0.07355281, -0.01556738,  0.02864558, ...,  0.06167622,
           0.04628854,  0.02131175],
         [-0.03417928, -0.0124186 , -0.05252033, ...,  0.05262793,
          -0.00573718,  0.03323399],
         [-0.07544547,  0.01690019,  0.04121422, ..., -0.00985106,
           0.04069445,  0.04838434]],

        [[ 0.06300485,  0.00597932,  0.01246179, ..., -0.00877726,
           0.03989196, -0.01937974],
         [-0.05769157,  0.02819068,  0.00864259, ...,  0.04365059,
           0.05534688, -0.00854297],
         [-0.00692914,  0.00883888,  0.02914542, ...,  0.02054063,
          -0.06421481,  0.02642464],
         ...,
         [-0.06544901,  0.03364707,  0.00831553, ...,  0.01144539,
           0.01202585, -0.04847465],
         [ 0.03994264, -0.04400675,  0.03330849, ...,  0.03308359,
           0.02289137,  0.02847621],
         [-0.04491688, -0.04859027, -0.06499625, ..., -0.06392115,
           0.04407847, -0.04592447]],

        [[-0.03627192,  0.06179332,  0.01665565, ..., -0.04541472,
           0.0156876 ,  0.0585241 ],
         [ 0.02389111,  0.03445809,  0.03897117, ..., -0.02445119,
           0.04061799,  0.00554026],
         [-0.04850631, -0.01188873, -0.0241464 , ..., -0.01808234,
           0.04813083, -0.00708963],
         ...,
         [-0.01256502, -0.01730952, -0.0128855 , ...,  0.04877504,
           0.01533768, -0.00365115],
         [ 0.00265748, -0.03506725,  0.04649865, ...,  0.03617827,
          -0.00050393, -0.04197438],
         [-0.07046799,  0.02056666, -0.01989446, ...,  0.00554406,
          -0.06650579, -0.05425334]]],


       [[[ 0.0098925 , -0.02248297,  0.00772673, ..., -0.04392948,
           0.02475389,  0.05085165],
         [-0.03236288, -0.04042364,  0.00373108, ..., -0.03193966,
           0.05122137, -0.01581037],
         [-0.03996309,  0.00390031, -0.00459011, ...,  0.03179003,
          -0.04121371, -0.02801672],
         ...,
         [-0.0167486 ,  0.06214712, -0.04164222, ...,  0.06429844,
          -0.00968391, -0.05960856],
         [-0.03291639,  0.03989991, -0.06455746, ..., -0.02240512,
           0.03270414, -0.07294398],
         [-0.04643289,  0.01609604,  0.02691208, ...,  0.01162896,
           0.02536384,  0.04987299]],

        [[-0.03514955,  0.02120248,  0.01043456, ..., -0.01071876,
          -0.03920027, -0.01197664],
         [-0.01473963,  0.01931675, -0.03277928, ...,  0.05171785,
           0.01487367,  0.0002402 ],
         [ 0.05634303, -0.0068603 ,  0.0289695 , ...,  0.00924064,
          -0.01064049,  0.02886646],
         ...,
         [ 0.02009253,  0.0442455 , -0.0093415 , ...,  0.06669136,
          -0.0680471 , -0.02978989],
         [-0.04697724, -0.0082737 , -0.01836526, ...,  0.02809925,
           0.0098612 , -0.05707591],
         [-0.06223526,  0.03839621,  0.03986022, ...,  0.05501447,
          -0.00962885,  0.01780217]],

        [[ 0.04741601, -0.02084435,  0.03104804, ...,  0.02159314,
          -0.04589517,  0.02541881],
         [-0.03218329,  0.04639157,  0.00798628, ...,  0.03551951,
           0.01122246,  0.00738897],
         [-0.03565248,  0.00452812,  0.04831376, ..., -0.05056253,
          -0.03772115, -0.00809287],
         ...,
         [ 0.02034376,  0.05912234, -0.00920007, ...,  0.07102279,
          -0.00868232, -0.06549835],
         [-0.06642617,  0.01643716, -0.05354646, ...,  0.02591518,
           0.0274832 , -0.02097424],
         [-0.0751077 ,  0.03475169, -0.04708678, ...,  0.05645514,
           0.01110739, -0.01742092]]]], dtype=float32), array([ 0.00492871, -0.00052121, -0.00568518,  0.0158205 , -0.02155546,
       -0.00064707,  0.0081996 , -0.00722169, -0.00984561, -0.00119539,
       -0.01272407,  0.01126577,  0.00654376, -0.00524072, -0.00769304,
       -0.00010095, -0.01014796,  0.02443666,  0.00932965, -0.00774316,
        0.00078861, -0.00901282, -0.00555417,  0.00977729, -0.0100942 ,
        0.00757189,  0.00575272, -0.00992407,  0.00947432, -0.01218583,
       -0.00408807, -0.00491627,  0.00360304, -0.00905788, -0.00196062,
       -0.00924733,  0.02887208,  0.01657131, -0.00118452,  0.0035934 ,
        0.00538602,  0.00065114, -0.00874439, -0.00302465, -0.00735858,
       -0.0140937 ,  0.01411854, -0.00705882,  0.01130076, -0.00249907,
       -0.0027823 ,  0.00446059, -0.00674331, -0.00853961,  0.01064784,
       -0.0024954 ,  0.01256052, -0.00374553,  0.00788388, -0.00723137,
        0.00420909, -0.00029676, -0.00704766,  0.01345754,  0.01302599,
        0.00075026,  0.01391013, -0.00946113, -0.00704772,  0.00189552,
        0.01301346,  0.00024068,  0.00463663, -0.01310123, -0.00268456,
       -0.01233883, -0.00588006,  0.01446316,  0.00316316, -0.00942575,
        0.00275127, -0.01536748,  0.02166324, -0.02577096, -0.00152665,
        0.00302744,  0.00032308, -0.00703628,  0.01353666,  0.00817159,
       -0.01923293, -0.01202523,  0.01511632, -0.00257057, -0.00150863,
        0.01003054,  0.00083181,  0.00742354,  0.00482768,  0.0017201 ,
       -0.00171342, -0.0009541 , -0.00520198,  0.01090861,  0.01062635,
       -0.0051264 ,  0.00134198, -0.01158349,  0.02011968,  0.00172754,
       -0.018828  ,  0.01269897,  0.00043512, -0.00895084, -0.00313193,
        0.01351597, -0.00126237,  0.00905011, -0.00135565, -0.02009592,
       -0.00291377, -0.00481363, -0.00361055, -0.00369177,  0.02578716,
       -0.01436762, -0.01352861, -0.01186172,  0.03008444,  0.00158647,
        0.00763559, -0.01116026,  0.01016223, -0.01006759, -0.01388508,
        0.01414158, -0.00385123, -0.00869137,  0.01004506, -0.00351019,
        0.00599923, -0.00296598,  0.00703193, -0.00697011, -0.00725117,
        0.00983347,  0.01599084,  0.00461018,  0.0137787 , -0.00996276,
        0.00455363, -0.00271164, -0.00791458, -0.00525543,  0.00884752,
        0.00748613,  0.00677226,  0.01841071,  0.00406721, -0.01796868,
        0.01010949,  0.01687171, -0.02052955,  0.01203745, -0.02312667,
       -0.01983552, -0.00281971,  0.00868425,  0.01567141, -0.01017851,
        0.02255362, -0.00787176, -0.01076901,  0.00033628, -0.00772496,
       -0.01347505, -0.00233453,  0.00405628,  0.00688041, -0.01665178,
        0.00012924, -0.0094126 ,  0.01381759,  0.02673167,  0.00520873,
        0.00021635,  0.00277136, -0.00479376, -0.00243165,  0.00153071,
       -0.00072284, -0.00474501, -0.00682738, -0.00798504, -0.00518155,
        0.03468556,  0.00531262,  0.00034768,  0.01049767, -0.00249748,
        0.00568042, -0.00997792,  0.01542055,  0.01688686,  0.00544158,
       -0.00133244,  0.02186412, -0.00432633,  0.01319771, -0.00027521,
        0.01371608,  0.00865975,  0.0003623 ,  0.00876741, -0.00841984,
        0.02347835, -0.00389201, -0.00422237,  0.00115484, -0.00531097,
        0.00914433,  0.00289126,  0.00607183,  0.02096841, -0.00086014,
       -0.01272624, -0.00763671,  0.0060191 ,  0.00105896,  0.00391546,
       -0.0021089 ,  0.00902431,  0.00523391,  0.01451476, -0.00819328,
        0.01496974, -0.02409622,  0.0022877 ,  0.00329784,  0.00245416,
        0.00472705, -0.02016444,  0.00916296, -0.01595592, -0.003426  ,
       -0.00234724, -0.00273675,  0.017052  ,  0.00942247, -0.00682003,
        0.0130486 , -0.00085352, -0.00963389, -0.00910742, -0.00911027,
       -0.00119626,  0.0130494 , -0.00611639,  0.01187593,  0.00165064,
        0.00290684, -0.01558515,  0.0093382 , -0.00731103,  0.01542656,
        0.00650204,  0.00595122,  0.01025819, -0.0023231 , -0.00763076,
       -0.00284626, -0.01829919,  0.00756519,  0.02169911, -0.01152374,
       -0.0033641 ,  0.01948421, -0.00851965, -0.0187172 ,  0.00283866,
        0.00114231, -0.01052116,  0.03040167,  0.00772388, -0.0076237 ,
       -0.014862  ,  0.01158654, -0.01596661, -0.01648282, -0.00593878,
        0.0028125 , -0.01161296,  0.01969035, -0.01052961, -0.00135902,
        0.00608114, -0.02283583,  0.0045904 ,  0.005161  , -0.00354846,
        0.00683996,  0.00831272,  0.00204599,  0.02417741,  0.00970491,
        0.00532026,  0.00133462, -0.00930041,  0.00580672, -0.01608011,
       -0.00015526, -0.01419824,  0.01145303, -0.00252122, -0.00629112,
        0.02464661,  0.00923481, -0.00806598, -0.02018014,  0.00033596,
        0.0031059 , -0.02027262, -0.00624453, -0.00520926,  0.01261578,
        0.01988526, -0.01163806,  0.00472689, -0.00258585, -0.00162328,
        0.02943649,  0.00867695, -0.00796769, -0.00817001,  0.00293166,
       -0.01189964, -0.00439816, -0.00995642,  0.01487834, -0.00329794,
        0.01587879, -0.00137723, -0.02035289, -0.00799717, -0.01510024,
       -0.00354722, -0.0008197 ,  0.010468  ,  0.03664791,  0.00302464,
        0.00371103, -0.00054574,  0.00755709, -0.00111883,  0.00940208,
       -0.00479801,  0.00776285, -0.00276462, -0.00085013,  0.01477359,
       -0.00675728,  0.01155391,  0.00160943,  0.00734029,  0.0054681 ,
       -0.01420148, -0.00330242, -0.00273097,  0.01791504, -0.00752376,
       -0.00480029, -0.00223651,  0.03513355, -0.03135217, -0.01615586,
        0.00997836, -0.00411657,  0.00704533,  0.023387  , -0.0305528 ,
       -0.01620499,  0.01225528, -0.02657594,  0.01019037], dtype=float32), array([ 0.6301833 ,  1.0907243 , -2.634372  ,  0.23066762,  1.3024303 ,
        1.83909   ,  0.74803853, -0.5692962 ,  0.2565306 , -2.2675958 ,
        1.3143864 , -1.0069008 ,  2.8790705 , -1.6186547 ,  1.2318386 ,
       -3.9887877 , -2.4298916 , -0.7281615 , -2.7337692 ,  2.0336857 ,
       -0.75588435,  0.03664201,  0.6866197 ,  1.5042136 , -3.0412698 ,
        0.99156046,  2.064553  ,  0.72179776, -0.32608292, -2.2946951 ,
        2.2504487 ,  2.2860825 ,  1.8685411 ,  2.1121306 , -2.432016  ,
        2.6381657 , -0.34261823,  1.2482699 , -0.3268622 , -1.0499616 ,
        0.5854046 ,  1.5192862 ,  0.07355692, -3.3168876 ,  0.4538006 ,
        0.5872767 , -0.3952712 ,  0.8533897 , -3.1255481 ,  1.557726  ,
       -0.33651343, -2.23411   ,  0.5854016 ,  1.8381433 ,  1.1013005 ,
        1.9677018 ,  0.43834955, -2.1891992 , -1.491949  ,  1.334603  ,
        0.13055821,  2.2270591 ,  0.70891833,  1.0715843 , -0.3816563 ,
       -3.4159079 , -1.1862775 ,  1.1445261 ,  1.3796928 ,  1.8567612 ,
       -2.1575205 , -0.03609439,  0.71852034,  1.606352  , -0.948145  ,
        2.147444  ,  1.971554  , -0.386571  , -0.8158077 ,  1.7201542 ,
       -2.347578  , -2.905354  , -3.341943  ,  1.0984435 ,  1.9112834 ,
       -0.03751628,  0.78140026, -1.79617   ,  0.5698734 , -1.067925  ,
        3.4069746 ,  0.3489979 , -2.241082  , -2.3072753 ,  2.3882415 ,
       -2.7513177 ,  1.2246069 , -0.23762661, -1.7431493 , -2.8439968 ,
        0.08300618, -2.9264216 ,  1.4541336 ,  0.55493885, -1.5144467 ,
       -0.30055013,  0.58169234,  1.1078577 , -0.22026195,  1.7620164 ,
        1.3696582 , -1.720082  ,  0.6476062 ,  1.9490012 ,  0.6112773 ,
       -1.2883265 ,  1.9415461 ,  0.19249038,  0.99938065,  0.24089383,
       -3.0362778 , -0.11522872,  0.84230834, -2.4968126 , -2.0884867 ,
        0.9448649 , -0.19767037,  1.2701932 , -0.6628141 ,  2.2450342 ,
       -0.75165856,  2.2050922 , -0.9249365 ,  0.86128503,  0.6115807 ,
       -2.4515593 ,  0.6292478 ,  0.7465583 , -2.277278  ,  1.8449923 ,
       -0.51634103, -1.0479399 ,  0.4267635 , -1.7991885 , -0.5790078 ,
       -0.8993915 ,  2.4340057 ,  1.0078442 , -0.20735931, -2.060044  ,
       -1.4043941 , -1.2897032 ,  1.5648053 ,  0.9019001 ,  2.3190439 ,
       -0.34746265, -1.6433997 , -1.6133162 ,  1.5504009 ,  0.48459628,
        1.1678607 , -1.8213476 ,  1.0032609 , -1.9677826 , -2.3398688 ,
        1.5345832 ,  0.28211004,  1.5368737 , -0.647962  , -0.34714153,
       -2.637122  ,  0.49348262, -1.4635141 ,  1.6813278 , -1.4770262 ,
        0.1002138 ,  2.4255638 , -0.03964088, -0.7689722 ,  1.4901607 ,
       -2.0677795 ,  0.72511995, -0.6118287 , -1.1785485 , -1.0625871 ,
        1.0571022 ,  0.7735473 ,  1.538075  , -0.4463691 ,  0.4679565 ,
        2.6636748 ,  0.63179404,  1.2947167 , -0.00551909, -2.2255583 ,
        0.19691679, -0.38246325, -2.0304086 ,  0.03479123, -0.60032314,
       -2.2731056 ,  1.6210965 , -2.0144951 , -0.3895553 , -1.9453481 ,
        1.5924234 , -1.1915656 , -1.4235768 , -1.2046751 , -0.9957572 ,
       -1.2873634 ,  2.5578907 ,  1.2554023 ,  0.46258575,  1.2559954 ,
       -3.2623956 ,  1.4329699 ,  0.2947909 ,  1.7803272 ,  1.5117928 ,
        1.0662768 ,  1.4310197 , -0.62576926,  0.8475836 ,  1.8197608 ,
        1.9483634 ,  0.6026005 ,  0.56050557,  0.9117473 ,  0.6674545 ,
        1.3348826 ,  0.5073266 , -2.046843  , -1.0592732 , -0.6960026 ,
        0.46944088,  2.5201635 , -2.5813322 ,  1.0690659 , -1.5551544 ,
        0.5475157 ,  1.7309409 ,  1.3894998 ,  0.29140106, -2.7848914 ,
        0.8351786 , -0.0823063 , -0.01560295, -2.8120492 ,  2.5281446 ,
       -0.7442228 ,  1.2945204 , -1.9299924 ,  2.432013  ,  0.89401376,
        0.08812761,  1.1940062 ,  2.9445279 , -3.1648753 ,  0.18748097,
       -1.7854381 ,  1.9950076 , -2.454534  ,  0.26343846, -1.4067391 ,
        0.69489944,  0.69069314,  0.41295403,  0.42972296,  2.1223745 ,
       -1.633291  , -0.11368785,  1.0798169 , -0.9907589 , -1.8840754 ,
       -0.5632708 , -1.656465  ,  0.37712026,  0.2663116 , -1.3812491 ,
        0.7774495 , -2.8161974 , -2.0031319 , -3.018806  ,  1.9431252 ,
        1.8542702 , -1.9811563 ,  1.5562404 ,  1.150862  ,  0.3610723 ,
       -1.3563766 , -0.2540397 , -0.18939233, -1.0596627 ,  0.49579775,
        0.25338396,  2.529146  , -0.9371467 , -2.0905035 ,  0.9940241 ,
        0.08657696,  1.0191092 ,  2.1586254 ,  0.2777833 , -2.0112529 ,
       -2.009312  , -1.872763  ,  1.3584107 , -0.41598   ,  1.9912313 ,
        1.9780207 , -0.00406766,  1.3507767 ,  1.7216824 ,  1.1628182 ,
       -0.3475967 ,  0.6862347 ,  1.2564371 , -1.4009006 , -2.4798293 ,
        0.8780047 ,  2.6379735 , -0.56097925,  1.1173968 , -2.6843333 ,
       -1.4137946 ,  0.5263174 , -2.5410163 , -0.38178906, -2.73104   ,
       -3.244873  ,  1.602519  ,  2.5942483 ,  0.96910965, -2.9805195 ,
        2.7332866 , -0.04579554,  2.837926  ,  1.4989915 ,  1.2811428 ,
       -1.8683554 , -1.4218799 , -0.30295148, -1.0846769 ,  1.8362668 ,
       -0.80941445,  0.7909222 ,  0.9787155 , -1.2056988 , -2.9982128 ,
        1.5137682 , -2.348736  , -0.98627055, -2.4203188 ,  0.6980021 ,
        0.93992555, -0.22699894, -1.7736163 ,  0.20756835, -1.7207174 ,
        2.2603226 , -1.3651183 ,  0.16944212, -1.1169125 , -1.4180102 ,
        1.8798937 , -0.8690543 ,  1.3884319 ,  1.9239426 , -1.0482408 ,
       -0.88460386,  1.2842561 ,  0.6897643 ,  1.1897272 ,  2.847918  ,
        1.2223577 ,  1.8286688 ,  2.9544175 , -1.9438175 , -2.073471  ,
        1.7976183 ,  1.4046593 ,  1.3897213 , -1.8092483 ], dtype=float32), array([ 3.493123 ,  4.6010604,  8.709659 ,  4.1024375,  5.4991803,
        7.370331 ,  8.8492365,  3.8472538,  9.768707 ,  5.6931396,
        5.7939725,  6.4500365,  8.80857  ,  9.201388 ,  5.355994 ,
       16.03497  ,  8.521355 ,  7.234917 , 10.614104 ,  5.6936464,
        5.2427106,  6.62945  ,  7.286687 ,  8.866217 ,  4.6063914,
        5.0724006,  7.5516677,  8.976219 ,  5.779394 ,  6.910474 ,
        7.8532686,  9.232618 ,  6.839505 ,  8.767839 ,  5.98406  ,
        7.136639 ,  5.957691 ,  5.2655306,  2.6568954,  8.018746 ,
        8.1569605,  7.612029 ,  5.588411 ,  9.016376 ,  4.0103703,
        4.920309 ,  8.729851 ,  3.3658917, 13.383093 ,  5.791394 ,
        6.876684 ,  3.7453554,  6.503109 ,  4.884912 ,  5.3281984,
        6.234086 ,  6.0942864,  8.116303 ,  4.420171 ,  4.701038 ,
        8.064749 ,  4.124598 ,  5.9017706,  6.3101263,  3.438169 ,
       14.46346  ,  7.364299 ,  6.5105844,  6.203552 ,  3.2898812,
       10.546294 ,  3.5651534,  5.5700502,  6.3318305,  8.938416 ,
        7.4145913,  5.6179314,  8.665163 ,  4.36871  ,  4.994574 ,
        9.829617 ,  8.909392 ,  8.263704 ,  3.874285 ,  6.7960377,
        7.0529237,  9.144861 ,  4.2048364,  3.0034995,  5.4591985,
        8.153152 ,  6.1468263,  9.948487 ,  4.8807535,  8.665242 ,
        9.782021 ,  7.9107614,  4.6597815,  6.8706527,  8.248862 ,
        1.4301835,  6.256875 ,  7.657724 ,  5.143904 ,  4.032131 ,
        2.1785812,  4.9770365,  4.2457   ,  8.250611 ,  6.4354687,
        6.3398104,  4.380055 ,  4.78176  ,  4.362899 ,  6.788942 ,
        2.563161 ,  5.033528 ,  2.5563736,  6.816434 ,  2.5214894,
        8.2546215, 10.408144 ,  2.282007 , 12.494977 ,  7.239312 ,
        3.287111 ,  4.668483 ,  3.2447286,  3.6155496,  6.957772 ,
        6.5504036,  6.4927225,  7.62568  ,  8.8296995,  4.156863 ,
        6.4994364,  8.227845 ,  4.000382 ,  9.580247 ,  4.28742  ,
        2.971545 ,  5.9139314,  4.6347947,  9.78434  , 13.022209 ,
        6.4097366, 12.034565 ,  1.6295596,  2.8406918,  6.469519 ,
        3.2839384,  3.376221 ,  5.5739675,  5.5609736,  7.197607 ,
        6.334092 ,  5.941548 ,  9.225804 ,  4.747161 ,  4.7016854,
        5.157922 , 12.169378 ,  4.861395 ,  5.9269156,  6.0408216,
        3.8764622,  6.0758066,  6.5095344,  4.0760283,  5.076808 ,
       13.781295 ,  6.3446436,  4.7216763,  4.9898596,  4.299321 ,
        7.69765  ,  6.4140067,  4.0511827,  4.7849545,  9.778264 ,
        8.770397 ,  6.6964355,  6.565511 ,  6.87116  ,  4.8718686,
        5.7072754,  2.7294703,  4.1655293,  3.1308732,  7.551504 ,
        9.295448 ,  3.7522447,  6.0047297,  6.882714 ,  7.074322 ,
        8.155119 ,  6.6175814, 12.999482 ,  3.6547961,  6.7124662,
        8.592915 ,  4.9047885,  9.623126 ,  6.6695504,  6.95074  ,
        5.261032 ,  3.384076 ,  7.3620358,  3.1246548,  6.935143 ,
        5.9737906,  9.211807 ,  5.727301 ,  2.9416554,  6.665013 ,
        7.494455 ,  8.851502 ,  3.6021683,  5.473074 ,  5.7135644,
        7.5732145,  4.602368 ,  5.0695415,  5.5325446, 11.974601 ,
        7.7856393,  8.665783 ,  8.962281 ,  4.3168874,  4.7959137,
        7.341809 ,  3.1319673,  7.2116127,  8.881087 ,  5.339667 ,
        3.8788283,  4.8458896,  5.511088 ,  3.8060477, 17.500765 ,
        7.167847 ,  5.9412303,  5.8649697,  6.0023813,  5.9980993,
        9.252727 ,  6.5665894,  5.608735 , 11.231765 , 13.526584 ,
        6.991314 ,  6.978116 ,  5.698566 ,  8.408292 ,  3.4838443,
        4.252982 ,  8.031032 , 11.2679205, 14.467213 ,  4.0198164,
        4.602432 ,  8.163497 ,  5.414664 ,  4.6660447,  4.106647 ,
        5.0853095,  6.2542496,  5.892888 ,  5.463473 ,  7.316662 ,
        5.6359935,  6.0520554,  6.023478 ,  6.2106586,  6.0514474,
        4.799191 ,  4.207237 ,  6.5505605,  8.219294 ,  5.615095 ,
        5.6181426,  7.8932524,  7.700853 , 11.885215 ,  6.8706436,
        5.0408883,  7.1144967,  4.4319143,  6.205218 ,  5.5632534,
        3.4300249,  2.4843707,  3.9017136,  7.40554  ,  5.202727 ,
        5.9926467,  8.563993 ,  6.7327175,  6.7246556,  4.346484 ,
        3.21587  ,  5.2703876,  5.6179776,  5.412298 ,  7.7235274,
        6.507811 ,  3.3945992,  5.6662416,  3.452791 ,  7.464987 ,
        6.5364995,  5.7698736,  8.755482 ,  6.2200255,  6.488128 ,
        5.2374744,  4.443105 ,  7.901394 ,  8.467689 ,  7.699541 ,
        5.392279 ,  6.082336 ,  2.6986582,  4.880686 , 12.285684 ,
        9.430892 ,  3.9626148, 12.070844 ,  2.8364115,  7.189479 ,
       17.248814 ,  5.4053802,  7.3075943,  5.289068 , 14.533999 ,
        7.28921  ,  3.8183897,  6.8384256,  7.437834 ,  3.7977095,
        4.1986966,  4.242008 ,  6.0229497,  4.5810666,  3.2610567,
        9.362894 ,  8.491209 ,  5.796901 ,  9.209724 ,  6.5252776,
        6.7257004,  8.793515 ,  4.522936 ,  6.0174026,  5.132415 ,
        6.7971272,  6.5592732,  6.5642257,  7.8640914,  6.2528067,
        5.1215916,  4.819362 ,  6.8566093,  4.4889045,  4.078486 ,
        7.04676  ,  5.272128 ,  6.0460567,  4.0487933,  3.6904893,
        8.694078 ,  4.097512 ,  4.0393414,  3.1039245,  8.690244 ,
        5.380797 ,  5.6955132,  5.9567275,  8.275332 ,  5.1887426,
        8.005375 ,  7.760152 ,  6.0923815,  8.7567215], dtype=float32), array([ 0.00506959,  0.00130985, -0.00064993, -0.00113836, -0.00098661,
        0.01326681,  0.00319984, -0.00245668, -0.00590955, -0.01426853,
        0.00621759,  0.01079036,  0.01952098, -0.00205185,  0.00830471,
        0.01374831, -0.02031048,  0.02302529, -0.01884546,  0.01188409,
       -0.01273353,  0.02484254, -0.00736827,  0.00545175,  0.00417818,
        0.00667215,  0.00934859,  0.00190699, -0.0068619 ,  0.00284007,
       -0.00168056, -0.00283463,  0.0125446 ,  0.00242745, -0.0011452 ,
       -0.00553929, -0.00932032,  0.01484074,  0.0246447 , -0.01207662,
        0.0003825 ,  0.00588787,  0.0144108 ,  0.01555591,  0.00080498,
        0.00155108, -0.0065844 ,  0.01014403, -0.01964325,  0.03438991,
       -0.00716284,  0.00758543, -0.0192706 ,  0.00682284, -0.01975892,
       -0.00791141,  0.00746295, -0.0137579 ,  0.02756443, -0.01612984,
       -0.01014252, -0.01779641, -0.01275267, -0.00798888,  0.00878725,
        0.00836783,  0.00331702, -0.01680901,  0.0004742 , -0.01195681,
       -0.00456235, -0.0097241 , -0.01036359,  0.00083857, -0.00500356,
       -0.00584469,  0.01281794,  0.00934425, -0.00502845,  0.00081972,
        0.02614695, -0.00072931,  0.00399436, -0.00987651,  0.02032478,
       -0.00331444, -0.00171433, -0.01013095, -0.00500764,  0.03171416,
        0.02573146,  0.02022724, -0.00130422,  0.00547646,  0.01234393,
        0.0069372 ], dtype=float32), array([-0.98395675,  0.7639603 , -1.1549826 , -0.38713482, -1.2414844 ,
        0.48985028,  1.4593747 , -0.7173962 , -0.6839301 , -0.02122257,
        0.24745663, -0.5202482 , -1.3926865 , -0.34954086, -1.3515038 ,
        0.9132232 ,  0.647197  ,  0.2665574 , -0.3188421 ,  0.09668032,
       -0.0796275 ,  0.49184588,  0.83088875,  1.4196455 ,  0.36926275,
       -0.702836  , -0.4763195 ,  1.1317513 ,  0.34232605, -0.43488073,
       -0.44843203, -0.2877383 , -0.10356402,  0.91161716,  0.7369272 ,
        0.6943936 , -0.6014313 ,  0.0577849 , -0.8602843 ,  1.6874021 ,
       -0.0499463 , -0.4467562 ,  0.45368597,  0.56047547,  0.6894646 ,
       -0.01293643,  1.0797416 , -0.05982465,  0.14789234, -0.17294289,
       -0.64449984,  0.367643  ,  1.1268064 ,  0.39019412,  0.9830812 ,
        0.97139543, -1.3360174 ,  0.90405357,  0.30830094, -0.7783569 ,
        0.6698524 , -0.84456474,  1.5039904 ,  0.7554414 , -0.22475189,
        0.44485947,  0.5866758 , -0.7672388 , -1.6520613 ,  0.4498927 ,
        0.27403504,  0.38147652, -1.0516489 , -0.37308887, -0.69590455,
        1.3787886 ,  1.2514952 , -0.4772547 , -0.04684997,  0.29682207,
       -0.06457359,  1.1290506 ,  1.1635568 ,  0.788899  , -0.3128457 ,
        1.222522  , -1.1620059 ,  0.47708914,  1.3928959 , -0.00828562,
        0.23164175,  0.04393588, -0.9071862 ,  0.99646866, -0.84631974,
        0.8511479 ], dtype=float32), array([2.9434636 , 2.189738  , 2.0365882 , 1.8462228 , 1.4102489 ,
       2.685296  , 2.233921  , 1.9024848 , 0.81308067, 2.7785442 ,
       1.5324355 , 4.9833765 , 2.7293801 , 1.8285834 , 2.2649288 ,
       1.2499944 , 1.2592093 , 1.6935332 , 0.9234197 , 3.101102  ,
       1.8680706 , 1.8096159 , 1.8330007 , 2.485     , 2.7373147 ,
       1.0223914 , 3.6338205 , 2.6408138 , 3.4088864 , 1.4145386 ,
       1.4831494 , 2.0259404 , 2.899552  , 4.1219473 , 2.4033427 ,
       1.698441  , 1.1937021 , 1.7070587 , 2.2079504 , 3.1093163 ,
       0.98137724, 1.451193  , 0.97550434, 1.9533149 , 2.8071527 ,
       2.8436177 , 2.7339058 , 1.4023267 , 1.59548   , 2.4915223 ,
       1.3692573 , 1.7642006 , 0.9136923 , 1.7493663 , 1.4825851 ,
       4.945873  , 1.5508924 , 1.6738098 , 6.4503803 , 1.3563483 ,
       1.3565637 , 1.3713539 , 2.9241128 , 3.3733187 , 2.0134094 ,
       1.3335253 , 1.9051406 , 0.8755076 , 6.3843117 , 1.4222898 ,
       2.9176488 , 1.9794497 , 3.3400507 , 1.0359268 , 2.2889528 ,
       2.471061  , 1.7920405 , 2.9357076 , 1.5318562 , 1.5256768 ,
       4.4623566 , 2.5262308 , 1.8816987 , 2.1424236 , 1.5847383 ,
       1.8994999 , 1.2743567 , 1.2913989 , 3.2879677 , 1.4954944 ,
       1.7153472 , 1.8527809 , 1.0284668 , 1.00544   , 0.8651955 ,
       4.5968084 ], dtype=float32), array([[[[ 0.06152323, -0.06213586,  0.02606434, ...,  0.07295677,
           0.02662028,  0.07345665],
         [ 0.0330985 ,  0.06039364, -0.0039318 , ..., -0.01635993,
          -0.06849953,  0.05986373],
         [-0.0275375 ,  0.00824418, -0.06641509, ...,  0.02459276,
           0.04969222, -0.08461276],
         ...,
         [ 0.04017799, -0.04771402, -0.06293971, ...,  0.02237889,
           0.03967959, -0.07025105],
         [ 0.07533674, -0.07007918, -0.02543043, ...,  0.03818911,
          -0.03813595, -0.06952127],
         [ 0.04445997, -0.0479777 , -0.04505515, ..., -0.07211453,
          -0.02585462, -0.01358717]]]], dtype=float32), array([-0.00907668, -0.01193265, -0.01216725,  0.01889088,  0.00394282,
        0.00384689,  0.00221709, -0.01373727, -0.01096759, -0.00383605,
        0.00661425, -0.01267434,  0.02177354,  0.00355759,  0.01779889,
        0.00743979, -0.0126866 , -0.01589072,  0.00332778,  0.01546617,
       -0.00355364,  0.00608459, -0.01589363, -0.00701889,  0.00427758,
        0.00255394, -0.0049202 ,  0.00663768,  0.00714725,  0.00877657,
       -0.01877456,  0.00479955, -0.00331673,  0.01105886,  0.0044912 ,
       -0.005943  , -0.01556931, -0.00563953, -0.0072286 , -0.01231229,
        0.00504811, -0.01970834, -0.01511617, -0.00541833, -0.00684777,
       -0.01042839,  0.00100716,  0.00040919, -0.00691526, -0.00649204,
       -0.00855602,  0.00791016,  0.00035254,  0.00494802, -0.00695808,
        0.00780729, -0.00091177, -0.01545656, -0.0085001 , -0.01818206,
       -0.00028929, -0.00031778, -0.00922338,  0.00734397,  0.01727492,
       -0.01296852, -0.01013875, -0.01447659, -0.00217849, -0.00264983,
       -0.00378044,  0.0010175 , -0.01210436, -0.00631755,  0.00082513,
       -0.01232474,  0.00836662,  0.00392778, -0.00135461,  0.01556897,
       -0.0036767 , -0.01009704,  0.02208741,  0.00491339,  0.0022773 ,
        0.00464841, -0.00340932, -0.00068058,  0.0178935 ,  0.00984308,
       -0.01319358, -0.00562617, -0.00124857, -0.01246991,  0.01254015,
       -0.0140892 , -0.00945093, -0.00735801,  0.00176347, -0.00311443,
       -0.00430512, -0.00394185, -0.01659646,  0.00090741,  0.00693847,
        0.00392363,  0.00087568,  0.0181733 ,  0.00801738, -0.00824563,
       -0.00726005,  0.00601106,  0.00607143,  0.00552558, -0.01166538,
        0.01390868, -0.00048589,  0.01477446, -0.01636164,  0.0185977 ,
        0.00202985, -0.00771429, -0.00439517, -0.00888287,  0.00168087,
       -0.00274201, -0.01641385,  0.01531223], dtype=float32), array([-1.7412937 ,  0.9858851 , -1.3715029 , -0.45350742, -0.53834194,
        0.15622085,  0.54683125, -0.34264988, -1.4256091 , -0.16077377,
       -1.0975739 , -0.5313204 , -0.22520956, -0.9618428 , -1.5244976 ,
        0.52768165,  0.15170144, -0.05908659,  1.0929927 , -1.2225304 ,
       -0.38541517,  0.3418027 , -0.11194018,  1.140128  ,  1.3136226 ,
        0.5903779 ,  0.15148804,  0.45311153, -0.85023785, -0.44061738,
       -0.5390101 ,  0.2433296 , -0.02404259,  0.6991948 , -1.0857004 ,
        1.3815706 , -0.55635357, -1.448337  , -0.01771241,  0.6532459 ,
       -0.93107706, -0.46257317, -0.7508323 , -1.0883683 ,  0.7049336 ,
        0.99794924, -1.9577162 ,  0.8465552 , -0.16092117, -1.4447488 ,
       -2.066494  ,  1.1267703 ,  1.136486  ,  0.263048  , -0.5461955 ,
        0.68076926,  0.1187073 ,  0.8388975 ,  0.5440905 , -0.5560773 ,
        0.02766488, -0.01168882,  1.1146467 , -0.47358313, -0.28962082,
        0.3311648 ,  0.6606927 ,  1.4589187 ,  0.87346655, -0.5932954 ,
        0.73713106, -1.6447228 ,  1.3901191 ,  0.83216417, -1.1171602 ,
        1.4206994 , -0.48385197,  0.74905306,  0.82975435, -0.55093586,
       -0.72182256,  0.7452316 , -0.84095836,  1.023463  , -0.58399653,
       -0.86295277,  1.1153855 ,  0.8030233 , -0.96228653, -0.7262974 ,
        0.18148005, -0.6012453 , -0.5552363 ,  1.0718709 ,  0.9340414 ,
        0.71878654, -0.29099485, -0.20462449,  0.3814576 , -0.06791408,
        2.079197  ,  0.23917334,  1.4065696 , -0.8266595 , -0.39582437,
       -0.97775817,  0.5201786 , -0.4973039 ,  0.24286309,  1.4988915 ,
       -0.26342052, -1.163718  , -0.67357004, -0.5321571 , -1.3757766 ,
        0.21619742, -0.14913093,  0.49103755,  1.5730726 ,  1.2630128 ,
        0.53770715, -1.0111414 ,  0.8122122 ,  0.5870999 , -0.5169714 ,
        1.2571833 ,  1.0037268 , -1.0249438 ], dtype=float32), array([2.7142632 , 2.4176672 , 3.6086614 , 2.4141343 , 1.5143087 ,
       1.8256259 , 2.2736263 , 1.8768443 , 6.55549   , 2.3180747 ,
       3.293216  , 2.913641  , 1.5198588 , 4.2284827 , 3.8600874 ,
       2.3806877 , 2.280869  , 1.3491366 , 2.1514754 , 3.7389054 ,
       3.242368  , 1.3240812 , 5.355538  , 2.5043344 , 1.875962  ,
       1.2493336 , 1.8346375 , 2.0101974 , 2.872526  , 1.902142  ,
       1.2793552 , 2.101739  , 2.4536974 , 1.9054495 , 2.4097667 ,
       4.1915483 , 1.4661388 , 7.28584   , 2.7662344 , 3.2468588 ,
       1.7733961 , 1.7756646 , 2.6834438 , 3.3190427 , 4.849668  ,
       3.202499  , 3.1347413 , 4.3871727 , 2.3396103 , 1.7237018 ,
       7.4974914 , 2.6298387 , 0.9941205 , 1.4363685 , 4.4771023 ,
       2.4901884 , 3.4688175 , 3.375317  , 3.1900678 , 1.0199718 ,
       1.2931854 , 2.4675114 , 3.296374  , 2.3556588 , 1.1595558 ,
       0.71847814, 2.2458742 , 7.2937517 , 1.9265612 , 2.3867173 ,
       4.56771   , 2.9422498 , 3.3283746 , 1.352664  , 4.7984433 ,
       2.080061  , 1.58647   , 1.4339769 , 2.6383562 , 2.133238  ,
       1.3296598 , 2.513913  , 6.817934  , 2.5683663 , 2.2181523 ,
       4.4533205 , 3.0052695 , 1.9201689 , 2.0347884 , 2.708887  ,
       3.067813  , 1.334894  , 1.9535418 , 1.0194408 , 1.1051799 ,
       2.8025177 , 2.3635547 , 2.7216914 , 2.008132  , 2.1209202 ,
       3.410569  , 1.2329048 , 2.9273236 , 3.5007253 , 2.2851155 ,
       5.395667  , 4.399889  , 2.260217  , 1.2081227 , 2.761401  ,
       3.0822475 , 4.063984  , 3.297355  , 1.8658161 , 1.770962  ,
       3.62102   , 1.048449  , 1.6413337 , 1.7618781 , 2.875873  ,
       1.9179043 , 5.237073  , 2.1743138 , 2.6183524 , 1.5344334 ,
       3.5968926 , 2.6667428 , 3.5804615 ], dtype=float32), array([[[[-0.02905328, -0.02832525,  0.02484311, ..., -0.03929779,
           0.03270459, -0.03172024],
         [-0.00461216,  0.0491956 , -0.03677776, ...,  0.03150245,
          -0.01067287,  0.03940313],
         [ 0.01788368,  0.01067207,  0.02057452, ..., -0.02900115,
           0.0117574 ,  0.02020493],
         ...,
         [-0.00902229, -0.00163656, -0.03019745, ..., -0.05907853,
          -0.01868534,  0.0418698 ],
         [ 0.04135307, -0.00014245, -0.025704  , ..., -0.01113851,
          -0.0188126 , -0.01480727],
         [-0.03692186,  0.04483104,  0.04033675, ..., -0.01215548,
           0.0062225 ,  0.02748333]]],


       [[[-0.05139098, -0.02120089,  0.01926452, ..., -0.03767096,
          -0.0299262 , -0.01510428],
         [-0.01445949,  0.03898233, -0.03202705, ..., -0.06099069,
          -0.0382125 ,  0.03454975],
         [-0.02089115, -0.04214204,  0.03942711, ...,  0.05306841,
          -0.05164629, -0.0177501 ],
         ...,
         [-0.01573628, -0.00893582,  0.02664617, ...,  0.01829498,
           0.06997789, -0.00153089],
         [-0.01561452, -0.04754699,  0.01503388, ..., -0.02875606,
           0.00191496,  0.03576025],
         [-0.02410652,  0.04194989,  0.04915375, ..., -0.02898008,
          -0.02494694, -0.04343938]]],


       [[[-0.02230339, -0.0428137 , -0.04966916, ...,  0.00913868,
           0.05512573, -0.03907392],
         [-0.00413004,  0.04201559,  0.05399597, ..., -0.03507881,
           0.01790184,  0.02314776],
         [-0.00889081, -0.04189961, -0.01362079, ...,  0.0293015 ,
           0.00544268,  0.0732516 ],
         ...,
         [-0.00880135, -0.01489907,  0.02465852, ..., -0.05270534,
           0.03154913, -0.04939372],
         [-0.01237153, -0.01781714,  0.00533858, ..., -0.03076431,
           0.00508754,  0.02333975],
         [ 0.0232861 ,  0.046263  , -0.04922409, ...,  0.02131665,
           0.00319592,  0.03945598]]],


       ...,


       [[[-0.04554573, -0.02380388,  0.05332154, ..., -0.00191808,
          -0.00397219,  0.04539041],
         [ 0.04306304,  0.04799988,  0.00106244, ...,  0.04608105,
          -0.01650173, -0.0396399 ],
         [-0.01118802, -0.02633112, -0.0143012 , ..., -0.045183  ,
           0.04390619,  0.00909273],
         ...,
         [ 0.00713806,  0.02109755, -0.02026876, ...,  0.0139799 ,
          -0.00636662, -0.0590437 ],
         [-0.04568729, -0.01756513, -0.01943738, ..., -0.04269607,
          -0.0141514 ,  0.04683332],
         [-0.03353735, -0.01191808,  0.04568546, ..., -0.00265557,
           0.01570982,  0.0115436 ]]],


       [[[ 0.00293533,  0.00567408, -0.0135342 , ..., -0.05813764,
          -0.0525468 , -0.038645  ],
         [-0.01019889,  0.02959571,  0.01203885, ..., -0.00117782,
          -0.06095954, -0.05532288],
         [ 0.0007929 , -0.04741153, -0.0335996 , ...,  0.00629566,
          -0.06198952,  0.02098336],
         ...,
         [-0.02458096,  0.00059332,  0.00836617, ...,  0.02518636,
          -0.0388355 , -0.04218851],
         [-0.01243238, -0.01111494,  0.06930314, ...,  0.00695244,
          -0.00437962, -0.0558044 ],
         [-0.05827663,  0.04668475,  0.05246931, ...,  0.03591867,
           0.04751717,  0.05348604]]],


       [[[-0.0376369 , -0.05623186, -0.01671219, ...,  0.00276382,
          -0.03027885,  0.01769317],
         [-0.031529  ,  0.04872798,  0.00122909, ...,  0.05114579,
           0.02849914,  0.01627562],
         [ 0.00996259,  0.00921206,  0.02204408, ...,  0.06694125,
           0.01476485,  0.02422857],
         ...,
         [ 0.04633771,  0.03131944, -0.01128627, ...,  0.00750383,
          -0.04719471,  0.01230161],
         [-0.01163273, -0.01079707,  0.01054212, ...,  0.01411185,
           0.03788782, -0.00835955],
         [-0.02103992, -0.04820121,  0.01407712, ...,  0.0510576 ,
           0.00083658,  0.03442799]]]], dtype=float32), array([ 0.00252084, -0.00702287, -0.00606512, -0.01170791, -0.00184628,
        0.00776994, -0.00598382, -0.01838695, -0.00921899, -0.00168376,
       -0.00871091, -0.01221527,  0.01094156,  0.01615479, -0.00500672,
       -0.00853202,  0.00806435,  0.00930342, -0.00494808,  0.00377838,
        0.01750096, -0.00066002, -0.0134382 , -0.00202654,  0.01871254,
        0.00851075, -0.00647461, -0.00026031, -0.00334164, -0.00639603,
        0.01395122,  0.01841117,  0.007433  ,  0.02139182,  0.00044895,
       -0.003526  ,  0.00052124, -0.00671815,  0.01035685, -0.00425726,
       -0.00555821, -0.01812024,  0.02939789,  0.02087053, -0.00168576,
       -0.00076906, -0.00548447, -0.01436262, -0.00017435,  0.00983561,
       -0.01124365, -0.01467293,  0.00165434,  0.0144881 , -0.00086947,
        0.00242265, -0.00225284, -0.00026378,  0.00159158, -0.00704481,
       -0.01085134,  0.00913891, -0.01498635, -0.01734915,  0.0044436 ,
        0.0022858 ,  0.00052516, -0.00140037, -0.00883989,  0.00213407,
        0.00038327, -0.00524424,  0.00998436, -0.01380146, -0.01514121,
       -0.01379228, -0.00993081, -0.02362093,  0.0054259 , -0.00166603,
       -0.01067939, -0.00444695, -0.00079594, -0.00655706, -0.00040126,
       -0.0011523 , -0.00043393,  0.00796314, -0.00761698, -0.00179523,
        0.00058128,  0.0084851 , -0.01651995,  0.00455785,  0.01549301,
       -0.00738911, -0.01467514, -0.01000196,  0.00894472, -0.00934324,
       -0.00311554,  0.00399934, -0.00167412,  0.00605258, -0.00477686,
        0.00078146,  0.00672264, -0.01456269, -0.00139194, -0.00247103,
        0.01201082,  0.01686109,  0.00450697, -0.00130398, -0.00307133,
       -0.00277275, -0.00020452,  0.01207087,  0.00021702, -0.00484928,
       -0.01995617, -0.01112864, -0.0036412 ,  0.00628867,  0.00244655,
       -0.00679517,  0.00464515,  0.00544487], dtype=float32), array([-0.1852087 ,  0.6535367 ,  0.82483745, -0.12192792, -0.19101925,
        0.058146  ,  0.9862786 ,  1.1991395 ,  0.5705835 , -1.1494704 ,
        0.25105292,  0.5368846 ,  0.19319935, -0.8322091 ,  0.7530294 ,
        0.46417826, -0.6581179 ,  0.33261254,  0.4051432 , -0.2150321 ,
       -0.07134951,  0.3863002 ,  0.36921132,  0.6014745 ,  0.14094754,
       -0.04788635, -0.19534995,  0.19261836, -0.4546612 ,  0.90472704,
       -0.8210776 , -0.06929396,  1.0046595 , -0.42348847,  0.69370437,
       -0.16530855,  0.4841873 ,  0.38427177, -0.18655886,  0.2379217 ,
       -0.7064255 ,  0.28017095, -0.5447372 , -0.41487697,  0.73677623,
        0.28768602,  0.23952213,  0.7745109 , -0.7555998 , -0.22420667,
       -0.71469975,  0.88257855,  0.53487784, -0.50059766,  0.7148566 ,
       -0.8700984 ,  0.5366443 , -0.7638505 ,  1.038321  ,  0.49783218,
        0.04740578,  0.45607263,  0.40473905,  0.24431786, -0.4287033 ,
       -0.20715927, -0.33910787, -0.10964403,  0.3866734 ,  0.05290622,
       -0.66377676,  0.47775254,  0.59041685,  0.481359  , -0.7743726 ,
       -1.2830136 , -0.688357  , -0.9064308 , -0.41975313,  0.45905656,
        0.27329388, -0.5691558 ,  0.7855039 , -1.0338358 ,  0.05178185,
        0.1335433 ,  0.36849207,  0.4932765 ,  0.4868069 ,  0.6701272 ,
        0.4492645 ,  0.7710817 ,  0.07831675,  0.19968666,  0.3837827 ,
        0.5846512 ,  0.5008665 , -0.8877293 , -0.6701021 ,  0.01368773,
        0.03068959,  0.48228204,  0.53118896,  0.17455961, -0.5172988 ,
       -0.2324932 , -0.48647738,  0.14330277,  1.3186014 , -0.67746747,
        0.6844959 ,  0.30496845,  0.43587178,  1.0015217 , -0.08253508,
       -0.15557276, -0.14436157, -1.1770188 ,  1.1614957 ,  0.53477263,
        0.2726971 ,  0.04087413, -0.8958447 ,  0.40653378,  1.0577059 ,
       -0.63493717, -0.14399655, -0.92543423], dtype=float32), array([1.8836691 , 2.2038436 , 1.5872405 , 1.0839237 , 1.0612327 ,
       2.3895307 , 2.3300831 , 1.6956713 , 1.9311264 , 1.2596582 ,
       2.366397  , 2.8990982 , 1.4265807 , 2.1130998 , 2.2074242 ,
       1.2075565 , 1.0558054 , 1.9815861 , 1.5889564 , 0.7550145 ,
       4.0473943 , 2.351371  , 1.4347701 , 1.7248298 , 1.7853061 ,
       1.5922692 , 1.244852  , 1.4352491 , 2.137773  , 2.6754475 ,
       1.7735528 , 1.5344721 , 2.2116256 , 0.9581033 , 1.5666794 ,
       1.9729633 , 3.2098215 , 2.2723951 , 2.7633574 , 1.8500212 ,
       1.6188241 , 2.904437  , 3.1191552 , 3.5287611 , 1.9217291 ,
       2.0075803 , 1.0000378 , 2.6888301 , 3.4418151 , 1.3236127 ,
       1.197138  , 1.7337446 , 2.5124764 , 0.9417671 , 1.4968554 ,
       1.9555658 , 0.94433653, 2.3320324 , 3.314722  , 1.1364664 ,
       2.7610104 , 1.7521199 , 1.5360047 , 2.4287522 , 0.89511734,
       0.9834791 , 2.5361035 , 2.7569346 , 1.2735499 , 2.5393553 ,
       2.3019347 , 1.4171582 , 1.9205822 , 1.6391116 , 1.3010336 ,
       2.0626178 , 1.2902262 , 1.2969791 , 5.047134  , 1.0960213 ,
       1.8841182 , 1.9202534 , 3.3633106 , 2.0569646 , 2.7080383 ,
       1.7968405 , 0.97178334, 0.6713917 , 3.153244  , 0.9844741 ,
       1.4919    , 2.1222112 , 3.2160463 , 2.0621214 , 0.7872474 ,
       2.522933  , 0.8562936 , 2.3135772 , 1.0068012 , 1.336912  ,
       1.1248715 , 1.7975862 , 3.1799855 , 1.5043004 , 4.5324693 ,
       0.788305  , 2.1652253 , 0.98462445, 1.9440103 , 2.7255297 ,
       1.6326538 , 1.7503632 , 1.5443627 , 1.5227247 , 0.8782384 ,
       1.1000761 , 1.9354732 , 4.1240306 , 2.5587015 , 1.0245239 ,
       0.47162956, 1.4183947 , 1.4184952 , 2.3032334 , 2.2629726 ,
       1.46805   , 1.402463  , 1.6453698 ], dtype=float32), array([[[[-0.03059115, -0.05343729, -0.03344223, ...,  0.02362751,
           0.09534857,  0.03758318],
         [-0.01287806, -0.01322891, -0.0641963 , ...,  0.00773798,
          -0.07604284,  0.06598155],
         [ 0.01380634, -0.02466763,  0.02613229, ..., -0.02289536,
           0.03315883,  0.02075616],
         ...,
         [-0.02193543, -0.02085668, -0.07184809, ..., -0.01443939,
          -0.05787757,  0.02871319],
         [-0.02151367,  0.00512117, -0.05650695, ..., -0.05461022,
          -0.05844985, -0.04154716],
         [ 0.02000694,  0.03209414,  0.05742691, ...,  0.04841201,
          -0.00419338,  0.01877318]]]], dtype=float32), array([[[[-0.04717901, -0.00659309, -0.04126739, ...,  0.03211784,
           0.00023187,  0.00248583],
         [ 0.01843303, -0.03485014,  0.05390527, ..., -0.01518818,
          -0.03752324, -0.02990675],
         [-0.06557234, -0.00557218, -0.00347851, ..., -0.03284891,
          -0.00499446,  0.02761987],
         ...,
         [ 0.03723995,  0.03958384,  0.03373494, ...,  0.0285816 ,
          -0.0536167 ,  0.04674376],
         [-0.03701962, -0.03756602, -0.03764256, ...,  0.04528448,
           0.05504849,  0.02466441],
         [-0.02219957, -0.0217299 ,  0.02996555, ..., -0.0135313 ,
          -0.0498769 , -0.03441456]],

        [[ 0.03700047,  0.02296399, -0.04291714, ...,  0.01524856,
           0.00790005,  0.03092977],
         [-0.02564107, -0.03698084, -0.05393238, ..., -0.03945541,
          -0.03187446,  0.05466226],
         [-0.03400599,  0.04888831, -0.017215  , ..., -0.02733333,
           0.03020142,  0.0217337 ],
         ...,
         [ 0.02456255,  0.05388757, -0.06618366, ...,  0.05405112,
           0.006223  ,  0.03523758],
         [-0.02093499,  0.04144009, -0.0013743 , ...,  0.00193999,
          -0.04632289, -0.01793719],
         [ 0.0485175 ,  0.04847428, -0.03827694, ..., -0.01380069,
          -0.03925264,  0.03396359]],

        [[-0.01163284,  0.0623213 ,  0.02791883, ..., -0.06093701,
          -0.02009897, -0.00048675],
         [-0.02940628,  0.05824869, -0.00699903, ...,  0.00643183,
           0.03421763,  0.05288763],
         [-0.05813047,  0.00197935,  0.00176267, ..., -0.00064966,
           0.01288686,  0.03494488],
         ...,
         [ 0.02816577,  0.00264079,  0.03109767, ...,  0.05941598,
          -0.00406986,  0.04537556],
         [ 0.01490649,  0.05826431,  0.04886783, ..., -0.01142457,
           0.02899411,  0.02491488],
         [ 0.02541167, -0.04624949, -0.06422029, ...,  0.03209104,
           0.04897019, -0.01195844]],

        ...,

        [[-0.02021344, -0.02622658,  0.01033522, ..., -0.06497283,
           0.04018003, -0.01872526],
         [ 0.05049616,  0.04288213, -0.03566846, ..., -0.06247198,
           0.03040286,  0.01357181],
         [ 0.00574624,  0.05456993,  0.01766016, ...,  0.02361194,
           0.01334577,  0.04647641],
         ...,
         [ 0.03577769, -0.0521551 ,  0.02601996, ..., -0.04259234,
           0.0097407 , -0.0368612 ],
         [-0.05351157,  0.01495189,  0.04052429, ..., -0.01253565,
          -0.01169888, -0.04966564],
         [-0.06181733,  0.00648172,  0.02114096, ..., -0.02584684,
          -0.03275896,  0.03016229]],

        [[ 0.03827055,  0.0406896 ,  0.03416076, ..., -0.03504625,
          -0.0193229 ,  0.01711421],
         [ 0.05023404, -0.03500523, -0.03641158, ...,  0.01982321,
          -0.04101051,  0.02387785],
         [-0.01906467,  0.03219288,  0.00170137, ..., -0.00933146,
          -0.05288879, -0.01749191],
         ...,
         [ 0.03509109,  0.05522591,  0.01589323, ...,  0.01149038,
           0.02823634,  0.00916329],
         [-0.05405965,  0.02758395,  0.03702663, ...,  0.03589137,
          -0.06053032, -0.00234236],
         [-0.03874191, -0.02591488, -0.01046618, ...,  0.01436599,
          -0.0032502 , -0.05438571]],

        [[ 0.03616401, -0.01505061, -0.04152681, ..., -0.00463677,
          -0.05326021,  0.01379524],
         [-0.05067744, -0.00936708,  0.0353523 , ...,  0.00170343,
           0.01323397,  0.02110183],
         [ 0.02118446, -0.01021524, -0.00023099, ..., -0.01750995,
          -0.05024596, -0.05157868],
         ...,
         [ 0.03692489, -0.01906009,  0.05488729, ...,  0.01155302,
           0.00922842, -0.01758185],
         [-0.02980263, -0.00352416,  0.02195073, ...,  0.02308944,
           0.0421494 ,  0.02667869],
         [ 0.021801  ,  0.02054974,  0.01393145, ...,  0.06030855,
           0.0254598 , -0.04286399]]]], dtype=float32), array([-0.01723366,  0.00600873, -0.00841176,  0.02083001, -0.00438448,
       -0.03292637, -0.02055765, -0.01692255, -0.02738888, -0.00776671,
        0.02210693, -0.00491501, -0.00038905,  0.00578874, -0.02435714,
        0.01251223,  0.01400366, -0.00735698, -0.00105429, -0.00488737,
        0.00349886,  0.00187702, -0.01036144, -0.00897758, -0.00865845,
       -0.0025128 ,  0.01061211, -0.01032035, -0.00302935,  0.00406301,
        0.00817003,  0.00075171,  0.00158295, -0.004625  ,  0.01821757,
       -0.01733067, -0.01789748,  0.00975323, -0.00891111, -0.02084431,
        0.00255879, -0.00237263,  0.00431232, -0.01342201, -0.00834762,
       -0.00975192,  0.01340697,  0.01204377, -0.00714434,  0.00324765,
       -0.02090872,  0.00411983, -0.00487824,  0.00522202,  0.01171097,
        0.00411741,  0.02515743, -0.00486332, -0.01105065, -0.00481104,
       -0.01097312,  0.00369574,  0.00909879, -0.00201227,  0.00059227,
       -0.00753157,  0.00464374,  0.0071405 , -0.00102408,  0.0094674 ,
        0.01323332, -0.00096049,  0.00010125, -0.02219829,  0.00548448,
        0.00732968, -0.00481541,  0.02078143, -0.00162956,  0.00712007,
        0.01566459,  0.00029051, -0.00889062, -0.0204235 , -0.00339794,
        0.01401123,  0.00012827,  0.00465023,  0.01698596, -0.00141543,
       -0.00041634,  0.003563  ,  0.00181215, -0.00117493,  0.00271179,
        0.00706964,  0.00824572, -0.00499649,  0.02600594, -0.00369195,
       -0.00255875, -0.02190364,  0.0067031 , -0.00559425, -0.01026652,
        0.00739746,  0.01299203,  0.0073938 ,  0.00545693, -0.01620012,
       -0.00732963, -0.0039041 , -0.01167913, -0.01007691, -0.00399462,
        0.02523529,  0.00308539, -0.00110565, -0.00659204, -0.01043733,
       -0.00047216,  0.00806476,  0.02627904,  0.00559504,  0.00133216,
        0.0109828 ,  0.00199284,  0.00284816], dtype=float32), array([ 1.8707101 , -0.23675308,  0.6562707 , -0.84010565, -0.24776332,
        0.44560477,  0.05416252,  1.16381   ,  0.04018846,  0.00441063,
       -1.6889203 , -0.31213862, -1.5492196 ,  0.204485  ,  0.06875224,
        0.14390382, -0.9284505 ,  0.28461596, -1.9434259 , -0.78319335,
       -1.114552  , -0.37545243, -1.071404  ,  0.06963836,  0.17587733,
        1.1129147 , -1.8018783 ,  0.88083905, -0.49508974,  0.35645446,
       -0.19984119, -0.42685863,  1.9299026 , -1.6504096 , -0.8801899 ,
        0.89312875, -0.246951  ,  0.71542156,  0.96783984,  0.4357831 ,
       -0.7621108 ,  0.23692133,  1.4616657 ,  0.23106688, -1.085608  ,
        1.0080287 , -0.45726377, -0.9471408 , -0.04779583, -0.31502107,
        1.5778021 , -0.92239493,  0.5014415 , -0.14158165, -0.3963703 ,
       -1.265885  , -0.2889658 , -0.00242754,  0.7492104 ,  1.0526509 ,
        0.27622664,  0.73986685,  0.40762806,  1.2806134 ,  0.82047874,
       -0.25718006, -0.07485572,  0.2416725 ,  0.6553499 , -0.79189575,
        0.21342999,  0.23341516, -1.1188141 , -0.08454116, -0.66287965,
       -0.10828396, -0.82677186,  0.21391322, -1.0368136 , -1.0115654 ,
       -0.8458019 , -0.2691669 , -0.9756779 ,  0.7635584 ,  0.21877548,
       -1.3030213 , -0.4398143 ,  0.45980945, -1.0614306 ,  0.57052696,
       -0.24113369,  0.5303972 ,  0.34121406,  0.25653678,  0.4695168 ,
       -0.02898769, -0.4973888 , -0.39881968, -0.14658636, -0.9186409 ,
       -1.0484091 ,  1.0406419 ,  0.69737333, -0.3549338 ,  0.27528098,
       -2.274676  , -0.4951812 ,  0.6639274 , -0.7935834 ,  0.6172272 ,
        0.3932132 ,  0.5387575 ,  0.30081674, -0.22860737,  0.20918821,
       -1.0225602 ,  0.3229718 ,  0.2742635 ,  0.2544255 ,  1.0389444 ,
       -0.05197144,  0.80350685, -0.13385968,  0.5080863 ,  0.93857396,
       -0.34289128,  0.829796  , -0.48792055], dtype=float32), array([4.884481 , 3.600473 , 4.793504 , 5.0664077, 1.2085961, 3.0192165,
       1.8092808, 2.2491271, 1.1414456, 2.1306822, 4.206392 , 5.1115956,
       4.33582  , 3.611659 , 1.530837 , 3.4322138, 2.377911 , 4.5953965,
       4.092746 , 2.8243642, 2.379482 , 5.435656 , 2.604895 , 4.1785703,
       3.1865144, 1.9872795, 3.9302773, 3.3085423, 3.9394925, 1.6367947,
       2.5990458, 1.0134866, 4.6180444, 5.1423125, 2.8428614, 3.1848273,
       1.6284201, 2.5441303, 2.1300874, 2.5976257, 6.3862944, 7.55125  ,
       3.5622375, 2.912086 , 2.3463619, 2.5157712, 1.6763117, 2.298099 ,
       4.2106714, 2.0321689, 2.3014617, 3.320574 , 2.978547 , 3.8811314,
       4.176335 , 4.2637563, 2.9849617, 1.3794702, 2.993615 , 5.9022326,
       6.9426956, 1.2030063, 4.493549 , 3.8151731, 2.7264547, 3.2712643,
       1.3535036, 6.8472548, 2.883899 , 2.5485392, 2.5701551, 2.308483 ,
       2.522217 , 1.4986815, 3.9400504, 4.081946 , 1.2452111, 3.1185322,
       1.7925454, 2.3240788, 5.4222894, 3.3703363, 4.3679795, 5.2387075,
       3.8194058, 4.4852343, 6.614948 , 2.9892125, 3.0407379, 2.4508417,
       3.2698433, 3.5243366, 1.7947297, 5.6340322, 6.3510246, 3.0882094,
       2.3873966, 2.8606777, 5.0671105, 2.180256 , 1.8833988, 2.2489393,
       2.2850704, 5.4560637, 4.117597 , 4.6390157, 2.5597818, 2.5819693,
       3.1063502, 2.4772463, 7.012214 , 7.6145535, 3.0511487, 1.1460067,
       2.8926105, 3.0205617, 2.5272434, 1.8785177, 2.0613387, 1.7921001,
       4.0079093, 4.445394 , 2.564876 , 2.1024866, 2.365585 , 8.030717 ,
       5.74311  , 4.7321734], dtype=float32), array([ 1.19529432e-02, -1.25411293e-03, -1.02629820e-04,  1.64172761e-02,
       -2.05370807e-03,  8.93547607e-04, -4.30771150e-03,  2.06155377e-03,
       -1.03412373e-02, -1.26357041e-02,  6.68893242e-03, -2.33209338e-02,
       -4.84311488e-03,  7.96126761e-03, -9.59782023e-03,  2.53921375e-03,
       -8.19669105e-03, -1.95879098e-02, -3.90353613e-03,  8.99487454e-03,
        1.93010364e-03,  9.52705462e-03, -9.53753199e-03,  9.06358194e-03,
        4.66555543e-03,  1.05909137e-02, -1.65401436e-02,  7.84633309e-03,
       -5.17394487e-03, -1.63795296e-02, -1.68795455e-02, -2.91046547e-03,
       -2.41387021e-02, -1.00465398e-02, -1.10589638e-02, -2.60592462e-03,
       -5.27161127e-03,  4.11141198e-03,  9.77343880e-03, -1.14651518e-02,
       -4.32592677e-03,  1.30177001e-02, -1.10535985e-02, -8.73632322e-04,
        5.51702734e-03, -1.06092473e-03, -1.18903667e-02, -1.61107292e-03,
        9.93023533e-03, -6.72982074e-03,  1.08806221e-02, -1.36470119e-03,
       -4.46767639e-03, -5.33546740e-03,  2.77792476e-02, -1.13902963e-03,
        6.96119154e-03, -7.82121718e-03, -1.66359649e-03, -3.23374942e-03,
       -1.47849228e-02, -8.54733773e-03, -8.57451558e-03, -1.62688307e-02,
       -1.49599407e-02,  5.17700054e-03,  1.37125654e-02,  1.88651979e-02,
        4.98389918e-03, -7.86767714e-03,  8.37487075e-03, -7.75165996e-03,
       -1.38955666e-02, -1.46171534e-02, -2.61436449e-03, -1.27554722e-02,
        1.40601089e-02,  6.81328913e-03,  1.31671960e-02, -4.00673877e-03,
        4.55882307e-03,  2.02479493e-02, -1.14156911e-02, -7.09414389e-03,
        1.16474777e-02, -1.27633987e-02,  3.66152567e-03, -5.67086088e-03,
        5.32385777e-04, -6.48448477e-04, -8.78141634e-03, -1.04796002e-02,
        9.34084691e-03,  1.24260364e-02, -7.54304929e-03, -1.03348624e-02,
       -4.93125001e-04, -1.67002585e-02, -6.29731047e-04, -1.24594867e-02,
       -3.75899079e-04, -5.80471102e-03, -1.57685205e-02,  1.84310391e-03,
        6.78527681e-03,  7.36905215e-03,  6.94337348e-03,  1.19589325e-02,
       -1.19300326e-02, -6.17752550e-03, -7.86674209e-03, -6.36259327e-04,
        6.55580591e-03,  1.05889635e-02, -8.23492836e-03, -4.30217944e-03,
        2.72973510e-03, -2.78961728e-03, -8.67179222e-03, -5.36425272e-03,
        1.12574417e-02,  2.12872028e-03,  1.07361213e-03,  2.77620112e-03,
       -1.94406081e-02,  9.11621464e-05,  4.72498965e-03, -1.05446633e-02],
      dtype=float32), array([-0.70986813,  0.9044945 ,  0.8912026 , -0.6115627 , -0.8098617 ,
       -0.3884223 ,  0.20870255,  1.0134476 , -0.58201224,  1.038177  ,
       -0.816186  ,  0.27541515,  0.6801787 ,  0.43634436, -0.11126229,
        0.52843755, -0.3668247 , -0.698064  ,  1.1061345 ,  0.7932302 ,
        1.2427537 ,  0.56265014,  0.73541564,  0.11872989, -0.1109265 ,
        0.9440668 ,  0.39258462, -0.0443993 ,  0.35391963,  0.32650763,
        1.1008236 , -0.47510543,  0.29339975, -0.47139758,  1.0936108 ,
       -0.12762107,  0.2119654 , -0.7880237 , -1.1086652 ,  0.7277238 ,
       -0.38230538,  0.36747447,  0.26619294, -0.8226817 , -0.5448634 ,
       -1.4951774 ,  0.7100638 , -0.17138578,  0.16191489,  0.1745266 ,
       -0.8925498 , -1.2773448 , -0.23208521,  0.46944863, -0.55333626,
        0.42718098,  0.5636923 ,  0.8661994 , -0.5044    , -1.3778564 ,
        0.33509988, -0.42735022,  0.5415696 , -0.17164963, -0.794051  ,
        0.36948463, -0.70965075,  0.4633246 ,  0.53120226,  0.21287352,
        0.8143715 , -0.4957339 , -0.60541064, -1.166163  , -0.732888  ,
        0.13232097,  0.8395296 ,  1.1135478 , -0.36211824,  0.9417654 ,
        0.73372304, -0.72548074,  0.58658093,  0.12774272,  0.12866017,
        0.03610683, -0.7564778 , -1.4073437 ,  0.59262323,  0.23956381,
        0.03142618,  0.65293175,  0.49789625, -0.7903808 ,  0.9750023 ,
       -0.50781095,  0.5003737 ,  1.213093  ,  0.17437242, -0.61415994,
        0.16914155,  0.7801056 ,  0.78544694,  0.809547  ,  0.543969  ,
        0.61652946, -1.1926175 , -0.2051473 ,  0.14095658, -0.59147435,
       -0.58436424,  0.09889257, -0.30239376, -1.109328  , -0.25177577,
        0.27536467,  0.4607976 ,  0.700383  , -0.6837905 , -0.2239431 ,
       -0.5325445 , -0.90250415,  0.97413075, -1.1187491 , -0.0967904 ,
       -0.63793176,  0.89922726,  0.03214634], dtype=float32), array([1.9048344 , 2.0968332 , 0.79843014, 6.970364  , 1.6945833 ,
       3.522353  , 3.9588637 , 1.5771003 , 1.4960467 , 1.8378004 ,
       6.0048203 , 1.3999933 , 2.167171  , 1.3502958 , 2.467635  ,
       3.1337225 , 1.9384793 , 1.8709277 , 7.7878084 , 1.9575061 ,
       2.9117033 , 1.3183702 , 2.3285625 , 2.329493  , 2.2084491 ,
       2.6037447 , 1.812028  , 0.5661172 , 2.5780213 , 0.9853241 ,
       3.471382  , 1.065916  , 2.483528  , 1.3631538 , 1.9418929 ,
       1.4958831 , 2.457703  , 1.0683784 , 4.330178  , 2.4351902 ,
       2.8123682 , 0.5874723 , 2.3742528 , 2.2768579 , 1.9663644 ,
       3.6845143 , 1.1137358 , 1.4660989 , 1.455718  , 1.0092616 ,
       4.0433784 , 3.3939948 , 1.2996309 , 1.1619568 , 6.2985883 ,
       2.1744297 , 2.0979164 , 1.741664  , 1.495945  , 5.5493846 ,
       0.9781027 , 2.1803274 , 1.39886   , 1.0478233 , 1.8141298 ,
       1.3538686 , 3.0843189 , 1.0924592 , 1.2026157 , 1.0208766 ,
       1.9322705 , 1.6293259 , 2.1729615 , 0.9345127 , 1.5118107 ,
       2.0633068 , 1.9388893 , 2.1678338 , 4.598667  , 2.3282688 ,
       1.9313657 , 5.372716  , 0.9784304 , 1.9859868 , 2.8086407 ,
       2.0836515 , 2.9122257 , 1.6635365 , 2.3982081 , 1.3862215 ,
       2.5599658 , 1.7441382 , 2.302751  , 3.4926565 , 2.0356188 ,
       1.8766922 , 1.4323897 , 1.1742367 , 1.1291457 , 0.81271124,
       4.069314  , 1.0816865 , 2.2487996 , 2.250376  , 2.5703504 ,
       6.253249  , 3.5166276 , 3.950547  , 2.1521707 , 1.9928328 ,
       3.2016838 , 3.9660614 , 3.4928284 , 3.542712  , 1.3261372 ,
       2.0500855 , 1.2827103 , 1.8943554 , 1.0888504 , 0.5590949 ,
       3.914764  , 4.043933  , 1.874168  , 2.4563873 , 1.6864512 ,
       2.383837  , 1.4672481 , 1.8266006 ], dtype=float32), array([[[[ 0.03622765, -0.02539738, -0.04410534, ..., -0.04151892,
           0.0500012 , -0.01651893],
         [ 0.01595122,  0.04327974,  0.0235023 , ..., -0.03355804,
          -0.05374664,  0.03163168],
         [ 0.00481219, -0.00951064,  0.06174195, ...,  0.01957379,
           0.03685647, -0.00863849],
         ...,
         [ 0.06207285,  0.02254665, -0.02192792, ...,  0.03819712,
          -0.07126317,  0.00638473],
         [ 0.0492404 , -0.01815483,  0.04599281, ..., -0.03054856,
           0.01426881, -0.01959582],
         [ 0.01305132, -0.00092937, -0.01379285, ..., -0.03409574,
          -0.0241406 , -0.00437056]],

        [[ 0.04731242, -0.02641742,  0.01374137, ..., -0.05177797,
           0.04281612, -0.02817172],
         [ 0.04524197, -0.03522944,  0.06567236, ...,  0.05437291,
           0.05603085,  0.03335151],
         [-0.01794068,  0.05702482, -0.04826945, ...,  0.00100479,
           0.0447864 , -0.0451018 ],
         ...,
         [-0.04127777,  0.036353  , -0.00427163, ...,  0.02184709,
           0.00175969,  0.04484945],
         [-0.00936857,  0.00604197, -0.00647594, ..., -0.05113458,
          -0.01885512, -0.0239759 ],
         [ 0.03527257,  0.03935099, -0.01352505, ..., -0.04281939,
          -0.03523162,  0.03290512]],

        [[-0.01312755,  0.00899766,  0.02724364, ...,  0.04452825,
           0.02884997,  0.0236156 ],
         [-0.03189553, -0.00551473,  0.04428429, ...,  0.02279123,
          -0.03377833,  0.00731116],
         [-0.00495869, -0.04481146, -0.02871702, ..., -0.0053957 ,
           0.00663452, -0.01829748],
         ...,
         [-0.03148804, -0.00448482,  0.03619799, ...,  0.05429876,
          -0.00018871, -0.01262231],
         [-0.01237021, -0.02369072, -0.0051397 , ..., -0.02975966,
           0.00226457,  0.04590447],
         [-0.03686323,  0.04647719, -0.00057556, ...,  0.00945265,
           0.05155769,  0.04685036]],

        ...,

        [[ 0.03524376, -0.00388804,  0.01610427, ..., -0.0238492 ,
           0.03738112,  0.02573218],
         [ 0.05153841, -0.04043257,  0.04553487, ...,  0.03258969,
           0.04240802, -0.00270874],
         [ 0.00963778,  0.05092887, -0.02852816, ..., -0.03689523,
           0.0217028 ,  0.02701072],
         ...,
         [-0.02625782, -0.03204376,  0.00968508, ..., -0.00497031,
          -0.00770785,  0.00809692],
         [ 0.00538199,  0.05401349,  0.04636844, ..., -0.06024328,
           0.00687314, -0.06946222],
         [ 0.01186988,  0.04780551,  0.04131509, ..., -0.00992365,
           0.03613842, -0.01961975]],

        [[-0.00159661,  0.06194446, -0.03915882, ...,  0.00191738,
          -0.00594512, -0.0472283 ],
         [-0.04903998, -0.00427055, -0.0094102 , ..., -0.04387849,
          -0.04309099, -0.02915643],
         [ 0.01364878,  0.03629675,  0.02170677, ..., -0.04285996,
           0.00094944,  0.01792952],
         ...,
         [ 0.00117318, -0.02908144,  0.02663278, ..., -0.03049286,
           0.01673265, -0.01051954],
         [-0.0147401 ,  0.03400426, -0.00333505, ..., -0.05820785,
           0.04237184, -0.05148587],
         [ 0.00650486,  0.03923044,  0.064064  , ...,  0.00411061,
          -0.00842227,  0.03770318]],

        [[ 0.02408884,  0.02539886,  0.04800333, ..., -0.0141698 ,
          -0.02614678,  0.05511632],
         [-0.00606543, -0.02513103,  0.03074931, ...,  0.0283137 ,
           0.02576685,  0.05492963],
         [-0.00238876, -0.01963631,  0.01272898, ...,  0.05109004,
           0.00638959, -0.00014148],
         ...,
         [ 0.00921317, -0.03576855, -0.02053842, ..., -0.045331  ,
          -0.01170126, -0.03498184],
         [ 0.00552399, -0.00378606, -0.04121938, ...,  0.01502828,
           0.01183763, -0.00021539],
         [-0.02299751,  0.04054627,  0.01981973, ...,  0.01627959,
           0.02222553, -0.01320529]]]], dtype=float32), array([[[[ 0.0304659 , -0.02217157,  0.00209239, ...,  0.03004405,
           0.01573199, -0.03706595],
         [ 0.01675621, -0.03065862,  0.01718386, ...,  0.03427297,
           0.06087111, -0.05024911],
         [ 0.00196676, -0.00693351,  0.02082248, ...,  0.01861265,
           0.03990868,  0.02560602],
         ...,
         [ 0.04262801, -0.05648222,  0.04192352, ...,  0.06322081,
          -0.04402331,  0.03309809],
         [-0.05679781, -0.00436032,  0.00945614, ..., -0.04919763,
          -0.04641889,  0.02931554],
         [-0.04332362, -0.02308866,  0.00284704, ..., -0.01692416,
          -0.0102819 ,  0.02534057]]],


       [[[ 0.02403072, -0.05720342, -0.01126332, ..., -0.01060855,
          -0.01571242, -0.00446673],
         [-0.04933044, -0.02423342,  0.02683218, ..., -0.03429154,
          -0.03576567, -0.06508119],
         [ 0.02173216, -0.04022895, -0.00805017, ...,  0.00839816,
          -0.00515688, -0.03286492],
         ...,
         [ 0.0074003 ,  0.0439121 , -0.04918262, ..., -0.02572427,
          -0.03057125,  0.01419824],
         [-0.0164485 , -0.01220204, -0.07100829, ..., -0.05356542,
          -0.0563656 ,  0.03075498],
         [-0.0362391 , -0.04984966,  0.0391629 , ...,  0.00931717,
           0.04198081,  0.02826774]]],


       [[[ 0.03965712, -0.00866149, -0.00951629, ...,  0.00468801,
           0.04066117, -0.04634897],
         [ 0.02218935,  0.02088729, -0.00101476, ...,  0.01240378,
          -0.01700198, -0.0614957 ],
         [-0.01056863, -0.03171911,  0.0364146 , ..., -0.00747983,
          -0.00850549, -0.03368245],
         ...,
         [ 0.02772128,  0.04581399,  0.02980594, ..., -0.04758108,
          -0.0529302 , -0.04945395],
         [-0.02429853, -0.05764991, -0.05970906, ..., -0.01960242,
          -0.03202824, -0.02481968],
         [-0.01074041,  0.05994057,  0.01133436, ...,  0.01081713,
           0.01205768,  0.00804747]]],


       ...,


       [[[ 0.02922157,  0.03717113, -0.05221927, ..., -0.0551521 ,
          -0.05370725,  0.01009946],
         [ 0.0352063 ,  0.02043172, -0.05828932, ...,  0.04856828,
          -0.02324077, -0.02558153],
         [ 0.00847433,  0.04550361,  0.0124004 , ..., -0.02183998,
          -0.00739996,  0.00875143],
         ...,
         [-0.00274765, -0.06252184,  0.06130765, ..., -0.00079881,
           0.03082176, -0.00951683],
         [ 0.00805353, -0.04898931, -0.06192981, ...,  0.00395082,
          -0.00658562, -0.04359548],
         [-0.03810588,  0.04641725,  0.0138823 , ...,  0.04952231,
          -0.02869922,  0.04403218]]],


       [[[-0.04517043, -0.04094413, -0.00795982, ..., -0.05486734,
          -0.01669426,  0.0315619 ],
         [ 0.0297614 , -0.05539557,  0.00361912, ...,  0.04761683,
          -0.04688909,  0.00511806],
         [-0.00294643,  0.01630618, -0.0133719 , ...,  0.01205475,
           0.03504767, -0.00085876],
         ...,
         [ 0.02482955,  0.03926791, -0.00370063, ...,  0.0495008 ,
           0.04115625,  0.00184408],
         [ 0.02247295,  0.01308746, -0.01601106, ..., -0.01692906,
           0.04672244,  0.0559251 ],
         [ 0.00187477,  0.05228792,  0.02290261, ...,  0.03012353,
          -0.00072379, -0.05416745]]],


       [[[ 0.01734776, -0.02822868, -0.00724139, ...,  0.03912488,
           0.01493016,  0.00761742],
         [-0.05408843,  0.05017555, -0.03453676, ...,  0.01158379,
          -0.05934999, -0.03155823],
         [-0.02306191, -0.03370851, -0.06977367, ...,  0.00862679,
          -0.04433586,  0.01440786],
         ...,
         [-0.05950596, -0.04626228, -0.01650644, ...,  0.054903  ,
           0.03173258,  0.0237341 ],
         [-0.05702891,  0.01208136,  0.04165392, ...,  0.01815926,
          -0.04633205,  0.048398  ],
         [-0.03456185,  0.03027006,  0.06714098, ...,  0.02662541,
          -0.01604331, -0.05379016]]]], dtype=float32), array([ 3.10297869e-02, -3.11894920e-02, -1.92703232e-02, -4.04053833e-03,
       -1.00130644e-02,  2.62822974e-02, -3.35108326e-03, -1.58285387e-02,
        7.41749117e-03, -7.12702796e-03,  1.10050235e-02,  1.98148135e-02,
       -6.79959217e-03, -7.22278142e-03, -3.49109829e-03,  4.53362986e-03,
        5.32881264e-03,  7.25757936e-03,  1.77034712e-03,  9.87303536e-03,
       -1.09842082e-03,  2.57751364e-02, -8.93522985e-03,  1.08822659e-02,
       -1.64676178e-02, -1.29392352e-02, -1.04598580e-02, -1.30624799e-02,
       -2.62985583e-02,  3.95150622e-03, -2.97143031e-03, -1.29617378e-02,
        3.36880679e-03, -9.42166708e-03,  1.97553518e-03, -7.68347923e-03,
       -1.70206539e-02, -2.55565881e-03,  1.86520088e-02,  1.06557482e-03,
        1.81292128e-02,  1.41869867e-02, -1.61777379e-03, -1.43693550e-03,
        1.10765250e-04,  1.40535994e-03,  2.62840977e-03,  8.28719698e-03,
       -1.05555002e-02,  3.06955469e-03, -1.77411840e-03,  1.74858351e-03,
       -9.00411885e-03,  8.48241244e-03, -3.53583717e-03,  5.75328013e-03,
        7.14961812e-03,  3.65715614e-03,  2.24893428e-02, -4.33724001e-03,
        1.36849526e-02,  2.30959449e-02, -1.63667500e-02,  1.29378838e-02,
        3.75913311e-04, -1.08204177e-02, -6.37632003e-03, -1.57693233e-02,
        7.99346715e-03, -3.65465344e-03, -9.02308337e-03, -1.29021164e-02,
       -9.55321174e-03, -1.73365057e-03, -1.51169160e-02, -5.94513351e-03,
       -1.68360758e-03, -8.03999323e-03, -1.54939173e-02,  1.72270313e-02,
        2.86914338e-03, -1.73055995e-02,  5.64167881e-03, -7.77815876e-05,
        3.58849508e-03, -4.39720694e-03, -8.98707379e-03, -1.08155473e-04,
        3.27277696e-03, -3.99567699e-03,  9.40788072e-03,  3.82504612e-03,
       -8.20665341e-03,  6.17668484e-05, -1.91166624e-03,  7.25316769e-03,
       -1.58940593e-03, -4.05977014e-03, -2.05807798e-02,  2.61788815e-02,
       -4.04374441e-03, -8.94331187e-03, -9.78680234e-03, -2.17905100e-02,
       -1.55913504e-02,  1.79899037e-02, -1.27281528e-03, -4.46213968e-03,
       -4.87994682e-03,  3.71239963e-03, -1.76035836e-02,  2.01300923e-02,
       -4.52041539e-04, -1.12555474e-02,  8.87318235e-03, -1.50588155e-02,
        8.50206357e-04, -1.36971619e-04,  2.20151581e-02, -1.73478834e-02,
        6.12126803e-03, -1.42471129e-02,  3.27329780e-03, -2.15780176e-02,
        2.48261821e-03, -1.06178233e-02,  6.42053876e-03,  1.93426125e-02],
      dtype=float32), array([-0.10569933,  0.5525577 , -0.42416725,  0.19536692,  0.57578427,
       -0.02205512, -0.57764155, -0.03807602, -0.67325443, -0.6351243 ,
       -1.2661538 , -0.6203533 ,  0.6992397 , -0.7129119 ,  1.0277259 ,
        0.35619065,  0.06030365, -0.3820506 ,  0.84417146,  0.35892516,
        0.44134697,  0.47336435, -0.12274589,  0.10371181, -1.0774359 ,
        0.69217044, -0.97236717,  0.5983978 , -0.06099134,  0.15905336,
        1.1541042 ,  0.9148437 ,  0.17225766,  0.86177355,  0.00794185,
       -0.31623104,  0.79571587, -0.7959894 , -0.06550914, -0.53520125,
        0.39609054, -0.14030917,  0.31651074,  0.62572247,  0.5030302 ,
       -0.12235478,  0.5076696 ,  0.8109908 ,  0.79132897, -1.645445  ,
       -1.1806693 , -1.0519344 ,  0.28014398, -0.18203667,  0.53937465,
        0.13593304, -0.08832881, -0.01681257,  0.17079799,  0.24212094,
       -1.011484  , -0.1107673 ,  0.45243657, -0.4223697 , -0.66565925,
        0.95255345, -1.0905812 ,  0.3777621 , -0.1281538 ,  0.3538842 ,
        0.40002117,  0.04646593,  0.20106977,  0.33129025, -0.4221097 ,
       -0.81643987, -0.13309827, -1.0621969 ,  0.6129204 , -0.09398596,
       -0.43528345,  0.5392323 ,  1.0608829 , -0.5344804 , -0.00421821,
       -0.1715103 ,  0.86090195, -0.33534566,  0.42200562,  0.13684775,
       -0.9795274 , -0.99643046, -0.44454932,  0.13218322,  0.7999167 ,
       -0.1921411 , -0.6832365 ,  0.16171186, -0.49099427,  0.2689723 ,
       -0.4741565 ,  0.7751276 ,  0.6643402 ,  0.5189302 , -1.0346111 ,
       -0.03000256,  0.5722449 , -0.3840349 ,  0.06390301, -0.33962193,
        0.84064215, -0.16007103, -0.32149783, -0.4225002 , -0.15564248,
       -0.73923427, -0.6055146 ,  0.18098313,  0.20172082,  0.7816364 ,
       -0.3206181 , -0.12590958, -0.7951026 ,  0.19201697, -1.0529629 ,
       -0.37394127,  0.04349032, -0.5239099 ], dtype=float32), array([1.8517512 , 1.1902791 , 1.9505881 , 2.9035337 , 2.200004  ,
       1.4420117 , 1.6643708 , 4.007334  , 2.5272803 , 1.8575501 ,
       2.1205406 , 3.2866895 , 1.8326868 , 1.5921601 , 2.481519  ,
       2.846948  , 1.5593262 , 1.9117384 , 3.2355695 , 1.4324902 ,
       4.3226166 , 1.1705302 , 3.9423227 , 3.5010653 , 2.961715  ,
       2.2280307 , 1.1265028 , 1.9409229 , 0.65179765, 5.1697097 ,
       4.2222805 , 2.2011178 , 2.21346   , 2.6825974 , 4.064072  ,
       1.2879285 , 1.5884295 , 1.2318695 , 4.1303988 , 1.3884891 ,
       1.2338953 , 2.7175193 , 5.4057493 , 3.2983675 , 1.5722352 ,
       1.7800028 , 3.8310845 , 4.185393  , 1.3449845 , 5.4568534 ,
       1.1119393 , 3.2200923 , 4.3173685 , 2.8292758 , 3.9590266 ,
       2.6604943 , 1.8763965 , 1.4644043 , 1.5383816 , 5.3209414 ,
       5.60494   , 3.1765966 , 5.9364204 , 3.462706  , 2.2545948 ,
       1.6099393 , 3.521379  , 1.4879919 , 3.9070175 , 4.7596407 ,
       1.0644821 , 1.3951794 , 1.2743387 , 2.5341048 , 1.0287225 ,
       1.7520103 , 4.6027684 , 2.8757315 , 1.6069101 , 5.5684733 ,
       2.2691875 , 4.5520988 , 2.9435127 , 3.8576486 , 4.535129  ,
       2.2153046 , 2.2970068 , 2.2823308 , 5.8436265 , 1.4127692 ,
       2.0951002 , 3.2899861 , 1.7159724 , 2.065806  , 2.5563831 ,
       1.8181909 , 1.260944  , 2.9305718 , 0.87732494, 3.028235  ,
       2.9357483 , 2.4207528 , 1.8469738 , 2.581357  , 1.9273385 ,
       1.475974  , 2.218881  , 2.4835954 , 2.2926826 , 2.6419835 ,
       2.4138172 , 1.829518  , 2.2513692 , 3.8210974 , 2.242679  ,
       3.2406085 , 1.9896789 , 2.0531611 , 2.3759408 , 2.9716513 ,
       2.117397  , 6.10226   , 3.4862907 , 0.8181767 , 2.1647866 ,
       2.0620835 , 1.5058818 , 4.0473895 ], dtype=float32), array([-5.93475113e-03, -4.53765178e-03,  8.19199253e-03,  5.07699698e-03,
        9.52160638e-03, -7.49783404e-03,  1.36075336e-02, -9.80098732e-03,
        1.70772057e-02, -1.33595672e-02, -1.40290214e-02,  1.06521584e-02,
       -1.78823248e-02, -1.16728488e-02, -7.84431864e-03,  7.52641214e-03,
       -9.41456296e-03, -1.76726729e-02, -1.34928739e-02, -7.10518099e-03,
       -7.72596477e-03, -6.76841848e-03,  6.19184552e-03,  1.71022955e-02,
       -1.84943492e-03, -5.73575031e-03, -9.16014332e-03,  1.57704428e-02,
       -2.70707230e-03, -9.33081005e-03, -1.61077455e-03,  4.71061189e-03,
       -5.19216107e-03, -1.74628850e-02, -5.98765630e-03,  6.90293219e-03,
       -2.91546178e-03, -5.71296457e-03,  4.36455756e-03,  4.49539511e-05,
       -9.05851461e-03,  1.28351348e-02, -8.92643468e-04, -1.96693316e-02,
        1.07374543e-03, -1.70917972e-03,  3.66833410e-03, -4.39346721e-03,
       -7.51416665e-03, -1.80353019e-02,  7.33007491e-03,  6.14968827e-03,
       -4.30704979e-03, -3.10762133e-03,  8.07505101e-03,  5.09944791e-03,
        9.19354800e-03, -5.44735650e-03,  8.04741587e-03,  1.55497168e-03,
       -2.03246418e-02, -8.72304291e-03,  1.64860091e-03,  6.35457039e-03,
       -3.29901325e-03, -8.78390018e-03, -1.06956670e-02, -1.04473624e-02,
        6.06444338e-03, -2.84260628e-03, -1.84202066e-03,  8.57414852e-04,
       -3.10153398e-03,  6.91625010e-03, -1.43708242e-03, -8.19831435e-03,
        3.90231796e-03, -7.21618440e-03, -2.14418033e-04, -3.07276932e-04,
       -1.73336007e-02, -1.56832282e-02, -6.27577677e-03, -1.00657074e-02,
       -1.55005418e-02,  1.18733011e-03,  1.12301332e-05, -5.73444925e-03,
       -1.03232320e-02, -2.64485609e-02, -6.68314239e-03,  3.63802630e-03,
       -9.20073222e-03, -7.16678379e-03,  2.04742746e-03,  4.90338029e-03,
       -7.46878237e-03,  5.86233160e-04,  1.09326188e-03,  4.03854251e-03,
        1.87064540e-02, -7.45053496e-03,  8.12060724e-04,  6.24684384e-03,
       -9.40033607e-03, -2.75291712e-03,  1.12951901e-02, -9.40151699e-03,
        1.39998796e-03, -1.97498892e-02,  2.18443777e-02, -6.45710574e-03,
       -1.56897982e-03,  1.25243003e-02,  2.15844228e-03,  1.03345057e-02,
        3.15193529e-03, -1.17232427e-02,  2.15226738e-03,  1.13723772e-02,
        3.27527686e-03,  2.56246272e-02,  2.98481109e-03,  2.08929181e-03,
        1.40664745e-02,  4.73178843e-05, -1.16283298e-02, -1.11988243e-02],
      dtype=float32), array([-0.28328708, -0.74519193, -0.00519692,  0.7809067 , -0.06381831,
       -1.225369  ,  0.02486497,  0.87736684, -1.068663  ,  0.4789276 ,
       -1.3126704 , -0.33926043, -1.225101  ,  0.56188816, -0.03891232,
       -0.4418733 ,  0.5280117 , -0.5618797 ,  0.45120883, -1.1399202 ,
        0.6536059 ,  0.29403427, -0.46534538, -0.30327275, -0.2686007 ,
        0.13099983,  0.10760934, -0.7422099 ,  0.5075503 , -0.6711613 ,
        0.36418957,  0.14367796,  0.42310637, -0.49760517,  0.07831542,
        0.24301577,  0.6655895 , -0.11172009, -0.5480463 , -0.1988989 ,
        0.0999906 , -0.3884882 ,  0.5683894 ,  0.20960599,  0.40139192,
        0.24413137,  0.66095823,  0.6783065 ,  1.0060213 ,  0.5358445 ,
        0.37863523,  0.5483821 ,  0.533667  ,  0.43038929, -0.9701462 ,
       -0.7030674 , -0.48277763, -0.03525389, -1.0611626 ,  0.859543  ,
        0.3433326 ,  0.41199216, -0.7962099 ,  0.98511946,  0.20882519,
       -0.5145381 ,  0.69167763, -0.6042644 ,  0.163621  , -0.27682847,
       -0.7195122 , -0.1845284 , -0.56725603, -0.77929014, -0.2773322 ,
        0.48654145, -0.6909657 ,  0.49478033,  1.0259516 ,  0.41830972,
       -0.5743669 , -1.781727  ,  0.6037239 , -1.1046987 ,  0.871555  ,
        0.4762339 ,  0.42312115,  0.6369105 ,  0.25291142,  0.21257591,
        0.9421616 ,  0.731206  , -0.10205309,  0.1389638 , -0.5691213 ,
        0.48955846,  1.0410866 ,  0.07376644,  0.7921948 , -0.49042895,
        0.08935848, -0.00223385, -0.28232205, -0.27015656,  0.1781505 ,
        0.20553145, -0.49346644,  0.23547816,  0.46454588,  0.9636623 ,
       -0.39780015,  0.59738666, -0.69823545, -0.15504535, -0.64119107,
       -0.25445104, -0.36001182,  0.7650168 ,  0.4519628 , -0.10924362,
        0.5071378 , -0.07219758, -0.90095776,  0.23421174, -0.3199614 ,
        0.47202283,  0.22186805,  0.13064858], dtype=float32), array([7.090411 , 1.8934749, 2.9873412, 3.1107237, 2.3405058, 3.245293 ,
       1.1527257, 2.7355   , 4.6552653, 2.852109 , 7.8761287, 3.2398999,
       3.294392 , 3.3005426, 2.8217537, 2.7316747, 2.4157953, 4.0535846,
       1.3915502, 2.8372927, 1.6429462, 1.8522968, 1.3376119, 2.2691772,
       2.385485 , 1.6933708, 1.4470062, 1.6370398, 4.2360954, 1.5097339,
       2.807154 , 3.5002058, 2.9536924, 3.33463  , 1.2188904, 2.092753 ,
       2.5262084, 1.7949387, 2.3807478, 0.9765289, 6.5051384, 3.7961254,
       1.04235  , 3.532294 , 2.767159 , 1.4572538, 5.3648286, 5.6128874,
       2.2794392, 1.665627 , 2.376458 , 2.907177 , 2.135133 , 2.2424545,
       4.2073593, 4.178944 , 4.179537 , 2.604039 , 2.920274 , 2.4654696,
       1.5324878, 3.7538137, 2.3015978, 3.697093 , 4.448725 , 2.3457773,
       3.7086532, 1.2724798, 2.1137893, 2.1590765, 2.6598668, 0.518353 ,
       1.8005843, 4.182369 , 2.0667114, 3.262817 , 3.0149038, 1.4310414,
       3.2529204, 0.8142744, 2.343453 , 5.5392513, 2.8785086, 1.97236  ,
       2.586603 , 3.54791  , 1.408052 , 3.023106 , 1.7324946, 4.9613557,
       4.457587 , 2.7371054, 3.0769696, 2.4341621, 1.2017227, 1.3845475,
       3.1569107, 1.6309325, 1.8584687, 6.739146 , 1.7628045, 4.3853383,
       2.2136147, 1.3505671, 2.5840476, 2.5139697, 2.378453 , 2.5390391,
       1.2066602, 3.3042407, 3.7436259, 2.0682366, 4.952296 , 1.353672 ,
       1.824007 , 2.7664492, 3.5393   , 5.8470783, 1.975415 , 2.546901 ,
       1.1941365, 6.2154646, 2.896659 , 3.2344258, 1.3858026, 4.855817 ,
       2.842028 , 3.1754332], dtype=float32), array([[[[-0.00504278,  0.02970361,  0.01782596, ...,  0.08888321,
           0.07181948,  0.00099959],
         [-0.04302542,  0.06388684, -0.01510602, ...,  0.03778187,
          -0.00294733,  0.03918073],
         [-0.05378984,  0.00367513, -0.06678899, ...,  0.0392543 ,
          -0.01847669,  0.06354064],
         ...,
         [ 0.04794858,  0.0093779 ,  0.03224757, ..., -0.08722818,
           0.01792444,  0.06485498],
         [ 0.03224147, -0.05375488,  0.02605464, ..., -0.04168556,
          -0.06264044,  0.03912254],
         [ 0.06864576,  0.07674643,  0.01410213, ...,  0.04279542,
           0.06150896, -0.05995608]]]], dtype=float32), array([[[[ 0.00042271,  0.03662365, -0.01671415, ..., -0.00856176,
           0.05158475,  0.02227702],
         [ 0.00232514,  0.01471498, -0.02958358, ..., -0.00153855,
          -0.02254769, -0.05476992],
         [ 0.0036592 ,  0.02550556,  0.00231187, ...,  0.00730382,
           0.03269238,  0.02476816],
         ...,
         [-0.04121085,  0.01325272,  0.03153783, ...,  0.04580649,
          -0.0220613 , -0.00950664],
         [ 0.00152036, -0.03913613,  0.01733969, ..., -0.03585054,
          -0.01357109,  0.03580409],
         [-0.06980852, -0.06910276,  0.0333242 , ...,  0.02303819,
           0.02385365,  0.06388886]]],


       [[[-0.01653017,  0.00014976, -0.0018075 , ...,  0.03948683,
          -0.02316177,  0.06075937],
         [ 0.00268966, -0.03980495,  0.05405254, ..., -0.04131144,
          -0.03296247,  0.03921121],
         [-0.03280022, -0.01928962, -0.00335251, ...,  0.0505104 ,
           0.03458886,  0.03821052],
         ...,
         [ 0.00735418,  0.02410899,  0.02938463, ..., -0.00247109,
           0.00830139, -0.03794609],
         [-0.04498492, -0.02487765, -0.03517997, ..., -0.02633919,
          -0.00587997, -0.02507418],
         [ 0.00686009, -0.04750237,  0.00467935, ...,  0.02994064,
           0.00544633,  0.05187257]]],


       [[[ 0.00040793, -0.06155941,  0.00693902, ...,  0.02168615,
          -0.01492991,  0.03190907],
         [ 0.00335175, -0.02940911, -0.02761052, ...,  0.00625618,
          -0.00858496,  0.02781712],
         [-0.04609464, -0.06117875, -0.01033108, ..., -0.02825579,
           0.03039193, -0.04874768],
         ...,
         [ 0.05012776,  0.00415385,  0.01429761, ..., -0.00036689,
          -0.03067699, -0.05368191],
         [-0.04152774,  0.05012866, -0.01687113, ...,  0.00830188,
           0.05755934, -0.00852524],
         [-0.06344042, -0.01420736, -0.02298062, ..., -0.03104128,
           0.0281103 ,  0.04736762]]],


       ...,


       [[[-0.0312158 ,  0.00084232,  0.0280534 , ..., -0.00930297,
          -0.02727127, -0.0290219 ],
         [-0.02322785,  0.01754285,  0.05938206, ...,  0.03412736,
           0.01101705,  0.04225491],
         [ 0.01467149,  0.03999911, -0.00732748, ...,  0.04762886,
          -0.02990691,  0.03784484],
         ...,
         [-0.05158528,  0.01428896,  0.03650086, ...,  0.03676577,
          -0.04277085, -0.03352371],
         [-0.00156635,  0.04501765, -0.03764934, ...,  0.00660541,
           0.00046367, -0.03268165],
         [-0.0292806 , -0.0101921 , -0.00800424, ...,  0.03300267,
           0.04946515,  0.00171795]]],


       [[[ 0.01900617,  0.02658581, -0.03408508, ..., -0.06781399,
          -0.01586383, -0.04524803],
         [ 0.03060929,  0.03267569,  0.01372238, ...,  0.01590254,
          -0.04104564, -0.0427498 ],
         [ 0.05370922, -0.05112273, -0.01099576, ...,  0.00765861,
          -0.03439173,  0.03581127],
         ...,
         [-0.05439637,  0.01079019,  0.03858176, ...,  0.01875822,
           0.02515134,  0.0447597 ],
         [-0.01088646,  0.02077107,  0.02863617, ..., -0.00126272,
          -0.01741108, -0.03294963],
         [-0.06848927, -0.04744354,  0.01053448, ...,  0.0075273 ,
          -0.0405252 ,  0.00678116]]],


       [[[-0.02274654, -0.06261817, -0.05286464, ...,  0.01605004,
          -0.01351138, -0.0160509 ],
         [ 0.01419239, -0.03106367,  0.04726317, ...,  0.03604594,
           0.03057552,  0.02128125],
         [ 0.0257397 ,  0.00917426, -0.01898334, ..., -0.03068966,
           0.03952897, -0.00355623],
         ...,
         [-0.01206631,  0.0403406 , -0.0146512 , ...,  0.01266205,
           0.04725276,  0.00574105],
         [-0.01365082, -0.05012027, -0.0425402 , ..., -0.02812647,
           0.02647044, -0.04079145],
         [ 0.02455655,  0.03420035, -0.04594251, ...,  0.00402241,
          -0.01145214, -0.01958814]]]], dtype=float32), array([[[[-2.88249999e-02,  1.37835285e-02, -5.80500811e-02, ...,
          -1.51831014e-02, -1.26904976e-02, -2.25069523e-02],
         [ 1.43735306e-02,  7.97200017e-03,  6.14515692e-02, ...,
           2.00907048e-02, -2.61323899e-02, -1.70613378e-02],
         [ 2.72581037e-02, -4.26949821e-02,  4.78686579e-02, ...,
          -3.52799073e-02, -1.01876454e-02,  2.28971802e-02],
         ...,
         [ 9.32677835e-03, -4.08231579e-02, -3.01444735e-02, ...,
          -7.26107182e-03,  4.01290581e-02,  2.26468891e-02],
         [ 5.58810607e-02, -2.33964575e-03,  4.70331721e-02, ...,
          -2.40094848e-02, -4.98855785e-02, -1.32826203e-02],
         [ 7.98955187e-03, -3.86397801e-02,  1.45447562e-02, ...,
           1.48894542e-04,  2.21569138e-03, -9.37455241e-03]],

        [[-6.39203340e-02,  1.75800978e-03, -2.76740305e-02, ...,
           2.19972748e-02, -3.87775188e-04,  1.42103583e-02],
         [-7.55153457e-03,  3.73823456e-02,  4.75169607e-02, ...,
          -9.60903987e-03,  2.33434681e-02, -5.83768226e-02],
         [-4.49810140e-02, -1.39780128e-02, -4.81524803e-02, ...,
           4.28967318e-03, -1.29096126e-02,  3.17402091e-03],
         ...,
         [ 3.64600085e-02, -4.38142307e-02, -1.07660750e-03, ...,
           2.34088730e-02,  2.45700357e-04, -1.22019462e-02],
         [ 2.39357091e-02,  8.59876443e-03, -3.67653966e-02, ...,
           4.28511649e-02, -6.28046226e-03,  3.32942717e-02],
         [-3.15539129e-02,  5.79258427e-03, -2.72744298e-02, ...,
           5.56757348e-03, -3.23431268e-02, -2.88756061e-02]],

        [[-1.67126972e-02, -3.99015769e-02,  5.01202978e-03, ...,
          -5.23915663e-02,  8.75911862e-03,  4.30655442e-02],
         [ 3.22670788e-02,  4.89979275e-02,  2.69978587e-02, ...,
          -6.44175755e-03,  4.82794568e-02,  3.65176983e-02],
         [-1.58545505e-02, -1.22686233e-02, -4.46562245e-02, ...,
          -8.86034686e-03,  3.11705861e-02, -2.40245927e-02],
         ...,
         [-3.27297822e-02, -2.18605008e-02, -4.89377566e-02, ...,
          -5.65557703e-02,  1.60793401e-02, -2.18404401e-02],
         [ 3.15652676e-02,  3.37873138e-02, -2.48780139e-02, ...,
          -3.29739563e-02,  1.67140958e-03, -1.66384764e-02],
         [-3.86970416e-02, -8.54447111e-03, -1.19632017e-02, ...,
           4.82608564e-02,  3.56396288e-02,  1.49623556e-02]],

        ...,

        [[-4.78510410e-02, -4.11678925e-02, -3.03647947e-02, ...,
           1.97463669e-02, -2.50928253e-02,  1.51390769e-02],
         [-4.22213711e-02, -3.61820087e-02,  3.97834294e-02, ...,
           2.88317893e-02,  2.70515718e-02, -4.50306796e-02],
         [-9.98136215e-03,  1.70886312e-02,  4.48038466e-02, ...,
           3.50535884e-02,  4.01329920e-02,  2.35155821e-02],
         ...,
         [-3.71756181e-02,  2.99124047e-02,  1.34879733e-02, ...,
           2.25280076e-02,  2.03007124e-02,  2.79455148e-02],
         [ 1.74792036e-02, -2.73853112e-02, -1.83074214e-02, ...,
           7.31404871e-03,  2.75588837e-02, -3.96815641e-03],
         [-5.57661802e-02, -3.76266837e-02, -5.89885786e-02, ...,
           5.91344833e-02, -1.67261176e-02, -4.71316464e-02]],

        [[-4.02093977e-02,  3.83714586e-02, -4.40578125e-02, ...,
          -1.16208689e-02, -7.57841999e-03, -8.03818833e-03],
         [-4.15818505e-02, -4.16830741e-02,  1.09735867e-02, ...,
           2.41011996e-02,  3.48064676e-02, -1.59529895e-02],
         [ 9.46028624e-03, -4.18330133e-02,  3.64012420e-02, ...,
           6.98794657e-03, -5.15233688e-02, -2.64587607e-02],
         ...,
         [ 2.51491778e-02,  3.16074044e-02,  2.18766998e-03, ...,
           2.68536974e-02, -5.07898107e-02, -3.98742147e-02],
         [-8.96399468e-03, -1.77972240e-03,  2.53704619e-02, ...,
          -1.73088963e-04,  2.35387050e-02, -6.53852820e-02],
         [-5.37245087e-02,  3.33065051e-03,  1.03003671e-02, ...,
          -3.44099179e-02,  1.60253234e-02, -4.99777235e-02]],

        [[ 3.23526077e-02, -2.43583936e-02,  6.21093065e-02, ...,
           4.07034904e-02, -1.04199937e-02, -3.36270332e-02],
         [-3.84054296e-02, -1.69247578e-04, -4.99556260e-03, ...,
           3.31435055e-02, -5.25842700e-03, -3.10426615e-02],
         [ 8.96541495e-03, -5.50196506e-02, -2.61424854e-02, ...,
           4.45853844e-02,  1.67184416e-02, -4.31635417e-02],
         ...,
         [ 1.16763040e-02,  5.35917990e-02,  7.02223770e-05, ...,
           4.69610048e-03, -5.09329624e-02,  9.61368252e-03],
         [-9.54134157e-04, -3.65336165e-02, -2.44369656e-02, ...,
          -3.92936170e-02,  2.90437508e-02,  1.37755424e-02],
         [-6.22792775e-03, -1.81368869e-02, -4.25515771e-02, ...,
          -5.37689868e-03, -1.32839885e-02, -3.63976844e-02]]]],
      dtype=float32), array([[[[-5.9349619e-02,  1.9284189e-02,  1.1671911e-02, ...,
          -2.6947889e-04, -5.2657492e-02,  2.6275676e-02],
         [-7.1239062e-02, -4.4943653e-02, -3.6530059e-02, ...,
           4.2878713e-02,  6.9494247e-03, -6.8525515e-02],
         [ 2.5782841e-03, -4.6981871e-02,  2.9401284e-02, ...,
          -3.6426336e-03, -5.8038380e-02,  1.5917789e-02],
         ...,
         [-3.7826888e-02, -1.2518643e-02,  5.1478878e-02, ...,
           3.9222538e-03, -5.1709465e-03, -6.6167161e-02],
         [-4.3396790e-02, -6.0126066e-02, -5.3916577e-02, ...,
           6.0483448e-02, -5.0855383e-02, -8.5008539e-02],
         [-1.5281835e-03,  6.5799810e-02,  5.4573424e-02, ...,
          -4.4384673e-02, -1.0922783e-02,  3.3187338e-05]]]],
      dtype=float32), array([-2.00248265e-04,  4.89023421e-03, -5.61937410e-03,  7.60744078e-05,
       -4.58881550e-04, -1.00747347e-02,  7.47561734e-03,  5.92064625e-03,
       -1.70084815e-02, -4.96711116e-03,  5.19038364e-03, -7.01093115e-03,
       -6.42319792e-04,  2.43813056e-03, -4.46682144e-03,  3.38390330e-03,
        3.75662707e-02,  1.38451206e-02, -4.99545597e-03, -1.00513408e-02,
       -5.96045237e-03, -1.51827885e-02, -4.87403898e-03, -1.97658129e-03,
        2.66842302e-02, -7.64121395e-03, -1.23592019e-02, -5.64937619e-03,
        1.24957273e-03,  5.22386655e-03,  1.31871160e-02,  1.71662252e-02,
       -1.33751603e-02, -6.08979166e-03,  5.25942026e-03, -5.89036755e-03,
       -1.53644616e-02,  1.39571019e-02, -5.86530194e-03, -7.24578928e-03,
        1.02953771e-02, -1.89441796e-02,  5.59043931e-03, -4.34383843e-03,
       -1.02668097e-02,  1.81052256e-02,  1.21969106e-02,  3.60240298e-03,
       -2.17125658e-03, -3.92186502e-03,  2.80505104e-04, -1.16027212e-02,
       -5.11014974e-03, -1.91370472e-02, -6.14520675e-03, -1.36760920e-02,
        1.63988734e-03,  6.72323955e-03, -8.59894510e-03,  1.47328433e-02,
        9.70177073e-03,  1.63312145e-02, -4.25793184e-03,  4.47655650e-04,
        1.19091780e-03, -1.52105400e-02, -1.14289690e-02, -3.91994463e-03,
        1.26178116e-02, -1.94077305e-02,  3.83287988e-04, -8.12496408e-04,
       -1.04246568e-02,  5.13335969e-03,  1.16597526e-02, -1.61489286e-02,
       -2.36207806e-02,  1.17218820e-02,  1.25734471e-02, -6.87023299e-03,
        8.50111712e-03, -7.82093778e-03, -8.69935285e-03, -5.88321174e-03,
       -8.23592360e-04,  1.03848858e-03,  2.10081898e-02, -3.03213624e-03,
        1.77219640e-02,  5.94538264e-03,  9.55026690e-03,  1.35950604e-02,
       -7.10891979e-03, -1.31180114e-03,  1.67761557e-02, -5.23153180e-03,
       -8.01275577e-03, -1.73652787e-02,  1.06711704e-02, -1.06535945e-02,
       -1.33010820e-02, -2.14943406e-03, -1.45857492e-02, -1.11350873e-02,
        3.67499376e-03, -1.18135372e-02, -3.95925716e-03, -1.01294862e-02,
        2.04413221e-03,  2.81495918e-02,  7.46756140e-03, -2.94333696e-03,
        2.56084278e-03, -9.14331619e-03,  1.31392945e-03, -8.18804558e-03,
        7.58783426e-03,  4.06210357e-03,  8.91635846e-03, -7.66871870e-03,
        9.98005853e-04,  6.71843719e-03,  6.02210732e-03,  2.75435089e-03,
        6.41185278e-03, -3.69815563e-04,  4.95125679e-03,  1.93977472e-03,
       -2.63781771e-02,  6.84037106e-03,  1.95993576e-02, -2.16203034e-02,
       -1.70140783e-03, -9.98503179e-04,  3.88553226e-03,  4.76574851e-03,
        4.51670680e-03,  8.47546197e-03, -3.26039875e-03, -1.54461879e-02,
       -1.54458489e-02, -8.50714557e-03,  6.59701414e-04,  1.63768288e-02,
        7.15444272e-04,  1.29045695e-02, -3.08548653e-04, -1.54215228e-02,
        4.73925658e-03, -1.07398285e-02, -7.33462337e-04, -1.42621184e-02,
        1.04705896e-02,  3.09732836e-03,  1.20355608e-03,  1.25610670e-02,
        8.78726598e-03, -4.02622944e-04, -1.69536602e-02,  4.57957387e-03,
       -1.44086070e-02,  1.91908590e-02, -1.42240589e-02,  1.89131743e-03,
        1.54980524e-02,  8.63564387e-03,  6.15507306e-04,  8.26365722e-04,
       -7.17342598e-03, -5.25375981e-05,  9.07537621e-03,  1.56541448e-02,
       -1.84988324e-02, -4.48850542e-03, -1.10606644e-02, -9.38603748e-03,
       -2.49216426e-02,  1.82294240e-03, -1.91232711e-02, -2.43473519e-02,
        6.98984275e-03,  3.22588650e-03,  5.40938461e-03, -1.18795047e-02,
       -4.01359797e-03, -1.13301706e-02,  3.13250371e-03,  7.87584949e-03,
        8.67968716e-04, -2.13392472e-04,  1.25362920e-02,  3.41737224e-03],
      dtype=float32), array([-2.35753322e+00, -2.27752328e+00,  1.47021699e+00, -6.43360540e-02,
        2.42495432e-01, -1.38999891e+00, -9.94405448e-01,  3.75503749e-01,
       -1.05360650e-01,  4.90842104e-01,  9.97298509e-02, -6.71016216e-01,
        1.17915297e+00, -2.33971700e-01, -2.20853522e-01,  1.55540848e+00,
       -7.34395862e-01, -8.92123461e-01,  9.81186271e-01,  1.51623642e+00,
       -9.51747149e-02, -4.94458735e-01,  7.48886764e-01, -7.54459023e-01,
       -4.16202217e-01,  2.34775019e+00,  9.83660877e-01,  1.26815391e+00,
        3.54788095e-01, -1.65352476e+00, -6.97897196e-01, -6.86591625e-01,
        1.22861542e-01,  4.05614853e-01,  1.72786427e+00,  1.44430721e+00,
        1.63452017e+00, -1.79651082e+00,  3.32380265e-01,  1.49777925e+00,
        1.11520720e+00,  1.63484287e+00,  1.36244133e-01,  9.33492184e-01,
       -2.89014876e-01,  1.38068363e-01, -1.06470561e+00, -1.33264172e+00,
       -1.72773883e-01,  1.80350804e+00, -5.04296362e-01,  1.16099727e+00,
       -8.58359456e-01,  3.33962262e-01,  2.66452670e-01, -6.09397352e-01,
        3.27134766e-02, -3.55297476e-01,  4.19617295e-01,  3.28565031e-01,
       -1.93573520e-01,  9.06190515e-01,  1.50639451e+00, -5.59489787e-01,
        5.84653616e-01, -4.65356074e-02,  9.57329333e-01,  1.77785122e+00,
        3.36285919e-01,  7.08038986e-01,  7.88332820e-01,  3.39901447e-02,
        1.16357096e-01, -6.36348784e-01,  2.49713689e-01, -2.95313507e-01,
       -7.61323631e-01,  5.64169526e-01, -6.31444216e-01, -1.07623076e+00,
        1.48407653e-01,  2.64891505e-01, -1.45086423e-01,  1.98630714e+00,
       -3.18832487e-01,  3.82321805e-01,  5.45862675e-01,  1.35664213e+00,
       -4.51179534e-01, -8.59425545e-01, -3.71556848e-01, -1.50503799e-01,
       -4.29796100e-01,  1.10360777e+00, -4.02578861e-01,  1.86928296e+00,
       -8.21002424e-02,  6.51778400e-01,  8.68719697e-01, -1.05815279e+00,
       -1.95885643e-01,  7.66469359e-01,  1.36706388e+00,  1.76526499e+00,
        1.90951496e-01,  6.37293696e-01, -1.06159377e+00, -1.06034267e+00,
       -1.08833086e+00, -4.56917852e-01, -9.78475392e-01, -6.65721536e-01,
        6.77909553e-01, -1.86538172e+00,  1.19919622e+00, -3.77331883e-01,
        7.27546513e-01, -3.08887064e-01, -6.45660982e-02,  1.09524739e+00,
       -3.22714865e-01,  6.99125707e-01,  1.63841343e+00,  5.30081689e-01,
        1.62960517e+00,  5.60859025e-01,  8.35109890e-01,  1.87134221e-01,
       -1.28530490e+00,  3.60038966e-01,  1.24536172e-01, -1.96897852e+00,
        3.83088619e-01, -1.01010418e+00, -1.47766423e+00, -4.20388967e-01,
        1.44491596e-02, -1.11679995e+00,  7.19081879e-01,  4.44481730e-01,
        1.15294755e+00,  8.93869042e-01,  5.66734225e-02, -6.40060604e-01,
        1.22779930e+00, -1.79241753e+00, -2.50393182e-01,  1.52316976e+00,
       -2.67695874e-01,  1.47446878e-02,  3.00736219e-01,  1.34942949e+00,
        7.83232212e-01,  5.43529987e-01, -1.16891101e-01,  7.19638020e-02,
       -5.54642193e-02,  1.02137947e+00,  4.29830581e-01,  9.75219905e-01,
        6.23343289e-01, -1.06326318e+00, -1.37071407e+00,  5.44573784e-01,
        1.24875404e-01, -1.22381318e+00,  5.70908725e-01, -1.38155088e-01,
        1.64450407e+00,  4.17775899e-01, -2.21561664e-03, -4.75979120e-01,
        7.69387007e-01, -5.73338047e-02,  6.06394529e-01,  2.47906685e+00,
        2.17687678e+00, -6.63120389e-01,  3.19311172e-01, -3.77488762e-01,
        2.97185004e-01,  1.09774232e+00,  4.43351328e-01,  5.31390905e-01,
        5.71215749e-01,  1.74598920e+00, -2.12181181e-01,  1.56098437e-02,
        1.13520026e+00,  3.45012128e-01,  4.33343351e-01,  6.76176473e-02],
      dtype=float32), array([6.4607515, 2.2182527, 3.9732108, 1.1406982, 2.269284 , 2.0070932,
       2.5086637, 1.9107709, 2.9137619, 4.8921323, 1.4731754, 1.7119536,
       4.673703 , 2.5210383, 1.235229 , 4.3736124, 3.8187282, 4.627946 ,
       2.132974 , 2.1920223, 4.0378833, 2.9973426, 2.218338 , 2.4120617,
       2.6708922, 4.0804834, 2.6344097, 3.5222018, 2.1790009, 2.180168 ,
       4.5896516, 1.7149167, 2.3157935, 1.6453615, 3.0251832, 3.0067163,
       4.944976 , 2.6473978, 2.915904 , 2.9354022, 2.8179452, 3.8251548,
       1.8633468, 4.86338  , 3.1505775, 3.754881 , 4.7678547, 4.9878364,
       3.071814 , 6.6911664, 2.363863 , 4.1323366, 2.034602 , 1.4340973,
       2.7612293, 1.4388512, 0.7465828, 1.4275985, 1.2029941, 2.8604164,
       5.3128   , 2.4567268, 3.1610963, 1.3060994, 2.2352076, 4.116901 ,
       2.0649238, 3.0272472, 1.6634197, 2.408414 , 1.8314573, 3.1235433,
       1.2262976, 2.3804393, 1.6653402, 2.2762277, 2.786269 , 3.2549841,
       5.3004084, 4.823831 , 4.466169 , 3.3841438, 4.2248597, 4.8494773,
       2.091927 , 3.9845097, 3.7535973, 3.7615676, 4.0056524, 2.7454317,
       3.9965289, 2.462468 , 1.0601372, 3.0582972, 6.252676 , 4.0694304,
       2.036273 , 1.5324974, 1.783513 , 1.8362745, 2.035978 , 1.9468045,
       2.9517963, 2.21125  , 2.4111881, 3.6715853, 2.972363 , 1.1949593,
       1.6890969, 5.811909 , 3.6762133, 4.857478 , 4.9015484, 4.8335023,
       3.3750188, 2.609973 , 2.2428746, 4.1473494, 4.0955544, 4.0465617,
       2.4745657, 3.2809231, 4.7689385, 1.6849614, 5.0225735, 1.6399509,
       1.8756766, 7.0957828, 6.0308814, 3.3039298, 1.9887524, 5.519785 ,
       3.164734 , 1.8341732, 2.1767974, 1.1862822, 2.631555 , 2.565037 ,
       2.6670394, 3.5091646, 1.3768979, 1.9504092, 4.7541175, 1.2464796,
       4.584157 , 4.140298 , 1.1127611, 3.3186567, 6.4869504, 2.0502505,
       2.9178176, 3.0943317, 2.9580853, 2.509957 , 3.5149205, 2.6535866,
       2.5288625, 4.4112535, 3.7878726, 5.0583076, 2.6677463, 2.1504095,
       2.6361892, 2.9290268, 1.1088786, 1.6452309, 2.5720787, 3.5266886,
       4.641262 , 2.7413735, 4.0190516, 1.9590106, 3.048419 , 2.3216395,
       2.9083076, 5.869516 , 3.164579 , 2.4380648, 1.5911813, 2.2582998,
       2.5621784, 3.015795 , 3.3311973, 3.016926 , 1.9940153, 4.6725183,
       3.2682624, 2.7018878, 4.2371454, 1.1669064, 3.6667466, 1.9784151],
      dtype=float32), array([ 0.00747768, -0.00098848,  0.00749937,  0.00599878, -0.00931831,
        0.01790767,  0.00934068, -0.02759756,  0.00594448,  0.00562155,
       -0.0149937 ,  0.00067638, -0.0030366 , -0.00657841,  0.01027204,
        0.01076245,  0.01451833,  0.01410365,  0.00771419, -0.00787617,
       -0.00312741, -0.00164122, -0.00932926, -0.00116613,  0.00069583,
        0.0088944 ,  0.00368119,  0.02237372,  0.00551559,  0.00223356,
        0.00784737,  0.00346596,  0.00378677,  0.01839655,  0.01028997,
       -0.01191261, -0.00886814,  0.01478787, -0.00603115, -0.01239569,
        0.00325417,  0.01485941,  0.00348088,  0.00371845, -0.00406127,
        0.00586304,  0.01024973,  0.00456636, -0.01391746,  0.02154574,
        0.01488449,  0.00290716, -0.01257325,  0.02602105,  0.0049124 ,
       -0.00374592,  0.00192088, -0.0182847 , -0.00240764,  0.0137372 ,
       -0.00387313,  0.0133116 , -0.02081159,  0.02222461,  0.01179611,
        0.01576952, -0.00939154, -0.01002028, -0.00320519, -0.0086435 ,
        0.00807034,  0.02141064, -0.00703558,  0.0013754 , -0.02004386,
       -0.01171819,  0.01103393,  0.00654399,  0.00484751,  0.00210186,
       -0.00864296,  0.00569168,  0.00750607,  0.02231841, -0.01244841,
        0.00265739,  0.00328178, -0.00389035,  0.00879393, -0.00127307,
       -0.01209057, -0.00429745, -0.00340257, -0.01383157, -0.01306422,
       -0.00282547, -0.00462297, -0.0034337 ,  0.02483225,  0.0003757 ,
       -0.00900334, -0.00271945,  0.01261535, -0.01189025,  0.00415859,
       -0.01301078, -0.00107242,  0.0054459 , -0.00695349,  0.01808405,
        0.01240936, -0.01231677,  0.02614792,  0.026994  , -0.0181505 ,
        0.01167271, -0.01645071, -0.01356547,  0.00229755, -0.03059762,
        0.00177264, -0.01447725,  0.00111576, -0.01106485, -0.0019077 ,
        0.01933323,  0.00231218, -0.00025856, -0.00319727, -0.00084176,
        0.00242379,  0.01266223, -0.01934874,  0.00202428,  0.00424959,
       -0.01436622,  0.004656  ,  0.00721563, -0.0100288 ,  0.00841448,
        0.00014275, -0.01242551, -0.0180242 , -0.01857239, -0.00096391,
       -0.00733393,  0.00419485,  0.01954616,  0.02999514, -0.00535783,
        0.00401821, -0.01153101,  0.00417438,  0.01267138, -0.00614935,
        0.02883609, -0.01335692,  0.01235357, -0.00271689, -0.00659669,
       -0.00604614, -0.00035153,  0.01085177, -0.00635327, -0.00322701,
        0.01376619,  0.01065388,  0.00765284,  0.02333641,  0.01028321,
        0.00509325, -0.00926963, -0.01785317,  0.01068733,  0.00635989,
        0.01540175, -0.01122533, -0.01113717, -0.00332249, -0.00274875,
        0.01489138,  0.01809139,  0.00869521,  0.0088764 , -0.01205777,
       -0.00317619, -0.00339501, -0.01091316, -0.01171272, -0.00604683,
       -0.02996264, -0.00010641], dtype=float32), array([-0.5108895 , -0.05973377, -0.8938801 , -1.6327642 ,  0.22847882,
       -0.4625481 , -0.7046495 ,  0.99161917,  0.68163955,  0.19125977,
        0.9026215 ,  0.22356166,  0.15052436,  0.81449   , -0.5456797 ,
        0.5590905 , -0.20502134, -0.22042458, -0.43501034, -0.8931842 ,
        0.1335201 ,  0.81449574,  0.70191437,  0.616198  , -0.742992  ,
       -0.07793321, -0.23456055,  0.03002682, -0.11618001, -0.69925135,
       -0.39234415, -0.6197047 ,  0.10556396, -0.23646398, -0.7452243 ,
       -0.13506316, -1.0514901 , -0.4771812 ,  0.12277722, -0.01638816,
       -0.4210182 ,  0.6246762 , -0.80245   ,  0.2429785 ,  0.69827795,
       -0.4871967 , -0.42471296,  0.00265343, -0.6893518 , -0.0609698 ,
       -0.44370595,  0.19372393, -0.33273748, -0.373175  , -0.09920175,
        0.50691473,  0.32218438,  0.12579651, -0.19184196, -0.02646767,
        0.64707744, -0.87689835,  0.90497154, -0.47631842,  0.31362617,
       -0.24610232,  0.88361126,  0.53685975,  0.04959162,  1.7877412 ,
       -0.14673315, -0.5025285 ,  1.0825006 , -0.5257928 , -0.14571981,
        0.28367817, -0.21459462, -0.78381425, -0.08757143,  0.0097518 ,
        0.7310059 ,  0.3805905 , -0.04365436, -0.20602015,  0.43475688,
       -0.05041522, -0.29132187,  0.33897358, -0.1298993 ,  0.07299116,
       -1.1373186 ,  0.8049101 , -0.73354614,  0.4573627 , -0.04834364,
       -0.10667488, -0.53700167,  0.34850863,  0.70858866, -0.5166279 ,
        0.72361535,  0.4625453 ,  0.26914218, -0.7324966 ,  0.04304023,
       -0.4288531 ,  0.17583394, -0.64973277,  0.5373994 ,  0.26495355,
       -0.17773834,  0.47601423,  0.54342693,  0.5960672 ,  0.3867203 ,
       -0.3192752 ,  0.0227374 , -1.0410464 ,  0.19682421,  0.3292445 ,
       -0.37684575,  0.24858265, -0.17498428,  0.9314412 , -0.8093626 ,
        0.40325966, -0.11317205, -0.04045932, -0.58610874, -0.28900248,
       -0.01194355,  0.75659907,  0.01458718,  0.9292999 , -0.43386027,
        0.06089387,  0.29683027, -0.24288608, -0.8696757 , -0.65885305,
       -0.57312906,  0.93585724,  0.14969388, -0.02387025, -0.63372135,
       -0.21614785,  0.44739065,  0.204261  , -0.22872666,  0.48442942,
       -0.35914022,  0.8686681 , -0.78165543, -0.05643712, -0.7777392 ,
       -0.50670904,  0.5384684 ,  0.34200478,  0.55693334, -0.24696516,
       -0.5906931 , -0.53769374, -1.1574056 , -0.24062912,  0.5165286 ,
       -0.02579826, -0.02112259, -0.04324486,  0.4044115 ,  0.27550477,
       -0.6721748 , -0.21687415, -0.10883534, -0.31267035, -1.0002018 ,
       -0.785416  ,  0.63424414, -0.50416154,  0.2306503 ,  0.4627278 ,
        0.612034  , -0.49816644, -0.23176055,  0.23072292, -1.0924962 ,
       -0.78558457,  0.5163068 , -0.33094338, -0.03009405, -0.03786944,
        0.7422865 ,  0.78430974], dtype=float32), array([3.0155916 , 4.18956   , 1.5290428 , 2.6534655 , 1.3587518 ,
       5.360177  , 2.2643495 , 2.8440256 , 2.0267625 , 1.2766905 ,
       2.646375  , 2.575436  , 1.2641573 , 1.4500479 , 1.421199  ,
       1.9400048 , 5.148696  , 2.3239017 , 1.2947651 , 1.5396721 ,
       2.4135635 , 3.0141919 , 1.6024932 , 1.5432137 , 2.8016036 ,
       2.8651373 , 1.7234408 , 1.829642  , 2.9488516 , 2.696763  ,
       1.9974204 , 1.8173219 , 1.4488207 , 1.7492598 , 1.6266474 ,
       0.9611698 , 1.2561293 , 2.5882823 , 2.2527955 , 1.0691936 ,
       2.4487631 , 2.0652342 , 2.809121  , 1.409978  , 2.806846  ,
       1.4309778 , 3.0193512 , 3.1300008 , 1.9115046 , 5.0971584 ,
       2.8168201 , 1.6861049 , 1.3794155 , 1.934542  , 3.5709872 ,
       1.2043765 , 1.3758131 , 2.325     , 2.354294  , 1.3375785 ,
       3.0095694 , 3.3145728 , 2.730386  , 2.410141  , 1.1935099 ,
       3.4149244 , 3.3246017 , 1.9201033 , 1.3859022 , 3.8019834 ,
       2.9297743 , 5.4746475 , 2.6455529 , 1.6577051 , 2.181637  ,
       1.284449  , 2.3962018 , 1.7684246 , 5.0131383 , 1.7056576 ,
       2.575936  , 0.66443044, 2.521483  , 1.5406554 , 2.1535099 ,
       1.9790995 , 1.6223578 , 1.2728447 , 5.3627424 , 1.0931658 ,
       3.6007175 , 2.7537668 , 2.5248055 , 1.1683749 , 1.7702729 ,
       2.5166335 , 1.5879165 , 1.085167  , 1.1377449 , 1.2495856 ,
       2.0209389 , 1.5890944 , 2.1107962 , 2.6809804 , 2.4334626 ,
       0.61403006, 0.74332106, 1.3265194 , 3.2866461 , 1.1351938 ,
       2.6664736 , 2.1383448 , 2.4746697 , 2.0382092 , 3.863284  ,
       3.5729976 , 1.7856323 , 1.4791751 , 2.5746658 , 1.0443847 ,
       1.5915174 , 1.1969262 , 3.552641  , 6.0735154 , 1.2877339 ,
       3.2465644 , 2.9589646 , 1.9256892 , 1.7765713 , 2.3673143 ,
       1.2538127 , 2.020295  , 3.2401    , 2.5310192 , 2.3239412 ,
       1.1144322 , 4.8653364 , 2.9859571 , 2.8374825 , 2.114011  ,
       1.9181195 , 1.8609021 , 2.3207352 , 0.85193336, 4.471746  ,
       2.7731519 , 1.1244998 , 2.4391398 , 4.04119   , 2.9549105 ,
       2.0472455 , 3.4913306 , 1.6175406 , 1.2045919 , 1.0762789 ,
       2.7773547 , 2.711289  , 1.5100136 , 5.2110863 , 1.5797297 ,
       1.5978084 , 2.2930934 , 3.1584814 , 1.4241523 , 2.4272976 ,
       1.8299041 , 1.8580282 , 2.3862004 , 2.0529191 , 1.2791629 ,
       2.749013  , 2.3844113 , 1.0095781 , 3.4003713 , 2.547324  ,
       1.4771135 , 2.2876613 , 0.83088213, 4.850861  , 1.7894349 ,
       1.4754246 , 3.8511455 , 1.7931643 , 1.791167  , 1.736141  ,
       1.5927815 , 0.67835104, 2.3499687 , 1.4575157 , 2.9843242 ,
       3.1503978 , 1.2678477 ], dtype=float32), array([-5.89499436e-03, -2.72160787e-02, -1.67366210e-02, -5.94603689e-03,
        1.99611410e-02,  8.85348860e-03, -1.29518704e-03, -1.28171351e-02,
       -5.31614386e-03, -1.53376646e-02, -1.98461860e-02, -1.54941343e-03,
       -1.82792433e-02, -1.81232730e-03, -1.30707519e-02, -9.38494038e-03,
       -8.52259900e-03,  4.93179401e-03,  1.49960499e-02, -4.98997793e-03,
        1.06350249e-02, -1.62496716e-02, -3.82976746e-03, -2.33306736e-03,
       -1.54890977e-02,  6.86731469e-03,  2.47112149e-03,  7.71275861e-03,
        5.68560138e-03, -2.87135714e-03, -1.24515193e-02, -5.22819068e-03,
       -6.29065931e-03, -1.64256524e-02,  1.04086781e-02, -1.86504442e-02,
       -2.56602652e-02, -1.61985792e-02,  1.12463413e-02,  1.88185684e-02,
       -1.03263864e-02,  7.46907026e-04,  1.74130015e-02,  3.19678523e-03,
       -8.63563444e-04, -1.37323765e-02, -9.53632966e-03,  7.87156075e-03,
       -5.06082177e-03,  9.42627434e-03, -1.26805902e-02, -2.02344749e-02,
        5.53426566e-03,  2.92844861e-03,  1.52157643e-03, -1.51955439e-02,
        1.12634934e-02, -4.80330433e-04,  6.06382545e-03, -2.30222978e-02,
       -5.40485885e-03,  1.03793037e-03,  2.36793677e-03,  5.59831969e-03,
       -6.24691322e-03,  2.51765363e-03,  6.57700514e-03,  8.60774517e-03,
       -7.74200633e-03,  4.49319743e-03, -1.26161780e-02, -3.97375366e-03,
        1.21933445e-02, -1.21278428e-02, -2.51912861e-04,  2.94794212e-04,
        1.51886954e-03, -7.67691247e-03, -1.86263211e-02,  1.69380684e-03,
        1.47382664e-02, -2.14745663e-02, -1.05272960e-02, -3.31934518e-03,
       -3.19246296e-03,  8.04951601e-03,  1.63308505e-04,  1.10748559e-02,
       -6.85192179e-03,  7.52499545e-05, -1.58186927e-02, -5.66626107e-03,
        2.04776414e-02,  8.05446133e-03,  2.84728408e-03, -1.38737243e-02,
        6.97940774e-03,  9.03052837e-03, -2.73165759e-02, -4.71957400e-03,
        7.89901614e-03,  4.01125726e-04, -1.32388901e-02, -4.17339383e-03,
        9.70920455e-03, -4.84191207e-03,  6.05534250e-03,  8.64261948e-03,
        1.03805342e-03, -1.45992339e-02, -1.84082314e-02, -7.72928819e-03,
        1.54600129e-03, -4.28153481e-03, -1.13473823e-02, -1.39305340e-02,
        4.11784137e-03, -8.29726737e-03,  9.87147912e-04, -1.06370477e-02,
        4.50160773e-03,  6.85212715e-03, -4.72820411e-03,  1.27454998e-03,
       -8.29744153e-03, -4.23192792e-03,  3.21508443e-04, -6.33327756e-04,
       -1.16336634e-02, -1.12588396e-02,  3.29249771e-03, -2.08846573e-02,
        1.95057353e-03, -2.96478672e-03,  1.19789047e-02, -9.76988580e-03,
       -4.94411029e-03, -2.74727889e-03,  8.60347040e-03, -6.18301239e-03,
        1.52752991e-03, -4.97651985e-03, -7.11109350e-03,  3.69924796e-03,
       -1.52866384e-02, -3.64952092e-03,  2.03618011e-03, -2.05849987e-02,
       -2.58529875e-02,  1.13408241e-04, -2.74862658e-04, -1.26873134e-02,
        1.20021543e-02,  2.44252337e-03, -6.54516462e-03,  2.45288899e-03,
       -1.55426795e-02,  2.62010086e-04, -8.22888035e-03, -1.25394352e-02,
       -1.73089129e-03, -1.20497970e-02, -3.96185461e-03,  3.89112765e-03,
       -1.29539371e-02, -7.95370806e-03,  9.33970045e-03,  5.11052320e-04,
       -5.00245485e-03,  2.80332752e-03,  1.34609323e-02, -5.05783642e-03,
       -7.06130173e-03, -1.91723928e-02, -1.34441797e-02, -5.86501649e-03,
       -1.55370194e-03, -1.03023285e-02, -4.51975688e-03,  8.83367751e-03,
       -6.02752855e-03, -1.93259735e-02, -1.28843859e-02,  1.88777584e-03,
       -2.24881386e-03,  4.09396016e-04, -7.86534231e-03, -4.18693945e-03,
       -1.38378516e-02, -5.39539833e-05, -1.28071131e-02, -4.74790158e-03],
      dtype=float32), array([-0.06492983,  0.66161567,  0.00620399, -0.3933343 ,  0.80145645,
       -0.02769609,  0.03263598, -0.16698964,  0.59803724,  0.08280767,
        0.19910541, -0.18423752,  0.26587254,  0.59362596,  0.6071186 ,
        0.83340925,  0.30349523, -0.8500431 , -0.99713796, -0.90363187,
       -0.96638465, -0.6255957 , -0.5110191 ,  0.22554626, -0.61063844,
       -0.3116559 ,  0.5945815 ,  0.1993479 ,  0.94610274, -0.15908767,
        0.85018414, -0.95413876, -0.11965624,  0.6852618 , -0.7271964 ,
       -0.39993227, -0.23801525,  1.1069702 , -0.21930616, -0.07343538,
        0.67980415,  0.57165915, -1.0999088 , -0.3578798 ,  0.49543637,
        0.62183905, -0.3741495 , -0.925331  ,  0.4956764 ,  0.225233  ,
        0.7656298 ,  0.3826479 , -0.86131173,  0.07940315, -1.2885953 ,
        0.993802  , -0.30196613, -0.17856163, -0.7111519 ,  0.36801952,
        0.80346733, -0.48809502, -0.4207791 , -0.82711214,  0.34788132,
        0.47701305,  0.18241757,  0.1440162 , -0.06764843, -0.32507786,
        0.58667177,  0.43253985, -0.4500047 ,  0.06216192, -0.6456644 ,
        0.93130773, -0.00429609, -0.5922901 , -0.02382276,  0.02010262,
       -0.8198552 ,  0.22907531,  0.48638362,  0.42097867, -0.3533849 ,
        0.09838745,  0.60091925, -0.49588618,  0.79987496,  0.23827514,
        0.67128193, -0.28628057, -0.2676081 ,  0.71970296,  0.6114615 ,
       -0.4902134 ,  0.21781619, -0.3104866 ,  0.7393716 ,  0.33204436,
        0.46087307, -0.5654286 ,  0.37685603, -0.5183894 ,  0.9994297 ,
        0.03725378, -0.06290507,  0.06553397,  0.8343976 , -1.1340632 ,
       -0.21887842, -0.02319446, -0.87446505, -0.93919337,  0.06347544,
        0.4263883 , -0.5483838 ,  0.6204913 , -1.1217662 , -0.27185044,
        0.24879351,  0.7516005 , -0.03508776,  0.4497242 ,  0.6681052 ,
        0.6664626 ,  0.61777246, -0.65331024,  0.06188431, -0.24424195,
        0.79796565,  0.7318467 , -0.5287054 ,  0.64072454,  0.8794147 ,
        0.90601134, -0.99443656,  1.0976653 , -0.04440508,  0.40366966,
        0.4315198 ,  0.7642952 ,  0.50248134, -0.14557321,  0.02880309,
        0.38956156, -0.8372247 ,  0.06632655, -0.29538906,  0.20613539,
       -0.6716208 ,  0.9167255 ,  0.3469188 , -0.96475464,  0.0223922 ,
        0.3637799 , -0.34676212,  0.5083105 , -0.60640985,  0.19873478,
       -0.6359586 , -0.31220976,  0.3667939 ,  0.01265867,  0.02236496,
        0.24606489, -0.7687357 , -0.61972564,  0.7191888 , -0.11907751,
       -0.17548534, -0.78059417, -0.12729383, -0.9435803 , -0.3364681 ,
       -0.8920493 ,  0.5813932 , -0.20460448,  0.61899453,  0.519973  ,
        0.3314612 ,  0.72695005, -0.60339165, -0.52268255,  0.03790657,
       -0.06884569, -0.8808523 , -0.3931211 ,  0.22506467, -0.09391034,
       -0.19312404, -0.46868938], dtype=float32), array([3.752315  , 2.4175425 , 0.7506795 , 0.65364367, 4.5539556 ,
       1.5213755 , 3.0736852 , 1.7989392 , 3.082439  , 2.5200365 ,
       1.7748324 , 1.3785156 , 2.016226  , 3.315647  , 2.707328  ,
       3.3496332 , 2.0290904 , 1.9764457 , 3.5543556 , 3.167672  ,
       5.8730545 , 3.2476892 , 1.3987237 , 2.0345945 , 2.1074276 ,
       1.9118125 , 1.9561476 , 3.1752942 , 9.003012  , 3.6409864 ,
       2.6771681 , 1.990839  , 2.2694843 , 2.9140284 , 2.3152204 ,
       1.5903559 , 2.7615407 , 4.804893  , 2.5556085 , 3.7025807 ,
       1.8623369 , 2.7473738 , 9.717823  , 2.8941755 , 2.4694092 ,
       2.1179528 , 1.9298533 , 3.6676958 , 2.2445736 , 1.237815  ,
       3.3359387 , 1.8841616 , 1.7333882 , 1.4367096 , 4.409946  ,
       5.305571  , 4.800798  , 3.7853093 , 2.256856  , 1.424102  ,
       4.371527  , 4.222644  , 0.95901465, 7.148653  , 0.6303514 ,
       2.8571548 , 1.7923057 , 2.0915217 , 2.3876727 , 0.7276232 ,
       2.5504296 , 1.1215973 , 3.6555932 , 2.4016535 , 3.5039644 ,
       2.0898802 , 1.2964524 , 2.928633  , 1.7567235 , 2.3465571 ,
       7.475833  , 3.6032941 , 2.2590756 , 5.2739253 , 1.9593023 ,
       0.69856197, 3.1282713 , 3.3466504 , 2.7451198 , 0.95428795,
       4.2899575 , 3.0260108 , 3.6470213 , 3.682965  , 2.6060882 ,
       4.33536   , 2.2623038 , 1.4930136 , 2.378287  , 2.4136446 ,
       1.6186073 , 2.5286534 , 2.0033147 , 3.425734  , 4.7734    ,
       1.7159811 , 1.0056193 , 2.7865028 , 1.9635425 , 3.4961975 ,
       4.223692  , 2.1971643 , 2.6296687 , 3.5001218 , 3.589599  ,
       4.160651  , 3.3619564 , 2.8912852 , 2.0837963 , 1.1521972 ,
       2.2409277 , 2.136287  , 3.1438038 , 1.412543  , 2.283203  ,
       1.9257607 , 1.5753641 , 2.7202694 , 1.1084454 , 1.184265  ,
       2.268679  , 4.1143703 , 4.9043603 , 1.8168467 , 4.985148  ,
       2.6267025 , 5.3962817 , 5.673403  , 2.4842763 , 2.423068  ,
       2.3482347 , 2.167087  , 2.5104203 , 2.9414802 , 1.49967   ,
       3.741294  , 5.3438635 , 6.656341  , 1.2125708 , 0.9585375 ,
       2.7041783 , 3.3667479 , 2.7478242 , 2.2468336 , 4.112852  ,
       2.8280807 , 3.1799517 , 8.699917  , 2.9449074 , 1.3341986 ,
       7.067225  , 2.1878543 , 1.5055157 , 1.4971445 , 1.87286   ,
       1.2091222 , 6.3086667 , 1.0288534 , 3.7269993 , 1.205562  ,
       2.386233  , 6.119823  , 3.5483682 , 2.4751258 , 1.825473  ,
       2.4533255 , 4.1152334 , 2.455199  , 4.8309355 , 3.9661403 ,
       2.1100898 , 2.12886   , 2.0457416 , 4.1784334 , 0.8926734 ,
       3.6591344 , 4.1430626 , 3.0942066 , 2.1080253 , 3.8047075 ,
       1.6896435 , 3.2998116 ], dtype=float32), array([-1.15302345e-02, -2.02712743e-03, -5.63335343e-05,  6.57556858e-03,
        4.04392462e-03,  1.08370269e-02, -9.18468367e-03,  2.83418838e-02,
       -1.79579500e-02,  8.68147984e-03,  5.57075534e-03,  6.05154922e-03,
       -5.07966382e-03, -1.51017010e-02, -5.25113614e-03,  1.63485073e-02,
       -6.22952497e-03,  1.35292215e-02, -2.28642952e-02,  8.83731700e-04,
       -1.22713414e-03,  7.89169036e-03,  2.27214099e-04,  2.37085228e-03,
        1.46005803e-03, -7.87789375e-03, -3.02399206e-03,  8.58805422e-03,
       -6.58432394e-03,  4.40216344e-03,  3.45584413e-04, -1.76715702e-02,
        1.64188701e-03, -1.34474682e-02, -1.59550179e-02, -1.34975486e-03,
       -1.14497114e-02, -5.42083464e-04,  7.09496718e-03, -4.50619077e-03,
       -7.17730168e-03, -2.05337331e-02,  2.31665242e-02, -1.62327141e-02,
        3.34544131e-03, -4.30854503e-03, -5.47206681e-03, -1.23943649e-02,
       -1.03999488e-03,  5.64687885e-03,  8.77415109e-03,  7.08195847e-03,
       -2.89710127e-02, -2.70456658e-03,  5.22548100e-03,  7.02164485e-04,
       -1.32950507e-02,  5.03121596e-03, -4.37542563e-03, -2.48620869e-03,
       -2.36346908e-02, -2.62610652e-02, -4.34687454e-03,  9.26486962e-03,
        6.75916718e-03,  1.13242138e-02, -2.67052129e-02, -8.73797946e-03,
       -1.07506150e-02, -8.62900726e-03, -9.50057432e-03,  1.63476337e-02,
       -2.70609837e-03,  3.61864502e-03,  2.22539669e-03, -2.09244639e-02,
        1.41187618e-03, -2.04080506e-03, -9.53859929e-03, -8.84351041e-03,
        1.78380636e-03, -5.86113473e-03,  1.77181046e-03, -1.97201408e-02,
        4.08992171e-03, -1.11554777e-02, -1.64181879e-03,  8.65110382e-03,
        4.24534455e-03,  2.65140012e-02, -3.66857462e-03, -3.68078542e-03,
        8.93471111e-03, -1.17142685e-02, -2.44605169e-03, -1.47326430e-03,
       -1.77926486e-04,  1.61166303e-02,  2.03372296e-02, -1.91765707e-02,
       -4.51110769e-03, -8.65355786e-03, -1.42845325e-02, -1.35216757e-03,
        3.36345984e-03,  2.05651429e-02,  5.76916803e-03, -1.15841608e-02,
       -1.61137152e-02,  4.68861964e-03, -4.95614903e-03,  1.16169425e-02,
        4.17846255e-03, -1.60673149e-02,  1.51409581e-02,  2.63256207e-03,
       -1.38620865e-02,  2.74560240e-04, -1.60854273e-02, -9.11415927e-03,
       -6.91178371e-04, -5.51352324e-03,  1.56675396e-03, -7.64932903e-03,
       -3.63470265e-03, -6.84836926e-03,  5.54548157e-03, -1.44968303e-02,
        3.90190585e-03,  3.26247164e-03, -6.48081210e-03,  2.33743549e-03,
       -1.74542125e-02,  2.53874529e-02, -7.20648211e-04,  1.19266687e-02,
       -1.15344366e-02, -8.12517665e-03,  7.67369475e-03,  2.86765099e-02,
       -2.16916483e-03,  4.59504873e-03, -1.54250618e-02,  1.27576094e-03,
       -7.72333378e-03, -7.62903458e-03, -1.47510357e-02,  2.90963184e-02,
        1.35040656e-02,  9.26203444e-04, -1.01554208e-02, -1.46693746e-02,
       -1.40435128e-02, -8.53037089e-03,  5.92730567e-03,  1.56790521e-02,
       -1.59131214e-02,  3.90728610e-03,  3.75897181e-03, -1.09039517e-02,
        1.86971687e-02,  1.50964726e-02, -1.08359745e-02, -1.07098473e-02,
        1.54987033e-02,  9.52070486e-03,  7.12527952e-04, -4.82908031e-03,
        6.99995365e-03, -8.36900715e-03,  1.04329700e-03, -1.42617971e-02,
        1.35989999e-02, -4.85226698e-03, -3.08060087e-02, -1.57517437e-02,
       -8.61127861e-03, -1.39790209e-04, -4.40528849e-03, -6.41018897e-03,
        1.18409656e-02,  2.64641875e-03,  1.80032119e-04, -2.55671539e-03,
        1.41988881e-02,  7.23034027e-05, -5.53970924e-03,  2.97096412e-04,
       -1.02004586e-02,  9.39064845e-03,  4.51853778e-03,  5.40043972e-03],
      dtype=float32), array([ 0.267955  ,  0.9049619 , -1.6298501 , -0.11880793,  1.2092128 ,
       -0.6856404 ,  0.2755743 , -0.73200005,  0.6001673 ,  0.02385973,
        0.5667021 , -0.64735985,  1.3838226 ,  1.3758403 , -0.3203344 ,
       -0.96161026, -0.62286425,  0.49136823,  1.0836962 , -0.9490095 ,
        1.3750154 ,  0.5122404 , -0.8330943 ,  0.360715  ,  0.00701935,
       -1.2043005 ,  0.3983218 , -0.5363458 ,  0.88982695,  0.4546109 ,
       -0.946929  ,  1.3194304 , -0.42772102, -1.2340662 ,  0.5737255 ,
       -1.2902945 ,  1.1958574 ,  0.08330463,  0.40598068, -0.03776319,
       -0.32129326,  1.0823601 , -0.35518843,  1.629861  ,  0.93797296,
       -1.0178009 ,  0.20598672, -0.28791857,  1.1300545 , -0.7434875 ,
       -0.0039546 , -0.10994758,  0.83069134,  0.83208287,  1.0222319 ,
       -0.64952135,  0.53155756, -0.13613212, -0.38985533,  0.28638625,
        1.5534366 ,  0.6194429 , -0.22124836, -0.03363585, -0.99308485,
        0.24514088, -0.3229621 ,  0.03217646,  0.75387603, -0.23223227,
        0.95770586, -0.4182927 , -0.31547928, -1.1851345 ,  0.29666865,
        1.5196319 ,  0.21150151,  0.24497762,  0.6032156 ,  1.1394175 ,
       -0.19846171,  0.2126763 , -1.2267258 ,  1.3025366 , -0.0934677 ,
        0.2836645 ,  0.95980877, -0.95789284, -0.7775931 , -0.744484  ,
        0.44250613, -0.6873181 ,  0.01575656,  0.889448  , -0.576423  ,
        1.7334998 ,  0.25019658, -0.90631044, -0.1782925 , -0.74917424,
       -0.29047337, -1.1223084 ,  1.9691322 , -0.31558293,  2.1048436 ,
       -1.4119242 , -0.86643434,  0.78235453, -1.8080645 ,  0.66411954,
       -0.8310406 ,  0.34464005,  0.03672522,  1.2160451 ,  0.3450688 ,
        2.1885698 ,  0.3877998 ,  0.72972405, -0.49498725,  0.7089086 ,
       -2.084715  ,  1.2284483 , -1.1753949 ,  0.9815641 ,  0.6611789 ,
       -0.16840318,  0.43103912, -1.3206966 ,  1.1849768 ,  0.30592096,
        0.7552211 ,  0.93589914,  0.16894957,  0.17962165, -1.1665916 ,
       -0.18489523,  1.235277  ,  0.43067417,  1.2440175 , -0.3777628 ,
        1.2472576 ,  0.31759617, -0.27058297,  1.2583218 , -0.3730087 ,
        1.0653819 ,  0.6093083 ,  0.3836762 , -0.47015333,  0.0959899 ,
       -0.24563557,  0.9400325 ,  0.29828587,  0.7937564 , -1.2680298 ,
        0.5103045 , -1.0155706 ,  0.4288846 , -0.45778796,  0.82445294,
        0.0678956 ,  0.09292653, -0.96425885,  0.4009063 , -0.09503812,
       -0.06941292, -0.4205864 , -0.02026004,  0.08476765, -0.04221376,
        1.3851999 , -0.07764529,  0.1941493 , -0.9857654 ,  0.9764112 ,
        0.6888613 , -1.3480957 , -0.31763083, -0.08034731, -1.3824704 ,
        0.29644123, -1.169237  , -0.8062178 ,  0.46605435, -0.07940464,
        0.05960349, -1.9440567 ,  0.5083338 ,  1.3024163 , -0.26958194,
        0.25069505, -1.9887033 ], dtype=float32), array([1.7942706, 1.9821073, 3.6842117, 2.986161 , 3.2277858, 3.147973 ,
       1.2819766, 4.559017 , 2.142632 , 1.6663157, 4.6794076, 4.8904386,
       2.8416562, 2.1963708, 3.2083688, 2.9306085, 2.7709215, 2.1747174,
       2.4899898, 2.6375465, 2.8743432, 6.265671 , 2.4777615, 1.8272814,
       3.199774 , 2.9621239, 1.187357 , 2.279717 , 0.9455323, 1.4236687,
       6.6729684, 2.525413 , 2.9826987, 2.9501634, 4.17016  , 1.3608998,
       3.3665695, 2.6113827, 2.389163 , 1.3877081, 3.4857345, 2.8682947,
       3.9147046, 2.1956496, 2.8338187, 3.9797494, 3.094911 , 1.3927469,
       3.885014 , 3.2306516, 3.0051515, 1.7285002, 4.498619 , 3.3246014,
       0.9361212, 3.841246 , 4.5381093, 1.3434883, 3.6717646, 4.5788345,
       2.3020303, 1.914873 , 1.7886314, 4.674874 , 3.4897425, 3.3006186,
       1.3850368, 1.0757521, 2.3251438, 3.1214333, 2.9064035, 3.7347202,
       1.8215953, 4.5845084, 3.391163 , 2.800317 , 3.43194  , 2.0535328,
       1.3449023, 3.230288 , 6.1616507, 3.257689 , 3.729607 , 4.2729797,
       1.2061495, 2.9765985, 1.9770228, 1.0633454, 3.0712368, 3.3025637,
       3.7167952, 3.5330894, 2.4756846, 2.8040738, 2.425251 , 5.0779495,
       1.4829727, 2.6244895, 1.7884965, 2.6279888, 1.6864437, 2.164863 ,
       4.29106  , 1.6976296, 3.8066058, 2.2585475, 2.3892202, 3.649907 ,
       3.964051 , 2.0410295, 2.011229 , 5.3089027, 1.9970679, 2.9072566,
       2.2526007, 4.0265326, 1.5969054, 3.992511 , 2.7927792, 3.3246028,
       4.471604 , 2.2527764, 4.0855565, 2.7943106, 1.7004993, 2.5458205,
       2.5395014, 2.206749 , 3.6590457, 1.7583294, 3.335346 , 1.0201836,
       1.8695105, 2.261763 , 2.4726827, 2.5980666, 2.6830726, 2.4153345,
       3.910605 , 3.7038286, 2.6639388, 2.4668677, 1.5454499, 3.12152  ,
       2.0407588, 2.6928291, 3.7873101, 1.7784629, 2.8047051, 1.6410019,
       1.5064021, 3.6540148, 3.6519349, 2.4989126, 3.2245722, 2.2218254,
       2.013955 , 1.9237994, 3.8228245, 2.6025457, 3.3643694, 3.0065813,
       2.8906796, 1.1033698, 2.5397525, 1.3084205, 1.3490899, 2.3266327,
       2.1697924, 3.2552764, 1.6800789, 1.8551276, 1.9105533, 3.3627734,
       1.397893 , 1.9923761, 2.1055524, 4.7788925, 3.624471 , 2.0938654,
       3.3639908, 1.8235766, 1.5348752, 2.6971915, 4.5554466, 4.5367765,
       2.6842773, 2.4778647, 3.3633592, 1.384408 , 1.9792452, 4.555933 ],
      dtype=float32), array([[[[-0.08095782,  0.0849158 ,  0.01459711, ...,  0.00467869,
           0.01217215,  0.0370733 ],
         [-0.05255252, -0.04047565,  0.06767452, ...,  0.01933013,
          -0.01446025,  0.03865631],
         [-0.05428313, -0.07786476,  0.09023995, ..., -0.02114353,
           0.02727455, -0.04961512],
         ...,
         [-0.09887964,  0.07067672, -0.02649145, ...,  0.04285722,
          -0.07178803, -0.06494778],
         [ 0.03974652, -0.07806267,  0.06819126, ...,  0.02987025,
           0.01081532,  0.02633321],
         [-0.03874004, -0.04373631,  0.04646149, ..., -0.05006304,
           0.0254363 ,  0.01525387]]]], dtype=float32), array([-0.00865538,  0.00090092,  0.00274068, -0.01106623,  0.00299846,
       -0.00051537,  0.03046737,  0.00257582,  0.00053139, -0.01844406,
        0.00484463,  0.01032421,  0.00035333, -0.01338422,  0.01049918,
       -0.00013688,  0.00937039, -0.01122066, -0.00708159, -0.00592068,
        0.00812928, -0.0068167 ,  0.00907013, -0.01014378, -0.00984119,
        0.00920124,  0.02536429,  0.00650788, -0.01376145,  0.00135577,
       -0.00410017, -0.01473165,  0.00120979, -0.00350396,  0.01957842,
       -0.00954926,  0.00738626, -0.00225828,  0.00019832, -0.00539058,
        0.01604101,  0.00152363, -0.00325236,  0.01894753, -0.00281456,
       -0.00538895, -0.00749812, -0.01405927,  0.01516871, -0.0185842 ,
        0.00415317, -0.0093829 ,  0.01003708,  0.00117795,  0.00889456,
        0.01236784, -0.00882409,  0.01359466,  0.01908775, -0.00476225,
       -0.00108586,  0.00799048,  0.0004276 ,  0.00425781,  0.002588  ,
       -0.00616681, -0.00963573, -0.01078366,  0.00428771, -0.00169726,
       -0.00021358, -0.01291313,  0.0088381 ,  0.00024751,  0.00631427,
        0.01764431,  0.01227837, -0.01674873,  0.00337933,  0.00761991,
       -0.00286026, -0.0012662 , -0.01475056, -0.00527207, -0.00127213,
        0.00949403,  0.01197374, -0.0156023 ,  0.00090948,  0.00863781,
        0.00603049,  0.00025857,  0.00671049, -0.00707375,  0.0107779 ,
       -0.00066408, -0.01708115, -0.00136055, -0.00895482,  0.02360162,
       -0.00972147, -0.01505848, -0.00260385, -0.00458403,  0.00072057,
        0.01368312,  0.00370035, -0.00678932, -0.00904076, -0.00479407,
        0.00800478, -0.0028478 , -0.00193891, -0.0084825 , -0.00309425,
       -0.00133413, -0.00029354,  0.00888864, -0.00351893, -0.01647138,
        0.01866457,  0.01035566, -0.01002582, -0.00319565, -0.00096728,
        0.00896929, -0.00172036, -0.0063025 ,  0.00468155, -0.00689305,
       -0.01131726,  0.002953  , -0.00645486, -0.01479337, -0.00519607,
        0.01154066, -0.01376317,  0.00467884, -0.00278824, -0.00301464,
       -0.00089122,  0.00572608, -0.01524487,  0.00148901, -0.02072444,
        0.00384964,  0.003837  , -0.00296588, -0.01007452,  0.00972356,
       -0.00012863, -0.02165559,  0.01790692,  0.01218846,  0.00535497,
       -0.00976692,  0.00021018,  0.01120369, -0.00473803, -0.00853993],
      dtype=float32), array([-1.4042876 , -0.99374443,  0.94179523, -0.8555084 , -1.3580829 ,
        0.5301975 , -0.7953615 , -1.100734  ,  0.37187904, -0.14782819,
       -0.52550256,  0.42190266, -0.36297342,  0.01443586, -0.74323595,
        0.23810855,  0.06272636,  0.04363253,  0.33517054, -0.9353956 ,
       -0.5739052 ,  0.9298406 ,  0.3392894 , -0.06983875,  0.6625465 ,
       -0.8025921 , -0.3239662 ,  0.51101637,  0.07040187, -0.54642457,
       -0.12094139,  0.857672  ,  0.49394253,  0.2698183 , -0.09270053,
       -0.22235833, -0.86733377, -0.93077415, -0.22251868,  1.412248  ,
       -0.7195336 ,  0.7170016 , -0.73168683, -0.3122463 ,  0.5600779 ,
       -0.4642745 ,  1.1212003 ,  0.27256206, -0.58700025,  0.8041866 ,
        0.26306707,  0.50584596, -0.03864014, -0.64779377, -0.09423588,
       -0.22889598,  0.15731676, -1.1601169 , -0.02565728, -0.04259611,
       -0.00945973, -0.9373992 ,  0.38910758,  1.152825  , -0.56067693,
       -0.9452092 ,  0.01779995, -0.09204255, -0.38353124,  0.26783505,
       -0.7363721 , -0.87125456, -0.31642455, -1.2647687 ,  0.65397817,
       -0.39992157, -0.16658767,  0.17820397,  0.488814  , -0.27920818,
        0.5867011 ,  1.0055729 ,  0.869021  , -0.43159294, -0.49442884,
       -0.39652616, -1.0233294 ,  0.30266345, -0.5361087 , -1.0316913 ,
       -0.21488309, -0.7675042 ,  0.28285676, -1.2466298 , -0.36257276,
       -0.5062731 ,  0.2689651 ,  0.3909948 ,  0.12300039,  0.17536081,
       -0.28392932,  0.671882  , -1.2456737 , -1.1113359 , -0.30604956,
       -0.39769495,  0.16275041, -1.6664805 ,  0.02073644,  0.5577331 ,
       -0.35934132, -0.20654044,  0.76662207,  0.25697595, -0.09643372,
        0.23774014,  0.0420865 ,  0.17914733, -0.38744265, -0.4609045 ,
       -0.9754685 ,  1.1328162 ,  0.2759328 ,  0.16751836, -1.0184331 ,
       -0.31433594,  0.51792544,  0.30262795, -0.11276297,  0.05717099,
        0.5045181 , -0.20723546,  0.27913457,  0.7767824 , -0.8855597 ,
       -0.54196644,  0.7191144 ,  0.1329813 ,  0.9933398 ,  0.39624724,
       -0.6859506 , -0.18496084, -0.9216395 ,  0.5057556 ,  0.2041351 ,
       -0.641492  , -0.8687299 ,  0.5739892 , -0.43204737, -0.28562424,
       -0.7624144 ,  0.9955039 ,  0.7522097 , -0.01853751,  1.0330172 ,
       -0.2722523 ,  0.22664471, -0.12185656,  0.9480025 ,  0.4386167 ],
      dtype=float32), array([2.325126  , 2.4013202 , 3.4335554 , 1.6353557 , 1.5691259 ,
       4.5763526 , 4.1862297 , 2.9586422 , 1.6204479 , 1.4274567 ,
       1.1691045 , 1.394632  , 0.96504843, 2.1771379 , 3.140076  ,
       4.6507587 , 0.93272465, 1.2327889 , 3.260699  , 2.4362288 ,
       3.3210921 , 1.8117356 , 1.2791942 , 1.6399941 , 2.0214818 ,
       4.716275  , 1.879345  , 2.5068264 , 2.3752294 , 2.5409794 ,
       4.097117  , 5.525054  , 4.7066817 , 1.5330539 , 1.7330717 ,
       1.4374461 , 1.5273261 , 1.74917   , 1.1623056 , 2.147416  ,
       1.4345726 , 2.0747457 , 3.325288  , 0.68677217, 1.4198714 ,
       3.45704   , 2.5036693 , 2.0764966 , 3.6171775 , 4.1703153 ,
       1.8095622 , 2.4608998 , 0.88582   , 5.552786  , 2.4549804 ,
       1.0086157 , 4.333467  , 3.8956215 , 1.8301412 , 4.822208  ,
       1.6208208 , 1.7162702 , 2.8040442 , 2.1741638 , 1.2125627 ,
       2.2235634 , 0.87074226, 2.399188  , 3.1640036 , 0.7230241 ,
       1.6313462 , 1.0990769 , 3.207624  , 1.0956668 , 4.0902243 ,
       1.9829668 , 1.8217467 , 2.759182  , 4.268442  , 1.4458756 ,
       1.0397096 , 4.3079343 , 2.279625  , 1.5599538 , 1.8701625 ,
       1.6842844 , 2.2639084 , 1.5422635 , 1.2210312 , 2.2051942 ,
       1.2994143 , 4.4027843 , 1.4035378 , 2.03699   , 1.6206423 ,
       1.1675429 , 1.4442576 , 6.0340276 , 3.2869024 , 3.9014025 ,
       3.382913  , 3.5247638 , 2.9571552 , 2.0283234 , 2.0177464 ,
       1.6831318 , 1.059336  , 2.925965  , 4.5006475 , 1.8522929 ,
       1.1752399 , 0.9508759 , 3.0112484 , 2.4400036 , 2.5694828 ,
       2.1452477 , 0.87121105, 3.1749878 , 4.7834735 , 0.9657698 ,
       1.3482206 , 6.8550215 , 4.568686  , 4.8387604 , 2.7572777 ,
       1.4437566 , 2.1217928 , 1.3747034 , 1.6919243 , 2.2019846 ,
       2.0305598 , 1.6688336 , 2.8461056 , 1.6941628 , 3.9256644 ,
       0.9884075 , 2.3808794 , 0.7592088 , 1.958678  , 1.3422202 ,
       1.9574529 , 1.6754864 , 1.6101518 , 2.863886  , 2.3846679 ,
       2.0600908 , 1.2393569 , 1.3283168 , 2.380687  , 1.7776206 ,
       2.576867  , 1.4115547 , 4.592654  , 5.7785892 , 3.3355844 ,
       1.7704419 , 2.4145622 , 4.9918165 , 4.490789  , 1.7225366 ],
      dtype=float32), array([[[[ 2.66763233e-02,  2.84965169e-02, -2.30146237e-02, ...,
           3.74629870e-02,  4.19637449e-02, -1.44617108e-03],
         [-2.91303676e-02, -1.52429035e-02, -5.06769270e-02, ...,
          -2.13395488e-02,  5.91562502e-03, -4.66857525e-03],
         [ 5.47121204e-02,  4.39561792e-02,  3.33043151e-02, ...,
           1.49065896e-03, -1.30155990e-02, -3.75199318e-02],
         ...,
         [-1.79655454e-03,  1.84321310e-02, -3.70506123e-02, ...,
          -1.56446770e-02, -2.88320892e-02, -3.67397554e-02],
         [ 6.04075082e-02,  2.06863377e-02,  4.96255374e-03, ...,
          -2.83193626e-02,  3.96814346e-02,  3.45945731e-02],
         [ 2.03074925e-02, -1.38184968e-02, -2.97787767e-02, ...,
           4.00689319e-02,  3.13953357e-03,  2.08803266e-03]]],


       [[[ 4.11789268e-02, -1.08579732e-03, -8.68958537e-04, ...,
           4.18526009e-02,  5.68041578e-02,  1.69077031e-02],
         [-4.27301116e-02,  2.89636534e-02,  8.19885754e-04, ...,
           2.69471016e-03, -4.64904793e-02, -4.20188531e-02],
         [ 1.12132197e-02,  1.86664134e-03, -2.20174305e-02, ...,
           3.79881635e-02, -2.97214873e-02,  1.75926890e-02],
         ...,
         [ 2.05787774e-02,  3.87152247e-02,  4.06862535e-02, ...,
           6.44872412e-02,  4.93263863e-02, -4.85703051e-02],
         [ 4.82314378e-02,  1.98560674e-02,  2.64396314e-02, ...,
           3.11425775e-02,  4.57739271e-02, -4.37018760e-02],
         [-1.70550197e-02,  1.84077378e-02,  2.07973514e-02, ...,
           5.60528459e-03,  1.41157601e-02,  9.52235516e-03]]],


       [[[ 2.28702798e-02, -2.66244449e-02,  2.93654539e-02, ...,
           3.30639109e-02,  3.35600264e-02, -4.14875820e-02],
         [-2.06204914e-02,  2.50568688e-02,  1.61667131e-02, ...,
          -7.78838247e-03, -5.71064539e-02,  5.48903309e-02],
         [-4.73778397e-02,  5.92162907e-02, -4.85977568e-02, ...,
          -3.17254439e-02,  9.25744316e-05, -8.47695209e-03],
         ...,
         [-2.93208025e-02, -5.36871180e-02, -7.13487621e-03, ...,
           4.56240997e-02,  2.51720324e-02,  4.83049303e-02],
         [ 3.19508240e-02,  4.87848371e-02,  2.31428854e-02, ...,
          -2.82589663e-02,  3.10592889e-03,  1.63660906e-02],
         [ 4.29155938e-02, -3.15819122e-02, -2.88835857e-02, ...,
          -2.83730254e-02,  1.06387259e-02,  4.21328768e-02]]],


       ...,


       [[[ 3.63064483e-02, -5.26767932e-02, -9.11917351e-03, ...,
          -2.59298012e-02,  6.51102094e-03,  4.91632558e-02],
         [ 3.74978818e-02, -4.23860773e-02, -1.81910656e-02, ...,
          -2.95228884e-02,  4.88250342e-04,  1.47038866e-02],
         [-1.51105439e-02,  5.50260544e-02,  9.48487490e-04, ...,
           4.54048030e-02, -5.48162544e-03, -4.28659236e-03],
         ...,
         [ 2.33070385e-02,  2.44133435e-02,  2.78651305e-02, ...,
           6.53709546e-02,  4.82110493e-02,  2.89787888e-03],
         [-4.39855680e-02,  4.75265086e-03, -2.36427737e-03, ...,
          -3.77587900e-02,  2.03931481e-02, -4.76396941e-02],
         [ 4.75927442e-02, -2.26629339e-02,  2.06794459e-02, ...,
           3.42901014e-02, -4.33790870e-02, -7.67391035e-03]]],


       [[[-5.21032102e-02, -4.27749939e-02,  3.60873248e-03, ...,
           3.33265774e-02, -2.70710401e-02, -2.97022108e-02],
         [ 1.70785058e-02,  9.19379294e-03, -4.47917022e-02, ...,
          -5.60437748e-03,  1.16397263e-02,  4.41403799e-02],
         [ 5.24507537e-02, -2.89657786e-02, -4.01334129e-02, ...,
          -4.68955785e-02,  6.68729693e-02,  1.14224497e-02],
         ...,
         [ 9.72416531e-03, -6.56202342e-03, -3.52040865e-02, ...,
           5.13255969e-03, -1.72251873e-02, -3.00930813e-02],
         [ 1.66396257e-02,  5.93191274e-02, -1.54239153e-02, ...,
          -1.88550372e-02, -2.40215287e-02, -1.50674907e-02],
         [ 6.97480328e-03, -2.44254731e-02,  3.18444544e-03, ...,
           3.79154272e-02,  1.80989951e-02,  1.38263600e-02]]],


       [[[ 3.43944691e-02, -2.89809294e-02,  2.24010851e-02, ...,
          -4.21016924e-02, -1.16690621e-02, -1.49594536e-02],
         [-4.87112217e-02, -3.53398127e-03,  1.89824980e-02, ...,
           1.07636433e-02, -5.39050475e-02,  1.71715626e-03],
         [-1.48944305e-02,  5.69770597e-02,  3.12798917e-02, ...,
          -1.48596196e-03, -7.74221611e-04, -2.46932656e-02],
         ...,
         [ 8.54556542e-03, -5.50281182e-02,  1.55949658e-02, ...,
           3.64661515e-02,  2.18469035e-02, -4.60000848e-03],
         [ 1.92918237e-02,  1.12202438e-02, -4.35592011e-02, ...,
          -2.91599501e-02,  1.48717908e-03, -4.73551750e-02],
         [ 1.06489053e-03,  3.92349884e-02,  1.38187297e-02, ...,
          -3.39610986e-02,  4.67411168e-02, -4.62246984e-02]]]],
      dtype=float32), array([-1.25470934e-02,  3.72387678e-03, -2.27258843e-03,  7.72521226e-03,
        4.31946665e-03, -4.60202759e-03,  1.19236205e-02, -5.58962766e-03,
        9.20830946e-03,  8.74724612e-03, -1.59476679e-02, -3.65635729e-03,
       -2.66552903e-03, -2.78457371e-03,  5.86309889e-03, -1.78356632e-03,
        1.04206121e-02, -4.94284264e-04, -1.73371844e-02, -1.81004778e-03,
       -1.32932253e-02,  9.76801850e-04,  2.86582368e-03, -1.94532573e-02,
        1.00238537e-02, -4.86008078e-03, -3.38667445e-03,  3.61849251e-03,
        1.03509761e-02, -4.29532118e-03,  7.89481401e-03,  1.30169205e-02,
       -3.13565019e-03, -9.93597601e-03, -3.11033265e-03, -2.44700313e-05,
        4.94887214e-03, -1.04252212e-02, -1.58001874e-02, -6.61312044e-03,
        1.78774039e-03, -6.09736610e-03, -1.45980332e-03, -6.79120282e-03,
       -2.84561515e-03,  6.05180906e-03,  9.22169350e-03, -3.71362292e-03,
        1.39670679e-02, -8.62147100e-03,  6.68538501e-03, -1.31455380e-02,
       -6.44205185e-03, -7.60891568e-03, -1.11184944e-03,  7.27457972e-03,
        2.67321593e-03, -1.96124776e-03,  5.82214678e-03, -1.60667934e-02,
        8.03738134e-04,  1.61661580e-02, -1.07798669e-02, -1.07294014e-02,
       -5.50547265e-04, -7.90201221e-03,  3.53115174e-04, -1.02772715e-03,
       -9.33975819e-03, -1.01250168e-02,  1.80436336e-02, -1.14019867e-02,
        1.46696821e-03, -1.04219187e-02, -8.65174085e-03, -8.66866298e-03,
       -2.47523095e-03,  3.44849774e-03, -7.88315199e-04, -8.37880839e-03,
       -1.80634309e-03, -2.21701383e-04, -8.91694985e-03,  1.37229124e-02,
       -6.76159374e-03,  1.20739061e-02,  1.33938668e-03,  1.07961772e-02,
       -1.23488875e-02, -7.27266818e-03, -1.56128500e-03, -1.16784871e-02,
        2.22253497e-03,  8.36130639e-04, -1.37721021e-02, -6.58516167e-03,
        1.12048639e-02,  1.30231110e-02, -2.06578104e-03,  8.44872836e-03,
       -6.07648119e-03,  1.03305364e-02,  3.68431816e-03,  5.99204004e-03,
        8.49484093e-03,  1.25165302e-02, -1.39827095e-02,  6.23242580e-04,
        3.62627115e-03, -4.24220366e-03,  9.83068836e-04, -1.59071165e-03,
       -7.10487075e-04, -3.77226807e-03, -1.10730492e-02, -5.46557643e-03,
        3.62746092e-03,  4.67713363e-03,  3.50360060e-04, -1.16061969e-02,
       -9.34626383e-04, -1.09738223e-02, -3.47890053e-03, -1.83854979e-02,
        4.88781556e-03, -7.47661386e-03, -1.74637958e-02,  9.98398405e-04,
       -3.04746558e-03,  1.61173251e-02, -1.35822338e-03, -3.60422162e-03,
       -3.54465167e-03,  9.88438632e-03,  4.06962587e-03, -1.56383384e-02,
       -2.08353507e-03,  9.42950230e-03,  2.63308827e-03,  9.08970740e-03,
        3.77030065e-03, -6.78309938e-03, -3.95774143e-03,  9.47786495e-03,
       -3.89164826e-03,  9.12190974e-03,  4.51065646e-03, -1.18244616e-02,
        1.68169960e-02, -3.07787652e-03,  8.26675072e-03, -2.73323455e-03,
        6.77761389e-03,  1.33817298e-02,  4.25123144e-03,  2.08187066e-02,
       -2.00556545e-03, -7.95060012e-04,  8.14869441e-03,  4.95401165e-03],
      dtype=float32), array([ 6.35377824e-01,  3.23378414e-01, -2.67192781e-01, -2.94217020e-01,
       -5.11003852e-01,  1.78228289e-01,  4.14330423e-01,  4.10404116e-01,
       -7.78145194e-01, -8.35280299e-01,  3.91389728e-01, -2.62399554e-01,
        9.45455909e-01, -4.20062512e-01,  6.08448386e-01, -8.19779038e-01,
        4.51471537e-01,  5.41069984e-01,  4.69606966e-01, -1.96463987e-01,
       -3.00167114e-01,  2.77742594e-01, -6.14094198e-01, -5.06141875e-03,
        3.31792802e-01, -6.90898836e-01, -1.54231060e+00, -1.04836965e+00,
       -5.12904644e-01,  1.45071059e-01,  1.09440660e+00,  4.65200156e-01,
       -1.71082258e-01,  2.76066270e-02, -8.12209189e-01, -2.56581515e-01,
       -3.96243423e-01, -2.60121465e-01,  1.02739386e-01, -5.14936209e-01,
       -1.59198225e-01, -4.93847996e-01, -6.06268287e-01,  6.62950754e-01,
        2.09831133e-01, -3.14057261e-01,  5.69263279e-01, -1.31613839e+00,
        2.75978208e-01,  2.51388490e-01,  5.94106436e-01, -1.07639027e+00,
        3.91527742e-01, -3.57513614e-02,  5.30670285e-01,  7.61905253e-01,
        7.77748078e-02,  1.69245720e-01, -5.34602404e-01,  4.01190400e-01,
        5.39978921e-01,  1.41987294e-01, -2.30084583e-01,  9.06079590e-01,
       -1.15979999e-01,  3.30021918e-01, -2.68667549e-01, -1.29646733e-01,
       -5.94163388e-02,  2.81877309e-01,  3.51457953e-01,  4.82156932e-01,
       -1.81548849e-01,  6.07719302e-01, -5.89292109e-01, -8.44053566e-01,
       -1.64777085e-01,  2.40767170e-02,  3.25554430e-01, -7.25136101e-01,
        6.51275277e-01,  2.43633166e-02,  4.15625960e-01, -4.94091481e-04,
        3.83144468e-01, -8.69957983e-01,  4.18954104e-01, -1.92040205e-01,
        8.56636465e-02, -1.03175659e-02, -2.79909670e-01,  5.27169943e-01,
       -3.74277592e-01, -2.90354411e-03, -6.08578503e-01, -2.86924154e-01,
       -1.17078550e-01,  7.34753087e-02, -1.41151637e-01, -4.31113765e-02,
       -6.79558218e-01, -4.62750457e-02,  3.52662623e-01,  1.40967226e+00,
       -3.45545709e-01, -3.80831987e-01,  2.32011318e-01,  3.92764300e-01,
        1.06742620e+00,  6.27914742e-02, -8.11208606e-01, -3.53955209e-01,
       -7.44251251e-01,  4.46707189e-01,  3.50995660e-01, -2.34132171e-01,
       -9.74167734e-02,  3.00785929e-01,  4.04555082e-01, -3.62623096e-01,
       -4.80907261e-01,  9.09916639e-01,  4.43082631e-01, -6.00913584e-01,
       -6.26250088e-01,  3.90198708e-01,  3.58452052e-02, -3.27780306e-01,
        6.56418979e-01,  1.56419769e-01,  5.23273289e-01, -2.79010415e-01,
       -6.45851254e-01,  4.53808278e-01, -8.03062797e-01,  6.19674742e-01,
       -4.37409103e-01,  1.11766148e+00, -2.06333160e-01, -3.26800734e-01,
        1.30203441e-01,  6.50167316e-02, -2.06083730e-01,  8.69378805e-01,
        9.89685655e-01,  1.33571148e-01,  1.48548007e-01,  4.35148120e-01,
        2.64018234e-02,  5.02701461e-01,  1.62997261e-01,  3.42474699e-01,
       -7.04254806e-01, -4.67311025e-01,  5.35324991e-01,  1.20708860e-01,
       -8.75852168e-01,  3.89644265e-01,  1.32919207e-01, -6.27753973e-01],
      dtype=float32), array([2.5133274 , 1.9588476 , 3.599392  , 2.9302511 , 1.8121731 ,
       2.1545405 , 2.6980674 , 0.8861819 , 1.7015673 , 2.0320387 ,
       1.6427902 , 2.2213147 , 4.3872933 , 1.0260923 , 3.6882417 ,
       3.3643906 , 0.72284174, 5.5048213 , 2.6106248 , 1.8927478 ,
       2.6040835 , 3.0990105 , 1.7535292 , 1.8685948 , 1.468563  ,
       3.5648956 , 4.2651258 , 1.8796617 , 3.7839224 , 0.9673635 ,
       3.7234697 , 1.894519  , 0.9781392 , 1.6391695 , 2.4006927 ,
       1.3026385 , 1.7643174 , 1.86731   , 2.6068664 , 2.5416949 ,
       1.0978718 , 1.7415695 , 1.1236786 , 2.347043  , 2.2317088 ,
       2.314472  , 3.4231246 , 1.5631515 , 5.552026  , 2.652734  ,
       0.60479873, 2.5219264 , 1.5528218 , 0.8327043 , 1.6465628 ,
       1.9495    , 1.4678218 , 3.7111113 , 1.5339559 , 2.456847  ,
       1.9469229 , 5.1913023 , 1.4864588 , 2.804052  , 3.7564368 ,
       1.7423018 , 3.3366158 , 6.00429   , 1.3902937 , 2.4532514 ,
       0.89064604, 1.0960177 , 0.83236724, 1.255359  , 1.9388714 ,
       1.3813012 , 2.005694  , 3.008965  , 2.5126724 , 2.7753682 ,
       3.2834246 , 0.98386866, 2.583637  , 2.1449265 , 1.5881776 ,
       2.7279296 , 1.4597695 , 1.3248456 , 1.6567175 , 2.5045528 ,
       2.9483442 , 0.96711403, 1.7046111 , 4.3690996 , 1.7072796 ,
       1.2066941 , 3.4367497 , 1.2584538 , 0.84875643, 2.179855  ,
       1.7798026 , 2.6667037 , 2.7518866 , 2.8065662 , 2.9319022 ,
       0.8918012 , 0.56829256, 3.5331252 , 1.5838367 , 1.3328505 ,
       1.5100485 , 0.92507035, 0.8691613 , 4.1828585 , 2.787157  ,
       1.1239396 , 2.6209092 , 2.3057115 , 1.7889318 , 5.65942   ,
       1.7454079 , 2.1787865 , 1.2371558 , 2.0758054 , 0.9998155 ,
       1.8396271 , 1.0199509 , 4.4755917 , 3.5042305 , 5.9596906 ,
       1.4784642 , 1.1314602 , 3.615764  , 3.8318725 , 1.4220397 ,
       3.6655846 , 1.945249  , 2.0992234 , 3.304515  , 0.56605583,
       1.0499368 , 0.97941965, 1.0796705 , 4.5931683 , 2.7226727 ,
       5.5608892 , 5.068226  , 1.8936021 , 4.3701997 , 2.5406308 ,
       3.4087791 , 0.7387198 , 1.9315821 , 1.7826395 , 2.0779426 ,
       4.233369  , 4.442579  , 3.2717614 , 5.269715  , 1.3323339 ],
      dtype=float32), array([[[[ 0.05090657,  0.02144537, -0.0509342 , ..., -0.00371754,
          -0.02285463,  0.00455188],
         [ 0.03029038,  0.0457735 ,  0.03254794, ...,  0.0070476 ,
          -0.02829609, -0.04056696],
         [-0.07753345,  0.01768572,  0.04720128, ...,  0.07587809,
          -0.01585533,  0.06814817],
         ...,
         [ 0.01556023,  0.04047895,  0.04212885, ...,  0.04384226,
           0.07323554, -0.08049162],
         [-0.00262095,  0.04738469, -0.05328914, ..., -0.02404684,
           0.07491492,  0.06153822],
         [-0.00774705,  0.0726882 , -0.07676166, ...,  0.01477326,
          -0.04773526, -0.06446823]]]], dtype=float32), array([[[[ 1.43593652e-02,  2.21483260e-02, -1.03504341e-02, ...,
          -1.48944845e-02, -3.37233692e-02, -3.77133712e-02],
         [-5.32766171e-02, -5.66388331e-02,  4.34623212e-02, ...,
           4.34584692e-02,  2.46545523e-02, -8.23119935e-03],
         [ 6.29938990e-02, -3.25541832e-02, -1.51461903e-02, ...,
          -5.03866151e-02, -4.37929370e-02, -3.74776758e-02],
         ...,
         [ 4.75172997e-02,  9.89820459e-04, -3.50311659e-02, ...,
           4.64778543e-02,  2.21711788e-02, -1.39357829e-02],
         [-2.82665212e-02,  4.22967933e-02, -4.20816150e-03, ...,
           6.35949848e-03,  3.27779260e-03, -1.79802161e-02],
         [-4.70991284e-02, -3.65529172e-02, -4.32975926e-02, ...,
           7.02650007e-03, -3.38081829e-02,  3.10343946e-03]],

        [[-1.45447010e-03,  3.64918113e-02, -2.23594047e-02, ...,
           2.74883537e-03,  8.81837402e-03, -3.39351743e-02],
         [ 3.91104771e-03, -6.37296634e-03,  2.79806126e-02, ...,
          -4.00662422e-02, -2.57434184e-03,  3.14363018e-02],
         [ 3.87008153e-02, -4.76748263e-03, -1.11644939e-02, ...,
           6.86153537e-03, -1.32097760e-02,  4.16732728e-02],
         ...,
         [ 2.71906685e-02,  1.32311825e-02,  1.53511099e-03, ...,
          -6.39506010e-03,  5.24972426e-03,  5.23363659e-03],
         [ 2.74419319e-02,  1.74305029e-02,  5.86472079e-03, ...,
          -2.86128707e-02, -4.77288961e-02,  8.16289987e-03],
         [-9.68049839e-03, -3.16974800e-03, -2.56549492e-02, ...,
          -3.78984697e-02, -4.39608358e-02,  1.13664363e-02]],

        [[-1.66251026e-02,  8.02301243e-03, -6.55245082e-03, ...,
           5.36471866e-02,  2.31933128e-02, -5.01212776e-02],
         [-3.62660475e-02, -3.30245346e-02,  2.85748448e-02, ...,
           2.32623331e-03,  9.01541859e-03,  2.58037690e-02],
         [-4.06045793e-03, -6.03532605e-03,  4.15818021e-02, ...,
           1.73534341e-02, -6.55155163e-03,  2.96623241e-02],
         ...,
         [ 5.87914735e-02,  2.21993160e-02,  2.00140551e-02, ...,
           4.08307053e-02, -1.35997254e-02, -7.73211708e-03],
         [ 2.95643322e-02,  3.26047391e-02,  3.47114094e-02, ...,
           2.27432903e-02,  2.74987929e-02,  3.85727249e-02],
         [-3.39291282e-02,  4.11294922e-02, -2.83254660e-03, ...,
          -3.17304395e-02,  3.66330072e-02, -3.45096029e-02]],

        ...,

        [[ 1.71038206e-03, -3.35603096e-02, -6.48942590e-03, ...,
          -1.84616316e-02,  3.40683409e-03,  4.00320701e-02],
         [-3.26225534e-02, -2.50486434e-02,  4.10846919e-02, ...,
           2.04098299e-02, -1.62745931e-03,  2.00289451e-02],
         [ 4.55493666e-02, -6.38992200e-03, -7.00040779e-04, ...,
           2.48808018e-03, -5.35243973e-02, -6.42937003e-03],
         ...,
         [-1.06838476e-02,  2.78375391e-02, -2.67991554e-02, ...,
           6.75974693e-03,  4.66838814e-02, -2.42689140e-02],
         [-2.88139433e-02,  5.00454195e-02, -1.25460224e-02, ...,
          -3.87395024e-02,  3.80868725e-02, -2.19869008e-03],
         [ 5.61450608e-03, -6.37072138e-03, -3.97073999e-02, ...,
           3.52607742e-02,  8.28283187e-03, -1.67108774e-02]],

        [[-1.10458955e-02,  4.45961468e-02,  9.83212702e-03, ...,
           1.37573835e-02, -3.21284821e-03, -3.37111391e-02],
         [-8.59745126e-03,  4.68395315e-02, -3.20493393e-02, ...,
          -2.93882433e-02,  1.76626705e-02,  2.10225508e-02],
         [ 4.00701165e-02,  2.15675905e-02,  7.22581986e-03, ...,
           1.78178642e-02, -3.16103399e-02, -2.59694085e-02],
         ...,
         [ 1.76258094e-03,  2.25078315e-02, -2.42788270e-02, ...,
           3.73359770e-02, -9.50219017e-03,  8.40382278e-03],
         [ 8.60353559e-03,  1.15942592e-02, -5.19598229e-03, ...,
          -2.94381473e-02, -6.41793609e-02,  8.70155418e-05],
         [ 2.53260788e-02,  2.60314085e-02,  2.52029095e-02, ...,
          -4.50429581e-02, -5.06125540e-02, -2.38506626e-02]],

        [[-1.77099351e-02, -3.56608517e-02,  4.09549139e-02, ...,
          -2.00638603e-02, -1.61337927e-02, -2.70340424e-02],
         [ 2.79196464e-02,  4.20517959e-02,  2.16388199e-02, ...,
           2.04142556e-02,  2.82216538e-02, -1.91963138e-03],
         [-3.04178451e-03,  1.05572604e-02,  3.08766812e-02, ...,
           1.05056206e-04,  3.11432709e-03, -3.42665352e-02],
         ...,
         [ 2.44259369e-02,  4.73510474e-02,  3.94656882e-02, ...,
           4.11507376e-02,  2.70294044e-02,  3.32994796e-02],
         [ 3.20601873e-02,  5.95731102e-02,  2.57964130e-03, ...,
           2.06774566e-02, -5.59594594e-02, -2.89690793e-02],
         [-5.69391288e-02, -5.34725823e-02,  4.65578446e-03, ...,
           6.88986853e-02, -4.06952165e-02,  3.33090983e-02]]]],
      dtype=float32), array([-4.00747592e-03, -8.67260341e-03, -7.40116555e-03, -1.30958883e-02,
       -9.67104174e-03,  4.26947925e-04,  1.98778268e-02, -8.50273110e-03,
       -1.27446121e-02, -7.48815108e-03, -4.21331590e-03, -5.03368536e-03,
       -1.05111822e-02, -9.68590658e-03,  1.80103593e-02,  9.17263422e-03,
       -7.61913077e-04, -2.86654406e-03,  7.81675335e-03, -7.48808729e-03,
        8.00335407e-03,  2.88296724e-03, -1.92874484e-02,  6.03066757e-03,
       -6.80068275e-03,  2.38986383e-03,  1.10792862e-02, -4.19451063e-03,
       -7.72031955e-03,  1.19986832e-02,  8.55094381e-03,  7.97789451e-03,
       -1.27721513e-02, -2.70993984e-03, -7.53953960e-03, -5.68477996e-03,
       -5.76354237e-03, -1.39630558e-02, -6.27301680e-03, -1.42499702e-02,
       -1.06605813e-02,  1.06351217e-02, -1.00600347e-02, -3.09133600e-03,
        1.66881196e-02,  2.38068961e-03, -6.48912741e-03,  9.80637688e-03,
       -1.37560358e-02, -4.82209912e-03, -1.53405396e-02,  1.65623650e-02,
       -9.46973916e-04,  2.18392387e-02,  1.99788734e-02, -1.65845118e-02,
        1.27173460e-03, -1.33067742e-02,  4.91841137e-03, -6.86655566e-03,
       -1.60616804e-02, -8.10453761e-03, -3.34838172e-03, -6.08081836e-03,
        6.68934966e-03, -3.22354655e-03, -1.49044907e-02, -2.45750824e-04,
        6.96559157e-03, -6.37202873e-04,  1.50930695e-02,  2.45323032e-02,
       -1.97898429e-02, -2.83102016e-03,  1.43910444e-03, -5.99093921e-03,
       -1.69245787e-02, -7.94250891e-03,  4.53825062e-03, -6.74126763e-03,
       -1.64814647e-02,  1.13380132e-02,  5.59533837e-05,  1.63843445e-02,
        7.52220443e-03,  3.13376798e-03, -7.92778376e-03, -3.48760956e-03,
        1.37954438e-02,  3.05504003e-03, -1.11941034e-02,  7.41613843e-03,
       -6.60516834e-03,  1.44529095e-05,  1.36231876e-03, -8.07664357e-03,
        1.64465718e-02,  7.11418223e-03,  4.54903347e-03,  1.03710070e-02,
        4.35906136e-03, -6.53834594e-03, -1.35576520e-02,  3.87503416e-03,
       -2.68880688e-02,  1.37114245e-02, -5.12822066e-04,  1.61182582e-02,
        8.46888218e-03, -8.73966888e-03, -1.25865834e-02, -5.37361111e-03,
       -4.02571866e-03,  3.24424962e-03, -7.43569015e-03,  2.90383212e-03,
       -2.33207061e-03, -1.92099754e-02, -6.83488883e-03, -1.36894137e-02,
        1.05828410e-02, -2.28042458e-03, -7.17247417e-03, -9.15631000e-03,
       -1.11416792e-02, -7.83202704e-03, -1.41548389e-03,  1.19648132e-04,
       -2.28201621e-03, -1.69082806e-02, -5.91294654e-03, -2.38642339e-02,
        5.20559074e-03,  2.22589672e-02,  2.46189837e-03, -9.94901545e-03,
        2.46981066e-03, -8.40704888e-03, -1.58946104e-02, -3.88488616e-03,
       -7.58051174e-04, -4.99700708e-03, -1.46728987e-02,  1.06415497e-02,
        1.11638941e-02,  1.60388614e-03, -7.55052688e-03, -5.53576462e-03,
        4.92499862e-03, -8.15300923e-03,  1.05341040e-02,  4.83412063e-03,
       -1.52956252e-03, -2.64886562e-02,  3.99687374e-03, -1.55068813e-02,
       -1.33395521e-02,  2.01599430e-02,  1.01652713e-02,  2.12362781e-03],
      dtype=float32), array([ 0.29692462, -1.0435802 ,  0.01541758,  0.06333426, -0.1715203 ,
        1.0414617 , -0.32575992,  1.2056959 ,  0.4060758 , -0.03504979,
       -0.7008833 ,  0.17950884,  0.5442788 , -0.70521396, -1.4522263 ,
        0.31312478,  1.1653737 ,  0.5666115 , -0.41748822,  0.42677498,
       -0.06949939, -0.1468705 , -0.00630054, -0.99182874,  0.5846563 ,
       -1.3964199 ,  0.03003334,  0.5774357 ,  1.3337668 , -1.409845  ,
        1.2497202 , -0.17463195,  0.9675238 , -0.91360134, -0.04931995,
        0.1307607 , -0.5945804 , -0.32525623, -0.4232006 ,  0.19857477,
       -0.8478581 ,  0.5387068 , -0.38289544,  0.902277  ,  0.43071902,
       -1.2507044 ,  0.4523187 , -1.0980319 , -0.36602062,  0.906011  ,
        0.41821113, -0.48755792,  0.50034386, -0.5843135 , -0.47044507,
        0.04432176,  0.8695285 ,  0.675082  , -1.1724795 ,  0.64592016,
       -0.62658376, -1.0878322 ,  0.4088999 ,  0.9225369 , -0.07008705,
       -0.87458456, -0.92261916,  0.12014431, -0.10554078,  1.4189997 ,
       -0.9224049 ,  0.50300574, -0.3894174 , -1.1262174 ,  0.783438  ,
        0.18343684, -0.15168162, -0.24835625, -0.03234859,  0.54883254,
        0.8362251 ,  0.14536715, -0.61429006,  0.3743227 ,  1.3208855 ,
        0.713842  ,  1.6249979 , -0.6620335 ,  0.48726854,  0.5063259 ,
        0.2678474 , -0.43522206,  0.19878066, -0.64263093,  1.5066458 ,
        0.57885057, -0.02893238, -0.32989094, -1.3708874 ,  0.20861512,
        0.27385145,  0.59233314, -0.34595776, -0.78938794,  0.39270782,
       -1.010073  ,  0.26145282,  0.10826793,  0.399156  , -1.2970009 ,
       -0.2265374 ,  1.1463366 ,  0.0600569 , -0.5690602 ,  0.16141927,
        0.7192754 ,  0.20636223, -0.12451413, -1.1174582 ,  0.47650087,
        0.443254  , -0.53220725,  0.60497665,  0.5134894 ,  0.293847  ,
       -0.03962345,  0.17837033,  1.0696414 ,  0.8946906 ,  0.46098068,
       -0.4839081 ,  0.37018895, -0.3260851 ,  0.15973738, -1.4747401 ,
       -0.20459405,  0.6224796 ,  1.1533418 ,  0.67686063,  0.19995086,
       -0.794982  ,  0.7757617 , -0.14434576, -0.08167253,  0.9310472 ,
        0.51938695,  0.8753598 ,  0.5827588 , -0.15846005, -0.8096785 ,
       -0.50182617, -0.5096321 ,  0.6452453 ,  0.10194802,  0.8406554 ,
        0.10644383,  0.25916883,  0.08655152, -0.08065898,  1.0912291 ],
      dtype=float32), array([6.1601186 , 1.5180157 , 6.490711  , 2.274128  , 2.8602664 ,
       4.2601194 , 4.543417  , 6.119935  , 1.6891869 , 2.1112802 ,
       1.6695971 , 1.4747729 , 3.5419333 , 1.6119472 , 1.6639132 ,
       4.197758  , 3.2757287 , 2.803444  , 3.8701806 , 2.1391017 ,
       2.9121437 , 2.0901408 , 2.6470017 , 1.3729528 , 1.45175   ,
       2.987862  , 1.3705982 , 2.5016394 , 6.4640193 , 1.2717485 ,
       3.4927523 , 1.5257827 , 3.579089  , 2.2948284 , 1.9612793 ,
       4.1090283 , 1.3144375 , 1.9267881 , 1.4783871 , 1.7724838 ,
       1.9431992 , 7.0044847 , 2.041768  , 5.65803   , 1.0885661 ,
       4.4135084 , 3.023068  , 2.0611155 , 2.791127  , 3.911214  ,
       1.8397305 , 1.7578778 , 2.7895463 , 3.1078768 , 2.3082948 ,
       5.343346  , 3.756168  , 5.981815  , 3.7487142 , 6.354815  ,
       2.6375663 , 2.4932678 , 3.3689759 , 2.6110573 , 1.485748  ,
       3.262825  , 1.8854066 , 1.0127001 , 2.8918438 , 3.1884358 ,
       4.2624846 , 3.7318015 , 2.463961  , 2.889864  , 3.9729397 ,
       1.9975128 , 4.3629193 , 1.9329277 , 3.645661  , 6.29129   ,
       3.4456835 , 2.0220315 , 2.7435308 , 3.1813812 , 9.427968  ,
       5.591643  , 7.2920923 , 1.9692106 , 3.6325765 , 5.9531    ,
       0.97709066, 2.421488  , 2.3064177 , 1.1075696 , 6.1174126 ,
       5.6872683 , 2.6856592 , 3.8197103 , 3.591324  , 4.991774  ,
       4.604858  , 4.579388  , 1.6033198 , 1.0771402 , 4.409625  ,
       1.9656912 , 1.0794808 , 4.6460905 , 2.0172694 , 2.615985  ,
       1.2119664 , 3.7494872 , 1.6709486 , 1.7479674 , 2.064253  ,
       2.093044  , 1.7425643 , 2.2588594 , 2.1597385 , 2.9502099 ,
       1.3712839 , 2.2863467 , 1.8996102 , 5.3790865 , 4.572629  ,
       1.5102199 , 1.805891  , 4.0047956 , 7.0547004 , 4.395974  ,
       1.6692331 , 1.4571191 , 1.8583267 , 2.4405758 , 3.21507   ,
       2.253105  , 4.54284   , 2.3860013 , 3.963251  , 0.9074682 ,
       3.8832865 , 3.527471  , 3.2543368 , 2.1028593 , 7.4023957 ,
       3.903668  , 3.1307912 , 2.3051958 , 1.2242092 , 2.1780314 ,
       1.8270411 , 2.315453  , 2.1783116 , 1.9518975 , 6.063205  ,
       5.5841827 , 3.8606498 , 2.3212543 , 3.0858142 , 2.7993155 ],
      dtype=float32), array([ 6.51417021e-03, -9.34493728e-03,  1.12656376e-03,  2.51161680e-02,
        4.52053361e-03, -1.22111728e-02,  1.73285429e-03, -8.93865153e-03,
       -2.02089120e-02, -6.99013984e-03, -1.23862717e-02, -4.27236967e-03,
        3.45612946e-03, -5.24413888e-04,  4.22344543e-03, -3.36481072e-03,
       -9.15433653e-03, -1.04164677e-02, -8.47675372e-03, -3.22077866e-03,
       -4.34638467e-03, -1.11512281e-02,  6.94773579e-03, -8.53357557e-03,
        5.88043127e-03, -5.22426004e-03, -1.99854653e-03, -8.80397018e-03,
        2.83353869e-03,  2.44174944e-03,  3.23023669e-05, -1.35738577e-03,
        2.53044860e-03, -4.96108551e-03, -7.77432323e-03,  1.46742836e-02,
       -3.91348125e-03,  1.73460264e-02,  6.94607105e-03, -2.19133217e-03,
       -1.65082868e-02, -1.90677983e-03, -5.59736881e-03, -1.15547946e-03,
       -3.85940121e-03,  2.72657897e-04, -1.87499579e-02, -3.07307765e-03,
       -1.04145799e-02, -1.95040349e-02, -7.73018273e-03, -1.77253690e-02,
       -1.12315677e-02, -1.43007170e-02, -6.67018211e-03, -5.57180028e-03,
       -1.18515734e-02,  4.71099699e-03, -4.61413618e-03, -3.87177523e-03,
       -1.44352429e-02,  6.44901954e-03, -2.09931284e-03, -4.41887835e-03,
       -1.19305672e-02, -6.11767825e-03, -9.00788605e-03, -5.09828422e-03,
        1.76692696e-03, -1.98022742e-03, -1.78568121e-02, -2.60013225e-03,
       -1.45833446e-02, -1.45869609e-03,  3.47482273e-05, -4.66941250e-03,
        9.70618054e-03, -1.87957287e-02, -3.67054506e-03, -4.52962378e-03,
       -1.45859644e-02,  6.17875345e-03, -1.01527711e-02,  7.91002158e-03,
       -8.45814310e-03, -4.88894805e-03, -5.01225656e-03, -5.77289658e-03,
       -1.00386329e-02,  3.90308350e-03,  8.04624753e-04, -9.28021781e-03,
       -5.09970356e-03,  1.53238298e-02, -1.61181635e-03,  1.02493269e-02,
       -1.28656509e-03, -3.39205121e-03, -3.33988038e-03,  7.15060811e-03,
       -1.04256747e-02,  6.52470673e-03, -1.19805150e-02, -1.44128839e-03,
        1.83151253e-02, -1.58547014e-02, -6.91458303e-03, -3.87422508e-03,
       -1.23452973e-02, -2.79759010e-03, -3.10423994e-03, -4.31180699e-03,
        1.69651881e-02, -6.78328797e-03, -1.79460719e-02, -1.19287763e-02,
        1.13407960e-02,  3.56341409e-03,  8.25593621e-03, -4.00178414e-03,
        4.71124332e-03, -5.88583481e-03, -1.26503315e-02,  5.62549612e-05,
        4.76533693e-04,  3.21734743e-03,  4.00382839e-03, -2.89451843e-03,
        1.76517712e-03, -6.36715069e-03,  1.69454550e-03,  7.56400125e-03,
       -1.87508371e-02,  1.03431602e-03,  5.36547462e-03, -1.47675686e-02,
       -2.21667229e-03,  9.31869261e-03, -1.78479664e-02,  8.98470264e-03,
       -2.48363544e-03, -1.51121300e-02,  4.27055871e-03,  6.02824090e-04,
       -6.61249913e-04,  1.79257970e-02,  1.21175982e-02,  9.75562166e-03,
        6.16108486e-03, -6.41956786e-03,  7.48648681e-03, -1.84601313e-03,
       -4.40156879e-03,  2.22087116e-03, -1.45127671e-03, -1.96042540e-03,
       -1.29220532e-02,  9.73912701e-03, -3.83950118e-03,  1.27133094e-02],
      dtype=float32), array([ 3.73562813e-01,  7.10436046e-01,  1.09125085e-01,  7.72127330e-01,
        5.55641651e-01, -3.99457276e-01, -2.40823254e-01, -2.39955589e-01,
       -3.90096128e-01,  1.18595667e-01, -2.13235125e-01, -1.01194227e+00,
        8.84810239e-02,  4.19591218e-01, -8.01832825e-02,  6.86974943e-01,
       -5.78388810e-01,  9.12587121e-02, -3.45929205e-01,  2.76771277e-01,
        4.25159007e-01, -5.28096333e-02,  6.76642060e-01,  6.88594759e-01,
       -1.38737869e+00,  1.09446239e+00, -2.20040634e-01, -8.10407043e-01,
        4.89388943e-01,  3.18917572e-01,  1.29913777e-01, -3.67264867e-01,
       -1.06952441e+00, -6.13159895e-01, -9.84969020e-01,  6.04294091e-02,
       -4.00992900e-01,  5.18871844e-01,  1.22942969e-01,  4.77707118e-01,
        2.04859793e-01,  6.90755725e-01, -1.14708066e+00,  4.98571575e-01,
       -6.42948925e-01, -1.10981214e+00, -1.20522571e+00,  7.65763968e-02,
       -1.08146533e-01, -5.77420533e-01, -3.00291687e-01,  4.70194399e-01,
       -4.71906513e-01,  4.53590276e-03, -8.35583866e-01,  8.98539960e-01,
       -2.76037246e-01, -6.29655421e-01,  2.70229399e-01, -1.80199012e-01,
       -3.90777558e-01, -1.04921746e+00,  2.15212449e-01,  9.05660819e-03,
       -2.97060102e-01, -3.55771273e-01,  5.82183778e-01,  1.14930868e-02,
       -1.15654314e+00, -3.47984731e-01, -6.72526717e-01, -1.41942516e-01,
        4.46520634e-02,  9.56476927e-02, -1.74833164e-02, -4.71346170e-01,
       -1.30476564e-01,  8.79545450e-01,  1.27688795e-01,  6.73919141e-01,
        4.21952814e-01, -5.84409237e-01, -6.23710692e-01,  6.65547401e-02,
       -7.01041892e-04, -1.58183515e-01, -1.71116106e-02,  5.06592870e-01,
       -1.08880174e+00,  4.80893180e-02,  3.32080036e-01,  6.96737587e-01,
       -1.84128240e-01,  3.46686095e-01,  1.34738612e+00, -2.09484175e-01,
       -1.30383337e+00,  3.80426854e-01, -7.74586082e-01, -3.29301119e-01,
       -2.20925771e-02,  7.30803143e-03, -4.93442029e-01,  1.15353942e+00,
        1.41636217e+00, -5.40346682e-01,  9.04683322e-02, -1.39931548e+00,
       -1.04447579e+00, -5.80435917e-02,  5.20134449e-01,  9.18318093e-01,
        1.03238785e+00,  1.35869920e+00, -5.80594130e-02,  1.48763344e-01,
        1.83990702e-01,  6.36382282e-01,  1.29111364e-01, -1.17728031e+00,
       -6.39079273e-01,  3.22937787e-01,  7.29632378e-01,  9.74449456e-01,
        6.22539520e-01, -3.78448188e-01,  6.06897427e-03, -4.43449169e-01,
       -9.12773088e-02,  2.14744091e-01,  1.32931471e-01,  1.10678339e+00,
        8.20616126e-01, -2.94047028e-01,  6.62415266e-01, -5.50899684e-01,
       -4.64321107e-01, -4.38518494e-01, -3.56921345e-01,  5.51444590e-01,
       -5.00239313e-01, -2.57446826e-01, -4.05912280e-01, -4.84046251e-01,
        4.50302601e-01,  6.49528861e-01,  3.94071996e-01, -7.44086325e-01,
        8.72279346e-01, -2.84258842e-01, -1.05473995e+00,  2.93448955e-01,
        1.55091390e-01,  3.60801220e-01,  1.48010477e-01, -4.29712653e-01,
       -6.60359085e-01, -1.39006376e-01, -4.52788383e-01,  6.14805102e-01],
      dtype=float32), array([3.6793907 , 6.099917  , 3.0825925 , 2.1813297 , 4.2674932 ,
       1.0315785 , 1.431188  , 1.2458653 , 2.9482386 , 1.9199929 ,
       1.879701  , 1.5218203 , 3.8949199 , 1.8090173 , 2.8276842 ,
       3.8614945 , 2.900986  , 2.6420164 , 2.1646147 , 1.930096  ,
       1.9963087 , 1.0069817 , 4.125985  , 1.6610132 , 3.463237  ,
       4.143902  , 2.3286817 , 2.2830791 , 3.0711617 , 4.245987  ,
       4.5063887 , 1.4394453 , 3.3809063 , 1.587443  , 2.0358634 ,
       0.8628127 , 1.2728592 , 4.74681   , 2.545668  , 2.4200978 ,
       1.1824268 , 2.7277062 , 2.6180658 , 5.4577093 , 1.1075417 ,
       1.9840115 , 2.1711118 , 1.1638979 , 0.81208956, 1.3510226 ,
       4.3008866 , 2.7581558 , 1.5413979 , 2.0385158 , 3.1746569 ,
       4.7191215 , 1.3162524 , 2.5967214 , 3.1282957 , 0.6904335 ,
       1.7127213 , 3.1434155 , 2.1491237 , 1.948849  , 1.6964695 ,
       2.342312  , 2.524947  , 3.229339  , 2.6736732 , 2.2640612 ,
       1.5153095 , 0.8692251 , 3.1375377 , 1.4956841 , 2.0867686 ,
       1.6544712 , 3.199765  , 2.5592039 , 2.7235408 , 2.907356  ,
       2.6039844 , 2.8626084 , 2.794505  , 0.74583936, 1.5853964 ,
       1.1126485 , 2.1485727 , 2.076874  , 3.231518  , 3.4018748 ,
       2.685359  , 5.8279305 , 2.3234692 , 5.1732097 , 5.2855544 ,
       3.333227  , 2.40965   , 3.410386  , 1.7730361 , 1.1781641 ,
       0.8574067 , 3.9506912 , 1.9695884 , 3.1712568 , 4.246597  ,
       1.4920055 , 3.1452847 , 2.4219146 , 1.8784746 , 1.5796795 ,
       1.4715657 , 3.3449109 , 2.292541  , 1.7857703 , 1.7801615 ,
       2.0865076 , 2.6110582 , 2.7865996 , 2.9633267 , 6.2381883 ,
       1.3486644 , 4.515968  , 6.2834897 , 5.5472455 , 2.4789727 ,
       2.1190715 , 4.696603  , 2.6930094 , 2.8551722 , 1.9565537 ,
       2.4228425 , 1.7198237 , 1.3927855 , 1.4705256 , 1.5697316 ,
       1.95069   , 1.8242989 , 1.4777544 , 1.1058562 , 1.5460776 ,
       0.9178747 , 2.2776945 , 2.007006  , 1.9570671 , 2.3294723 ,
       2.3543847 , 4.367023  , 1.7793204 , 2.281833  , 3.1159031 ,
       2.2989    , 2.7031565 , 1.4844214 , 1.9609523 , 3.7813215 ,
       3.3590138 , 2.387079  , 1.9232112 , 1.8035469 , 2.6312764 ],
      dtype=float32), array([[[[ 0.02388525, -0.01690694,  0.05971316, ...,  0.03160022,
           0.04951876, -0.01551751],
         [ 0.05088702,  0.03895723,  0.00023314, ...,  0.02981209,
          -0.010019  ,  0.03321726],
         [-0.03490707,  0.04412093,  0.0116465 , ...,  0.00524045,
           0.03566627, -0.04399548],
         ...,
         [ 0.02868525, -0.0573601 , -0.01479458, ...,  0.03602766,
          -0.02954949, -0.01940938],
         [-0.01406429,  0.04926251,  0.04537079, ...,  0.03599359,
           0.02791907, -0.0135234 ],
         [-0.04894051, -0.01295642,  0.00541987, ...,  0.05235159,
           0.04313035, -0.01627152]],

        [[ 0.01907949, -0.03217503,  0.03939273, ...,  0.0157071 ,
           0.01975704,  0.00684152],
         [-0.01312797,  0.00395401, -0.03050944, ..., -0.0352927 ,
           0.02282607, -0.0519859 ],
         [-0.00849437, -0.01878476,  0.04999581, ..., -0.0051866 ,
           0.01583118,  0.02808465],
         ...,
         [-0.0225854 , -0.04292464, -0.03273904, ..., -0.02582747,
          -0.04583609, -0.01408841],
         [-0.06390218, -0.03058876,  0.0040817 , ..., -0.0011057 ,
           0.02472117, -0.02554719],
         [-0.01343752, -0.00688566, -0.04078775, ..., -0.03177389,
          -0.01739505, -0.02585635]],

        [[-0.01122208,  0.02161404, -0.0301351 , ..., -0.04004851,
           0.03430991, -0.02553127],
         [ 0.01357   ,  0.0282064 , -0.03429632, ...,  0.02736868,
          -0.05224537, -0.02373691],
         [ 0.03642989,  0.03142952,  0.04504682, ...,  0.04906903,
           0.04371388,  0.04469249],
         ...,
         [-0.01082191, -0.02682876,  0.0227311 , ..., -0.02555224,
          -0.04362159, -0.03365931],
         [ 0.01938101, -0.01156376,  0.01996347, ...,  0.02154974,
           0.01163616, -0.03646154],
         [-0.04232633,  0.02815391,  0.03585235, ...,  0.03459217,
          -0.03848752, -0.04202668]],

        ...,

        [[-0.02478858,  0.02682879, -0.04456054, ...,  0.02304109,
          -0.01549854,  0.05175754],
         [-0.03123299, -0.00233125,  0.03222625, ..., -0.00508975,
          -0.01916178,  0.02803812],
         [-0.01563376, -0.00415189, -0.00754851, ...,  0.02336777,
           0.01488459, -0.02387016],
         ...,
         [ 0.02905967, -0.01015875,  0.02665043, ...,  0.0321634 ,
           0.00657683,  0.03639102],
         [ 0.01567689,  0.01075559, -0.00275711, ..., -0.03713944,
          -0.03959266,  0.02978322],
         [-0.02423201,  0.05542431, -0.03051832, ..., -0.01087064,
           0.04012467,  0.01017098]],

        [[ 0.040019  ,  0.04499329,  0.06117873, ...,  0.03734967,
           0.02417182,  0.01399651],
         [-0.03475999,  0.01548064, -0.05062135, ...,  0.00497709,
          -0.00110055, -0.00781615],
         [-0.00182435, -0.04350331, -0.0004377 , ..., -0.01109843,
          -0.01911157, -0.01601983],
         ...,
         [ 0.02604849, -0.01627797, -0.00465705, ..., -0.04670858,
          -0.00911144,  0.02375674],
         [-0.01328693,  0.03123103,  0.01865276, ..., -0.06125986,
          -0.03999097,  0.01011509],
         [-0.02301252, -0.01308746, -0.0490226 , ...,  0.00470494,
           0.00650435, -0.01457159]],

        [[-0.03820717,  0.02072869,  0.03830532, ...,  0.06720637,
           0.02205504,  0.01943265],
         [ 0.00661271, -0.01948877,  0.03376551, ...,  0.01038686,
           0.03399502,  0.01804686],
         [-0.02333958,  0.03679723,  0.02681947, ...,  0.03411691,
           0.01579058, -0.01173974],
         ...,
         [-0.05454921, -0.03352332, -0.00728678, ..., -0.01607291,
           0.03992983, -0.04655397],
         [-0.03829747, -0.00620103, -0.0381875 , ...,  0.00075667,
           0.02149382, -0.0565853 ],
         [ 0.04661642, -0.00178856,  0.00098069, ...,  0.02367202,
           0.06136367, -0.0055925 ]]]], dtype=float32), array([[[[ 1.20212529e-02, -1.60561725e-02,  2.79961731e-02, ...,
          -5.11698276e-02, -5.46384230e-02, -1.08954422e-02],
         [-6.40665069e-02, -5.61472625e-02, -4.46923189e-02, ...,
           2.75821742e-02,  2.82258913e-03,  4.76859398e-02],
         [ 9.03344341e-03, -2.47069579e-02, -3.50452140e-02, ...,
           3.58940773e-02,  2.56008375e-03, -4.88611460e-02],
         ...,
         [ 5.82277316e-05,  1.48078986e-02, -4.77372669e-02, ...,
          -4.53547649e-02,  2.55814362e-02, -2.47431733e-02],
         [ 4.32614684e-02, -5.88692538e-02,  2.36510020e-02, ...,
           3.28519456e-02, -4.32553217e-02, -1.89302803e-03],
         [-3.84060219e-02,  2.81927902e-02,  3.83458398e-02, ...,
           1.54303666e-02,  1.73402373e-02,  3.96075249e-02]]],


       [[[ 2.75735650e-02, -5.10189533e-02, -3.45809907e-02, ...,
          -3.00505944e-02, -5.65067343e-02, -4.70891930e-02],
         [-1.05189737e-02, -2.47922502e-02,  1.37131559e-02, ...,
          -3.94735336e-02,  6.12645298e-02,  7.83619285e-03],
         [-4.26600128e-02, -1.40513955e-02, -4.17002589e-02, ...,
           2.52892543e-02, -1.76714025e-02,  2.40433346e-02],
         ...,
         [-3.64723317e-02, -6.12953529e-02, -2.87160724e-02, ...,
           1.39484312e-02, -2.63532251e-02, -3.03319711e-02],
         [ 2.50384547e-02,  1.48913711e-02, -1.15208402e-02, ...,
          -5.07830717e-02,  2.23115478e-02, -4.24515344e-02],
         [-4.13436182e-02, -5.29334843e-02,  2.64884755e-02, ...,
          -2.42673270e-02, -1.77902188e-02,  1.29233338e-02]]],


       [[[-4.78883758e-02,  2.15298571e-02, -3.56095890e-03, ...,
          -9.32726450e-03, -8.51003639e-03, -4.23191208e-03],
         [ 2.60657519e-02, -2.60664914e-02,  1.18862567e-02, ...,
           8.35520215e-03, -2.57495586e-02, -6.19659666e-03],
         [ 2.75304914e-02,  1.53979631e-02,  5.20882793e-02, ...,
          -3.08437590e-02, -1.27481306e-02, -7.41662318e-03],
         ...,
         [ 1.34232817e-02, -3.57325077e-02,  3.84952012e-03, ...,
          -1.50186485e-02,  3.17202359e-02,  4.88737673e-02],
         [-3.21522951e-02,  2.32756473e-02,  3.44796591e-02, ...,
           3.36667225e-02, -6.04509450e-02, -2.86901854e-02],
         [-4.81593385e-02, -4.30328511e-02, -2.75574699e-02, ...,
          -4.50209342e-02, -2.24241130e-02, -9.01618786e-03]]],


       ...,


       [[[ 1.23982755e-02, -2.75063794e-02, -2.85260230e-02, ...,
           4.60940823e-02,  1.20070986e-02,  2.96034385e-02],
         [ 1.19548282e-02,  3.69588025e-02,  4.72352915e-02, ...,
          -2.23038513e-02, -2.63257846e-02, -2.51782034e-02],
         [ 1.30367270e-02, -4.84500527e-02, -4.49900292e-02, ...,
           4.52315509e-02,  3.35616693e-02, -4.32417588e-03],
         ...,
         [-2.54489295e-02, -2.06208117e-02,  5.38901687e-02, ...,
           6.30411040e-03, -3.32341082e-02, -1.86319195e-03],
         [-1.45645710e-02, -4.91764136e-02,  4.30333428e-02, ...,
           3.26185934e-02,  2.20666584e-02, -3.87162566e-02],
         [-5.65150566e-02,  3.35531197e-02,  2.54257061e-02, ...,
           4.37543578e-02,  3.20086777e-02,  3.32057886e-02]]],


       [[[-2.68890150e-03,  2.81596854e-02, -3.79190482e-02, ...,
           6.54808246e-03, -2.17476916e-02, -4.02564593e-02],
         [-2.46557649e-02, -2.94130482e-02,  8.86828545e-03, ...,
          -1.44444462e-02, -2.76649203e-02,  6.12021647e-02],
         [ 1.63752250e-02,  6.67520217e-04,  8.90827831e-03, ...,
           2.09546275e-02, -3.77141871e-03, -1.43971695e-02],
         ...,
         [-5.78385852e-02,  3.45522687e-02,  1.38806561e-02, ...,
          -1.28591126e-02,  2.08067019e-02,  5.76362852e-03],
         [-7.52439396e-03, -1.98082700e-02,  3.11895572e-02, ...,
          -2.45399447e-03,  4.27410379e-02,  3.41868331e-03],
         [-3.00020333e-02, -3.82510573e-02, -1.86001491e-02, ...,
           5.70917428e-02,  2.03996189e-02,  2.04965230e-02]]],


       [[[-4.66495939e-02, -3.27009596e-02, -2.17380505e-02, ...,
           1.40069323e-02,  2.27190070e-02,  4.33470346e-02],
         [ 3.93003412e-02,  4.08379510e-02,  1.20340372e-02, ...,
           2.68050935e-02,  4.22952250e-02, -8.89548939e-03],
         [-1.18291322e-02, -1.34098874e-02, -3.45622972e-02, ...,
          -2.24330816e-02, -1.59011930e-02,  5.93173094e-02],
         ...,
         [-2.86659896e-02,  2.17355392e-03, -1.87548678e-02, ...,
           3.68932188e-02,  1.88795682e-02, -2.81844977e-02],
         [-8.81038606e-03, -1.97809637e-02, -5.09448089e-02, ...,
          -5.39695807e-02, -4.13822196e-02,  5.03004156e-02],
         [-4.93417457e-02, -2.23529395e-02, -4.36607283e-03, ...,
          -2.23001726e-02, -2.33178423e-03, -1.36592081e-02]]]],
      dtype=float32), array([ 0.0102301 , -0.00794625,  0.00522969,  0.00182397,  0.00224257,
        0.00976888,  0.00099161, -0.00849194, -0.00247771, -0.00801653,
        0.00157609, -0.00161968, -0.00209305, -0.02171896, -0.00727225,
        0.00914788, -0.00451798,  0.00328217,  0.00737639,  0.03311384,
        0.01729891,  0.01339894,  0.02558345,  0.02284675, -0.00284436,
       -0.00167431,  0.01120296,  0.00139864, -0.01014377,  0.00617436,
        0.00937057, -0.01182164, -0.02662222, -0.0034864 ,  0.0004211 ,
       -0.01124093,  0.00523034, -0.00581406,  0.00507186, -0.00219571,
        0.00496501, -0.00796648,  0.00113259,  0.02218314,  0.02256002,
        0.00068021,  0.00784395,  0.01250971, -0.01476198,  0.01418505,
       -0.0035537 , -0.01680874, -0.00616684, -0.00645174, -0.00474583,
       -0.00406831,  0.00211728,  0.0147801 , -0.01736911,  0.00016547,
        0.00060448,  0.00123312,  0.01593785, -0.00775475, -0.01435189,
        0.00138422, -0.00591962, -0.00031217, -0.01915144, -0.00289756,
       -0.02848573,  0.00773459, -0.02451641,  0.04318289,  0.00904472,
       -0.00284673, -0.00016909, -0.00026846,  0.00297249, -0.00333736,
       -0.00697547, -0.0107759 , -0.00284622, -0.00609544, -0.00335601,
        0.00243515, -0.01174649, -0.00645705, -0.01205613,  0.0022691 ,
        0.00297957, -0.00548202, -0.00026194, -0.00822498,  0.00706723,
        0.0051864 , -0.01457691, -0.01125416, -0.01832161, -0.01455006,
       -0.00542507, -0.00312034, -0.01179766,  0.01703039,  0.02379716,
        0.00617956,  0.00186437,  0.0146708 ,  0.0167254 , -0.00438445,
       -0.00837414,  0.00369263, -0.00745571,  0.00834153, -0.01148582,
       -0.01407805,  0.00382444, -0.0021008 , -0.01665059, -0.00123866,
        0.01301671, -0.03474265, -0.00678758, -0.00500936, -0.00921011,
        0.00952853,  0.01839614,  0.01549417,  0.01998459,  0.00581555,
        0.00032493, -0.00030422, -0.01404958, -0.0012636 ,  0.01248567,
       -0.0141969 , -0.00124046, -0.01464896, -0.00889905,  0.00152798,
       -0.00883602,  0.00209581, -0.02128979, -0.00283442,  0.00234644,
        0.01052942, -0.02012696, -0.00634682, -0.00274766,  0.00503507,
        0.00134225, -0.01700828, -0.02508625, -0.00112369, -0.03477434,
        0.00393038, -0.00788565, -0.0023734 ,  0.00481751, -0.01037017],
      dtype=float32), array([ 1.99145913e-01,  9.46107805e-01, -1.15939856e+00, -1.49733257e-02,
        3.99295449e-01, -3.75498414e-01,  5.69744289e-01, -1.31121218e+00,
       -2.22299278e-01,  8.32550466e-01,  2.95254588e-01, -4.36769366e-01,
        5.90055048e-01, -2.94347376e-01, -1.45536089e+00, -1.84083366e+00,
        6.34719431e-01,  1.85232341e-01, -9.44000185e-01, -1.41308200e+00,
       -1.25046861e+00, -3.67542148e-01, -6.37975037e-01,  5.50659537e-01,
       -6.82018936e-01,  1.16203630e+00,  1.04587889e+00, -6.25499368e-01,
        6.91899657e-01,  4.77040946e-01, -9.96149898e-01, -1.01822279e-01,
        1.62567198e-01, -1.18462694e+00,  8.91573071e-01,  1.69983670e-01,
       -8.30597639e-01,  4.02398974e-01, -8.85197580e-01,  6.99594617e-01,
        1.42714930e+00,  2.15411231e-01, -2.27431417e-01, -1.48575401e+00,
        3.68583947e-01,  4.89753395e-01, -1.44657552e+00, -3.93265098e-01,
       -5.15811324e-01,  1.05925512e+00,  4.15367842e-01, -6.29755020e-01,
        1.35200703e+00,  5.80229819e-01,  3.16456407e-01,  7.73294330e-01,
       -1.59452343e+00,  5.32180429e-01,  1.34543389e-01,  1.40704536e+00,
        5.43441996e-03, -1.03905141e+00, -1.95549782e-02,  1.21032262e+00,
       -8.12922716e-01, -9.90563452e-01,  5.31988621e-01, -9.92471218e-01,
        6.60669327e-01,  1.12238216e+00,  1.11910164e+00,  1.02141976e+00,
       -3.20500612e-01,  3.02469969e-01, -7.83620596e-01, -8.77465010e-01,
       -1.42412949e+00, -1.18844151e+00, -9.12347250e-03, -1.91246367e+00,
        1.17353249e+00,  1.21335757e+00,  5.74294686e-01,  1.23265362e+00,
        6.14129901e-01,  6.55716807e-02,  1.20931774e-01, -6.60175204e-01,
        4.68037844e-01, -5.91259956e-01,  1.29848874e+00, -6.41512930e-01,
        7.69097745e-01,  1.30002177e+00,  9.43477392e-01, -1.37112272e+00,
        7.60609061e-02, -4.14213121e-01, -1.09837806e+00,  4.84136403e-01,
        7.43777335e-01,  3.95075738e-01,  1.06000173e+00,  4.62619185e-01,
       -7.41681337e-01, -1.89492926e-01,  1.02591586e+00, -1.15057588e+00,
        1.42232406e+00,  6.44171298e-01,  8.52810293e-02,  5.68458498e-01,
       -1.19568074e+00, -5.85750818e-01, -1.81612775e-01, -8.74566287e-03,
        4.74730045e-01,  5.84517598e-01, -5.16680360e-01,  3.63153845e-01,
       -7.33170152e-01,  1.81425586e-01,  9.90423799e-01,  2.40981027e-01,
        5.88649154e-01,  1.00664377e+00, -1.06028306e+00,  4.95225668e-01,
        3.04135501e-01,  1.00348997e+00,  6.25377774e-01,  2.45882377e-01,
        6.48134112e-01,  3.59548748e-01, -3.69617462e-01,  8.39054286e-02,
       -3.89825135e-01, -3.60566467e-01,  1.26988041e+00,  4.57957029e-01,
        1.20033905e-01, -3.97779852e-01, -5.78824759e-01, -1.15929270e+00,
       -8.78490880e-02,  4.21368629e-01, -8.09651196e-01,  3.48927677e-02,
        9.50740814e-01, -7.69857725e-04, -1.25217688e+00,  4.35461372e-01,
        2.28873357e-01, -5.69716752e-01,  8.24007869e-01, -6.01864159e-01,
        4.08118963e-01,  6.50312126e-01,  1.16754329e+00,  7.83950388e-02],
      dtype=float32), array([ 3.7707055 ,  6.2138143 ,  4.2831187 ,  1.6389335 ,  5.4696116 ,
        2.0360634 ,  1.3051437 ,  4.2901816 ,  1.8217672 ,  4.1775146 ,
        6.086218  ,  3.789075  ,  3.9483204 ,  4.9095845 ,  2.4006896 ,
       11.597191  ,  8.270047  ,  1.191923  ,  2.165674  ,  2.4029663 ,
        7.036818  ,  4.477056  ,  2.3943133 ,  5.9369135 ,  2.0625591 ,
        5.43289   ,  6.874037  ,  5.1379576 ,  5.6931243 ,  5.854663  ,
        9.54873   ,  1.8391804 ,  3.090582  ,  2.6309867 ,  7.7935576 ,
        2.7385702 ,  1.6921622 ,  0.7635776 ,  4.6197295 ,  6.4098005 ,
        8.385663  ,  1.2899745 ,  1.2766564 ,  6.81973   ,  1.4059765 ,
        2.9740973 ,  2.6497447 ,  0.8473647 ,  2.5678248 ,  7.2786    ,
        3.506916  ,  1.3243557 ,  5.483531  ,  4.471817  ,  2.6973336 ,
        6.0816226 , 10.806577  ,  6.635342  ,  6.4597898 ,  3.465836  ,
        2.2584145 ,  1.9020894 ,  1.4489388 ,  4.7356997 ,  1.3016918 ,
        7.4970565 ,  0.8119927 ,  1.9786792 ,  4.7699585 ,  3.648573  ,
        3.0764341 ,  6.429668  ,  3.3099675 ,  1.7491423 ,  1.8099098 ,
        1.985573  , 10.2237835 ,  8.924379  ,  1.6829304 ,  6.594083  ,
        6.528104  ,  5.738236  ,  1.3002578 ,  6.0926676 ,  5.6574435 ,
        3.2678509 ,  1.4746537 ,  2.0077608 ,  1.4851846 ,  2.6129954 ,
        6.2657046 ,  6.7672114 ,  9.7465725 ,  6.973117  ,  4.1511626 ,
        2.9888437 ,  3.577902  ,  1.7482603 ,  4.062236  ,  2.9572577 ,
        4.212     ,  5.4793453 ,  3.0268023 ,  5.868717  ,  5.9800496 ,
        1.6555115 ,  6.6045012 ,  5.1706867 ,  7.5587435 ,  2.249168  ,
        3.806066  ,  7.6096215 ,  5.1778936 ,  1.9817696 ,  1.1972845 ,
        1.085482  ,  6.332245  ,  3.3277571 ,  2.483951  ,  5.721975  ,
        1.2903191 ,  1.4308854 ,  8.5106735 ,  5.1765623 ,  7.7149167 ,
        5.2875786 ,  4.036944  ,  1.9082067 ,  3.831772  ,  6.285884  ,
        4.1709247 ,  1.3976481 ,  3.0291135 ,  2.5762343 ,  2.0485978 ,
        3.5715482 ,  1.4932547 ,  1.0423237 ,  6.2126565 ,  4.8448052 ,
        1.4347174 ,  2.2889116 ,  1.7211438 ,  4.2264647 ,  1.1891948 ,
        4.3080683 ,  0.76849484,  4.2700977 ,  4.838747  ,  1.7821646 ,
        2.7268262 ,  1.8064138 ,  4.570309  ,  1.6255752 ,  2.5384896 ,
        2.7967308 ,  2.0005488 ,  3.527545  ,  3.8736444 ,  4.4580674 ],
      dtype=float32), array([ 5.46627399e-03,  2.52435985e-03, -8.61074217e-03,  8.25907290e-03,
       -6.68415288e-03, -2.98684975e-03, -7.41228834e-03,  3.69712454e-03,
       -4.87649394e-03, -1.74321292e-03,  6.32058596e-03, -7.67759653e-03,
       -1.40739409e-02, -2.41511012e-03, -5.63884340e-03,  1.67644024e-02,
       -1.15119601e-02,  1.13592073e-02, -1.11865373e-02, -1.33650154e-02,
       -4.50591464e-03, -7.06530549e-03,  2.16596713e-03, -6.35482138e-03,
       -6.44864421e-03,  9.06440197e-04, -1.20627824e-02, -1.70304716e-04,
        2.38791690e-03,  5.32961404e-03,  7.18411058e-03,  1.12554124e-02,
        1.43499626e-03,  2.87885428e-03,  2.83737411e-03, -1.80928037e-02,
        4.84691351e-04, -3.19550163e-03, -6.07232423e-03,  7.71562941e-03,
       -2.85221916e-03,  9.28238092e-04, -9.24000237e-03, -5.21075027e-03,
        4.94251866e-03, -3.06064989e-02, -4.96343710e-03,  2.61743413e-03,
       -1.10113239e-02, -1.85023639e-02,  1.47964321e-02, -6.19817572e-03,
        3.91193054e-04,  1.09167527e-02,  4.96486016e-03, -4.72384784e-03,
       -2.88229645e-03, -8.30393564e-03,  4.01022239e-03, -5.24432771e-03,
        5.91358915e-03,  2.35486794e-02,  5.29320678e-03, -1.90570496e-03,
        1.78263069e-03, -2.11286768e-02, -2.22441424e-02, -8.76882952e-03,
       -1.74182688e-03, -1.49930678e-02,  1.80151407e-03,  1.37187727e-02,
        6.47629704e-03,  1.33463396e-02, -2.66189757e-03, -8.28591920e-03,
       -2.97691702e-04, -8.33570585e-03,  2.98213996e-02, -1.96021097e-03,
       -1.35632344e-02,  8.52424372e-03,  1.15672837e-03, -1.94705296e-02,
        1.24844871e-02, -1.43338395e-02, -1.41211422e-02, -3.60264978e-03,
       -1.12240752e-02, -1.69807505e-02, -1.02520613e-02,  1.28042791e-02,
       -5.58370166e-03, -1.60151569e-03, -1.42426761e-02,  5.14006941e-03,
       -1.62169691e-02,  1.84600689e-02, -1.59198174e-03, -9.75101357e-05,
        1.12805434e-03, -1.59099903e-02, -1.04935300e-02,  9.17063619e-04,
        3.87115334e-03,  8.76578502e-03, -5.26242284e-03, -1.00610256e-02,
       -2.01197099e-02, -1.98509563e-02,  8.51407833e-03,  1.68215262e-03,
       -5.15080849e-03,  1.32414484e-02, -9.42059979e-03, -1.24362074e-02,
        5.12916083e-03, -9.95901413e-04, -1.16884094e-02,  5.01103001e-03,
        4.55451227e-04, -1.75040551e-02, -8.73084180e-03, -8.06641765e-03,
       -5.51081961e-03, -2.62361369e-03, -7.36015150e-03, -7.85987824e-04,
        8.18202621e-04, -4.61910944e-03,  7.32512027e-03, -1.11311011e-03,
       -1.82665209e-03, -1.45323551e-03, -1.08187590e-02, -9.03053395e-03,
       -1.31690148e-02, -1.23823928e-02,  1.24193568e-04,  4.15153569e-03,
       -2.22422997e-03, -3.00659519e-03,  8.65388429e-05, -1.97457243e-02,
       -9.77056660e-03, -2.48776246e-02, -1.73194092e-02,  1.05733946e-02,
       -1.44669889e-02,  7.13080633e-03, -5.37439995e-03,  6.80938736e-03,
       -1.62599906e-02, -7.58084329e-03, -1.84531361e-02, -3.45489080e-03,
       -1.38651272e-02, -1.82294343e-02, -5.69059886e-03, -1.05701583e-02],
      dtype=float32), array([-0.46577066, -1.2322598 ,  0.36768848,  0.23694631, -0.8891011 ,
       -0.45698333, -0.31193545,  0.43872437, -0.09982172, -0.6683154 ,
        0.7726216 , -0.51404774, -1.0274307 , -0.2741633 , -0.21457124,
        1.1030765 ,  0.5762418 ,  0.7775812 ,  0.8947422 , -0.16831297,
        0.5860047 ,  0.04123555,  1.4156362 ,  0.02976851, -0.31303942,
        0.39925367, -0.80360967,  0.661409  ,  0.08088363, -0.16797043,
        0.77738166,  0.06447323, -0.10117244,  1.2353469 ,  1.2336403 ,
        0.7838908 , -0.41238797, -0.85685056, -0.9303323 ,  0.14304759,
       -1.0805162 ,  1.036473  , -0.28664184,  0.54465497,  0.0044659 ,
        1.0326018 ,  0.77062386, -0.71906894,  0.00532987,  0.8859874 ,
       -0.01907839, -1.2089074 , -0.18966575,  1.1276344 ,  0.37534007,
       -0.6886223 , -0.3170762 , -1.264364  ,  0.05813242, -0.22350763,
        0.13304557,  1.0394104 , -1.1494957 ,  0.3459246 , -0.8047201 ,
        1.090092  ,  0.19676256, -1.0760025 , -1.2211077 ,  0.7162625 ,
       -0.210542  ,  0.7279837 ,  0.0322775 ,  0.6526528 ,  0.07586045,
        0.3888926 ,  1.5894735 ,  0.41305742,  1.2727567 ,  0.33831057,
       -0.04005507, -1.2566899 , -0.5754841 ,  0.12134087, -0.40569532,
       -0.6310846 ,  0.30617052,  1.4594338 ,  0.4502001 , -0.34011886,
        0.04384473, -1.0896618 ,  1.0121405 , -0.24066547, -0.62590086,
       -0.7455134 , -0.05776257,  0.36566716, -0.10313867,  0.81947005,
        0.5837243 , -1.045571  ,  1.3364295 ,  0.21878533,  0.78537214,
        0.4315077 ,  0.99056363, -1.2175859 ,  0.96226746, -0.25358465,
       -0.56438553,  0.4502893 , -0.27649567, -0.0196274 ,  0.40058774,
        1.3224214 , -0.27279022,  0.749711  ,  0.08468791,  0.39643368,
       -0.9128424 , -0.04495344,  0.03261971, -1.2242328 , -0.95649743,
       -1.039687  ,  1.0041248 , -0.917845  , -0.6276645 ,  0.87716186,
        0.27147242, -0.23684305, -0.49185035, -0.23460689,  0.70678854,
       -0.63411194,  0.51879674,  0.19281739, -0.45565766, -0.6741481 ,
        0.5391825 ,  0.8013381 , -0.88892597, -0.09050144,  0.7599753 ,
        1.004122  ,  0.39612505, -0.5500628 ,  0.48454672, -0.7899938 ,
        0.32421306, -1.1046478 ,  0.02591153,  0.39067823,  0.7838524 ,
       -0.42758676,  0.96319926,  1.0498226 ,  0.30012554,  0.5029993 ],
      dtype=float32), array([1.8442868, 3.3460588, 2.7183256, 2.6087434, 2.3837829, 3.1481934,
       1.5054971, 3.6347408, 4.673645 , 1.9264162, 4.573573 , 2.6181734,
       3.1108382, 2.0571077, 2.458027 , 3.276965 , 3.0721064, 5.103701 ,
       3.0105858, 1.6796663, 1.690029 , 1.4325141, 9.349846 , 3.0411272,
       2.0379164, 1.8711205, 3.710863 , 2.6850405, 3.4275415, 2.0218976,
       4.683547 , 1.9838157, 3.415211 , 4.5123596, 3.7148345, 2.9474525,
       2.196195 , 3.2991462, 2.043751 , 3.0556564, 2.9780588, 3.5715704,
       2.0566258, 2.4960718, 2.9762142, 4.5399356, 3.2060158, 4.6550913,
       1.5363884, 4.9787645, 2.0668724, 6.146473 , 1.5364807, 5.1488795,
       2.6687994, 2.0408032, 1.8013272, 5.3231106, 3.8804696, 3.0984118,
       3.47556  , 4.031245 , 4.261772 , 1.9025651, 2.7887049, 3.8467119,
       3.3731513, 4.7359967, 3.0040915, 4.2029643, 2.298964 , 4.4456058,
       3.6569314, 3.0465007, 2.9176373, 2.7076352, 4.165581 , 3.9123073,
       5.9837956, 2.778869 , 1.7630682, 4.154629 , 4.5380316, 1.7816358,
       2.6223834, 2.2632415, 2.6164234, 4.70349  , 2.9349742, 2.9546864,
       2.1465187, 2.612662 , 4.649601 , 1.5787984, 3.0834992, 2.1953714,
       2.617495 , 2.8944514, 1.9543585, 2.4686003, 3.4901135, 2.2344692,
       3.9040802, 2.0525086, 1.2926512, 4.330183 , 6.5063877, 3.3825414,
       1.9408821, 1.9284827, 2.149539 , 2.0656903, 1.8501126, 2.0503895,
       2.8692734, 5.250647 , 2.5601795, 2.5353234, 2.5591686, 1.9076647,
       3.1036725, 3.603167 , 2.298901 , 4.9126325, 3.8405874, 2.2425644,
       3.6942167, 2.254368 , 2.6844718, 3.8153253, 2.1601834, 2.6805813,
       3.638015 , 2.573493 , 4.229808 , 3.6486664, 2.1493301, 3.2308135,
       1.7204583, 1.9532636, 1.267422 , 4.0915685, 4.2423506, 1.9066895,
       5.052881 , 6.2220073, 3.8961523, 1.4546446, 4.285049 , 1.4002981,
       3.1839159, 2.3564696, 2.0864618, 2.0552592, 4.7553053, 3.0075684,
       4.637794 , 2.7529194, 3.6388624, 3.458781 ], dtype=float32), array([[[[-0.02522874,  0.06701554, -0.0650828 , ..., -0.07474749,
          -0.05259843,  0.0401842 ],
         [-0.05891386, -0.04642926, -0.02457559, ..., -0.03793874,
          -0.06281629,  0.02865035],
         [ 0.00133621,  0.05166715,  0.04238519, ...,  0.02309879,
          -0.01490806, -0.06800517],
         ...,
         [-0.04201759,  0.04840104,  0.03255305, ...,  0.01389796,
           0.06860836, -0.00162949],
         [-0.0238056 ,  0.03334018,  0.02798509, ...,  0.07353722,
           0.01887106, -0.06663372],
         [-0.05954798, -0.02982587, -0.06966412, ..., -0.0137922 ,
           0.03955889, -0.0029463 ]]]], dtype=float32), array([[[[-4.10438627e-02,  4.29919660e-02, -1.99649427e-02, ...,
          -3.57310772e-02,  2.47132946e-02,  2.03533955e-02],
         [ 1.85353290e-02, -4.19955589e-02,  3.91752385e-02, ...,
           2.20744163e-02, -4.87269163e-02,  4.44169678e-02],
         [-3.87736633e-02, -3.68877873e-02,  3.24447043e-02, ...,
          -1.24617796e-02,  2.79842652e-02,  1.17173215e-04],
         ...,
         [-1.41340932e-02,  3.62721793e-02, -3.49103287e-02, ...,
           4.15429845e-02, -1.99049655e-02, -4.25953120e-02],
         [-4.21871617e-03, -8.81827809e-03,  2.27887407e-02, ...,
           8.60234071e-03, -1.79994013e-02,  1.09375163e-03],
         [-3.07032615e-02, -3.94877605e-02, -2.30561532e-02, ...,
           1.27033316e-04, -3.01897191e-02, -8.85509606e-03]]],


       [[[ 5.33338352e-05,  3.48695517e-02, -3.37978937e-02, ...,
          -2.49526426e-02,  3.93800400e-02, -4.25827913e-02],
         [-4.20509912e-02, -1.52473310e-02, -8.44859146e-03, ...,
           4.52120081e-02, -3.00312582e-02,  5.74534340e-03],
         [ 4.19577956e-02,  2.23637559e-02, -4.57583740e-02, ...,
           3.40017565e-02, -9.94237419e-03, -1.79218687e-02],
         ...,
         [-6.18930813e-03, -3.86427343e-03,  1.06060356e-02, ...,
           3.79690044e-02,  1.57303233e-02,  2.26785038e-02],
         [ 1.97871830e-02,  1.88044328e-02,  3.12559456e-02, ...,
           1.33876712e-03,  2.59678848e-02, -2.94192210e-02],
         [ 4.94511276e-02, -3.61651666e-02,  2.18583606e-02, ...,
           1.93159319e-02,  5.46900509e-03,  3.48275825e-02]]],


       [[[-3.52072483e-03, -2.43942719e-02,  1.06144883e-02, ...,
           1.04357619e-02, -1.36990035e-02, -6.93087801e-02],
         [ 2.91163493e-02,  6.74988283e-03, -2.64733750e-02, ...,
          -2.80930996e-02,  2.21565552e-03,  3.93352658e-03],
         [ 4.61236425e-02,  1.63874752e-03, -1.19765308e-02, ...,
          -3.26588154e-02,  5.49400132e-03,  1.14328768e-02],
         ...,
         [-4.70168097e-03,  4.72929031e-02,  2.08947044e-02, ...,
           5.55028731e-04,  2.39261761e-02,  1.32198175e-02],
         [ 3.39682736e-02, -1.13387760e-02,  3.55387963e-02, ...,
          -3.63877304e-02, -1.21977124e-02,  4.58978899e-02],
         [-1.10370957e-03,  1.23207886e-02,  2.97739124e-03, ...,
           1.28631992e-02,  9.82477609e-03, -3.00536547e-02]]],


       ...,


       [[[-4.49469388e-02, -4.48733196e-02,  3.91212218e-02, ...,
          -2.14783475e-02,  4.91208732e-02, -3.32981795e-02],
         [-3.06767877e-02,  2.54197102e-02,  1.61556881e-02, ...,
           9.20204073e-03, -7.38447299e-03, -1.60275039e-03],
         [ 9.71328560e-03, -4.27782536e-02, -4.37282324e-02, ...,
          -1.71750374e-02, -5.31091765e-02, -3.55875231e-02],
         ...,
         [-2.59337071e-02, -2.12937966e-02, -2.50331406e-02, ...,
          -1.88736878e-02,  7.38666160e-03,  2.80735157e-02],
         [-4.81875949e-02, -3.81975770e-02, -5.94336726e-03, ...,
          -1.47084035e-02, -2.74725724e-02,  4.16894667e-02],
         [ 2.53425576e-02,  1.04838675e-02,  2.39592530e-02, ...,
          -9.69432946e-03,  2.73812264e-02, -3.13305780e-02]]],


       [[[ 2.93904897e-02,  1.28274439e-02, -1.93106271e-02, ...,
          -1.66212376e-02,  7.24399164e-02,  6.42126426e-03],
         [ 5.52316476e-03,  4.97317836e-02,  2.12873127e-02, ...,
           3.51316780e-02,  5.02618141e-02, -1.49296066e-02],
         [ 1.29296621e-02, -5.46823349e-03,  1.27804643e-02, ...,
           1.85158290e-02, -3.28736939e-02, -4.42489870e-02],
         ...,
         [-8.84064939e-03, -6.25166064e-03,  3.14634740e-02, ...,
          -1.04882037e-02, -2.46964563e-02, -2.03701612e-02],
         [-6.17451482e-02,  6.36092424e-02, -4.54262756e-02, ...,
           1.51550174e-02, -6.05158275e-03,  2.29902994e-02],
         [-2.62454413e-02, -4.71516252e-02, -5.02051301e-02, ...,
           5.52673228e-02,  5.00307344e-02,  4.77830926e-03]]],


       [[[ 5.64034423e-03,  3.97696197e-02, -8.25295411e-03, ...,
           5.49141057e-02,  4.19654883e-02, -6.02259152e-02],
         [-6.28355891e-02,  4.40372201e-03,  3.48677323e-03, ...,
          -5.57522476e-03,  2.69548334e-02,  2.77202073e-02],
         [-5.35052968e-05, -1.67941544e-02, -8.47014785e-03, ...,
          -1.67259108e-02, -5.39083406e-02,  4.35813032e-02],
         ...,
         [-5.09092435e-02, -2.84548514e-02,  2.50810962e-02, ...,
           3.03030200e-02,  3.04422490e-02, -2.06610914e-02],
         [-3.62947546e-02,  1.08428225e-02, -2.90094223e-03, ...,
           5.70096169e-03,  4.89162244e-02,  5.35785109e-02],
         [-1.84295382e-02,  1.02699483e-02, -3.79348174e-02, ...,
           4.97537516e-02,  4.00244221e-02, -4.36878540e-02]]]],
      dtype=float32), array([[[[-0.00744601,  0.02797678, -0.04402782, ..., -0.01202985,
          -0.03852484,  0.03628226],
         [-0.02084747, -0.04524703, -0.03868482, ..., -0.04153863,
          -0.03509894,  0.00873526],
         [ 0.01001292,  0.02976015,  0.05324289, ..., -0.00964941,
           0.00716347, -0.03179285],
         ...,
         [ 0.03755885, -0.02085258, -0.01701406, ...,  0.0199298 ,
           0.03356174, -0.02489083],
         [-0.0411341 , -0.03011521, -0.00473251, ...,  0.01341253,
          -0.01337103, -0.00680099],
         [ 0.04041038,  0.00810921, -0.0456875 , ...,  0.03077449,
           0.01979212, -0.02438027]],

        [[ 0.03656474,  0.03151507,  0.02726354, ...,  0.03567308,
          -0.01910074, -0.0269147 ],
         [-0.03205493,  0.02675908, -0.02791762, ..., -0.04087686,
          -0.04115999,  0.00870361],
         [-0.01255012,  0.0378466 ,  0.01174573, ..., -0.03282118,
          -0.01098506, -0.00587548],
         ...,
         [-0.04604823,  0.00618331, -0.02261444, ...,  0.01793904,
           0.01812114,  0.01026624],
         [-0.03822522,  0.00581578,  0.03432804, ...,  0.04657106,
          -0.01539074, -0.01068703],
         [-0.02473962,  0.00632311, -0.0249403 , ..., -0.03898514,
          -0.03102784, -0.00729993]],

        [[ 0.01801208, -0.0059236 , -0.00558118, ..., -0.01031851,
          -0.03884755,  0.05051044],
         [ 0.01565921,  0.01951237,  0.02123082, ..., -0.02792944,
          -0.01982554, -0.01499697],
         [ 0.02257395,  0.0390614 , -0.01849989, ..., -0.00872778,
           0.02756408, -0.00406487],
         ...,
         [-0.01033266, -0.03407042,  0.00753958, ..., -0.03034604,
          -0.00309379,  0.02813776],
         [-0.02585132, -0.00980478, -0.01639348, ...,  0.01247275,
          -0.0008071 ,  0.03160058],
         [-0.02243203, -0.00412459,  0.01671894, ..., -0.00420873,
          -0.00647502, -0.02893461]],

        ...,

        [[-0.0344114 , -0.00054269, -0.04496872, ...,  0.02347141,
          -0.04765388,  0.00506846],
         [ 0.03836839,  0.01444814,  0.00952843, ..., -0.04874901,
          -0.03513762,  0.0319605 ],
         [-0.00955749, -0.03745782, -0.02681867, ..., -0.02798253,
           0.00054838,  0.02714302],
         ...,
         [ 0.00650169, -0.03933193, -0.03830856, ..., -0.0222268 ,
           0.04171094,  0.04270863],
         [-0.03247716,  0.02454561, -0.01035954, ..., -0.05361927,
          -0.03333978, -0.00680698],
         [ 0.01950025,  0.06364577,  0.01374312, ..., -0.01463515,
           0.01091978,  0.00764064]],

        [[-0.0028113 , -0.0278367 ,  0.02941282, ..., -0.01448132,
           0.02308233,  0.01389471],
         [-0.05090443, -0.00462514, -0.04560744, ...,  0.03739141,
           0.02431976, -0.01513413],
         [-0.01295318,  0.00844852,  0.01867202, ...,  0.03012431,
           0.02873197,  0.04138399],
         ...,
         [ 0.03059355,  0.02894596, -0.02789209, ...,  0.03559126,
          -0.01392253,  0.05004713],
         [-0.02177282, -0.00900364,  0.01358381, ...,  0.00759746,
           0.04029731, -0.01412977],
         [ 0.01868209, -0.01373576, -0.05411518, ..., -0.0201377 ,
           0.00106794, -0.00432224]],

        [[ 0.03382369,  0.04818365,  0.04663457, ...,  0.01699476,
          -0.0265902 ,  0.03495219],
         [ 0.0236649 , -0.00982378,  0.00032677, ..., -0.00761851,
           0.00193813,  0.06015967],
         [-0.04041013, -0.03054984,  0.03492232, ...,  0.02538075,
           0.02416731,  0.00400976],
         ...,
         [-0.01600651,  0.02472654, -0.05597526, ..., -0.03747394,
          -0.00676691,  0.03183052],
         [-0.01505451,  0.01936168,  0.02235233, ..., -0.03423269,
           0.02561973,  0.01347464],
         [-0.02228414,  0.02474407, -0.00476847, ...,  0.00525227,
           0.00280819,  0.00245781]]]], dtype=float32), array([[[[-0.03813218, -0.03653936, -0.01403383, ...,  0.03733955,
           0.01482131,  0.02015095],
         [ 0.01479624, -0.04001186, -0.07663414, ...,  0.05886083,
          -0.04784407,  0.05854017],
         [-0.04668915, -0.04962467,  0.00360743, ...,  0.03822532,
           0.02671584, -0.01477522],
         ...,
         [ 0.01448457, -0.02342297,  0.05026488, ...,  0.06919867,
          -0.0355063 , -0.05604488],
         [-0.07016397,  0.06002268,  0.00534245, ..., -0.04965752,
          -0.07096156, -0.08452203],
         [ 0.01074862, -0.06959417, -0.02698222, ...,  0.06298807,
           0.02036724,  0.05821595]]]], dtype=float32), array([-6.34094322e-05,  1.71407778e-02, -5.70988469e-03,  2.31795944e-02,
        1.74243432e-02,  6.18966529e-03,  2.05565114e-02,  4.86137066e-03,
       -1.82028692e-02,  9.29204471e-05,  7.88843352e-03, -5.42055862e-03,
        1.12447664e-02,  6.70670345e-03, -1.08760968e-02, -1.26683908e-02,
       -8.27301014e-03,  1.06412740e-02, -9.35685763e-04, -2.91256234e-04,
        2.66368855e-02, -1.25340384e-03,  2.28992477e-02, -1.08919572e-02,
       -2.40382720e-02,  6.37108460e-03, -4.20037610e-03, -3.41989473e-03,
       -1.97244734e-02, -5.67809446e-03,  2.06401129e-03,  3.94273037e-03,
       -1.95218786e-03, -1.33802844e-02, -9.05349758e-03, -1.00359106e-02,
        1.07887434e-02, -1.41006494e-02,  1.22590754e-02,  2.34377217e-02,
        1.14461146e-02, -6.47453265e-03,  1.75857488e-02, -2.01308485e-02,
        3.29282600e-03,  1.57708395e-02,  3.42443492e-03, -1.47639820e-03,
       -1.60598606e-02, -1.21452753e-02,  9.15516168e-03,  1.11735631e-02,
        4.93790302e-03,  5.10684506e-04,  7.35370442e-03,  2.45959521e-03,
        1.08744334e-02,  7.25879753e-03,  1.31872818e-02,  1.35128470e-02,
       -1.81744322e-02, -1.37200598e-02, -1.47776464e-02, -1.66975949e-02,
       -1.14220446e-02,  1.44048715e-02,  1.40251862e-02, -9.59938206e-03,
        5.91206015e-04,  3.08336969e-02,  2.64977757e-03, -8.65654740e-03,
        5.45115035e-04, -1.64802710e-03, -1.11019872e-02,  1.22148367e-02,
       -1.29064089e-02, -1.61509812e-02, -5.70145668e-03,  7.01162126e-03,
        7.45359389e-03,  7.93111976e-03,  1.33269150e-02, -5.82976267e-03,
       -2.16971245e-03, -1.12193301e-02, -1.16349095e-02,  6.47340948e-03,
        7.71173858e-04,  1.00353071e-02, -6.99213287e-03, -5.25941281e-03,
       -4.42889193e-03,  9.63633135e-03,  1.75231660e-03,  1.39933648e-02,
        1.50690656e-02, -1.54740792e-02,  2.98885419e-03, -2.58798338e-02,
       -1.29711325e-03, -1.91508289e-02, -9.22932848e-03, -6.32445142e-03,
       -3.79581400e-03,  5.18902438e-03, -7.29579595e-04, -1.12944534e-02,
       -5.57769882e-03,  8.70925607e-04, -9.59701557e-03, -9.94989462e-03,
        6.24894747e-04,  8.40633083e-03,  7.32786069e-03,  2.82248296e-03,
       -2.09350698e-03, -1.19448630e-02, -1.21795954e-02, -2.19460707e-02,
        6.72191521e-03, -2.13140529e-02, -1.58886313e-02, -1.96614186e-03,
       -1.64550287e-03,  1.39101101e-02,  2.07916042e-03, -2.44089607e-02,
       -6.37980783e-03, -8.20587296e-03, -1.02103474e-02,  8.14708415e-03,
       -3.57737206e-03, -1.78440623e-02,  1.03188232e-02,  8.28070194e-03,
        3.40027735e-02, -8.16867780e-03, -6.18832558e-03,  1.19502638e-02,
        4.92401514e-03,  2.84663960e-02,  7.34615698e-03,  2.11768877e-03,
        2.60686339e-03,  1.04182996e-02, -7.96503015e-03,  6.12714281e-03,
        4.77612950e-03, -8.93305056e-03,  2.02239230e-02,  2.14585103e-03,
       -6.52145687e-03,  9.17603821e-03, -1.26441224e-02,  8.66099447e-03,
       -2.96694762e-03, -1.08160237e-02,  5.56331547e-03, -1.25460932e-02,
        6.35540579e-03,  8.09092075e-03, -1.69019382e-02,  4.95247170e-03,
        1.36654153e-02, -2.70994700e-04, -8.70784186e-03, -7.99401850e-03,
       -4.95758792e-03, -8.63371976e-03, -1.96086634e-02, -2.31957156e-03,
       -6.16276357e-03,  5.22650965e-03, -2.96598990e-02,  4.98841936e-03,
       -9.55443736e-03,  1.12119792e-02, -1.27088102e-02, -3.70836281e-03,
       -8.13257881e-03, -1.42506016e-02, -5.90334460e-03, -5.14869671e-03,
       -9.06964124e-04, -2.37706956e-02,  9.83656035e-04,  6.43242942e-03,
        2.25854609e-02, -4.60525928e-03,  1.51107302e-02,  1.98661145e-02],
      dtype=float32), array([ 0.2435491 ,  0.17085537, -0.2839607 , -0.30458024, -0.50297   ,
       -0.97166795, -0.27547202, -0.47007224,  0.5797677 , -0.0196024 ,
       -0.90676194,  0.47160754, -1.1423655 ,  0.772122  ,  0.6082797 ,
        0.40990707,  0.6931664 ,  1.767935  , -0.32864645, -0.6094936 ,
        0.5232955 , -0.1564898 , -0.5746798 ,  0.98808414,  0.1250433 ,
       -0.33168036, -0.26488084,  0.30948406,  0.26628205,  0.19168207,
       -0.54358214, -1.1175723 ,  1.0123338 ,  0.5956464 ,  0.40884   ,
       -0.30211425,  0.07342722,  0.5102287 ,  0.11799081, -0.2476992 ,
       -0.34806165,  0.00400089,  0.8342128 ,  0.57854766, -0.7533159 ,
       -0.92727625,  0.4917465 , -0.11680938,  0.83251286,  0.7638206 ,
        0.5415253 ,  0.9315018 , -0.03634354,  1.1620102 , -0.38844746,
       -0.7605314 , -0.14196455, -0.30473214, -0.7278246 ,  0.3853945 ,
        0.14944547,  0.47014537,  0.17769562,  0.37225607,  0.30093852,
        0.7151685 , -0.53149426, -0.80824757,  0.51299614, -0.71381724,
       -0.38557908, -0.45288837,  0.65014577,  0.33809444, -0.6852673 ,
       -1.7834941 ,  0.7859144 , -0.28901094, -0.6530489 ,  0.03996414,
       -0.14343883,  0.37726948,  0.6860214 ,  0.8002849 , -0.5771063 ,
        0.37547034,  0.35922143, -0.67543113, -0.33009633, -0.38674727,
       -0.78330207,  0.7213907 ,  1.6090586 , -0.8804703 ,  0.57668954,
       -0.78826666, -0.10677843,  0.68177044,  0.4197332 ,  0.9244947 ,
        0.63411593, -0.4221459 ,  0.87990785,  0.33556977, -1.8724555 ,
        0.27485934,  0.7804343 ,  0.79762524,  0.1547083 ,  0.44159505,
       -0.5608155 ,  0.35894206, -0.42518163, -0.8284986 , -0.06422982,
        0.7387899 ,  0.41993067,  0.5715985 ,  0.2654811 ,  1.2017367 ,
        0.43668103, -0.31410608,  0.6944619 , -0.9056361 ,  0.32151634,
       -0.17768832, -0.29437897, -0.49667102, -1.1276845 , -1.0050074 ,
       -0.0549074 , -1.1933756 ,  0.80853844,  0.4074465 , -1.03059   ,
        1.1374195 , -1.2047155 , -0.03533209,  0.313802  , -0.04790726,
        0.58314794, -0.65122986, -0.14627816,  0.0973483 , -1.311002  ,
       -0.77025324,  0.75688124,  0.02160738, -1.0175838 ,  1.3041526 ,
       -0.17766498,  0.99340427,  1.3691301 ,  0.4222698 ,  0.1005844 ,
        0.8272017 , -0.1620348 ,  0.44467655,  0.14818159,  1.1733073 ,
        0.5539611 ,  0.10198527,  0.42283672, -0.341159  , -0.3412869 ,
        0.873809  ,  0.09746096, -1.4830692 ,  0.9661139 ,  0.7113458 ,
       -0.3313995 ,  0.36276624,  0.809472  , -0.05963165, -0.89117706,
        1.2699869 , -1.1008978 ,  0.88729566, -0.10130474, -0.08957312,
        0.8413263 ,  0.15752262,  0.66063774, -1.2776582 , -0.37862897,
       -0.8189333 , -0.6466951 , -1.1275365 ,  0.12215056,  0.69109726,
       -0.8570359 ,  0.15912583], dtype=float32), array([1.50591   , 2.9070861 , 2.5709686 , 1.1526171 , 3.0324402 ,
       2.081385  , 2.3871958 , 1.1252197 , 2.71616   , 2.2868707 ,
       4.98163   , 2.1578772 , 1.2087543 , 2.8864317 , 1.7123302 ,
       1.8030087 , 1.5014192 , 4.6807055 , 2.0212922 , 4.1342106 ,
       2.9746926 , 2.6710374 , 4.178273  , 2.4612088 , 2.2765448 ,
       2.3689299 , 2.8719497 , 1.3203008 , 1.4524658 , 3.464682  ,
       1.7602398 , 3.4324696 , 4.466821  , 3.0638576 , 1.685709  ,
       2.6421561 , 3.1645737 , 0.6091093 , 3.3605793 , 2.6744592 ,
       2.5767016 , 2.631043  , 2.3314633 , 1.0856473 , 2.5798266 ,
       3.242053  , 2.406748  , 1.0475986 , 1.1367404 , 2.216834  ,
       1.5998971 , 3.3700638 , 1.8664182 , 3.2583318 , 1.1946151 ,
       1.2945402 , 1.3748678 , 1.9316392 , 3.2299728 , 3.3070316 ,
       2.1557553 , 2.6389337 , 2.348749  , 1.477809  , 4.424081  ,
       4.397266  , 3.2336936 , 2.4850497 , 2.3563836 , 2.617051  ,
       3.1103954 , 2.8227944 , 2.2427433 , 1.3762045 , 1.0488466 ,
       5.447084  , 1.4753036 , 1.5162203 , 3.067806  , 1.7838551 ,
       0.95332086, 2.713333  , 2.1369681 , 1.2249006 , 1.2842884 ,
       1.2938169 , 3.4860544 , 2.2417645 , 1.0966221 , 2.3355918 ,
       1.4855946 , 2.2961543 , 4.11882   , 2.3810298 , 1.5167826 ,
       3.0408719 , 2.4796827 , 2.7260973 , 1.9310573 , 2.2350101 ,
       2.7796228 , 1.3542503 , 2.5553997 , 1.4386882 , 3.4189873 ,
       3.281074  , 2.354046  , 2.7807374 , 3.487079  , 1.86075   ,
       1.5426315 , 2.7615943 , 2.8403096 , 2.488887  , 1.9335903 ,
       4.338018  , 2.9229267 , 1.3094479 , 2.178357  , 2.602037  ,
       1.8026186 , 1.7980088 , 3.649414  , 3.6464999 , 1.7464739 ,
       2.9604106 , 1.1893773 , 2.591994  , 2.6019015 , 2.3612485 ,
       1.489345  , 3.2841012 , 3.1393955 , 2.1698413 , 2.9878716 ,
       3.8250084 , 6.931714  , 1.6859131 , 2.7695916 , 2.0287917 ,
       3.0680625 , 4.0078545 , 1.949483  , 3.4749055 , 2.6011083 ,
       2.6215785 , 3.2776077 , 2.1748276 , 3.1281    , 3.3843331 ,
       4.1312785 , 2.3993871 , 3.678236  , 3.3372853 , 2.5775602 ,
       2.1508346 , 1.9403093 , 2.2731006 , 3.9429848 , 3.9377475 ,
       4.9775167 , 2.135551  , 2.4954724 , 3.9560225 , 2.2952769 ,
       2.780627  , 3.3850873 , 2.4708169 , 3.3583465 , 5.71968   ,
       2.3123999 , 0.8873929 , 2.4262936 , 2.1225488 , 2.5595064 ,
       1.9405639 , 3.3367286 , 2.9119728 , 1.5568209 , 1.3759701 ,
       3.8435502 , 2.3861198 , 1.0846173 , 4.2417417 , 3.3020709 ,
       0.8396534 , 2.3697884 , 2.5268466 , 3.208879  , 2.725321  ,
       3.5048225 , 1.8440894 ], dtype=float32), array([ 0.01551064,  0.00056515, -0.00848663, -0.00582569, -0.01562227,
        0.02059232, -0.00148837, -0.02274533,  0.01520687,  0.00542328,
       -0.02135542, -0.00287431, -0.00712484, -0.00793386, -0.00232565,
        0.00274966, -0.0181472 ,  0.00948507,  0.01788553,  0.00798487,
        0.00394562,  0.0038597 ,  0.01602116,  0.02658543, -0.00981145,
        0.00699803, -0.00693656,  0.02613349,  0.01611931, -0.00630424,
        0.00166548, -0.0054891 ,  0.00331837, -0.00290615,  0.01468696,
       -0.01584155, -0.01947973,  0.01763882,  0.01695426,  0.00257871,
        0.00012054,  0.0145935 ,  0.0197346 ,  0.01022121, -0.00217263,
       -0.00497978,  0.00981568,  0.0072006 ,  0.00538362,  0.01074619,
        0.00747902, -0.01187741, -0.00545855, -0.01448886,  0.00763026,
        0.00633201, -0.01097745, -0.01259731,  0.00854115,  0.00720196,
        0.00556978, -0.00817658, -0.02287434, -0.00651583,  0.00958692,
        0.00652843, -0.02288031, -0.01373254, -0.02039465, -0.00926524,
        0.00292939,  0.00022375,  0.02256938, -0.02701746, -0.00078445,
        0.01862941,  0.00107172, -0.00229955,  0.01689782, -0.00695946,
        0.01018479,  0.00327991,  0.00924759,  0.00615116, -0.00280722,
       -0.00301513,  0.00626856, -0.01936506,  0.01114506, -0.00802431,
        0.00059277,  0.01037981, -0.00439291, -0.00665275,  0.00754389,
        0.00700088, -0.01072007, -0.00549354, -0.0171721 , -0.00628691,
       -0.00154054,  0.02903667, -0.0080263 ,  0.00994395, -0.00834179,
        0.00953383, -0.00088174, -0.00922563, -0.01199167,  0.00658253,
       -0.01093546,  0.00830914,  0.00789494,  0.0051086 , -0.00143604,
       -0.00163248,  0.01206948, -0.00109567, -0.00722301, -0.01266772,
       -0.01713573, -0.00076918, -0.00807346, -0.00870779,  0.00700412,
        0.01129059, -0.00480937,  0.00094819, -0.01185943,  0.01188912,
        0.00472034, -0.00194852,  0.01615272,  0.01208987, -0.01040263,
        0.0007573 , -0.02040175,  0.00057504, -0.00471748,  0.00341372,
        0.00588591,  0.00480991, -0.02119285,  0.01096012,  0.01473495,
       -0.00218458,  0.01573257, -0.00066648,  0.00599711, -0.00064923,
       -0.02258972, -0.00533919, -0.01311322, -0.00329103,  0.01404746,
        0.00382273,  0.00421587,  0.01007997, -0.00654722, -0.02303028,
        0.0019919 ,  0.00133213, -0.01261317,  0.00299425, -0.00652003,
       -0.01846681, -0.01688357, -0.00663435, -0.00447632,  0.00579975,
        0.00878828, -0.00742035,  0.00344691,  0.00480212, -0.01138099,
        0.01447398, -0.01147856, -0.0063816 ,  0.00316436, -0.00877181,
       -0.00395071,  0.01812716, -0.00161254,  0.00764081,  0.00834197,
        0.00683087,  0.01130808,  0.01244476, -0.00729741, -0.00518312,
        0.03899135, -0.00176157], dtype=float32), array([-0.6627805 ,  0.8802047 ,  0.4131577 , -0.01644718, -0.7244961 ,
       -0.5083918 , -0.21140045,  0.3917719 , -0.67620385, -1.0653554 ,
        1.4329424 , -1.37158   , -0.50250036,  0.6501315 , -0.3810131 ,
        0.57561815,  0.785407  , -1.181259  , -1.3489442 ,  0.9548866 ,
       -0.3261999 ,  0.80254376,  0.10153136, -0.75813544, -1.1174362 ,
       -0.64771056,  0.08438522, -0.3776918 ,  1.0006261 ,  1.4476454 ,
       -0.745274  ,  0.02154279,  1.1688334 , -1.0352796 , -0.55766326,
        0.04565917, -0.28753513,  0.5078944 , -0.67915356, -0.9730185 ,
        0.3864466 , -1.1098187 , -0.93546796, -0.8222452 ,  0.21239729,
        0.720189  , -0.94408107, -0.576956  ,  0.72155076, -0.568124  ,
        0.11044741,  0.35622987,  0.02622042,  0.47932762,  1.2610899 ,
       -0.50802124,  0.7238555 ,  1.3272028 , -0.43781105, -0.6908248 ,
       -0.33384308,  0.60646725,  0.6195205 ,  0.30151215,  1.18071   ,
        0.9359956 ,  0.26615536,  1.012625  ,  0.78698903, -0.8038654 ,
       -0.84706575, -1.7134396 ,  0.44047037, -0.6879402 ,  1.0553756 ,
        1.1855773 , -0.7379259 ,  0.49096102, -1.1886485 ,  0.19881696,
       -0.49488857,  0.3727687 ,  0.87288946,  0.9871907 ,  1.0914592 ,
       -0.48930433,  0.95622396,  0.74766284, -0.47412297,  0.42703512,
       -0.954823  , -2.028217  ,  0.9987134 ,  0.72521114, -1.0177296 ,
       -0.34752142, -0.40645394,  0.31230932, -1.325872  ,  1.3527131 ,
       -0.3527548 , -0.02816042,  0.9198993 ,  1.0411081 ,  1.1643238 ,
       -0.67866504,  0.716102  , -0.94218385, -1.2501179 , -1.0627664 ,
        0.8308198 , -0.00806007,  0.79886144, -0.06529894,  0.26834795,
       -1.620199  , -0.86386627,  0.3216141 ,  1.2025789 ,  0.8044831 ,
       -0.02722452,  0.2661741 , -0.9418177 ,  1.2248561 ,  0.9762426 ,
       -1.152867  ,  0.6616537 ,  1.7223473 , -0.51304096, -0.3166982 ,
        0.871     ,  0.806861  , -1.0167205 ,  1.4788334 ,  0.6093108 ,
        0.71568453, -1.3550762 ,  0.82644826, -0.29399177, -1.6529803 ,
        1.2886167 , -1.007457  ,  1.3687418 , -0.8131244 , -1.1099169 ,
       -0.16225012,  0.76311356,  1.6656902 , -0.11566317, -0.25561243,
       -1.0627258 , -0.8756032 ,  1.0910761 ,  0.13134977, -1.310974  ,
       -0.14706409, -0.46737394,  1.4225194 ,  0.97798187, -1.1039814 ,
        0.5712437 ,  0.19946629,  0.6804958 ,  0.551557  , -0.19117083,
        0.6271287 , -1.2278545 ,  1.2455934 ,  0.9768612 , -1.3177848 ,
       -0.48923475,  1.4301126 , -0.8506944 , -0.9427065 , -0.95443   ,
       -0.2884992 ,  0.0574574 ,  0.6061001 ,  0.72922075, -1.4100063 ,
        0.36327624,  0.88706183,  0.69261074, -1.0194196 , -1.1843885 ,
        1.4345131 , -1.1277442 ,  0.5558768 ,  0.3032974 ,  0.37257132,
        0.5947379 ,  0.2818147 ], dtype=float32), array([ 3.9703376,  3.4972835,  1.2564083,  4.2767706,  7.7927737,
        2.2158904,  1.3269986,  9.072983 ,  3.6861563,  3.1750195,
        5.076061 , 10.308989 ,  2.1225271,  3.330681 ,  5.4526014,
        5.665373 ,  8.289774 ,  7.1080303, 11.682655 ,  4.987765 ,
        2.1994078,  6.6933703,  2.1390996,  3.8526702,  5.3324485,
       11.002126 ,  6.025959 ,  1.5658796,  3.2451267,  5.6170735,
        4.7006516,  1.903192 , 12.807774 ,  5.7811604,  3.617421 ,
        4.8895855,  1.4297276,  8.243997 ,  3.3668685,  9.257359 ,
        6.3235626,  6.023126 ,  3.730761 , 11.441603 ,  3.9218695,
        1.6045994,  7.1742167,  2.8659317,  8.879343 ,  0.8686467,
        2.8038926,  5.031049 ,  1.1367934,  1.3244283, 12.549642 ,
        1.9318013,  6.841466 ,  3.7470334,  5.1969905,  5.0075955,
        4.699858 ,  1.5655551,  4.5781717,  6.4990444,  7.9124804,
        6.570258 ,  3.8556921,  7.6799607,  8.196242 ,  3.463485 ,
        5.5249195,  8.294398 ,  9.651627 ,  2.3020334, 11.535179 ,
        9.038471 ,  6.679663 ,  1.3450452,  6.318208 ,  2.624366 ,
        2.1145167,  2.2548301,  3.5937884,  9.045749 ,  5.672594 ,
        1.8047419,  6.145479 ,  4.743094 ,  3.6459732,  5.639501 ,
        5.3558254, 13.473534 ,  7.4323077,  5.780189 ,  9.495329 ,
        1.6675802,  1.4128282,  1.6930995,  3.9842262,  6.517276 ,
        2.475931 ,  2.5280948,  9.938384 ,  2.957273 ,  9.139396 ,
        2.5410528,  1.9732903,  6.885473 ,  3.0439844,  5.6724977,
        6.3322845,  1.2522604,  6.468005 ,  1.2287955,  5.5805116,
        4.5281653,  2.2694232,  5.1829123,  6.36712  ,  3.5088212,
        1.5963999,  4.0671024, 14.741156 , 12.792093 ,  2.5228045,
        5.5967984,  6.2095275,  9.319965 ,  5.146554 ,  3.5721142,
        8.135522 ,  6.7617593,  3.640306 ,  8.588262 ,  2.151147 ,
        8.016434 ,  3.1808522,  5.7854223,  3.3377702,  7.3423414,
        8.811742 ,  3.365985 ,  6.6875043,  2.7538369, 10.871648 ,
        4.080102 ,  5.0557356,  9.438359 ,  3.3395028,  5.9998074,
        4.321576 ,  2.5695958,  6.293214 ,  2.653691 ,  9.009578 ,
        2.0084   ,  2.9030876, 10.274895 ,  7.4807034,  2.3087642,
        5.272208 ,  2.9728494,  7.9482317,  2.5383565,  1.6340959,
        6.342399 ,  2.7871325, 12.766257 ,  5.3966126,  4.3647738,
        8.742773 ,  9.020546 ,  3.2099721,  5.6900787,  3.1791759,
        3.376509 ,  3.8017051,  3.9194374,  5.0260487,  4.774328 ,
        2.0648713,  6.067695 ,  6.0559797,  7.423172 ,  4.058298 ,
        4.053715 ,  3.066991 ,  4.7755756,  5.6724234,  2.4703395,
        7.265023 ,  2.1172404], dtype=float32), array([-7.57403160e-03, -1.16313929e-02, -4.51401062e-03,  2.42916914e-03,
       -1.29006524e-02,  7.17250817e-03,  9.77095217e-04,  2.71069258e-03,
        1.34608904e-02, -2.62447353e-03, -9.38181358e-04, -2.59369705e-03,
       -1.27784917e-02, -2.20834687e-02,  4.69060196e-03,  7.93751422e-03,
       -1.61561761e-02, -1.67450085e-02,  4.87445621e-03, -7.70382909e-03,
        8.21851660e-03,  4.34921170e-03, -3.36825359e-03, -1.12669636e-02,
       -1.40026677e-02,  3.03374287e-02, -2.66792979e-02, -1.85563061e-02,
        1.51603566e-02,  1.89299081e-02,  8.65550339e-03,  1.18812881e-02,
       -7.28405733e-03, -2.62164092e-03,  2.05692509e-03, -1.08171795e-02,
        5.56199392e-03,  7.00666290e-03,  1.61051713e-02, -5.42669697e-03,
       -9.99573804e-03, -8.86766892e-03, -7.76539650e-03, -1.94832115e-04,
        2.40105204e-02,  3.98567785e-03,  7.52555160e-03, -1.65401846e-02,
        1.49110872e-02,  2.16493178e-02,  1.02031545e-03,  8.91166739e-03,
        1.07136173e-02,  6.16934430e-03,  2.78901518e-03, -2.39896937e-03,
        4.22529597e-03, -1.17960833e-02, -2.05710065e-02, -3.71446181e-03,
       -2.03351793e-03, -1.90243497e-03, -6.84398739e-03, -1.53724803e-02,
       -8.06036126e-03,  4.94553428e-03, -1.39460275e-02,  1.45627884e-03,
       -7.77856726e-03, -1.80464406e-02, -7.43552716e-03, -1.27940793e-02,
       -5.74067095e-03, -7.76073709e-03,  1.94116600e-03, -2.47566588e-03,
        1.21920779e-02,  2.00609514e-03, -1.44927325e-02,  1.12051275e-02,
        7.59959966e-03, -8.59105960e-03,  1.10820420e-02,  9.20488499e-03,
        1.05943577e-02, -1.43285207e-02,  5.64482762e-03,  2.19786242e-02,
        1.39884157e-02,  1.26817974e-03, -6.58212346e-04,  2.12658737e-02,
       -2.34531425e-03, -2.07705051e-02, -7.82502349e-03, -5.00664115e-03,
        1.29175354e-02, -1.83323154e-03, -3.51015897e-03,  1.23105869e-02,
        1.25116222e-02, -2.46430887e-03, -4.10527689e-03, -1.66953949e-03,
        3.14030400e-03,  3.49078514e-03,  2.29056505e-03, -1.02036241e-02,
       -1.19506344e-02,  2.18474609e-03, -2.59005144e-04,  9.36434418e-03,
       -1.27269933e-02, -8.54790863e-03,  3.88265634e-03,  6.64776145e-03,
        2.32869992e-04, -1.13822129e-02,  1.01500656e-03, -1.38612790e-02,
       -3.56571190e-03,  1.40356561e-02, -1.95069499e-02, -1.13519579e-02,
       -8.91608838e-03, -1.18998410e-02,  4.99724783e-03,  1.63440891e-02,
        2.03713425e-03, -5.61112072e-03, -8.58552475e-03, -8.53496511e-03,
       -1.14748459e-02,  2.36454271e-02,  1.38804526e-03, -4.47361637e-03,
        1.44492825e-02,  1.56209734e-03, -3.36228899e-04, -6.14304375e-03,
       -1.71301625e-04, -9.14293528e-03,  5.31313941e-03,  6.17626915e-03,
       -3.25777708e-03,  4.26333252e-04,  1.12127117e-03, -1.42004490e-02,
       -1.51208369e-02, -1.75029258e-04, -1.14875911e-02, -9.81382676e-04,
        2.36263615e-03,  9.02031641e-03,  4.33213729e-03,  7.77933886e-03,
       -1.67705733e-02,  1.46894241e-02,  7.36657064e-04,  5.92059270e-03,
       -3.25499242e-03,  1.92627520e-03,  5.73349511e-03, -1.84634402e-02,
       -1.85212877e-03,  2.84060906e-03, -1.78126327e-03, -2.77363625e-03,
        3.36576207e-03,  1.12174097e-02, -7.49685988e-03, -6.31834613e-03,
        1.26549415e-02,  1.33084934e-02, -6.17025699e-03, -1.09422468e-02,
       -6.86258310e-03,  1.37359556e-02,  8.30750540e-03, -8.28077737e-03,
        2.11733058e-02,  2.97962427e-02,  4.68903221e-04,  1.11802723e-02,
       -2.76704738e-03, -1.72523074e-02,  2.77030305e-03, -8.86099227e-03,
        7.82090798e-03,  2.84204925e-05, -4.01583919e-03,  2.29818355e-02],
      dtype=float32), array([-0.9097695 ,  0.9795036 , -0.73872113, -0.7029398 ,  0.57049185,
       -0.42812663, -1.1040989 ,  0.55489224,  0.3765818 ,  0.10761081,
        0.87985593,  1.0216963 ,  0.33392164,  0.9893049 ,  1.3329989 ,
       -0.94133294,  0.8766589 ,  0.17258339, -0.5328054 , -0.7343005 ,
       -0.38752845,  0.29513788,  0.5549438 , -1.0026788 ,  1.272789  ,
       -0.44351962,  0.6035529 ,  0.8007404 , -0.30616114, -0.2103093 ,
       -0.65075684,  1.0368854 , -0.60703117,  0.7584707 ,  0.15774733,
        1.4165311 , -0.7717495 ,  0.60431707, -0.2711127 , -0.6781418 ,
        0.4296808 , -0.80336225, -1.3196089 ,  1.247291  , -0.1986432 ,
       -1.1663786 ,  0.22092448,  0.6906824 , -0.94419277, -0.5323915 ,
        0.10251404, -0.5445225 , -0.6384531 , -0.494069  , -0.6670451 ,
        0.22433262, -0.96062833, -1.1331946 ,  0.45988023,  0.2618179 ,
       -0.6565111 , -0.3137482 , -0.23575413,  0.6872928 ,  0.673485  ,
       -0.9646956 ,  0.5916915 , -0.54296875,  0.70264757,  0.36587483,
        0.7511533 ,  0.47619665, -0.5298487 , -1.305797  , -1.2179697 ,
       -0.33321846, -0.80375236, -0.10732208, -0.38240686, -0.79667664,
       -1.0463967 , -0.73947793, -0.9194098 , -0.71460015, -1.0469896 ,
        0.6793785 , -0.366829  , -1.2998658 , -0.2298042 , -0.62396646,
       -1.5606937 , -0.8191564 ,  0.5002202 ,  0.7786509 ,  0.54446304,
       -0.5600751 , -0.615577  ,  0.8658168 ,  0.9679159 ,  0.37549767,
        0.72644734, -1.1177527 ,  0.9437982 ,  1.0933512 , -1.0584638 ,
        0.8105975 , -0.8778155 , -0.76030624,  0.7147507 ,  0.39609262,
        0.3439916 , -0.8804332 ,  0.30538425, -1.0294266 ,  0.41567105,
        0.451461  , -1.1338359 , -1.461152  , -1.1127691 ,  1.0520867 ,
       -1.1210338 , -1.1475576 ,  0.2659196 ,  0.7529643 , -0.27575687,
        0.8310589 ,  0.57280695, -0.68912417, -0.7493497 , -0.86748564,
        0.8326511 , -0.1562797 ,  1.2687794 , -0.19082715,  0.59696764,
       -1.460514  , -0.567099  ,  0.5196914 , -0.42507306, -0.9276737 ,
       -0.77761936, -1.2283435 , -0.25857565, -0.44291183, -0.39265546,
       -1.434331  ,  1.1482621 , -1.1544044 , -0.5806286 , -1.2996246 ,
        0.2509844 , -0.6263354 , -0.81992304,  0.40560347, -0.8966455 ,
        0.04707033,  0.11915661, -0.23673084,  0.24924187, -0.5921066 ,
       -0.7311692 , -0.21395262, -0.9728059 ,  0.8703127 ,  0.55715144,
        0.12821798, -1.0209442 ,  0.5444335 ,  0.94909257,  0.5877978 ,
       -1.1237187 , -0.05471829, -1.3645754 ,  0.5863943 , -0.81075364,
       -1.1350838 , -0.66770375, -0.429729  , -0.24835941,  0.78825986,
       -0.7713302 , -1.391511  , -0.4830999 , -0.54703027,  0.93757373,
        0.59589523, -0.42034942,  0.2930735 ,  1.0133532 , -0.8437722 ,
        1.2022274 ,  0.48829177], dtype=float32), array([ 4.770937 ,  3.238782 ,  4.0883083,  2.7913451,  3.0249138,
        4.920214 ,  2.6079795,  4.7502646,  5.636583 ,  1.6942432,
        7.283187 ,  3.9373744,  2.944635 ,  3.6775403,  5.44882  ,
        3.9523563,  6.5665355,  4.474228 ,  2.8328516,  5.558361 ,
        4.3299847,  4.2641   ,  2.6904767,  5.0501513, 10.373238 ,
        3.5578716,  2.066776 ,  2.3806298,  3.8748329,  2.139574 ,
        2.6940522,  6.154545 ,  1.9859548,  5.5621743,  3.2689383,
       10.366445 ,  6.2738743,  4.3096137,  3.99939  ,  3.5914683,
        2.1781507,  4.2127447,  5.460505 ,  8.543405 ,  1.8184448,
        5.50837  ,  4.2936974,  3.7259364,  5.539098 ,  3.3558064,
        2.9352443,  3.130662 ,  2.2555473,  3.771802 ,  4.2958946,
        2.348007 ,  5.8493276,  5.319709 ,  2.860324 ,  8.375121 ,
        3.0547698,  4.497567 ,  0.8498423,  3.5401645,  6.1703086,
        4.897051 ,  2.4991214,  5.3821626,  4.3229523,  3.8054726,
        5.239877 ,  2.3762476,  3.9642844,  6.6791873,  5.917559 ,
        6.323614 ,  5.8211536,  3.241109 ,  4.4319415,  3.5848002,
        3.7089117,  1.4371074,  4.401053 ,  3.1400917,  5.817244 ,
        4.30334  ,  5.469756 ,  3.668946 ,  2.4694035,  3.5201676,
        7.470973 ,  3.7863288,  2.493908 ,  6.1580043,  1.3376681,
        6.21844  ,  5.229177 ,  4.8498187,  3.8591652,  3.803623 ,
        6.760477 ,  4.22969  ,  3.9663174,  4.5998526,  5.087611 ,
        3.010103 ,  2.509585 ,  3.2454798,  2.9111898,  2.7783601,
        2.725404 ,  3.3159919,  3.3845294,  6.6433215,  2.364915 ,
        1.9782243,  3.5283465,  7.2485814,  5.3692555,  4.318259 ,
        3.233058 ,  7.117092 ,  4.9650865,  5.467388 ,  1.92915  ,
        2.1762483,  7.154963 ,  9.790999 ,  2.001139 ,  2.4820771,
        5.2866316,  2.389541 ,  6.455545 ,  0.6741898,  4.8877144,
        6.2014527,  3.5955753,  1.8868606,  2.3528755,  7.234261 ,
        4.146181 ,  3.8978608,  2.3242376,  3.2111933,  1.392285 ,
        5.319159 ,  6.0064588,  6.51288  ,  3.1030529,  6.996659 ,
        2.3438733,  2.1394954,  4.415489 ,  6.9963994,  4.4139585,
        3.9568756,  3.8609571,  3.8465564,  4.0601544,  2.0082157,
        4.232283 ,  4.298667 ,  5.271841 ,  3.723348 ,  4.156948 ,
        3.5936337,  2.181694 ,  3.861218 ,  6.05907  ,  3.8154345,
        4.7700963,  1.3158623,  3.7139785,  3.5614035,  2.740855 ,
        5.249298 ,  2.8542514,  3.9056625,  2.5609477,  2.9423752,
        4.287677 , 10.64007  ,  4.255939 ,  3.593795 ,  3.1361156,
        2.230392 ,  2.3325272,  2.3837562,  4.49535  ,  2.8249042,
        4.8138947,  4.3668065], dtype=float32), array([-1.38547206e-02,  1.24895573e-03,  1.71119422e-02,  3.44276032e-03,
       -1.53535204e-02,  6.90172426e-03,  2.91383849e-03,  2.21192371e-02,
        2.75893457e-04,  9.91633534e-03,  6.82009431e-03, -8.17352720e-03,
       -2.24158168e-03,  7.31485663e-03,  4.53886716e-03,  2.44351896e-03,
       -1.44972495e-04,  2.58496962e-02,  2.54876856e-02, -1.11375311e-02,
       -1.76569296e-03, -3.31723900e-03,  5.14058257e-03, -6.58968091e-03,
       -7.21012801e-03, -4.85477457e-03, -1.25145139e-02, -4.89652157e-03,
       -9.51076578e-03, -5.87533182e-03, -5.02841361e-03,  9.54023097e-03,
        2.88372539e-04,  2.28251088e-02, -1.08378762e-02, -8.80232453e-03,
       -3.82370339e-03,  3.94350413e-04,  1.38965519e-02, -1.86626296e-02,
        3.55508644e-03, -4.16106923e-05, -2.84108479e-04, -4.78349486e-03,
        2.43487284e-02, -6.23516412e-03, -1.57584040e-03,  6.44837157e-04,
       -1.24428365e-02, -4.94701648e-03, -1.53873069e-02,  6.36546640e-03,
        1.05800191e-02, -7.30497716e-03,  1.19508314e-03,  1.24051934e-02,
        1.15822116e-03,  8.06753244e-03,  1.54484892e-02,  1.31681887e-02,
        7.53244245e-03,  9.91549226e-04,  2.52563059e-02,  2.36409181e-03,
       -1.44803757e-02, -3.45602562e-03,  8.56458675e-03, -1.78977847e-02,
       -1.08106500e-02,  7.64516788e-03, -3.65425670e-03,  4.57588909e-03,
        1.52318238e-03, -6.51873508e-03, -1.52474409e-02, -8.21174774e-03,
       -5.48064662e-03,  7.75502995e-03,  9.19607526e-04, -2.05086991e-02,
       -3.19222803e-03, -4.57331631e-03,  1.41122574e-02,  1.39245922e-02,
        1.80940318e-04,  1.09348260e-02,  3.08071822e-02, -3.72084934e-04,
        1.59078185e-02, -8.06006137e-03, -7.17767095e-03,  1.06472261e-02,
       -1.34864338e-02,  1.92130532e-03,  1.06054009e-03, -1.17498012e-02,
       -1.07344259e-02, -2.87717488e-03, -2.15649493e-02, -9.86872474e-04,
       -7.90688768e-03, -3.12908576e-03, -7.48580555e-04, -9.35666077e-03,
        1.71392527e-03,  2.51485463e-02, -5.86252660e-03, -4.37560445e-03,
        1.13372570e-02,  3.79549502e-03, -5.41130453e-03, -7.05180457e-03,
        1.65623594e-02, -1.30778439e-02,  1.99773815e-02, -7.49315834e-03,
       -2.96243146e-04, -2.12480817e-02,  1.12380006e-03, -1.41824195e-02,
       -5.07041754e-04,  1.08878380e-02,  2.60855420e-03,  7.65352370e-03,
        9.64817533e-04,  1.84878532e-03,  1.09458424e-03, -1.54376030e-02,
       -6.03224733e-04, -6.01672009e-03,  1.19858375e-02, -5.29103214e-03,
       -4.48182598e-03,  2.37876503e-03,  6.96688518e-03,  2.04292522e-03,
        2.11548689e-03,  8.97785276e-03, -7.02959113e-03, -7.82815274e-03,
        4.51499876e-03,  2.20652632e-02, -4.71624685e-03,  9.15213581e-03,
        5.17482869e-03, -1.05216382e-02,  1.81007143e-02,  9.63091478e-03,
        8.24455731e-03,  2.04227939e-02,  5.58601879e-03, -1.41674969e-02,
       -4.12802584e-03,  1.41828842e-02,  1.25199910e-02,  9.41062998e-03,
       -9.92507581e-03,  1.14581035e-02, -7.48758111e-03, -5.19707426e-03,
        2.00581718e-02, -8.93586955e-04,  6.27862196e-03, -4.85797506e-03,
        1.59599129e-02,  1.00813787e-02, -2.24950388e-02, -9.05893650e-03,
       -5.94302732e-03, -1.84938684e-02, -2.95614614e-03,  1.38488505e-02,
       -3.05961556e-04, -1.53746083e-03, -1.76093951e-02,  9.42442159e-04,
       -7.98894837e-03, -8.59999284e-03,  1.51279001e-02, -4.93113277e-03,
        5.31934341e-03,  4.77752555e-03,  4.06760926e-04,  4.29599918e-03,
       -5.61326882e-03, -1.37815662e-02,  3.62816011e-03,  1.35740200e-02,
       -4.67692968e-03, -9.20548476e-03,  1.16309524e-02,  9.26226284e-03],
      dtype=float32), array([ 0.7620156 , -0.84050184, -0.32442653,  0.5253787 ,  0.5622249 ,
        1.1594231 ,  0.16328108, -0.31155977,  1.2585653 , -0.04988094,
       -0.30275106, -1.4041667 ,  0.9642113 ,  0.9105942 ,  0.637842  ,
        0.31443664,  0.2020706 , -0.5207265 ,  0.5877718 ,  0.02448676,
       -0.84022176,  1.3096169 ,  0.4242921 , -1.2478598 , -0.54262656,
       -1.0649279 ,  0.5776118 ,  0.28608003, -0.44552076, -1.4399401 ,
        0.21734366, -1.3198836 ,  1.1841062 ,  0.49040532, -1.022078  ,
        0.5925798 , -0.15035865,  0.6051143 , -0.20890878, -0.2595523 ,
        0.67428917,  0.28465095, -1.161033  ,  0.31067505, -0.88473135,
        1.4781196 ,  0.3271664 ,  1.0458239 ,  0.90845466, -0.27321434,
       -0.28975895, -1.176531  , -0.9993968 ,  0.20777479,  0.42402688,
       -1.0750405 , -0.15645592, -1.1502984 , -0.13827471,  0.4836941 ,
        0.4032043 , -0.946776  ,  0.6308575 ,  1.1707387 ,  0.73518217,
       -0.90993667,  0.2089655 , -0.9279593 ,  0.37200364, -0.71430916,
        0.5399273 ,  0.08754805, -1.3666687 , -0.21795793, -0.20734525,
        1.2578154 ,  1.1850928 , -0.5033337 ,  0.01699089,  1.4616299 ,
        0.16424584,  0.21650806,  0.6429365 ,  0.07902401, -0.55403006,
       -0.02984277, -0.19535235,  1.2613109 , -0.21020994,  0.70079875,
        0.9633634 , -0.9797996 , -0.5568973 , -0.23281175, -1.0687399 ,
       -0.6703251 ,  0.8539449 ,  0.70327395,  0.59628546, -0.8026159 ,
        1.3340673 ,  1.1741691 ,  0.6983404 , -0.58144635,  1.0224009 ,
       -0.04680043, -0.63197845, -0.42969957,  0.03408898, -0.04587169,
        0.7168713 , -0.8494872 , -0.13359974,  0.89710504,  0.42266107,
        0.10042741,  0.32223666,  1.0151267 ,  0.6147223 ,  0.44903165,
       -0.07356753,  0.74063855, -0.2745804 ,  0.2855659 ,  1.1824521 ,
       -0.32787856,  0.42809457,  0.58620113,  1.382574  , -0.5184213 ,
       -0.50474596, -0.7584783 ,  0.83311695, -0.07766692, -0.6232245 ,
        1.0914129 , -1.3300867 , -0.10981952, -0.35832718, -0.5730856 ,
       -0.07943036, -0.6381473 , -1.6111702 , -0.77888036,  0.1554455 ,
       -0.73498356, -0.6772857 , -0.04022398,  0.3179071 , -0.45214447,
       -0.6630018 , -0.31490993, -0.6003262 ,  0.25794965,  0.11248591,
       -1.2567883 ,  0.6189034 ,  0.02202981, -1.0460105 ,  1.1074142 ,
       -1.111044  ,  0.5625765 ,  0.02471445, -0.6986642 , -0.6759847 ,
        0.06910626, -0.26311108,  0.26795328,  0.5985885 ,  0.27642223,
        0.18648948,  0.838571  , -0.3749829 ,  1.0803175 ,  0.05012396,
        0.39901724, -0.00991686,  0.7306234 , -0.33263925,  0.72008187,
       -0.5507295 ,  0.8232222 , -0.41444924, -0.42513165, -1.3305472 ,
       -0.17178766,  0.19787851, -0.17951466, -0.02405212,  0.42950213,
        0.48356637, -1.5445522 ], dtype=float32), array([3.6614828 , 1.2067126 , 1.456933  , 3.1278577 , 3.2361994 ,
       4.160887  , 1.1564229 , 4.4172616 , 5.035364  , 2.2147331 ,
       2.3288288 , 3.885835  , 1.4745297 , 1.9227595 , 3.0245738 ,
       2.3604753 , 2.48342   , 1.290067  , 2.118727  , 1.5787638 ,
       1.8003744 , 2.3168633 , 1.5055264 , 2.2213643 , 4.293667  ,
       2.3378506 , 3.280704  , 2.770894  , 2.9805698 , 1.710967  ,
       2.0582945 , 1.475798  , 1.6679511 , 3.7826142 , 2.4167576 ,
       2.3166027 , 1.7047324 , 2.7611604 , 2.1750064 , 1.0351144 ,
       1.7568809 , 0.94742143, 2.798117  , 2.2703917 , 2.3513222 ,
       3.3723593 , 2.4133732 , 3.4773147 , 1.9380392 , 1.1129242 ,
       1.9114043 , 1.8899494 , 2.0487304 , 1.1701093 , 3.3372037 ,
       2.2379863 , 1.0420601 , 2.843893  , 2.6709588 , 2.7712624 ,
       2.5004969 , 2.8363788 , 1.7949562 , 4.0413613 , 1.9253628 ,
       1.3511415 , 2.578262  , 4.788038  , 3.7674308 , 2.8322651 ,
       4.5059476 , 1.8838652 , 2.3203652 , 1.8664649 , 3.520988  ,
       4.605785  , 3.3337023 , 1.6014291 , 2.1467602 , 3.049507  ,
       1.4512684 , 1.0088888 , 3.3804932 , 3.2444305 , 1.8556981 ,
       2.527318  , 2.5142708 , 3.1778667 , 1.8621811 , 2.830297  ,
       1.9388384 , 2.931224  , 1.3251762 , 1.1003609 , 2.4502573 ,
       1.4248291 , 2.1959202 , 2.3283834 , 2.8883703 , 3.0678546 ,
       3.2172985 , 2.119634  , 2.6336951 , 3.1012206 , 2.5779836 ,
       1.5744836 , 2.3813827 , 1.8884691 , 1.7081656 , 1.3898296 ,
       2.6437528 , 3.6744254 , 2.6829531 , 3.5583498 , 2.6501737 ,
       1.4935569 , 2.1110826 , 2.9866567 , 1.983682  , 2.102992  ,
       1.2303131 , 3.9027724 , 1.5954392 , 1.5931838 , 4.194458  ,
       2.1993918 , 2.1715908 , 2.5169165 , 4.2860637 , 2.3135486 ,
       3.7023342 , 2.3153074 , 5.1287136 , 2.695655  , 1.2270474 ,
       2.5415857 , 2.5639806 , 1.6990343 , 2.1299555 , 1.7480621 ,
       5.2186017 , 3.0400124 , 3.050459  , 2.3971078 , 1.1501719 ,
       1.7934568 , 4.2160006 , 2.2424924 , 2.3882587 , 3.4857013 ,
       2.2735128 , 1.7272106 , 1.580607  , 2.8636258 , 2.7411718 ,
       3.3331032 , 4.1426425 , 2.9718037 , 1.4976877 , 3.7766922 ,
       7.4988675 , 1.8598236 , 1.7092621 , 3.0972593 , 4.0592284 ,
       1.5388751 , 2.7835314 , 3.194985  , 1.7617811 , 2.986967  ,
       2.037894  , 3.9299307 , 0.9754368 , 3.31672   , 1.4348248 ,
       3.3168743 , 0.7661678 , 3.8206213 , 1.6569717 , 2.5655105 ,
       1.9953128 , 1.8156886 , 2.315806  , 2.2455058 , 3.3632677 ,
       2.5807712 , 1.2182194 , 2.5631623 , 1.2564558 , 2.416356  ,
       5.0397735 , 3.7636552 ], dtype=float32), array([[[[ 0.03886708, -0.00917592,  0.02923558, ..., -0.04867212,
          -0.08463183,  0.00718184],
         [-0.02314217, -0.08083829,  0.0639079 , ...,  0.00381048,
           0.08848961, -0.00263235],
         [-0.0762834 , -0.03753077,  0.06324505, ...,  0.04414795,
           0.00277964, -0.01843559],
         ...,
         [-0.03738831, -0.03713575, -0.01595711, ..., -0.00478226,
          -0.04351696,  0.04905058],
         [-0.01627217,  0.01039741, -0.02989061, ...,  0.05314681,
          -0.07247779, -0.08551906],
         [-0.04762131,  0.07602857, -0.03352335, ...,  0.04570191,
           0.02964438,  0.04520353]]]], dtype=float32), array([-1.4451075e-02, -1.2761866e-02, -5.4316013e-03, -7.4520982e-03,
        1.5039743e-02,  8.4972382e-03, -1.4996789e-03,  2.2626502e-04,
       -2.3548841e-03,  1.5132460e-02,  5.6252312e-03,  5.7648285e-03,
       -1.1988066e-02, -1.1365685e-02, -4.9458654e-03, -2.8600713e-02,
        6.3423896e-03, -2.7146474e-03,  1.3145450e-02,  2.2332152e-02,
        6.3456642e-04, -5.9425062e-03, -1.4393494e-02, -1.0499298e-02,
        1.0097175e-02, -1.4422190e-02,  1.3803450e-02, -5.8151269e-03,
       -1.6665446e-02, -1.1442869e-02,  1.5950369e-02,  4.7450126e-03,
       -1.4082487e-03,  1.8745573e-03, -2.3073265e-03, -1.2185183e-02,
        1.1531789e-02,  2.0236121e-02,  4.1732183e-03, -1.4105955e-02,
        1.4744341e-02,  1.1553705e-03,  9.5056184e-03, -1.0897656e-02,
        2.0105124e-02,  2.8367590e-03,  2.0841202e-03,  6.8292175e-03,
       -9.6636321e-03, -1.0813244e-02, -3.9351392e-03,  8.7320628e-03,
       -4.3773516e-03, -1.4501225e-02, -4.4510860e-04, -1.3138551e-02,
        2.7875839e-02, -7.7485684e-03,  2.0023454e-02,  3.5714952e-03,
        8.3652511e-03, -1.8760735e-02, -3.0444632e-03, -4.8681716e-03,
       -1.7570043e-02,  1.9624878e-02, -1.8736763e-02,  9.0266922e-03,
       -9.3741398e-03, -1.1697601e-02, -9.8881507e-03,  7.3490888e-03,
        1.2263950e-02,  2.8020253e-03, -7.5805616e-03,  4.4723367e-03,
       -1.5926644e-02,  1.3269693e-02, -4.4886754e-03, -1.9371446e-02,
       -7.9863360e-03, -1.2189385e-03, -1.7036444e-02,  1.0933883e-02,
        5.8278581e-03, -9.4243241e-03, -4.7866837e-03,  6.7011933e-03,
        6.3050240e-03,  1.8154325e-02,  2.8965613e-03,  1.5089770e-02,
       -9.4954576e-03,  1.7694147e-02, -1.7671970e-03,  2.1340111e-02,
       -5.0755898e-03, -2.4705941e-03,  1.7136935e-04,  7.1660276e-03,
        3.5387822e-03, -9.7618559e-03, -6.0778456e-03,  4.3150592e-03,
        3.5986004e-03, -4.0760175e-03, -1.2504605e-02,  9.8481541e-03,
        7.4986126e-03, -2.5766983e-03, -4.5460877e-03, -7.7992566e-03,
       -1.1076270e-02,  8.2311323e-03, -7.9115974e-03,  1.4587034e-02,
        1.5266034e-02, -2.4749018e-02, -3.0756600e-03, -2.2338640e-02,
       -3.1168766e-03,  1.3183008e-02,  1.8084474e-02,  2.3503408e-02,
        1.7724027e-03, -4.3361305e-04, -5.5909194e-03,  1.9222689e-03,
       -8.1432154e-03, -1.8635910e-02, -1.0316071e-02,  2.0432556e-03,
       -8.8434201e-03, -1.7247651e-02,  3.0660356e-04,  8.2803266e-03,
       -2.2918654e-03,  2.3498941e-04,  6.9400715e-03,  6.6628554e-03,
       -4.1485382e-03, -7.4794232e-05,  4.2162258e-03,  4.7669555e-03,
       -7.7207061e-03,  9.6057774e-03,  1.5326217e-02, -1.4712557e-02,
        1.1273876e-02,  1.4171142e-02, -2.5756622e-04, -7.9081878e-03,
        1.2817470e-02, -3.6450934e-03,  1.8740110e-02,  5.1014712e-03,
       -1.6937139e-02,  2.4219409e-02,  4.7398037e-03,  1.8968105e-02],
      dtype=float32), array([-1.0192115 , -1.4720227 , -1.0656801 ,  0.90449136,  0.48454672,
       -0.35833657,  0.56332517, -0.33239824, -0.764407  , -0.2318866 ,
        0.9449144 ,  0.38244963,  0.10297175, -1.1302644 , -0.54007715,
       -0.08920191,  0.31299648, -0.42251655, -0.11529445,  1.0522879 ,
       -0.85165477, -0.43859926,  0.74856424,  0.46852005, -0.15559684,
        0.1049391 , -0.8854433 , -0.31487352,  0.86038977, -1.1181968 ,
       -0.8319164 ,  0.6550045 ,  0.30876052, -0.5844942 ,  0.6521254 ,
        0.95386255,  0.18483195, -0.84551555, -0.17338465,  0.7314047 ,
        0.77532274,  0.24619062,  0.08777305,  0.5773402 , -1.0371305 ,
       -0.3417015 ,  0.26771888, -0.5368451 ,  0.74171036,  0.56146336,
        0.87674946,  0.28105906, -0.05452586,  0.5474349 , -0.676225  ,
        0.5676461 , -0.11530412, -0.32305416, -0.4083713 , -0.69582677,
        0.4828456 , -0.5026253 , -0.0698633 ,  0.7631964 , -0.02161685,
       -0.8013334 , -0.5205014 ,  0.3257951 ,  0.3862972 , -0.35501832,
        0.3865965 , -0.15538876,  0.58567405,  0.714723  ,  0.15350631,
       -0.00321273, -1.1675316 , -0.6405776 ,  0.34238347, -0.58530253,
       -1.2747413 ,  0.63699657, -0.21678191,  0.7677963 , -1.2890794 ,
       -0.10233918,  0.48524112, -1.2662055 ,  0.5874264 , -0.40009302,
       -0.03541745,  1.0185925 ,  0.60219574, -0.8903316 ,  0.2474282 ,
        0.3556918 ,  0.62077665, -0.6056782 ,  0.21394052,  0.87363994,
        0.23023891, -0.15559788,  0.7199159 , -0.945991  ,  0.66287386,
       -0.31521297,  0.3322809 ,  0.05276241,  0.5479629 ,  0.08822833,
       -0.49568895, -0.5226533 , -1.0992454 ,  0.39987004, -0.0368727 ,
       -0.00743881, -0.669779  ,  0.7738832 , -0.7901664 ,  0.26774555,
        0.2688954 , -0.60574996,  0.8564736 , -0.94115084, -0.02254234,
        0.8445902 ,  1.5273465 , -1.3789878 , -0.26350224,  0.11826678,
        0.4216945 ,  0.24462296,  0.44519666, -0.31031576,  0.23838715,
       -0.13016672, -0.17738517,  0.5599093 , -0.35238272,  0.5043533 ,
       -1.5249768 , -0.096931  , -0.92268884, -0.32641828,  1.1663595 ,
        0.16835453, -0.51662886,  0.4897151 , -0.8310921 , -0.815404  ,
        0.2933374 , -0.47671106,  0.49352652,  0.8799199 , -0.55479836,
        0.83392644, -0.04636976, -0.27749202, -0.27638757, -0.9091981 ],
      dtype=float32), array([1.7270468 , 3.9652905 , 3.2173193 , 6.5932875 , 6.638334  ,
       2.4191136 , 2.6471236 , 2.4604628 , 6.0615315 , 1.9727235 ,
       2.175539  , 2.6417549 , 4.024194  , 2.6150053 , 2.4229307 ,
       2.070596  , 3.1932554 , 1.5459378 , 3.1593904 , 4.6822896 ,
       2.336657  , 2.6020765 , 2.552451  , 2.225064  , 1.088361  ,
       1.2407522 , 3.391313  , 1.3693343 , 2.3282537 , 2.5316682 ,
       3.0194404 , 3.223523  , 1.8589407 , 1.7725554 , 1.8275759 ,
       3.188454  , 2.356378  , 2.4757469 , 1.9595933 , 1.9758425 ,
       3.4195523 , 3.1781244 , 4.623414  , 2.2815626 , 3.3094015 ,
       2.1489818 , 2.1487122 , 1.4476031 , 2.446797  , 1.8306534 ,
       2.5489142 , 5.539235  , 2.4647226 , 1.8405265 , 1.8953533 ,
       2.6910212 , 5.1513114 , 3.0221868 , 2.289899  , 1.6221049 ,
       4.2588224 , 2.6466968 , 3.7288163 , 1.8270895 , 1.2863256 ,
       3.1403673 , 1.6640943 , 0.76799357, 2.0493135 , 0.67506164,
       2.7759788 , 2.1718192 , 3.2446418 , 5.9588103 , 2.886867  ,
       1.2390115 , 1.4594687 , 2.0792985 , 1.4831241 , 2.0867836 ,
       4.2368712 , 2.3577547 , 2.5552819 , 3.7328832 , 3.1839237 ,
       1.9113388 , 2.7407146 , 3.3752015 , 5.2606816 , 2.3236072 ,
       0.8775562 , 3.1757245 , 2.4234452 , 2.9131577 , 1.6726072 ,
       1.3259851 , 4.782583  , 3.200195  , 2.061868  , 4.120313  ,
       1.1238724 , 1.8550091 , 3.3539279 , 2.9913054 , 3.7997332 ,
       2.498905  , 4.187032  , 2.793312  , 4.164021  , 1.1769342 ,
       2.0539575 , 3.7826161 , 2.8159869 , 5.5690804 , 2.8620563 ,
       1.4853638 , 1.817253  , 1.8836873 , 2.8946073 , 2.1670678 ,
       3.6344495 , 2.2902951 , 4.8150725 , 3.561512  , 4.640732  ,
       2.5440037 , 3.1511762 , 2.578097  , 1.9976043 , 1.7977414 ,
       4.009296  , 1.8111562 , 1.1719438 , 3.042145  , 1.5035528 ,
       1.971824  , 2.289248  , 4.3284116 , 3.9420967 , 4.8672223 ,
       2.9452941 , 2.4804895 , 2.8732097 , 1.837105  , 3.4216483 ,
       4.021293  , 2.3900218 , 1.732097  , 2.3338788 , 2.0158484 ,
       1.9658431 , 1.0387135 , 6.294039  , 1.9347186 , 2.7614386 ,
       4.5308166 , 1.4084398 , 2.4053123 , 2.0557413 , 4.656886  ],
      dtype=float32), array([[[[ 0.0342986 ,  0.01301022,  0.04503172, ..., -0.03360617,
           0.03261555, -0.03002315],
         [-0.01804285,  0.00416036,  0.04318191, ...,  0.01250852,
           0.00926912, -0.01538557],
         [-0.00272179,  0.01471713, -0.01107759, ...,  0.03487872,
          -0.00229458,  0.02185931],
         ...,
         [ 0.03910449, -0.01748869,  0.006073  , ...,  0.03001548,
          -0.06217586, -0.04496983],
         [ 0.04527768,  0.02329655,  0.04342551, ...,  0.02559691,
           0.01574533, -0.03901864],
         [-0.0074941 , -0.04786812,  0.04266285, ..., -0.06595027,
          -0.00444811,  0.01992928]]],


       [[[ 0.0065646 ,  0.04556677, -0.02402477, ..., -0.00419279,
          -0.01205737, -0.01898113],
         [-0.02224074, -0.02309577, -0.05487256, ..., -0.00678228,
           0.00706798,  0.02575641],
         [-0.01643992,  0.0052516 ,  0.02386055, ..., -0.03034781,
          -0.03403493, -0.01047896],
         ...,
         [ 0.01711578,  0.02179548,  0.05342402, ..., -0.05088761,
           0.03828407,  0.02412527],
         [ 0.03188558,  0.00827269,  0.02197461, ...,  0.03405267,
           0.03887545,  0.00864788],
         [ 0.0515641 , -0.0483203 ,  0.00546226, ...,  0.03235795,
           0.02218276, -0.0161577 ]]],


       [[[-0.05149471, -0.012752  , -0.04021446, ...,  0.04814032,
           0.02135722,  0.03952988],
         [ 0.04657783, -0.0671339 ,  0.02660302, ..., -0.03920226,
           0.01548619,  0.03829816],
         [ 0.00592218,  0.03855228, -0.01394542, ..., -0.0162808 ,
           0.01179761,  0.04015304],
         ...,
         [ 0.00226513, -0.02791646,  0.00922485, ..., -0.00641202,
          -0.02731693, -0.0230328 ],
         [ 0.02072167, -0.00664196,  0.02896982, ..., -0.00709046,
           0.00275661,  0.03302884],
         [ 0.04403351, -0.02639451,  0.02221551, ...,  0.03983033,
          -0.00191332, -0.02346519]]],


       ...,


       [[[ 0.01804349, -0.03396792, -0.0355147 , ..., -0.02545686,
           0.04058415,  0.03336077],
         [-0.00964804, -0.00317315, -0.01264212, ..., -0.00246621,
           0.04915032, -0.0011687 ],
         [-0.0351298 , -0.00672947, -0.0191442 , ...,  0.00969864,
           0.00328343,  0.04198696],
         ...,
         [ 0.00238394, -0.00590531,  0.01838037, ...,  0.0356511 ,
           0.00226032, -0.04231462],
         [-0.02712308, -0.047817  ,  0.05509888, ..., -0.03214245,
           0.01241585,  0.02219343],
         [ 0.0437285 , -0.00759004,  0.00397655, ..., -0.02063411,
           0.04717275,  0.0265791 ]]],


       [[[-0.03566614, -0.04367702, -0.01054375, ...,  0.01619929,
           0.02595495, -0.03662011],
         [ 0.02827144,  0.03634834,  0.01569326, ..., -0.05467974,
           0.00790721,  0.03420008],
         [ 0.02332733,  0.01736455, -0.0359332 , ...,  0.02924058,
          -0.0411212 ,  0.00768196],
         ...,
         [ 0.05990144,  0.00737569, -0.04235033, ...,  0.02516648,
           0.03719899,  0.003512  ],
         [-0.01254517, -0.02357008,  0.03360565, ...,  0.01231856,
          -0.03099981,  0.01251958],
         [ 0.05273798, -0.00840687, -0.00536005, ...,  0.03407604,
           0.01499157, -0.00797569]]],


       [[[-0.03123392,  0.02546055,  0.04784349, ...,  0.04933975,
          -0.0180424 , -0.01789944],
         [-0.02783442, -0.04737989, -0.00930405, ..., -0.05812518,
           0.02744935,  0.01217409],
         [-0.02481124,  0.01091663, -0.03559934, ..., -0.01293223,
          -0.05338065, -0.03717813],
         ...,
         [-0.03776265,  0.05424844,  0.03820609, ..., -0.01822316,
           0.00323859,  0.01923875],
         [-0.02463843, -0.03617919, -0.04772584, ...,  0.02238328,
           0.01307914,  0.038971  ],
         [-0.02082825, -0.059645  ,  0.04341597, ...,  0.02870555,
           0.01730168, -0.05805181]]]], dtype=float32), array([ 2.06877086e-02, -2.63992581e-03, -3.75128654e-03, -5.63165173e-03,
        8.36838968e-03, -4.76645492e-03, -1.26439268e-02,  9.37474333e-03,
       -4.52474633e-05,  7.07481013e-05,  1.62306037e-02, -1.66057032e-02,
        3.05630593e-03, -4.79814503e-03,  2.88258679e-03,  1.08027749e-03,
        1.10734981e-02,  8.56647547e-03,  5.33538638e-03,  3.53228115e-03,
       -1.82390045e-02,  1.49839632e-02,  2.97966006e-04,  5.29928273e-03,
       -8.70972406e-03,  2.48202845e-03,  2.14702860e-02, -1.12844666e-03,
       -1.20882527e-03,  1.98938046e-02, -4.86135436e-03,  1.22926349e-03,
       -9.07278899e-03,  1.09603368e-02, -5.15811669e-04,  3.93831450e-03,
        5.62322745e-03,  1.22027546e-02,  1.69392433e-02,  9.51409154e-03,
       -1.39605692e-02, -1.94163865e-03, -6.45339314e-05, -3.59260268e-03,
        1.32932682e-02,  2.23734193e-02,  4.63972305e-04,  1.21392624e-03,
        1.08183268e-02,  6.75089471e-03, -2.74408085e-04, -8.92760046e-03,
       -9.33503173e-03, -2.61987261e-02, -2.61269254e-03,  1.18939476e-02,
       -9.30067245e-03, -1.21246465e-02, -7.24565517e-03, -7.28419935e-03,
       -8.92918929e-03,  1.18836307e-03,  2.29524635e-02, -3.07426881e-02,
       -1.30794328e-02,  9.85306408e-03,  1.06621585e-04,  1.89191345e-02,
       -1.69577785e-02, -6.30889460e-03, -5.14645246e-04,  7.91392941e-03,
       -7.09344214e-03, -1.83332972e-02, -4.97250119e-03, -2.63159367e-04,
       -1.64810829e-02, -3.61075066e-03,  1.83106475e-02, -2.76397215e-03,
       -6.49210066e-03,  7.10133044e-03, -3.02709872e-04, -4.57591232e-04,
       -1.20704425e-02, -1.99000295e-02,  1.29866283e-02,  2.08119936e-02,
       -2.77751940e-03,  1.05357207e-02, -1.10127898e-02,  1.65397697e-03,
        6.78268773e-03,  8.92679393e-03,  2.86333244e-02, -1.82948299e-02,
        2.94078421e-03, -1.04353484e-02, -7.60322204e-03,  9.20914859e-03,
       -5.91313094e-03,  9.05690901e-03, -9.19224054e-04,  1.47159351e-02,
       -7.27119204e-03,  8.26431531e-03,  8.18280783e-03, -7.14852614e-03,
        7.51679996e-03,  1.97019204e-02,  1.26379533e-02, -3.72246187e-03,
       -1.69839133e-02,  8.43295455e-03, -3.98087595e-03,  1.46305759e-03,
       -2.04953155e-03,  6.88711088e-03,  2.49183662e-02, -2.96794763e-03,
        6.28321199e-03,  1.17408121e-02,  1.61903910e-02,  8.41935445e-03,
       -2.08524801e-03, -1.31165925e-02,  1.26264747e-02,  1.61258560e-02,
       -5.52497385e-03, -9.92180780e-03, -6.96027791e-03,  1.71822049e-02,
        3.41559853e-03,  7.65713630e-03, -1.15259690e-02, -8.17100052e-03,
        4.79023857e-03,  9.01707727e-03,  1.06487824e-02,  8.30159616e-03,
       -6.03262859e-04, -9.99081973e-03,  2.54200529e-02, -1.04947332e-02,
       -7.62651442e-03, -1.30118232e-03,  1.49217190e-03,  5.34181483e-04,
        1.39384083e-02,  5.91506774e-04,  7.46936304e-03, -1.37338405e-02,
        2.07237322e-02, -8.11933656e-04, -4.55375150e-04,  6.12410065e-03,
        7.93095678e-03, -8.05207156e-03, -4.51380759e-03,  2.08803602e-02],
      dtype=float32), array([-0.56174517,  1.1456004 ,  0.47534874,  0.7564624 , -0.5000375 ,
        0.8865119 ,  0.48881274,  0.00591442, -0.73629004,  0.33488563,
        1.2795504 ,  0.8466116 ,  0.9676254 , -0.37026384,  0.71047974,
        0.7677162 , -0.7885503 , -0.43658745, -0.7633438 ,  0.4076305 ,
       -0.9831266 ,  0.45027667, -0.3225077 ,  0.00585092,  1.0709754 ,
       -0.5621369 , -0.5814542 ,  1.1501691 ,  1.016914  ,  0.08512352,
        0.54375553,  1.0033629 ,  1.2255723 ,  0.54035705, -1.3800913 ,
        1.4921893 , -0.519627  , -1.1432577 , -0.8602276 , -0.4482342 ,
        0.1920588 , -0.6159024 ,  0.04008745,  0.0903078 ,  0.40034986,
        1.0429854 ,  1.4278979 ,  0.21661538,  1.0333399 , -0.9186343 ,
        1.1669395 , -0.5652665 , -0.9878363 ,  0.5046935 , -0.91153336,
        0.6841733 ,  1.1518445 , -0.9429454 ,  0.41904697, -0.18409126,
        1.3636645 ,  0.54101163,  0.9622368 , -0.35851967, -0.24656062,
       -0.08706423,  0.22047675,  0.9418269 , -1.106028  ,  0.2473513 ,
        0.71748084,  0.3900452 , -1.5084451 ,  0.08619986,  0.20156758,
       -1.0308905 ,  0.7788785 ,  0.23729464,  0.31552845,  0.47227585,
        0.47038794,  0.3339059 , -0.49574396, -0.44065726,  1.2501335 ,
       -0.74719626, -0.52270657,  0.478945  ,  0.77981496,  0.05439672,
       -0.55955994,  0.60337454,  0.3622373 ,  1.2163893 , -1.4342742 ,
        0.94461036, -1.0028899 , -1.4610242 ,  0.9964732 , -0.6388008 ,
        0.957068  , -0.5100254 ,  0.84085315, -1.0403129 , -0.26476806,
        1.2326634 , -1.1060231 ,  0.40057278,  1.0050453 ,  0.93827647,
        0.3889819 , -0.8294887 ,  0.38507387, -1.1430453 ,  1.0496064 ,
        0.14426658, -0.9101985 ,  1.1798589 ,  0.5508075 , -1.313286  ,
       -1.2359784 , -1.2134417 , -1.2771351 ,  0.65665966, -1.0143789 ,
        1.0054754 ,  0.4069307 , -0.92552316, -1.5999346 , -0.7468465 ,
       -0.74568725, -0.4795832 ,  0.76483965,  0.5410669 ,  0.02441609,
       -0.8500045 , -0.82053673,  1.402546  ,  0.4445697 ,  0.84646904,
       -1.1904773 , -0.63482755,  1.0608217 ,  0.09922853,  0.821385  ,
        1.2034068 ,  0.41070825, -0.7154106 , -0.9292639 ,  1.1563987 ,
       -1.0947481 ,  0.5562238 , -1.2045611 , -0.24685293, -0.7594711 ,
        0.48622593,  0.7255203 , -0.59420305,  0.34172243, -1.5567219 ],
      dtype=float32), array([ 3.0166988 ,  7.663916  ,  6.8996363 ,  5.7483854 ,  1.9820054 ,
        2.8679943 ,  1.5014422 ,  5.052879  ,  2.9048793 ,  4.7964826 ,
        6.6769814 ,  9.285389  ,  4.496676  ,  1.6100379 ,  5.387755  ,
        5.9851604 ,  1.6677027 ,  5.260604  ,  3.812205  ,  6.058766  ,
        4.975818  ,  2.9912477 ,  3.1353667 ,  1.7025837 ,  3.2940383 ,
        3.11815   ,  5.062871  ,  5.17231   ,  3.7081895 ,  2.2578225 ,
        9.506619  ,  6.428384  ,  6.5147586 ,  1.5212929 ,  4.5709095 ,
        5.676623  ,  0.975952  ,  8.593666  ,  2.5624795 ,  3.3327289 ,
        2.1067085 ,  2.9448225 ,  1.8623724 ,  5.3081474 ,  3.5592275 ,
        6.880351  ,  6.2818155 ,  6.202053  ,  7.7545805 ,  0.98620635,
        6.3925505 ,  1.8886926 ,  2.814098  ,  4.384769  ,  1.8205624 ,
        4.332993  ,  8.57988   ,  3.85638   ,  5.511608  ,  2.6400082 ,
        8.079151  ,  5.121479  , 10.220345  ,  1.7540294 ,  0.8374485 ,
        2.6421    ,  5.903467  ,  5.5556483 ,  3.9586549 ,  3.9974325 ,
        3.3511121 ,  4.129317  ,  5.702959  ,  6.895508  ,  5.770804  ,
        1.3645322 ,  5.958871  ,  6.541441  ,  5.089231  ,  5.0411725 ,
        1.8369448 ,  3.7871382 ,  1.7336752 ,  1.9416673 ,  3.9800596 ,
        3.4291377 ,  2.0460799 ,  7.068447  ,  4.78518   ,  3.3905036 ,
        1.4750906 ,  8.5491085 ,  1.5352288 ,  7.446967  ,  4.4544683 ,
        2.0913846 ,  3.4673033 ,  3.56491   ,  7.38858   ,  4.2866163 ,
        6.22781   ,  1.7876511 ,  2.4276555 ,  3.7290618 ,  1.3687167 ,
        4.365121  ,  2.2327588 ,  8.057676  ,  5.253447  ,  8.196392  ,
        1.2817982 ,  3.7865999 ,  1.9007543 ,  6.135438  ,  1.9726467 ,
        1.1768997 ,  5.4965367 ,  6.6857657 ,  6.605243  ,  3.5754538 ,
        3.9750402 ,  5.9480467 ,  7.058522  ,  4.0623875 ,  2.6727197 ,
        5.213412  ,  5.520119  ,  9.186181  ,  4.3598924 ,  5.139273  ,
        3.1532972 ,  6.895841  ,  5.7043815 ,  4.363074  ,  1.3842046 ,
        1.2101809 ,  3.515719  ,  3.7712219 ,  6.4319844 ,  4.7672005 ,
        1.8111353 ,  2.0378249 ,  6.469099  ,  1.4140455 ,  2.1738806 ,
        8.94709   ,  1.6929321 ,  2.9220774 ,  3.5137603 ,  4.548725  ,
        2.5759957 ,  7.3664336 ,  4.420882  ,  2.1927664 ,  2.8823524 ,
        5.998334  ,  6.204817  ,  0.7465082 ,  3.3645215 ,  6.945886  ],
      dtype=float32), array([[[[ 0.05699546,  0.02031588, -0.01816806, ..., -0.00844843,
          -0.00230231,  0.01748927],
         [ 0.03549926,  0.04368636, -0.0745244 , ..., -0.0444271 ,
           0.00615296,  0.03911519],
         [-0.00921618,  0.07178556,  0.01661903, ..., -0.00090726,
           0.03923252,  0.0037059 ],
         ...,
         [ 0.00858057,  0.09092443,  0.08023573, ..., -0.06640933,
          -0.0343621 , -0.02011304],
         [ 0.05442087, -0.06178015,  0.08723973, ..., -0.06073514,
          -0.06280301,  0.03800078],
         [-0.04634989, -0.00998103, -0.00367951, ...,  0.03009195,
          -0.05593806, -0.04809244]]]], dtype=float32), array([[[[ 0.04597682,  0.03188054,  0.03907704, ...,  0.04674653,
          -0.04182455,  0.02882648],
         [-0.00742618, -0.03258817,  0.0194006 , ...,  0.05386937,
           0.02191741,  0.00296928],
         [-0.00992016, -0.02122312,  0.0006503 , ...,  0.03363421,
          -0.04515987, -0.04967405],
         ...,
         [ 0.03141611, -0.02031298,  0.01013077, ..., -0.00399518,
          -0.02564695,  0.01016049],
         [-0.05105017,  0.0467624 , -0.02551796, ...,  0.01207694,
          -0.05343736, -0.01329481],
         [ 0.0406187 , -0.03454267, -0.00732593, ..., -0.03610149,
          -0.00674725, -0.04013029]],

        [[ 0.0005991 , -0.00883008,  0.03141274, ...,  0.02534535,
          -0.02661309, -0.03454394],
         [-0.0389937 ,  0.02450565, -0.04134074, ...,  0.01264325,
          -0.00671772,  0.02346101],
         [ 0.03566416, -0.02833678, -0.01755598, ..., -0.03100009,
           0.0191166 , -0.0318021 ],
         ...,
         [-0.0222124 ,  0.06004844, -0.00746579, ...,  0.02062875,
          -0.05963591,  0.00056198],
         [ 0.0084624 ,  0.03746421, -0.02572647, ..., -0.01253948,
          -0.02540509, -0.01938343],
         [ 0.03827768, -0.0231792 ,  0.03830614, ..., -0.03934602,
          -0.05148903,  0.05316088]],

        [[-0.0370186 , -0.0080929 , -0.00264026, ...,  0.02558786,
           0.04767907, -0.01677932],
         [ 0.00941538,  0.04834895,  0.02481848, ...,  0.03654433,
          -0.06219938,  0.05212404],
         [ 0.01136588,  0.01446811, -0.02733912, ..., -0.01966042,
          -0.04798044, -0.02959008],
         ...,
         [-0.03569056,  0.02228178, -0.00154047, ...,  0.02496641,
           0.03798521, -0.03348923],
         [-0.01524032, -0.01110052,  0.038995  , ..., -0.04687047,
          -0.01922816, -0.02710592],
         [ 0.04842256,  0.02373037, -0.03144823, ..., -0.02536385,
           0.01786759, -0.04381535]],

        ...,

        [[-0.05596913, -0.04119473,  0.00118494, ..., -0.00418731,
           0.02312967, -0.03943209],
         [-0.02918236, -0.04495565, -0.01548072, ...,  0.01916282,
           0.00136293,  0.01378603],
         [-0.01618841,  0.01833139,  0.0135517 , ..., -0.03325861,
           0.02242756, -0.01707773],
         ...,
         [-0.02121915, -0.02201607, -0.02304021, ...,  0.04325698,
          -0.03296905,  0.00259192],
         [ 0.03619629,  0.04295452, -0.02091736, ...,  0.04744479,
          -0.03268161,  0.06601628],
         [ 0.02788404,  0.00978624, -0.047358  , ..., -0.02503002,
           0.01732803, -0.04278271]],

        [[-0.02692409, -0.00554269,  0.01132814, ...,  0.00659549,
           0.03968868,  0.0210361 ],
         [-0.00510578,  0.04480475,  0.02828366, ...,  0.01063074,
          -0.02863355, -0.03401477],
         [-0.01531883, -0.03122927, -0.02205141, ...,  0.01621117,
           0.04050146, -0.02653101],
         ...,
         [-0.0260854 ,  0.05780646, -0.00540444, ..., -0.01206543,
          -0.0548057 , -0.0194094 ],
         [-0.0410246 , -0.0048816 , -0.00018433, ..., -0.02443929,
          -0.06139316,  0.04143238],
         [-0.03962782,  0.0189718 ,  0.02325004, ...,  0.02170706,
          -0.01221431, -0.05828404]],

        [[-0.02566449, -0.0097728 ,  0.01722376, ..., -0.03257586,
           0.06474742, -0.05392868],
         [ 0.02059442, -0.01268023,  0.00159566, ..., -0.00293419,
          -0.01492422, -0.02826622],
         [ 0.00340929, -0.05778962, -0.00324316, ..., -0.01388784,
          -0.03986535,  0.03998686],
         ...,
         [ 0.00491794, -0.00544394,  0.030646  , ...,  0.00628965,
          -0.03346165, -0.03492893],
         [-0.02655845, -0.04382583, -0.03660371, ...,  0.01033151,
          -0.00535542,  0.01915146],
         [ 0.03017229,  0.03052727,  0.04802695, ...,  0.0068791 ,
          -0.00969407,  0.00860687]]]], dtype=float32), array([ 0.00020338, -0.00266663,  0.0153113 ,  0.01613534,  0.00726633,
       -0.01037043, -0.00347242,  0.02589691, -0.01438591, -0.01494074,
        0.00103409,  0.02562281, -0.017232  ,  0.01629225, -0.01604212,
       -0.00524522, -0.0075873 ,  0.00911771, -0.00679773,  0.00962667,
       -0.00403884,  0.00108991,  0.00041682, -0.00441891,  0.00313209,
       -0.00497671,  0.00874811, -0.01210955, -0.02021649, -0.01710105,
        0.01681197, -0.01688318, -0.0112285 , -0.01689022, -0.00374061,
       -0.02211201, -0.01069151,  0.0010558 , -0.00856525, -0.00170535,
       -0.01421068, -0.01223306, -0.00466842, -0.00774478, -0.02078503,
       -0.0015263 , -0.0139328 , -0.00114418,  0.00789558, -0.02770425,
        0.00920912, -0.01101248, -0.02514437,  0.01304851, -0.00873626,
       -0.00296898,  0.01274876, -0.0031868 , -0.00066605,  0.00276021,
        0.00470528,  0.00683152,  0.01643271,  0.01489167, -0.02396497,
       -0.02090088, -0.00924767, -0.00658404, -0.01113496, -0.00243741,
       -0.018863  ,  0.0122408 , -0.02324872, -0.0102244 ,  0.02307543,
        0.00071165,  0.01625336,  0.01256712, -0.01169349, -0.0217032 ,
       -0.01774933, -0.00383319, -0.01456544, -0.0198881 ,  0.00383114,
        0.0130516 , -0.01954002, -0.00155046, -0.014362  ,  0.00446467,
       -0.02063424, -0.00396571, -0.01542849, -0.00492092,  0.02628061,
       -0.00662945, -0.00662695, -0.01939445, -0.01334519,  0.0068481 ,
       -0.01863735, -0.00433867,  0.00545142,  0.00571837, -0.01154092,
       -0.00098463,  0.01181839, -0.00473486,  0.00398935,  0.00487379,
        0.00474967, -0.01163757, -0.00272842, -0.00942069,  0.01782863,
        0.00841772,  0.00940751, -0.01461429, -0.02349618,  0.00545116,
       -0.00301227, -0.02864066, -0.00651866, -0.01761244,  0.01193606,
        0.00282079, -0.03138942, -0.00109438, -0.00985261,  0.01818431,
       -0.01411138,  0.01022373,  0.00914284, -0.01678048, -0.0121078 ,
       -0.02482856,  0.01386906, -0.0093089 , -0.01321913, -0.01001918,
       -0.0100636 ,  0.00582603,  0.01549727, -0.00020609, -0.01555924,
       -0.00324557, -0.00500044, -0.01329063, -0.00580199, -0.01568392,
       -0.00045076,  0.00698721, -0.00081662, -0.0196486 ,  0.00567767,
       -0.01635641, -0.0096265 , -0.00672125, -0.00668121, -0.01048061],
      dtype=float32), array([ 7.57939458e-01,  4.60242927e-01,  9.53397274e-01, -6.75858736e-01,
        2.14017093e-01,  1.25668272e-02, -4.74935055e-01, -2.84493804e-01,
        1.70983660e+00, -3.21780562e-01,  9.15431082e-01, -3.05163592e-01,
       -1.45336199e+00, -1.09164858e+00, -1.26380956e+00,  9.07593012e-01,
       -6.68975532e-01, -7.23628759e-01,  3.20465714e-01, -3.69659305e-01,
       -1.23262858e+00, -6.70355931e-02, -7.86192417e-01, -1.06945789e+00,
       -2.50820488e-01, -1.10248172e+00, -1.73197672e-01, -3.82148534e-01,
        1.14677876e-01,  4.91017818e-01,  3.11171502e-01, -8.43198717e-01,
        3.87853056e-01,  4.67844129e-01, -3.41341019e-01, -5.84779441e-01,
       -3.03152055e-01, -1.82589620e-01,  4.03819680e-01,  4.25603777e-01,
       -7.64293969e-01,  1.11204171e+00, -2.89895982e-01, -5.19353449e-01,
        7.07308948e-01, -2.99022138e-01,  1.18456507e+00, -4.28904772e-01,
       -8.85071039e-01,  5.73788285e-01, -2.13798285e-01,  1.07432759e+00,
       -1.15151584e-01, -2.16053233e-01,  1.66301817e-01, -3.92864943e-02,
        3.08086067e-01,  6.88321531e-01,  1.44466087e-01, -4.80655357e-02,
       -4.93690968e-01, -2.86817729e-01,  2.47971758e-01, -3.33037019e-01,
        7.30355680e-01,  2.30331600e-01, -1.23177803e+00, -3.12046725e-02,
       -1.55123860e-01, -1.82655796e-01,  1.00181341e+00, -9.07178447e-02,
        1.32594869e-01,  5.50389767e-01, -9.39076990e-02,  2.20252410e-01,
       -1.85226128e-01, -8.42932284e-01,  1.55823082e-01,  4.35991049e-01,
        3.41422483e-02,  5.14925480e-01, -1.62716544e+00, -1.36898220e-01,
        3.39337252e-02, -4.42575291e-03,  1.53537214e+00, -2.07661852e-01,
        1.81774899e-01,  6.81594908e-01,  1.02011824e+00,  5.69428444e-01,
        4.42272127e-01, -1.67849690e-01,  3.78519803e-01, -7.99897075e-01,
       -1.17687523e+00,  2.78286099e-01, -9.92563546e-01, -2.78383523e-01,
        2.25530222e-01,  7.47739077e-01, -8.02795053e-01,  1.05219580e-01,
        4.69397008e-01, -2.88696319e-01, -1.14871979e+00, -5.10722101e-01,
        3.90988171e-01, -7.36204624e-01,  4.20362622e-01,  4.75698039e-02,
       -3.66257466e-02, -6.30135238e-01, -7.99274147e-01, -7.72336543e-01,
       -6.13687813e-01, -7.69372940e-01, -9.73947585e-01, -2.02802449e-01,
       -1.39624977e+00, -3.54183406e-01,  4.52068269e-01,  8.82315695e-01,
       -1.54093489e-01,  8.45935524e-01,  9.25805718e-02,  5.08813202e-01,
        3.65247466e-02, -4.36118513e-01,  2.67656054e-02, -9.60093379e-01,
        1.79236040e-01, -1.08682871e+00,  6.05371773e-01, -1.90202281e-01,
       -1.16867699e-01,  3.41847181e-01,  1.71545208e-01, -8.49958360e-01,
        6.62707567e-01,  1.02188623e+00,  3.70269845e-04, -4.29867685e-01,
        6.60811424e-01,  1.95185795e-01,  8.37231338e-01,  4.28236693e-01,
       -3.37641221e-03, -6.20455384e-01, -7.44636655e-01,  4.59402800e-01,
       -5.87483108e-01,  8.33701566e-02, -6.80195332e-01,  4.56212252e-01,
       -1.25007975e+00,  1.33999097e+00,  8.80950272e-01,  5.73190510e-01],
      dtype=float32), array([3.3832848 , 3.2603588 , 4.782441  , 3.9656985 , 3.6926808 ,
       1.8376634 , 3.1493297 , 3.3950758 , 5.181505  , 4.246184  ,
       7.4160247 , 2.2094862 , 2.0428562 , 4.4165726 , 3.9898622 ,
       2.5260253 , 2.5279634 , 2.1421552 , 2.7677908 , 3.9196846 ,
       5.6544957 , 1.3211263 , 5.32701   , 2.7899284 , 3.3467221 ,
       3.186802  , 3.798977  , 3.4156792 , 3.7810888 , 2.3055048 ,
       2.0388925 , 2.117664  , 3.1650615 , 2.183205  , 4.11643   ,
       4.628763  , 2.6514945 , 1.925596  , 5.148942  , 2.1984787 ,
       4.8007016 , 5.1723585 , 2.487533  , 2.7313156 , 3.3015442 ,
       2.940525  , 5.457188  , 2.057646  , 5.2239714 , 6.2750497 ,
       1.8648548 , 2.4934518 , 2.8904347 , 4.6041484 , 2.47543   ,
       1.6900598 , 1.6556066 , 3.29799   , 1.581695  , 0.9574533 ,
       3.4672194 , 1.8633478 , 4.3275037 , 2.381648  , 1.7677896 ,
       4.5508165 , 0.96426266, 1.3490568 , 1.2918998 , 3.0958946 ,
       2.3292694 , 1.7188449 , 2.9811118 , 3.2135766 , 3.8787458 ,
       3.2003417 , 2.7117355 , 2.8602643 , 2.560964  , 1.0895673 ,
       3.0738063 , 1.9484429 , 2.6989198 , 2.7117305 , 2.8399343 ,
       4.850554  , 6.5212827 , 2.2154763 , 1.142289  , 4.32758   ,
       2.1117442 , 4.8171697 , 2.884352  , 1.4461578 , 1.3932017 ,
       1.5621235 , 3.020426  , 2.070831  , 3.0086672 , 3.9471996 ,
       2.7902489 , 6.351117  , 4.0294275 , 4.9014797 , 4.009751  ,
       1.6435214 , 1.7520362 , 2.7762816 , 3.3904247 , 2.5557532 ,
       4.9196277 , 2.1638129 , 3.7705822 , 1.3293301 , 8.239196  ,
       1.8085166 , 4.150181  , 4.393936  , 3.261174  , 5.1272187 ,
       2.8760808 , 0.9846588 , 2.7551343 , 3.2098222 , 5.2258053 ,
       5.1880345 , 3.6651728 , 2.6420028 , 2.4955432 , 4.1885815 ,
       2.4145052 , 5.8840537 , 2.820355  , 4.48353   , 2.893202  ,
       1.7028414 , 4.033381  , 1.2424809 , 4.9588203 , 1.3962622 ,
       2.5104635 , 7.3099585 , 4.199038  , 2.616613  , 4.495725  ,
       1.1368579 , 3.261305  , 5.634006  , 1.5928925 , 3.6898465 ,
       2.4950323 , 2.82963   , 1.4593213 , 4.795665  , 2.7036242 ,
       1.3334588 , 6.0466485 , 2.4126782 , 2.5778987 , 2.873164  ],
      dtype=float32), array([ 0.00368242,  0.0096889 , -0.01861711, -0.01281636, -0.00664372,
       -0.00978144, -0.01853136,  0.0132093 , -0.02525589, -0.0043003 ,
        0.00415097, -0.00850739, -0.00401884,  0.00219899, -0.00128878,
       -0.01479698, -0.01776164, -0.01132303, -0.02463087, -0.0027632 ,
        0.00685789, -0.00597769,  0.02137142, -0.00821911, -0.00214279,
       -0.00653831,  0.00164728, -0.01114574, -0.00267979, -0.01545001,
       -0.00876083, -0.00541148, -0.0114762 ,  0.00151767,  0.00372224,
       -0.02306948, -0.01015366,  0.00854275,  0.01599252,  0.00228046,
       -0.00239495, -0.00500242,  0.00156737, -0.02259098, -0.01088254,
        0.00965185,  0.00070123, -0.00526825,  0.00823688,  0.00246447,
        0.00555791,  0.00371119, -0.01380276,  0.00628284,  0.00641703,
        0.01002517,  0.0091097 , -0.00089842, -0.00038553, -0.00587417,
        0.00096   , -0.01231532, -0.00072259, -0.00598618, -0.01087903,
       -0.01203493,  0.00577829,  0.00192064,  0.01512882, -0.00016552,
       -0.0023101 ,  0.01124018, -0.01359364,  0.00945302,  0.01317295,
       -0.01977626, -0.00853457, -0.00313336, -0.00963234, -0.00851963,
       -0.01344684, -0.0059216 , -0.00759977,  0.02880991, -0.00974024,
       -0.00082135,  0.01362187,  0.01026339, -0.00103603,  0.00336277,
       -0.0027447 , -0.00079186, -0.0059036 , -0.01956468, -0.00235428,
       -0.01896431, -0.02514344, -0.00890094, -0.00019253, -0.00295502,
       -0.00868013, -0.0019034 , -0.00418538,  0.0090902 , -0.02893029,
       -0.00255988,  0.00618242, -0.01247445, -0.00268384,  0.02143203,
        0.00563983,  0.0158845 , -0.00631624,  0.02461576, -0.0063194 ,
       -0.02604555,  0.0057191 , -0.00783425, -0.00988591, -0.02081094,
       -0.00823029, -0.00712891, -0.0005529 ,  0.00962675, -0.00446782,
        0.00963954,  0.00314955, -0.02660336, -0.00147856, -0.01583264,
        0.00072431,  0.00670624, -0.00994242, -0.00123927, -0.00407057,
        0.0086552 ,  0.01378503,  0.00487405,  0.01227998,  0.0129667 ,
        0.00431092, -0.00769953,  0.00253845, -0.00456989,  0.01100037,
       -0.00419419, -0.01734949,  0.00735396, -0.00316602,  0.0036706 ,
        0.01189507,  0.02596827,  0.00685118, -0.00540074, -0.00798709,
       -0.00199453, -0.00527598, -0.01200539, -0.01001319, -0.00774273],
      dtype=float32), array([-0.73757106, -1.1450427 ,  0.4869104 , -0.52524376,  1.2262528 ,
       -0.8593146 , -0.65611595,  0.5881418 ,  0.90658885,  0.8651855 ,
       -0.3793672 , -0.8775568 ,  0.778152  ,  0.8153118 , -0.934548  ,
        1.0036801 ,  0.39761233,  0.44096115, -0.53481466,  0.19480005,
        0.49191973,  0.52341664, -0.92174375, -0.90281844, -0.44546923,
        1.3264929 ,  1.012106  ,  0.6079532 , -0.4863941 , -0.6412062 ,
       -0.539705  ,  1.2511709 ,  0.7731934 ,  0.58691275, -1.0545404 ,
        1.1060501 , -1.284714  , -0.45663112,  1.2120768 , -0.5266766 ,
        0.92446786, -1.4613773 ,  0.82694787, -1.4419631 ,  0.52547336,
        0.10214625,  0.63872135, -1.3139434 ,  1.2822542 , -0.8509325 ,
       -0.9068585 , -0.05140197, -0.528463  , -1.4779619 , -0.8482508 ,
        0.8016854 , -0.83036363, -1.2462548 , -1.3657607 ,  1.2023923 ,
       -1.5069412 ,  1.1758732 ,  0.5513654 , -0.45434785,  0.88510054,
        0.15292683, -0.5010045 ,  0.6991409 , -0.9519356 , -0.9862947 ,
        0.9806672 ,  0.13569081,  0.8823431 , -0.9522993 , -1.3132086 ,
       -0.93980294,  0.83053756, -1.1871227 , -0.7714191 , -0.15865321,
       -0.5745008 ,  0.6265779 ,  0.2771375 , -1.5272568 ,  1.1073933 ,
        0.5548865 ,  0.50710505, -0.98533   , -0.7207589 ,  0.46877414,
       -1.1087205 ,  0.7089855 , -0.67957693, -1.2616992 , -1.2026922 ,
        0.13705865, -1.1688849 , -0.36188537,  0.72453564,  0.66084254,
       -0.90298516, -0.34667853, -0.23825465, -0.95311636, -1.0563987 ,
       -1.5961789 , -0.94504035, -0.7724534 , -0.11332076, -0.32784265,
        0.71446824,  0.8824172 ,  1.1661528 , -0.8163244 ,  1.2635041 ,
       -0.62883866, -0.5152967 ,  0.41942915, -0.7762451 , -0.12416168,
       -1.3204755 , -1.0482996 ,  1.0878029 , -1.6003885 ,  0.3612893 ,
        1.1004847 , -1.543291  , -0.52522904,  1.200661  , -1.0579722 ,
       -0.3802584 , -0.7461108 , -0.89021343, -0.76180404,  0.6046186 ,
        1.0734671 , -0.59977716, -0.89291614, -0.36112764,  0.56767863,
       -1.2958015 , -0.41568437,  1.3228353 ,  1.376864  ,  0.7137076 ,
       -1.0429269 , -0.5012277 , -0.6878596 , -1.4044474 ,  0.68801963,
        0.51430565,  0.47710398, -0.48199582,  1.0332325 ,  1.3512352 ,
       -0.88257784,  0.91370696,  1.0839195 ,  0.05152126,  1.3542929 ],
      dtype=float32), array([ 3.3403983,  2.3671396,  7.0870366,  5.370162 , 13.070526 ,
        2.3061433,  1.9014018,  5.279119 , 10.618002 ,  7.919834 ,
        3.9642556,  6.0557094,  9.383099 ,  8.784086 ,  4.0035024,
        9.508995 ,  5.328247 ,  5.457555 ,  2.7042215,  2.2097292,
        5.148741 ,  8.055093 ,  7.141684 ,  4.751995 ,  4.0838413,
        9.6250515,  8.673896 ,  2.744244 ,  5.985699 ,  5.7980547,
        3.1875472, 11.548807 ,  4.456528 ,  3.917129 ,  4.509257 ,
       13.581238 ,  7.498811 ,  3.8654675,  8.9742365,  5.0158253,
        7.8473954,  3.7380934,  8.275878 ,  9.24262  ,  4.599812 ,
        2.7310255,  5.575207 ,  6.922575 , 11.144243 ,  3.8844018,
        7.4594054,  4.1739116,  2.4386382,  7.288942 ,  5.6452785,
        9.444516 ,  6.092603 ,  8.269545 ,  6.1925387,  6.8968716,
        3.9505136, 13.590347 ,  6.9724326,  1.5768408,  9.310196 ,
        4.145318 ,  3.590607 , 11.259624 ,  6.47354  ,  5.8230267,
        9.329588 ,  2.8012135, 12.151655 ,  3.6498296,  7.3381915,
        7.906301 ,  8.3214855,  9.498563 ,  8.174222 ,  1.4842765,
        5.4684577,  9.208811 ,  3.7843242, 23.542929 ,  9.365477 ,
        3.9281046,  3.2654653,  5.0756664,  6.48532  ,  6.81468  ,
        6.9036036,  4.036685 ,  3.1569686,  5.442589 ,  2.832836 ,
        3.1519508,  6.03366  ,  2.7077732,  8.967171 ,  7.640018 ,
        2.36079  ,  3.101483 ,  1.2850999,  7.930157 ,  9.3607645,
        9.744444 ,  4.3079443,  6.0450215,  3.073556 ,  5.514801 ,
        5.137671 ,  7.1235094, 12.491621 ,  2.522015 , 11.201149 ,
        2.45876  ,  1.4857997,  7.152842 ,  6.058746 ,  1.7489579,
        6.0236998,  4.6034803,  9.663622 , 14.431475 ,  2.1207514,
       11.181772 ,  5.2722616,  1.110923 ,  6.5906396,  8.192756 ,
        2.7726347,  4.651195 ,  3.8970683,  1.7994806,  5.0996637,
        6.545542 ,  7.9537573,  9.08461  ,  3.9811814,  6.4029803,
        5.372902 ,  7.8789883,  8.996041 , 11.89315  , 10.082515 ,
        4.666732 ,  5.4418197,  2.8788197,  5.74144  ,  2.3972175,
        8.506628 ,  3.2530193,  4.0942173, 10.790938 , 15.023245 ,
        2.3725822, 10.957347 , 10.283062 ,  1.0447165, 13.097405 ],
      dtype=float32), array([[[[-1.68513693e-02,  4.92947102e-02,  1.28077269e-02, ...,
          -2.57295906e-04, -1.12843076e-02,  3.55037041e-02],
         [ 3.71790095e-03, -2.89671700e-02, -4.72081564e-02, ...,
           4.65599261e-02, -5.25381565e-02, -2.29699705e-02],
         [ 1.86113194e-02, -7.17463195e-02,  1.50121786e-02, ...,
           5.66207096e-02,  1.40505629e-02,  6.88765757e-03],
         ...,
         [ 7.15545192e-02,  1.48802157e-02,  2.13756729e-02, ...,
          -2.69919802e-02, -5.18788025e-03, -4.27450389e-02],
         [ 6.40237704e-02, -2.21575610e-02,  3.56210284e-02, ...,
           1.24995075e-02, -3.63758355e-02,  1.45620713e-03],
         [-6.35151519e-03, -3.90348658e-02,  2.72391662e-02, ...,
           4.35575321e-02,  4.16235253e-02, -6.12443686e-02]],

        [[ 5.51209338e-02,  8.50554369e-03,  4.63727154e-02, ...,
          -5.09564392e-02,  2.10610852e-02,  5.99529669e-02],
         [ 2.56589390e-02,  5.45380376e-02, -4.41156365e-02, ...,
          -5.07283136e-02, -2.90698037e-02, -8.37048795e-03],
         [-2.11558063e-02, -6.36726711e-03, -6.59123957e-02, ...,
           2.94115767e-02,  1.20963845e-02,  2.15867776e-02],
         ...,
         [-2.66442373e-02,  4.58154865e-02, -2.01975666e-02, ...,
           9.42244101e-03,  2.31623650e-02, -5.38716977e-03],
         [-3.19022611e-02, -3.71356010e-02, -1.75788719e-02, ...,
          -7.14584207e-03, -2.94533912e-02, -2.74883360e-02],
         [ 1.53576536e-02, -1.26156304e-02,  4.05267719e-03, ...,
          -2.14342084e-02, -2.54693851e-02, -2.52838880e-02]],

        [[ 4.34893072e-02,  2.31985878e-02,  2.22284067e-02, ...,
          -2.83105876e-02,  5.03205396e-02, -1.34392008e-02],
         [ 2.55298074e-02, -2.94111837e-02,  1.60278603e-02, ...,
           3.50854322e-02,  2.29765754e-02, -6.49662241e-02],
         [-8.77124164e-03, -1.45834722e-02, -2.74590235e-02, ...,
           1.28348907e-02, -3.90974954e-02, -4.60207053e-02],
         ...,
         [ 6.38521910e-02,  5.47589287e-02, -2.08303407e-02, ...,
          -5.09190448e-02, -8.11116828e-04, -3.38166617e-02],
         [ 5.82848638e-02,  2.17935350e-02, -5.39637990e-02, ...,
           1.51971597e-02, -2.29747314e-03,  1.48156211e-02],
         [-2.51152962e-02, -3.55350152e-02,  1.97815001e-02, ...,
           3.08939777e-02,  2.88991556e-02, -4.48470302e-02]],

        ...,

        [[ 5.95117174e-03, -3.38365026e-02, -5.01714237e-02, ...,
           1.75928995e-02, -3.89912575e-02,  2.89291367e-02],
         [-1.31645706e-02, -4.15900834e-02,  4.11157198e-02, ...,
          -9.90524609e-03,  2.69793514e-02, -4.58965078e-02],
         [ 1.47961527e-02, -3.29171754e-02,  4.14501391e-02, ...,
          -7.57217547e-03, -3.09644602e-02,  2.81069838e-02],
         ...,
         [ 3.80545259e-02,  8.77472945e-03, -9.83355846e-03, ...,
           4.16203216e-02, -4.62807715e-02,  1.88750010e-02],
         [-1.89725533e-02, -3.52614895e-02, -5.07789366e-02, ...,
          -3.97044457e-02,  4.15839367e-02, -1.39273144e-02],
         [ 2.71904585e-03, -2.73355078e-02,  4.87593785e-02, ...,
          -4.84694317e-02,  1.15214009e-02,  1.82069223e-02]],

        [[ 2.04383377e-02, -8.07424728e-03,  1.75361447e-02, ...,
          -2.83405557e-02,  1.71904247e-02, -7.98599515e-03],
         [ 3.57505456e-02,  1.52618298e-02,  9.87690524e-04, ...,
          -1.82952248e-02, -3.33484896e-02, -4.83495370e-02],
         [ 4.01339866e-02,  4.32770476e-02, -5.32178162e-03, ...,
          -2.57620513e-02,  4.76057418e-02, -1.66066960e-02],
         ...,
         [ 2.78820097e-03,  1.31131839e-02, -4.31822911e-02, ...,
          -1.81792937e-02, -4.49034311e-02, -9.34077834e-05],
         [-3.27558368e-02, -4.05403450e-02, -2.39607524e-02, ...,
          -4.61787097e-02, -2.32377984e-02,  2.35536527e-02],
         [-1.47877624e-02,  1.23407794e-02, -1.63070150e-02, ...,
          -6.43586693e-03, -4.74221557e-02,  3.81793231e-02]],

        [[ 3.12052220e-02, -2.45537795e-02, -9.91676282e-03, ...,
          -2.52269618e-02,  1.09955873e-02,  4.47343774e-02],
         [ 2.47505289e-02, -1.48228547e-02,  2.81934887e-02, ...,
          -8.09683744e-03,  3.02844658e-03,  3.00764572e-02],
         [ 1.19155636e-02, -1.29974457e-02,  1.22908382e-02, ...,
          -9.21939127e-03,  1.66775309e-03, -2.90603898e-02],
         ...,
         [ 5.30931354e-02,  3.34193325e-03,  5.38020991e-02, ...,
          -8.31350219e-03, -3.03645767e-02, -1.01682525e-02],
         [ 6.76316209e-03,  4.49411422e-02,  1.20077236e-02, ...,
           2.56499965e-02,  5.94097143e-03,  1.77643746e-02],
         [ 4.10800874e-02,  2.25520693e-02, -1.46647589e-02, ...,
          -1.14037506e-02, -3.69336568e-02, -1.60029177e-02]]]],
      dtype=float32), array([[[[-0.05679434,  0.03714116,  0.02082307, ...,  0.00300105,
          -0.05321705, -0.01176559],
         [ 0.04208073,  0.03031957,  0.01923986, ..., -0.03834052,
          -0.03471433,  0.04322011],
         [ 0.02889596, -0.0058543 ,  0.05926654, ..., -0.03520803,
          -0.01703187, -0.02054318],
         ...,
         [ 0.02452233, -0.05088615,  0.04524018, ...,  0.03107619,
          -0.01645216, -0.00537014],
         [-0.01457174, -0.01031438, -0.00698803, ..., -0.03955437,
          -0.03732935, -0.04054591],
         [ 0.00644916,  0.00309164,  0.03690583, ..., -0.01672504,
           0.02844651, -0.05593515]]],


       [[[-0.04394889, -0.04337434,  0.03527806, ..., -0.03959855,
          -0.05918193,  0.00688541],
         [-0.02972939,  0.0414664 , -0.00596281, ..., -0.04097237,
           0.04962011,  0.02928144],
         [-0.01766925, -0.01928219,  0.01515552, ..., -0.0247612 ,
           0.00028749,  0.00527907],
         ...,
         [-0.0428897 ,  0.04211752,  0.04630711, ..., -0.00800276,
           0.0542796 ,  0.02632647],
         [-0.00844757, -0.01178419, -0.01796191, ..., -0.01940369,
           0.00782273, -0.00802508],
         [ 0.02586054, -0.05883873,  0.00711061, ...,  0.02488646,
          -0.03049708, -0.00723505]]],


       [[[-0.01521959,  0.01015391, -0.05323998, ..., -0.00637978,
          -0.06199681,  0.02864481],
         [ 0.02103917,  0.02468472, -0.03557545, ..., -0.03687091,
           0.03192712, -0.01156319],
         [ 0.0057274 , -0.01824861,  0.04353535, ..., -0.03761069,
          -0.00091434, -0.01755806],
         ...,
         [ 0.0016085 , -0.0612535 , -0.00127289, ..., -0.022016  ,
          -0.0372376 ,  0.04584647],
         [ 0.05054209, -0.03326034, -0.04192023, ..., -0.01982644,
           0.05358907, -0.0078433 ],
         [ 0.05296663, -0.03035942, -0.0438199 , ...,  0.02125478,
          -0.015512  ,  0.03148125]]],


       ...,


       [[[-0.05018697, -0.00551852,  0.02600564, ...,  0.0220207 ,
          -0.03865156, -0.01687202],
         [ 0.02304685,  0.00481474,  0.01556589, ..., -0.04282816,
          -0.03863928, -0.03642923],
         [ 0.06261587, -0.05235405, -0.01520805, ...,  0.04714427,
          -0.01126354, -0.02371644],
         ...,
         [-0.00483286,  0.00712186,  0.05447339, ..., -0.00159482,
          -0.03425265,  0.004428  ],
         [-0.01872675, -0.0002517 , -0.01069562, ...,  0.02663052,
          -0.04755648, -0.04921701],
         [ 0.01283577, -0.05682381,  0.0274935 , ..., -0.01813148,
           0.06031413,  0.03594624]]],


       [[[-0.01495825, -0.00894063, -0.01701771, ..., -0.00714208,
           0.00474928,  0.00365475],
         [ 0.05703476,  0.03124278, -0.00997417, ...,  0.00618878,
           0.00159184,  0.0216809 ],
         [-0.02887082,  0.03826441, -0.00544291, ...,  0.04961928,
          -0.00438643,  0.03944158],
         ...,
         [ 0.00580845, -0.01876247, -0.0064528 , ..., -0.03943242,
           0.03273448,  0.0205107 ],
         [-0.04857144, -0.01757608, -0.02473279, ..., -0.00800482,
          -0.01032571,  0.01212286],
         [-0.03728858,  0.00368371, -0.01337127, ...,  0.00603978,
           0.0533636 ,  0.00421392]]],


       [[[ 0.02981422, -0.04521773, -0.0262725 , ...,  0.02450369,
           0.02956682,  0.0197768 ],
         [ 0.01979125,  0.0500426 , -0.00795272, ...,  0.02801525,
          -0.03165612, -0.02652695],
         [-0.01468621,  0.03728046,  0.05659215, ..., -0.0464814 ,
          -0.03074394,  0.02081294],
         ...,
         [ 0.01970001,  0.0329016 , -0.03357999, ..., -0.01293037,
           0.03553664,  0.02086798],
         [ 0.03777255,  0.03073959,  0.04683379, ..., -0.0310781 ,
           0.03547773,  0.01566642],
         [ 0.0407805 ,  0.00588091, -0.0316575 , ...,  0.03107536,
           0.05676872,  0.00793019]]]], dtype=float32), array([-1.14663718e-02, -1.57733597e-02,  1.54681625e-02,  1.50537472e-02,
        1.47842821e-02,  4.17476706e-03, -1.68603100e-02,  9.94654931e-03,
        4.13027126e-03,  1.15998909e-02, -1.28171351e-02, -1.12221418e-02,
       -1.56514929e-04,  6.39669085e-03,  6.60734624e-03,  7.31329806e-03,
       -9.20115999e-05, -8.48123524e-03,  1.89020317e-02, -1.13241095e-02,
       -8.44260212e-03, -1.10899247e-02,  1.38336781e-03,  7.85245933e-03,
       -6.53448328e-03, -1.22460304e-02, -2.38556694e-02,  1.17964158e-02,
       -4.08829423e-03, -5.81685395e-04, -4.94791893e-03, -2.03427076e-02,
        5.78970509e-03, -1.25579871e-02,  1.31286951e-02, -1.64738037e-02,
        2.22600251e-02, -2.23016404e-02, -3.22031952e-03,  2.52736569e-03,
       -6.41793245e-03,  1.87035115e-03, -1.43347541e-02, -1.56292180e-03,
       -1.40736811e-02, -2.19217371e-02, -2.09735613e-02,  9.40301549e-03,
       -3.40685528e-03,  9.16476734e-03, -6.64871605e-03, -1.46833966e-02,
        1.85132655e-03, -9.71749891e-03, -2.96127284e-03, -1.06329089e-02,
       -6.57201326e-03,  5.00927679e-04,  5.18039055e-03, -7.56578986e-03,
       -2.20952891e-02,  1.44668343e-02,  1.22267008e-02,  1.32796252e-02,
        2.44061253e-03, -1.97767024e-03, -1.32645648e-02, -9.39999800e-03,
        6.95172930e-03, -5.89535630e-04,  9.34195053e-03,  4.40296391e-03,
       -6.28689013e-04,  9.13051702e-03,  9.23879258e-03, -7.55495764e-03,
        2.78572110e-03, -2.21261177e-02,  6.96059549e-03, -4.82483115e-03,
       -1.34064248e-02, -2.92084692e-03,  7.40012573e-03, -1.58739928e-03,
       -7.93227274e-03, -9.65835899e-03,  1.14092231e-02, -6.25263667e-03,
        5.68047911e-03,  2.36208504e-03,  1.44820074e-02,  1.05144188e-03,
       -2.89385449e-02,  7.44250650e-03,  8.15239764e-05, -1.26289092e-02,
        5.56019368e-03,  1.70717028e-03, -1.60295330e-03, -9.49930586e-03,
        2.36101877e-02, -5.48325898e-03,  4.26975079e-03, -6.23104908e-03,
        1.01415045e-03,  9.51753464e-04,  1.33861024e-02, -2.18391791e-03,
        3.07089905e-03,  2.45952094e-03, -1.67501904e-02,  1.14543028e-02,
       -1.28688256e-03,  7.25458667e-04,  6.15976518e-03, -1.32981949e-02,
        5.75611880e-03, -3.13673378e-03,  1.16657058e-04, -1.21445432e-02,
        4.30838298e-03, -1.89052634e-02,  2.03757780e-03, -5.41179627e-03,
        1.33107854e-02,  2.84170639e-03,  1.58530511e-02, -2.53563654e-02,
        1.70812942e-02, -9.54468921e-03,  5.29581495e-03,  1.26092350e-02,
       -1.80912502e-02, -2.68499088e-03, -1.18670973e-03,  6.83392910e-03,
        4.22224356e-03,  2.10870318e-02,  1.83926411e-02, -2.55911169e-03,
        4.25913883e-03, -2.87643466e-02, -5.33558009e-03, -4.30742465e-03,
       -7.05820136e-03, -2.75743823e-03, -1.02604581e-02,  8.60134431e-04,
        7.34136347e-03,  2.82337759e-02,  3.99471493e-03, -7.53363967e-03,
        4.59506502e-03, -9.74005368e-03, -2.05484573e-02, -1.81443188e-02,
        5.28068095e-03,  1.88049825e-03,  9.26780794e-03,  2.63051665e-03],
      dtype=float32), array([ 0.480535  ,  1.3911686 , -0.08501291, -0.8712565 , -0.7293178 ,
        0.23861153,  0.43597645,  0.13879976,  0.0990013 , -1.0425342 ,
       -0.38011146, -0.20563576, -0.43616214,  0.04906489, -0.5474677 ,
        0.29470417, -0.00364185, -1.030822  , -0.10935246, -1.1042578 ,
       -0.08724312,  0.72383314, -0.8271365 , -1.0305021 ,  0.5058572 ,
        0.42334563,  0.31547675, -0.6610493 , -0.7982979 , -0.5452903 ,
       -0.03447789,  0.2858611 ,  0.10804508, -1.6068922 , -0.26425877,
       -2.2535357 , -0.6658893 , -0.5182607 ,  0.338601  ,  0.3216415 ,
       -0.72237444, -0.5456032 , -0.17685032,  0.42223784,  0.33325782,
        0.40219063,  0.7385699 , -0.41667724, -0.67329484, -0.43200317,
        0.27592656, -1.0566142 , -0.8316263 , -0.97156996, -0.29699033,
        1.0377679 ,  0.01893223,  0.5945241 , -0.6788714 ,  0.6803644 ,
       -0.120929  , -0.5693627 , -0.5900666 ,  0.08296757, -0.85073376,
       -1.4838543 , -0.09060985,  0.31633875,  0.23501731, -0.6459104 ,
       -1.2414953 , -1.0591636 ,  0.28891203, -0.46877396, -0.19427231,
        0.42611426, -0.7424087 ,  0.5943333 , -0.737777  , -0.10088255,
        0.3748816 , -1.3152407 , -1.2043481 ,  0.52379465,  0.83666056,
       -1.3740343 , -0.6119206 , -0.7290375 ,  0.16831495,  0.1085301 ,
       -0.11604367, -0.5699017 ,  0.3920141 , -0.32767504, -0.88086504,
       -1.2014523 , -0.00627417, -0.30706355, -0.33473012,  1.0144867 ,
       -0.00480679,  0.6691258 , -0.2553854 , -0.6800515 , -0.31545022,
        0.5506614 ,  0.11034533, -0.4672109 , -0.02124668, -0.8110635 ,
        0.33844396, -0.08643935,  0.24620025, -0.9984854 , -0.3001927 ,
        0.6552073 , -0.56152445,  1.1502876 , -0.48773125,  0.87113607,
        0.07241585, -0.77769125, -0.16940969, -0.43448013, -0.71589726,
       -0.41133103,  0.44177568, -0.07142358, -1.1874703 ,  0.32582676,
        0.05739944,  0.1845284 ,  0.9261313 , -0.83216035, -0.19746192,
        0.30809337, -0.6456016 , -0.08101533, -0.48684227, -0.11881095,
       -0.32379463, -0.35102832, -1.1792324 , -0.43869847,  0.32267663,
       -0.8577528 ,  0.38467333,  0.6691408 ,  0.37905338, -0.4767267 ,
       -0.9456613 ,  0.3410391 , -0.2640657 , -1.040479  ,  1.4202666 ,
        0.5876843 ,  0.4551764 , -0.21396148, -0.23374796, -0.57628703],
      dtype=float32), array([2.2967799, 6.574988 , 3.5375974, 9.477706 , 5.761827 , 3.644243 ,
       6.3147893, 3.2397537, 2.3730316, 4.602185 , 3.4201217, 3.8133497,
       2.1755383, 1.4692762, 2.403767 , 3.2133687, 5.750405 , 2.8601413,
       3.820925 , 4.2632484, 1.9285095, 7.123214 , 3.9273098, 4.0713363,
       1.5297794, 1.1423286, 4.694302 , 3.5168285, 2.1503508, 3.1178794,
       5.1364603, 1.7892232, 3.1212516, 4.6036115, 5.508516 , 5.533079 ,
       3.014665 , 3.422101 , 7.3414116, 5.373704 , 3.0891   , 2.5584385,
       2.785553 , 1.3495866, 4.1423454, 5.1434774, 1.0955065, 2.2209933,
       3.8303075, 5.94157  , 5.434876 , 5.9270835, 3.012863 , 2.06589  ,
       6.3580694, 3.3841162, 2.715358 , 5.681621 , 3.2991917, 1.8704584,
       1.4900566, 6.5908175, 4.4309125, 5.3293576, 3.637372 , 4.8979135,
       3.2060282, 3.741158 , 3.32471  , 2.262946 , 5.590152 , 6.745783 ,
       1.737038 , 5.8659797, 5.8708215, 4.011145 , 4.554542 , 4.7850137,
       3.2643096, 2.029973 , 5.0839076, 4.314795 , 3.148988 , 2.183209 ,
       5.4170523, 3.7692134, 2.8406768, 3.088179 , 6.843722 , 3.465416 ,
       3.3522327, 2.526518 , 6.0347476, 1.9166291, 4.379878 , 4.913453 ,
       3.3244276, 3.8849437, 4.119093 , 9.635528 , 4.0101953, 3.6325443,
       2.1528761, 4.2002277, 3.6224113, 3.700667 , 2.0184534, 3.1097283,
       2.9074967, 0.9988415, 2.724041 , 2.3894582, 1.5045846, 2.608894 ,
       4.0735908, 2.1118367, 3.3666775, 8.311015 , 2.4145079, 4.3339624,
       5.185096 , 2.8248744, 1.9739447, 1.8656584, 4.5977817, 4.467681 ,
       3.170343 , 4.4248605, 3.2341833, 2.955502 , 2.9710972, 2.9381745,
       9.179668 , 3.3450832, 5.6168447, 7.279762 , 5.27076  , 2.3003256,
       3.9134958, 2.722003 , 1.6612799, 2.4312346, 4.5300927, 3.8200727,
       3.8347273, 5.191295 , 6.763241 , 1.9287921, 6.8928623, 4.000683 ,
       3.4210691, 4.693036 , 2.1909726, 6.020932 , 5.880156 , 3.3984811,
       2.1846974, 2.1128228, 2.7964642, 3.0419197], dtype=float32), array([ 0.00654573,  0.00725259, -0.00723459, -0.00486574, -0.01593956,
        0.00021406, -0.0064889 ,  0.00734079, -0.01061596, -0.01369896,
        0.00473258, -0.00476761,  0.00447397,  0.00357536, -0.0012686 ,
        0.00418231, -0.0013267 , -0.02586269,  0.00643536, -0.00840321,
       -0.00943035, -0.01204134,  0.00058247, -0.00810541,  0.00022877,
        0.00901424, -0.01246787, -0.00364937,  0.0096193 , -0.00779155,
       -0.00354175,  0.00582467, -0.00456147, -0.01197046,  0.00782079,
       -0.00815254, -0.00643186, -0.01509343, -0.00431273, -0.02060017,
        0.00423566, -0.01309039, -0.00202719,  0.00694589,  0.01006327,
        0.01623595, -0.01108046, -0.00175162, -0.00930766, -0.00108878,
       -0.01837606, -0.00422393, -0.01215861, -0.00481491,  0.02065023,
        0.02036928, -0.00889268, -0.00786063,  0.00145015,  0.00558358,
        0.01046715,  0.00567735,  0.01239266, -0.01015373,  0.00372553,
       -0.01468791,  0.00195639, -0.01245587,  0.00323964,  0.01184547,
        0.00540159,  0.00815868, -0.01911316,  0.00278372,  0.00403426,
        0.01617452,  0.00475497, -0.00724185, -0.00337748, -0.00564623,
       -0.0154827 ,  0.00071011,  0.03225492,  0.00469544,  0.0005701 ,
       -0.00132097, -0.02531145, -0.01068629, -0.00793836, -0.02073656,
       -0.00978826, -0.01579583, -0.00343777,  0.01270187, -0.01473159,
        0.0054266 , -0.00082912,  0.00774668, -0.00399253, -0.0006385 ,
       -0.00173431, -0.00329095, -0.0066228 ,  0.01485925, -0.00521094,
       -0.01536508, -0.00286689, -0.01841043,  0.00930346, -0.00516245,
        0.01836873, -0.0023754 , -0.02127304,  0.00148902,  0.00129314,
        0.00831529,  0.00278739, -0.00277762, -0.00456888, -0.00044157,
       -0.00753522, -0.02080919,  0.02900044, -0.00849861, -0.00106174,
       -0.00610127, -0.00495151,  0.01126982,  0.00820009, -0.00765172,
        0.00586719, -0.00535662, -0.01946964,  0.00425195, -0.02359458,
       -0.00764443,  0.00511423, -0.00038805, -0.01150403,  0.00156155,
        0.01735812,  0.00244389,  0.00967   ,  0.00934817,  0.00327646,
        0.01381942,  0.0208669 ,  0.00243495, -0.01266344,  0.0106337 ,
        0.02157701,  0.01588168, -0.01263443, -0.02090135,  0.00800072,
        0.01287621,  0.00250268,  0.01333385,  0.00484897,  0.00903041],
      dtype=float32), array([ 1.0944294 , -1.210969  ,  0.59144396,  0.2776499 ,  1.4242874 ,
       -0.70105654, -0.8768687 , -0.7355001 , -1.0814095 , -0.7111274 ,
       -0.8029441 ,  0.49892923,  0.21082139,  1.4159558 ,  1.3352643 ,
       -1.1550386 ,  0.64263755, -0.46636963,  1.2304668 ,  0.850979  ,
        0.18691176, -0.62150264, -0.7812963 , -0.39855343,  1.5296383 ,
       -0.92259794,  0.8571855 ,  1.3018007 ,  0.18049607, -1.0887371 ,
        0.17048056,  1.5027763 , -0.8590599 , -0.5832914 ,  1.3478589 ,
        0.96122724, -1.3364829 ,  1.1124364 , -0.02740062, -0.01677958,
       -1.2759542 , -0.72758913, -0.93240833, -0.92514795, -0.7774097 ,
       -0.9243574 , -1.4350516 , -0.8638265 , -0.07557553,  0.95412683,
       -0.69785434,  1.8343022 , -1.1733141 , -1.0859786 ,  1.0607511 ,
       -0.7726698 , -1.479871  , -0.886017  ,  1.0870078 , -0.28087324,
       -0.61058784, -0.9558934 ,  0.19569331, -1.1574984 , -0.8697439 ,
        0.9219825 , -1.1399035 , -0.68073785, -0.08341455,  0.14095248,
        0.20331371, -0.67737997,  1.3032256 ,  0.48278755, -1.1070004 ,
        0.17003825, -0.84946376,  0.3658279 , -0.03019144, -1.4377439 ,
       -0.8231234 ,  1.6642572 , -0.7643648 , -1.1342778 ,  0.97555673,
        0.55793285,  0.5373109 , -0.9563456 , -1.1177514 , -0.78714806,
       -0.8832112 , -0.93845886,  0.9282367 , -1.3204354 ,  0.5487713 ,
       -0.8967236 ,  0.60777336, -0.5323414 ,  1.6458447 , -0.36208323,
       -0.8117285 , -0.6875393 ,  0.28193104, -0.7614273 , -0.46433225,
       -0.55851084,  0.70256215, -0.16559847, -1.0886745 , -1.5152621 ,
       -1.0246886 , -0.18568724,  0.9838482 ,  1.2619812 , -0.4606986 ,
       -1.504066  , -0.68684894,  1.1490978 , -1.0811466 , -1.6164215 ,
       -0.31884274, -0.9462004 , -0.01348872, -1.0203909 , -1.3639182 ,
       -1.1318545 , -0.20745984, -0.24314885,  0.40921575, -0.5398074 ,
        0.63092494,  0.75504905, -1.0207099 , -1.1576707 , -0.679072  ,
        1.3184661 , -1.0789979 ,  0.50437975, -0.619084  , -1.1599444 ,
       -0.71318626, -0.30839166, -1.308371  ,  0.4799561 ,  1.4269935 ,
        0.26716468,  0.19701645,  0.62972796,  0.75196224, -1.5551662 ,
        0.2805488 , -0.47322184, -1.4833897 ,  0.08229379, -0.65317523,
       -0.6670953 ,  0.7171061 , -1.077515  ,  1.439238  ,  0.04864607],
      dtype=float32), array([10.591452 ,  4.7561297,  8.306072 ,  5.6611567,  9.154517 ,
        5.210506 ,  4.8020988,  3.3592901,  9.362744 ,  2.4447515,
        1.4222195,  2.1689467,  8.489684 ,  4.859197 , 11.536568 ,
        8.299005 ,  8.04533  ,  2.9536264,  7.415505 ,  6.879952 ,
        4.0647855,  4.8830667,  8.72318  ,  2.2161489,  6.2183647,
        7.892638 ,  1.6420381,  9.562026 , 11.252082 ,  4.769692 ,
        8.129878 , 10.305513 ,  6.626095 ,  3.087364 , 12.933413 ,
        6.5034204,  3.440503 ,  3.9496708,  8.184039 ,  3.7863002,
       10.134111 ,  6.761362 , 11.745979 ,  1.0874485,  4.6526413,
        3.2087667,  7.6668463,  3.8790514,  1.9707991,  8.751095 ,
        2.353478 , 13.370349 ,  4.357382 ,  3.315814 ,  6.3585105,
        1.7251458,  5.632619 ,  2.3694808,  9.820732 ,  1.2815472,
        8.416542 ,  7.0442476,  7.6961412, 11.495986 ,  4.9466696,
        6.271387 ,  3.2332482,  7.726055 ,  5.9892716,  1.8875744,
       13.757617 ,  5.4868693, 11.970422 ,  7.712529 ,  6.3714914,
        6.79339  ,  3.3085358,  5.294871 ,  9.294136 ,  6.918399 ,
        3.338244 ,  9.470167 , 12.202988 ,  8.728043 ,  4.876498 ,
        5.525223 ,  4.941796 ,  3.2279792,  8.502507 ,  4.1735344,
        8.030059 ,  2.2351866, 10.019062 ,  4.734669 ,  4.530861 ,
        7.941633 ,  4.899781 ,  1.9354889,  8.913512 ,  4.64127  ,
        5.154883 ,  1.250598 ,  5.2742095,  5.474393 ,  3.4727576,
        4.06037  ,  3.403953 ,  4.028009 ,  1.6913252, 10.39553  ,
        6.5228868,  6.733049 ,  7.2060776, 16.370932 ,  2.2699788,
        8.685753 ,  8.438052 ,  7.7485986,  9.86172  , 11.2351885,
        1.8674899,  6.6058416,  3.1615202,  7.2250023,  6.7705054,
        2.0960827,  2.7022195,  5.5871096,  9.364174 ,  4.298414 ,
        3.6731188,  4.8698955,  7.661388 ,  5.66224  ,  1.436896 ,
        8.455066 ,  4.7035174, 10.036464 ,  6.5636034,  5.0423036,
        4.68813  ,  0.8688812,  7.1531825,  6.4119205,  8.218631 ,
        5.9873943,  2.992563 ,  7.64047  ,  4.1062484,  9.164399 ,
       11.098224 ,  3.6805403, 12.61753  ,  2.7834723,  3.185719 ,
        4.6808486,  9.4562845,  3.8618917, 10.4421015,  1.2863929],
      dtype=float32), array([[[[-0.04186699,  0.024475  , -0.00202702, ..., -0.07409308,
          -0.05148713, -0.07453529],
         [ 0.07661421,  0.06439278,  0.08678043, ..., -0.0001502 ,
           0.0440572 , -0.0792716 ],
         [-0.04112515, -0.06366284,  0.0543026 , ...,  0.07492546,
          -0.00307151,  0.02437105],
         ...,
         [-0.05112548, -0.0863122 , -0.03501743, ...,  0.08360768,
           0.05467722,  0.05296836],
         [-0.02029149, -0.02525856,  0.02571259, ..., -0.00132141,
          -0.02467505,  0.02549048],
         [ 0.06447484, -0.04789399,  0.02103268, ...,  0.02310426,
          -0.02192006,  0.03255367]]]], dtype=float32), array([[[[ 0.03132674, -0.04370182, -0.01173028, ..., -0.03076603,
           0.03491684,  0.04561022],
         [ 0.01283716,  0.03346311, -0.00593741, ...,  0.03770607,
           0.03465863, -0.02700932],
         [ 0.05251636,  0.03700084, -0.03853636, ...,  0.02865515,
           0.03960582,  0.04551566],
         ...,
         [-0.02345006, -0.0331438 ,  0.04465589, ...,  0.04927495,
          -0.03232465, -0.04270807],
         [-0.009547  ,  0.00168109,  0.01370839, ..., -0.00614564,
          -0.01131499, -0.00981358],
         [-0.06772135, -0.00202508, -0.01707561, ...,  0.01339334,
          -0.049094  , -0.00920054]]],


       [[[-0.00458565, -0.02263315,  0.04294148, ...,  0.00464768,
           0.00257411,  0.05070711],
         [-0.00727694, -0.01799033, -0.02089771, ...,  0.04249571,
           0.03067684,  0.05251203],
         [ 0.02363434, -0.05162501, -0.02636242, ..., -0.03624001,
          -0.04643111,  0.02818738],
         ...,
         [ 0.02602798,  0.00947163, -0.03405061, ...,  0.04501789,
           0.0242507 , -0.03704217],
         [-0.0311951 , -0.02142116,  0.01076074, ..., -0.02200531,
           0.00570565, -0.05559888],
         [ 0.01173743,  0.03341018,  0.00742105, ...,  0.04732198,
          -0.01392688, -0.03106041]]],


       [[[ 0.0491442 ,  0.03474588, -0.00385944, ..., -0.0121789 ,
          -0.03938807, -0.03111682],
         [ 0.04649893,  0.0310887 , -0.00052855, ...,  0.01843078,
          -0.02837331,  0.01852932],
         [ 0.04306049,  0.02236385, -0.03803552, ..., -0.00767069,
           0.01007258, -0.03211101],
         ...,
         [ 0.00331787, -0.02070631,  0.05214374, ...,  0.02988412,
           0.02270392, -0.01838294],
         [-0.05658707, -0.01546336,  0.05294651, ..., -0.00157049,
          -0.02178251,  0.01915435],
         [-0.04786742, -0.00753961, -0.05016503, ...,  0.00237442,
           0.02939487, -0.02600967]]],


       ...,


       [[[ 0.01830681,  0.04891058,  0.05547146, ..., -0.0093356 ,
          -0.02364073,  0.04248316],
         [-0.02993236,  0.02818132,  0.01643075, ..., -0.04783897,
           0.0052274 , -0.01521227],
         [-0.00690292, -0.01323779, -0.02300914, ..., -0.03241174,
           0.0307878 , -0.03943343],
         ...,
         [-0.02482699, -0.03711845,  0.05097819, ...,  0.01450287,
          -0.04103891, -0.02025876],
         [-0.04554147,  0.02997249,  0.0158485 , ...,  0.0371918 ,
          -0.02297371,  0.00772742],
         [ 0.00172163, -0.01224771,  0.01624481, ..., -0.03271769,
          -0.04120345,  0.00973223]]],


       [[[ 0.0126473 ,  0.03639615,  0.00141104, ...,  0.05294091,
          -0.04762183, -0.01678214],
         [ 0.01842816,  0.0316606 , -0.01549631, ..., -0.05624249,
          -0.05913938,  0.0071022 ],
         [-0.00111194, -0.0096497 , -0.02947897, ..., -0.00124556,
          -0.04234793,  0.01768848],
         ...,
         [ 0.02308051,  0.0340067 , -0.01914559, ...,  0.02548211,
          -0.03658757, -0.0332423 ],
         [-0.05324252,  0.03240482, -0.00397426, ..., -0.00052511,
          -0.04871311,  0.02232223],
         [-0.00202059,  0.00487514,  0.00351192, ...,  0.01810784,
          -0.04006802,  0.0354642 ]]],


       [[[-0.01249071,  0.00903474, -0.009356  , ..., -0.03216354,
          -0.04542619,  0.01190787],
         [-0.05040814,  0.0424038 ,  0.06024637, ...,  0.00030317,
          -0.03167471,  0.05108204],
         [ 0.03128169, -0.0089529 ,  0.00268541, ..., -0.04571376,
          -0.00930345,  0.02254287],
         ...,
         [ 0.02901161,  0.01765813,  0.04717599, ..., -0.00256851,
          -0.02870384,  0.00897073],
         [-0.02346702,  0.04350325,  0.03618122, ...,  0.06120386,
          -0.02596609,  0.0042002 ],
         [ 0.01471196,  0.02317755, -0.04345689, ...,  0.04409928,
          -0.01511922,  0.05542481]]]], dtype=float32), array([[[[-2.62397882e-02,  2.40423027e-02,  9.72698629e-03, ...,
          -1.92031655e-02, -1.32602220e-02, -1.45731671e-02],
         [ 1.07814781e-02,  1.50914462e-02,  3.68868448e-02, ...,
           1.32035632e-02, -2.86866967e-02,  2.59597618e-02],
         [ 5.02662398e-02,  6.20773900e-03,  2.91387793e-02, ...,
           4.71796803e-02,  4.87051345e-02,  3.33040021e-02],
         ...,
         [-4.75030132e-02, -3.00328583e-02, -7.42017990e-03, ...,
           3.34097780e-02,  2.09634788e-02, -2.23136675e-02],
         [ 2.83712763e-02,  4.72141020e-02, -2.27857661e-02, ...,
           4.59960811e-02, -3.66005823e-02, -3.62694599e-02],
         [ 3.15581411e-02, -4.22239229e-02,  4.45016697e-02, ...,
          -2.75955927e-02, -3.10301390e-02,  4.47506178e-03]],

        [[-9.22408048e-03,  2.16858704e-02,  2.24800296e-02, ...,
           3.16863693e-02,  6.91512376e-02, -4.74537956e-03],
         [ 2.64238976e-02,  2.82102432e-02, -4.55848612e-02, ...,
          -4.61775884e-02, -4.33084294e-02, -1.71668902e-02],
         [ 1.46010611e-02, -1.79994646e-02, -6.03074348e-03, ...,
          -2.59721447e-02, -9.10024624e-03,  1.61345564e-02],
         ...,
         [-2.77506877e-02,  4.82919887e-02, -2.50998680e-02, ...,
          -6.83771772e-03, -1.78356152e-02,  4.19878475e-02],
         [-8.30413960e-03, -2.22572517e-02,  1.55228935e-02, ...,
           3.83375548e-02, -4.55163196e-02,  4.21517976e-02],
         [-3.44799571e-02, -6.12131786e-03,  2.79930364e-02, ...,
           1.78851113e-02,  2.01779529e-02, -3.13351639e-02]],

        [[ 5.64891621e-02,  4.52199988e-02, -1.79462694e-02, ...,
          -3.03737056e-02,  2.50520427e-02, -3.59914601e-02],
         [-1.11431694e-02,  3.87271456e-02, -4.05769981e-02, ...,
          -3.66475135e-02, -4.70658280e-02, -3.05570140e-02],
         [ 2.33594868e-02,  1.63400546e-02,  5.29514346e-03, ...,
           7.88081624e-03,  4.68021110e-02, -3.91307063e-02],
         ...,
         [-1.49525627e-02,  4.94083762e-02, -2.94776559e-02, ...,
          -2.07498148e-02, -1.23363128e-02,  3.18217762e-02],
         [-2.32082438e-02,  3.63247320e-02, -5.80959991e-02, ...,
           2.40165442e-02, -3.21406010e-03,  3.10208481e-02],
         [-2.73374887e-03, -3.13378684e-02,  2.24899948e-02, ...,
           2.85495315e-02, -2.85810512e-02,  2.18340084e-02]],

        ...,

        [[-1.66216381e-02, -3.57242115e-02, -5.69955446e-02, ...,
          -1.07174013e-02,  3.70087437e-02, -4.84541170e-02],
         [-3.79202366e-02,  3.45293954e-02, -8.66172195e-04, ...,
           4.87304293e-02, -3.74078788e-02,  8.68383050e-03],
         [-6.38132030e-03,  3.16329636e-02, -3.15326639e-02, ...,
           2.05100719e-02,  3.81708406e-02, -5.47900461e-02],
         ...,
         [-4.45551649e-02,  1.15731042e-02, -2.26866733e-02, ...,
          -2.16947049e-02, -6.61959872e-03,  5.83442859e-04],
         [-2.89206263e-02, -4.23157364e-02,  2.16265358e-02, ...,
           4.30708639e-02, -4.26293164e-02,  5.21643879e-03],
         [-4.66719829e-02,  1.39870411e-02,  1.09038036e-02, ...,
           2.52937134e-05,  1.06384084e-02,  3.80108599e-03]],

        [[-4.09157462e-02,  9.71648283e-03, -2.08656825e-02, ...,
          -6.91846898e-03, -4.16979007e-02, -4.95364852e-02],
         [-1.71274925e-03,  3.60504799e-02, -4.63393051e-03, ...,
           3.66955660e-02,  1.83856133e-02,  3.70122418e-02],
         [-2.21305490e-02, -5.04853688e-02,  1.07452702e-02, ...,
           1.97394993e-02, -3.17816436e-02, -3.68585438e-02],
         ...,
         [-4.95514832e-02, -3.32696326e-02,  1.61899254e-02, ...,
           2.13893130e-02, -3.74780782e-02, -1.05528906e-02],
         [ 3.73108475e-03,  3.92966382e-02,  1.22558959e-02, ...,
           2.27316679e-03,  4.03248109e-02, -6.22989535e-02],
         [-2.30780779e-03,  2.41151229e-02,  3.06225698e-02, ...,
           4.46475521e-02,  4.92771715e-02, -3.75838950e-02]],

        [[-1.96220092e-02,  1.49916299e-02, -3.26702408e-02, ...,
           2.02023052e-02,  4.52294573e-02, -1.86391994e-02],
         [ 2.27129702e-02,  1.55365849e-02, -2.06680852e-04, ...,
          -1.92269462e-03, -3.70204747e-02, -2.47804374e-02],
         [ 4.82330844e-02,  1.77204777e-02, -2.50270516e-02, ...,
          -4.55153268e-03,  1.22614829e-02, -4.25257199e-02],
         ...,
         [-8.82839970e-03,  2.33013369e-02,  3.43908276e-03, ...,
           1.49817383e-02,  2.92052440e-02, -1.86218396e-02],
         [ 5.81472889e-02, -4.89804372e-02, -4.44696471e-02, ...,
          -9.18183848e-03, -3.61908749e-02, -7.86294928e-04],
         [-1.78808626e-02, -6.94129057e-03,  3.22865099e-02, ...,
           3.14900987e-02,  4.54615392e-02, -1.94830280e-02]]]],
      dtype=float32), array([[[[-0.05519224,  0.05600257,  0.03044896, ..., -0.01062071,
           0.00830697, -0.04108106],
         [ 0.06383975, -0.01540771, -0.00034671, ..., -0.04494996,
           0.0024354 ,  0.06047444],
         [-0.08476027, -0.01213102, -0.0537302 , ...,  0.01569744,
          -0.06524268, -0.04391376],
         ...,
         [ 0.0395354 , -0.00789173,  0.01830431, ...,  0.0124508 ,
          -0.01643841, -0.01614211],
         [ 0.07690936, -0.01419541,  0.05857289, ...,  0.00468197,
          -0.04232845, -0.07606708],
         [ 0.04809979, -0.01716962,  0.05728522, ...,  0.02497219,
          -0.02388284, -0.003872  ]]]], dtype=float32), array([-1.52554864e-03,  8.09843745e-03,  9.63334460e-03,  6.45815302e-03,
       -8.10801983e-03, -9.96674132e-03,  1.71014981e-04, -3.41079221e-03,
        1.46626215e-02, -4.57594544e-03,  1.01192039e-03,  2.11044922e-02,
       -5.92909334e-03,  9.79917310e-03,  4.75935312e-03, -5.67763392e-03,
        2.65766867e-05,  7.05264509e-03,  1.00655039e-03,  1.47313776e-03,
       -2.56300787e-03, -1.01831555e-02, -5.90798620e-04, -7.11464556e-03,
       -1.36335408e-02, -1.50936786e-02, -2.32414063e-02, -1.29197119e-02,
       -2.89220037e-03,  2.94209737e-03,  6.68727187e-03,  5.69802709e-03,
        1.20782768e-02,  1.85765680e-02, -1.02822492e-02,  4.24653757e-03,
       -4.85985773e-03,  4.71890206e-03,  1.34268105e-02, -1.16775222e-02,
        3.63634463e-04,  4.22649427e-05, -6.07316475e-03,  1.15033309e-03,
        3.18899658e-03,  4.09628684e-03,  2.57813465e-03, -1.61858741e-02,
       -1.21096652e-02, -1.32649597e-02,  1.17520066e-02, -1.48595106e-02,
        4.92222840e-04,  1.69419162e-02, -1.86160058e-02,  1.94589444e-03,
       -1.00308163e-02, -1.56380907e-02,  7.00088032e-03, -3.91520746e-03,
        4.97566350e-03, -9.87349637e-03,  2.88482872e-03, -6.84374571e-03,
        1.03574190e-02, -3.09901498e-03,  7.77435908e-03, -1.78824668e-03,
       -1.64941158e-02,  2.11577350e-03,  1.17725050e-02,  1.33144446e-02,
       -2.08524335e-03,  1.84749663e-02,  1.47470497e-02,  2.03080638e-03,
       -2.29586363e-02,  1.17258159e-02, -8.92739650e-03, -4.11527377e-04,
       -5.62322047e-03, -8.55467562e-03,  1.59261115e-02, -8.70832708e-03,
        7.73345074e-03, -5.97774563e-03, -4.13119502e-04, -2.62393691e-02,
       -6.85747992e-03,  3.85596789e-03, -1.47184515e-02, -2.98503018e-03,
        6.31584669e-04,  9.79749020e-03,  7.00136973e-03, -1.87571719e-03,
       -2.02338560e-03, -7.94284418e-03,  2.13250937e-03,  7.11435173e-03,
       -3.39638535e-03,  4.47529089e-03,  8.99012014e-03, -1.05513567e-02,
       -1.17762340e-02, -1.11055598e-02,  8.00911151e-03, -5.60065685e-03,
       -6.81111682e-03, -4.80374042e-03,  1.81116946e-02, -3.23926611e-03,
        2.27679405e-02,  2.68698134e-03, -1.09122815e-02, -4.07218840e-03,
       -2.02831756e-02,  1.94080807e-02, -4.25394531e-03,  1.77570637e-02,
        1.27102099e-02,  1.48161110e-02, -2.40337718e-02,  7.45835539e-04,
        4.53280425e-03, -6.45893277e-04, -2.28595803e-03,  1.32469311e-02,
       -2.47929189e-02, -1.75191474e-03,  5.32359770e-03, -2.07123868e-02,
        8.66362173e-03, -4.22531553e-03, -1.39318360e-02,  4.93845204e-03,
        1.22573376e-02,  2.28333846e-02, -1.79858599e-02, -1.27808824e-02,
        2.03417670e-02, -1.21106142e-02,  3.51050729e-03,  4.57108440e-03,
       -1.65084854e-03, -1.27334082e-02, -6.67784642e-03, -5.68524934e-04,
       -8.42020288e-03, -5.88194560e-03, -1.18642766e-02, -2.50887562e-04,
        2.27256306e-03, -8.60032532e-03,  1.46932229e-02, -1.59316149e-03,
       -1.01391142e-02,  1.45788258e-02, -1.33704115e-03,  2.17547966e-03,
        1.11872086e-03, -2.38461653e-03, -2.78691435e-03, -2.85716774e-03,
       -6.72043301e-03, -2.08672434e-02, -4.75592352e-03, -1.31507707e-03,
       -3.64835927e-04,  8.62516928e-03, -2.39339587e-03, -1.65410060e-02,
       -1.56057547e-04, -2.50663771e-03,  1.21553615e-02, -1.05958497e-02,
       -1.04602771e-02, -1.29652573e-02, -1.87722296e-02,  8.27631261e-03,
        9.38735623e-03, -3.43536399e-03,  2.17985921e-02,  5.88674890e-03,
        1.55043404e-03, -5.51284151e-03, -2.34170668e-02, -8.46789777e-03,
       -7.70821096e-03, -1.63057651e-02, -1.05362395e-02, -1.79504771e-02],
      dtype=float32), array([-0.8294453 , -0.32061592,  1.5795513 ,  0.72220796, -0.17367879,
       -0.2881409 , -0.8352875 ,  0.74865305, -0.91771525,  1.205941  ,
       -0.54143703, -0.5137449 ,  0.3249356 ,  0.7725089 ,  0.03659748,
       -0.27405912, -0.40226525, -1.3617111 ,  0.09553909,  0.7254564 ,
       -0.6042258 , -0.02169769, -0.6443901 ,  0.19536431,  1.0213782 ,
        1.2601787 , -0.8005998 ,  0.42258373, -0.09203382,  0.2558032 ,
       -1.0412385 , -0.767269  , -0.35084176, -0.8074543 , -1.0049392 ,
        0.83981097, -0.4526918 , -0.93140274,  0.2019109 ,  0.02813005,
        0.30293888, -0.6334081 , -0.01203982,  0.21233912,  1.1194347 ,
       -1.0926416 , -0.4778944 ,  0.76932067,  0.5460434 , -1.0165832 ,
        1.0721115 , -0.9446075 , -0.2052554 , -0.9933205 ,  0.5195615 ,
        0.12826695, -1.2976965 , -0.36521754, -0.7810554 , -0.2534319 ,
        0.5269377 , -0.4524771 , -0.05818234,  1.0951788 , -0.24630587,
       -0.60098195,  0.70968246, -0.34824622,  1.2102395 , -0.05507347,
       -0.4678599 , -0.51024014,  1.5225315 ,  0.00227253,  1.0492427 ,
        0.04083106,  0.15437025,  0.10104669,  0.07463861,  0.49005684,
        0.05246156,  0.45723444, -0.93774724, -0.09079565, -0.23715113,
        0.50640714,  1.1363777 , -1.1526451 , -0.3996774 , -0.164926  ,
       -0.70511407, -0.62343186, -0.9799778 , -0.5330112 ,  0.8495389 ,
        1.361106  , -1.1031315 , -0.4863419 ,  0.597903  , -0.72216916,
        0.61013234, -1.0443426 ,  0.69783115,  0.1816951 , -1.1336898 ,
        0.42326197,  0.6862098 ,  1.0501012 , -0.6243799 ,  0.45875975,
       -0.7327575 ,  0.08395737, -0.83476776, -0.34891295,  0.14531642,
       -0.01416502,  0.36705342, -0.09928042, -1.1716045 ,  0.13798192,
        0.04682436, -0.46115702,  0.44104576,  0.15335707, -0.3527361 ,
       -0.16369312, -1.2115357 ,  0.04470069,  0.32499877,  0.12539937,
       -0.05238683,  0.441267  ,  0.24640113, -0.9550925 , -0.3625864 ,
        0.09908511, -0.11680727, -0.3771373 ,  0.91531473, -0.05384501,
        0.9048371 , -0.04393309,  0.30979386,  0.62940097,  0.8267883 ,
       -1.4134707 , -0.06822781, -0.51454586,  0.64871806,  0.633779  ,
        0.6128092 ,  0.4025782 ,  0.6476919 ,  0.29779586,  0.16451935,
       -0.64034015, -0.43383682, -0.37774017, -0.06511828,  0.15541284,
       -0.627525  ,  0.08501695,  0.6093875 ,  0.84218097,  0.7459211 ,
        1.0014341 , -1.0056813 ,  0.7366233 ,  0.7894039 ,  0.16498376,
       -0.56728077, -0.8546529 , -0.8525575 , -1.08903   , -0.21322317,
        0.5379741 ,  0.30962026, -0.11682367,  0.8095326 , -0.24345988,
        0.19476272,  0.8234001 , -0.83919317,  0.38704392, -0.46348098,
        0.78869003, -0.863181  , -0.66624033, -0.13102959,  1.332805  ,
       -0.67611444, -0.29761896], dtype=float32), array([1.6486942 , 2.7184296 , 5.9910965 , 2.4211385 , 1.4156735 ,
       2.0106187 , 2.936195  , 4.101699  , 4.152004  , 5.2743917 ,
       1.6974839 , 1.7853742 , 4.8640647 , 4.1137204 , 0.86796904,
       0.8553213 , 2.40194   , 2.8094285 , 1.8567457 , 4.045195  ,
       1.4709786 , 1.702095  , 2.2612035 , 2.3628752 , 3.6641686 ,
       1.176351  , 2.4352822 , 0.8505539 , 1.8891628 , 2.431663  ,
       3.127605  , 2.3384914 , 1.466459  , 3.0015106 , 2.2019548 ,
       5.180114  , 3.3413973 , 2.5119514 , 1.4089504 , 2.6182675 ,
       1.8593119 , 2.816401  , 2.825669  , 1.1629204 , 4.0773215 ,
       4.019519  , 1.7074306 , 1.3183348 , 1.4365312 , 4.3865256 ,
       2.6628907 , 3.583262  , 1.3331677 , 4.022136  , 3.2377083 ,
       3.2894197 , 2.2429142 , 1.5395775 , 2.7072554 , 2.4871128 ,
       2.3093297 , 1.1483737 , 2.4960914 , 3.8255057 , 2.2813425 ,
       2.8002343 , 4.125743  , 2.8704195 , 4.431783  , 1.267012  ,
       1.5825629 , 1.2973608 , 8.385865  , 2.5266845 , 3.8932645 ,
       1.4833746 , 2.9793038 , 1.507781  , 2.0491242 , 4.1624184 ,
       3.9245307 , 1.7012918 , 3.7273118 , 2.1562665 , 2.85039   ,
       3.4707034 , 4.717425  , 2.1070602 , 2.9286098 , 2.5627086 ,
       2.4219766 , 2.792015  , 5.1702366 , 2.0403986 , 5.607544  ,
       5.682367  , 2.6394494 , 1.5685362 , 1.5895395 , 3.0792863 ,
       3.1137192 , 2.3529968 , 2.0591583 , 1.3616503 , 2.1471703 ,
       1.7902633 , 3.8718295 , 5.813699  , 1.8338271 , 1.6832365 ,
       4.7842836 , 3.3277893 , 2.3590734 , 2.407     , 2.0675101 ,
       1.5194523 , 1.6471665 , 1.7986239 , 3.294017  , 1.8855321 ,
       1.859849  , 1.5372428 , 2.1078494 , 3.1023865 , 2.4050455 ,
       3.8828354 , 6.9144506 , 2.111152  , 1.2286801 , 1.3706578 ,
       3.9480472 , 1.8024087 , 5.00148   , 3.493799  , 5.862236  ,
       2.0451305 , 1.6846312 , 1.2307608 , 1.8712199 , 1.5737071 ,
       3.4797866 , 2.3233085 , 3.9671547 , 2.2707224 , 8.1259575 ,
       3.2502694 , 0.9944683 , 1.2921163 , 2.0027094 , 4.8655643 ,
       5.766196  , 2.7553246 , 1.2738999 , 1.700947  , 1.603926  ,
       2.5162    , 2.3405948 , 3.689589  , 1.2072535 , 1.2102982 ,
       2.4862504 , 2.6915805 , 8.190289  , 4.2244787 , 2.874749  ,
       4.6465282 , 3.3847022 , 1.4506608 , 4.9612584 , 1.7476826 ,
       2.7432592 , 3.9436677 , 2.6038568 , 2.5434039 , 3.412316  ,
       5.9617496 , 1.2895477 , 1.5635914 , 1.5099019 , 1.7712853 ,
       1.7608488 , 2.3342443 , 2.4362438 , 3.2769947 , 3.5239875 ,
       4.8918643 , 3.8450346 , 2.0079508 , 2.1674824 , 2.6923425 ,
       3.0471296 , 1.3345835 ], dtype=float32), array([ 8.44148360e-03, -1.19031165e-02, -2.28368514e-03, -9.94258840e-03,
        3.85540654e-04, -1.54587170e-02,  8.12274311e-03,  1.75867919e-02,
       -1.07845115e-02, -6.50171144e-03,  7.72305112e-03,  7.41548697e-03,
       -1.98802687e-02, -9.72047821e-03,  1.97795965e-02, -2.37521660e-02,
       -8.06670170e-03,  1.75647438e-02,  7.03355437e-03,  5.17517747e-03,
        1.49754365e-03, -2.18331092e-03, -6.97752926e-03, -7.18313549e-03,
        1.83334872e-02, -2.04720888e-02, -1.08094781e-03,  1.48655912e-02,
       -6.74222084e-03,  3.41772276e-04,  9.69576370e-03,  3.83081450e-03,
       -7.49350199e-03,  5.33619954e-04,  3.96685936e-02,  8.82830378e-03,
        2.42680218e-02, -1.14618149e-03,  1.62097532e-02, -4.42074798e-03,
       -3.64742614e-02, -2.41771876e-03,  8.29657260e-03, -1.21113972e-03,
        4.67539299e-03,  1.48213962e-02, -3.17859603e-03,  1.24841705e-02,
       -1.12172570e-02, -2.30144300e-02, -1.88010037e-02, -1.27005214e-02,
       -1.75952557e-02, -1.02000972e-02,  8.55216105e-03, -2.36452464e-02,
       -8.07287917e-03, -1.64010897e-02, -4.51939786e-03,  3.13198729e-03,
       -8.75743944e-03, -1.42036136e-02,  3.68720386e-03,  7.95901113e-04,
        9.74871963e-03, -4.15989431e-03, -1.84703320e-02,  6.40534004e-03,
        3.03472299e-03, -2.35977292e-04,  2.17332002e-02,  1.35364309e-02,
        1.10064475e-02,  1.00987209e-02,  1.34556694e-02,  7.05248956e-03,
        7.09520327e-03, -2.00445391e-03,  3.00728548e-02,  1.68633610e-02,
        1.82619703e-03,  1.58159547e-02, -2.82626762e-03,  4.90351487e-03,
        8.48484691e-03,  2.77444683e-02, -1.16269467e-02, -2.17936113e-02,
        1.03967087e-02, -1.80050749e-02, -1.39241386e-02, -2.05740854e-02,
       -7.51421647e-03, -2.77654175e-02, -1.31214364e-02, -3.89153697e-03,
        1.90274545e-03,  2.72910413e-03, -1.99685898e-02,  8.14670639e-04,
       -1.48938261e-02, -5.59630478e-03, -3.42332711e-03,  5.46880881e-04,
       -7.55046913e-03, -1.98610104e-03, -1.08339982e-02, -1.56747934e-03,
        1.48649989e-02, -7.66951125e-03, -4.05020721e-04,  1.51798432e-03,
       -1.23579556e-03, -1.58566923e-03,  1.26275625e-02, -8.21739342e-03,
       -8.79901089e-03,  1.32087935e-02,  1.41054196e-02, -7.64241861e-03,
       -5.78653021e-03, -1.87863410e-02, -9.67945380e-05, -6.53849822e-03,
       -2.05067545e-03, -2.22682841e-02,  4.11216822e-03,  8.65050592e-04,
       -4.48914431e-03,  1.73322726e-02,  7.07771163e-03, -8.51176027e-03,
       -1.29164746e-02,  2.51110084e-03,  7.33341463e-03, -5.99782635e-03,
       -1.36322221e-02,  7.58344494e-03, -5.89498878e-03, -9.46473423e-03,
       -2.29770527e-03, -1.61707047e-02,  9.88796237e-04, -9.03041626e-04,
        4.45372751e-03,  1.92150604e-02, -2.51668058e-02, -1.52482809e-02,
        1.09214121e-02,  1.79013442e-02, -1.91325205e-04,  1.75340660e-02,
        1.25571061e-02, -1.27255050e-02,  3.40435514e-03, -1.30042504e-03,
       -8.07778724e-03, -6.19672379e-03, -3.26061323e-02, -1.54807121e-02,
       -1.86983272e-02, -2.45959428e-03,  1.89536940e-02, -7.50546996e-03,
       -1.23904953e-02,  3.18413810e-03,  3.07994056e-03,  1.23299640e-02,
       -1.62651204e-02, -1.07530653e-02, -2.72254795e-02, -1.28255766e-02,
        7.63886375e-03,  1.70095712e-02,  8.05621874e-03,  9.37208533e-03,
        1.11026661e-02,  2.00863574e-02, -3.91716473e-02,  1.69582013e-02,
       -1.35968318e-02,  1.96278770e-03,  1.81284174e-02,  1.44828372e-02,
       -1.45709803e-02,  1.62478797e-02,  1.47990407e-02, -6.07917202e-04,
        7.57375779e-03,  4.47956438e-04, -5.49757527e-03,  1.05999620e-03],
      dtype=float32), array([-0.8262004 ,  0.95971346,  0.8389449 , -1.1625274 ,  1.1597761 ,
        0.29453617, -0.43964338, -1.2851529 , -0.80562466, -0.72542745,
       -0.8076687 ,  0.16527237,  1.5518421 ,  0.60192436, -1.0941458 ,
        0.7242914 ,  0.31774786, -0.7694608 ,  0.24195784,  0.03971815,
       -0.1883617 ,  0.8137942 ,  1.0819548 ,  0.9563421 ,  0.36132005,
       -0.1834143 ,  0.28881478,  0.5097034 ,  0.60567063, -0.7359693 ,
        0.23240025, -1.0708838 ,  1.4087121 ,  0.20857216,  0.4736238 ,
        0.3028354 ,  0.49233007, -0.4538389 , -0.18595928, -0.18672428,
        0.9136017 ,  0.00987347,  1.0320607 , -1.5497856 ,  0.08339386,
       -0.64774096, -0.18513858, -0.9387598 , -0.23648849, -0.02709015,
        0.23255515, -0.22666799,  0.30381843, -0.75810057, -0.88705045,
        0.45203364, -0.04521479,  0.44760597,  0.6347517 , -0.32050705,
        0.28631645, -0.55588484,  0.23411328,  0.08417898,  0.0326587 ,
        0.15875994, -0.6567433 ,  0.32451218,  0.48305976,  1.5308976 ,
       -1.4271733 ,  1.0125293 , -0.43734232, -0.11254092, -0.5682381 ,
        1.3433704 , -1.3710916 ,  0.33086032,  0.65444016, -1.4703834 ,
        0.22011808, -0.31087476,  0.6798869 , -0.21195395, -1.0415703 ,
        0.26040673, -0.8730524 ,  0.84993553,  0.40295386, -0.498543  ,
        0.6922646 ,  0.742678  ,  0.1573673 ,  0.9618678 , -0.00299014,
       -0.81537277,  0.4346514 , -0.88839537,  0.65805656, -0.17710763,
       -0.89313173, -0.7171592 ,  0.54786175, -0.7432169 ,  1.2032434 ,
        1.0209622 , -0.07357913,  0.08995663,  0.02335119, -0.3958803 ,
       -0.13561006, -0.79610044, -0.40358067, -0.00749242, -0.5610728 ,
        1.2420582 ,  1.1654239 , -0.6339152 , -0.8238579 ,  0.3725902 ,
        0.7578699 ,  0.58707905,  0.94474787, -0.04633952,  0.5138425 ,
        1.4179661 , -0.62376827,  0.92076826,  0.54980904, -0.03136638,
       -1.1926174 ,  0.14065562,  0.70271766,  0.82871145,  0.42622292,
        0.18158011,  0.36551332,  0.3341043 ,  0.1218617 , -0.54034215,
        1.0131954 ,  1.0994464 ,  0.97496367, -0.156746  ,  0.15740177,
       -0.57677716,  0.43621045,  0.05138032,  0.49627367, -0.91123396,
       -0.9537653 ,  0.51812345,  0.38890156,  0.3346252 ,  0.30050588,
        0.5102624 , -0.8153051 ,  0.6102235 ,  0.5976295 ,  1.2815697 ,
        0.9350984 , -1.1889424 ,  0.49824417, -0.8394865 , -1.0083343 ,
       -0.10456982, -0.9029221 , -0.48893532, -0.01689572, -0.6758357 ,
        0.7243995 ,  0.53638047, -0.7993407 , -0.9421473 ,  0.4505536 ,
       -0.0497523 ,  0.20075233, -1.6221327 ,  1.3346101 ,  0.4215899 ,
        0.5917226 , -0.9060714 ,  0.4981718 , -1.5513207 , -1.5906395 ,
        0.41140267,  0.09835351,  0.62536496, -0.7515261 , -0.71254253,
       -1.4857341 ,  0.06318275], dtype=float32), array([ 6.1454372,  3.9426236,  3.971237 ,  3.5194972,  5.5981054,
        7.5848885,  6.0804534,  5.780144 ,  1.4561955,  2.469732 ,
        5.1622124,  5.467458 ,  4.6274357,  3.7498538,  2.8915398,
        5.5292735,  5.483018 ,  3.703454 ,  3.5647454,  1.6797038,
        3.843028 ,  3.3327513,  3.846238 ,  2.1976204,  4.385977 ,
        1.623822 ,  4.375182 ,  5.810731 ,  3.9754653,  2.2633162,
        5.075771 ,  3.4777505,  4.523097 ,  4.099287 ,  6.9621887,
        1.7907346,  4.902212 ,  4.52335  ,  4.024784 ,  3.0895493,
        3.1799285,  4.7715683,  6.5668335,  9.024637 ,  3.059358 ,
        2.0165906,  2.1340387,  3.891116 ,  1.9786178,  3.9184299,
        1.2037095,  2.4677386,  5.7950516,  4.8266387,  2.1782749,
        3.5715714,  5.7213326,  7.8391232,  5.7814417,  1.9789224,
        5.474212 ,  2.7545168,  6.653314 ,  2.973286 ,  5.0074916,
        4.978979 ,  3.9457986,  4.7720933,  2.8648443,  3.3346667,
        4.692188 ,  5.3739185,  1.6339526,  4.5232825,  4.3717823,
        5.6322546,  4.0464997,  6.005398 ,  8.577544 ,  3.8854039,
        4.4415   ,  6.4630127,  1.0636479,  7.730611 ,  5.0365977,
        5.4369273,  3.7532325,  9.518238 ,  5.146887 ,  1.228352 ,
        1.4932169,  8.285517 ,  2.8400376,  7.1684213,  2.0725405,
        9.6516485,  1.7141045,  4.8386073,  3.3309047,  4.0102677,
        7.720619 ,  4.4170995,  7.779595 ,  5.851992 ,  6.298447 ,
        5.9849577,  4.7458415,  5.169399 ,  3.7925365,  3.797618 ,
        4.0307827,  5.0215125,  1.7064557,  7.090632 ,  7.218333 ,
        7.63921  ,  4.6319413,  4.1119967,  3.8002882,  1.6070746,
        2.9838526,  2.111497 ,  4.4438844,  1.6642075,  3.7858262,
        4.4047527,  2.7633986,  3.3221748,  3.2866986,  7.556958 ,
        4.535194 ,  3.6258783,  1.691911 ,  1.8917559,  5.196031 ,
        6.5251894,  7.165607 ,  3.2666345,  0.9971396,  5.98469  ,
        3.914972 ,  9.081181 ,  5.421821 ,  4.644881 ,  1.4258218,
        4.243215 ,  5.648267 ,  5.5778027,  5.766635 ,  3.4066985,
        4.1500063,  5.2154036,  1.6245475,  7.0276527,  7.408307 ,
        4.3379965,  3.2187986,  4.7431693,  7.0207014,  3.3810294,
        6.343066 ,  3.4736795,  2.54336  ,  3.2016404,  3.006257 ,
        2.2536473,  3.5833066,  3.0315213,  2.4126549,  2.8083522,
        4.462643 ,  1.0768806,  2.9073348,  4.1907754,  1.4848826,
        4.1700563,  4.210849 ,  5.008408 ,  4.4007897,  0.9195906,
       13.451619 ,  6.008574 ,  6.3843803,  2.4561477,  1.4853356,
        8.640095 ,  4.4962254,  3.947177 ,  3.911287 ,  5.149393 ,
        4.626918 ,  4.0790915], dtype=float32), array([ 1.88725686e-03,  6.98630372e-03, -1.73663944e-02, -7.18654459e-03,
       -1.22787217e-02,  1.09434605e-03,  6.44800859e-03, -2.53017526e-02,
       -2.18565715e-03, -1.12002632e-02,  1.05986698e-02,  1.31691312e-02,
        3.53413001e-02, -1.05294297e-02,  4.76091355e-03, -1.08841127e-02,
       -2.96970760e-03, -6.55895565e-04, -1.33434115e-02,  1.92407463e-02,
        8.82190710e-04, -2.45730439e-03, -1.22289890e-02,  6.97759632e-03,
       -2.34210547e-02,  7.27633014e-03, -3.87082109e-04, -1.81393244e-03,
       -4.67390614e-03, -2.07921769e-03, -1.07648205e-02,  1.71913318e-02,
        1.37479650e-03, -1.02521889e-02,  4.60050954e-03,  3.07205413e-03,
        5.55231608e-03, -1.81929599e-02,  7.88212102e-03,  7.97306001e-03,
       -1.55762769e-02, -8.16384330e-03, -5.33761922e-03,  5.42648369e-03,
       -4.60646162e-03,  3.97276506e-03,  6.94058929e-03, -5.25686331e-03,
        7.26182573e-03, -7.44402921e-03, -5.33822272e-03,  1.27032055e-02,
       -1.11977849e-02,  7.24925054e-03,  1.06015848e-02,  4.11643367e-03,
       -3.44693311e-03,  1.25023979e-03,  1.74989144e-03, -1.73056982e-02,
       -1.28604546e-02, -1.92512048e-03,  6.34812471e-03, -1.92162057e-03,
        1.30071081e-02,  1.02124671e-02, -8.26048199e-04, -4.36333241e-04,
       -1.13092847e-02,  5.42337401e-03,  3.73710203e-03, -8.91236961e-03,
        9.31883045e-03,  1.30654208e-03,  7.22426269e-03, -1.60013893e-04,
       -1.14245433e-02, -6.76241610e-03,  6.15182286e-03,  1.38494670e-02,
        6.71736058e-03,  2.69761775e-03, -1.97327994e-02, -1.53732793e-02,
       -2.89366357e-02,  3.95712862e-03, -3.25207948e-04,  1.12228738e-02,
       -2.99885846e-03, -1.00649446e-02,  7.21610710e-03, -5.56699792e-03,
        9.26739909e-03,  2.22352799e-03, -1.06036216e-02,  8.43027234e-03,
       -8.14293139e-03, -2.74852756e-02,  9.58687998e-03,  4.07187734e-03,
        1.98222622e-02, -1.72322076e-02,  4.73829033e-03, -1.39609119e-02,
       -1.51647972e-02, -1.15223499e-02,  1.12825083e-02, -1.18595818e-02,
       -9.43526346e-03,  4.31898749e-03, -5.09122852e-04, -7.13409018e-03,
       -1.32802967e-02, -1.71752833e-02, -7.06628338e-03, -5.12971776e-03,
       -1.32141160e-02,  1.06060226e-02,  1.34018641e-02,  1.81618482e-02,
       -1.38999559e-02, -5.53209847e-03,  1.23222582e-02, -1.24536110e-02,
       -1.50080808e-02, -1.04619237e-02, -3.59556219e-03,  9.83668026e-04,
       -5.97180938e-03, -1.61398749e-03,  2.81569944e-03, -8.95867962e-03,
       -1.06915412e-02, -1.02662100e-02,  1.20214215e-02,  1.50800049e-02,
       -5.84884314e-03,  6.95659779e-03,  7.56148016e-03, -8.98819882e-04,
       -5.24863740e-03, -1.39835635e-02,  3.62608884e-03, -2.57264338e-02,
       -2.94597307e-03,  2.91288190e-04,  5.92333311e-03,  2.83100433e-03,
        4.75607318e-04,  1.04836039e-02, -5.52946562e-03,  5.05966088e-03,
       -1.35795567e-02,  3.66660068e-03,  7.83330295e-03, -4.51153889e-03,
        6.04162225e-03,  1.81268528e-02,  2.12979736e-04,  6.17571501e-03,
       -1.10703269e-02,  6.44078059e-03,  5.60202030e-03, -1.61168948e-02,
       -3.89699033e-03, -7.24032149e-03,  6.31146226e-03, -8.66204593e-03,
        6.93808217e-03,  9.06099658e-03,  6.63069636e-03, -1.71758868e-02,
       -9.16746911e-03, -1.75559558e-02, -1.45309875e-02,  1.56035845e-03,
        1.92475156e-03, -1.75455436e-02, -1.84851617e-03,  4.78310185e-03,
        7.32350908e-03,  7.78063317e-04, -6.82937866e-03,  2.18800013e-03,
       -8.59961566e-03, -8.48268345e-03, -5.56802377e-04, -4.88256570e-03,
       -2.69361371e-05,  4.64721490e-03,  1.20891463e-02,  1.93943537e-03],
      dtype=float32), array([ 0.7518693 , -0.8061395 , -0.46274498, -0.8788531 , -0.47951293,
        0.3288616 , -0.07648916, -0.47499892, -1.018365  , -0.9713176 ,
        1.0663884 , -0.23977   , -0.47158787, -0.9069614 ,  1.1646607 ,
        1.2671727 ,  0.65037286, -0.4511689 , -0.70894337,  0.16285987,
       -0.5708618 , -0.83520114, -1.0668063 , -0.5384207 ,  1.8327824 ,
       -1.4308021 ,  0.36140093, -0.0424003 , -1.471843  , -0.5401186 ,
        0.40379754, -1.2408417 , -0.9117514 , -0.8254509 , -0.47816128,
        0.9841434 ,  0.00253757, -0.47529504,  0.19763397,  1.2314514 ,
        0.37436342, -0.73816633,  0.13180584, -1.0401244 , -0.6208278 ,
        0.44443524, -0.43879735, -0.65804935,  1.0481974 ,  0.44587484,
        1.1614735 ,  0.3774821 ,  0.01587516,  0.3470699 , -0.56087965,
       -0.34118134,  1.381107  , -1.1749039 , -0.60278744, -0.08338054,
        0.33653837,  0.57773125, -0.13288347,  0.14523335, -0.44651344,
        0.724053  , -0.09330254, -0.12113906,  0.92216307, -1.3753234 ,
       -0.00747469, -0.92356837,  0.5771498 ,  0.48071927,  0.43583182,
       -0.43518588, -1.1879648 , -0.6491919 , -1.1824024 ,  0.18291634,
       -0.22746487, -0.65463424, -1.1616986 , -0.36778823, -1.1959616 ,
        0.7630663 ,  0.187761  ,  0.6907459 ,  0.16494125,  0.19620268,
        0.01300585, -1.2154126 , -0.5197349 , -1.1613296 ,  0.22354877,
       -1.1799432 , -1.3134693 ,  0.47616082,  0.71590453, -0.9335361 ,
        0.3166608 , -0.89121765,  0.29443458, -0.72485673, -0.12914343,
       -0.7345395 , -1.0859821 , -1.7974101 ,  0.33286425, -0.6909928 ,
       -1.0081465 ,  0.9955292 , -0.81833094,  0.09511903, -1.3731476 ,
        0.31639275,  0.42519507,  0.29934385,  0.3883779 , -0.9813644 ,
        1.4581326 , -0.66296595, -1.1043749 ,  0.9281117 ,  1.2882681 ,
        1.0572963 ,  0.9042716 , -0.7462016 , -0.44640687, -1.1355268 ,
       -1.168293  ,  1.0334609 , -0.5578192 , -0.82155395, -0.41140422,
       -0.01682923,  0.64629275,  0.9253608 ,  0.13509525, -0.5946254 ,
       -0.28072047, -0.87397665,  0.24936965, -0.7954401 , -0.7035809 ,
       -0.6006784 , -0.15534207,  0.8174923 ,  0.13844311, -0.21078722,
       -0.75614375, -0.32468137,  0.11029752, -0.9843491 ,  0.40846422,
       -1.1835141 , -0.2935799 ,  0.30514628,  0.77282196,  1.2086146 ,
       -1.0648794 , -1.6442229 ,  1.1105372 , -0.6015923 ,  0.27891672,
        0.40338653, -1.0946628 , -0.209855  , -1.3198125 ,  0.31924832,
        0.02081892, -0.2831575 , -1.0403031 , -0.88783073, -1.130785  ,
       -0.13602772,  0.01957619, -0.610866  , -0.68705505,  0.92817664,
        0.11191173,  1.1106138 , -0.8925205 , -1.0189792 , -1.2059814 ,
       -0.5513498 , -0.7818077 , -0.73552656, -0.48961014,  0.54407936,
        0.10413709, -0.45188236], dtype=float32), array([ 6.1287417,  3.9522235,  7.9764924,  6.1622615,  4.340907 ,
        5.253184 ,  5.600081 ,  2.8167741,  2.8939776,  5.0065336,
        6.5107503,  1.9687726,  7.626672 ,  7.521254 ,  7.2094746,
        3.798303 ,  8.885007 ,  3.8709092,  8.091887 ,  4.931999 ,
        4.7322273,  5.0085974,  5.144999 ,  9.532239 ,  4.413025 ,
       12.938842 ,  7.4063315,  2.1832554,  4.785442 ,  1.0713814,
        2.6616693,  7.154145 ,  7.453408 , 10.806983 ,  1.1281353,
       10.627621 ,  1.5904808,  3.4093096,  4.9612913, 15.737471 ,
        3.6654139,  1.8327496,  3.2467127,  4.3255053,  3.8436022,
        3.2305372,  2.8369398,  8.318263 ,  8.899173 ,  2.242322 ,
        5.383636 ,  2.9860213,  2.9107585,  4.820827 ,  0.876936 ,
        1.5320781,  4.4186597,  6.8056526,  3.0440292,  9.139893 ,
        3.1173737,  2.5028572,  2.369435 ,  4.053545 ,  3.1519449,
       13.48952  ,  2.3958337,  1.9221498, 12.084    ,  6.7966266,
        6.558335 ,  5.42168  ,  5.464329 ,  5.0548825,  3.744022 ,
        2.9941428,  4.439957 ,  5.5653253, 13.656677 ,  6.0430846,
        5.720138 ,  2.994783 , 17.398024 ,  3.3726594,  5.037309 ,
        7.515017 ,  1.3641683,  6.553861 ,  2.8192236,  6.2044787,
        6.714018 ,  3.1895266,  3.2898593,  6.08072  ,  3.1730347,
       10.273225 ,  6.202359 ,  1.7783747,  8.266915 ,  4.41557  ,
        6.5666513,  8.320088 ,  5.7786465,  6.9575386,  6.953149 ,
        5.1554427,  6.3134127,  3.6826167,  5.0344753,  6.934741 ,
        5.593837 ,  3.6969903, 12.737654 ,  4.998103 ,  6.511006 ,
        2.4709518,  2.354434 ,  5.655712 ,  4.4741926,  3.813201 ,
        7.1394567,  6.774674 ,  2.8123028,  3.8299794,  4.9793873,
       13.313431 ,  5.9230614,  7.0765834,  1.6762244,  6.8231463,
        3.3017046,  5.225212 ,  3.2442393,  9.30533  ,  7.6367016,
        6.147308 ,  3.3239784,  5.2238607,  6.541331 ,  2.6473522,
        0.7975357,  6.9389873,  1.7275933,  6.3960648,  2.5558982,
        3.8399596,  4.6013947,  5.454419 ,  2.5075846,  5.049463 ,
        3.4019642,  3.3706057,  5.1810565, 11.115068 ,  8.565268 ,
        7.1100636,  4.575513 ,  5.417001 ,  6.000118 ,  7.269904 ,
       11.798605 , 12.325768 ,  4.872804 ,  5.2156496,  7.5099826,
        2.2152183,  8.086402 ,  8.89313  ,  7.899286 ,  8.712362 ,
        3.7748857,  6.260932 ,  1.5715755,  3.1865869,  3.58046  ,
        2.6356823,  3.123011 ,  6.770857 ,  2.4362953,  5.5359817,
        6.541681 ,  5.658362 ,  3.7103088,  4.8092027,  2.76497  ,
        1.5215257,  6.5974274,  3.4812238,  1.3086158, 10.144207 ,
        8.926771 ,  4.716878 ], dtype=float32), array([-0.00124973, -0.00193576, -0.00126558, -0.00235353, -0.0050186 ,
        0.0013602 , -0.00499787, -0.00831186, -0.00303504,  0.01763663,
       -0.00969972,  0.00799537,  0.03434343,  0.0035955 ,  0.00166067,
       -0.00971638,  0.00686589,  0.01115107,  0.01837805,  0.00619113,
       -0.00663676,  0.01434136,  0.00092635, -0.02022405, -0.00445751,
        0.00605558,  0.01594218, -0.02780133, -0.00409375,  0.00920364,
       -0.00865556, -0.02023049, -0.00142263,  0.00336262, -0.00598738,
       -0.00427931, -0.01714894, -0.0139935 ,  0.00403299,  0.01719928,
        0.00342203, -0.00536404,  0.01564001, -0.00502332,  0.00798141,
       -0.00199325,  0.0025199 ,  0.0063563 ,  0.01184061, -0.00785513,
       -0.02452838,  0.00322147,  0.00075766,  0.01718008,  0.00688805,
        0.00062647, -0.00511714, -0.00383844, -0.00127636, -0.00925502,
       -0.01579362, -0.01321684, -0.00345154, -0.02070131, -0.00473714,
        0.0007881 ,  0.00350632, -0.00726073,  0.00207335, -0.00500932,
       -0.0008716 , -0.00524319, -0.00499043,  0.00337133, -0.01325974,
       -0.00691552,  0.00067844,  0.00141881,  0.01246816,  0.0051837 ,
       -0.00386724,  0.00225083, -0.01792764, -0.01035284, -0.00380708,
       -0.01136481,  0.00260594,  0.00575939, -0.01041878, -0.00123137,
        0.00784436, -0.0208009 ,  0.00025585, -0.00233332,  0.0168048 ,
        0.00289487, -0.00952167,  0.00310957, -0.01677198,  0.01407272,
       -0.00605816, -0.00017935,  0.0155064 ,  0.00243646, -0.01043399,
       -0.01690535,  0.00530708,  0.00634482,  0.00325156, -0.00344885,
        0.00355713, -0.00190464, -0.0055193 , -0.02301254,  0.00624415,
        0.00631191,  0.00830141, -0.0027222 , -0.01553198,  0.02317404,
        0.00194382,  0.00171257,  0.00682993,  0.00794732, -0.00395421,
       -0.01295551,  0.00491376, -0.00043467,  0.00308729,  0.00648555,
        0.00567338,  0.00546992,  0.01044629,  0.00625588,  0.00199689,
        0.00049659, -0.00017923, -0.00460413,  0.00075278,  0.01123551,
       -0.00049077,  0.00950551, -0.01118116, -0.0027497 ,  0.00425621,
       -0.00592889, -0.00700535, -0.01165587,  0.0302906 , -0.0033668 ,
        0.00040201, -0.01176814,  0.00384745,  0.00320675, -0.00140577,
       -0.00942827, -0.0103242 ,  0.0008155 ,  0.00017862, -0.00343742,
        0.00913436,  0.01096703, -0.00408937,  0.00592564, -0.00357131,
       -0.00122248, -0.01503638,  0.01165334,  0.00340794, -0.00719104,
       -0.00814658,  0.00860717, -0.01797504,  0.01159968,  0.00536726,
       -0.00413884, -0.02305284, -0.01102517,  0.01113136,  0.00037236,
       -0.00819135,  0.01054648,  0.0004178 , -0.01614055, -0.01206275,
       -0.00125288,  0.00843411, -0.02725394, -0.0025166 , -0.00509552,
       -0.01801429,  0.01279841], dtype=float32), array([-0.5423521 , -0.41520354,  0.81961864,  0.57318306, -0.84542274,
        1.0737913 , -0.27467865, -0.42057163,  0.6142938 ,  0.86911964,
        0.64794797,  0.97436315, -0.40280312, -1.4083767 ,  0.11218396,
        0.27121785, -0.06568512, -0.42001292, -0.38007194, -1.4432507 ,
        0.06281555, -0.56009394, -0.20256649, -0.8382601 , -0.54690343,
       -0.20190191, -0.66225666,  0.42772993,  0.3521547 , -1.2959481 ,
        0.07912298, -0.78808737,  0.2769035 , -0.41769767, -1.09768   ,
       -0.0366591 , -0.736635  , -0.7963297 ,  0.03080699, -0.62425363,
       -0.83039826,  0.6650182 , -0.9469947 ,  1.1232427 , -0.5461457 ,
        0.6899395 ,  1.0478833 ,  0.17071801, -0.29504102,  0.2112868 ,
        1.2036848 , -0.98385143,  0.8650841 , -0.18741189,  0.26063842,
        1.012607  ,  0.8858157 ,  0.31929198, -0.80209565, -0.73332745,
       -0.45781964, -1.3860198 , -0.4010129 , -0.73594135,  0.5925951 ,
       -0.18702592, -0.9748278 , -0.01118067,  0.4437204 , -0.77114946,
       -0.25790128, -0.69171673,  0.6528531 , -0.88904583, -0.69154745,
       -0.3638728 ,  0.41700637, -0.651099  , -0.27568868, -0.59661716,
        1.0070012 ,  0.6069865 , -0.6552875 ,  1.2388198 ,  0.44671217,
       -0.8386506 ,  0.7376015 ,  1.4033855 ,  1.1384703 ,  0.33342347,
        0.40310746,  0.47686514, -0.7151949 , -0.5453274 , -1.0092055 ,
       -0.8125207 , -0.13906313,  0.39906257,  0.07257119, -0.7695432 ,
        0.8216445 , -0.46539277, -1.2924557 ,  0.7895942 , -0.5574132 ,
       -0.8454456 , -0.63825893,  1.1475893 , -0.33033323, -0.63181114,
        0.2702035 ,  0.6826811 , -0.2551967 ,  0.7774018 ,  0.56598985,
       -1.1225249 , -0.50326365, -1.0265695 ,  0.7253186 ,  0.60531694,
        0.7473056 ,  0.03368555, -0.84424   , -0.9253836 ,  1.0704114 ,
       -0.10765918,  0.13310874,  0.06497032,  0.6153161 , -0.834817  ,
        0.9539447 , -0.3903181 , -0.42996463, -0.9514004 , -0.20476693,
       -0.25008878, -0.9492301 ,  0.2780596 , -0.5995759 , -0.22636864,
       -0.35377443,  1.231515  , -0.2821892 ,  0.27547395, -1.3249927 ,
        1.2040408 ,  0.88786185,  0.37764335, -0.65299636,  0.64549947,
        0.28103733,  0.271022  , -0.20030382, -0.23641327, -0.48509067,
       -0.9865508 , -0.12014478,  0.04426565, -0.55853885,  0.55851614,
        0.59363395, -0.6469128 , -0.11281493, -0.02432661,  0.43363816,
       -0.343078  , -0.60432637, -0.68196005,  0.26106796,  0.99672264,
        0.24916899, -0.09161891,  1.3171947 , -0.5073657 , -0.5621028 ,
        0.03413295, -0.48972487,  0.5089213 ,  0.09473382, -0.15023963,
        0.27939218, -0.7162638 ,  1.1785868 , -1.1293417 , -0.9494879 ,
        1.1202499 , -0.38148588,  0.30067447, -1.5591784 ,  0.13572483,
       -0.10854885,  0.19498818], dtype=float32), array([0.8445583 , 1.7331866 , 2.5071611 , 1.1092263 , 3.2090719 ,
       2.5268924 , 1.8180708 , 1.7479197 , 3.6360106 , 2.777038  ,
       3.7402737 , 2.510552  , 2.1037867 , 4.2893376 , 1.8404799 ,
       2.901738  , 1.7334516 , 1.1254227 , 1.405666  , 3.3181596 ,
       2.0425775 , 2.6312687 , 1.4310205 , 2.4851213 , 1.5348909 ,
       0.8433905 , 4.1993065 , 2.5009894 , 1.0918633 , 4.4945493 ,
       2.1199875 , 1.439859  , 6.39674   , 3.8021698 , 5.2544327 ,
       1.6961842 , 2.163823  , 2.0946574 , 3.8400404 , 2.8985875 ,
       1.4096062 , 5.659899  , 2.3012247 , 4.903192  , 2.6355848 ,
       1.3991827 , 2.7574239 , 0.99731225, 1.3539947 , 1.343629  ,
       3.782247  , 4.3750453 , 3.844279  , 2.4246645 , 1.616853  ,
       4.323107  , 5.0906224 , 1.3119988 , 1.4500349 , 4.2607923 ,
       3.1508477 , 4.533531  , 1.1085457 , 2.9861727 , 3.2784028 ,
       5.0296054 , 3.177173  , 3.5036259 , 4.0599284 , 1.7602396 ,
       1.5604333 , 3.9829562 , 1.6333984 , 4.387819  , 2.0260277 ,
       3.9050577 , 1.803562  , 2.4898577 , 3.110892  , 5.173323  ,
       1.2266853 , 1.7688994 , 3.5217764 , 5.5321593 , 1.5849444 ,
       1.5302885 , 1.5751638 , 1.5433631 , 5.221738  , 2.455549  ,
       1.631476  , 1.3726152 , 4.527407  , 1.3432319 , 3.5391726 ,
       3.9526072 , 2.5442114 , 3.68286   , 1.6765461 , 1.8602412 ,
       7.537559  , 1.3282593 , 2.5364099 , 1.7206519 , 4.197871  ,
       3.108909  , 1.4010589 , 3.1572511 , 2.4035113 , 1.6192319 ,
       1.995516  , 3.5522535 , 1.6859916 , 2.4184678 , 4.212203  ,
       3.8158767 , 1.6150808 , 3.00462   , 2.1272438 , 3.5262406 ,
       2.592924  , 0.9288995 , 2.9176006 , 3.0113049 , 5.041013  ,
       0.52631706, 2.705554  , 2.591528  , 2.459328  , 3.2117603 ,
       4.549436  , 4.5299244 , 2.6615388 , 2.743075  , 2.8763747 ,
       1.9842786 , 2.849849  , 1.7668225 , 2.0548956 , 1.7268265 ,
       1.5770417 , 5.0485544 , 4.932581  , 2.3351731 , 3.2891915 ,
       4.678341  , 4.926114  , 3.2221763 , 2.1681702 , 1.6616536 ,
       2.0949683 , 1.2173138 , 0.8364168 , 1.1594788 , 4.582925  ,
       2.0968082 , 2.336597  , 1.8007157 , 1.4879866 , 1.9982917 ,
       1.4529537 , 1.4837959 , 1.3050288 , 3.035427  , 2.1504748 ,
       4.1323256 , 2.5228903 , 3.1308942 , 2.934222  , 2.0546916 ,
       2.54563   , 2.0431628 , 4.1558814 , 2.019526  , 2.3577259 ,
       4.22813   , 1.504147  , 3.4093423 , 3.1413982 , 3.0362089 ,
       5.640681  , 2.6888697 , 4.6364493 , 2.9848225 , 3.4386108 ,
       4.5514383 , 2.2420619 , 5.0105405 , 3.7115314 , 2.3560288 ,
       2.5029278 , 1.707876  ], dtype=float32), array([[[[-0.05545479, -0.04390881,  0.01388725, ..., -0.06328062,
           0.01608308,  0.00248999],
         [ 0.04640123,  0.04128823, -0.06276444, ...,  0.0597081 ,
          -0.00047749, -0.01852264],
         [ 0.07113513, -0.06114135, -0.07038505, ...,  0.01657685,
           0.03110254, -0.01659633],
         ...,
         [ 0.00606977,  0.05230253, -0.03612352, ...,  0.04429632,
          -0.03779654,  0.08172933],
         [-0.01438248, -0.03878702,  0.02121054, ...,  0.02982245,
          -0.03797321, -0.00031924],
         [ 0.01507946, -0.04968549,  0.02452218, ..., -0.0792592 ,
           0.06220905, -0.07076856]]]], dtype=float32), array([ 8.76433589e-03,  2.77513545e-03,  3.40635353e-03, -3.60490642e-02,
       -1.02289312e-03,  3.34076285e-02, -3.00150327e-02,  2.89406236e-02,
       -8.50388315e-03, -4.45149466e-03,  1.11047616e-02, -4.61832620e-03,
       -1.27502962e-03, -7.57695735e-03, -1.15421126e-02, -8.75471625e-03,
       -4.11339384e-03,  3.65830725e-03,  9.80839040e-03,  1.81623772e-02,
        3.40062659e-03, -1.00337192e-02,  2.79260986e-02,  1.64499301e-02,
        3.97287495e-03, -2.98979059e-02, -1.25598572e-02,  7.08619878e-03,
        8.01330805e-03, -1.91324251e-03, -9.43568815e-03,  3.42101674e-03,
       -1.52401906e-02, -3.44457780e-03,  2.01272615e-03, -1.25878509e-02,
       -1.69524942e-02, -3.23544745e-03,  2.93127466e-02, -8.91724695e-03,
       -2.67273504e-02, -4.34190780e-03, -3.02715995e-03, -3.29572894e-03,
        1.71445124e-02, -2.37969700e-02, -8.73228349e-03, -2.28398107e-02,
       -1.78471748e-02, -1.26390336e-02, -3.08869570e-03,  3.42776068e-03,
       -2.53855772e-02,  5.35203097e-03,  7.98271224e-03, -1.17431618e-02,
       -1.70909390e-02,  1.51484851e-02,  8.83320998e-03,  7.37476489e-03,
        8.18518549e-03,  1.45674692e-02,  1.80987455e-03, -7.82904774e-03,
       -2.51431186e-02, -1.01911072e-02,  3.36094038e-03, -1.15214596e-02,
        7.06992950e-03, -1.13235740e-02, -2.01301556e-02,  1.26257248e-03,
        3.89495934e-03,  2.10457221e-02, -6.50177104e-03,  1.84085760e-02,
        4.90241162e-02,  3.54028831e-04, -1.03774872e-02, -7.13344477e-03,
        1.30606424e-02, -1.41834123e-02, -3.75178014e-03, -1.56815946e-02,
       -1.30081931e-02, -3.23548131e-02, -5.89977019e-03, -3.97661095e-03,
        4.28610258e-02, -2.60211229e-02,  4.52328427e-03,  2.09527346e-03,
       -4.24554525e-03,  6.73982268e-03, -1.45480465e-02,  1.63797643e-02,
       -1.46520762e-02,  9.49733146e-03,  3.56680937e-02,  3.36281862e-03,
        2.90683117e-02, -2.60345917e-03,  1.37141813e-02, -9.33638122e-03,
       -1.12604341e-02,  7.13181077e-03, -1.34930871e-02, -2.72265775e-03,
        1.61045864e-02, -5.44170383e-03, -1.53932869e-02,  1.14692086e-02,
        4.69140988e-03,  7.23933626e-04,  2.21882612e-02,  9.09953937e-03,
        2.10370440e-02, -1.05554750e-02, -4.96352790e-03,  1.52745354e-03,
        2.24027354e-02,  4.47020633e-03,  7.10720103e-03,  2.28591114e-02,
        5.57755399e-03, -1.85176991e-02,  1.38629442e-02, -7.39570707e-03,
        2.00700574e-02, -7.01259403e-03,  4.16394370e-03,  8.70224927e-03,
       -4.14075237e-03,  1.03427703e-02, -5.16123185e-03,  1.72338053e-03,
        9.65406932e-03, -2.67072227e-02, -7.81734940e-03,  1.22368429e-02,
       -1.33190642e-03,  4.74286499e-03, -6.20662933e-03, -8.16846825e-03,
        1.61763132e-02,  2.55641285e-02,  6.20006444e-03, -2.43829587e-03,
       -1.26147252e-02, -4.99769486e-03,  2.46589333e-02,  9.62738850e-05,
       -1.45653207e-02,  2.66765933e-02, -3.93280713e-03, -9.41057503e-03,
        1.35640870e-03, -3.57030593e-02,  1.05149858e-02,  1.16214226e-03,
       -3.64932814e-03, -1.35212485e-02, -2.06338875e-02,  1.46417404e-02,
       -1.11588202e-02,  5.09430887e-03, -8.73144157e-03,  1.32910609e-02,
        5.26476512e-03, -1.58239137e-02,  8.83410312e-03,  2.07840949e-02,
        2.28825700e-03, -3.96540426e-02, -5.39739011e-03, -2.81341840e-03,
        9.53769311e-03, -1.23469438e-02,  3.47092142e-03,  1.09998528e-02,
        1.98215451e-02,  5.31807914e-03, -1.59999914e-02,  1.98282413e-02,
        2.26678420e-02,  9.34647396e-03,  2.99120862e-02,  1.10314395e-02,
        2.31101085e-03, -7.15976441e-03, -8.15680251e-03, -8.29264801e-03],
      dtype=float32), array([ 0.9941311 ,  0.9503802 , -0.4910988 , -1.5580704 ,  0.22461775,
        0.19761305,  0.7219524 ,  0.25678933,  0.82305276,  0.5677236 ,
        0.09190767,  0.21238264, -1.1983813 ,  0.7705448 ,  0.13945098,
        0.09969908,  0.42782584, -0.81255066, -0.64644825, -0.66728765,
       -1.236081  ,  0.93193275, -0.16169716, -0.06165726,  0.3399942 ,
       -0.5681119 , -0.91606337, -0.21079598,  0.28867033,  0.42070088,
        0.2956076 , -0.6265427 ,  0.64264566, -0.57508796, -1.1641182 ,
       -0.05944777, -0.0831002 ,  0.23915003, -0.07358221,  0.69437075,
        1.312434  ,  0.01251102,  0.9595999 , -0.04451707, -0.84837544,
       -0.05145153,  0.10195541,  0.6959691 ,  0.8016517 ,  0.73821265,
        0.61294186, -0.09199455, -0.04033622,  0.87191474, -0.9056685 ,
       -1.3698336 ,  0.37103155, -1.075228  ,  0.09711804,  0.5461859 ,
       -0.2834693 , -0.79436046,  1.093017  ,  0.97203255,  0.671418  ,
        0.5468156 ,  0.78196746,  1.1715869 ,  0.40876967, -0.5551538 ,
       -0.3898965 , -1.1069428 , -0.03402971, -0.84081346,  1.1150687 ,
       -0.8117777 , -0.274663  ,  0.212889  ,  0.1897027 , -0.7798721 ,
       -0.1782757 ,  0.6722477 ,  0.56012934, -0.28495488,  0.8147944 ,
       -0.08147524, -1.1433479 ,  1.1724259 , -1.3264704 ,  0.56086516,
        0.12111376,  0.0135878 , -0.4201597 , -0.98600847,  1.1349175 ,
       -0.01851886,  0.8056341 , -0.21952735,  0.08279336, -0.24536364,
       -0.50347775,  1.1588142 , -0.84521466, -0.3887009 , -0.7498792 ,
        0.59285486,  0.3435804 ,  0.89942616, -0.05350105,  1.043946  ,
       -0.5362973 ,  0.24585627, -1.2750663 , -0.73230135, -0.3726703 ,
        0.31234366,  0.6695342 , -0.53060454,  0.5357256 ,  0.28611022,
        0.49643248,  1.1815642 ,  0.6158798 , -0.4372335 , -1.5314125 ,
       -1.4182119 ,  0.61369616,  0.18555072,  0.2388732 ,  0.38257816,
       -0.5446834 ,  0.1601193 ,  1.0089823 , -1.6289227 , -0.5170461 ,
        0.04970785, -0.16723719,  1.3665032 , -0.74789536, -0.5419027 ,
        0.62312776,  0.11828215, -0.11293101,  0.5389056 , -0.17276333,
        0.21662115, -0.17797238, -0.5432521 ,  0.18105449, -0.38686308,
       -0.5584604 , -0.99370974, -0.71529245, -0.94430006, -1.0076904 ,
       -0.40376246,  0.48787096, -0.7292255 ,  0.45994684,  0.9378548 ,
        0.50523615, -0.51916915, -0.02878891,  0.6523798 ,  0.23932539,
       -0.8431573 , -0.7718216 , -1.0272686 ,  0.27142954, -0.58256024,
        0.65165013,  0.15191185, -0.82055736,  0.66684073,  0.3163264 ,
       -0.3358971 , -1.4956554 ,  0.42872602, -0.5528648 ,  0.64270306,
        0.36523783,  0.49901912,  1.0162221 , -0.23500237,  0.3105293 ,
       -0.13112585,  0.28001097, -0.5603265 , -0.54684484, -0.6771429 ,
       -0.19023724,  0.11990127], dtype=float32), array([8.678871  , 6.135328  , 2.2632005 , 2.982063  , 3.055766  ,
       4.664331  , 2.2421837 , 5.7858067 , 6.491686  , 2.2719908 ,
       4.6416903 , 1.7692384 , 3.2257411 , 4.716489  , 1.6747222 ,
       5.5950546 , 2.6093183 , 7.3716717 , 2.7839446 , 4.691313  ,
       2.7668238 , 5.377259  , 1.6570259 , 1.3571877 , 2.8550313 ,
       3.9144409 , 7.058012  , 2.5553546 , 1.2239578 , 4.5946765 ,
       2.5315955 , 2.5191624 , 9.149261  , 3.031636  , 3.0524364 ,
       3.2285116 , 1.9071726 , 4.8499885 , 2.5274103 , 2.8730454 ,
       5.9744515 , 1.4159234 , 5.832361  , 2.0437598 , 2.4645162 ,
       5.2833977 , 6.5740213 , 2.4997976 , 1.3476269 , 3.0052679 ,
       6.2223916 , 1.8430713 , 1.7409587 , 2.3529077 , 3.1006486 ,
       2.4728065 , 6.182764  , 3.9658704 , 1.978486  , 2.0409076 ,
       3.7471693 , 3.9653184 , 7.17798   , 2.7060165 , 3.1580884 ,
       1.7514223 , 5.0633383 , 7.899221  , 4.682329  , 4.143457  ,
       3.9624803 , 3.997954  , 1.6743231 , 6.4796686 , 3.8646338 ,
       6.761492  , 2.9136734 , 1.2589514 , 4.3074574 , 2.467582  ,
       5.2076583 , 0.7967015 , 6.1377544 , 3.018872  , 2.2077446 ,
       4.432544  , 5.833329  , 5.1106844 , 4.5831637 , 1.9589535 ,
       6.9178743 , 1.7004575 , 4.4447937 , 2.8092754 , 5.649024  ,
       2.6718256 , 6.194736  , 2.452953  , 3.0464566 , 2.8473248 ,
       5.09864   , 7.374482  , 4.1808686 , 4.071657  , 1.2206402 ,
       5.440777  , 2.7727394 , 1.92601   , 2.927199  , 2.9435978 ,
       4.1775355 , 4.402208  , 1.7211742 , 6.839695  , 2.365883  ,
       0.978677  , 5.1200886 , 1.8335336 , 1.7996349 , 1.3939532 ,
       2.8254468 , 7.953429  , 1.6499604 , 2.2968462 , 3.191812  ,
       7.8094697 , 3.3291237 , 1.3712502 , 3.326629  , 3.082187  ,
       3.5020297 , 0.87985396, 7.572069  , 5.4895787 , 5.5766463 ,
       2.383616  , 1.730064  , 2.8762429 , 1.8141289 , 1.6021651 ,
       5.1028085 , 4.5158987 , 1.7565224 , 1.4250928 , 5.0028396 ,
       3.1051264 , 5.2478642 , 3.8582695 , 1.821112  , 5.101054  ,
       4.490712  , 4.0994115 , 3.7896762 , 4.875241  , 2.377776  ,
       6.5199375 , 3.7871554 , 2.7749195 , 3.8323874 , 7.5047784 ,
       1.5426193 , 4.775318  , 0.9731239 , 4.0098677 , 5.8226247 ,
       5.52241   , 2.4487734 , 2.7592752 , 1.0391679 , 2.726803  ,
       4.3520284 , 4.2918873 , 5.915161  , 3.816213  , 2.3679812 ,
       1.9354415 , 3.7922685 , 2.1235518 , 2.048111  , 4.8792624 ,
       3.0333421 , 6.5987754 , 5.998685  , 2.8665593 , 1.928785  ,
       2.6488268 , 1.1623031 , 1.1058058 , 6.1729627 , 6.9350944 ,
       6.3560452 , 2.6392262 ], dtype=float32), array([[[[ 4.60211858e-02,  4.02420126e-02, -1.70047279e-03, ...,
          -1.97190251e-02, -4.59118038e-02,  2.78275330e-02],
         [-3.82682383e-02,  1.90542024e-02,  1.10280132e-02, ...,
           1.73187405e-02, -1.16720831e-03, -3.11615923e-03],
         [-1.45799937e-02, -4.49858460e-04,  3.10862418e-02, ...,
           1.11784050e-02,  8.50491319e-03, -3.01224738e-02],
         ...,
         [ 1.95374992e-02, -2.89938841e-02, -2.27398481e-02, ...,
          -3.41841392e-02,  1.73640449e-03,  2.45961510e-02],
         [-2.23113336e-02, -1.09898513e-02,  4.10703272e-02, ...,
           6.63607521e-03, -1.00139445e-02,  1.32465791e-02],
         [ 4.11511809e-02, -6.67610299e-03, -3.75688635e-02, ...,
           4.35911417e-02,  4.77914661e-02, -1.95401628e-02]]],


       [[[-2.81893797e-02,  1.13704251e-02, -1.89921632e-02, ...,
          -2.41092383e-03, -3.03865001e-02, -3.30073163e-02],
         [-1.09938849e-02,  3.54874507e-02,  2.17982680e-02, ...,
          -2.38698497e-02, -7.04959482e-02,  1.22864377e-02],
         [-3.88111779e-03,  5.37862703e-02,  2.66821380e-03, ...,
          -2.59846076e-02,  2.29151398e-02, -3.07643786e-02],
         ...,
         [ 1.33799470e-03, -1.75875314e-02,  2.69958042e-02, ...,
          -6.03693724e-03, -1.88847911e-02,  4.50144447e-02],
         [ 3.36030335e-03,  3.89857031e-02, -1.08284857e-02, ...,
           3.83796170e-02,  1.42671186e-02,  6.67979941e-03],
         [-1.94511097e-02,  7.14819832e-03, -1.37719717e-02, ...,
           8.41681194e-03,  3.25419605e-02,  1.95750897e-03]]],


       [[[ 3.16053629e-02, -2.27981918e-02,  4.43479279e-03, ...,
           3.06664854e-02, -6.08379915e-02,  1.42187728e-02],
         [-9.23177972e-03, -2.44574491e-02,  2.74394955e-02, ...,
           1.85974427e-02, -1.32877296e-02,  3.02231926e-02],
         [-6.78205676e-03, -3.31469215e-02,  1.45465117e-02, ...,
           1.12779392e-02,  3.38159502e-02, -1.82729736e-02],
         ...,
         [-2.96077859e-02, -1.97614897e-02,  3.34035307e-02, ...,
           3.51164397e-03, -1.56879835e-02, -1.56299993e-02],
         [-2.07312610e-02, -2.34671868e-03,  2.41973121e-02, ...,
          -1.05485395e-02,  6.91248104e-03, -2.26496905e-02],
         [ 1.49879577e-02, -8.54514912e-03, -2.71699820e-02, ...,
          -2.96653551e-03,  2.73845326e-02, -3.25062349e-02]]],


       ...,


       [[[ 5.87462040e-04,  6.25815446e-05,  2.73458380e-02, ...,
           2.64965538e-02, -3.63452211e-02,  1.29065737e-02],
         [ 4.16118931e-03, -3.46253850e-02, -1.96829420e-02, ...,
           4.02696393e-02, -4.43917550e-02,  4.12732325e-02],
         [-1.21215805e-02, -2.59629358e-02,  1.59307476e-02, ...,
           3.02059632e-02,  5.87397926e-02,  2.21458235e-04],
         ...,
         [-4.89975102e-02, -5.24172634e-02,  1.00310445e-02, ...,
          -5.18137030e-02, -2.29912177e-02, -2.68608835e-02],
         [-2.09858529e-02, -4.90914807e-02, -2.06652246e-02, ...,
          -2.80301478e-02,  3.30407210e-02, -2.00211513e-03],
         [ 5.13051264e-02, -6.20493153e-03, -1.30685875e-02, ...,
          -1.06996698e-02,  5.33069149e-02,  3.59026901e-02]]],


       [[[ 1.87485591e-02, -2.72215046e-02,  1.34164048e-02, ...,
           2.68518273e-02,  2.76317876e-02, -4.48899083e-02],
         [ 6.41742628e-03,  3.45763899e-02, -2.92433668e-02, ...,
          -1.96404960e-02, -8.57656915e-03,  2.85702944e-02],
         [ 1.68993883e-02,  4.79418552e-03,  1.70261860e-02, ...,
          -1.23229157e-02,  1.21128303e-03,  4.85126395e-03],
         ...,
         [-3.43342423e-02,  3.98451090e-02, -1.86698940e-02, ...,
          -4.07721411e-04, -3.87889296e-02,  2.44712234e-02],
         [-4.28344831e-02, -1.55720152e-02, -3.66092734e-02, ...,
           1.64331775e-02, -2.88856588e-02, -4.01013009e-02],
         [ 5.50202541e-02, -2.81692836e-02,  1.98143185e-03, ...,
          -2.25460231e-02, -1.17824711e-02, -1.11086629e-02]]],


       [[[-2.35207174e-02,  3.77133675e-02,  1.70468874e-02, ...,
           2.83529405e-02,  3.52344103e-02,  2.48968005e-02],
         [ 3.54232602e-02, -2.26334538e-02, -2.60876771e-02, ...,
           6.04085959e-02,  1.56556256e-02,  9.08973534e-03],
         [ 1.83857065e-02,  6.47004833e-03,  1.58253487e-03, ...,
           1.56918485e-02,  3.14289853e-02,  8.34840070e-03],
         ...,
         [ 1.03923967e-02, -1.39432820e-02,  3.91957723e-02, ...,
          -3.37445363e-02,  3.62184532e-02, -7.75552122e-03],
         [-2.78468709e-02,  1.76304188e-02,  2.41056848e-02, ...,
           6.64183730e-03, -2.67468505e-02,  2.16326173e-02],
         [-1.94339454e-02,  1.38642853e-02, -5.43052182e-02, ...,
          -1.36187412e-02,  3.90558280e-02,  3.32378969e-02]]]],
      dtype=float32), array([ 0.01519628, -0.0006479 , -0.01786545, -0.0008009 ,  0.00408644,
        0.00647623, -0.00933605, -0.00307516,  0.00633011, -0.00877337,
       -0.02089055, -0.01297298,  0.02010037,  0.02389369,  0.01062517,
       -0.01019587,  0.00463451, -0.00946289,  0.01217799, -0.01197419,
       -0.01518779,  0.01819112,  0.02443443, -0.01619556, -0.00434388,
        0.02658833, -0.01150272, -0.01837002,  0.01951808,  0.0078768 ,
       -0.00285447,  0.02913458, -0.00847422, -0.00860531, -0.01269868,
        0.0185553 , -0.02299521, -0.00900184,  0.01695731,  0.00915687,
        0.00212687, -0.00788658, -0.01339774, -0.00654894,  0.00713648,
       -0.00463686, -0.00634624, -0.00923592, -0.02206226, -0.02165046,
        0.00501865,  0.01680104,  0.01896946,  0.01418131,  0.02005183,
        0.00720855, -0.00420579, -0.00709047, -0.0016741 ,  0.00585467,
       -0.00180344, -0.00477215,  0.00030547, -0.00282109, -0.00554396,
        0.00107643,  0.02313093,  0.00405885,  0.01557621, -0.00271831,
        0.00962328, -0.02192452,  0.00838029,  0.00971577, -0.01504246,
       -0.0160922 ,  0.00209987,  0.0093626 ,  0.0063101 ,  0.00805112,
        0.00171286, -0.01032016,  0.00181703,  0.01486736, -0.01799832,
        0.01229286, -0.00449982,  0.00082837, -0.00877698, -0.00319985,
       -0.00503228,  0.01350456, -0.00093887, -0.01498251, -0.00700767,
        0.02196298, -0.0103951 ,  0.00107456, -0.00272821,  0.01595129,
       -0.00370163, -0.02440435, -0.0231149 , -0.0041741 ,  0.00121748,
        0.00828013, -0.01655607,  0.00795375, -0.00103363,  0.0014051 ,
        0.02570005,  0.00755406,  0.01246124, -0.01579492, -0.00876509,
        0.0234202 ,  0.00318705, -0.00574727,  0.01149659, -0.00512125,
        0.01157046,  0.03226664, -0.00686671,  0.01174797,  0.0297839 ,
       -0.00644357,  0.02351555, -0.01472966, -0.00501828, -0.00094954,
        0.00460861,  0.02703588,  0.00853512, -0.00870191, -0.00095077,
       -0.00332743,  0.01191341, -0.00857976,  0.00469571,  0.01120955,
        0.01067291,  0.00357372, -0.01613231, -0.02741554,  0.00561071,
        0.00395979,  0.01773447,  0.00553317, -0.02688496, -0.00815588,
       -0.00709649,  0.01423302,  0.00718257, -0.00933379,  0.0218029 ,
        0.00469691, -0.01223903,  0.01019963,  0.0087869 , -0.01148242,
       -0.00826856,  0.00403055, -0.00420363, -0.00404062,  0.01045072,
       -0.02001876, -0.00533646,  0.00304338,  0.00716131,  0.03041832,
        0.00339614,  0.01161516,  0.01067975, -0.00460728, -0.01797866,
        0.01532986, -0.00442903,  0.011905  , -0.00924968, -0.02163289,
        0.01216794,  0.02617801, -0.01712886,  0.00896274, -0.00606162,
        0.00711256,  0.00889875,  0.00700769,  0.00405399,  0.03433512,
       -0.00351081, -0.00994009], dtype=float32), array([ 1.39449906e+00, -5.78159869e-01,  1.26047647e+00, -1.11677885e+00,
       -1.05726683e+00,  1.43895209e+00, -1.21441996e+00, -4.71031815e-01,
       -1.26602560e-01,  9.11964238e-01,  7.69753993e-01, -5.99873006e-01,
        8.49646330e-01, -3.77781361e-01,  1.42203712e+00,  1.15386739e-01,
       -8.12712669e-01, -6.39684722e-02,  3.89376193e-01, -3.92033726e-01,
       -6.66236579e-01, -2.16793269e-01,  1.32659280e+00,  3.68163258e-01,
       -5.18189490e-01, -4.70130257e-02, -7.52253592e-01,  4.23275203e-01,
        4.84198064e-01,  1.32688677e+00, -8.16723883e-01,  1.62980235e+00,
        2.25731760e-01, -1.12954414e+00, -3.42141718e-01,  1.05916917e+00,
        1.84652972e+00, -6.15939140e-01, -1.00487685e+00,  1.49137545e-02,
        1.31138217e+00, -1.05525398e+00,  1.21203744e+00, -4.44894433e-02,
       -5.87729394e-01, -9.03400630e-02,  1.98689029e-01,  8.25307429e-01,
       -2.31998265e-01, -2.94255465e-01,  5.69855690e-01,  7.59323895e-01,
        1.07539713e+00, -5.90593815e-01, -1.02876616e+00, -8.61393452e-01,
       -7.31312871e-01, -1.02009082e+00, -6.57593906e-01, -3.29465032e-01,
       -7.24326015e-01,  4.56135362e-01, -2.94714004e-01,  1.01218939e-01,
        1.27922285e+00, -3.57135147e-01, -4.15138245e-01,  8.72440338e-01,
       -5.66803932e-01, -1.29520670e-01, -1.05224885e-01,  1.03511559e-02,
       -2.01838708e+00, -6.01244211e-01,  1.71572308e-03, -5.65200686e-01,
        6.28239393e-01,  1.02032018e+00,  1.25162768e+00, -7.90251553e-01,
        1.38801956e+00,  1.90133834e+00, -9.00891781e-01,  9.73220646e-01,
       -1.08522904e+00, -1.44916594e+00, -2.22848892e+00,  2.75609493e-01,
       -1.04311275e+00,  1.14440036e+00, -6.28057837e-01, -1.67269659e+00,
        1.33289516e+00, -9.75879073e-01,  6.09820485e-01, -5.88628531e-01,
        8.56257856e-01, -1.47976205e-01, -1.06162119e+00,  1.71399921e-01,
       -5.16596854e-01,  5.40997744e-01, -8.66155088e-01, -6.69158161e-01,
        6.40679598e-01, -3.39444816e-01, -3.98012042e-01, -3.48990142e-01,
       -1.54710793e+00, -7.07585454e-01,  4.66846287e-01, -1.40630412e+00,
        1.78063273e+00, -6.96379125e-01, -5.26861608e-01,  7.86034286e-01,
        3.09723288e-01,  7.31398284e-01,  6.35623097e-01, -6.56160116e-01,
       -4.49820161e-01,  3.43949139e-01,  1.13624454e+00, -1.73448861e+00,
        9.41238165e-01,  1.32498264e+00,  2.34575391e-01, -5.65958798e-01,
       -9.93675828e-01,  1.49398804e+00,  1.44461370e+00, -3.29151489e-02,
        1.68258739e+00, -6.53258741e-01, -2.74288327e-01, -9.64770973e-01,
       -7.80870378e-01, -2.73800433e-01,  1.03770185e+00, -2.00134844e-01,
       -1.09660387e+00, -1.37644148e+00, -5.62558234e-01,  6.34715199e-01,
       -1.33237487e-03, -4.60697353e-01, -1.12816644e+00, -5.74577808e-01,
       -1.90960407e-01,  1.21884298e+00, -1.40235710e+00, -5.58540046e-01,
        8.03735554e-01, -1.16000998e+00,  8.60951021e-02, -2.79322892e-01,
        5.90946138e-01, -3.54305834e-01, -1.64945453e-01,  9.10469413e-01,
        9.44729865e-01, -9.52586532e-02, -5.54187238e-01,  1.12667477e+00,
        1.10824978e+00,  1.87769607e-01,  1.36542201e+00,  1.16697729e+00,
       -6.89135194e-02,  7.09792018e-01, -2.60117769e-01, -7.38475084e-01,
       -5.36870211e-02,  1.01560783e+00,  6.04330480e-01, -8.61622930e-01,
       -9.36087608e-01, -5.47228813e-01, -1.08765209e+00, -4.85695511e-01,
        1.08771765e+00, -1.07475519e+00, -5.61120749e-01, -1.37589395e+00,
        9.75978673e-01, -8.15195560e-01,  9.53211546e-01,  2.54118979e-01,
       -5.68629026e-01,  1.09415126e+00, -6.02378607e-01, -5.27321577e-01],
      dtype=float32), array([11.58986  ,  1.4438193,  6.0482044,  4.4288616,  9.120558 ,
       10.395416 ,  8.993748 ,  5.1003256,  2.3428228,  2.4333754,
        1.8268554,  3.2634807, 11.014165 ,  2.2963805, 12.988297 ,
        3.7198126, 11.264399 ,  3.7738097,  4.115264 ,  1.5732688,
        4.4539313,  2.150072 , 12.292888 ,  1.8003942,  3.1716735,
        1.7410626,  1.7468531,  1.1307421,  7.063007 ,  7.1787615,
        3.6974392, 17.33817  ,  6.5033855,  3.8803332,  2.913661 ,
        6.0146394,  7.549814 ,  5.323565 ,  2.7300527,  6.012614 ,
       10.407181 ,  6.1905293,  9.719074 ,  1.9632317,  4.2679324,
        2.5266788, 10.879686 ,  6.2708683,  3.9005013,  5.4577284,
        2.4205482, 10.828329 , 14.789814 ,  4.2344933, 10.161857 ,
       10.667648 ,  3.9213378,  9.982152 ,  7.70205  ,  4.1734977,
        4.48316  ,  4.567635 ,  4.7507014,  6.3413024, 11.613412 ,
        3.0667994,  1.9197382, 10.582839 ,  4.3743167,  9.301239 ,
        3.496151 ,  5.403892 , 19.242113 ,  2.5792918,  7.753193 ,
        3.3387651,  4.161449 ,  8.5307255,  7.7322   ,  5.651283 ,
       11.385786 , 11.525602 , 12.2782345, 10.347387 ,  6.186899 ,
       16.757816 , 11.607543 ,  2.3827453,  5.86965  ,  7.7651334,
        5.977976 , 17.236967 ,  8.894503 ,  5.072411 ,  2.5737963,
        5.893222 ,  3.6429503,  2.1238017,  7.765847 ,  9.5217495,
        6.331873 ,  2.604257 ,  5.600192 , 11.5304   ,  5.191941 ,
       10.842335 ,  4.540726 ,  0.9923267,  6.0935497,  4.794668 ,
       14.393568 , 16.202242 , 16.42288  ,  7.725547 ,  3.4997926,
       11.683404 ,  3.9369223,  4.4982257,  5.264167 ,  3.8423233,
        3.624491 , 12.792863 ,  4.3330383, 21.639334 ,  6.274961 ,
       15.736205 ,  3.3383634,  6.032546 ,  6.2146773, 17.85253  ,
       11.138474 ,  2.9077291, 21.11953  ,  3.9662087,  1.6369907,
        4.511713 ,  4.4867053,  3.4774308,  4.7996454,  1.5026723,
        9.077804 ,  9.347058 ,  6.4005003,  8.016271 ,  4.539037 ,
        6.0170383, 14.842676 ,  7.817369 ,  4.331689 ,  6.081306 ,
       14.113696 ,  4.711874 ,  3.15809  ,  6.0738974,  3.5412915,
        5.009357 ,  3.8380866,  4.0880775,  6.17052  ,  3.1493025,
        2.4558516,  3.3869815,  9.632012 ,  7.833778 , 12.971752 ,
        3.6163433,  8.480002 ,  8.849444 ,  3.6229389, 10.006605 ,
        2.4784396,  3.8604004,  3.7061877, 10.943232 ,  1.5552281,
       12.210197 ,  3.5415888,  5.028872 ,  5.7958217,  4.534743 ,
       18.478678 , 11.64448  ,  5.6163297,  7.365331 ,  6.153834 ,
        7.6765094,  5.0413394,  4.17182  ,  5.0615225, 10.5044   ,
       11.460778 ,  4.3587213], dtype=float32), array([[[[ 0.01957332,  0.03296219,  0.02549482, ..., -0.08589358,
          -0.01054842, -0.01573016],
         [ 0.05600195,  0.05320045, -0.08373193, ..., -0.01224259,
          -0.03977538, -0.06636032],
         [ 0.0273896 , -0.05595295,  0.05446495, ...,  0.04595448,
           0.05243908,  0.07365734],
         ...,
         [ 0.05702198,  0.0256387 , -0.05292112, ..., -0.04946451,
          -0.01430209,  0.01089677],
         [ 0.09814772,  0.06624483,  0.06977148, ..., -0.05204127,
          -0.06108411, -0.02310081],
         [ 0.04730437, -0.00639297,  0.05116855, ..., -0.00196315,
           0.07715786,  0.05409421]]]], dtype=float32), array([[[[-1.96640864e-02,  1.83246080e-02,  1.35488836e-02, ...,
          -3.19328345e-02,  3.96466590e-02,  2.27263216e-02],
         [-2.53876802e-02, -7.47326249e-03, -9.01908334e-03, ...,
           1.37201427e-02, -7.29736499e-03,  9.09147027e-04],
         [-1.42273903e-02,  2.20885295e-02,  1.18241562e-02, ...,
          -2.50085015e-02, -2.59050597e-02,  8.84562079e-03],
         ...,
         [-2.39729006e-02,  1.16284005e-02,  1.80969071e-02, ...,
          -3.08411252e-02,  3.92639041e-02,  2.80291885e-02],
         [ 2.01377105e-02,  4.34745029e-02, -3.27201164e-03, ...,
          -4.97105345e-02, -1.67451873e-02, -1.69258565e-02],
         [ 3.19730490e-02,  4.37266789e-02,  1.19093787e-02, ...,
           5.49750589e-02, -3.37152556e-02, -3.00039165e-02]],

        [[ 4.42174040e-02,  4.65860739e-02, -4.40318808e-02, ...,
          -1.38851348e-03, -1.47598861e-02, -1.58957634e-02],
         [ 3.64466049e-02, -3.11586019e-02, -9.54896770e-03, ...,
          -9.34513099e-03, -1.61114819e-02,  1.05976814e-03],
         [ 9.59105892e-05, -7.58806011e-03,  2.99497191e-02, ...,
          -5.17016277e-04, -2.53060535e-02, -3.08928895e-03],
         ...,
         [ 1.72253661e-02,  1.36426128e-02,  2.25567389e-02, ...,
          -7.33335409e-03,  4.05244492e-02, -1.77263916e-02],
         [ 1.53115476e-02, -5.77914193e-02,  3.04493727e-03, ...,
          -4.80692014e-02,  2.23160181e-02,  2.54709497e-02],
         [ 3.79015245e-02, -1.82591621e-02,  1.34373577e-02, ...,
          -4.13960665e-02, -4.09710668e-02,  1.43602025e-02]],

        [[ 4.37054075e-02,  4.14569005e-02, -5.15684225e-02, ...,
          -2.31754892e-02, -7.12896138e-03,  2.64025666e-02],
         [ 4.80942726e-02, -1.00658489e-02,  3.70226242e-02, ...,
          -3.60167474e-02,  1.30343512e-02,  3.15338261e-02],
         [-3.20905298e-02, -5.18828770e-03,  6.96511753e-03, ...,
          -2.72455607e-02,  2.99006533e-02, -4.96075340e-02],
         ...,
         [-3.16564254e-02, -4.54709120e-02, -3.30161974e-02, ...,
          -8.18334171e-04, -4.61910069e-02,  5.88383572e-03],
         [-1.41204931e-02,  2.10456233e-02,  4.53768298e-02, ...,
           1.13755809e-02,  9.63415671e-03, -1.75661817e-02],
         [ 5.24691753e-02,  5.88695593e-02, -1.59648769e-02, ...,
           3.59727815e-02,  1.84415113e-02, -5.27867489e-03]],

        ...,

        [[-3.02249230e-02, -1.66755076e-02, -5.24607226e-02, ...,
           4.18304875e-02,  3.91539978e-03, -7.97786936e-03],
         [-1.23575088e-02, -1.63096543e-02, -1.12156039e-02, ...,
          -3.64395157e-02, -1.16997557e-02,  2.69349664e-02],
         [-1.08216098e-03, -1.75375193e-02, -2.84714531e-03, ...,
           4.39515039e-02, -1.09509612e-03, -4.01019268e-02],
         ...,
         [-1.60030443e-02, -3.73996608e-02, -1.86646637e-02, ...,
          -5.22510596e-02, -4.51678559e-02, -1.86315197e-02],
         [ 4.48043644e-03,  5.49252657e-03,  3.59265693e-03, ...,
          -5.34886867e-02,  3.99162732e-02, -3.56054194e-02],
         [ 5.09927347e-02, -2.32498627e-02,  1.90196484e-02, ...,
          -1.56150693e-02, -4.56550298e-03,  1.08106504e-03]],

        [[-3.03400885e-02, -2.66150385e-02, -5.39210290e-02, ...,
           4.17656898e-02, -4.47198190e-02,  5.11959370e-04],
         [ 2.36225803e-03,  1.81831121e-02,  7.00978842e-03, ...,
           3.96255665e-02,  2.64619719e-02,  3.88767425e-04],
         [ 1.02611464e-02,  2.32314933e-02, -2.07904559e-02, ...,
          -3.99128720e-02,  1.86584005e-03, -6.71442272e-03],
         ...,
         [-1.39529875e-03, -4.45036124e-03, -1.30989272e-02, ...,
          -1.15114404e-02, -4.03467305e-02, -1.45286443e-02],
         [-1.24949990e-02, -3.19390185e-02,  5.42766638e-02, ...,
          -2.39778999e-02,  1.86591130e-02,  6.45686984e-02],
         [ 6.11271616e-03,  4.76134708e-04,  2.54036002e-02, ...,
          -1.02763195e-02,  4.40415926e-03, -3.94470571e-03]],

        [[-2.21011098e-02, -3.66311073e-02,  3.32517512e-02, ...,
          -1.25228046e-02, -4.81746887e-04, -2.36247648e-02],
         [-1.73868109e-02,  2.46553179e-02, -2.09738277e-02, ...,
           4.42340001e-02, -2.28245128e-02,  3.23091336e-02],
         [ 2.99523957e-03,  3.21921892e-02, -4.45794463e-02, ...,
          -3.90734524e-02, -8.31744634e-03, -2.62345411e-02],
         ...,
         [ 3.75812352e-02, -2.13373844e-02, -5.66734038e-02, ...,
          -1.38383247e-02, -3.23938578e-02,  4.65894118e-03],
         [-1.84113979e-02,  4.32652794e-02,  1.74766965e-02, ...,
          -2.43701320e-02,  5.83378272e-03, -2.79232729e-02],
         [-1.80813763e-02,  3.78095247e-02, -3.84278148e-02, ...,
          -1.02404347e-02,  1.71142761e-02,  1.68737012e-03]]]],
      dtype=float32), array([-9.76569392e-03, -7.83159863e-03,  1.80607159e-02, -8.43730057e-04,
       -1.05069936e-04, -9.02852975e-03,  9.09731817e-03, -1.36732860e-02,
       -5.78418979e-03, -1.42423203e-03, -3.73528455e-03,  1.33142131e-03,
       -1.21132878e-03,  1.05422630e-03, -1.30370660e-02,  1.08883306e-02,
       -5.62861143e-03, -8.46740510e-03,  4.34009777e-03,  1.39514953e-02,
       -7.09650340e-03, -3.32235429e-03, -1.32016221e-03,  3.29102809e-03,
       -4.65233903e-03, -4.70677670e-03, -3.67096299e-03, -1.23831965e-02,
       -2.22341693e-03, -1.34358471e-02, -1.41669461e-03, -5.99707058e-03,
        7.50107365e-03,  1.78783981e-03, -1.78466309e-02,  7.50741875e-03,
       -2.26139952e-03,  1.13954656e-02,  6.01346110e-05, -2.59894296e-04,
       -1.22014433e-02, -5.18683577e-03, -7.23974733e-03,  5.03078662e-03,
        1.48095153e-02, -6.66990923e-03,  1.37680452e-02,  2.00734977e-02,
       -2.49686721e-03,  5.94951492e-03,  2.68917577e-03, -8.28459673e-03,
       -6.24051027e-04,  6.08963659e-03,  1.18818777e-02,  1.65180601e-02,
       -8.77454784e-03,  7.14356732e-03, -5.84973628e-03,  6.77022943e-03,
        5.65856835e-03,  2.02924106e-02,  1.95842469e-03, -7.90553051e-04,
        2.93637696e-03,  1.41202090e-02, -7.47565459e-03,  1.40182460e-02,
       -9.30717739e-04,  6.33636257e-03,  5.66952489e-03,  2.14738445e-03,
       -7.36083789e-03,  1.13277661e-03,  3.12852743e-03, -2.77920830e-04,
        1.06700975e-02,  1.37715542e-03, -3.53749585e-03,  7.13658566e-03,
        8.00457504e-03, -6.79909764e-03, -1.05580240e-02, -2.19914620e-03,
        5.89502649e-03,  1.29249245e-02, -3.66321718e-03, -2.20724940e-03,
        1.51183382e-02, -4.01628931e-04, -9.77216661e-03,  7.71109480e-03,
       -4.84692078e-04,  7.00086588e-04,  7.48738227e-03,  3.41062224e-03,
        1.02421995e-02,  6.60708593e-03, -7.19877612e-03,  1.50300842e-03,
       -2.15271270e-04, -8.17054417e-03,  3.05325072e-03,  5.21551492e-03,
       -3.05855810e-03, -1.11077458e-03, -9.59288701e-03, -1.17631447e-04,
       -4.33469331e-03,  1.52658466e-02,  1.63511261e-02, -9.40760225e-03,
       -1.04053812e-02,  4.96891234e-03, -5.33432327e-03,  1.20568005e-02,
       -1.48367947e-02,  1.22516335e-03,  1.70667621e-03, -1.43437064e-04,
       -5.47843240e-03,  5.63462777e-03, -2.19030376e-03,  1.11596296e-02,
       -7.63754686e-03, -6.71090558e-04,  4.24699811e-03,  1.84861552e-02,
        2.82986555e-03,  1.39595596e-02, -2.92713498e-03, -3.86834051e-03,
        6.95488416e-03,  7.71176349e-03, -3.17720580e-03, -1.29477084e-02,
       -9.60602984e-03,  3.14401742e-03,  3.84057686e-03, -9.74018127e-04,
        6.45834906e-03,  1.25167323e-02,  2.91059236e-03,  1.22376494e-02,
       -8.86837486e-03,  1.71677917e-02, -6.62538502e-03, -2.36834004e-03,
        1.89183012e-03, -1.81071013e-02, -3.31857591e-03, -9.35069378e-03,
        3.08423745e-03, -4.44746623e-03, -1.91632044e-02, -7.83173367e-03,
        8.45550466e-03,  3.51469591e-03, -5.45174628e-03,  6.29593711e-03,
        5.21190418e-03, -4.27882466e-03, -1.40813468e-02,  1.54462818e-03,
        3.09981522e-03,  6.70364185e-04,  4.87940124e-04,  6.47889636e-03,
       -1.84702948e-02, -1.62880297e-03,  1.11951982e-03, -2.57621100e-03,
       -1.46818012e-02, -7.87467323e-03,  1.20632565e-02, -6.06034463e-03,
       -1.26061530e-03,  8.85900948e-03,  4.34274226e-03, -5.13669383e-03,
       -4.84785484e-03, -1.26755778e-02, -4.63701726e-04, -9.35094804e-03,
        1.67133962e-03,  9.20256786e-03, -1.48383947e-02, -7.62427133e-03,
       -1.42508736e-02, -8.20190553e-03, -2.58129742e-03, -5.01100672e-03],
      dtype=float32), array([ 1.0253159 ,  0.54714656,  0.3210449 , -0.7138237 , -0.17003089,
        0.08196154, -0.06303889,  0.58441186, -1.1014982 ,  0.67936593,
        0.17905979, -0.90328705, -0.46741858, -0.70070475,  1.1779441 ,
        0.6041395 , -0.20989388, -0.4383419 ,  0.64721644,  0.8874575 ,
        0.46284044, -0.511762  , -0.03308366, -0.64920175, -0.37044445,
       -0.47808197, -1.24417   , -1.1007695 ,  0.5301684 ,  0.6125355 ,
        0.7698121 ,  0.13013625,  0.71321803,  0.17946336, -0.12461995,
        0.16448109, -0.00930685, -1.11191   , -0.27393597, -0.19339718,
        0.27328572,  0.77069813,  0.43340483,  0.23062985, -0.21189223,
       -0.6080937 ,  0.53536195, -0.14555834,  0.8366507 ,  0.20864725,
       -1.0171615 ,  1.2255093 ,  0.05578566,  0.89102834, -0.5819179 ,
        0.79659283,  0.56012577,  0.5711173 ,  0.55439085, -0.6489997 ,
        1.0151871 , -0.45949012,  0.9387101 ,  0.63706625, -0.7096229 ,
        0.14550713,  0.73390824, -0.08105636, -0.06869563,  0.06327605,
       -0.29751801, -0.14139137,  0.87789553,  0.77598876,  0.54721355,
        0.59044224, -1.0293581 ,  0.34909776,  0.38932592, -0.39421052,
       -0.18125217, -0.7206657 , -0.5822993 , -0.47016096, -0.9546971 ,
       -0.5245883 , -1.2257546 ,  0.09884262, -0.17370278,  0.04543617,
       -0.2496955 ,  0.09011757,  0.9698295 , -0.38845295, -0.5645773 ,
       -0.03846474,  0.94746095, -0.27264535,  0.06442092, -0.21839908,
       -0.45951512, -0.68004835,  0.16025665,  1.0329247 ,  0.69934076,
        0.6720285 ,  1.1615341 ,  1.2264733 , -0.2749369 ,  0.02361247,
       -0.73856   , -0.2215942 , -0.4438892 ,  0.23745152, -0.20700894,
        0.932522  ,  1.1200845 , -0.56432134,  0.42067033, -0.5709177 ,
        0.6412076 , -0.8467222 , -0.30127284,  0.08910149, -0.77430785,
        0.5877645 , -0.40147385,  0.48275417,  0.643718  , -0.6277426 ,
       -1.1640785 ,  0.25696653, -0.14315827, -1.319461  ,  0.5728852 ,
       -0.7199155 , -0.07589372,  0.05175873, -0.6556494 , -0.5287472 ,
        0.43120375,  0.31953704,  0.43363923, -0.5343911 ,  0.04629132,
       -0.9158925 ,  0.38281313, -0.08268851,  1.1371279 , -0.14602643,
       -0.24117894, -1.0297046 ,  0.72237164, -0.33887997, -1.0989747 ,
       -0.54461485, -0.27714163, -0.17160489, -0.00288295, -0.10535608,
        0.13005307, -0.209043  , -0.3407505 , -0.6200908 ,  0.18812597,
        0.8751128 ,  0.5469783 , -0.10961473,  0.89965546, -1.0664594 ,
        0.49987042, -0.797389  ,  0.05938057,  0.1399324 ,  0.27100137,
        1.0212271 , -0.2664508 , -0.8074429 , -0.81183064, -0.14505795,
       -0.9007819 , -0.03821678, -0.15097575,  0.80354273,  0.3778237 ,
       -0.87506807, -0.05447648, -1.240817  ,  1.0184318 ,  0.41407362,
       -1.0932372 ,  0.9837268 ], dtype=float32), array([3.3088236 , 0.8167285 , 2.8052993 , 1.7398655 , 0.9342174 ,
       1.1867174 , 1.083093  , 3.4146008 , 1.4328175 , 1.2346137 ,
       0.9465022 , 2.5795374 , 1.9614114 , 1.392509  , 2.3991017 ,
       0.9966833 , 0.9778758 , 0.6664254 , 1.4838998 , 1.0152786 ,
       0.8649295 , 1.6273271 , 0.6011999 , 1.7706366 , 0.5657908 ,
       1.188546  , 2.2857022 , 2.373537  , 2.1378157 , 1.7551782 ,
       4.433206  , 1.0946853 , 1.024446  , 1.4775054 , 1.3924536 ,
       1.0767746 , 0.5901519 , 1.2118254 , 1.8683686 , 1.1176462 ,
       2.1769662 , 1.425178  , 0.97099155, 2.2913125 , 0.9785199 ,
       2.4593527 , 3.0239532 , 2.1977541 , 0.67671144, 0.50760823,
       0.8256458 , 6.6573157 , 1.4476724 , 2.6696322 , 2.4269512 ,
       2.7707064 , 0.69382286, 1.916688  , 1.4335744 , 0.8994999 ,
       5.335897  , 0.91870534, 2.5168333 , 1.4373914 , 1.1598762 ,
       2.6810951 , 2.157074  , 0.9871038 , 0.7691892 , 1.1547441 ,
       0.7897822 , 1.0184582 , 2.0493443 , 2.233985  , 1.7443742 ,
       1.0935107 , 3.7876065 , 1.4565151 , 1.603852  , 3.3475578 ,
       1.3862232 , 2.1228073 , 2.5223224 , 1.2801331 , 1.4316891 ,
       0.78512424, 3.809056  , 0.7582915 , 2.4301937 , 0.7727866 ,
       2.0838134 , 1.1927875 , 2.766952  , 0.68928105, 1.6314242 ,
       0.89661616, 1.7850679 , 1.1661512 , 0.875373  , 1.3223947 ,
       0.9321548 , 1.6057708 , 2.5346932 , 2.302621  , 1.9334339 ,
       2.7766428 , 4.0568542 , 1.9702096 , 0.74329776, 0.6366362 ,
       1.7435237 , 0.5223393 , 1.7757733 , 0.98315966, 1.5923252 ,
       2.766131  , 3.9737375 , 0.80353594, 0.56216675, 2.5973074 ,
       1.4759932 , 2.0748744 , 1.2093587 , 2.362369  , 1.9714355 ,
       3.1507285 , 2.386374  , 1.5263802 , 1.6394058 , 2.9901412 ,
       3.3548155 , 0.7192584 , 0.6066297 , 3.445348  , 0.90707153,
       1.0393867 , 0.8134328 , 0.7510101 , 0.6304486 , 0.82046205,
       1.080053  , 1.6366189 , 1.0895833 , 1.3816118 , 0.84631294,
       2.0050745 , 0.99747854, 0.889218  , 6.1145945 , 0.88508993,
       1.1124386 , 3.0608563 , 1.3320857 , 2.2594116 , 2.126603  ,
       2.9630783 , 0.6618174 , 0.53732044, 1.2869403 , 0.53253025,
       1.4618087 , 1.3158029 , 1.136147  , 1.0958191 , 1.4059912 ,
       0.8762444 , 1.6139581 , 2.1412132 , 2.3117898 , 3.4724333 ,
       0.6904381 , 2.1751027 , 1.9020267 , 0.4898134 , 1.7318796 ,
       3.6270804 , 0.9756254 , 1.5176791 , 1.2833289 , 1.1461749 ,
       1.7271166 , 0.8967772 , 1.3707434 , 2.2110417 , 1.9983251 ,
       2.0813873 , 0.6958994 , 3.1370063 , 2.0655627 , 1.0743668 ,
       1.7027729 , 1.9493632 ], dtype=float32), array([-0.00304804, -0.00962692,  0.0106348 ,  0.00067627,  0.00207594,
        0.01348267,  0.00618969,  0.00129177,  0.00561404, -0.0235566 ,
       -0.0002777 , -0.00961613, -0.0146747 ,  0.00132762, -0.00982839,
        0.01058273,  0.00510748, -0.02304855, -0.02230448,  0.00074975,
       -0.01483992,  0.00111916, -0.01513895,  0.00480783,  0.00774185,
        0.00889705,  0.00751471,  0.01553661, -0.01306745, -0.01430418,
       -0.00289586,  0.0087251 ,  0.02452317,  0.00266368, -0.024557  ,
       -0.00886238, -0.01188853, -0.00704139,  0.00177576,  0.00792291,
        0.00076315, -0.00889762, -0.01729798, -0.00248068,  0.00455727,
       -0.02384907, -0.00582903, -0.01290049, -0.00093017, -0.01306575,
       -0.01780415, -0.01809391,  0.00772052,  0.00687787,  0.01615393,
        0.00961194,  0.00059051,  0.01310137,  0.00391651,  0.00421483,
        0.02983059,  0.00690966,  0.01055499,  0.01768285,  0.00961515,
       -0.00589553,  0.01445808,  0.01499953,  0.00402059, -0.01475367,
       -0.01040009,  0.00477224,  0.00512521,  0.00103191, -0.01243554,
       -0.00083014, -0.00829546,  0.00551916,  0.00107676, -0.00427261,
       -0.01877439, -0.01343197, -0.00444936, -0.01380942, -0.00757652,
        0.00336597,  0.01663731,  0.00397501, -0.01291042, -0.00730208,
       -0.00404774, -0.01191853, -0.00203542, -0.02208614, -0.00140919,
        0.01301046, -0.00691448,  0.00464519,  0.00837694, -0.00945435,
       -0.00211148,  0.01751562, -0.00559983,  0.00299296,  0.01047647,
       -0.02427668,  0.00480982,  0.01215832, -0.00689267,  0.01066742,
        0.01443052, -0.01222862, -0.00676527, -0.01130953,  0.00772418,
        0.00785041, -0.00775698,  0.00758808, -0.01017346,  0.03099636,
       -0.00661216, -0.01486646, -0.01191705, -0.00200862,  0.0016525 ,
       -0.00346211,  0.00568201, -0.02401292,  0.00274066, -0.00272069,
       -0.0059204 , -0.01106339, -0.00183461, -0.01561711,  0.00650787,
       -0.02778633, -0.00623155, -0.02294876, -0.01020004, -0.00874938,
        0.0141824 ,  0.02008326, -0.00753626, -0.01709504, -0.00452106,
       -0.00536169, -0.00810714, -0.00022362, -0.00446066,  0.00511889,
        0.01689265, -0.00411252, -0.02173491, -0.0295    ,  0.01785391,
       -0.00036852, -0.01377911, -0.00291293,  0.00539658,  0.0037294 ,
       -0.02406597, -0.01270898,  0.00333753,  0.01120412, -0.00447232,
        0.01058938,  0.00787488,  0.00737894,  0.02806991,  0.00025234,
       -0.01758755, -0.00962299,  0.02240539, -0.01076343, -0.00270797,
        0.00567403, -0.01038904,  0.00165755, -0.00592892,  0.00310718,
        0.01371989, -0.01999211,  0.01119679, -0.0313213 ,  0.00649827,
       -0.02143153,  0.0065105 ,  0.00696674, -0.00930356, -0.01155544,
        0.00143782, -0.00335682], dtype=float32), array([-1.0474350e+00,  4.8281366e-01, -1.0387052e+00, -1.0197791e+00,
       -1.1988846e+00, -1.2096264e+00,  1.0232635e+00,  1.2920804e+00,
       -1.1380893e+00, -1.8311198e-01,  2.4188373e-02, -7.9720092e-01,
        9.2709243e-01,  4.1527593e-01, -1.0549453e+00, -8.9812130e-01,
        3.4220216e-01,  7.8699213e-01,  1.1696208e+00, -1.4790741e-01,
       -7.8983694e-01,  1.0252926e+00, -1.0596331e-03,  1.7492051e+00,
       -1.4978850e+00, -5.7779747e-01, -5.9187138e-01,  1.6588157e-01,
       -8.8303351e-01, -2.2392606e-02,  8.2660240e-01,  8.8261046e-02,
        1.3484540e+00, -3.8372660e-01,  7.0158079e-02, -2.9716393e-02,
        5.3859872e-01, -4.5339885e-01, -1.1461964e+00, -1.4954506e-01,
        9.8769951e-01, -1.3119965e+00, -1.4174148e-01,  1.0350183e+00,
       -4.8641330e-01, -4.5732924e-01,  1.0802059e+00,  1.2000388e+00,
       -6.4247209e-01, -2.5816795e-01, -2.8849158e-01,  1.3048617e+00,
       -1.3571490e+00,  2.8659475e-01, -1.5296590e-01,  9.4239986e-01,
       -9.5276475e-01, -7.1192110e-01,  3.4894800e-01, -7.7295953e-01,
        1.3467747e-01, -1.0517527e+00,  4.1216642e-01, -6.5117306e-01,
        3.9511067e-01, -2.8028288e-01, -7.6961374e-01,  3.3940321e-01,
       -1.1845195e+00, -1.2883983e+00,  2.0226099e-01,  3.5279459e-01,
       -1.6830523e+00, -7.0476048e-03, -6.5866143e-01,  6.5213072e-01,
        9.2167062e-01, -1.5948051e+00,  4.4281214e-01,  3.0166730e-01,
        1.1137125e+00, -3.8419944e-01, -7.9752493e-01, -6.6554144e-02,
       -7.7423334e-01, -1.6965990e+00, -3.8192907e-01,  1.5357733e+00,
        7.4186110e-01,  7.1758255e-03,  6.5611057e-02,  3.0979538e-01,
       -1.4356446e+00,  7.6756805e-01, -1.0968400e+00, -8.2452273e-01,
       -1.6062573e+00, -8.7833768e-01, -7.0245951e-01,  4.8180449e-01,
        2.6439521e-01,  4.1691515e-01,  1.0663674e+00,  7.7246630e-01,
       -8.6082000e-01, -1.4911153e+00,  1.3060344e-04,  1.1618004e+00,
        2.6491293e-01, -1.3372710e+00, -5.3201485e-01,  7.3717213e-01,
       -3.2092136e-01,  2.4614060e-01,  8.6854261e-01,  2.5309178e-01,
       -8.5309082e-01,  2.2898251e-01,  6.0871011e-01, -1.0931058e+00,
        4.1928831e-01, -1.3212594e-01,  1.0496755e+00, -1.2701457e+00,
        1.0947571e+00,  4.9560386e-01,  1.3386320e+00,  5.7380289e-01,
       -9.8872882e-01, -2.0242183e+00,  6.7504980e-02,  3.4792250e-01,
        2.6569512e-01, -3.3187160e-01,  4.5047736e-01, -2.2060268e-01,
        3.6001697e-01,  5.9429711e-01, -1.1935291e+00,  5.8768147e-01,
        4.6202862e-01, -9.9160559e-02,  9.2647052e-01,  4.1940093e-01,
       -9.1991723e-01,  1.0589315e+00, -1.6208464e+00,  7.4901605e-01,
       -1.4843315e+00, -1.0777664e+00,  4.2354932e-01, -2.9889020e-01,
        9.1481966e-01, -4.7387135e-01,  6.2356442e-01, -1.0640687e+00,
        1.1719570e+00,  1.3388168e+00, -1.0430079e+00, -4.8697934e-01,
        1.0803224e+00, -3.5943705e-01,  1.0882692e+00,  3.6100483e-01,
       -8.5139179e-01, -9.3558449e-01, -4.2104283e-01,  5.0284421e-01,
        6.9553947e-01,  9.5898569e-01,  8.2919902e-01,  9.3835747e-01,
       -1.1028171e+00, -1.3100013e+00, -2.8862244e-01, -1.8067925e+00,
        5.6584036e-01,  5.3669822e-01,  1.0018966e+00,  7.7175945e-01,
        9.0477628e-01,  5.2213031e-01, -1.4959127e+00, -1.1184556e+00,
        2.8119045e-01,  1.6283298e+00,  8.9597696e-01,  6.0614896e-01,
        5.4329079e-01,  3.1815195e-01, -1.1389227e+00, -1.4139732e+00],
      dtype=float32), array([ 3.217854 ,  6.697653 ,  4.915891 ,  4.616078 ,  5.1804914,
       21.589947 ,  7.644064 ,  5.685449 , 16.610031 ,  7.34203  ,
        2.9121134, 23.6812   ,  5.956617 ,  5.712159 , 13.318382 ,
       23.867329 ,  5.45198  ,  7.835832 ,  4.076734 ,  1.9987296,
        3.577387 ,  6.0052567,  4.7821593,  4.960696 , 19.942022 ,
        5.047895 , 23.235046 , 13.5285   ,  2.1170058,  2.076762 ,
        5.344827 ,  4.277795 ,  9.165132 ,  6.97813  ,  3.3839056,
        2.9037247,  1.7635223,  1.0327688, 14.355911 ,  8.894264 ,
        3.2455034, 15.633661 ,  4.074497 ,  3.926864 ,  6.5883665,
        1.9034759,  5.4170427,  3.9745572,  3.0125499,  1.206393 ,
        6.3945346,  5.954784 , 16.711887 ,  1.4917587,  9.840494 ,
        3.0548708, 23.93146  , 20.400635 ,  3.1185641, 26.224249 ,
        4.7467637, 20.791864 ,  6.5358186,  3.2188885,  6.75204  ,
        3.798149 , 22.793598 ,  7.6004543,  3.697044 ,  2.9321086,
        2.427509 , 12.489666 , 19.98926  ,  5.6789813,  2.1832874,
        1.7829994,  4.041062 , 24.316898 ,  5.21071  ,  5.386244 ,
        4.676416 , 14.005403 , 14.107326 ,  7.2043366,  3.6602535,
       23.684584 , 14.45933  ,  6.736849 ,  6.156991 ,  3.0830424,
        3.7826068,  3.050729 ,  7.0483966,  6.7962027,  3.8453066,
        7.8041687, 13.06073  ,  2.9864125, 17.198107 , 10.488029 ,
        2.2217717,  7.3325133,  5.4298515, 11.385676 , 16.33222  ,
       19.85729  ,  5.006867 ,  8.150314 ,  7.0011506, 19.907839 ,
        3.8481014,  7.929104 ,  4.396028 ,  6.419525 ,  4.786485 ,
        7.778064 , 16.594511 ,  7.6083417,  6.957129 ,  4.348798 ,
        7.224171 ,  6.142095 , 10.114587 , 14.003118 ,  5.4644704,
        5.6055846,  7.2322774,  6.16381  , 16.10616  , 21.557087 ,
       10.94599  ,  5.462485 ,  9.531309 ,  2.9656117, 13.301951 ,
        1.8346007,  4.6067076,  4.8770847,  8.831702 ,  3.4977329,
        6.713251 ,  3.0643997, 11.595299 ,  6.998232 ,  4.105727 ,
        3.6071403, 25.713863 ,  3.268738 ,  5.017052 ,  2.135594 ,
        5.1077943, 13.784823 ,  9.924442 ,  9.106267 ,  6.6855316,
        2.3073404,  9.922702 ,  3.750577 , 11.691898 ,  2.7857249,
        4.3407507,  4.2537074,  3.6516402, 10.592317 ,  4.990873 ,
        6.518785 ,  7.721137 ,  2.6465843,  5.9871836,  2.7292786,
        5.441437 ,  5.48042  , 11.928408 , 10.842533 , 14.825665 ,
       21.267244 ,  6.427058 ,  1.8056109,  6.147211 ,  4.633441 ,
        5.383707 ,  4.700122 ,  4.5410995, 13.450057 ,  7.7763247,
       10.187124 ,  1.566198 ,  5.224464 ,  6.2564774,  3.2621944,
       10.268718 ,  4.998913 ], dtype=float32), array([[[[ 0.01263219, -0.01614717, -0.03224632, ..., -0.02280754,
           0.06333119,  0.03917284],
         [ 0.03745368,  0.02136817,  0.00758033, ..., -0.00725944,
          -0.02737696,  0.00521657],
         [ 0.02187012,  0.02230635,  0.01256459, ..., -0.00666242,
           0.04652747,  0.02954701],
         ...,
         [ 0.00824271,  0.04085761,  0.027236  , ...,  0.02315743,
           0.00555894,  0.00575531],
         [ 0.02981813, -0.03623436,  0.02875846, ..., -0.02646301,
          -0.00964493, -0.0374243 ],
         [ 0.00952554, -0.01688562, -0.01201033, ..., -0.01311411,
          -0.02398377,  0.05059643]],

        [[ 0.00490022, -0.023276  , -0.03261562, ...,  0.01702115,
           0.03955367,  0.03513914],
         [-0.0134399 , -0.02970676,  0.00132653, ...,  0.00533364,
          -0.01792768,  0.01845546],
         [-0.01186803, -0.03532802,  0.03430201, ..., -0.02335827,
          -0.01836921,  0.04370318],
         ...,
         [ 0.03207215, -0.02299529, -0.03732495, ...,  0.02649289,
          -0.01180707, -0.04607392],
         [-0.03632483,  0.04202026,  0.02752912, ...,  0.01388597,
          -0.03608365, -0.01303369],
         [-0.04502362, -0.02944931,  0.00175662, ..., -0.00143489,
           0.02932601, -0.02953453]],

        [[ 0.02590252, -0.03851963, -0.01668659, ..., -0.02067509,
           0.05149981,  0.05127342],
         [ 0.001249  , -0.02364867, -0.03722698, ..., -0.05101777,
          -0.03776454, -0.02906022],
         [ 0.00814081, -0.04156788,  0.05408941, ..., -0.04487805,
           0.01754397, -0.01743769],
         ...,
         [ 0.03443024,  0.02167545,  0.03105572, ..., -0.03077781,
          -0.02916576, -0.02964313],
         [ 0.01510788, -0.02082094,  0.04567786, ..., -0.01319075,
          -0.04525612, -0.05501684],
         [ 0.00453796,  0.0116283 ,  0.03858627, ..., -0.02508489,
           0.03150386,  0.0536808 ]],

        ...,

        [[ 0.02886551, -0.04854227,  0.03472467, ..., -0.04028402,
           0.01617807,  0.04397419],
         [ 0.00320219, -0.01245662,  0.02384754, ..., -0.024647  ,
           0.00083178, -0.03625992],
         [ 0.05028047, -0.04366625, -0.01358984, ...,  0.01003932,
          -0.03596429, -0.02785208],
         ...,
         [-0.02374285,  0.04505142, -0.03439058, ..., -0.00067436,
           0.04633853,  0.00847993],
         [-0.04470385, -0.03449091,  0.03455332, ...,  0.02540766,
           0.04372681, -0.02021619],
         [-0.0298217 , -0.0332165 ,  0.03643354, ...,  0.01071533,
           0.02136384,  0.00465563]],

        [[-0.00096347, -0.00427753, -0.00344714, ..., -0.03452204,
           0.03753065, -0.0235656 ],
         [ 0.01193729, -0.00730126,  0.02294222, ...,  0.0161993 ,
           0.02663701, -0.0157054 ],
         [ 0.0308137 ,  0.03249973, -0.01174243, ..., -0.02107418,
          -0.04920915,  0.03287278],
         ...,
         [ 0.03572166,  0.00306855, -0.02309747, ...,  0.01943098,
           0.00446903,  0.02441757],
         [ 0.01057279, -0.02706401, -0.03275386, ...,  0.01914093,
          -0.04531998,  0.0150493 ],
         [-0.01782798, -0.01369165,  0.02582074, ..., -0.00759341,
           0.01588942, -0.00130801]],

        [[ 0.04629393,  0.01024792,  0.0035022 , ..., -0.04827739,
          -0.01049123,  0.02422086],
         [ 0.05312981, -0.05051543, -0.02442701, ...,  0.03467617,
           0.02978204,  0.00148209],
         [ 0.01720683,  0.01425023, -0.03840847, ...,  0.00365919,
           0.01987996,  0.01830352],
         ...,
         [-0.03486687, -0.0323011 , -0.02910073, ..., -0.01905396,
          -0.02026294, -0.03690915],
         [-0.00554066, -0.00723357, -0.02000781, ..., -0.00811921,
           0.04408833,  0.0372596 ],
         [ 0.0090922 , -0.01382679, -0.03987758, ...,  0.00601131,
           0.0365811 ,  0.02258999]]]], dtype=float32), array([[[[ 0.00252042,  0.03101836, -0.01341135, ..., -0.01935725,
          -0.00976992,  0.01184191],
         [-0.0228476 , -0.03940272, -0.00923939, ...,  0.03344976,
           0.03185516,  0.01042731],
         [ 0.02386844, -0.04333118, -0.03737778, ..., -0.00100547,
          -0.01196839, -0.00075718],
         ...,
         [-0.02157405, -0.04815966,  0.03710104, ...,  0.00496295,
           0.05053549, -0.01096792],
         [-0.05149295, -0.01768197, -0.04403213, ...,  0.04818053,
          -0.01437901,  0.01807151],
         [-0.00978231, -0.02944272,  0.03238323, ..., -0.00698519,
          -0.02913414,  0.04844531]]],


       [[[ 0.03563102,  0.01371952,  0.0396664 , ..., -0.01798198,
          -0.04345372,  0.02694213],
         [ 0.01194809,  0.02951606, -0.01013905, ...,  0.02957372,
          -0.00578855, -0.00253435],
         [-0.0187501 ,  0.01152594,  0.03556026, ..., -0.01580909,
           0.02658848,  0.02870729],
         ...,
         [ 0.03362348,  0.00646003, -0.02488066, ...,  0.06809597,
           0.03192564, -0.04757348],
         [-0.03140789, -0.02652041, -0.02031947, ..., -0.00129933,
           0.00202214,  0.04253552],
         [ 0.04423979,  0.02358708,  0.00844875, ..., -0.00692986,
          -0.04296676, -0.01014784]]],


       [[[-0.0268883 ,  0.01453244, -0.01646548, ...,  0.03047974,
           0.0487852 , -0.02001467],
         [-0.04509613, -0.0094559 ,  0.01724563, ...,  0.03238723,
           0.05001222,  0.04050882],
         [-0.00822905, -0.0336083 , -0.01889887, ...,  0.01039157,
          -0.01923679, -0.04030513],
         ...,
         [ 0.01149964, -0.04083005, -0.03455105, ..., -0.00856484,
           0.02545707, -0.00248417],
         [ 0.03916094,  0.03491487,  0.03068213, ..., -0.00621862,
           0.01017688,  0.03740858],
         [-0.00938056, -0.02430861, -0.02834474, ..., -0.03365536,
          -0.05595778, -0.0379906 ]]],


       ...,


       [[[-0.02201881,  0.0595812 ,  0.01961963, ...,  0.05085997,
           0.0235839 ,  0.01307337],
         [ 0.03209601,  0.00649635, -0.02642289, ...,  0.05951516,
           0.03189167,  0.05255951],
         [ 0.01160082, -0.01268082, -0.04604953, ...,  0.01948292,
           0.0290967 ,  0.03535871],
         ...,
         [ 0.03462484,  0.05198298,  0.02389117, ..., -0.02143951,
          -0.01013402, -0.03479275],
         [-0.0239634 , -0.02601353,  0.02199862, ..., -0.04891312,
           0.03574406,  0.00080271],
         [ 0.03943816,  0.01838709, -0.02716771, ..., -0.03127566,
          -0.05814865,  0.02233391]]],


       [[[ 0.02898308,  0.02189608, -0.01026227, ...,  0.02732165,
           0.01253164,  0.04250894],
         [-0.00151018,  0.02094935,  0.01333111, ...,  0.00100771,
           0.0340788 , -0.0010492 ],
         [ 0.03852335,  0.04324915,  0.02594507, ..., -0.01132585,
           0.0316037 , -0.05266151],
         ...,
         [ 0.0389749 ,  0.04179312,  0.03100296, ...,  0.0548662 ,
          -0.01562927,  0.00805244],
         [-0.03748887, -0.03976798, -0.03557674, ...,  0.05482133,
           0.02935462, -0.0249224 ],
         [-0.02531147,  0.02663747, -0.00500145, ...,  0.01844828,
          -0.02470317, -0.0254565 ]]],


       [[[-0.03016468, -0.02402556,  0.04071452, ...,  0.04981743,
          -0.03398731, -0.03388927],
         [ 0.00648992,  0.02278617,  0.00716355, ...,  0.00568514,
          -0.00597575,  0.03958516],
         [ 0.00504645,  0.02177275, -0.04166963, ...,  0.02543182,
          -0.03454715, -0.00145836],
         ...,
         [-0.0373999 , -0.04432375,  0.03476841, ...,  0.05145759,
           0.03024086, -0.0137553 ],
         [-0.02272739,  0.03541138, -0.03948131, ...,  0.03297606,
          -0.03340914,  0.03974186],
         [-0.02052901, -0.03429596,  0.04339876, ..., -0.01954133,
          -0.03171286,  0.05170113]]]], dtype=float32), array([-3.44428606e-03,  1.07634282e-02, -5.62335970e-03,  4.83171176e-03,
        3.72010330e-03,  8.53292178e-03, -3.30285681e-03,  1.18977128e-04,
        1.17038274e-02, -6.06769172e-04,  2.41358229e-03,  4.28509200e-03,
       -1.30326143e-02, -2.81378115e-03, -2.11443240e-03,  3.65598872e-03,
        2.34925514e-03,  8.75448284e-04,  1.51291431e-03,  6.48738816e-03,
        1.90942292e-03, -3.57833109e-04,  1.57305449e-02, -1.62041304e-03,
        1.49692618e-03, -2.60307943e-03,  1.19913870e-03, -3.89624666e-03,
        1.11108636e-02,  4.39516793e-04,  8.49464536e-03, -6.71630679e-03,
        5.16243698e-03, -2.04579951e-03, -7.87071325e-03,  6.76167081e-04,
        8.72661173e-03, -2.35769013e-03,  8.65284746e-05, -1.04627367e-02,
       -5.39104827e-03,  8.52504559e-03,  1.32312370e-03, -8.39313772e-03,
       -6.95936894e-03, -2.85521313e-03, -9.15443152e-03, -7.44451769e-03,
        7.93803204e-03,  1.41808740e-03,  7.01530976e-03, -5.51338727e-03,
        4.98662982e-03,  2.50227982e-03,  2.81593006e-04, -1.19584510e-02,
       -3.76783242e-03, -1.90160645e-04,  1.00920508e-02, -9.59428772e-03,
       -7.54895015e-03,  6.21881476e-03, -1.44975139e-02,  3.87563673e-03,
        3.26067046e-03,  4.90619428e-03,  1.52727431e-02,  5.70949633e-03,
       -5.14560193e-03, -4.26031696e-03, -1.27678430e-02, -5.06654987e-03,
       -1.34228803e-02, -1.16090651e-03,  5.42212604e-03,  7.03657838e-03,
       -3.86359938e-03, -4.51596035e-03,  1.36316160e-03, -4.49367287e-03,
        3.00042029e-03, -9.17735670e-05, -3.92579054e-03,  5.78755420e-03,
       -2.45799567e-03, -9.99151636e-03, -2.01007612e-02, -2.46049254e-03,
        4.88193985e-03, -2.86535244e-03, -7.29074888e-03,  1.18796518e-02,
        6.77685195e-04, -1.01533569e-02,  7.61099625e-03,  7.12224888e-03,
       -1.26961675e-02, -4.63919714e-03, -4.70376835e-04,  1.15528097e-02,
        3.39105120e-03, -1.22861937e-03,  1.64449203e-03,  4.05425113e-03,
       -6.52227970e-03, -1.15097072e-02,  2.20488780e-03,  2.33183126e-03,
       -1.03220968e-02, -4.48545488e-03,  3.60614830e-03,  5.54888416e-03,
        7.73035083e-03,  6.67183008e-03,  5.05957892e-03,  6.34596730e-03,
       -4.46266588e-03, -8.73698108e-03,  4.18138737e-03,  5.26672229e-03,
       -5.15937991e-03, -3.50099592e-03, -6.91560330e-03,  1.24154901e-02,
       -4.17311676e-03,  1.23795858e-02, -1.01632150e-02, -9.39132087e-03,
       -1.88137835e-03, -3.73472483e-03, -3.85657069e-03,  1.14444532e-02,
       -7.36144139e-05,  8.86372849e-03, -2.53715529e-03, -8.76880158e-03,
        2.87046982e-03, -2.43684812e-03, -1.22070417e-03, -1.61115360e-03,
        1.10681914e-03, -2.86767841e-03, -5.56339696e-03,  1.70574943e-03,
        9.08412319e-03,  2.32086633e-03,  1.31801395e-02,  1.25974705e-02,
        4.06624796e-03, -1.04156267e-02, -6.34946395e-03, -1.13415914e-02,
       -6.05775323e-03, -9.37771425e-03,  3.45015479e-03, -5.99812530e-03,
       -3.23433685e-03,  9.23151337e-03, -7.21268449e-03,  9.12692491e-03,
        1.68501155e-03,  6.21932745e-03,  1.46424752e-02, -3.27592716e-03,
       -1.32761393e-02,  9.45821218e-03,  6.56557875e-03, -2.49571679e-03,
       -2.83098267e-03, -1.76751856e-02, -4.46470454e-03,  5.79436542e-03,
        4.38349554e-03, -9.08203516e-03,  2.06375890e-03,  6.46099076e-03,
       -5.00857888e-04,  5.86190401e-03,  3.91604519e-03,  2.50969431e-03,
       -1.28125108e-03, -1.64961051e-02, -1.77430897e-03,  1.03865368e-02,
       -7.09406799e-03,  7.15240743e-03, -3.61925137e-04,  9.45464987e-03,
        8.46272102e-04,  9.98063385e-03, -8.55499040e-03,  1.09099317e-03],
      dtype=float32), array([ 0.48558718, -0.91653323,  0.74722606, -0.9855373 , -0.45220584,
       -1.2756648 ,  1.2121131 , -0.80476284, -0.7622849 ,  0.30223572,
       -0.7355684 , -1.2113068 ,  0.42788485,  0.9573343 ,  1.0896987 ,
       -0.37197858, -0.11084075, -0.3733096 ,  0.96937454, -1.2292371 ,
        0.28832847, -0.16626726, -0.32931823, -1.1131644 , -0.29246533,
        0.58439213,  0.35379517,  1.1758909 , -0.67764664,  0.67654806,
       -1.1278048 , -0.44521713,  0.6329854 , -0.37352097, -0.43095493,
       -0.8517056 , -0.48646203,  0.5541403 ,  0.9846    , -0.46826902,
        0.7727113 , -0.6675532 , -0.12077389,  0.6181447 , -0.39750117,
        0.36580002,  1.0886235 , -1.5739908 , -1.0421251 , -0.33316824,
       -1.1606654 , -0.87398386, -0.61524856,  1.0879029 ,  0.8102661 ,
        0.7116588 ,  0.9977474 , -0.46489158, -0.6049513 , -0.5272781 ,
        0.79513025, -1.0035166 , -0.61645204,  0.67275554, -0.17682306,
       -1.4685265 , -1.2601559 ,  0.16308711,  0.14609097,  0.9334132 ,
        0.7852106 ,  1.1808351 ,  1.2719558 ,  0.5320651 , -0.8553988 ,
       -0.49333298,  0.7648487 , -1.0418061 , -0.4898662 ,  0.61127037,
       -1.3835475 ,  0.03322806, -0.6969682 , -1.1427574 , -0.24618328,
        0.46151972,  0.63674366,  0.20238611,  0.71347   ,  0.5052249 ,
        0.5315947 ,  0.8071245 ,  1.0016029 ,  0.85408866,  0.4900685 ,
       -1.1367598 ,  0.78502756,  1.3694096 ,  1.0369192 , -0.5563537 ,
        0.27523398, -0.81657135,  0.6783246 , -1.1175632 , -1.0966924 ,
        0.3110505 ,  0.34883252,  1.0084254 , -1.1266932 ,  0.4782425 ,
       -0.46475235, -0.2746145 , -0.8330119 ,  1.213171  , -1.317253  ,
        0.88334   , -0.84283257,  0.92612785, -0.47087973,  0.16266398,
       -0.35611767, -0.53753895, -0.34431303, -1.3175524 ,  0.61612517,
       -0.19533701, -0.75163114, -0.91490597, -1.4604988 ,  1.1119145 ,
        0.58419704, -1.4295012 ,  0.92370236, -0.62301445, -1.2995923 ,
       -1.4874    , -0.4100657 ,  0.06104779, -0.79580635, -1.0650597 ,
        0.06330671, -1.16207   ,  0.3603909 , -0.65708685,  0.79967344,
       -0.28897494,  0.79361194,  0.88235676, -0.83138245,  0.63234544,
       -0.21525429,  0.9339566 , -0.8393604 ,  1.7419722 , -1.5506434 ,
        0.3097499 ,  1.7406749 , -0.4208505 , -0.08776738,  0.7315579 ,
       -1.076915  ,  0.26230597, -0.65344036,  1.0672958 , -0.25085863,
       -1.0515424 ,  0.11172524,  0.41601124,  0.73072773, -1.0915235 ,
       -0.94961303, -0.75146985, -0.69144845, -0.35889944,  0.27938867,
       -0.27748892, -0.9310604 , -0.7136815 ,  1.3624631 , -0.79584444,
        0.9933694 ,  0.59711933,  0.97300893, -0.15556523,  1.2690537 ,
       -1.240657  , -0.71529573,  0.414387  , -1.1710366 , -0.33414972,
        0.6532557 ,  0.7510597 ], dtype=float32), array([1.7275109 , 3.8295295 , 3.2934601 , 6.2618704 , 2.3591337 ,
       6.574086  , 6.2038345 , 3.023567  , 2.605123  , 0.91055804,
       2.6377556 , 5.364954  , 1.4230177 , 3.3868837 , 4.287346  ,
       1.0398933 , 0.6411114 , 1.6214674 , 1.3477652 , 7.480429  ,
       1.1931046 , 2.8523438 , 2.8152616 , 3.6919236 , 2.6555996 ,
       2.385908  , 1.466686  , 3.3007429 , 4.126315  , 3.3346953 ,
       4.554197  , 1.7434453 , 3.4782507 , 2.2165968 , 1.699996  ,
       3.5053842 , 2.6971014 , 4.0110464 , 2.6172128 , 2.00168   ,
       2.4377751 , 3.1289566 , 1.8326052 , 3.060601  , 3.1212351 ,
       1.5423669 , 1.7069693 , 2.7195096 , 3.9562302 , 2.7650542 ,
       5.9883027 , 4.7956996 , 1.2886227 , 5.2213674 , 3.4165103 ,
       2.3426607 , 2.266729  , 1.6172689 , 2.811557  , 3.5005853 ,
       3.9499667 , 4.9656944 , 2.982694  , 2.7586994 , 1.6510925 ,
       5.345809  , 3.2687588 , 1.5825269 , 0.797202  , 2.517657  ,
       2.376626  , 4.953011  , 3.9194944 , 1.9732497 , 6.1359315 ,
       1.1389472 , 3.0316813 , 2.2683218 , 3.036611  , 3.1262546 ,
       4.792966  , 2.343942  , 1.1842163 , 5.2557383 , 1.3077185 ,
       3.0825288 , 2.0087352 , 1.8737974 , 3.7999601 , 1.1168461 ,
       3.0823262 , 1.9753135 , 4.76801   , 2.7409801 , 0.92226845,
       8.265432  , 4.65976   , 5.424172  , 2.9977205 , 2.763788  ,
       3.9061186 , 4.6514993 , 2.5814993 , 2.126799  , 2.757625  ,
       1.67758   , 1.9561027 , 3.658893  , 2.185797  , 1.9393485 ,
       1.1396421 , 1.8544222 , 3.7793887 , 4.697907  , 8.868717  ,
       4.154852  , 2.7465568 , 1.703643  , 5.248539  , 1.1261529 ,
       0.9302029 , 2.6593895 , 2.4497666 , 6.469634  , 3.2276025 ,
       1.8207015 , 1.891703  , 1.5791785 , 4.7560396 , 2.7975392 ,
       2.5077076 , 6.7205048 , 4.5061345 , 3.2136722 , 4.5351787 ,
       3.401743  , 3.1104515 , 1.6918681 , 1.7537214 , 2.5144823 ,
       1.3351201 , 4.7738247 , 1.5510999 , 5.2404103 , 3.4345818 ,
       2.1107583 , 4.2261534 , 3.9052432 , 4.1901755 , 3.6312754 ,
       3.1672313 , 1.5029031 , 2.7893345 , 5.4832563 , 2.8906713 ,
       0.7838935 , 4.7399826 , 2.085693  , 3.590643  , 2.1691897 ,
       4.477105  , 2.3302875 , 5.82927   , 1.4602703 , 1.9676516 ,
       5.0623236 , 2.940492  , 2.4681733 , 3.3590264 , 4.136044  ,
       4.8859925 , 2.0648007 , 2.4962497 , 2.9750957 , 1.243357  ,
       0.8805208 , 2.3982525 , 1.4243047 , 4.116184  , 2.8324172 ,
       3.240068  , 3.3415506 , 3.8026724 , 1.5371829 , 6.8118367 ,
       7.210207  , 2.665047  , 0.95528823, 5.2631793 , 2.2766774 ,
       3.8679042 , 3.5167487 ], dtype=float32), array([-2.20798030e-02, -2.21224478e-03, -3.98729229e-03, -1.77385714e-02,
       -7.69782392e-03, -5.93282748e-03,  2.56681023e-03, -6.10116776e-03,
       -6.51817489e-03, -6.71445578e-03, -1.25911171e-02,  3.33890924e-03,
       -1.59051511e-02,  1.99934817e-03, -6.45925337e-03, -1.42708085e-02,
       -1.60408299e-03,  4.75703040e-03, -7.17344275e-03, -6.17030868e-03,
       -1.60744172e-02,  6.21941872e-03,  2.92221010e-02,  2.95522925e-03,
       -1.80423260e-02,  6.82190992e-03, -1.56057114e-02, -1.82346720e-02,
       -1.35447821e-02,  8.05562455e-03, -7.01476028e-03, -2.85794958e-02,
        7.74026942e-03,  3.72055732e-03, -6.23640418e-03,  7.41918804e-03,
       -3.58580844e-03, -7.18826195e-03, -1.43908318e-02, -8.70876573e-03,
       -1.76788997e-02,  8.53551392e-05, -2.63883919e-03, -2.41759941e-02,
       -9.04519949e-03, -2.29342021e-02, -1.85544472e-02, -1.14787165e-02,
       -1.43085066e-02, -6.06884854e-03, -1.02789300e-02, -1.26060518e-02,
        8.84226616e-03, -2.06220858e-02, -6.19756849e-03, -1.06071709e-02,
       -8.20911489e-03, -8.67757108e-03, -1.08960699e-02,  2.03108042e-03,
       -2.57882308e-02,  5.39410068e-03, -4.21710731e-03, -3.93470097e-03,
        1.86677407e-02, -1.60913225e-02, -1.90400481e-02, -6.63833413e-03,
       -8.85158405e-03,  3.76805267e-03, -2.22058524e-03, -3.18991835e-03,
       -1.19699007e-02, -1.19147412e-02, -2.43213102e-02,  1.95491896e-03,
       -1.29022468e-02, -7.31124775e-03, -1.66118573e-02, -7.72896595e-03,
        1.29232705e-02, -1.50354654e-02,  1.77994855e-02, -1.37336887e-02,
       -1.22874498e-03,  1.25806788e-02,  1.02646593e-02,  8.48543737e-03,
       -1.59347318e-02, -2.39370465e-02, -1.10849878e-02, -2.05079447e-02,
       -2.59797298e-03,  1.40283648e-02,  4.67533106e-03,  2.10246863e-03,
       -4.71461471e-03, -6.27713744e-03, -2.44792663e-02, -2.51515340e-02,
       -2.03250628e-02, -6.74512703e-04, -2.79535148e-02, -8.60100903e-04,
       -3.19702341e-03,  1.21058198e-02, -1.47382785e-02, -4.30760672e-03,
        3.97674367e-03,  4.98869922e-03,  2.57480610e-02,  1.83635904e-03,
       -1.32992575e-02,  9.26118158e-03, -1.27730542e-03, -9.23065841e-03,
        2.21823715e-03, -5.22988755e-03,  1.67133822e-03, -8.88998806e-03,
        4.31077322e-03, -2.17886679e-02, -6.17749710e-03, -8.41985084e-03,
       -5.32888249e-03, -4.64723445e-03, -1.18193282e-02, -1.34942494e-02,
       -1.42354844e-02, -2.10969541e-02,  1.83624681e-02, -6.89192070e-03,
       -1.91553812e-02, -1.36555340e-02, -3.02020228e-03, -4.67352755e-03,
       -6.71097636e-03, -3.12040490e-03,  1.10886274e-02,  7.63733592e-03,
       -2.03743372e-02, -1.11715598e-02, -1.99874807e-02,  1.23091992e-02,
        1.98307028e-03, -4.65373136e-03, -1.94719229e-02, -1.15468474e-02,
       -1.43917147e-02, -2.51294803e-02, -2.40287222e-02, -3.80909373e-03,
       -8.11775215e-03, -1.26633644e-02, -1.56115610e-02, -1.24474987e-02,
       -1.37903513e-02,  6.86312560e-03,  3.91450850e-03, -5.40643139e-03,
       -1.95865147e-02, -2.42185481e-02, -1.59808900e-02, -1.39164529e-03,
        4.13152622e-03, -4.88269096e-03, -1.62099265e-02, -1.13033748e-03,
       -2.70053800e-02, -2.28797048e-02, -1.13216341e-02,  3.51175736e-03,
       -4.25270991e-03, -2.42828950e-02, -1.19947502e-02, -8.96154996e-03,
       -1.11028673e-02, -1.72007130e-03, -2.80972430e-03, -2.10795924e-02,
        1.58336163e-02, -1.54374493e-02,  2.42145779e-03,  1.15654375e-02,
        2.89516035e-03,  7.08779134e-03,  7.82267671e-06, -1.18602486e-02,
       -1.53621053e-02, -1.79698281e-02, -6.42686011e-03, -1.27989296e-02],
      dtype=float32), array([-2.0595323e-01,  5.2509093e-01, -6.2687375e-02,  1.0622166e+00,
        4.0715060e-01, -1.3413168e+00,  3.5761410e-01,  9.6484745e-01,
        6.9958812e-01,  9.8087329e-01,  1.2152759e+00, -4.8904911e-01,
        1.2475787e+00,  6.0536712e-02,  1.0009462e+00,  9.9350178e-01,
        8.8877439e-01, -5.8407718e-01, -8.0924171e-01,  1.2340560e+00,
        8.6486685e-01,  6.0410984e-02,  3.4973830e-01,  5.9184527e-01,
        9.1164482e-01, -1.1947805e+00, -5.3446966e-01, -7.2179854e-01,
        2.0667785e-01,  2.5445703e-01,  2.8032821e-01,  6.2983716e-01,
       -4.6789867e-01,  1.6110457e-01,  1.1402283e+00, -9.4078161e-02,
       -1.0299861e+00, -1.3601098e+00,  1.2429051e+00, -4.7212774e-01,
       -5.2316976e-01,  2.8225678e-01, -8.9260536e-01, -6.7965719e-03,
       -1.0784186e+00, -1.0065290e+00,  1.1905271e+00,  5.8179545e-01,
       -1.1035049e+00,  8.5365438e-01, -9.8221469e-01,  1.5343149e+00,
       -5.2155697e-01,  1.1686027e+00, -1.1582789e+00, -4.0789276e-01,
       -1.2944517e+00, -2.8163511e-01,  2.4580571e-01,  5.4364514e-02,
        7.3918796e-01,  9.2815572e-01,  3.5745062e-02,  3.5635737e-01,
       -2.3172264e-01,  8.7397498e-01,  1.7559288e+00,  7.4428089e-02,
       -6.2393552e-01, -4.4974691e-01, -5.0970894e-01,  1.7829610e+00,
       -5.3843629e-01, -1.0375885e+00,  1.0040303e+00, -3.8243467e-01,
        2.0261079e-01,  3.3717254e-01,  1.0897365e+00, -1.5734342e-01,
        1.8723752e-02,  1.0772936e+00, -4.2557585e-01, -5.4286337e-01,
       -9.1586065e-01,  3.1987658e-01,  6.2457520e-01, -1.7387213e-01,
        1.0768716e+00,  1.0108776e+00, -1.1936303e+00,  4.5694858e-01,
        4.6643654e-01,  6.6004023e-02,  3.9491403e-01, -8.1489034e-02,
        8.6256820e-01,  5.7947707e-01,  2.4142072e-01,  4.7778082e-01,
        5.6430715e-01,  9.1094536e-01,  5.7665068e-01, -4.7266144e-01,
        6.1284328e-01, -3.6237559e-01,  4.2981213e-01,  6.2879616e-01,
        8.9835036e-01, -2.4263828e-01, -5.1072128e-02,  1.8707114e-01,
       -1.4750338e+00,  2.1033622e-01,  3.7409508e-01,  2.0178850e+00,
       -2.0004237e-01, -1.1545542e+00, -8.5535127e-01, -2.2610402e-02,
       -7.1730328e-01,  1.0800476e+00, -4.9490282e-01,  1.1184469e+00,
        8.2249594e-01, -6.8392003e-01,  9.0972418e-01,  5.9412950e-01,
        1.3897630e+00,  1.2599384e+00,  3.2019779e-01,  3.8085175e-01,
        9.7138673e-01,  1.1565655e+00, -9.8635840e-01,  9.8838395e-01,
       -1.8299689e-03, -6.4775062e-01, -9.6938074e-01, -3.5667133e-01,
        6.5568513e-01, -1.0014175e+00, -8.3450377e-01,  3.9749289e-01,
        4.1048566e-01,  1.0649719e+00, -2.2355615e-01,  8.0573827e-01,
        6.5417910e-01,  9.9470896e-01, -9.1122943e-01, -4.7100881e-01,
       -7.8282702e-01,  5.7183105e-01,  1.4923913e+00, -1.0724895e+00,
       -7.7882886e-01, -2.1809654e-01,  1.8459736e+00,  3.1149643e-02,
       -3.1080830e-01,  1.2666113e+00,  1.9102651e+00,  5.2676886e-01,
        4.5603636e-01,  8.9318866e-01,  9.0500385e-01, -8.3214414e-01,
       -9.4884551e-01,  5.4253721e-01, -5.6783122e-01,  3.9988938e-01,
       -4.8168066e-01,  1.1989108e+00,  8.5329562e-01, -8.3828652e-01,
        3.7116909e-01,  2.1216957e-01,  1.2375131e-01,  1.1582736e+00,
       -4.2407891e-01, -9.1778278e-01,  6.9922787e-01,  9.4700003e-01,
        6.9780952e-01, -9.4990931e-02, -1.2388517e+00,  8.4794962e-01,
        4.3652365e-01,  1.7111473e+00, -2.9028592e-01,  2.3936607e-01],
      dtype=float32), array([ 2.6545124,  7.4016695,  7.6683154, 28.602633 ,  3.3066885,
        3.9926205,  3.45987  , 10.068074 ,  9.914215 ,  5.0576787,
        4.4212823,  1.8635857, 10.288988 , 12.613147 ,  8.140038 ,
        4.445913 , 25.261772 ,  2.438434 ,  3.3366978, 27.55276  ,
        2.6067326,  8.416399 ,  4.3829594, 20.275547 ,  2.766041 ,
        1.6853272,  2.8059242,  4.1658688,  2.8039427,  4.4786954,
        2.2548351,  2.0090373,  2.4301505, 12.765996 , 23.204067 ,
        2.071275 ,  9.146946 ,  8.545051 ,  5.797036 ,  2.743731 ,
        5.7134514,  2.7195883,  6.885976 ,  2.1701102,  3.6691568,
        6.2583227,  4.7021585,  2.5661333,  4.0165997,  4.0041227,
        7.4344893,  9.170882 ,  4.6613297,  3.1216214,  6.4831715,
        5.180608 ,  3.52286  ,  1.4216065,  2.7934344,  7.2280073,
        4.467431 ,  8.241364 ,  5.5383587, 15.042997 ,  3.4369752,
        3.985907 , 20.538338 ,  1.4856104,  3.2269812,  3.4641285,
       10.195771 , 22.209457 ,  9.753325 ,  3.331698 ,  4.4613557,
        1.4097064,  6.8601556, 11.016713 ,  3.574096 ,  3.4373796,
        3.8017747, 14.987616 ,  1.6656073,  2.828833 ,  3.562783 ,
        1.6708544, 15.131115 ,  3.172396 ,  3.8078868, 11.843788 ,
        1.7540506,  5.463872 , 11.265203 ,  8.142693 ,  7.4146852,
        2.323758 , 15.802559 ,  2.532515 ,  3.4150238,  3.188935 ,
        5.766219 , 11.032667 ,  2.5037029,  2.915007 , 22.840761 ,
        3.263608 ,  5.275568 ,  2.4409804,  9.259255 ,  1.8008395,
        1.5246327,  1.3568351,  8.8851385, 14.371834 ,  3.2786098,
       26.222702 ,  4.066102 ,  3.6727364,  3.37734  ,  3.882185 ,
        2.4900622,  5.2245483,  8.152594 , 19.845533 ,  1.9690751,
        1.8587748,  9.746234 ,  8.310899 , 33.652966 ,  4.9760456,
        4.3531423,  6.3121314,  5.670186 ,  6.0028896,  5.873597 ,
       22.01951  ,  2.0039146,  9.240315 ,  5.959749 ,  4.6140738,
        3.1217117,  3.6109328,  6.196581 , 13.247303 ,  4.10398  ,
       11.225017 ,  3.99642  , 15.15994  ,  4.8126917,  7.240621 ,
        1.9753395, 12.336732 ,  3.989256 ,  2.6254034, 20.244997 ,
        9.763213 ,  3.3860674, 15.304597 , 38.479687 ,  9.041429 ,
        5.3654814,  8.364396 , 31.654053 ,  3.5840802, 23.071787 ,
       11.218874 , 26.36661  ,  6.0749493,  4.0786138,  2.5079293,
        9.143545 , 14.306503 ,  3.564671 ,  3.6510894,  4.411018 ,
        5.1213136,  1.8802963,  4.3471804,  3.6142492,  9.448006 ,
        3.7131872,  3.020514 ,  4.9859896,  3.5111616, 11.803442 ,
        1.5101753,  7.430436 , 19.769983 ,  2.3799372, 33.64569  ,
       12.8758   ,  2.6193066], dtype=float32), array([[[[-0.04944688,  0.03183994,  0.03167672, ..., -0.05033632,
           0.02643749,  0.01805178],
         [-0.05632337, -0.08292919, -0.06225871, ..., -0.00210651,
           0.01647832, -0.04758152],
         [ 0.00915043,  0.03353684, -0.0249595 , ...,  0.07672396,
          -0.07930143,  0.00334185],
         ...,
         [ 0.05679417,  0.05437416, -0.04008317, ..., -0.02395025,
           0.00686868, -0.03795838],
         [-0.07335719, -0.01217471, -0.02813468, ..., -0.04197486,
           0.00059747, -0.03587358],
         [ 0.05382331, -0.05884834, -0.03073071, ..., -0.04638604,
          -0.05943778, -0.00692331]]]], dtype=float32), array([[[[ 1.54655855e-02,  2.40946133e-02, -4.83134910e-02, ...,
          -2.06460916e-02,  2.44513359e-02, -3.75460163e-02],
         [-1.37936277e-02,  3.47971693e-02, -3.48574743e-02, ...,
          -1.57787558e-02, -1.46720605e-02, -2.24748384e-02],
         [ 5.25321178e-02, -3.05742938e-02, -4.87439521e-02, ...,
          -6.55805878e-03,  9.64712165e-03, -4.16323692e-02],
         ...,
         [ 3.93622406e-02, -5.65285012e-02,  4.77674752e-02, ...,
          -2.81839333e-02,  4.49474119e-02,  1.26092676e-02],
         [-2.61720531e-02,  5.41106015e-02, -3.80432443e-03, ...,
          -5.17833307e-02,  1.12680730e-03,  3.60077471e-02],
         [-1.36574893e-03, -3.61516401e-02,  5.71300369e-03, ...,
          -4.04201634e-02,  1.75441150e-02, -5.09356009e-03]]],


       [[[-1.99947115e-02,  3.59948948e-02, -3.26359458e-02, ...,
           4.65386873e-03, -7.27504306e-03, -1.80430561e-02],
         [-5.24591580e-02,  2.81765964e-02, -3.01296897e-02, ...,
           2.13022623e-02,  1.41742127e-02,  4.72104438e-02],
         [ 1.35269379e-02,  4.41849157e-02,  1.77928079e-02, ...,
           2.48002791e-04,  6.97891088e-03, -1.14485119e-02],
         ...,
         [-2.70298328e-02,  3.30007486e-02,  3.70676629e-02, ...,
          -2.91054528e-02, -3.49883214e-02,  3.83117646e-02],
         [-4.36348841e-02,  1.95257366e-02,  3.29056568e-03, ...,
          -4.95871603e-02,  4.17972989e-02,  1.20851223e-03],
         [-4.41037416e-02,  4.40501682e-02,  2.83584874e-02, ...,
          -2.05389522e-02,  1.18446741e-02, -9.51198768e-03]]],


       [[[-4.53920439e-02,  2.49526296e-02,  2.62873434e-02, ...,
           5.56241209e-03, -3.41625232e-03, -2.19568908e-02],
         [-2.38040928e-02,  4.32690699e-03,  4.00188901e-02, ...,
          -3.06278411e-02,  4.03853618e-02,  4.23738137e-02],
         [-3.55149359e-02,  3.12762856e-02, -4.57772836e-02, ...,
          -6.86513409e-02, -1.23201730e-02,  2.77849641e-02],
         ...,
         [-5.93595672e-04,  5.74504491e-03, -3.43859685e-03, ...,
           6.40525669e-03, -2.08965689e-02, -9.54835862e-03],
         [ 1.55427186e-02,  5.33935428e-02,  4.45377678e-02, ...,
           6.30550133e-03, -3.04047558e-02,  5.05219996e-02],
         [ 3.74142616e-03,  2.91218925e-02, -1.38346497e-02, ...,
          -4.12177332e-02,  3.45847681e-02,  1.66969912e-05]]],


       ...,


       [[[-1.62193906e-02,  5.14391549e-02, -2.33451333e-02, ...,
          -2.88919476e-03, -7.98324868e-03, -2.66723689e-02],
         [-3.69694568e-02, -2.91958582e-02, -2.78406944e-02, ...,
           3.60715985e-02, -4.58251089e-02,  4.95302081e-02],
         [-4.57210839e-02,  4.39287908e-02,  2.21293885e-02, ...,
           1.30768511e-02, -1.39946947e-02, -1.51862931e-02],
         ...,
         [-2.22801194e-02, -5.12033217e-02,  2.37318557e-02, ...,
           8.89611244e-03, -9.52393096e-03, -3.14458683e-02],
         [-1.35793211e-03,  3.54137830e-02, -3.12341787e-02, ...,
          -3.42780650e-02, -3.61034311e-02,  2.98620053e-02],
         [ 2.85487752e-02, -2.96679884e-02, -4.47153524e-02, ...,
          -1.26106082e-04, -3.15560475e-02, -1.93746984e-02]]],


       [[[-9.23204329e-03,  5.03454246e-02,  3.04587521e-02, ...,
          -1.40016591e-02,  1.49005307e-02,  3.36456485e-03],
         [ 5.95309027e-03, -3.63853872e-02, -2.24523973e-02, ...,
           4.23015468e-02, -2.97014732e-02,  4.72447611e-02],
         [ 2.85118669e-02, -2.30174232e-02,  3.92322652e-02, ...,
          -1.22632822e-02, -3.15675400e-02,  1.61382761e-02],
         ...,
         [ 1.39165102e-02, -3.33500430e-02,  4.66777105e-03, ...,
           4.69204411e-02,  4.44140472e-02,  3.45456824e-02],
         [-3.06852013e-02, -5.59973950e-03, -9.57361830e-04, ...,
           4.75173779e-02, -3.34597164e-04,  3.13503621e-03],
         [ 1.83720468e-03, -2.78982949e-02, -2.08461601e-02, ...,
           4.75507136e-03, -4.96902270e-03, -8.50230735e-03]]],


       [[[ 2.91291475e-02, -2.56528854e-02, -3.50678153e-02, ...,
           1.13326712e-02,  7.07069831e-03,  2.96817124e-02],
         [ 2.65053548e-02, -2.70168073e-02, -2.01472845e-02, ...,
           5.55745959e-02,  3.79637210e-03,  1.13085676e-02],
         [-2.62866374e-02,  2.23850794e-02,  3.62009071e-02, ...,
          -2.03077346e-02,  6.84520742e-03, -2.14516837e-02],
         ...,
         [ 5.44022396e-02,  2.47555407e-04, -1.59677514e-03, ...,
          -2.97718290e-02, -4.15782770e-03,  1.27906920e-02],
         [-3.36104520e-02,  4.25417982e-02, -4.06351164e-02, ...,
          -4.36858945e-02,  1.72084048e-02,  4.26292839e-03],
         [ 1.84518807e-02, -4.72356081e-02, -2.01131031e-02, ...,
          -5.36194146e-02,  7.81531353e-03, -3.65868509e-02]]]],
      dtype=float32), array([[[[-0.00945598,  0.02841613, -0.04020047, ...,  0.00127307,
          -0.03757545,  0.04017625],
         [ 0.01112853,  0.03301222,  0.02871325, ..., -0.03615589,
           0.00201223, -0.03515606],
         [ 0.00696996, -0.01672533, -0.04696714, ..., -0.03364775,
          -0.03847058, -0.05230547],
         ...,
         [-0.00818293,  0.04252392, -0.03185375, ..., -0.02227944,
          -0.0170473 ,  0.01991128],
         [ 0.05235721, -0.04227291,  0.03198914, ..., -0.04914775,
          -0.04092005,  0.00819345],
         [ 0.01801684,  0.00724008,  0.00647338, ..., -0.01723821,
           0.02680267, -0.02508125]],

        [[ 0.01701027,  0.02570957, -0.00207635, ...,  0.02599224,
          -0.03373102,  0.02898713],
         [ 0.06029374,  0.01180277, -0.0118236 , ...,  0.01580129,
          -0.00759436,  0.02955465],
         [ 0.00585443,  0.00180286, -0.02260593, ..., -0.01311675,
           0.01308925, -0.04766629],
         ...,
         [ 0.04541196,  0.03835889, -0.00602041, ...,  0.04351494,
          -0.05427241,  0.04843681],
         [-0.0297417 ,  0.03363052,  0.03791275, ...,  0.0034712 ,
           0.00072465,  0.03659126],
         [-0.01315953,  0.03893169, -0.00600468, ..., -0.00067449,
           0.05294299, -0.0289511 ]],

        [[-0.01508565, -0.03274999,  0.02882067, ...,  0.0059304 ,
           0.03053453,  0.045702  ],
         [ 0.03368375,  0.01174897,  0.03773272, ..., -0.01856161,
           0.00276092,  0.023925  ],
         [-0.01416689,  0.02094896,  0.01553441, ..., -0.04401079,
          -0.01059739, -0.00720304],
         ...,
         [ 0.01119307,  0.02194777, -0.06546329, ...,  0.03560471,
          -0.01731801, -0.00595808],
         [ 0.02320332,  0.02017538,  0.02506248, ...,  0.0147858 ,
          -0.00228817,  0.01006596],
         [-0.00587562,  0.02678664,  0.02196457, ...,  0.01966772,
           0.0225291 , -0.00070902]],

        ...,

        [[ 0.02058868,  0.04579152, -0.00136837, ..., -0.02304792,
          -0.04036546, -0.00629852],
         [ 0.01693507, -0.04236389, -0.03258004, ...,  0.03582069,
           0.04984747,  0.03914234],
         [ 0.0287505 , -0.01094929, -0.00454874, ..., -0.04959707,
          -0.0013853 , -0.00700428],
         ...,
         [-0.02059009, -0.00803695, -0.00957832, ...,  0.06443757,
          -0.03641737, -0.01949557],
         [-0.01828408,  0.03584052,  0.01025262, ...,  0.03374818,
          -0.03000612, -0.05504053],
         [-0.02204821,  0.04334053,  0.04741602, ..., -0.03376495,
          -0.02085155, -0.0248751 ]],

        [[-0.01459182,  0.04618521,  0.0216709 , ...,  0.04236485,
           0.00357836,  0.00558848],
         [-0.0344244 ,  0.03808422,  0.04530268, ...,  0.03447289,
           0.00744386,  0.03000662],
         [-0.01183631, -0.01607232, -0.02028474, ..., -0.03384801,
          -0.01142965, -0.02908564],
         ...,
         [-0.01238061,  0.03077932, -0.00357373, ...,  0.02696279,
          -0.0640066 ,  0.00915961],
         [ 0.01361722,  0.01020887, -0.04548527, ...,  0.0283833 ,
           0.01601032,  0.03510857],
         [ 0.02149919, -0.03825399,  0.01487574, ..., -0.00251511,
           0.03978853,  0.02819081]],

        [[-0.01172263,  0.00915654, -0.02382975, ..., -0.02797189,
          -0.00434547,  0.04711732],
         [-0.00605178, -0.03032601, -0.01890704, ..., -0.02998234,
           0.00621525,  0.01147081],
         [ 0.04700278,  0.00839376, -0.01869011, ...,  0.01739628,
           0.02711339, -0.02879045],
         ...,
         [-0.03568255, -0.01872321,  0.00097731, ...,  0.05684798,
           0.01326404, -0.04520174],
         [ 0.04599718,  0.00546769, -0.03857959, ...,  0.00793821,
          -0.0502454 , -0.05251091],
         [ 0.02373693, -0.026515  , -0.00502962, ..., -0.03689104,
           0.05894177,  0.03658053]]]], dtype=float32), array([[[[-0.04350176,  0.06279013,  0.01840225, ...,  0.05963832,
          -0.00495585,  0.01839451],
         [ 0.05607625, -0.05752335,  0.03267692, ...,  0.03031711,
           0.01595881,  0.02430122],
         [-0.0257891 ,  0.05817683, -0.02217916, ..., -0.05560855,
          -0.06811162,  0.05147288],
         ...,
         [-0.02198073, -0.02932294, -0.05179107, ..., -0.01312411,
          -0.00640274, -0.00162082],
         [ 0.00055819, -0.03356099, -0.00991996, ..., -0.00443632,
           0.01649496,  0.03108657],
         [-0.04771621,  0.00797852, -0.02989343, ...,  0.01855477,
           0.06582355, -0.04583936]]]], dtype=float32), array([-1.77114699e-02, -8.10432248e-03, -1.07625099e-02, -6.56862697e-03,
       -4.02214983e-03, -9.10967030e-03, -4.93633444e-04, -1.50728608e-02,
        1.97450444e-02, -4.84680617e-03, -1.31472677e-03, -8.71931948e-03,
        2.12704716e-03, -1.84244793e-02,  5.01747616e-03,  8.51040590e-04,
       -1.54425735e-02, -1.47083336e-02,  6.30561635e-03, -2.95077509e-04,
        2.53333268e-03, -1.10380398e-03,  2.85147340e-03,  1.52779371e-03,
        2.31887656e-03, -1.07897772e-03, -1.18087744e-02, -5.79510443e-03,
       -5.32501959e-04,  2.72735022e-03, -7.02924421e-03, -1.29890982e-02,
        3.18222702e-03, -1.09157795e-02, -1.15365414e-02, -1.45318508e-02,
       -1.05822915e-02, -8.21382366e-03, -1.47484045e-03, -4.13512299e-03,
        1.80397630e-02, -2.48673800e-02, -2.00700737e-03, -1.09171132e-02,
       -6.55157585e-03, -2.06219200e-02, -2.94174487e-03, -3.58632504e-04,
       -9.48977005e-03, -9.33177397e-03,  8.26014671e-03, -6.11813180e-03,
        6.05259556e-03, -5.77905308e-03, -1.81713495e-02, -1.65149737e-02,
       -1.39851458e-02, -1.58997029e-02,  1.43485218e-02, -6.89832401e-03,
       -9.19352379e-03,  2.45273206e-03, -7.09713483e-03, -2.26035784e-03,
       -1.76157057e-02, -5.16795274e-03,  1.45434486e-02, -1.57308225e-02,
       -1.51732601e-02, -1.23695182e-02, -1.04728248e-02,  3.61245847e-03,
       -1.88484322e-02, -1.95153970e-02, -5.89178409e-03, -5.56237949e-03,
       -1.15935151e-02, -1.74226996e-03,  2.29121908e-03, -5.04043885e-04,
       -1.00294745e-03, -2.04964597e-02, -8.77017993e-03,  7.66803324e-03,
       -1.20661436e-02, -6.94553414e-03, -1.32663855e-02,  8.37529369e-04,
        6.81441976e-03, -1.10925743e-04,  3.92145058e-03, -6.85359119e-04,
       -1.23400921e-02, -6.70410087e-03,  1.11502931e-02,  9.25636850e-03,
       -9.75169428e-03, -6.54846954e-04,  1.05114579e-02,  7.88162812e-04,
       -1.02245659e-02, -9.73655935e-03, -1.01903966e-02,  6.35353208e-04,
       -1.39098000e-02, -7.61714019e-03,  1.29840085e-02, -5.85493445e-03,
        4.55926452e-03, -4.04279941e-04, -3.64472833e-03,  1.47091702e-03,
       -2.03230884e-02, -8.80613457e-03,  9.54915117e-03, -1.31047461e-02,
       -1.96736678e-03, -5.67622576e-03, -6.64173672e-03, -2.97509949e-03,
       -1.32107697e-02, -1.92680545e-02, -1.39579189e-03,  7.70575693e-03,
        4.40095086e-03,  9.43590794e-03, -1.23943659e-02, -7.51286978e-03,
       -1.94173809e-02, -1.41742472e-02,  4.86329198e-03, -7.42431218e-03,
       -3.74295004e-03, -1.53148463e-02,  4.91723465e-03,  4.19161143e-03,
        1.93820032e-03, -9.33435559e-03, -5.34683373e-03, -2.18365360e-02,
        4.52288147e-03, -1.28914807e-02,  1.32598998e-02, -7.52525113e-04,
        6.63612550e-03,  4.12318949e-03, -2.89325486e-03,  1.05687547e-02,
       -8.13639443e-03,  6.06345944e-04, -5.93261840e-03, -5.39316237e-03,
       -1.61322523e-02,  1.26088178e-03, -1.17592001e-03,  1.20858895e-02,
        9.48400237e-03, -1.68286581e-02, -5.17523428e-03, -5.77850593e-03,
        9.70489439e-03,  1.19883753e-02, -2.50293734e-03, -1.36318738e-02,
        2.23254077e-02, -9.82717238e-03,  3.13429814e-03,  1.00633986e-02,
       -6.77302771e-04, -1.01960311e-02,  7.82258692e-04, -1.36270169e-02,
       -1.04989586e-02,  4.98927711e-03, -6.95833191e-03, -3.87296823e-05,
       -1.90463960e-02, -4.27205022e-03, -1.73143353e-02,  3.21371644e-03,
       -1.11294203e-02, -8.15607700e-03,  1.81470886e-02, -2.04295591e-02,
        2.95856455e-03,  6.26422465e-03, -4.50116582e-03, -1.01627130e-02,
       -9.25197173e-03, -2.74602440e-03, -2.77844584e-03, -1.88005471e-03],
      dtype=float32), array([-0.8457445 , -0.80157727,  0.65362513,  0.6329015 , -0.8030427 ,
        0.8725854 , -0.4451176 ,  1.2913966 , -1.0349187 ,  0.22189057,
        0.41428924,  0.28436857,  0.6397587 ,  0.4366616 , -0.48620927,
        0.37508357,  0.8410998 , -0.25921342, -0.81050783, -0.10595994,
       -1.2431841 ,  0.18141708, -0.21121334, -1.5501776 ,  0.6592975 ,
       -0.1846918 ,  0.442579  , -0.42206794, -0.03666183, -0.393755  ,
        0.6159067 ,  0.43075085, -0.6719777 ,  0.93941665, -0.42248887,
        0.89602387, -0.0631237 , -0.5025931 , -0.633887  , -1.0828843 ,
       -1.1010351 ,  0.16297033,  0.6602591 , -0.91860074,  0.13326666,
       -0.88607234, -1.2160909 , -0.49142802,  0.6346333 ,  0.3649787 ,
       -0.8172398 , -0.36371997, -0.28239647, -0.9575148 , -0.395048  ,
        0.83328635,  1.1518207 , -0.27982342,  0.51517147, -0.56864214,
        0.35955617, -0.5452014 ,  0.49501565, -0.9454618 ,  0.23506945,
       -0.7961959 ,  0.11960418,  1.0153768 ,  1.3124707 , -0.23513527,
       -0.14871256, -0.51478237, -0.35201243, -0.9833625 ,  0.81590575,
       -0.8013501 , -0.78161496, -0.40290704, -0.3322554 ,  0.280425  ,
        0.5280275 ,  1.5366007 ,  0.33102253, -0.6504558 ,  1.1343455 ,
       -0.19963995, -0.7301506 ,  0.21654336, -0.67366314,  0.716202  ,
       -0.49896082, -0.689367  ,  0.23173344, -1.2199973 , -1.1485147 ,
       -0.92730457,  0.00647374, -0.4627371 , -0.53968376, -0.43166533,
        0.22713248,  0.64119947, -0.26090834, -0.6374674 ,  0.6874258 ,
        0.57290536,  0.5183227 ,  0.97474897, -1.3092076 ,  0.13344036,
       -0.41482526, -0.18141448,  0.4557095 , -0.16748652, -0.7385818 ,
        0.06033431, -1.3560278 ,  0.5949673 ,  0.2769744 ,  0.12088337,
        0.9148041 ,  0.99276495, -0.42591083, -0.48913875, -0.14719422,
       -0.9131471 , -0.61431247,  0.22786798, -0.40804887,  1.0775502 ,
        0.00704445,  0.5624767 ,  1.4015627 ,  0.01009466, -0.40252286,
       -0.9542419 , -0.6427005 , -1.005245  ,  0.3479819 , -0.05102669,
       -0.11801889,  0.12696743, -1.2281672 , -0.3347313 , -0.42894453,
        0.5705187 ,  0.19835751, -0.32130617, -0.33442435,  0.30922598,
       -0.8960988 , -0.09290392,  0.6273294 ,  0.01345221,  0.14154059,
        0.72722685, -0.6677495 ,  0.92971987, -0.698565  , -0.545775  ,
        0.4136513 , -0.40087146,  1.0012629 ,  0.05854788, -0.5800197 ,
       -0.17753208, -0.38351485, -0.7661137 , -1.2097499 ,  0.35777643,
       -1.0978005 , -0.9111623 , -0.5537026 , -0.5861336 , -0.22649688,
       -0.8370849 ,  0.93496424,  0.30402836,  1.1651093 , -0.6627831 ,
        1.1779094 , -0.79766506, -1.0973984 ,  0.26878116, -0.57527727,
       -0.28106433,  0.98611045,  1.1484275 ,  0.8749121 ,  0.5083894 ,
       -0.47979605,  0.96507293], dtype=float32), array([2.771506  , 2.1133208 , 0.7103249 , 1.691784  , 1.7471814 ,
       1.0807581 , 1.3206047 , 6.0596757 , 2.6208882 , 0.8143742 ,
       0.74227935, 0.60760087, 2.0189893 , 1.7142633 , 1.9452215 ,
       1.4205707 , 1.241507  , 1.8858675 , 1.120404  , 0.7829865 ,
       1.920922  , 1.1436158 , 0.68089485, 3.573173  , 0.49307758,
       1.7681792 , 1.294992  , 2.4926689 , 1.2948009 , 1.374033  ,
       1.284761  , 1.0844879 , 1.0217522 , 1.2638999 , 1.2169946 ,
       1.693591  , 1.6535103 , 2.192157  , 0.9772559 , 3.06277   ,
       1.5795462 , 0.52629083, 1.8223063 , 0.90729123, 0.5881708 ,
       1.3515506 , 2.1407595 , 1.971061  , 1.4198418 , 1.9474571 ,
       1.6709142 , 0.82690036, 0.8517646 , 2.4408927 , 1.5898788 ,
       2.5356467 , 2.1104097 , 0.7680131 , 3.9794142 , 1.6783842 ,
       1.9078022 , 1.3453717 , 1.4863714 , 2.2505996 , 1.6472751 ,
       2.0916245 , 2.5798843 , 2.1834133 , 2.1741703 , 2.0288303 ,
       1.5308875 , 2.3345733 , 1.5699706 , 3.1832926 , 0.9389202 ,
       1.164408  , 2.383082  , 1.5621443 , 2.179197  , 1.0406762 ,
       0.68286026, 4.179088  , 2.54617   , 2.6919534 , 2.3228545 ,
       2.0570564 , 1.0724257 , 1.1860021 , 2.4761665 , 0.96757805,
       1.5039191 , 2.1072273 , 3.1260068 , 2.9137821 , 2.6677663 ,
       2.6531425 , 1.3321966 , 2.714221  , 1.964331  , 0.6416294 ,
       1.8409313 , 0.8118698 , 1.5141689 , 1.687418  , 0.7438564 ,
       1.2229674 , 2.190491  , 0.9583752 , 3.9638302 , 1.4524941 ,
       1.9673284 , 2.097412  , 0.8885475 , 1.0214841 , 1.7323751 ,
       0.93146634, 2.665587  , 0.8040365 , 1.1258382 , 1.4237819 ,
       0.89600885, 1.6792119 , 1.3871871 , 1.0413325 , 1.0010228 ,
       2.1498795 , 3.8602283 , 1.1762422 , 1.6712124 , 0.97378963,
       1.718995  , 1.1839991 , 3.8871617 , 0.50558007, 3.8376868 ,
       2.0760212 , 1.8188412 , 1.5960823 , 1.3585641 , 1.5943729 ,
       0.93376184, 1.102254  , 2.5921571 , 1.4739136 , 1.8240265 ,
       1.5843564 , 0.6042341 , 1.4471378 , 1.3947299 , 0.97619903,
       1.6355089 , 0.8256817 , 1.4629201 , 1.312339  , 0.88581836,
       2.0274878 , 0.94251996, 2.8766422 , 1.4344141 , 1.7859042 ,
       0.5061717 , 1.7490804 , 1.3873181 , 1.257964  , 0.9134593 ,
       2.3881006 , 0.8880209 , 1.3676869 , 2.8781514 , 0.89809066,
       4.173968  , 2.3222103 , 0.9708083 , 1.2869856 , 0.70032847,
       3.4198668 , 2.9164515 , 1.7331382 , 1.0378194 , 0.80914325,
       3.199314  , 1.732153  , 5.5352936 , 0.64805466, 2.6873178 ,
       0.9037819 , 2.6419811 , 1.8720242 , 1.2987751 , 0.4201868 ,
       2.0083747 , 1.8545796 ], dtype=float32), array([ 0.00161015, -0.01230804,  0.00119042,  0.01008154, -0.00402688,
       -0.0036723 ,  0.01254891, -0.00915217,  0.00906186, -0.00739654,
        0.00178671, -0.0076496 , -0.01378371, -0.00497482, -0.00167564,
        0.01071866,  0.010846  , -0.0038936 ,  0.00195191, -0.00074924,
        0.01352427,  0.00780399, -0.00030722, -0.01834248,  0.00148411,
       -0.00733218, -0.01698182, -0.00237471,  0.00141259, -0.00868446,
       -0.01546273, -0.00304006, -0.0162478 , -0.009764  ,  0.0077818 ,
       -0.01852331, -0.01100588,  0.00092448, -0.00683213, -0.00900087,
        0.0062172 , -0.01352675,  0.00319276, -0.00869805, -0.00105815,
       -0.0093652 , -0.01630929, -0.01351005, -0.01263967,  0.011573  ,
       -0.00176444, -0.00185864, -0.0031728 ,  0.00304206, -0.00867752,
        0.01178044, -0.00268223, -0.00303807,  0.00161511, -0.01264966,
        0.00751929, -0.00161913, -0.01376645,  0.00831829,  0.01467124,
       -0.00796588, -0.01369292, -0.00352406, -0.02100463,  0.00696507,
        0.00074961,  0.00775582, -0.02357509, -0.00773656,  0.0044316 ,
       -0.00228321, -0.00556356,  0.00412682, -0.00168617, -0.00064838,
        0.00071707,  0.00182721, -0.00677602,  0.01070626,  0.00216766,
       -0.01654428,  0.00112411, -0.00313975,  0.00031896,  0.00132938,
       -0.00357314,  0.00739852, -0.00701615, -0.00655044, -0.01195644,
        0.00628943,  0.00470838, -0.01120806, -0.0136451 , -0.01402388,
       -0.00522979, -0.01072021, -0.0071939 , -0.00593162, -0.01430481,
       -0.00341895,  0.00382249, -0.01478494, -0.00853466,  0.00306771,
       -0.00787625, -0.02064586, -0.00847577, -0.0091231 , -0.00897706,
       -0.01361837, -0.00268705, -0.00852036, -0.00382947, -0.01246349,
       -0.00859888, -0.01018046,  0.00135637,  0.00020215,  0.00308333,
        0.00639644,  0.01054344, -0.00502384,  0.00391277,  0.00125451,
        0.00417075, -0.00044708, -0.01006339, -0.00062771, -0.00017449,
       -0.00598472,  0.00173319, -0.00148762, -0.00622819,  0.00731196,
        0.0053535 , -0.00399122,  0.00269909, -0.01246401, -0.00513494,
       -0.00131348, -0.0068079 , -0.01570113, -0.02237296,  0.00292674,
       -0.01253296,  0.00141165, -0.00347192, -0.01401288, -0.00279555,
        0.00637937, -0.01894031, -0.00879728, -0.01089578,  0.00708606,
       -0.00311101, -0.00072834, -0.00872928, -0.00801362, -0.0136047 ,
       -0.0030383 , -0.0148053 , -0.00982965, -0.01158572, -0.021617  ,
       -0.022966  , -0.01853325, -0.00267102, -0.01132298, -0.00679836,
       -0.01129023,  0.00480521, -0.0107525 , -0.00085874,  0.00134495,
        0.00580348, -0.00799994, -0.00811713,  0.00619947, -0.01188325,
       -0.00045761, -0.01234332, -0.00544107, -0.01066659,  0.00121919,
       -0.00978152,  0.007055  ], dtype=float32), array([-0.8521117 ,  0.21609439,  0.6822487 , -0.7034344 , -0.63050234,
       -0.7895329 ,  0.7519036 , -0.11636494, -0.33851942, -1.2293513 ,
       -0.10369103,  1.4153031 ,  0.9122595 ,  0.5770233 , -1.1757585 ,
       -0.5183881 , -0.1946864 , -0.7741598 , -0.5687796 , -0.44040883,
        0.81161755, -0.6373255 ,  0.45970255,  0.9343464 ,  0.78873193,
        0.05493455,  0.48828572, -0.01114117,  1.682497  ,  0.778113  ,
       -1.284524  ,  1.142483  ,  0.5417913 , -1.2937016 , -0.63221097,
       -0.7225319 ,  1.4289538 ,  0.02036004,  1.4474552 , -1.1167367 ,
       -0.80467916, -0.6641621 ,  1.076399  , -0.67646813,  0.40581247,
        0.16196483, -0.68581563, -0.26709044,  0.47728595, -0.41072667,
       -0.7210965 ,  0.5142046 ,  0.24184419,  0.29731575,  0.7343926 ,
       -1.0010216 , -0.4246952 , -0.48242062,  1.0982211 ,  1.0454518 ,
       -0.80661714,  0.18536055,  0.25447178, -0.7767573 , -0.6939524 ,
       -0.42859754,  0.8641111 ,  0.22210753,  1.0219412 ,  0.7729804 ,
       -0.85002476,  0.22921221,  1.1465571 ,  0.47838706, -0.31170124,
        0.28506622,  0.9302584 , -0.4069288 , -0.03842885,  0.79470634,
        0.8260493 , -0.3512169 ,  0.5295622 , -1.1439348 ,  0.8164338 ,
        1.495584  , -1.1640846 , -0.6279533 , -0.20037311, -0.9521925 ,
       -0.39186934, -0.24880005, -0.77107155, -0.1550627 ,  1.040009  ,
       -0.25780666, -1.0883332 ,  0.5334715 ,  0.79991966, -0.38547862,
        1.0067974 ,  0.19391577, -0.22750618,  0.25013703,  0.7246957 ,
       -0.77007765, -0.60493207,  0.04636176,  0.9256042 , -0.09810548,
       -0.4119528 , -0.70964825, -1.1508172 , -0.97672826,  1.0413712 ,
       -0.40693521,  0.46801075,  0.6112517 , -0.8441012 , -0.80964047,
       -0.7328284 ,  1.3131908 ,  0.65522933, -0.78182584, -0.4146454 ,
        0.09763791, -1.3872494 , -0.367881  ,  0.01118333,  0.01342794,
        0.7536176 , -1.0891263 ,  0.11757183, -0.6009904 , -2.0720787 ,
        0.40093362, -0.3063438 , -0.01197074,  1.2551608 , -0.2661937 ,
        0.37691146,  0.16265659, -0.6840322 ,  1.2695436 ,  0.5794042 ,
       -0.5332821 , -0.31107002,  0.47213885,  0.8459918 ,  0.71674854,
        0.5236477 , -0.2575823 , -0.29835257,  1.5966482 ,  0.36119622,
       -1.2286425 ,  0.8194705 ,  0.7907005 ,  0.99491394,  0.2971772 ,
       -0.9149733 ,  0.07742547,  0.23095986, -1.2154313 , -0.4741054 ,
       -0.30701515, -0.19441877,  0.74242574,  0.16831237,  0.11289202,
        0.97840285,  0.9659258 , -0.633402  ,  0.7198735 ,  0.47469267,
       -0.79332554, -0.4344779 ,  1.1115876 , -0.9404242 , -0.33450705,
        0.5412535 , -0.5193036 ,  0.98178166, -0.6115791 ,  0.5713775 ,
        0.11726616,  1.241715  , -0.5734423 ,  1.2767248 ,  0.02941616,
        0.2511748 ,  1.3233364 ], dtype=float32), array([ 3.0294645,  2.544959 ,  2.9171069,  5.074438 ,  4.740501 ,
        3.3486943,  1.32164  ,  1.5045666,  1.9351926,  5.222534 ,
        6.5465326,  4.931139 ,  7.281977 ,  2.5780358,  2.6879294,
        1.9249383,  0.8088532,  3.595724 ,  5.16501  ,  2.2522025,
        1.8848553,  2.4733088,  1.5897554,  5.1542754,  5.0744624,
        2.407109 ,  2.367698 ,  1.5209936,  1.8703452,  1.2131729,
        5.6606774,  4.8696666,  2.7889683,  5.3607807,  4.5354953,
        4.4939804,  1.1858371,  2.4155858,  5.524197 ,  5.157421 ,
        4.018121 ,  3.3124614,  3.7138224,  5.9456186,  1.862593 ,
        2.936522 ,  4.513774 ,  5.693174 ,  3.5638065,  6.128184 ,
        6.092003 ,  1.3212132,  3.7944076,  4.3411226,  5.474505 ,
        8.45953  ,  4.2905664,  7.20811  ,  4.584565 ,  4.9007697,
        1.6431657,  2.0117526,  1.9821981,  5.0344915,  3.2554934,
        5.273871 ,  7.6641827, 11.14934  ,  4.6665893,  3.2330115,
        2.759542 ,  5.2353473,  2.947486 ,  4.637327 ,  1.2632623,
        2.6210885,  6.67829  ,  4.7739534,  4.6206193,  5.1111865,
        1.9552463,  5.7808332,  3.7645416,  5.7899714,  5.8069816,
        1.9469213,  1.9867713,  1.5089607,  3.830042 ,  6.82152  ,
        2.7512004,  1.7887785,  4.976567 ,  1.2591949,  1.4365599,
        3.813799 ,  6.1970387,  7.603661 ,  5.3586144,  3.104526 ,
        2.897788 ,  1.8675877,  5.1124105,  4.371116 ,  2.699159 ,
        8.584967 ,  3.1055534,  2.5609472,  2.155372 ,  4.2336397,
        2.4578354,  3.7816815,  2.5028896,  5.0095124,  5.797477 ,
        1.509115 ,  1.0528978,  2.4538293,  5.637358 ,  4.1521425,
        5.484832 ,  7.2377563,  7.987005 ,  7.3173795,  2.967386 ,
        3.7671688,  6.345694 ,  2.4049199,  2.9736376,  3.5630627,
        1.9999524,  6.5742207,  2.2060487,  2.7451148, 11.990225 ,
        3.1393538,  2.8173518,  7.186095 ,  1.7944762,  5.0932884,
        2.6731837,  2.0580077,  6.398728 ,  8.627426 ,  4.7811513,
        1.7471665,  4.2894464,  1.8465824,  2.1755095,  3.3083172,
       10.906598 ,  5.7036195,  3.7842484,  5.6225944,  3.0284927,
        8.2358885,  1.5877972,  2.9565823,  3.4187772,  3.2939599,
        3.029272 ,  2.2281508,  8.253087 ,  1.6505798,  1.9993299,
        0.9304872,  2.1434448,  3.627347 ,  3.1054492,  5.6275024,
        1.6399932,  5.7665396,  1.7971227,  2.737305 ,  2.7507734,
        1.8038174,  1.913585 ,  3.2880018,  6.563264 ,  3.7401588,
        2.7864149,  5.3262725,  2.0733917,  4.398038 ,  4.317008 ,
        5.565331 ,  1.8148227,  2.372656 ,  5.4955096,  4.1987004,
        3.638486 ,  1.537414 ], dtype=float32), array([-0.01172337, -0.00130103, -0.01679296,  0.01081465, -0.02536343,
        0.00850918, -0.02053194, -0.00734201, -0.01700671, -0.0056257 ,
       -0.0131362 , -0.00337142, -0.01760969, -0.01563613, -0.01306594,
        0.00257588,  0.01542235, -0.00668178, -0.01373517, -0.01772297,
       -0.01385218, -0.01298244,  0.00785798, -0.01477948, -0.00922251,
       -0.012303  , -0.01456866,  0.01035504, -0.02002981, -0.00794736,
       -0.00969591, -0.00557463,  0.00128568, -0.0050605 , -0.00948137,
       -0.01322525, -0.01756824,  0.00084059, -0.01176371,  0.00492452,
        0.0136832 , -0.00117679,  0.00245166,  0.00277249, -0.0330907 ,
       -0.01787642, -0.02949437, -0.02659632, -0.01236165, -0.01796176,
        0.00230827, -0.00500464, -0.01447064,  0.01415606, -0.01072337,
       -0.00944653, -0.02276379, -0.02088453, -0.00566572, -0.01436262,
       -0.0269662 , -0.0097529 , -0.00612828, -0.00341155, -0.0035386 ,
       -0.00984607,  0.00688479, -0.00270905, -0.00971323, -0.02475824,
       -0.01889143, -0.00554851, -0.00882801, -0.00208933,  0.00155563,
       -0.02114468, -0.00138402, -0.0261931 , -0.00108482, -0.01222012,
       -0.01484889, -0.00384045, -0.01470683, -0.02405522,  0.01508389,
        0.00147061, -0.01338496, -0.00406198,  0.01391444,  0.00704046,
        0.00584151,  0.01153966, -0.01584866, -0.00934324, -0.02126812,
       -0.01069744, -0.00053382,  0.02071189, -0.01414063, -0.01438029,
       -0.00673212, -0.00898536, -0.00884993, -0.00645404, -0.00709294,
        0.00235782,  0.00441835,  0.00130391,  0.0033351 , -0.00959196,
       -0.02337211, -0.01776446, -0.02808969, -0.02048112,  0.00368818,
       -0.0092545 , -0.00806241,  0.01699124, -0.01536498, -0.00405465,
       -0.00410588, -0.01505174, -0.00154772, -0.01581018, -0.00407242,
       -0.01063333, -0.01533036,  0.00479984, -0.01262425,  0.00229998,
       -0.02364622, -0.01611401, -0.01159909, -0.02376316, -0.02956281,
       -0.00759481,  0.00906909, -0.01214277,  0.00091102, -0.00220912,
       -0.00981421, -0.03428088, -0.01687582, -0.02230851,  0.00176024,
        0.02443621, -0.00658318, -0.01723349, -0.02594427,  0.00653962,
       -0.00711157, -0.01084826,  0.00951068,  0.00413853, -0.02118602,
       -0.00142962,  0.00275848, -0.0094665 , -0.01125876, -0.00174706,
        0.00801311,  0.01490944, -0.00581977, -0.01678188, -0.00254455,
       -0.00566605, -0.01030653,  0.00651864,  0.01316954, -0.01244555,
       -0.02340793,  0.00082798,  0.00485321, -0.01239035, -0.0167367 ,
       -0.01414968, -0.02171633,  0.0003986 , -0.01212709, -0.00966708,
       -0.00624986, -0.00086175, -0.00729399,  0.00289405,  0.00212018,
        0.00044129, -0.01131936, -0.00485619, -0.0099849 ,  0.01899377,
       -0.02103286, -0.0155061 ], dtype=float32), array([-0.6254663 , -0.02033238,  0.2550596 ,  0.5553411 ,  1.4591557 ,
       -0.06643026, -0.2599877 ,  0.96938646,  1.1964047 , -0.02836953,
        0.23382734,  0.33954418, -0.76071674,  1.0239415 ,  1.8408525 ,
        0.6567683 , -1.6189123 ,  0.13322353, -1.6468978 ,  0.24184223,
        0.36158547,  0.55824804,  1.7190771 ,  0.54829735, -0.28526828,
       -1.7783895 ,  0.5451609 , -0.7888631 ,  0.3459806 ,  1.4220599 ,
        0.9946975 ,  1.2910968 , -0.24691914,  0.61171925, -0.65955603,
        0.52931815, -1.1960564 , -1.8460542 ,  0.55066776,  0.13348939,
       -0.68237114, -0.40748212,  2.1988187 , -0.22648844,  0.0652149 ,
        0.84990746,  1.2299141 , -0.06465434,  0.7519733 ,  0.97111326,
        1.1174614 , -0.4357448 ,  1.4748763 , -0.5402391 ,  0.78326356,
        0.79657555,  0.90282774, -0.2700961 ,  1.0237448 , -1.2644275 ,
        0.82664686, -0.22232503, -0.85927737,  0.60800683,  0.58974016,
       -0.75032645, -0.6877898 , -1.2122362 ,  0.17689739,  1.8210331 ,
        0.66581076, -0.13547401,  0.6391696 , -1.4409422 ,  0.06519294,
       -0.5327691 ,  1.0683231 ,  0.7602107 , -1.5869771 , -1.2566439 ,
       -1.0066203 ,  0.59278303, -0.11547308, -1.4444052 , -0.21976154,
       -0.96664435,  1.4025431 ,  0.5201822 , -0.3100485 ,  0.5236502 ,
       -1.2163332 , -0.4655544 ,  0.40575173,  1.5500251 ,  0.22871709,
        0.60879457,  1.0863608 , -1.2137924 ,  0.36604285, -1.7302414 ,
        0.15518112,  0.05144758, -1.1168437 ,  0.92287254, -0.7548964 ,
        0.41212237,  0.87205327,  0.79517055,  0.57701904,  1.5623355 ,
        0.29101834,  0.93227047,  1.0183634 ,  1.6391227 , -1.1375543 ,
        0.9583983 ,  1.2445225 ,  0.55947554,  0.08557975, -0.9594971 ,
        1.0481175 ,  1.5038207 ,  0.05661859,  0.8842502 , -0.2566578 ,
       -0.75578666, -1.1976613 , -0.56012475, -0.34565628,  0.47360554,
        0.92006433,  0.24289814,  1.5455626 , -0.3267949 ,  0.41760993,
        1.3669795 ,  0.351991  ,  0.94487953, -1.4030032 ,  1.4804873 ,
        0.7307607 ,  0.8298864 ,  0.69369256,  0.8927155 ,  0.8333495 ,
        0.10500675,  1.2240846 ,  1.0981395 ,  0.9802146 , -0.06152688,
       -1.3804326 ,  1.418819  , -0.2712463 , -0.41010925,  1.1424714 ,
       -0.0294242 , -1.7318268 ,  1.6189843 ,  1.5198576 , -0.78050774,
        0.47643515, -0.06185868,  0.401609  ,  0.11033943,  1.496442  ,
       -0.51855624,  1.6051648 ,  0.6237115 ,  0.60991925,  0.9872738 ,
        0.81170684, -0.40645155,  0.86538637,  1.1031728 , -1.2548975 ,
       -1.4533205 ,  0.9703852 , -1.7745457 ,  1.0726305 ,  0.594086  ,
        0.7089357 , -0.8439772 , -0.8639903 ,  0.8161724 , -0.7707427 ,
        0.3906914 ,  0.12821376,  1.4861217 ,  1.5526265 ,  0.8300062 ,
        0.03324151,  0.7728632 ], dtype=float32), array([ 1.4132226,  8.544961 ,  2.979815 ,  8.71167  , 24.457333 ,
       10.766804 ,  2.99993  , 13.231344 , 12.399829 ,  2.251806 ,
        1.0778351,  9.135652 , 12.598811 ,  9.797297 , 20.334545 ,
       13.035864 ,  5.9494386,  2.7350693,  6.7456875,  1.3862045,
        2.1583803,  5.895842 ,  5.8447027,  9.838403 ,  3.9229894,
        5.860948 ,  2.764392 ,  2.643054 ,  8.474443 , 19.264713 ,
       14.490378 ,  7.393299 ,  4.096498 ,  3.2752156,  2.0543778,
       14.006758 ,  4.1311784, 10.433856 ,  7.79289  ,  7.025382 ,
        4.1638975,  8.728294 , 25.424646 ,  5.2419925,  8.959505 ,
        4.129447 , 24.615252 ,  2.6566904,  9.897365 ,  2.8066797,
        9.343582 ,  4.7063   , 25.189947 ,  1.6964204,  6.404244 ,
        5.8896947, 11.797624 ,  2.3417337, 10.793171 ,  3.1997256,
       12.286493 ,  1.7710351, 13.069111 ,  3.6739705, 21.96825  ,
        1.3830293,  2.1603434,  6.140578 ,  8.926003 , 26.584488 ,
        5.4081097,  0.7752752,  8.234683 ,  6.917183 ,  2.247215 ,
        3.039578 , 14.566508 ,  3.08814  ,  6.5420556,  4.1603203,
        4.3621173,  9.575858 ,  8.1788845,  8.221004 ,  4.687355 ,
        4.949563 , 17.242918 ,  2.7769673,  2.8805218,  5.8803926,
        7.2495685,  2.758056 ,  1.2184308, 10.752585 ,  2.4452538,
        2.6096992,  7.0908823,  5.9084425,  2.4028575,  7.975045 ,
        2.8996167,  2.8848693,  1.6070547, 11.086334 ,  2.3487506,
       13.724841 , 19.63812  , 10.130019 , 17.498386 , 24.939968 ,
        2.4730654, 14.073579 ,  3.4621346, 25.046408 ,  7.877225 ,
        5.828049 , 12.962856 ,  3.87921  ,  2.8465374,  2.7809207,
       12.549295 , 19.68571  ,  6.9533534,  3.0786867,  2.9438539,
        3.982125 ,  2.978917 ,  3.079843 , 12.10234  , 21.581339 ,
        5.6176095,  3.451017 , 22.47     ,  5.2297235,  1.9726721,
       20.857372 , 10.136227 , 11.915425 ,  9.339894 , 18.48528  ,
       16.768433 ,  3.3294847, 13.4156685, 12.929386 ,  4.991543 ,
        2.920847 , 12.528328 , 10.011055 , 17.460785 ,  3.267455 ,
        9.844608 , 21.754034 ,  2.0487401,  4.124993 , 16.14551  ,
        1.6554859, 10.372917 , 19.223654 , 19.06892  , 13.592173 ,
        5.071063 ,  1.7591197, 10.108662 ,  9.512341 , 12.436056 ,
        3.0414667, 18.1588   ,  6.6913543, 12.376511 ,  9.3329315,
        6.4848437,  4.977779 , 13.9480295, 14.946198 ,  2.065412 ,
       10.168015 ,  3.5738902,  5.5381675, 11.008462 , 10.744519 ,
        5.088228 ,  3.338849 ,  2.1105616, 25.223343 ,  3.4717727,
       11.595538 ,  1.1790104, 17.505972 , 17.800257 , 15.948692 ,
        9.151094 ,  7.937203 ], dtype=float32), array([-1.49294231e-02, -4.18113172e-03, -5.10093640e-04, -9.61185992e-03,
       -3.34433070e-03,  1.19791664e-02,  7.57603860e-03,  3.46568529e-03,
        2.53591011e-03, -2.75053885e-02,  4.71563730e-03,  1.47943301e-02,
       -5.53901261e-03, -6.61733560e-03, -7.05745211e-03, -7.26818293e-03,
        1.23459450e-03, -2.77456883e-02, -2.46864697e-03,  3.60458577e-03,
        7.64286192e-03, -1.58019131e-03,  7.03192502e-03, -1.44895185e-02,
        2.93340022e-03,  6.96790125e-03, -1.72919389e-02, -6.85736630e-03,
       -8.74097459e-03, -1.06405735e-03,  6.70384429e-03, -4.66953544e-03,
        7.67824473e-03, -1.15604931e-02, -1.19065086e-03,  1.21530471e-02,
       -5.60099073e-03, -1.15000866e-02, -2.25215009e-03,  1.40565936e-03,
       -1.81752015e-02, -2.83827400e-03,  6.23702025e-03, -5.19142440e-03,
        4.32115002e-03,  1.52760441e-03,  1.70498074e-03, -2.93127936e-03,
       -5.82955731e-03, -9.57336277e-03, -1.08086225e-02,  1.79724640e-03,
       -6.81710429e-04, -2.20048465e-02, -1.01671759e-02, -1.88994326e-03,
        3.01802298e-04,  6.16637431e-03, -8.02711770e-03,  1.49409426e-02,
       -1.26367155e-03, -2.72590923e-03, -9.32879094e-03, -5.02271997e-03,
       -3.79377301e-03, -3.84040555e-04,  5.74180903e-03, -1.60617922e-02,
        4.25734965e-04, -5.65367844e-03, -8.19549430e-03, -6.65385369e-03,
       -1.85612662e-04,  5.27758524e-03,  7.44588207e-03, -1.51408426e-02,
       -1.23045957e-02,  9.29571781e-03, -7.99336843e-03, -1.43497642e-02,
       -9.51986853e-03, -1.56262144e-03,  4.92402399e-03, -4.12268983e-03,
        2.16197199e-03, -7.59037584e-03, -9.60266031e-03,  5.44931798e-04,
       -2.43578088e-02,  2.32518255e-03,  6.63078437e-03,  1.62179512e-03,
       -8.06499179e-03, -3.53737222e-03, -2.04989277e-02, -7.64354784e-03,
        6.86365180e-03,  7.45323161e-03, -9.64507554e-03, -7.71832420e-03,
       -7.97216687e-03, -5.24687115e-03, -1.30357696e-02, -4.96777566e-03,
        5.75822720e-04, -6.00108970e-03,  1.52026601e-02, -1.57547370e-02,
       -7.53225153e-03, -7.59242335e-04, -5.07834181e-03, -5.70498593e-03,
       -1.46603240e-02,  6.83505554e-04,  1.11009344e-03,  8.18369817e-03,
       -1.31574729e-02, -1.01938136e-02, -1.05749182e-02,  8.02244525e-03,
       -1.47149954e-02,  7.42413336e-04,  3.33766825e-03,  1.05767301e-03,
       -8.25042278e-03,  7.80880637e-03, -1.11551881e-02, -1.46811800e-02,
        1.65512953e-02, -1.25344575e-03,  3.19801416e-04,  7.49299536e-03,
       -5.26934909e-03, -9.53775714e-04,  4.61400300e-03, -1.74754660e-03,
       -1.70473196e-02,  1.27311170e-04,  5.18070813e-03, -1.24353124e-02,
       -4.76402027e-04, -7.08657876e-03, -1.46429371e-02, -2.07334897e-03,
       -1.69400554e-02, -2.59545855e-02, -1.33082615e-02, -2.19725003e-03,
        7.11971289e-03, -1.20795732e-02, -9.28312168e-03,  4.31180652e-03,
       -1.24659855e-02, -6.59114309e-03, -1.56057356e-02, -2.29555648e-02,
        3.01555102e-03, -3.45372874e-03, -3.31850653e-03, -1.70271553e-03,
       -1.01935528e-02,  6.22183224e-03,  3.30470013e-03,  2.77775805e-03,
        4.12538368e-03, -2.12664455e-02, -9.80858784e-03, -1.85008859e-03,
        1.98053382e-03,  8.73548706e-05, -1.71710942e-02,  8.39127507e-03,
       -1.75931025e-02,  6.90242788e-03, -1.56628294e-03, -6.15207665e-03,
       -2.73337169e-03, -2.82108132e-03,  1.10680179e-03, -3.89529683e-04,
       -3.39984871e-03, -1.29686913e-03,  7.14672357e-03, -2.11321213e-03,
        6.79903617e-03, -7.70374667e-04, -2.46471539e-03, -7.56455585e-03,
       -6.68751914e-03, -1.68751040e-03, -7.76121533e-03, -1.82323638e-04],
      dtype=float32), array([ 0.64696175,  0.03171297, -0.91180015,  1.2586077 ,  0.74297565,
       -1.1047534 , -0.4147223 ,  0.03724759, -0.90682393,  1.1447018 ,
       -0.76367986, -0.5708099 , -0.40423402,  0.5621053 ,  0.38456282,
        0.9284586 ,  0.02054238, -0.837888  , -0.6360716 ,  0.08782997,
       -0.45995194,  0.46203923,  0.2902708 , -0.69107896,  0.41661426,
       -0.25164813, -0.70477086,  0.04301403,  0.7485267 , -0.36900845,
        0.70419616,  0.3600587 , -0.1197283 ,  0.57546365, -0.4410372 ,
        0.12995921, -0.6553832 , -0.10789239,  0.18979321, -0.05089088,
       -0.35823917,  0.01120749,  0.14833036,  0.31611794, -0.8698214 ,
       -1.2883866 , -1.0918074 ,  0.07206753, -0.479578  , -0.8946313 ,
       -0.3809792 ,  0.06780491, -1.0048877 ,  0.04068759, -0.82270074,
       -0.6513368 , -0.8284392 ,  0.34014925,  0.53085756, -0.6474063 ,
        0.02585387, -0.20220213,  0.33347917, -0.69958544,  0.734753  ,
        0.3179051 ,  0.00676448,  0.6878711 , -0.04326421, -0.56858796,
        0.02639871,  0.17129195, -0.15354992, -0.6131062 , -0.5608083 ,
        1.0951972 ,  1.0915332 , -0.02690503,  0.6629292 ,  1.0185826 ,
       -0.10716122, -0.6307507 ,  0.56476265, -1.017041  ,  0.7002981 ,
        0.2737236 , -0.6470707 ,  0.6181181 , -0.7016841 , -0.37761143,
       -0.22913502, -0.8189839 ,  0.5212549 , -0.31588542,  0.9317818 ,
        0.09979413,  0.77214694,  0.55202144, -0.40988043, -0.6784525 ,
        0.63256174, -0.00878567, -0.80033827,  0.5373241 , -0.91420317,
       -1.1275842 , -0.28956854,  0.6925322 , -0.39699513,  0.6908864 ,
       -0.6402041 ,  0.8457054 ,  0.32581702,  0.9460094 , -0.2142523 ,
       -0.1538067 , -1.5053669 , -0.02762844, -0.48271447,  0.29845044,
        0.39137527,  0.35375348, -0.5872319 ,  0.5284427 , -0.41508365,
       -0.7122447 , -0.9306533 ,  0.4958686 , -0.7446221 , -0.5096212 ,
        1.1484168 , -0.55617523,  0.58223575,  0.00587056,  0.14456594,
       -0.34354874,  0.08338749, -0.7638722 ,  0.18116792, -0.404643  ,
        0.9928123 , -0.19643046, -0.7517855 ,  1.0212198 , -0.21441604,
        1.1341444 , -0.4821456 , -0.3294156 , -0.4890981 ,  0.15007812,
        1.2752302 , -0.58544827,  1.1053805 , -0.56863815,  0.5237269 ,
        0.9640764 , -0.5227798 , -0.5662332 , -0.79457974, -0.7723392 ,
        0.454676  ,  0.2727482 , -0.6719339 , -0.7312184 , -0.4993071 ,
        0.12290792,  0.20633024,  0.45997694,  0.8167748 ,  0.21453248,
        0.98373187, -0.86711234,  1.4295346 , -1.0905843 , -1.0927995 ,
        0.23705985, -0.22421673,  0.74030906, -0.22995917,  0.14689508,
       -0.33297104, -0.68992287, -0.01094591,  1.3269638 , -0.56429565,
        0.47267666, -0.04746648, -0.7503219 ,  1.0578073 , -0.84486717,
       -0.8731031 ,  0.39200833], dtype=float32), array([1.5104531 , 1.0890913 , 2.630276  , 1.4762918 , 0.98093224,
       4.5021496 , 1.7719973 , 1.3960887 , 2.6062107 , 1.962223  ,
       2.298227  , 1.2808988 , 1.239797  , 1.6684679 , 1.2079723 ,
       3.2984614 , 2.1454263 , 2.040824  , 2.7937195 , 1.3665557 ,
       2.0715816 , 1.9010463 , 0.76782984, 0.74057794, 1.3061614 ,
       1.7554281 , 1.2948472 , 1.3933543 , 1.9658362 , 1.7803717 ,
       1.3692086 , 2.3901317 , 1.1110072 , 2.3952665 , 1.1162281 ,
       1.419706  , 1.2277086 , 1.0662521 , 1.2193921 , 2.1025004 ,
       0.96326   , 1.0168916 , 0.9674667 , 1.2158302 , 4.318118  ,
       2.8563342 , 2.712815  , 0.67374414, 1.5520133 , 1.080384  ,
       1.5351901 , 2.7834342 , 2.328126  , 1.6133206 , 1.3199974 ,
       3.6171238 , 1.352736  , 0.7885817 , 1.5180632 , 2.0053458 ,
       0.76003045, 2.576321  , 1.4465916 , 1.3009866 , 0.5514271 ,
       2.0828784 , 1.6190112 , 1.3858706 , 0.9399042 , 1.5717891 ,
       1.217425  , 1.1052684 , 1.5816048 , 2.2587638 , 1.4585466 ,
       1.0595618 , 3.5160756 , 2.3214157 , 0.95829654, 1.6238456 ,
       0.73576516, 1.5702271 , 1.1644627 , 2.5313284 , 1.7878864 ,
       1.3329662 , 3.1694095 , 0.6913787 , 1.6555678 , 1.4750047 ,
       0.73044723, 3.7298942 , 1.0691111 , 1.6433827 , 1.6843089 ,
       0.7717359 , 2.2648652 , 2.0287085 , 2.085952  , 1.2646221 ,
       0.64292777, 1.5066377 , 1.6335819 , 0.9320962 , 1.000818  ,
       1.8667202 , 1.4775317 , 1.8368549 , 0.8157423 , 4.022788  ,
       2.2220635 , 2.3761654 , 1.5591949 , 2.1758237 , 1.5923506 ,
       0.98921704, 2.939796  , 1.3015985 , 0.71226144, 2.051174  ,
       1.40927   , 0.87421876, 0.8664618 , 1.2851851 , 1.3108044 ,
       2.1213853 , 2.9980128 , 2.6995325 , 1.7826208 , 1.2128104 ,
       2.7520378 , 1.9568143 , 1.7025462 , 0.94629645, 0.9343091 ,
       0.46234265, 1.7893484 , 3.0488207 , 1.6808331 , 2.0944433 ,
       1.3325557 , 1.0387133 , 3.088198  , 7.1265073 , 0.58927137,
       2.5563354 , 1.9446716 , 0.5497412 , 0.9126368 , 0.8091542 ,
       1.7768644 , 2.2215736 , 1.695586  , 3.9548419 , 1.3698392 ,
       1.0693548 , 1.3450565 , 1.1554155 , 0.95232165, 2.3339732 ,
       3.88513   , 3.0909233 , 1.3309649 , 2.1480172 , 2.8937833 ,
       1.5981354 , 1.2506568 , 1.6308906 , 1.4638314 , 1.6610101 ,
       1.6119854 , 1.6105888 , 3.6901455 , 2.6422734 , 2.9594343 ,
       1.3327488 , 1.2792541 , 0.9384738 , 0.7948252 , 1.7434472 ,
       1.1012083 , 0.96158963, 1.1285777 , 2.0805216 , 1.3641859 ,
       0.9637311 , 1.0713621 , 2.3010857 , 1.265061  , 2.1701713 ,
       1.9005091 , 0.44422007], dtype=float32), array([[[[ 0.04397434, -0.05411662,  0.03705351, ..., -0.07846014,
          -0.05668188,  0.02086702],
         [ 0.06742957,  0.03629155, -0.05195201, ..., -0.0658105 ,
          -0.02627601,  0.07308611],
         [-0.00444425, -0.06300098,  0.00550034, ...,  0.01903789,
           0.06647256,  0.01324649],
         ...,
         [ 0.03900791, -0.05150395,  0.06461589, ..., -0.02011899,
          -0.01446879,  0.03099488],
         [-0.04693896,  0.01352883,  0.01202124, ..., -0.07460675,
          -0.07456691, -0.06129245],
         [ 0.04889164, -0.00930248, -0.04498271, ..., -0.07770265,
           0.08211312,  0.02215872]]]], dtype=float32), array([-2.53173104e-03,  6.24297652e-03, -7.26046460e-03, -4.52602841e-03,
        4.86985734e-03, -1.05669105e-03,  2.83002364e-03, -1.27400300e-02,
       -1.03059215e-02,  5.44274598e-03,  3.50456219e-03,  5.95451007e-03,
       -2.02589724e-02, -1.30598722e-02, -1.07108280e-02,  1.83908525e-03,
        6.80977060e-03,  2.01446959e-03, -6.88006403e-04, -1.00352988e-02,
       -1.78070888e-02,  5.43433614e-03, -7.58453389e-04, -8.26931000e-03,
       -2.91668018e-03, -1.37249716e-02,  7.64257647e-03, -3.70581774e-03,
        2.66510039e-03, -4.38534701e-03, -1.96689516e-02, -1.08073093e-02,
       -1.04207797e-02, -2.67144816e-04, -1.43285099e-04,  4.96644154e-03,
       -1.98513959e-02,  1.27206510e-02, -2.92968331e-03,  6.52556913e-03,
        1.27271470e-02, -1.13397120e-02, -2.95781158e-03,  7.82937452e-04,
       -3.95461312e-03, -5.62709116e-04, -1.66485028e-03, -4.31284308e-03,
        1.84041597e-02,  3.49944877e-03, -7.50897592e-03, -9.65357060e-04,
       -5.76736499e-03,  4.32092324e-03, -6.38570916e-03, -7.35141337e-03,
        7.20001175e-04,  9.04019643e-03,  9.74771939e-03, -5.19074872e-03,
       -4.57488373e-03,  1.05833253e-02,  1.73407176e-03,  5.94494445e-03,
       -4.32898896e-03,  3.07919458e-04, -2.35156599e-03, -3.65911680e-03,
       -1.67481527e-02, -2.23606685e-03, -4.39452520e-03,  1.12086888e-02,
       -3.33204959e-03, -1.14069935e-02, -1.12750754e-02,  7.11673638e-03,
       -1.31170847e-03, -1.73395444e-02, -2.54494109e-04, -1.38988197e-02,
        1.22832265e-02, -9.64663271e-03,  3.78362089e-03, -8.65477603e-03,
       -1.29980920e-03,  3.59944114e-03, -2.87926942e-03,  5.36218565e-03,
       -5.05103031e-03,  7.24898325e-03, -2.56483955e-03,  2.15418870e-03,
       -6.34542434e-03, -6.71225879e-03, -2.07320955e-02,  6.56433869e-03,
       -2.40272172e-02, -9.74540319e-03,  5.43620018e-03, -6.50017196e-03,
       -2.64533353e-03,  4.40379418e-03, -7.09616719e-03, -1.84455961e-02,
       -4.98398580e-03,  5.35553787e-03,  3.53561627e-04,  1.51022831e-02,
        9.00354795e-03, -1.19070560e-02, -6.73658308e-03, -1.11274393e-02,
        6.61457831e-04, -1.07743894e-03, -1.49796009e-02,  6.38305850e-04,
        1.44339064e-02,  1.31925214e-02, -2.35865777e-03, -1.54888947e-02,
       -1.53393932e-02,  1.95381548e-02, -3.65051371e-03, -5.91587275e-03,
       -3.46939568e-03, -9.73370112e-03,  2.06903554e-03,  1.12963310e-02,
       -4.60498454e-03,  6.15872705e-05, -2.01686705e-03, -8.18063878e-03,
        1.44371254e-04,  1.29195321e-02, -1.55486092e-02, -9.31652728e-03,
       -9.91708227e-03,  3.09629855e-03,  5.42387320e-03, -1.25393746e-02,
       -2.48524942e-03, -1.96788082e-04, -1.15201976e-02,  9.94496699e-03,
        1.66947057e-03,  3.98232462e-03, -8.87152855e-05, -8.74594436e-04,
       -1.40987076e-02,  4.08200035e-03, -1.36065288e-02, -2.51630992e-02,
       -1.32434247e-02,  1.85363332e-03, -6.21193496e-04, -1.67190470e-02,
        2.97995307e-03,  1.26778428e-03, -2.93168821e-03, -2.88105812e-02,
       -2.22003786e-03,  9.31948051e-03, -5.55104436e-03, -5.97241509e-04,
       -1.37555683e-02, -8.38417560e-03, -1.22460919e-02, -6.25127321e-03,
        3.94559791e-03,  2.37902254e-03,  1.03268130e-02, -2.56986404e-03,
       -6.60125457e-04, -1.23675829e-02, -9.51492041e-03, -1.06974586e-03,
       -8.29853211e-03, -1.54170562e-02, -2.74719391e-03, -3.46844853e-03,
       -1.52449869e-02, -2.21720487e-02, -1.93980783e-02, -1.54066356e-02,
       -2.61298800e-03, -1.74448872e-03, -4.06620442e-04, -1.16327079e-02,
        1.19805885e-02, -6.97998796e-03, -1.96154006e-02,  1.04766004e-02],
      dtype=float32), array([-0.06209008,  0.09029497,  0.34659022, -0.7546945 , -0.15738162,
       -1.0300764 ,  0.84873444, -0.8486995 , -0.52475995, -0.11342155,
        0.39766046, -1.0626332 , -0.8313407 ,  0.7235642 ,  0.11058946,
        0.09297583, -0.25783902, -0.6876192 ,  0.3173142 ,  1.0923793 ,
        0.46177962, -1.3176608 ,  0.0516776 ,  0.06491709, -0.46673992,
       -1.1347637 ,  0.10020782, -0.53439087, -0.22284266,  0.38563803,
        0.39963406,  0.6373087 ,  1.0275731 , -0.3218189 ,  0.6147666 ,
        0.2364775 ,  1.0772507 ,  0.69263077,  0.6590403 ,  0.11640941,
       -0.10878991, -0.63461673, -0.03875051,  0.12328563,  0.33952317,
       -0.12752262,  0.14263478, -0.2615785 ,  0.3070113 ,  0.11502213,
        0.21951394,  0.12803698, -0.14447731, -0.68516773,  0.65735483,
        0.27529153,  0.28599402,  0.03120883, -0.05891214, -0.24828117,
        0.08110005, -0.52524143,  0.07798402,  0.5560239 ,  0.30071774,
        0.08863855,  0.6858545 ,  0.90899146, -0.49932873,  0.35139552,
       -0.95166916, -0.1883808 , -0.12398905, -0.73232734, -0.33138704,
        0.04067023, -0.34593672,  1.4666835 ,  0.15086424,  0.02531782,
        0.3697866 ,  0.31254536, -0.39272067, -0.57082623,  0.7080766 ,
       -0.6630234 , -0.6013335 , -0.29902866,  0.16499972, -0.25921637,
       -0.02528732,  0.36516738,  0.74664026, -0.38699242,  0.08511989,
        0.10564476,  0.6885917 ,  0.48858038, -0.37174094,  0.34857476,
        0.5453835 , -0.46377727, -0.58061737,  0.44871956,  0.16104126,
       -0.6742678 ,  1.1405818 ,  0.27754188,  0.2452962 , -0.29858512,
        0.5328879 ,  0.7403574 , -0.9124876 , -0.07048634, -0.10224112,
        0.52689976, -0.15314403,  0.04876527, -0.23054315, -0.530388  ,
        0.04652537, -0.32500845, -0.3074857 ,  0.3418437 ,  0.71314013,
        0.8491367 , -0.22497278, -0.09028903, -0.16113773, -0.05023254,
       -0.36844504, -0.59753877,  0.10564888,  0.16288544,  0.54640967,
       -0.13764252,  0.28480992,  0.25136298, -0.05069987,  0.07103935,
        0.4566312 ,  0.2883445 ,  0.32740834,  0.25771552, -0.00511272,
       -0.57883877,  0.07714747,  0.696808  ,  0.31779906, -0.5626444 ,
       -0.83384144,  0.3353994 ,  0.63378954, -1.4114715 , -0.9536541 ,
        0.3744489 , -0.22315487,  0.14038552,  0.33801317,  0.6944965 ,
       -0.07386786,  0.1922779 ,  0.78814274, -0.43698174,  0.6207888 ,
       -1.0076286 ,  0.47047672, -0.16311477, -0.6114595 , -0.30012634,
        0.9287843 ,  0.23955502, -0.09779657,  0.3123018 , -0.17092924,
        0.05006877,  0.03443   ,  0.8742476 ,  0.5229007 , -0.16038206,
       -0.47972298,  1.1279306 , -0.6637031 ,  0.74775684,  0.24964064,
       -0.79559165, -0.19803509, -0.1671622 ,  0.2938987 , -0.5558774 ,
        0.74554574, -0.59312147], dtype=float32), array([1.0658039 , 1.888177  , 2.473852  , 0.55361646, 3.038267  ,
       2.7481441 , 3.0706785 , 0.83117217, 3.3612225 , 0.7007285 ,
       0.62064385, 2.5386865 , 1.5303985 , 5.377357  , 2.286201  ,
       1.4860039 , 2.189322  , 1.1969272 , 1.424176  , 6.351467  ,
       1.9287242 , 3.1566901 , 3.8367672 , 4.174249  , 0.58507925,
       1.166517  , 1.1576624 , 0.40058798, 1.51665   , 4.1734266 ,
       3.0549827 , 0.4536113 , 4.4508624 , 3.8276818 , 3.7842617 ,
       2.3892543 , 7.0729156 , 1.4019918 , 4.823107  , 2.2960863 ,
       0.929688  , 1.9724652 , 1.0324919 , 1.8830644 , 0.8605438 ,
       1.5510362 , 1.503895  , 0.511675  , 2.1713789 , 1.6191187 ,
       1.4605105 , 1.7391225 , 1.0476421 , 0.86261344, 5.291652  ,
       3.3531346 , 1.0458115 , 0.3743303 , 1.77712   , 0.95911086,
       3.8339853 , 1.7912877 , 0.8407565 , 1.5265673 , 1.4613221 ,
       0.43080932, 0.5297748 , 4.963016  , 0.9812738 , 1.2821124 ,
       3.7195797 , 3.5879993 , 1.2768849 , 2.133863  , 2.0150857 ,
       2.5458398 , 1.8144141 , 6.1037626 , 2.4124205 , 3.4833279 ,
       1.1394944 , 1.9408946 , 1.0750105 , 1.3674725 , 0.5863887 ,
       4.0643034 , 1.8280516 , 1.9880372 , 3.6365712 , 1.1639326 ,
       1.1580507 , 3.2126663 , 0.8567382 , 0.95819855, 1.2358171 ,
       0.5806662 , 3.349843  , 2.3644812 , 1.5128862 , 2.330717  ,
       1.1755452 , 2.9196928 , 1.4235418 , 1.8694557 , 1.4116108 ,
       1.4749849 , 3.334289  , 3.3868194 , 1.8426858 , 2.9190998 ,
       3.069017  , 3.4703577 , 2.2293608 , 1.1363403 , 0.83970344,
       0.7123617 , 2.3007274 , 0.51149696, 1.1860964 , 1.592676  ,
       4.9691863 , 0.9268814 , 3.5013847 , 1.3563261 , 6.1778765 ,
       6.7602835 , 1.9331481 , 0.79676217, 0.86408377, 1.6899081 ,
       1.4540218 , 1.9100076 , 1.7599181 , 0.8084683 , 3.149656  ,
       1.9263762 , 1.8618771 , 5.0129285 , 2.0186765 , 3.730494  ,
       3.9502814 , 2.3687959 , 2.5878978 , 3.7125647 , 1.6927487 ,
       1.4978236 , 1.0854163 , 3.0562043 , 3.520346  , 1.0764912 ,
       0.94539654, 5.728287  , 7.163749  , 3.5129588 , 2.613254  ,
       4.6562366 , 1.4437385 , 5.734362  , 1.9029421 , 9.829289  ,
       2.2485316 , 1.9510407 , 0.85664207, 1.1079773 , 7.132397  ,
       1.6781161 , 3.1942987 , 0.7784775 , 0.6502427 , 0.92731935,
       1.0750151 , 0.66630197, 2.7440057 , 2.0232787 , 1.7492452 ,
       3.2055464 , 3.6717532 , 4.4387846 , 2.9324577 , 1.9071534 ,
       1.034065  , 4.8046207 , 1.064453  , 2.585417  , 1.6909338 ,
       2.268716  , 4.0951138 , 1.3885615 , 3.0630383 , 1.7368017 ,
       4.389694  , 0.9606945 ], dtype=float32), array([[[[-0.02285915,  0.02883862, -0.02863124, ..., -0.01597728,
          -0.02629687, -0.01790757],
         [ 0.04908294,  0.00074059,  0.01772959, ...,  0.02024937,
          -0.00972736, -0.00316591],
         [-0.03819646,  0.02088994,  0.01888137, ...,  0.01063827,
           0.02212896,  0.04947416],
         ...,
         [-0.00032598,  0.01161802, -0.01872624, ..., -0.0072935 ,
           0.00405156,  0.03730831],
         [-0.04463229,  0.02707501, -0.02218571, ...,  0.02325795,
          -0.03787959,  0.03467503],
         [ 0.0344644 , -0.03155402,  0.03654532, ...,  0.01963472,
           0.0356015 ,  0.0064874 ]],

        [[ 0.00131768, -0.02796692, -0.03312999, ..., -0.02328785,
           0.03857468,  0.00801156],
         [ 0.03154327, -0.03683446, -0.00232279, ..., -0.01159766,
           0.02468477, -0.01684759],
         [-0.02728497, -0.03121639,  0.01836583, ..., -0.00017745,
           0.01709853,  0.01596471],
         ...,
         [-0.00360782,  0.04562483,  0.02345189, ..., -0.00683758,
          -0.03389661, -0.00785759],
         [ 0.00180329, -0.02391387,  0.05131319, ...,  0.04739877,
          -0.01682653,  0.03403571],
         [ 0.00625547, -0.0117459 ,  0.00086266, ...,  0.00466197,
           0.03759351, -0.02635882]],

        [[ 0.00872273,  0.02858784,  0.03030113, ...,  0.01133213,
          -0.01166267, -0.04226651],
         [ 0.02095095,  0.00205902,  0.02330034, ...,  0.02356464,
          -0.01845537,  0.02951387],
         [-0.03215542, -0.04385148, -0.01628131, ...,  0.00138701,
           0.01309902,  0.01487605],
         ...,
         [-0.00414025,  0.03644381, -0.04632868, ..., -0.01234031,
           0.00119682, -0.02545268],
         [-0.0428695 , -0.04332292, -0.02781769, ...,  0.01574358,
           0.00136872, -0.04629181],
         [-0.01523599, -0.03623143, -0.01816185, ..., -0.00721256,
           0.03163625, -0.002401  ]],

        ...,

        [[ 0.04255463, -0.0006674 ,  0.04654158, ..., -0.02852497,
          -0.03121166, -0.02697926],
         [ 0.02492106, -0.04465261, -0.02504068, ...,  0.04189997,
           0.00117942, -0.04950082],
         [-0.04421275,  0.02146044,  0.03633755, ...,  0.03664891,
           0.01674564, -0.00812471],
         ...,
         [-0.00193395,  0.02740248,  0.02986521, ..., -0.01312718,
           0.03425313,  0.00858513],
         [-0.03432053,  0.02898143,  0.00584988, ...,  0.00546657,
          -0.02616784,  0.00298257],
         [-0.00800921,  0.02706833, -0.00638762, ...,  0.02881747,
          -0.02638922,  0.04507712]],

        [[ 0.03925238,  0.04159037, -0.00234294, ..., -0.04126815,
          -0.04271266, -0.01514742],
         [-0.03987468,  0.02243802, -0.00483498, ...,  0.04365736,
           0.03809877, -0.03871049],
         [-0.04415772, -0.04172506,  0.02140195, ...,  0.03081115,
           0.00456979, -0.04162275],
         ...,
         [ 0.00587064, -0.02427757,  0.0343413 , ..., -0.00904534,
           0.02691308, -0.03140774],
         [-0.02517486,  0.0080907 , -0.01646957, ...,  0.00406561,
          -0.0245582 ,  0.0112964 ],
         [ 0.04347919, -0.0091765 ,  0.01060292, ...,  0.04798204,
          -0.01913628,  0.03221822]],

        [[ 0.00103113,  0.02559758, -0.03944407, ..., -0.027313  ,
          -0.01724102,  0.02766124],
         [-0.03605266, -0.02207971, -0.02607583, ...,  0.019163  ,
          -0.00409165,  0.00734793],
         [ 0.03992468, -0.00830158, -0.00792204, ..., -0.0387061 ,
          -0.03558898,  0.02069849],
         ...,
         [ 0.03167233, -0.00213136, -0.04552784, ..., -0.04662289,
          -0.0404689 ,  0.00600467],
         [ 0.02277555,  0.01608774,  0.04091766, ..., -0.03235018,
          -0.00019232, -0.01472781],
         [ 0.00132513,  0.00428362,  0.02391171, ..., -0.01080278,
          -0.00372982, -0.02744681]]]], dtype=float32), array([-7.36861257e-03,  1.23837835e-05,  4.88561578e-03,  2.90536229e-03,
       -1.15312058e-02, -1.68345578e-03, -1.12947682e-02, -2.23711208e-02,
       -7.20743975e-03, -8.50237533e-03, -2.94891559e-03,  6.42230408e-03,
       -1.51141994e-02,  2.86758877e-03, -1.70418862e-02, -1.68088917e-02,
        5.36635146e-03,  3.18124564e-03, -1.43853603e-02, -4.64578765e-03,
        1.08675491e-02, -1.69221256e-02,  4.71232878e-03, -1.23090055e-02,
       -1.45718642e-02, -2.13827621e-02, -3.93332588e-03,  8.56523961e-03,
        6.19427720e-03,  9.45919380e-03,  2.90886825e-03, -7.76946731e-03,
       -3.90603254e-03, -1.24472817e-02, -1.91070251e-02, -1.02358556e-03,
        7.94132426e-03,  7.65163591e-03,  6.39007753e-03,  2.37718050e-04,
        8.99937376e-03, -5.57275768e-03,  3.51618888e-04,  1.05979554e-02,
       -1.59314014e-02,  1.09071098e-02, -7.13993190e-03, -1.92023385e-02,
       -1.10891145e-02, -3.78847518e-03, -1.01101417e-02,  8.11957754e-04,
       -2.00364087e-02, -3.28821735e-03,  8.15425906e-03, -7.99196959e-03,
        6.73127966e-03, -9.99599788e-03, -1.99378282e-02, -7.63024529e-03,
        5.34768449e-04, -2.48412439e-03, -1.12333510e-03, -1.43755348e-02,
       -2.64738873e-02, -1.15921171e-02,  2.29472225e-03, -6.81373337e-03,
       -2.17415672e-02, -2.37614219e-03, -1.28500378e-02,  8.38389434e-03,
        7.61937443e-03,  7.80459447e-03,  7.18172593e-03, -5.95250120e-03,
        4.80806315e-03, -1.93890017e-02,  1.51839235e-03, -2.50139553e-02,
       -7.88913853e-03,  5.72241563e-03, -1.35586010e-02, -1.46304034e-02,
        1.88651250e-03, -4.92518861e-03, -1.07559748e-02, -7.14823185e-03,
        8.49787891e-03, -1.01274466e-02, -5.99776115e-03, -8.96656513e-03,
        6.53921021e-03, -1.82331316e-02, -1.76671743e-02, -6.85736537e-04,
        4.59012110e-04, -1.93559583e-02, -9.88137443e-03,  5.59065305e-03,
        1.06850620e-02,  4.62579122e-03,  5.72382053e-03, -7.90103432e-03,
       -6.51451852e-03, -1.77376077e-03, -1.21144857e-02, -1.86027621e-03,
       -1.97485667e-02, -7.20257778e-03, -2.16285624e-02, -1.32475523e-02,
        9.63116623e-03,  1.11878049e-02,  6.85914420e-03,  1.33713912e-02,
       -1.99043639e-02, -1.21583892e-02, -5.88555122e-05, -1.85372159e-02,
       -1.21273310e-03,  3.51156719e-04,  6.50456734e-03,  2.77166115e-03,
       -1.03222048e-02, -6.57203561e-03, -2.67980471e-02, -6.38690544e-03,
       -2.07486656e-02,  6.94158894e-04, -1.64538752e-02, -1.53391706e-02,
        2.50680884e-03, -1.44168576e-02, -1.04652410e-02, -6.03724597e-03,
       -8.47869832e-03,  2.13847030e-03, -3.09016858e-03, -8.43492709e-03,
       -3.91908549e-03, -2.27706041e-02, -2.41529159e-02, -4.58729127e-03,
       -1.05624981e-02, -4.49559279e-03,  2.16672034e-03, -1.35339927e-02,
       -5.10338042e-03, -2.33942969e-03, -7.82389939e-03, -3.39108100e-03,
        1.51030784e-02, -2.49381009e-02,  1.56456791e-03, -1.68465748e-02,
       -2.69736513e-03, -1.57959107e-02, -2.35222727e-02, -5.38846618e-03,
        5.53973252e-04, -1.00704981e-03, -1.50196366e-02, -8.59351177e-03,
        9.25822183e-03, -2.09775940e-02, -2.41833143e-02, -6.40011951e-03,
        4.97349072e-03, -3.80275818e-03,  2.14476575e-04,  8.95771605e-04,
        9.34895873e-03,  5.51967882e-03, -7.89818354e-03, -7.98323471e-03,
       -1.54551538e-02,  6.76098466e-03, -4.39504813e-03, -4.80692834e-03,
       -1.70191694e-02, -1.35017987e-02, -1.60661116e-02, -4.76166280e-03,
        4.23048856e-03,  1.48694431e-02, -1.72160491e-02, -1.20163476e-02,
       -4.17543342e-04, -1.92940850e-02,  1.09955873e-02, -2.66886745e-02],
      dtype=float32), array([ 0.4680425 , -0.3528252 ,  0.9343702 , -0.27175108,  0.7230625 ,
       -0.6936563 ,  0.5691204 , -0.29377955,  0.517413  ,  0.9270182 ,
        0.27513552, -0.3501847 ,  0.7951171 , -0.13292517,  0.95842546,
        0.7315189 , -1.0293566 , -0.79945356, -0.071198  , -0.03137828,
       -0.03915473,  0.18993627, -1.1757034 ,  0.5065086 ,  0.7017922 ,
        0.66916955, -1.0210152 ,  0.01087263, -0.4556214 , -0.94039816,
       -0.7429763 ,  0.60249215, -1.2204925 ,  0.23816642,  0.7990504 ,
        0.34569994, -0.53692794, -0.9568512 , -0.7298065 ,  0.5633899 ,
       -0.97582716,  0.24279636, -0.24568439, -0.9533657 ,  0.9978045 ,
        0.2787213 ,  0.38912007,  1.2813575 ,  0.5630195 , -0.25135157,
       -0.71703714, -0.82970256,  0.8029459 , -0.50917464, -0.7961493 ,
        0.18989111, -0.73302263,  0.73707515,  0.818773  ,  0.961638  ,
        0.39477155, -0.6647015 , -0.90267825,  0.01339594,  0.99479353,
        0.9333517 , -0.6916901 ,  0.7588766 ,  0.94904137, -0.5627464 ,
       -1.286111  , -0.32118863, -0.05325818,  0.28126043, -0.88682586,
        0.28564495, -0.76558244,  0.7208306 , -0.01339801,  0.53468823,
       -0.79095525,  0.42115244,  0.7080217 , -0.21021032, -0.8524094 ,
       -0.44424218, -1.0757179 , -0.23083058,  0.35370654, -0.02864284,
        0.66767895,  0.7339765 ,  0.6528232 ,  0.7448095 ,  1.149753  ,
       -0.9083919 , -0.8210404 , -0.22315685, -0.08905748,  0.2848825 ,
       -1.5752991 ,  0.27959165,  0.20210907, -1.695511  , -1.0990555 ,
       -1.0212922 , -0.17963867, -0.58673227,  0.4661165 ,  0.25988632,
        0.45378247,  1.1764874 ,  0.2621005 , -1.3587762 , -0.03935718,
       -0.6944473 ,  0.32934478, -0.07688503, -0.57011986,  0.3121809 ,
       -1.1133019 ,  0.4287429 , -1.0618248 ,  0.46161708,  0.19891067,
       -0.8559662 ,  0.8155609 ,  0.9122721 ,  0.78910565, -1.0440124 ,
        0.54308057,  0.01530308, -0.00782664,  0.05313638,  0.5508893 ,
        0.45419213, -0.7701272 ,  0.8789227 , -0.26144978,  0.14463463,
        0.74259186,  0.48261344,  0.65753245,  0.27784443, -0.91108817,
        0.59239614,  0.12921688,  0.40688837, -0.5521682 , -0.78659636,
        0.560315  , -0.92236096, -1.8173736 ,  0.99273413, -1.2529505 ,
        0.89577127,  0.48020944,  0.13685691,  0.8020829 ,  0.21362545,
        0.05365201, -0.06985427,  0.7307157 ,  0.72683483, -0.31331682,
        1.0353479 ,  0.9427936 , -0.58941466, -1.1517937 ,  0.00227882,
       -0.40725586,  0.569526  , -1.0451635 , -1.1306392 , -1.0490496 ,
       -0.28191137,  1.1151593 , -0.8350627 , -0.10840877,  0.51918906,
        0.63927585,  0.6518244 ,  0.73691297,  0.8057784 , -0.97906566,
       -1.1831245 ,  1.0499718 ,  0.1816622 ,  0.11156037,  0.08099236,
       -1.057838  ,  0.52682513], dtype=float32), array([ 4.213826 ,  1.7544086, 12.008891 ,  4.706004 , 14.347832 ,
        2.7494555,  4.5279202,  1.3896772,  2.913179 ,  1.9768904,
        0.9396439,  2.5107074,  1.6893814,  3.9325006, 11.613083 ,
        9.974888 , 11.011582 ,  3.9435227,  3.393821 ,  3.9228728,
        4.8979716,  2.7432086,  3.0182757,  4.8019104, 13.83573  ,
       10.828917 ,  3.7783844,  3.4799895,  4.4251947,  5.186461 ,
        8.039386 ,  5.198642 ,  5.1658525,  7.1503644, 11.545555 ,
        6.1641655,  1.734255 ,  4.1678476,  2.2725165,  5.5619087,
        3.492267 ,  1.289268 ,  2.0054574,  4.564525 , 14.484399 ,
        1.8890774,  7.724389 , 12.75031  , 12.644608 ,  1.770413 ,
        1.7345484,  5.3389764,  7.658444 ,  2.446763 ,  3.515017 ,
        1.0073986,  2.184843 ,  5.449775 , 14.822483 ,  6.9630365,
        1.4443722,  4.1454043,  9.823773 ,  0.9240208, 12.976379 ,
       14.148945 ,  3.6358657,  4.021053 , 13.151043 ,  3.868991 ,
        6.0421195,  1.2944223,  0.4731919,  5.755026 ,  5.0538535,
        1.156755 ,  2.3397632,  6.44425  ,  2.1534638,  7.0063086,
        4.142435 ,  5.9869804, 13.328825 ,  1.7740216,  3.3703785,
        2.8679247,  4.2739334,  2.2950742,  9.853051 ,  1.6749218,
        1.5177522,  1.3999684,  2.551283 ,  3.770614 , 12.155926 ,
        5.8228383,  1.4749038,  6.7238092,  0.9385163,  4.367885 ,
        8.629933 ,  7.235246 ,  4.1768465,  5.8128967,  5.563374 ,
        2.9198985,  5.148833 ,  2.2375002, 13.06341  ,  7.2829447,
        8.816059 , 15.151086 ,  7.140447 ,  5.003128 ,  1.6506221,
        3.542377 , 11.061099 ,  1.3857019,  2.0408   ,  8.258671 ,
        7.4215717,  1.1621236,  2.0290835, 10.262076 ,  1.5928115,
        2.101083 , 11.4332075,  3.9989426,  3.3298216,  7.023976 ,
       12.876597 ,  1.1227152,  3.523522 ,  1.2414397,  1.2377311,
        5.3128886,  4.7679253,  2.8800836,  6.392303 ,  2.0890923,
        8.01104  ,  6.3078   ,  7.333093 ,  8.778929 ,  2.428025 ,
        7.0288095,  5.6045904, 11.78762  ,  2.2307463,  4.3626614,
        6.5127735,  2.021563 ,  9.388879 , 16.93295  ,  5.2753844,
       12.964808 ,  2.7682307,  2.7183683, 10.348239 ,  7.634153 ,
        2.875654 ,  1.947331 ,  4.2211514,  3.4867253,  0.9245765,
       12.374367 , 10.798791 ,  2.9002657,  5.624832 ,  1.4410213,
        1.849887 ,  7.149968 ,  6.3134665,  3.163008 ,  4.2688894,
        1.770219 , 17.369967 ,  2.1808069,  2.3756425,  3.972171 ,
       12.849749 ,  8.745704 , 12.553896 ,  4.629589 ,  2.258254 ,
        5.3514447, 13.904557 ,  2.356648 ,  2.2634602,  4.5670977,
        4.813872 , 12.300204 ], dtype=float32), array([[[[ 0.04966339, -0.00644311, -0.00639025, ..., -0.04407179,
           0.06905795,  0.05676598],
         [ 0.08589745,  0.06636941,  0.05464965, ..., -0.01950267,
          -0.06633473,  0.00922726],
         [-0.05373269,  0.02895409,  0.03886192, ...,  0.09407962,
           0.03502423, -0.06393565],
         ...,
         [ 0.04262916,  0.06574791, -0.01722316, ..., -0.03218697,
           0.00372159,  0.07390106],
         [-0.02268269,  0.03829829,  0.06277861, ...,  0.00735042,
           0.00376748, -0.06868306],
         [-0.01254287, -0.01976304,  0.08642036, ...,  0.03435612,
          -0.01421558,  0.0167592 ]]]], dtype=float32), array([[[[-1.54216578e-02,  1.04887085e-02,  2.63290703e-02, ...,
          -1.83321135e-05,  1.39322625e-02,  3.44906114e-02],
         [ 1.43194590e-02, -7.64523121e-03,  3.84036973e-02, ...,
          -3.82220037e-02,  1.72353033e-02,  1.38604660e-02],
         [ 4.24103662e-02,  2.28589587e-02,  6.92968443e-03, ...,
           1.52281905e-03,  1.10085204e-03,  2.99273394e-02],
         ...,
         [-7.18985591e-03, -5.63433841e-02,  1.74881294e-02, ...,
          -8.07297789e-03, -7.54170411e-04,  2.74098981e-02],
         [ 2.17669066e-02, -6.85618678e-03, -1.86112393e-02, ...,
           5.24577945e-02,  3.00418511e-02,  1.55889420e-02],
         [ 3.74491215e-02, -1.96252018e-02, -3.03652659e-02, ...,
          -2.78885439e-02,  2.44293511e-02,  5.14828693e-03]]],


       [[[ 9.72399861e-03,  8.82211328e-03, -3.80035117e-02, ...,
          -6.04633242e-03, -2.13751383e-02,  2.43987665e-02],
         [-3.96806933e-02,  1.96802299e-02, -9.66692634e-04, ...,
          -3.37425545e-02, -1.16637712e-02, -1.56440344e-02],
         [ 3.61121371e-02, -3.54260802e-02,  2.46157832e-02, ...,
          -4.38735895e-02, -4.24944982e-02,  1.51849380e-02],
         ...,
         [-2.35614218e-02, -1.98827498e-02,  4.58357017e-03, ...,
           1.83985755e-02, -5.97467972e-03, -1.67366229e-02],
         [ 6.83294050e-03,  2.46839542e-02, -3.38554233e-02, ...,
           5.21128811e-02, -1.04770642e-02, -4.51330245e-02],
         [-1.80067699e-02, -3.69363986e-02, -3.75461131e-02, ...,
          -6.97660213e-03, -2.55762096e-02, -4.46098037e-02]]],


       [[[-3.37483897e-03,  5.08131571e-02, -3.26623544e-02, ...,
           3.68654355e-02, -3.92979868e-02,  2.35043168e-02],
         [-3.06665543e-02,  2.37646978e-02,  3.95436361e-02, ...,
          -2.54228637e-02, -5.31928688e-02,  1.38633940e-02],
         [ 3.61286402e-02, -2.72530429e-02,  1.28643569e-02, ...,
          -3.44101363e-03, -1.05159571e-02, -4.39949110e-02],
         ...,
         [-1.22612296e-02,  1.16645610e-02,  1.00139203e-02, ...,
          -5.13899960e-02, -3.30085643e-02,  1.88017972e-02],
         [-2.50591207e-02,  2.93674208e-02,  1.03131020e-02, ...,
           4.90238070e-02, -9.79202241e-03, -9.47468076e-03],
         [-1.11065228e-02, -1.24737481e-02, -1.35721294e-02, ...,
           4.46973480e-02, -2.44894996e-02,  1.44100795e-02]]],


       ...,


       [[[-1.07735693e-02, -2.93129589e-02, -2.69594118e-02, ...,
          -4.04193178e-02,  1.29040312e-02,  4.64547705e-03],
         [ 5.03698178e-02, -1.98384225e-02, -2.55261660e-02, ...,
          -3.13337408e-02, -3.45060229e-02,  1.55134462e-02],
         [-2.27869321e-02, -2.49690097e-02, -1.19124018e-02, ...,
          -4.17124154e-03,  1.98206473e-02,  3.07035493e-03],
         ...,
         [ 5.59696602e-03,  1.29698608e-02, -2.03575008e-03, ...,
          -7.09013361e-03, -2.05269456e-03,  3.04496642e-02],
         [-1.80439819e-02, -4.69289869e-02,  2.32568500e-03, ...,
           1.97537560e-02, -1.91741176e-02, -1.36322773e-03],
         [-4.97041196e-02, -1.38339391e-02, -3.63549106e-02, ...,
          -3.10761333e-02, -1.06954332e-02, -3.18737980e-03]]],


       [[[-1.88792385e-02, -1.09845176e-02, -4.00546044e-02, ...,
          -2.22350042e-02,  2.15438884e-02, -9.53829661e-03],
         [ 4.00130935e-02,  4.57470678e-02, -2.74882565e-04, ...,
           2.81978641e-02,  3.31091322e-02, -3.54514904e-02],
         [-4.28930521e-02,  2.56968271e-02, -2.09243838e-02, ...,
          -3.82670164e-02, -4.59805839e-02, -4.32447493e-02],
         ...,
         [-3.30598652e-02,  4.15334255e-02,  1.87872779e-02, ...,
          -5.08133648e-03, -4.46438082e-02, -3.46276313e-02],
         [-2.46320274e-02, -5.90211805e-03, -4.07260954e-02, ...,
          -3.83338183e-02,  3.48319090e-03,  6.66543003e-03],
         [-4.38909493e-02,  1.51807824e-02,  6.74039871e-03, ...,
           4.68708836e-02, -2.45831739e-02, -2.44476944e-02]]],


       [[[-4.35459651e-02, -1.56792197e-02, -3.54843438e-02, ...,
          -4.12292331e-02,  1.39110982e-02, -7.42184790e-03],
         [-1.22469347e-02,  5.70819667e-03, -1.24694547e-02, ...,
          -9.87067353e-03,  1.45854999e-03,  6.78761629e-03],
         [ 1.62822343e-02, -3.22338985e-03, -3.68614160e-02, ...,
           2.54945010e-02,  3.78784165e-02, -4.37663645e-02],
         ...,
         [-3.67441475e-02, -4.40500714e-02, -6.89651584e-03, ...,
          -5.13602123e-02, -3.37517448e-02,  2.62568034e-02],
         [ 4.81496751e-03, -3.27122882e-02, -8.15230887e-03, ...,
          -3.44180018e-02, -1.86072066e-02,  5.47190802e-03],
         [-2.26200894e-02,  6.50180504e-03, -2.63953302e-02, ...,
          -2.76887007e-02,  4.17222343e-02, -6.87944796e-03]]]],
      dtype=float32), array([-9.61916347e-04,  1.02761220e-02, -1.88328158e-02, -1.06531428e-02,
        8.21518525e-03, -8.00742023e-03, -7.00830529e-03,  3.01475200e-04,
       -4.63077100e-03,  7.86333624e-03, -9.31182690e-03,  7.09337601e-03,
        8.31957348e-03, -4.04591532e-03,  4.46392689e-03, -1.40694324e-02,
       -1.62236637e-03,  4.89713205e-03, -2.83898460e-03,  3.70862312e-03,
       -1.66731533e-02,  2.17841403e-03, -1.42286820e-02, -1.98899559e-03,
       -2.16895691e-03,  8.62385798e-03, -1.16634071e-02, -7.55405566e-03,
        2.90689501e-03, -1.31673121e-04, -1.49036394e-02, -4.71284939e-03,
       -3.42676369e-03, -8.64195917e-03, -3.64495954e-03, -3.07462388e-03,
       -1.19335204e-02, -1.42265921e-02,  8.42105784e-03,  7.36698566e-05,
       -2.41847383e-03, -1.08861402e-02, -2.59298533e-02,  1.13165490e-02,
       -2.50738431e-02,  1.64256943e-03, -1.21570583e-02, -1.04414215e-02,
        1.00677162e-02,  1.91564416e-03,  1.29116764e-02, -1.82670483e-03,
       -2.40366645e-02, -1.51904058e-02, -2.94542592e-03,  5.90900704e-03,
       -3.97810771e-04, -1.48255564e-03, -2.23245602e-02, -1.30311418e-02,
       -6.56991964e-03, -6.89296238e-03, -2.04051025e-02, -5.76718361e-04,
       -6.47737086e-03, -2.14143917e-02, -1.96331684e-02,  4.03240614e-04,
       -1.03144515e-02,  1.37150362e-02, -1.40976394e-02,  6.40061544e-03,
       -3.70419002e-03, -1.86732486e-02, -3.07738525e-03, -1.77935734e-02,
        3.04568373e-03,  1.00492162e-03,  1.93860456e-02,  6.84904662e-05,
       -3.41836130e-03,  7.62799894e-03, -4.55526053e-04, -9.62884445e-03,
       -7.11714849e-03, -1.20236780e-02, -6.53624116e-03, -1.13415178e-02,
       -1.01309940e-02,  1.93889823e-03, -7.92618282e-03, -2.90944986e-03,
        9.33981675e-04, -2.37176418e-02, -9.16501693e-03,  8.39910656e-03,
        2.98894476e-03, -1.40164476e-02,  4.40562004e-03, -2.02111192e-02,
       -5.07179694e-03, -1.57218128e-02, -8.87148827e-03,  1.43419215e-02,
       -7.54939020e-03, -5.34709916e-03, -9.41959210e-03, -2.26977915e-02,
        2.25618621e-03, -4.86094132e-03, -1.65733807e-02,  3.14756972e-03,
        1.14246681e-02, -3.65653285e-03, -1.15481010e-02, -1.85436010e-02,
       -2.10535675e-02, -8.27090815e-03, -3.73778283e-03, -1.64615698e-02,
        6.11948781e-03, -1.89127568e-02,  2.35907733e-03, -6.05759583e-03,
       -7.02684978e-03, -3.44115961e-03, -3.76952766e-03, -5.73036587e-03,
        3.21783754e-03, -5.49006555e-03, -6.92688907e-03,  1.35334194e-04,
        7.99332745e-03, -4.17748466e-03, -8.29070713e-03, -1.34079214e-02,
       -4.63908800e-04, -7.74616515e-03, -1.14900842e-02, -2.40422152e-02,
       -6.13041397e-04, -2.54823584e-02, -1.11098597e-02, -1.01259025e-03,
       -4.14559431e-03,  8.26886215e-04,  5.13713690e-04,  1.62561890e-02,
       -1.14455365e-03, -9.41957906e-03, -8.82588211e-04, -1.41420413e-03,
        9.31759458e-03, -1.51916686e-02, -1.79080851e-02, -1.07139936e-02,
       -1.60910618e-02, -8.96769296e-03, -1.96406301e-02, -1.23709962e-02,
       -4.94859274e-03, -8.00982234e-04,  1.16004003e-02, -3.50541575e-03,
        8.27709027e-03, -5.14259096e-03,  3.74721945e-03,  6.10511191e-03,
       -5.68885822e-03, -1.22719239e-02, -5.67799201e-03, -1.33126900e-02,
       -1.24716917e-02, -1.25690615e-02, -7.72905862e-03, -1.07212234e-02,
        1.73487584e-03, -9.74038523e-03,  9.44277085e-03, -8.64291936e-03,
       -1.10837612e-02, -6.22158870e-03,  5.15299989e-03,  5.85170055e-05,
       -5.59365842e-03, -1.64180789e-02, -1.68964602e-02, -1.37695484e-02,
        8.11523665e-03, -1.84661578e-02,  5.23362914e-03, -6.04571356e-03],
      dtype=float32), array([-0.49723613, -0.9847471 ,  0.54993695,  0.51324034,  0.2899798 ,
        0.2395136 ,  0.6663089 ,  0.9649869 ,  0.7548093 , -0.25055137,
        0.8185588 , -0.9444566 , -1.6099669 , -0.2251254 , -0.5499677 ,
        1.832003  , -0.36727262, -0.83270866, -0.7095819 , -0.6514918 ,
        1.0058361 ,  0.13368721,  0.9875697 , -0.46906435,  0.17926973,
        0.24692607,  0.39269963,  0.5477193 ,  0.46392867,  0.2129167 ,
       -0.19352038, -0.10584188,  0.3528521 ,  0.14559318,  0.06864797,
        0.80951345,  1.1371434 , -0.86466527, -0.09435752, -0.2388457 ,
       -0.9762305 ,  0.5786539 ,  1.0208863 ,  0.43619293,  1.4230556 ,
        0.07756238,  0.71914446, -0.5163686 , -0.34986326, -0.5527188 ,
       -0.56608737, -0.15976387,  0.26516607,  0.31967807, -0.7100063 ,
       -0.6713529 , -0.7843353 ,  1.2245066 ,  1.297661  , -0.76343733,
        0.7838521 , -0.94363713,  1.1635782 , -1.0629996 , -0.8460689 ,
        1.0912216 ,  0.98696417, -0.56320083,  0.15734328,  0.30545825,
        0.3334758 , -0.25165793, -0.3989151 ,  0.59499705,  0.03633447,
        1.2949798 ,  0.13910681, -0.78989494, -0.56650597, -0.5792364 ,
       -0.4876873 ,  0.49347165, -0.00575457, -0.02996594,  0.14243609,
       -0.5743126 ,  0.047639  ,  0.50744605,  0.61545867, -0.25152892,
        0.24032243,  0.9932043 , -1.4936459 ,  0.868531  ,  0.5817774 ,
        0.5644638 , -0.05910464, -0.33146027,  0.04488607,  1.0277529 ,
       -0.13265154,  1.0888511 ,  0.21269326, -0.80461407,  0.78139764,
        0.61497796, -0.26224297,  0.5400517 ,  0.0841955 , -0.19400567,
        0.9412536 ,  0.44518328,  1.01824   ,  0.08523363, -0.7539586 ,
        0.731632  ,  0.16176176, -0.33562136, -0.22581439,  1.2031424 ,
       -0.4543333 ,  0.99734914, -0.48519737, -0.1285322 , -0.27660832,
       -0.686417  , -0.4366554 , -0.23929241,  0.57018894,  0.1047632 ,
        0.70892876, -0.15115586,  0.2718426 ,  0.2558436 ,  0.9087737 ,
        0.83005595,  1.410493  , -0.34069017,  0.7709117 ,  0.99541354,
        0.8058458 ,  0.16219322, -0.14661697,  0.63186675,  0.50100654,
       -1.5480946 ,  0.16711113, -0.34109607,  0.07292941,  1.2046379 ,
        0.3744689 ,  0.63037103,  0.37550172,  0.5348677 ,  1.2916856 ,
        0.0714239 ,  0.77184105,  0.5504699 ,  0.88907105, -0.2984427 ,
        0.8943992 ,  0.28147352,  0.04804337,  0.800046  ,  0.14356863,
        1.1394185 , -0.03215855, -0.70063084,  0.22766517,  1.0189272 ,
       -0.03477117,  1.1476626 , -0.61282235,  0.2391311 , -0.29679066,
        0.49502513, -0.31947204, -0.36611405,  0.25658345,  0.7571604 ,
        0.98908097, -0.71178406, -1.0304719 , -0.24178849,  0.44572392,
        1.2390912 ,  0.82479364,  1.0552199 , -0.961973  , -0.07671151,
        0.01084221,  0.62876564], dtype=float32), array([0.8869542 , 3.2780204 , 4.5448256 , 1.4351729 , 0.55441743,
       4.3265553 , 1.6492573 , 1.4134817 , 2.9175544 , 2.1259453 ,
       2.6614637 , 3.9691231 , 4.3810096 , 1.3096018 , 2.568984  ,
       3.1678572 , 1.9913428 , 2.2845566 , 1.4017351 , 1.8644564 ,
       7.712161  , 1.7919452 , 4.786857  , 1.6860168 , 1.0513698 ,
       1.5896763 , 1.1934055 , 2.3188913 , 1.0506251 , 1.5391505 ,
       3.9205232 , 2.3612664 , 2.6453574 , 2.2607439 , 1.7900833 ,
       2.7158763 , 4.02798   , 2.6303349 , 1.125066  , 0.59651047,
       3.2050154 , 1.3815708 , 6.3994613 , 1.1847192 , 9.229433  ,
       0.514816  , 3.3607554 , 2.5746634 , 1.7969538 , 1.1838213 ,
       1.928226  , 1.828721  , 1.5219445 , 4.840815  , 1.858853  ,
       2.5945387 , 1.476428  , 1.207826  , 7.0736766 , 0.8269448 ,
       2.2842891 , 2.8156188 , 7.0453477 , 2.1493845 , 2.1962893 ,
       7.4999924 , 3.7088351 , 1.5519977 , 3.4678798 , 2.1923568 ,
       1.8282791 , 1.2097341 , 1.7384557 , 3.6913936 , 1.4084228 ,
       5.022089  , 2.0099676 , 3.491553  , 2.9128234 , 1.2997515 ,
       3.5862148 , 1.4190007 , 1.4432517 , 2.9570146 , 1.2452222 ,
       1.3352332 , 1.0395309 , 1.8195966 , 3.9437604 , 1.8334655 ,
       1.1984652 , 2.9735105 , 2.223306  , 4.211423  , 1.4893602 ,
       4.1469398 , 1.4509515 , 0.61659586, 2.5279307 , 4.341423  ,
       1.3370721 , 7.831571  , 0.5941218 , 1.8484396 , 1.0686172 ,
       3.7390568 , 2.2632353 , 1.7272422 , 0.8541102 , 1.178963  ,
       1.7651141 , 2.5310066 , 3.2653449 , 2.1492586 , 3.610059  ,
       5.5289564 , 2.6762993 , 3.0788693 , 1.5495152 , 2.5572138 ,
       1.1055814 , 3.6414819 , 2.3087301 , 1.1303976 , 1.913749  ,
       2.1887245 , 1.7524215 , 1.4729486 , 1.9041213 , 1.1123264 ,
       2.5437672 , 2.0772378 , 0.7044665 , 2.0900953 , 0.9611895 ,
       0.9600807 , 0.8965564 , 0.7201795 , 1.9048302 , 6.035157  ,
       3.7071872 , 2.503038  , 0.8677817 , 2.7847106 , 0.5468406 ,
       5.0464277 , 1.4955592 , 1.9433272 , 2.65239   , 3.350769  ,
       2.1757555 , 0.84140533, 1.547078  , 3.3314068 , 4.8213043 ,
       2.0484028 , 1.9152113 , 3.6556385 , 4.4787107 , 1.9360194 ,
       2.091061  , 1.9670982 , 1.2636775 , 0.63033056, 5.0885572 ,
       1.1510072 , 0.8640386 , 3.0600314 , 0.6040751 , 3.3483703 ,
       1.1174021 , 5.984667  , 1.5349299 , 1.3931288 , 2.4333513 ,
       3.1607714 , 1.3185574 , 1.3664762 , 0.4887171 , 2.445234  ,
       3.667412  , 1.538891  , 2.0123823 , 2.0622818 , 3.4964638 ,
       4.73942   , 7.0014253 , 1.6126966 , 1.8781133 , 1.4877981 ,
       1.4507475 , 1.714972  ], dtype=float32), array([ 1.73303735e-04,  5.39117586e-03,  8.48316960e-03, -1.30923785e-04,
       -1.21436771e-02,  5.76500373e-04,  6.00673817e-03, -3.42269847e-03,
        5.01779793e-03, -1.00490283e-02, -1.47754783e-02, -1.95765421e-02,
        2.04766244e-02, -5.06755197e-03, -2.82202270e-02, -7.87888654e-03,
        7.51408841e-03,  8.87849927e-03, -1.68041829e-02, -7.35603785e-03,
       -2.55110729e-02,  1.76285449e-02,  8.86245072e-03, -5.57930395e-03,
        6.66059880e-03, -1.14676543e-03,  2.34072115e-02, -3.08578089e-02,
        4.35657147e-03, -1.14198169e-02, -2.22916622e-02, -1.54872434e-02,
       -1.42887598e-02, -8.95779394e-03,  9.19540506e-03,  1.69969120e-04,
       -1.66080855e-02, -2.65201200e-02, -4.39925212e-03, -1.18488667e-03,
        2.68344139e-03, -1.40637998e-02, -2.20804941e-02, -2.80190213e-03,
        2.03772308e-03, -1.72899570e-02,  1.74729582e-02, -1.14726285e-02,
        1.87646281e-02, -3.80429183e-03,  1.21186720e-02, -1.85504630e-02,
        6.89215772e-03, -1.26960650e-02, -9.31364764e-03,  1.07901888e-02,
       -1.25077423e-02, -1.10389199e-02, -1.13981869e-02,  2.53085829e-02,
       -8.11759010e-03,  7.74501124e-03,  3.72438924e-03, -1.88272670e-02,
        2.02242029e-03,  1.38269309e-02, -1.13246217e-02, -9.74765327e-03,
       -4.13408969e-03, -8.23741965e-03, -1.90655235e-02,  1.58418007e-02,
        2.30946322e-03,  5.15914615e-03, -1.17444561e-03, -1.06085455e-02,
       -2.24527251e-02,  5.10020880e-03, -1.50979543e-02, -2.71745902e-02,
        3.07722948e-04, -3.11882123e-02,  9.35486052e-03, -9.30743292e-03,
       -2.65814569e-02,  2.40980703e-02, -4.90981201e-03, -1.10926507e-02,
       -1.97767336e-02,  7.45995343e-03, -8.38257466e-03, -1.89558193e-02,
       -2.27184147e-02,  9.56628006e-03, -2.25146636e-02,  9.75431968e-03,
       -1.63466316e-02, -1.42438030e-02,  1.60279535e-02, -4.90860362e-03,
       -2.91149295e-03, -6.31950470e-03, -9.33010597e-03, -1.92234740e-02,
        8.62399396e-03, -2.56607251e-04,  1.83194187e-02,  1.63011961e-02,
       -2.45936383e-02,  2.14375779e-02, -6.50821161e-03, -6.46204269e-03,
       -1.81643087e-02, -2.07253136e-02,  9.55230463e-03, -1.64503381e-02,
       -1.90444023e-03, -1.87785327e-02, -8.58346373e-03,  1.21868197e-02,
        1.05658071e-02, -3.60132311e-03,  1.28894281e-02,  2.01132149e-02,
        1.57272350e-02,  1.24805672e-02, -7.78526487e-03, -3.08196014e-03,
        6.58778287e-03,  8.60170275e-03,  4.88145815e-05, -1.76264346e-02,
        3.50514846e-03,  6.79334253e-03, -9.57995467e-03, -2.16524536e-03,
       -2.12024506e-02,  1.12940855e-02, -7.70131405e-03, -1.10208523e-02,
        7.83995166e-03, -1.30073838e-02, -2.95362491e-02,  1.10599520e-02,
        3.37193301e-03, -4.84146818e-04, -1.23819504e-02, -1.69331450e-02,
       -3.78203206e-02, -9.27408691e-03, -3.22695822e-03,  1.06689166e-02,
       -4.41184686e-03, -1.17039802e-02, -7.87740108e-03, -1.69266239e-02,
       -1.27429338e-02, -8.07933789e-03, -2.08985899e-02,  6.92340371e-04,
       -9.65087488e-03, -2.62327604e-02, -1.51966431e-03,  1.89175131e-03,
       -1.17288926e-03, -1.73109211e-02, -2.60303430e-02, -1.08950837e-02,
       -2.45135315e-02, -1.55843869e-02,  1.01563539e-02,  1.64805129e-02,
       -1.70357917e-02,  3.74163128e-03,  8.66372138e-03,  8.46740417e-03,
       -9.54874698e-03, -5.44953020e-03, -1.07790656e-04,  1.68249547e-03,
        2.10480038e-02, -2.46260408e-02,  6.69258786e-03, -1.99319795e-03,
        1.92693307e-03, -2.05033626e-02, -1.36570800e-02,  2.48536170e-02,
        1.84169784e-02,  4.46694624e-03, -3.68861179e-03, -4.73112147e-03],
      dtype=float32), array([-0.7169612 , -0.8344346 , -0.27551553, -0.59217626,  0.19512257,
       -0.3478455 , -0.7861224 , -0.7079089 , -0.96198726,  0.4940625 ,
        0.78423744,  0.69088954, -0.62492603, -0.02063537,  1.2261813 ,
       -1.0534961 , -0.73127544, -0.49960133, -0.2885632 , -0.00171285,
        0.7667105 , -0.7895758 , -0.6719545 , -0.48789552, -0.6248007 ,
        0.61436725, -1.1781244 ,  0.89000505, -0.9182944 ,  0.33843714,
        0.54920316,  0.7931655 ,  0.84677124,  0.2310475 ,  0.32151657,
       -0.8011791 , -0.17866625,  0.969527  , -0.33769503,  0.62650913,
       -0.73895407,  0.5862645 ,  1.5033206 , -0.12940395, -0.43391567,
        0.4773957 , -1.4788773 , -0.87925094, -0.9687105 , -0.13989039,
       -0.65076923,  0.9617358 , -0.70000213,  0.60994005,  0.55538744,
        0.05688123,  0.6135998 ,  0.66584355, -0.661384  , -0.8788171 ,
        0.54681176,  0.48023427, -0.80199564,  0.8168339 , -0.08073226,
       -1.0969746 ,  1.1797823 , -0.29061535,  0.22962616,  0.6195206 ,
        0.44736508, -0.8428933 , -0.6907875 , -1.2864729 , -0.34897563,
        0.5914591 ,  0.69096476,  0.6435748 ,  0.70704633,  0.6698675 ,
       -0.8360264 ,  1.2560954 , -0.99087274,  0.9903292 ,  1.108176  ,
       -0.84356475,  1.0592703 ,  1.1729991 ,  0.96350884, -0.56000084,
        0.44042692,  0.42906755,  1.6172653 , -0.7061504 ,  0.9999823 ,
       -0.31494743,  1.1889504 ,  0.77925634, -0.08727587,  0.33446696,
       -0.6646958 ,  0.61061066,  0.6094782 ,  0.74575007, -0.55624056,
        0.64409214, -0.24515271, -0.825733  ,  0.57505304, -0.5896497 ,
       -0.62415594,  0.65564716,  0.77549165,  0.5979737 , -0.34759617,
        0.8371996 , -0.8968471 ,  0.35372636,  0.6391649 , -1.1272577 ,
       -0.50250536,  0.6972464 , -0.4852022 , -0.39029664, -0.99197155,
       -0.9322767 ,  0.75857127,  0.11824672, -0.30152106, -0.47665182,
        0.05731743,  0.47335744, -0.8601845 , -1.1221082 , -0.553463  ,
        0.7492691 ,  0.48702145, -0.57730544,  0.7852776 , -0.73336935,
       -0.654205  , -0.2891409 ,  1.0882758 , -0.4862104 , -0.80351007,
       -0.24870022,  1.1406009 ,  0.9293319 ,  1.2246966 ,  0.4481591 ,
        0.39125606, -0.34251943, -0.16945966,  0.433673  , -0.254374  ,
        1.1425784 ,  0.9608785 , -0.7099359 ,  1.2608658 , -0.509084  ,
        0.7691241 ,  0.8775493 , -0.6453689 , -1.0675663 , -0.6920268 ,
        1.3154569 ,  1.1946156 , -0.64159113,  0.98287815, -0.8673283 ,
       -1.0195044 , -0.3273642 ,  0.5046853 , -0.2888344 , -0.6929654 ,
       -1.0738688 , -0.2121083 , -1.0726655 ,  0.77955186, -0.11011925,
       -0.73778874,  0.6405757 , -0.8592298 , -0.6983795 , -1.0865598 ,
        1.3599602 ,  0.95134854,  0.4374502 , -0.549473  , -0.5444528 ,
        0.38956478, -0.64569235], dtype=float32), array([ 3.6075482 ,  3.4404552 ,  3.4157102 ,  4.9109406 ,  9.620749  ,
        6.559591  ,  6.962841  ,  3.662303  ,  6.6180463 ,  3.237454  ,
        4.8675323 ,  6.6494617 ,  2.4592733 ,  2.9398758 , 16.444418  ,
        5.5949626 ,  7.39866   ,  8.015248  ,  2.7988918 ,  0.913906  ,
        7.897115  ,  7.342172  ,  3.2361882 ,  5.4494424 ,  3.4062123 ,
        2.1939018 , 11.43984   , 11.763018  ,  7.841913  ,  6.9611487 ,
        5.542225  , 10.00055   , 15.856428  ,  3.492999  ,  3.5535038 ,
        6.0742393 ,  0.97790056,  7.2792535 ,  2.3098981 ,  4.500312  ,
        5.2881813 ,  6.663225  , 12.801286  ,  2.3619106 ,  2.204838  ,
       12.278487  , 13.316753  ,  4.186451  ,  5.8040576 ,  0.8598803 ,
        3.3473067 , 13.728182  ,  4.8278213 ,  2.6880827 ,  1.7572237 ,
        1.7582784 ,  5.8537126 ,  7.5980577 ,  2.2131124 ,  5.6475816 ,
        7.5066757 ,  3.3734982 ,  7.8976126 , 10.478911  ,  1.9605992 ,
       14.945909  , 10.229846  ,  1.2594427 ,  2.1459968 ,  4.680596  ,
        4.784196  ,  7.553182  ,  2.3361726 ,  5.1213384 ,  1.1773711 ,
        3.8430994 ,  7.6425138 ,  2.655552  ,  7.6777816 , 11.196324  ,
        5.8407335 ,  7.4637365 ,  8.827266  , 12.059786  ,  9.071552  ,
        7.859817  , 21.779305  , 14.701503  ,  6.8112893 ,  2.2477896 ,
        8.635616  ,  5.200297  , 21.809341  ,  3.4633203 , 12.792087  ,
        4.880591  , 13.368743  ,  7.0872545 ,  2.264017  ,  2.226781  ,
        6.662401  ,  2.7802784 ,  3.1296625 ,  8.839515  ,  4.024947  ,
        7.846051  ,  3.3360252 ,  5.7019606 ,  5.2680616 ,  5.006499  ,
        9.084489  ,  4.424135  ,  7.32881   ,  3.2827682 ,  3.0766258 ,
        9.222067  ,  3.0250192 ,  4.6701164 ,  1.3444332 , 12.386536  ,
        1.8732127 ,  8.873535  ,  6.4315414 ,  1.9847293 , 10.462475  ,
        5.956185  ,  9.757832  ,  2.3063593 ,  1.6936487 ,  3.469812  ,
        1.8883642 ,  5.4032965 , 10.099358  ,  6.447399  ,  2.566586  ,
        3.7045631 ,  5.391026  ,  6.757516  ,  9.153539  ,  8.285026  ,
        3.808806  ,  3.9762013 ,  9.603727  ,  2.5618737 ,  4.044181  ,
        3.300674  , 12.224139  ,  8.915807  ,  9.447445  ,  3.5916896 ,
        4.145391  ,  3.5290601 ,  2.3681195 ,  7.00257   ,  2.3332393 ,
        5.8166275 ,  8.560464  ,  1.9191382 , 25.26868   ,  2.8735337 ,
        3.5799382 , 10.06844   ,  8.763013  ,  8.850487  ,  4.3054    ,
       10.503579  , 12.430265  ,  3.586187  ,  8.516468  ,  6.9553766 ,
        6.401711  ,  3.3971498 ,  3.30195   ,  2.2658465 ,  6.602167  ,
       10.200434  ,  2.153385  ,  9.969253  ,  9.069695  ,  1.6039231 ,
        6.2125936 ,  7.3037233 ,  3.424253  , 10.359662  ,  8.319307  ,
       15.643791  , 10.941124  ,  0.6254721 ,  4.838707  ,  4.500864  ,
        4.130183  ,  1.7293273 ], dtype=float32), array([[[[ 0.0360008 ,  0.01566671, -0.02501954, ..., -0.02526091,
          -0.00026934, -0.00770059],
         [-0.02444349, -0.00077437,  0.0202065 , ...,  0.01193261,
          -0.00092864,  0.02267371],
         [-0.01897554,  0.02601615, -0.00974841, ..., -0.02481534,
          -0.02521787, -0.00141522],
         ...,
         [-0.02567659,  0.01275802, -0.00208236, ...,  0.00230945,
          -0.00336902, -0.00101249],
         [-0.00196327,  0.03993773, -0.00887274, ..., -0.02846945,
          -0.00416414,  0.03086107],
         [-0.00631825, -0.00187995,  0.00696877, ...,  0.00155751,
           0.00822588,  0.01552334]],

        [[-0.00819772,  0.01290939, -0.02046452, ..., -0.0157328 ,
          -0.01164524, -0.00812923],
         [-0.00732888, -0.00330872,  0.00484468, ...,  0.02087587,
           0.01774122, -0.01592349],
         [-0.03896129,  0.01229057,  0.01477017, ...,  0.00208894,
           0.01282581, -0.01436726],
         ...,
         [ 0.03770582, -0.00291525, -0.01754985, ..., -0.00560357,
          -0.0176697 ,  0.04126733],
         [ 0.01689639, -0.01218349,  0.00640171, ..., -0.02400143,
          -0.00712142,  0.00718819],
         [-0.01447625, -0.01829592,  0.02016362, ...,  0.01047182,
          -0.00029197,  0.03844392]],

        [[-0.01513036,  0.00795789, -0.02064116, ..., -0.04361385,
          -0.02955467,  0.02496475],
         [ 0.0121811 , -0.00686133,  0.00557557, ...,  0.00027394,
           0.02240308,  0.03137237],
         [-0.0169848 , -0.030239  ,  0.0310568 , ..., -0.02307811,
           0.00706098, -0.03443538],
         ...,
         [ 0.02786858,  0.00143266,  0.02699488, ...,  0.02069739,
          -0.00892335,  0.01108994],
         [ 0.01188293,  0.01769345, -0.0220714 , ..., -0.04115178,
           0.00913552, -0.02180177],
         [ 0.03460388, -0.0248307 , -0.0216839 , ..., -0.02022293,
          -0.00937843,  0.03955654]]],


       [[[ 0.02538441,  0.03153088, -0.00748662, ...,  0.01030681,
          -0.01330886,  0.02565955],
         [ 0.0127791 , -0.00880918,  0.02790751, ..., -0.03930067,
          -0.03823067, -0.00848685],
         [-0.02470432, -0.02680879,  0.02735948, ..., -0.00311583,
           0.0377546 , -0.01587681],
         ...,
         [ 0.02439119,  0.03151413,  0.00670366, ..., -0.02922449,
           0.02595851, -0.01951315],
         [-0.03160032,  0.0321453 ,  0.01544156, ...,  0.02998978,
          -0.0084536 ,  0.03016217],
         [-0.01660467, -0.03185921,  0.0230779 , ..., -0.00179753,
          -0.02316977, -0.0020897 ]],

        [[ 0.00381451,  0.01288321,  0.00287759, ..., -0.01875838,
           0.01540874, -0.03205353],
         [ 0.03187235, -0.00902156,  0.03205918, ..., -0.01239969,
           0.01198029,  0.00169754],
         [ 0.00608563,  0.00888858,  0.01840868, ..., -0.00650978,
           0.02686887,  0.02831686],
         ...,
         [ 0.02646774,  0.03282149,  0.03018484, ..., -0.02893285,
          -0.00490493,  0.00450121],
         [ 0.0313485 , -0.02043946, -0.01233994, ..., -0.04434567,
           0.02851379,  0.01350999],
         [-0.03361894,  0.02024265, -0.0110229 , ..., -0.04079752,
          -0.01950608,  0.01613849]],

        [[ 0.02358387,  0.00371258, -0.02805435, ...,  0.00406688,
          -0.03713881, -0.02790269],
         [-0.00238218,  0.0264168 ,  0.00576173, ..., -0.02958415,
          -0.01939671, -0.03379133],
         [-0.04112437, -0.01270188,  0.02746305, ..., -0.0025673 ,
           0.03235927,  0.04462398],
         ...,
         [-0.03267832, -0.00043565, -0.03243183, ...,  0.02273315,
          -0.00811999,  0.01875142],
         [-0.01609567, -0.00213018, -0.0028294 , ..., -0.02402789,
           0.02537884, -0.02150395],
         [-0.02834055,  0.01535149, -0.02113711, ...,  0.00027219,
          -0.03776542,  0.02856752]]],


       [[[ 0.0314521 , -0.0325276 ,  0.02166082, ..., -0.00429218,
           0.02145082, -0.02481809],
         [-0.01825021,  0.0153574 , -0.00595352, ...,  0.01199144,
          -0.03187772,  0.00100971],
         [-0.02101739, -0.0142935 , -0.02592121, ...,  0.03279372,
           0.01983905, -0.01995132],
         ...,
         [ 0.01505881,  0.02042679,  0.01770032, ..., -0.01220737,
           0.02707845, -0.01187056],
         [-0.00378828, -0.00230209, -0.02216963, ..., -0.03575794,
          -0.03415357, -0.01486587],
         [-0.02961469, -0.01430405, -0.02251578, ..., -0.02771153,
          -0.00642661, -0.0174149 ]],

        [[ 0.01614982, -0.02189526,  0.00033387, ..., -0.02651972,
           0.02877639,  0.0047652 ],
         [-0.02036716, -0.01870509,  0.04479039, ..., -0.03444207,
          -0.00142294,  0.02627221],
         [-0.02881597,  0.0286755 , -0.01491458, ...,  0.03555592,
          -0.01634645,  0.02585013],
         ...,
         [-0.00573841,  0.01188041,  0.00806271, ...,  0.02791631,
          -0.01698967,  0.02788179],
         [-0.02834394,  0.0253641 ,  0.04669917, ...,  0.02975545,
          -0.03683385, -0.01140218],
         [ 0.02805598,  0.01215193, -0.00466183, ..., -0.02997497,
          -0.00747421, -0.01718231]],

        [[-0.00631242,  0.02469712, -0.00818245, ..., -0.0166257 ,
           0.00450137,  0.02510882],
         [ 0.00774079, -0.03743284,  0.03185598, ...,  0.00525071,
          -0.01525636, -0.02218057],
         [ 0.01407237, -0.02466211, -0.02268023, ...,  0.00564687,
           0.00580623, -0.00824168],
         ...,
         [-0.03714641, -0.00952147, -0.00365655, ..., -0.02145306,
           0.03270931, -0.00491229],
         [-0.01423896,  0.02118388, -0.00117706, ..., -0.03763653,
          -0.02393121, -0.0090028 ],
         [ 0.0036166 , -0.03646457, -0.00188424, ..., -0.0271816 ,
          -0.02736086,  0.02761261]]]], dtype=float32), array([[[[ 3.90086360e-02,  1.91941187e-02, -3.14811282e-02, ...,
          -1.82120465e-02, -2.90847272e-02, -4.00591902e-02],
         [-2.24638823e-02, -2.18579862e-02,  1.93156675e-02, ...,
          -3.38659175e-02, -1.01216026e-02, -1.43759297e-02],
         [-4.76992689e-03,  1.23978462e-02, -2.04921514e-02, ...,
           1.58624947e-02, -2.18638387e-02,  4.14207056e-02],
         ...,
         [-3.59930471e-03, -2.85225771e-02,  8.67437292e-03, ...,
          -6.64265687e-03,  1.24004232e-02, -8.38220213e-03],
         [-4.09797989e-02,  2.55346112e-02,  3.24591212e-02, ...,
          -3.47884111e-02, -2.66108960e-02, -2.81122867e-02],
         [-3.27177346e-02, -1.05365254e-02, -2.72260252e-02, ...,
          -3.69964205e-02,  6.22900948e-03,  4.49914392e-03]],

        [[-2.96267606e-02,  4.41444777e-02, -3.08397803e-02, ...,
          -2.51668934e-02, -1.68694854e-02, -7.50133675e-03],
         [-2.51625013e-02, -1.43012768e-02,  2.61119138e-02, ...,
          -4.13865149e-02, -4.55334375e-04,  2.90455893e-02],
         [-2.36213356e-02,  1.64006166e-02,  1.57210752e-02, ...,
          -5.67460293e-03,  1.64369419e-02,  2.45024860e-02],
         ...,
         [-6.00088621e-03,  6.35165721e-03,  4.08234522e-02, ...,
          -3.23255658e-02, -9.78720025e-04, -2.88403109e-02],
         [ 2.93687992e-02, -3.03956736e-02,  4.44569672e-03, ...,
          -1.16216997e-03,  1.90024786e-02, -5.80024673e-03],
         [-1.97586399e-02,  7.97485292e-04,  2.35388111e-02, ...,
          -2.65257210e-02,  1.07351365e-03,  3.77670713e-02]],

        [[ 2.96761468e-03, -1.85155999e-02, -3.72335613e-02, ...,
           2.54606958e-02, -3.75026502e-02,  2.03600060e-02],
         [ 3.11995950e-03,  9.51136183e-03,  3.48465368e-02, ...,
          -2.97513902e-02,  4.79649520e-03,  3.50494459e-02],
         [-1.57108288e-02, -3.46495211e-02, -2.89625619e-02, ...,
           2.43827105e-02,  3.40197934e-03,  3.76217403e-02],
         ...,
         [-3.28609906e-02, -3.06447335e-02, -1.91784650e-02, ...,
          -6.20900840e-03, -1.01037230e-02,  1.28012216e-02],
         [ 1.32235391e-02, -1.86199788e-02,  3.21349055e-02, ...,
           2.47859359e-02,  1.11173661e-02,  9.98413563e-03],
         [-1.95983797e-02, -2.10078210e-02,  2.92714350e-02, ...,
           2.58659888e-02, -1.65927187e-02,  2.59890202e-02]]],


       [[[-1.57261156e-02, -2.32218839e-02, -4.70605306e-02, ...,
          -1.36852544e-02,  4.42042202e-02, -3.45227607e-02],
         [ 1.28083993e-02,  1.70890559e-02, -1.08794477e-02, ...,
           1.21498033e-02, -2.09048912e-02,  3.38478126e-02],
         [ 1.92231275e-02, -2.84367707e-02,  2.09423490e-02, ...,
          -7.93281011e-03,  6.25215191e-03,  5.47695486e-03],
         ...,
         [ 7.49716396e-03, -1.47205088e-02,  2.82518740e-04, ...,
           1.13797020e-02,  2.68306304e-03, -1.70288347e-02],
         [-4.51026298e-02, -1.28046703e-03, -4.55378070e-02, ...,
           2.02545449e-02,  1.03800083e-02, -4.66892496e-03],
         [ 1.99733768e-03,  1.07593564e-02,  3.80217156e-04, ...,
          -1.77919026e-02,  4.42558248e-03,  2.06096955e-02]],

        [[-3.03373914e-02, -1.49291530e-02,  7.88817089e-03, ...,
           5.06987516e-03,  3.35518681e-02,  2.20769122e-02],
         [ 3.34866233e-02, -2.58907285e-02,  3.25910896e-02, ...,
           1.65406354e-02,  6.66584680e-03, -3.59837823e-02],
         [ 1.88568905e-02, -3.43031250e-02,  1.31096244e-02, ...,
          -1.49699803e-02, -1.97122004e-02, -1.97193539e-03],
         ...,
         [-2.25941092e-02, -4.56205569e-02,  2.27078293e-02, ...,
           2.53747683e-03, -8.80160276e-03,  3.29505466e-02],
         [-1.57912839e-02,  3.38966548e-02, -2.78148390e-02, ...,
           4.23777364e-02,  4.37812619e-02,  3.31506645e-03],
         [-5.86284697e-03,  2.54331268e-02,  2.10178569e-02, ...,
          -1.19395286e-03, -9.68863629e-03, -8.01607128e-03]],

        [[-2.59302892e-02,  3.73213701e-02,  3.08317374e-02, ...,
          -2.35894453e-02,  3.31787765e-02,  3.31770852e-02],
         [-3.49894650e-02, -1.53253153e-02, -3.08507923e-02, ...,
           3.77503820e-02,  4.74783480e-02, -3.56248318e-04],
         [-1.29546896e-02,  2.65245000e-03,  3.32928151e-02, ...,
           1.52143883e-02,  7.45228666e-04, -2.58002300e-02],
         ...,
         [ 1.54962996e-02, -2.91228052e-02,  1.89378788e-03, ...,
          -3.35744135e-02,  3.78563069e-02, -2.39893124e-02],
         [-4.67612557e-02, -2.56730542e-02, -1.42030837e-02, ...,
          -3.86034139e-03, -4.02141400e-02, -2.64256913e-03],
         [-2.86272187e-02,  2.09874604e-02, -4.76568826e-02, ...,
           3.53719770e-05, -1.67115871e-02, -2.94951759e-02]]],


       [[[ 1.07643744e-02, -1.62182488e-02,  3.05374097e-02, ...,
          -4.36392166e-02,  3.01025435e-02, -1.29069872e-02],
         [-2.57700551e-02, -3.92716356e-05, -1.12151774e-03, ...,
          -2.03520022e-02, -3.42946872e-02,  1.69568025e-02],
         [-3.23759168e-02,  3.67239378e-02, -3.66485454e-02, ...,
           2.60497853e-02,  1.05423955e-02, -2.42512990e-02],
         ...,
         [-3.55765857e-02,  8.87258444e-03, -1.32356323e-02, ...,
          -4.62655649e-02, -2.98796277e-02,  4.35491987e-02],
         [ 4.20489814e-03, -4.00392078e-02,  5.67423832e-03, ...,
          -2.00371374e-03, -1.02842888e-02,  1.55625381e-02],
         [-4.27807085e-02,  8.25392734e-03, -3.42126377e-02, ...,
           2.69634277e-02,  1.54876933e-02,  1.63402427e-02]],

        [[ 2.67673526e-02,  2.87109427e-02,  2.83242520e-02, ...,
           3.31559628e-02, -1.52293798e-02, -1.94053743e-02],
         [-4.40283194e-02, -1.68076549e-02, -1.36651164e-02, ...,
           2.55679395e-02, -2.15193927e-02,  2.29717623e-02],
         [ 6.79674966e-04, -4.28074859e-02, -2.97676008e-02, ...,
          -1.33055886e-02, -2.52746104e-04, -3.55386315e-03],
         ...,
         [-3.62447649e-02, -2.78102383e-02,  4.80083227e-02, ...,
          -1.22589516e-02,  2.40287706e-02,  2.01429054e-02],
         [ 4.02550260e-03,  1.82117932e-02,  2.32581492e-03, ...,
           9.21941083e-03, -3.78680155e-02,  4.47689882e-03],
         [-3.16460803e-03,  2.31724549e-02, -2.14055497e-02, ...,
          -1.18001522e-02,  8.48053303e-03,  1.77069623e-02]],

        [[ 2.22471682e-03,  2.09153332e-02, -2.37530880e-02, ...,
          -4.53208722e-02,  3.75220589e-02,  4.51960526e-02],
         [ 1.25777966e-03,  1.38305780e-02, -6.24063937e-03, ...,
           3.31415012e-02,  1.52459498e-02, -2.39203647e-02],
         [-1.91148929e-02, -5.01721166e-03,  1.45274983e-03, ...,
           2.71967798e-02,  1.14987539e-02, -2.03647651e-02],
         ...,
         [-2.06826050e-02,  2.82284431e-02,  4.13896237e-03, ...,
          -3.77745889e-02,  1.40492921e-05, -3.16805914e-02],
         [ 2.22930890e-02,  1.23230787e-02, -5.41417813e-03, ...,
           2.20754109e-02,  1.79437976e-02,  2.34702174e-02],
         [ 2.08845828e-03, -1.24976588e-02, -3.79215670e-03, ...,
           3.26160900e-02, -3.75078879e-02,  8.80977139e-03]]]],
      dtype=float32), array([-2.37475178e-04, -5.57600334e-03, -2.68064323e-03,  4.84495936e-03,
       -5.71540464e-03,  1.18460245e-02, -4.90938593e-03,  1.84685376e-03,
       -1.64444912e-02, -1.25313951e-02, -7.49321980e-03, -2.75602564e-03,
        8.98150727e-03,  1.02742845e-02,  3.89258354e-03, -3.39252618e-03,
       -2.93340185e-03,  7.37641519e-03, -6.26789755e-04, -4.92285891e-03,
        9.62699577e-03, -6.61439635e-03,  4.96744830e-03,  1.65977981e-04,
       -1.50228431e-02, -1.59800593e-02, -1.88459162e-04, -4.43707779e-03,
       -3.35250748e-03, -3.51238507e-03, -2.27594795e-03, -1.05447456e-04,
        6.14922727e-03, -6.05533505e-03, -6.71077578e-04, -1.83895342e-02,
        2.81670327e-05, -1.35587770e-02, -1.30870212e-02, -4.29567741e-03,
       -1.49777737e-02, -6.12367922e-03,  7.10778963e-03,  1.10252593e-02,
       -3.28403525e-03,  5.20730205e-03, -1.01441087e-03, -1.15581946e-02,
        1.20846480e-02,  2.74934620e-03,  4.28207591e-03,  1.44298095e-02,
       -1.63100306e-02,  1.60550624e-02, -1.47216124e-02, -1.22389349e-03,
       -5.50916884e-03,  6.59939926e-03, -1.56340059e-02, -4.78015339e-04,
        5.29822800e-03, -5.59504097e-03, -1.12173250e-02, -6.46372093e-03,
       -9.12857335e-03, -2.66198255e-02, -4.69342293e-03,  1.63551010e-02,
        1.08977770e-02, -2.79500987e-02,  1.46446722e-02, -6.01976132e-03,
        2.92381388e-03, -1.53462933e-02, -1.15185454e-02, -5.91588300e-03,
       -1.56480353e-02, -1.33902160e-02, -6.94183540e-03, -6.07236149e-03,
        1.02928337e-02,  7.24627695e-04, -2.07075296e-04,  8.39417335e-03,
       -2.70155314e-02,  2.55786139e-03, -1.33285969e-02, -1.47567620e-03,
        7.25546479e-03, -7.88023695e-03, -2.10806634e-02,  4.33669612e-03,
        7.03868829e-03,  4.12080763e-03, -4.09575924e-03,  2.01954576e-03,
       -5.57785807e-03, -1.67765247e-03, -2.62026396e-02, -1.27843944e-02,
        8.95675551e-03, -1.18720746e-02,  2.66784756e-03,  6.14089426e-04,
       -1.16990916e-02, -9.12649743e-03,  2.83613335e-03, -2.08645277e-02,
       -1.75215746e-03,  8.88031442e-03,  3.62440664e-03,  1.71753820e-02,
       -1.25854770e-02, -9.76091903e-03, -9.07887612e-03, -3.92039027e-03,
        2.20846338e-03, -2.91756401e-03, -1.26882400e-02, -6.35831663e-03,
       -3.79947713e-03, -1.50285354e-02,  3.14114708e-03, -8.71173851e-03,
        2.61536986e-03,  1.26953302e-02, -2.02750526e-02,  1.19640045e-02,
        4.00089612e-03, -3.00557422e-03,  1.96930370e-03, -1.94319878e-02,
       -1.31975496e-02, -9.40790772e-03, -2.06236076e-02, -1.69312172e-02,
        1.40760355e-02,  3.51282564e-04, -1.46576175e-02, -2.75808759e-03,
       -1.51228700e-02, -1.14225317e-02,  1.00678345e-02, -1.21240206e-02,
       -1.55057609e-02, -1.63637828e-02, -5.60946949e-03, -1.91672414e-03,
        6.74276799e-03,  1.11617576e-02,  1.05432803e-02, -1.95350032e-02,
       -9.81265679e-03, -6.12329924e-03,  7.55236810e-03, -1.77795850e-02,
       -2.00997423e-02, -1.18673814e-03,  8.40390101e-03,  8.58528726e-03,
        2.30246037e-03,  2.92912358e-03,  3.92479077e-03, -3.56749399e-03,
        1.35024795e-02,  2.43661620e-04,  2.45902920e-04, -9.31446149e-04,
        1.74371693e-02,  1.26663540e-02, -1.63199229e-03, -7.81685673e-03,
       -3.28973285e-03, -1.27710318e-02,  1.38491988e-02, -1.10058067e-02,
       -3.60494945e-03,  1.17221251e-02, -1.44831566e-02, -7.06219627e-03,
        9.40114725e-03,  5.17499540e-03, -3.56311956e-03, -1.24373892e-02,
       -7.79055525e-03,  1.01501504e-02, -5.68608241e-03, -9.56015289e-03,
       -5.28967427e-03,  2.57425592e-03,  2.69705197e-05, -8.36629793e-03,
       -1.49803124e-02,  2.08387757e-03,  6.40402641e-03, -2.13223919e-02,
        1.03260437e-02, -1.02239409e-02, -1.05985412e-02, -1.01899086e-02,
        1.32159507e-02, -1.54326232e-02,  4.92219534e-03, -5.58603927e-03,
       -1.12728309e-02, -6.22157287e-03, -1.54847801e-02,  1.58165749e-02,
       -9.63223516e-04,  9.10144765e-03,  7.46142643e-04,  1.12703480e-02,
        1.10710645e-02,  9.83176433e-05,  6.35195989e-03, -8.65391828e-03,
       -5.68941562e-03, -1.08097782e-02,  9.93693131e-04, -6.55467762e-03,
       -2.25990405e-03, -2.18611863e-03,  1.16543826e-02, -2.73075905e-02,
       -1.61316320e-02,  6.91052619e-03, -5.21429302e-03,  6.92976452e-03,
       -2.97464919e-03,  5.22060553e-04, -9.42583382e-03, -2.61237589e-03,
       -4.27351380e-03,  2.23962241e-03,  5.47452783e-03, -2.33097319e-02,
       -1.64571051e-02, -2.22269129e-02, -1.61190126e-02, -2.82569299e-03,
       -4.07302054e-03, -9.99295618e-03, -1.61751583e-02,  1.37867741e-02,
       -4.48506372e-03, -2.51892465e-03,  2.20464822e-03,  1.04638580e-02,
       -1.39666554e-02,  1.05843060e-02, -1.24610858e-02,  7.05883512e-03,
       -1.08076399e-02,  9.64433048e-03, -5.51076094e-03, -1.98233016e-02,
       -3.11769731e-03, -8.14901572e-03, -3.23969945e-02,  1.36513822e-03,
       -4.09057923e-03, -7.21127307e-03, -2.50869263e-02, -3.22728371e-03,
        2.70311907e-03, -1.02171004e-02, -1.34288194e-02, -2.40112306e-03,
       -1.51445242e-02,  4.22865705e-04, -6.35773735e-03,  1.30162677e-02,
       -1.44690508e-02,  4.96938033e-03, -1.32252071e-02, -2.73038018e-02,
       -5.23508666e-03, -1.04294214e-02, -5.81095833e-03, -1.01589225e-02,
        8.47706385e-03, -1.93855092e-02, -1.62669849e-02, -2.25856481e-03,
        8.26415233e-03,  2.83849658e-03, -9.48196463e-03, -7.24499114e-03,
       -1.30150598e-02, -1.01353796e-02,  6.34767534e-03,  1.46108018e-02,
        6.50458084e-03, -2.13485062e-02,  8.97309463e-03, -1.12605086e-02,
        1.44065823e-03, -1.05800061e-03, -1.59424581e-02, -3.56221921e-03,
       -1.18105486e-02, -3.44757922e-03, -1.17128957e-02, -1.68277621e-02,
       -1.20094151e-03, -6.77779969e-03, -1.58840995e-02,  1.73786599e-02,
        1.71937246e-03, -5.54312300e-03,  1.29620573e-02, -2.58957664e-03,
       -1.35851847e-02, -1.74429081e-02, -8.25565890e-04,  5.58340410e-03,
       -1.81198213e-02,  1.13818357e-02,  1.23865744e-02,  1.30015798e-03],
      dtype=float32), array([-0.6742325 , -0.9662529 , -0.11213148,  0.4455103 , -0.78983337,
       -0.8903584 , -1.0880275 , -0.66989255,  1.444608  ,  0.62946975,
        1.2148858 , -1.2728602 , -1.2032866 ,  0.55367684, -1.8527433 ,
       -1.038516  , -0.833506  , -1.1256917 ,  0.7147933 ,  0.40868723,
       -1.393132  , -0.54465646, -1.4070972 , -0.74682695,  1.0491611 ,
        1.0436777 , -0.78143764, -0.60408545,  0.9132761 ,  0.8775155 ,
       -1.5998892 , -0.9592829 , -1.1275177 ,  0.6550951 ,  1.5426531 ,
        1.667879  , -1.0568385 ,  0.52691066,  0.8181368 ,  1.4452592 ,
        0.9771225 ,  0.14853272, -1.3880863 , -1.2823018 ,  0.42397624,
        0.70810455, -0.9455434 , -1.3979497 , -1.0099162 , -0.22961725,
        0.653069  , -1.6822621 ,  0.4348459 ,  0.1977698 ,  0.9741874 ,
        0.8929845 ,  0.96262664, -1.1732199 ,  1.4539067 ,  0.14499633,
       -0.6941977 , -0.25443023,  0.7280782 , -1.2666589 , -1.472284  ,
        1.0373914 ,  1.4869574 , -0.7287752 , -1.3100647 ,  0.7471479 ,
        0.37221798,  1.6296226 , -1.1895816 ,  1.2682644 ,  0.46115378,
        0.60859454,  1.2161632 ,  0.82656574, -0.8387762 ,  0.11178724,
       -1.4140999 , -1.410673  , -0.4488349 ,  0.44579968,  1.3075995 ,
        0.81661594, -0.16816923, -1.1222594 , -1.447247  , -0.53560364,
        0.9882981 , -1.5155985 , -1.3043593 , -1.1998651 , -1.3394636 ,
       -0.64421076, -0.56048656,  0.4025398 ,  1.0746757 , -1.1876106 ,
       -1.012045  ,  1.2034857 ,  0.5469406 , -0.88934004,  1.5336703 ,
        1.4341724 ,  1.1109834 ,  1.6008013 ,  0.57794285,  1.1123084 ,
       -0.6320305 , -1.5637912 ,  0.99935997, -1.1486754 ,  0.80998194,
       -0.80570817,  0.64349693, -0.712071  ,  1.4137647 ,  1.0428376 ,
        1.1584067 ,  1.6380689 , -1.4916996 ,  1.791253  , -0.35070512,
       -0.5774486 ,  1.2389535 , -1.1358106 , -0.8400281 , -1.4667357 ,
       -1.070194  ,  1.5114863 ,  0.53539175, -1.3091617 ,  0.5504215 ,
        1.3322723 , -1.2541647 ,  0.9665409 ,  0.9537378 , -1.0048934 ,
        1.0413463 ,  1.9539517 , -0.09272236,  0.4321412 ,  1.5662495 ,
        0.9421781 ,  1.0417736 , -1.445368  , -0.94921947, -1.2315022 ,
       -0.4113544 ,  0.98110163,  0.7894776 ,  1.0294064 , -1.2260431 ,
        0.9776614 ,  1.3869624 , -1.6344278 ,  0.10931355, -0.7024868 ,
        1.291189  , -0.601585  , -0.8617857 ,  1.2921853 , -1.4566851 ,
       -0.9175085 ,  0.8143809 , -0.61382496, -1.1996084 ,  1.2439295 ,
       -1.1785506 ,  0.43034953, -1.5379665 , -0.8460786 , -1.4116672 ,
        0.50452363, -0.53968763, -1.6924398 ,  1.0361637 , -1.2468865 ,
       -1.4059078 ,  1.0829868 , -1.2977128 ,  0.9147001 , -1.324048  ,
       -1.6527158 , -0.95606315,  1.8338286 , -0.89808977,  0.923048  ,
       -0.84176034,  0.8969741 ,  1.379889  , -1.9110459 , -1.336547  ,
        0.7866626 , -1.7822022 ,  0.31358922,  1.5870397 ,  1.2065989 ,
       -1.2269849 ,  1.0999666 , -1.2067959 , -1.5111619 ,  1.2547399 ,
       -0.9324814 ,  1.133227  , -1.19415   , -1.558645  , -1.7298927 ,
        0.7136898 , -1.3045958 , -1.1360595 ,  0.3739903 , -1.1713173 ,
        1.877259  ,  1.1760266 ,  1.0595236 , -1.3749751 , -1.4289349 ,
        1.3102722 ,  1.1755174 , -1.1269932 ,  0.90172917,  1.2825952 ,
       -1.3111175 ,  1.0420073 , -0.53522605,  1.4784763 , -1.8077351 ,
        1.052387  ,  0.8949457 ,  1.4222172 ,  0.6509582 ,  0.6013963 ,
        0.8323489 ,  1.0928869 ,  1.0863265 ,  1.4925971 ,  0.98689896,
        1.6055143 ,  0.7204856 ,  1.080994  , -1.325355  , -0.6490668 ,
        0.62393767, -1.0771934 , -0.39834395,  0.9533331 , -1.5496886 ,
        1.3733197 , -1.8965504 ,  1.2263309 , -0.9321749 , -1.4548372 ,
        1.4281219 , -1.1518166 ,  0.821127  ,  1.4935019 , -1.0793431 ,
        0.63590086,  0.72445434,  0.9269197 ,  0.988558  ,  0.6753833 ,
        1.7286992 ,  1.4686261 , -0.01535758,  0.7014275 ,  1.1904535 ,
        0.9584252 , -1.1032389 ,  1.380353  ,  0.97814584,  0.9844469 ,
        0.8244102 ,  0.5058826 , -0.7810635 ,  1.0819525 ,  0.9790051 ,
       -1.7337935 ,  1.3163812 ,  0.8185831 ,  1.1802416 , -1.8080457 ,
       -1.2042043 ,  0.55431134,  0.7395369 ,  1.4245576 ,  1.2021847 ,
       -1.2584723 , -0.4856335 , -0.8916852 ,  1.621372  , -0.541978  ,
        1.0439235 , -1.1413194 , -0.3768476 ,  0.7029654 ,  0.48876575,
        0.26623237,  0.71438557,  0.16251588,  0.51743156,  0.525814  ,
        0.68899757,  1.4148602 , -1.6496902 , -1.2595328 ,  1.3520333 ,
       -1.0335628 , -0.9068055 ,  1.3944098 ,  1.0973234 ,  1.2141268 ,
       -1.5017174 ,  1.4636312 , -1.3311839 , -1.6328495 ,  0.92616326],
      dtype=float32), array([12.66631  ,  3.2974522,  2.7616463,  3.550169 ,  3.8987901,
        5.19692  ,  3.720451 ,  2.2123282, 19.041595 ,  4.418898 ,
        7.6388035,  7.448545 ,  6.8130374, 12.604743 ,  8.385412 ,
       14.017505 ,  2.8860857,  5.269323 , 14.033416 ,  3.1667948,
        7.457573 ,  6.2265778,  9.578787 ,  8.958105 , 14.756582 ,
       18.599855 ,  6.029069 ,  4.4968414,  4.553043 ,  3.8841047,
       11.47342  ,  7.269282 ,  4.368723 , 11.478196 , 24.26266  ,
       16.349241 ,  7.5036826,  9.554687 ,  3.3251033,  8.130784 ,
       17.009981 ,  7.1634   ,  8.72498  ,  9.799192 ,  2.0671737,
       10.026696 ,  6.6771874,  6.6510496,  3.5562186,  4.1153727,
        2.7617373, 12.669464 , 20.77849  , 28.810244 , 10.754308 ,
        6.017913 , 16.694872 ,  8.183851 , 19.74659  ,  3.4224844,
        3.5549052,  1.5417757, 14.851826 ,  9.019558 ,  5.9197707,
       18.877455 , 21.455076 ,  5.6341443,  8.79554  , 14.869007 ,
        9.27338  , 18.851904 , 11.074272 , 20.390102 ,  7.578138 ,
        3.7024758, 15.0573845, 10.826689 , 11.854617 ,  1.810821 ,
       12.362051 , 11.336098 ,  1.5338795,  1.484192 , 22.25115  ,
        7.3864355,  2.1810627,  6.752011 ,  8.484214 ,  2.7811048,
       19.816833 ,  6.659527 ,  9.262623 , 11.73018  , 12.733192 ,
        3.2870927,  4.1119504,  5.357687 , 19.0467   , 11.47659  ,
       11.976801 , 18.402796 ,  2.6358352,  6.2836804, 15.503788 ,
       12.857166 ,  4.717169 , 20.907345 , 13.119375 ,  4.2084327,
        4.5396132,  4.834227 ,  5.1845407,  4.8916698,  9.421315 ,
        6.569352 ,  2.6078734,  6.506743 , 18.81661  , 15.568218 ,
        9.753577 , 26.670258 , 10.225756 , 29.02304  ,  3.1817987,
        2.0668275, 17.42215  ,  7.5438333,  6.216331 , 12.273853 ,
        7.156477 , 12.556322 ,  2.6190534,  9.95655  , 15.65603  ,
       25.242826 ,  9.623591 , 17.717997 , 15.412596 ,  7.358951 ,
       12.089217 , 28.396065 ,  4.962627 , 10.519365 , 13.928069 ,
       16.754894 , 16.817604 ,  9.7665825,  6.116043 ,  8.148961 ,
        3.2721505, 15.653657 ,  6.5777073, 10.384306 , 11.401212 ,
       10.156761 , 21.922724 , 11.626448 ,  6.6154704,  6.851235 ,
       21.970041 ,  3.200564 ,  5.5704293,  9.80999  ,  6.7089033,
        4.9076347,  2.100416 ,  3.5055046, 12.025906 ,  6.88268  ,
        5.176489 , 14.463163 , 13.274991 ,  3.4910676, 10.617329 ,
        1.4985999,  2.4726434, 14.343514 , 19.222956 ,  8.337947 ,
       10.477588 ,  5.060135 ,  9.161679 , 20.494133 , 10.562868 ,
       12.246748 ,  2.1035316, 17.34929  ,  6.076945 ,  7.163137 ,
        4.6344914, 13.911507 , 25.255814 , 12.6552105, 11.488923 ,
       22.397516 , 16.488773 ,  1.6912378, 14.050651 ,  7.233959 ,
        4.5714283, 11.100071 , 13.625419 ,  8.850432 , 16.928633 ,
        6.1411233, 11.127954 ,  9.656833 , 11.714097 , 15.74144  ,
        6.0662136, 14.5505495,  9.340751 ,  4.264991 ,  7.4307904,
       25.857252 ,  9.80457  , 17.673016 ,  6.7573667, 14.410948 ,
       15.942132 , 21.023039 ,  2.788429 , 17.959385 , 27.412657 ,
       11.903645 , 16.279959 ,  2.5532866, 13.000592 , 15.805355 ,
       14.446517 ,  5.061789 , 21.890293 ,  7.0367537,  6.569188 ,
       19.54413  , 19.166239 , 19.083723 , 13.18168  , 20.142187 ,
       20.410736 ,  5.9243193, 15.622566 , 12.452739 ,  4.389651 ,
        3.027387 ,  6.13197  ,  2.5177925, 21.52228  , 17.859484 ,
       27.032871 , 13.554727 , 14.87308  ,  3.7457528, 10.208803 ,
       10.901618 ,  8.357643 ,  8.094384 , 31.19807  , 13.589311 ,
        3.3626907,  8.171186 , 22.955526 , 10.569383 ,  4.41487  ,
       27.458889 , 11.7624   ,  5.1996465, 10.472597 ,  7.6534796,
       10.8706455,  9.262664 , 20.218977 ,  7.6138096, 15.567209 ,
       21.780365 ,  7.70448  ,  5.919112 , 10.591332 ,  9.506127 ,
       12.362795 , 15.209901 , 16.808338 , 13.772575 , 15.374186 ,
       13.043778 ,  7.341674 ,  3.7345197, 22.053246 , 12.314366 ,
        9.158684 ,  3.3824487,  2.7557766, 18.959389 ,  4.783246 ,
       16.479652 ,  6.145514 ,  3.7252645, 15.727801 , 12.53418  ,
       13.8700905,  6.8591037,  2.5740716,  9.1238   ,  5.252824 ,
        6.0468593, 25.909334 , 18.921862 ,  6.739116 , 18.202456 ,
        4.7974963,  4.129268 , 17.374048 , 14.536402 ,  2.2457204,
       11.125588 , 18.818335 ,  7.4698405, 10.558653 ,  9.631196 ],
      dtype=float32), array([ 1.13988565e-02,  4.11194330e-03,  2.30889418e-03,  6.37685880e-03,
       -4.05885605e-03, -2.11503431e-02,  4.75143635e-04, -2.01089121e-02,
        1.49863295e-03,  1.81312300e-03, -1.43035606e-03,  2.05149725e-02,
        3.60597693e-03, -7.37846270e-03, -5.81036904e-04, -8.74529406e-03,
       -1.19173038e-03, -1.38673084e-02, -8.91740620e-03, -2.49699634e-02,
       -9.74199083e-03,  7.36773573e-03,  3.41552822e-03, -8.38531088e-03,
       -2.10059853e-03,  5.19844331e-03, -6.44471147e-04, -2.28297412e-02,
        1.90711347e-03, -1.41606759e-02,  1.06071485e-02, -6.69625401e-03,
        2.65806704e-03,  9.73234477e-04, -2.55250768e-03, -1.81378946e-02,
        3.78058013e-03, -9.53075569e-03, -1.16884224e-02,  5.19027002e-04,
       -8.85830168e-03, -5.00104530e-03, -1.67756854e-03, -1.26437377e-02,
        8.49570613e-03,  4.17694775e-03, -6.23319810e-03,  3.10094468e-03,
       -3.88977211e-03, -1.17162429e-02, -6.54605730e-03,  1.50402319e-02,
        5.72758168e-03, -1.13061490e-03, -9.12274607e-03, -3.63507704e-03,
       -3.85662005e-03,  1.54567566e-02, -8.16666149e-03, -1.46630118e-02,
       -5.18461876e-03, -1.36489756e-02,  4.68679797e-03,  1.81401090e-03,
        5.34811709e-03,  2.03185785e-03, -5.10087982e-03, -1.32799512e-02,
       -9.34089068e-03,  3.43917683e-03, -3.24474834e-03,  7.75497314e-03,
       -8.68421141e-03, -1.32755395e-02, -1.40454108e-02, -8.69213138e-03,
       -1.53152794e-02, -2.64862413e-03, -1.50816422e-03,  1.13171283e-02,
        5.83248097e-04, -1.04513634e-02, -1.54052731e-02, -3.48059158e-03,
       -9.53627471e-03, -9.77336336e-03,  7.01078260e-03, -1.89651903e-02,
        4.11977107e-03,  1.88696254e-02, -1.23203192e-02, -1.72664761e-04,
       -3.83876613e-04,  8.56681634e-03, -1.02038719e-02,  8.44714232e-03,
        1.01495367e-02, -3.85436276e-03, -1.71794500e-02,  1.82074425e-03,
        2.71760020e-03, -4.87971772e-03,  6.38240576e-03,  4.87421732e-03,
        4.65541147e-03, -1.19370408e-02, -1.86366739e-03, -6.47704350e-03,
       -1.47755316e-04, -3.91221792e-03,  1.08155776e-02, -7.47487415e-04,
        1.15201641e-02, -1.00081103e-04, -4.71556181e-04, -1.37963397e-02,
       -5.39872656e-03,  3.80239543e-03,  3.28097912e-03, -7.01731211e-03,
       -1.06947562e-02,  1.14569732e-03,  1.09621538e-02,  7.19274720e-03,
        4.94703709e-04, -6.69828802e-03,  7.73332408e-03,  4.58277017e-03,
       -7.05790520e-03, -1.15807774e-02, -7.12720677e-03, -3.44240596e-03,
        8.84740520e-03, -3.91438883e-03,  1.13557922e-02,  1.15108518e-02,
       -8.84188747e-04, -3.00105917e-03,  6.97013093e-05,  5.49942895e-04,
        8.40577018e-03, -4.98111779e-03,  7.87363853e-03, -3.16469255e-03,
        1.21216988e-02, -1.22383870e-02, -5.70425997e-03, -6.87579997e-03,
       -1.48574403e-02,  8.66846368e-03, -3.39028146e-03, -8.89166072e-03,
       -7.20298570e-03,  1.28606847e-02, -1.52203944e-02, -9.67486587e-04,
       -5.52693324e-04,  7.13512709e-04, -1.32357953e-02, -1.78244971e-02,
       -1.91717427e-02, -1.17021445e-02, -2.01577339e-02, -1.87113155e-02,
        3.80244514e-04, -5.95914898e-04, -1.76958647e-03, -2.48884759e-03,
        1.13975918e-02, -1.50476480e-02, -1.04309134e-02, -1.41926692e-03,
       -1.34099852e-02,  3.05942632e-03,  9.53838986e-04, -9.49419755e-03,
       -8.20025057e-03, -1.08384136e-02,  1.58426370e-02, -3.65876453e-03,
       -1.84380915e-02, -2.44179498e-02, -9.38945636e-03,  1.73835270e-02,
        1.89809781e-03, -6.12193893e-04,  9.33393463e-03, -8.95301439e-03,
       -8.44612438e-03,  5.53288776e-03, -1.31178237e-02, -1.10755302e-02],
      dtype=float32), array([-0.90884924, -1.2152631 , -1.2450998 , -0.44261593,  1.2560347 ,
        2.015545  ,  1.462413  ,  1.771142  , -0.7907875 , -0.80583215,
        1.1774052 , -0.93062764, -0.7344196 , -0.33054295, -0.96006244,
        0.76343447,  0.49939612,  0.94235575,  0.7262644 ,  2.0307894 ,
        1.0597125 , -0.9479616 , -1.204444  ,  0.32257015, -0.4910227 ,
       -0.81611246, -0.6865715 ,  1.5371245 ,  1.8996977 ,  1.2413367 ,
       -1.2647434 ,  1.5238688 , -1.0307139 , -1.3369112 ,  1.1304963 ,
        1.7243441 , -0.65355635,  1.1614809 ,  1.7830561 , -0.655644  ,
        1.3259581 ,  1.023447  , -1.1934574 ,  1.8756716 , -1.2106204 ,
        1.1820195 ,  1.6236831 , -0.48916483,  1.724115  ,  0.87750334,
        1.2172323 , -1.1244717 , -1.1857702 , -0.98499876,  1.7095428 ,
        1.1558973 , -0.84732187, -0.575361  ,  1.9039857 ,  1.8656524 ,
        1.3340669 ,  1.6550714 ,  1.1247782 , -1.0784328 , -0.76039636,
       -0.8163623 , -0.956145  , -0.82086575,  0.9569712 ,  0.53883535,
        1.0528228 ,  0.6028999 ,  1.5500635 ,  1.7991948 ,  1.2377696 ,
       -1.2037244 ,  1.2390087 ,  1.4127786 , -0.93982875, -1.1712247 ,
        1.1389225 ,  1.1603163 , -0.9682672 ,  0.04147534, -1.1201398 ,
        1.1987134 , -1.1911916 ,  1.7461343 , -0.66745555, -1.1172014 ,
        1.2003669 ,  1.7984169 , -0.555018  , -1.0106527 , -1.2967606 ,
       -1.346593  , -0.82879895, -0.7180776 ,  1.667905  , -1.6389298 ,
       -0.19449012, -0.23819411, -0.22684407, -0.9304106 , -0.86080456,
        2.0909843 ,  0.46417174,  1.5717943 , -1.0195332 , -1.0409639 ,
       -1.049556  ,  1.1544846 , -1.359588  , -0.27494618,  0.75908256,
        1.0437248 ,  1.7076243 ,  1.4117088 ,  1.1018531 , -1.1600629 ,
        0.9412436 , -1.0900007 , -0.3793805 , -0.80455446,  1.1400511 ,
        1.088565  , -0.39286616,  0.9629033 , -0.8415915 ,  2.0522115 ,
        1.4934992 , -1.4069803 , -1.4017571 ,  1.6384212 , -0.65561527,
       -1.591178  , -0.8407201 , -0.998094  , -0.8994929 , -0.91856563,
       -1.5132372 ,  0.50231946, -1.2118082 , -1.2138746 , -0.7073524 ,
        1.3647006 , -0.42972538,  0.44292182,  2.2888217 , -1.7319995 ,
       -0.48210403, -0.74472344,  1.5002635 , -0.88594574,  1.6453203 ,
        0.55344087, -1.4957814 , -1.2676151 ,  1.6630616 ,  1.4771227 ,
        1.3265038 ,  1.5128907 ,  0.97628266,  0.9968907 , -1.174223  ,
       -0.4940299 ,  0.35864037,  1.2417306 , -0.9352354 ,  1.4459919 ,
        0.80268735,  0.3644316 ,  1.5840272 , -1.0143527 ,  1.3044444 ,
        1.0302258 ,  0.8850976 ,  1.5505912 , -0.17478655, -0.43852663,
        1.477663  ,  1.2736682 ,  1.7515855 , -1.0538584 , -1.8397439 ,
       -0.03134577, -0.66150165,  1.5378945 ,  1.4465148 , -0.8655469 ,
        1.4401083 ,  0.8183633 ], dtype=float32), array([13.863319 ,  4.764499 , 17.675875 ,  1.8235612, 14.075285 ,
       21.279322 , 15.263875 , 10.951798 , 12.032925 ,  7.7936535,
        7.0522304, 10.811713 , 10.76632  , 12.269239 , 13.853818 ,
        6.2894993, 11.348451 ,  9.244883 ,  4.8085027, 10.784558 ,
        5.584229 , 17.196163 ,  8.565458 ,  7.570953 ,  6.241231 ,
        5.6259604, 10.079501 , 10.695643 , 10.663933 , 14.244446 ,
       20.071154 ,  5.3246098,  8.132061 , 18.920368 ,  6.5341244,
       10.477249 ,  8.157992 ,  8.108482 ,  8.48819  ,  7.6114736,
       10.496888 ,  4.8638735, 11.16817  , 10.518463 ,  8.241693 ,
        6.5741806, 29.340754 , 11.936565 ,  8.572375 , 15.782585 ,
        6.975929 , 14.638122 , 16.843576 ,  8.828697 ,  9.333723 ,
        6.723647 , 17.370293 ,  4.6942654, 11.171709 , 11.335444 ,
       10.111885 , 10.531997 , 12.732386 ,  5.520977 ,  8.665705 ,
        9.461154 ,  8.137725 , 12.408762 ,  3.6805263,  4.542769 ,
        9.197145 ,  3.871737 , 11.185259 , 11.059069 , 11.692018 ,
        9.503302 , 11.353612 , 15.835073 ,  9.984533 , 14.933886 ,
        8.56818  , 11.957329 ,  7.9282827,  5.989795 , 10.278994 ,
        9.864056 , 14.635571 , 10.952595 ,  1.5831571, 13.691502 ,
        8.791877 , 11.659364 ,  9.44228  , 14.3898735,  6.350775 ,
       19.890308 , 17.691624 ,  2.8403535,  9.233548 , 16.095997 ,
        5.012512 ,  3.734144 ,  3.592331 , 12.4522085, 13.2974825,
       29.4026   ,  3.2562475, 12.967587 ,  8.9345   , 13.209098 ,
        8.403418 ,  4.141867 , 13.159273 ,  5.9204507,  6.645927 ,
        6.113107 ,  9.577354 , 10.380597 ,  8.371705 , 21.708406 ,
        4.98182  , 12.92685  ,  6.590377 , 11.787453 ,  8.73889  ,
       10.637206 ,  4.556027 ,  7.699862 ,  7.350342 , 14.479114 ,
       19.396435 ,  8.21614  , 17.543892 , 16.992348 ,  9.761602 ,
       19.354275 ,  4.1053314, 12.560914 , 11.083176 ,  9.769793 ,
       15.911247 ,  5.571083 ,  4.7587028, 12.382959 , 12.516791 ,
       14.575531 ,  7.315573 ,  5.3613405, 18.587847 , 18.086506 ,
        3.8044999,  9.725464 , 14.964759 ,  7.9015336, 18.384537 ,
        5.276825 , 21.448112 , 16.55706  , 16.02492  ,  9.769789 ,
       13.396714 ,  9.454487 ,  6.7373557,  7.1183534, 16.083864 ,
        3.7381544,  2.3860135,  6.0481462, 17.218023 , 14.312776 ,
       18.515406 ,  3.5280986, 11.020965 , 20.264948 , 11.5012045,
       11.815823 , 17.90469  , 27.72949  ,  4.974407 ,  6.3570933,
        8.932669 , 12.629311 ,  8.816869 , 14.811853 , 32.907322 ,
        1.8861187,  9.315676 ,  8.995287 , 14.494888 ,  7.5121536,
        7.6373897,  5.2217703], dtype=float32), array([[[[ 0.02605638,  0.0421881 ,  0.02663138, ...,  0.01590777,
          -0.00381269,  0.04033744],
         [-0.02164045, -0.03969108,  0.01441814, ..., -0.05475254,
          -0.06035091, -0.00127591],
         [-0.03851443,  0.00271342, -0.04632993, ...,  0.02048252,
          -0.0291086 ,  0.00104834],
         ...,
         [ 0.04876217, -0.0355972 ,  0.00759939, ..., -0.02078249,
           0.0131872 ,  0.03989229],
         [ 0.06473731, -0.04049981,  0.04605466, ..., -0.02053423,
           0.01981918, -0.00455947],
         [ 0.03214351,  0.05119714, -0.00301053, ..., -0.01813719,
          -0.04832781, -0.0096438 ]]]], dtype=float32), array([-9.74040944e-03, -1.07710185e-02, -1.06135840e-02, -9.18912236e-03,
       -1.35359960e-02, -1.65123846e-02,  1.50375217e-02,  2.12014490e-03,
       -4.52824356e-03, -1.07629886e-02,  4.58669104e-03, -5.53420791e-03,
       -3.89964879e-03, -7.39049911e-03,  8.33090581e-03,  7.23366998e-03,
       -1.49620057e-03, -1.89410476e-03,  1.73579697e-02, -7.16311997e-03,
       -2.50614015e-03,  9.82375233e-04, -1.19719496e-02, -8.28334875e-03,
       -4.84508229e-03, -2.31285533e-03, -1.41927758e-02, -1.28494352e-02,
        6.97932718e-03, -7.19776051e-03, -2.44917744e-03, -1.33788427e-02,
       -1.43457567e-02, -7.52767315e-03,  1.98689115e-04, -2.73396703e-03,
       -6.46592397e-03, -1.21380119e-02, -6.85285497e-03, -7.85428192e-03,
       -1.73300952e-02,  5.75944502e-03, -8.45882855e-03,  1.33676361e-03,
        8.74779467e-03, -1.45556042e-02, -1.38495173e-02, -2.27821283e-02,
       -6.64382614e-03, -2.42207386e-03, -1.20032318e-02, -1.71183865e-03,
        3.10220034e-03, -6.75289985e-03, -7.13940384e-03, -6.66532060e-03,
        1.11677358e-02,  2.49808165e-03,  3.58919264e-03, -7.30315968e-03,
       -4.93691955e-03, -2.04656459e-02, -9.29531269e-03,  1.77299289e-03,
        1.68005249e-03,  1.26828358e-03, -1.79008959e-04, -1.22395074e-02,
       -1.56839993e-02, -2.00587772e-02, -1.69817265e-02, -6.89328322e-03,
        1.20009854e-03,  5.38402889e-03,  6.52157178e-05, -3.22771911e-03,
       -8.86129215e-03, -9.72071663e-03,  4.85033402e-03,  7.52343051e-03,
       -3.50325485e-03, -8.96921102e-03, -1.60155371e-02, -1.44031830e-02,
       -6.58710580e-03,  5.08325920e-03,  8.82653170e-04, -5.71339158e-03,
       -5.33180498e-03, -1.31564960e-03, -5.37033426e-03, -8.50424077e-03,
       -2.39416640e-02,  6.09678857e-04, -3.64064216e-03, -7.29480665e-03,
       -1.35666532e-02,  1.20135844e-02, -6.88349036e-03, -1.25975655e-02,
       -7.20675942e-03, -1.28114764e-02,  3.26039456e-03, -1.41856745e-02,
       -5.58063155e-03, -8.92326329e-03, -6.06091460e-03, -4.89059463e-03,
        3.39785963e-03, -9.95373633e-03, -6.96432078e-03, -1.73814297e-02,
       -7.11027579e-03, -1.27025871e-02, -1.03691407e-02,  4.85742744e-03,
        1.57777150e-03,  4.41021612e-03, -1.24690672e-02, -1.61979981e-02,
       -8.42809025e-03, -1.21545549e-02,  1.58440543e-03,  7.13657821e-03,
       -9.11938213e-03, -9.16667690e-04, -5.92537550e-03, -3.97885591e-03,
        9.00322292e-03, -6.35838835e-04, -8.21137708e-03, -7.60740018e-04,
        1.12481816e-02, -8.85621365e-03, -4.86565987e-03,  3.15345172e-03,
       -1.01179807e-02, -1.11855669e-02,  6.16624113e-03,  5.71567845e-03,
       -9.50737949e-03, -8.95754341e-03,  7.74098560e-03,  1.81243406e-03,
       -1.18783163e-02, -6.80121500e-03, -1.24005107e-02, -7.97269400e-03,
       -1.07129607e-02, -1.66975390e-02, -3.76080279e-03,  3.46360495e-03,
        1.29244952e-02, -9.74004157e-04, -4.82074771e-04, -4.35809419e-03,
       -7.18113175e-03,  3.10197705e-03, -8.63250811e-03,  1.22527303e-02,
        5.54895401e-03, -4.36376687e-03, -3.34019866e-03,  1.49177926e-04,
       -1.19295856e-02, -6.59613498e-03, -1.35234080e-03, -1.10240765e-02,
        4.60632471e-03, -2.66016461e-03, -7.05729425e-03, -8.08740593e-03,
       -8.12445069e-04, -1.21547021e-02,  2.67059286e-03, -9.63982567e-03,
       -3.99586558e-03, -5.34135941e-03,  5.95252495e-03, -1.79396123e-02,
       -5.91868209e-03, -3.11146869e-04,  2.74887914e-03,  6.85012841e-04,
       -2.74542649e-03, -6.17825426e-03, -9.05878469e-03,  1.97666464e-03,
        1.04258524e-03, -1.74270626e-02, -9.97934956e-03, -2.58695916e-03,
       -6.54474739e-03,  1.02493139e-02, -4.95509384e-03, -5.78019768e-03,
       -7.14498712e-03, -1.87619950e-03, -6.22819085e-03, -1.65091436e-02,
       -4.97814734e-04,  1.53399697e-02,  3.62576731e-03, -9.28303879e-03,
        2.66169733e-03, -1.15103583e-04, -1.32675481e-03, -3.59872729e-03,
        7.72940461e-03, -5.91829512e-03, -6.48286240e-03, -1.94012932e-02,
       -5.76285366e-03,  6.40222745e-04, -4.67094593e-03, -4.34710411e-03,
        1.62510779e-02, -1.24593161e-03,  1.65853277e-02, -2.19312198e-02,
        2.91944109e-03,  6.27296651e-03, -2.04687309e-03,  7.24996487e-03,
       -9.53316456e-04, -6.76927855e-04,  7.14506069e-03, -8.04804172e-03,
       -1.78147424e-02,  7.15352711e-04, -7.06451293e-03, -5.14471950e-03,
        3.17095197e-03, -1.89096835e-02, -5.73244458e-03,  2.02108268e-03,
        7.72216183e-04,  6.85348269e-03, -6.54807221e-03,  5.03261574e-03,
       -7.28967367e-03,  5.58254484e-04,  8.10273271e-03, -7.12842681e-04,
       -2.03361902e-02, -1.46043971e-02, -6.92262687e-03, -1.12698134e-02,
        3.66260018e-03,  8.89322779e-04, -1.15927029e-02,  1.56168547e-03,
        4.79034754e-03, -7.18409987e-03, -9.55086015e-03, -4.62893950e-04,
       -8.89981259e-03, -1.24842874e-04,  1.06943212e-03, -4.08784114e-03,
       -4.87047946e-03, -8.76430608e-03, -2.30303733e-04,  2.64054257e-03,
       -9.47664119e-03, -4.55418043e-03, -1.13820303e-02, -5.48528694e-03,
       -1.12188058e-02, -3.38877249e-03, -6.52208971e-03,  5.21377381e-03,
       -7.91304093e-03, -7.92104751e-03, -1.68444011e-02, -1.18745137e-02,
       -7.62907369e-03,  1.64289388e-03,  1.41853373e-02, -5.13903913e-04,
       -2.10189484e-02,  3.01341433e-03, -8.48474354e-03, -7.18482770e-03,
       -3.80714540e-03, -7.98481889e-03, -1.15936724e-02, -4.95936302e-03,
       -6.42306078e-03,  6.73459144e-04, -1.22642638e-02,  4.05182643e-03,
       -5.13925310e-03,  1.41361044e-04, -1.76005941e-02, -1.30638909e-02,
       -1.26508698e-02,  6.91884011e-03,  6.85840938e-03,  7.17198185e-04,
       -1.69402664e-03, -4.76533035e-03, -8.52287933e-03, -3.58637306e-03,
       -7.03038229e-03, -4.16301144e-03, -8.88322294e-03, -1.35537125e-02,
        7.87328836e-03, -8.12700484e-03, -2.19965843e-03,  6.88497268e-04,
       -7.18796207e-03, -1.56982560e-02, -8.29404779e-03,  2.08384683e-03,
       -1.62880905e-02,  2.29517580e-03, -1.34131871e-03,  1.01378318e-02,
        5.68025094e-03, -5.69280470e-03,  2.63351086e-03, -1.03130089e-02,
       -9.43266787e-03, -4.76400368e-03,  2.83800950e-03, -2.28979886e-02,
       -7.82575645e-03, -1.01688085e-02, -5.86379785e-03, -9.87374442e-05,
       -1.76490508e-02, -9.09788907e-03, -7.16917822e-03, -1.55967544e-03,
       -9.47295502e-03, -4.43946198e-03, -1.84283815e-02, -5.18388674e-03,
       -1.15652783e-02, -9.61805752e-04, -1.73703255e-03, -8.96694418e-03,
        6.27401751e-03,  8.70979484e-03, -1.02530408e-03,  3.13312165e-03,
       -7.42323697e-03, -1.78249329e-02, -6.09006500e-03,  6.13880716e-03,
       -8.95392336e-03, -1.58771966e-02,  1.02981152e-02, -1.23359812e-02,
        1.50547805e-03,  8.73976969e-04,  6.46529533e-03, -4.94457083e-03,
       -2.68684351e-03, -1.78935821e-03, -5.71045931e-03,  6.56771520e-03,
       -2.34620143e-02, -2.34235190e-02,  2.10694358e-04,  1.81448068e-02,
       -7.93573447e-03, -3.21512064e-03, -4.84407274e-03, -6.77971588e-03,
       -5.51011413e-04,  7.59311114e-03, -4.62723291e-03, -1.28143653e-03,
        5.24386007e-04, -6.06310414e-03,  6.37662946e-04, -1.40278395e-02,
       -5.17653674e-03, -1.44133531e-02, -1.48555972e-02,  3.61889810e-03,
       -9.97293554e-03, -4.83508920e-03, -8.16316716e-03, -1.45520456e-02,
       -3.63749731e-03, -1.06984079e-02,  4.57421131e-03, -7.25081889e-04,
       -3.60073894e-03, -5.74094662e-03,  3.42387846e-03, -6.14391034e-03,
        5.35125658e-03,  3.44244810e-03, -5.15719224e-03,  2.74630683e-03,
        5.46174729e-03, -2.04346119e-03, -1.02229146e-02, -4.30679787e-03,
        8.46517505e-05,  1.98387485e-02, -1.46912364e-02, -1.89843327e-02,
        2.16032378e-03, -1.26593411e-02, -6.27094600e-03, -2.06915056e-03,
        1.37229664e-02, -8.46915226e-03, -8.86362325e-03, -1.70536235e-03,
       -5.70517732e-03, -1.03514986e-02,  6.50438620e-03,  2.13955576e-03,
       -1.09420810e-02, -7.38800177e-03, -3.45909642e-03, -3.41128721e-03,
        1.25670945e-03,  1.27382148e-02, -3.92183691e-04, -9.90674272e-03,
       -1.42201653e-03,  1.14673218e-02,  3.21617350e-03,  1.55021413e-03,
       -4.09745472e-03, -1.99536502e-04,  1.64273456e-02, -8.59981403e-03,
        5.81570959e-04,  1.12260564e-03,  7.83518981e-03,  2.63195136e-03,
        1.73606202e-02, -4.34796885e-03, -9.55206342e-03, -6.50642905e-04,
       -5.44316741e-03, -3.47082620e-03, -9.58974287e-03,  1.10649248e-03],
      dtype=float32), array([ 0.80735964,  1.031428  ,  2.3951356 ,  1.6734055 ,  1.6809458 ,
        0.69351834, -1.1525663 , -0.71365476, -0.69068795,  1.21503   ,
       -1.2139065 , -0.284291  ,  1.0727515 ,  2.0153847 , -0.41012922,
       -0.9404485 ,  1.6059684 ,  1.2792077 , -0.99391615,  1.5232147 ,
        1.6875362 ,  0.04957077, -1.8006896 ,  0.98864263,  2.305376  ,
        1.4742877 ,  1.3541511 ,  1.3162636 ,  1.3044219 ,  0.89330643,
       -0.24749602, -1.3761566 , -0.8374347 ,  0.35559762, -0.93211395,
       -0.35713944,  0.12930448,  1.1543322 , -0.33722287,  1.5974131 ,
        1.2051871 , -1.004866  ,  0.7703556 , -0.8779951 , -0.3804555 ,
        0.8843531 ,  0.889046  ,  1.504774  ,  1.3363774 ,  0.07407606,
        1.2393304 ,  1.6449181 , -1.0154523 , -1.7886308 ,  0.87400025,
        1.3573194 , -1.9657817 , -1.7583493 , -2.043548  ,  0.27907416,
       -1.3639553 ,  1.6560619 , -0.7493742 , -1.6001681 , -0.11075462,
       -1.223063  ,  1.4603888 ,  0.9432337 ,  0.8592675 ,  1.3037658 ,
        0.96603405,  0.33338943, -1.1253508 , -0.62983555,  0.3272247 ,
        1.2955511 ,  1.3395146 , -0.17539656, -0.28499234, -0.13936435,
        0.91909003, -0.14474142,  1.4205389 ,  1.4946582 ,  0.85906994,
       -1.7604165 ,  0.412701  ,  1.851853  , -1.8164128 , -1.1079175 ,
       -1.184537  ,  0.56712306,  1.2680193 , -0.5149482 ,  1.8864632 ,
       -1.2304909 ,  1.1203188 , -1.6265793 ,  0.4595376 ,  1.1880158 ,
       -2.2122889 ,  1.8078327 , -1.2698634 ,  1.0472889 , -0.91589504,
        0.54845405, -1.8393601 ,  1.1601613 ,  0.40475938,  0.389736  ,
        1.1379535 ,  2.2420516 ,  1.1248282 ,  1.5923985 ,  0.30044988,
        1.0691831 , -1.3234788 , -1.296807  ,  1.4226984 ,  1.9322793 ,
        1.449582  ,  1.3604811 , -1.0503105 , -1.4651886 ,  1.1675384 ,
       -1.531661  , -1.2591162 , -1.772122  , -2.1812053 ,  0.68662417,
        1.4426953 , -0.47565985,  1.4206464 , -1.2309003 ,  1.6716017 ,
       -1.4844526 , -2.2533844 ,  1.1241785 , -0.6934931 ,  1.1485898 ,
        0.93679035,  1.5344831 , -0.4068715 , -1.7322466 ,  1.275178  ,
       -0.5070384 , -1.0714449 ,  1.1522877 ,  0.91566104,  1.3307445 ,
        0.31337935, -1.0391235 , -1.2985462 ,  0.08147123, -0.9746073 ,
       -1.9412781 ,  1.2070036 , -1.6863916 , -0.6073655 , -1.431646  ,
       -0.5687645 ,  0.9318523 ,  1.7756356 , -2.2314236 , -0.90833575,
       -0.8331522 ,  0.57393175,  0.732299  , -1.5836098 , -1.3254898 ,
       -1.1375474 ,  0.336029  , -0.67701864,  1.4745237 ,  0.41033944,
        2.3144803 , -0.43284273,  1.074807  , -1.190646  ,  1.442769  ,
        1.7080989 ,  1.6080182 , -1.0457382 , -0.91426146, -1.1368943 ,
       -0.9429401 , -0.80503607, -1.8725934 , -0.7917838 ,  1.9107158 ,
        0.9434383 , -0.6158407 , -0.77777237, -1.622015  , -1.3110946 ,
        0.021092  ,  1.3665483 ,  1.1937869 , -0.8699755 ,  1.3953412 ,
        0.02666775,  0.29481575, -1.0067943 ,  1.4491515 , -1.3240608 ,
       -1.5576891 , -1.1322551 ,  1.2088706 , -1.1779257 ,  1.0141077 ,
        0.32018816,  1.3551015 ,  0.55858475, -2.014534  ,  0.30400363,
       -1.2484202 , -1.579827  ,  0.4501716 , -1.2546465 ,  1.5865073 ,
       -1.2715858 , -1.5251923 , -0.8408713 , -2.3035686 ,  0.2155805 ,
       -0.91805923, -0.01079477,  1.1648058 ,  1.3907633 , -1.7151954 ,
       -0.34929922,  1.0073678 , -1.9704152 ,  1.3671448 , -0.19929406,
        1.2692769 ,  1.0846337 , -1.5942023 ,  1.6307068 ,  1.1466002 ,
        1.127334  , -1.830159  , -1.577164  , -0.93199307,  1.1153079 ,
        0.9462167 ,  1.0655717 ,  0.52331924, -0.09703861, -0.14560734,
        0.5250446 , -1.6938863 , -1.3222394 ,  0.51904607, -1.4998511 ,
        0.57455623,  1.1338919 , -1.7223686 , -0.5565216 , -2.1115704 ,
       -0.83487034,  1.4107674 ,  1.2378879 , -0.31205994,  1.0836182 ,
        0.3222452 ,  1.2100035 , -1.1789978 ,  1.2393242 ,  1.232062  ,
       -0.51516694, -1.2831194 ,  1.8957729 ,  0.3174414 ,  2.1206572 ,
       -0.9029592 , -0.49519446, -1.2887871 , -0.46277463,  0.6701793 ,
        0.82253647, -1.2862388 ,  0.0765008 , -1.638898  ,  1.5705764 ,
        2.0341165 ,  0.9595227 , -0.6396337 ,  1.1578017 ,  1.7621812 ,
       -0.09204515, -1.52348   , -0.14216848, -1.1113248 , -0.20022298,
        1.1777492 ,  0.94988924,  1.1239305 , -1.9678195 , -0.46015722,
        2.0770729 , -1.9195132 ,  0.3404999 , -0.20430826,  1.0712615 ,
        1.2353567 ,  1.1121857 ,  1.3344289 , -0.6097398 ,  1.391063  ,
       -1.1079837 , -0.03920984,  0.80420953, -1.6105    , -0.4691695 ,
        0.42347986,  1.1403888 , -0.42206684,  1.6241946 , -1.2823747 ,
       -0.87210196, -0.39023292,  1.1106752 ,  1.3064404 ,  0.84281   ,
        0.55266416, -1.2493465 ,  1.6753546 ,  0.32989773,  1.363698  ,
       -1.4527621 , -1.5295032 ,  1.3116006 ,  2.2270558 ,  1.1646698 ,
        1.8952626 ,  0.71674114,  0.9558095 ,  1.3314096 ,  2.0741193 ,
        0.94358665,  0.82178164,  0.55599666,  1.0977798 , -2.057519  ,
       -0.8821668 , -0.3420674 , -1.8438014 , -0.38028327,  1.1648848 ,
        0.8345244 , -1.1882243 ,  0.48302606,  0.46704817,  0.4699394 ,
        0.8107121 ,  1.1682658 , -1.6123079 ,  1.6431955 , -0.42922127,
        0.70415616, -1.4405272 , -1.929688  , -1.0560226 ,  1.9116156 ,
        1.3590232 , -0.4943613 , -1.4109386 , -0.24479981, -1.2406533 ,
       -0.8609663 ,  0.6755783 ,  0.89375716, -1.361383  , -0.14735104,
        1.6575042 ,  1.0712789 , -0.4128568 ,  1.096548  ,  0.60225487,
       -1.8266567 ,  1.3630853 ,  1.0705558 , -1.4807112 ,  1.6746957 ,
       -1.4835999 ,  0.9110674 ,  1.911739  ,  0.3790345 ,  1.7689801 ,
       -1.4497544 , -1.8034576 , -0.87283623,  0.36737192, -0.7514498 ,
        0.9841255 , -1.3801475 , -0.09983486,  1.0797055 , -0.9529716 ,
       -0.82011765, -0.9429113 ,  1.5573443 , -1.8623198 , -0.92690176,
       -1.1189727 ,  0.6048014 ,  1.5687524 ,  0.61247325, -1.503572  ,
       -0.38931468, -0.32325783, -1.6663804 ,  0.3709184 ,  1.8266984 ,
       -0.75316906,  0.72640604,  1.5864111 ,  0.53838223, -1.7425679 ,
        1.408204  , -0.7972789 , -1.7724066 , -0.7555937 , -1.2685794 ,
       -1.2396293 , -0.89151734,  1.4943907 , -2.5179634 ,  0.39218414,
        0.45481056, -1.3285162 ,  0.87475634, -1.238116  , -1.0537858 ,
        1.4591653 ,  2.2037106 , -1.0885748 , -1.3197365 , -0.37524527,
       -1.5535138 , -1.2140719 ,  0.45071602, -1.0066485 , -1.1813015 ,
       -0.02046056, -0.01920546, -0.90695316], dtype=float32), array([ 6.9856687,  5.0101137, 19.429562 , 12.750453 , 17.262419 ,
        5.229091 ,  2.369864 ,  3.5503938,  2.4931984, 15.473894 ,
       13.149527 ,  1.8379885,  2.313233 , 10.068316 ,  2.6771035,
        3.3595934, 12.448127 ,  9.455295 ,  3.6479926, 14.312527 ,
       10.31846  ,  2.2181015,  7.2751   ,  4.86971  , 14.651088 ,
       11.214597 ,  6.8010893, 14.081408 ,  3.370987 ,  3.7437031,
        2.7073402,  4.4458528,  4.2763734,  2.642108 ,  4.808229 ,
        2.2671194,  1.2547512,  8.991496 ,  2.121106 ,  7.957965 ,
        9.804168 ,  2.028079 ,  5.609551 ,  2.1536791,  3.6040702,
       13.049922 ,  6.5163884,  9.4586525,  9.7863655,  1.1839542,
       13.3356285, 10.424941 ,  3.7073398, 14.544008 ,  4.3243866,
        8.995303 ,  7.745711 , 13.623798 ,  8.761003 ,  5.4914904,
        3.693796 , 14.443549 ,  3.353853 ,  5.102379 ,  3.2882729,
        7.493977 , 12.709328 ,  8.304733 ,  5.8848085, 11.379204 ,
        7.2668614,  2.4051895,  7.3378744,  3.537247 ,  2.0901637,
        8.618581 ,  4.448599 ,  3.3089006,  4.196324 ,  0.6800872,
        2.8858209,  5.897117 ,  6.100065 , 15.997282 ,  5.4042945,
        8.858093 ,  4.042993 ,  9.833242 ,  7.2044578,  5.801917 ,
        3.3778863,  5.8575077, 10.015752 ,  3.6573575,  7.603675 ,
        3.2742934,  8.813359 ,  8.092078 ,  3.3512692,  8.740448 ,
       16.855095 , 14.986615 ,  4.559822 ,  7.9068933,  5.640267 ,
        5.726102 ,  8.801419 ,  5.4337354,  3.9306989,  7.592904 ,
        3.5575073, 10.774015 ,  7.7255416, 14.030062 ,  3.7938552,
        5.7519073,  3.0904486,  4.69328  , 11.7676935, 11.001562 ,
       12.159691 ,  5.3107276,  4.0311723,  8.321104 ,  8.291459 ,
        2.2846916,  5.878251 ,  5.824498 , 13.08134  ,  8.099902 ,
       10.337315 ,  3.3139925,  2.9582357,  3.7401998, 14.027352 ,
        3.637673 ,  6.5847383, 11.111875 ,  3.3576267,  3.1805618,
        7.093066 , 13.705827 ,  2.9599187,  6.598285 ,  8.271348 ,
        2.294591 ,  3.9734414, 11.490514 ,  6.658794 , 13.016654 ,
        3.84099  ,  5.194589 ,  8.259167 ,  3.6523044,  3.2623665,
        5.8456187,  3.6600044,  6.275839 ,  2.2416828,  4.597598 ,
        5.255534 ,  5.2684894, 13.799675 , 10.12787  ,  2.6111565,
        3.6510997,  6.977398 ,  6.0250645,  4.31984  ,  4.457142 ,
        5.332535 ,  1.5614102,  2.235678 , 10.143785 ,  1.7350373,
       18.821384 ,  3.2270277,  3.751631 ,  4.9645877,  7.755604 ,
        7.8699145,  6.3002048,  1.6260039,  4.6350803,  2.374001 ,
        3.8808193,  5.0702586,  3.6558056,  2.9191155, 12.982422 ,
        3.5370305,  2.998414 ,  5.6253357,  9.175336 ,  2.7109296,
        3.525068 ,  6.9344287,  5.5712566,  8.398693 ,  8.0482855,
        3.3265479,  3.4000833,  1.3502443, 13.363628 ,  3.8161628,
        6.385683 ,  3.2133932,  2.090737 ,  3.494394 ,  8.793581 ,
        2.3637216, 13.659201 ,  2.7712038,  8.203544 ,  1.4817268,
        3.3936594, 13.140324 ,  5.1211357,  9.243855 , 13.618816 ,
        4.631723 ,  4.6283145,  1.4470347,  9.133304 ,  7.503743 ,
        2.644555 ,  2.0377522, 13.473124 , 13.027303 , 10.703048 ,
        4.0043488,  2.4772017, 15.23396  , 11.288853 ,  1.380487 ,
        5.84285  , 10.254894 ,  7.8439565, 13.321535 ,  3.8109243,
       12.158244 ,  7.1313324,  5.932794 ,  8.068895 , 10.827753 ,
        4.5848465,  5.0823264,  9.74016  ,  1.9451596,  3.1141808,
        7.632501 ,  5.3431287,  4.931942 ,  3.805855 ,  5.1398377,
        4.2184434,  5.8983445,  2.254024 ,  3.656026 , 11.089021 ,
        3.2156482, 10.370321 ,  4.754503 ,  4.0715556,  5.6271763,
        0.9080682, 10.872158 ,  3.6059747,  9.095039 ,  8.197696 ,
        3.453872 ,  5.1359277,  7.6160235,  1.6064919, 20.195847 ,
        3.1502228,  3.3139925,  9.138218 ,  3.281819 ,  3.839238 ,
        6.2948184,  5.074279 ,  4.899613 ,  5.0959034, 21.346155 ,
       18.932716 ,  5.6459813,  4.333946 ,  7.729357 , 10.667902 ,
        1.0227759,  3.0361774,  1.5036399,  5.3253827,  3.7663248,
        9.611973 , 10.349546 ,  5.4882607,  5.3539457,  4.36568  ,
       14.121597 ,  5.140354 ,  2.9046094,  1.9065495,  4.579683 ,
        3.7096214,  5.6061335, 14.134271 ,  1.0459421,  5.855686 ,
        5.2861705,  3.4971244,  5.7512956, 13.758827 ,  1.8524314,
        2.984132 ,  9.552059 ,  4.5371637,  5.361033 ,  5.3480062,
        8.219557 ,  1.2914346,  7.553586 ,  5.1961894,  8.464584 ,
        1.4280648,  2.1091821, 20.996094 , 10.102626 ,  9.299212 ,
        7.679795 ,  3.454222 , 10.906941 , 11.351141 ,  2.3373983,
        8.08863  ,  5.862027 ,  6.954138 , 16.025951 , 17.580334 ,
        6.377936 ,  6.242215 ,  6.282384 ,  3.4866524, 11.477916 ,
        5.381368 ,  3.074599 ,  5.635145 ,  1.6318883,  6.289093 ,
        8.732413 ,  7.2052894,  5.9172964, 10.955007 ,  2.9835699,
        7.4810934, 10.467592 ,  4.573819 ,  6.6114206,  2.133739 ,
        4.000371 ,  5.7083907,  8.830834 ,  4.8715725, 10.36243  ,
        9.709654 ,  4.4609513,  6.2726016,  2.7628002,  7.4520082,
        4.1621547,  9.656095 ,  7.367241 ,  3.7351875,  2.4178648,
        5.5854483,  2.3417156,  1.0213804,  5.127325 ,  9.239836 ,
        7.128001 ,  9.536371 , 11.738335 ,  9.577721 , 12.525321 ,
        5.322699 ,  8.85003  , 19.864733 ,  2.0563238, 11.886804 ,
       11.388096 ,  8.810068 ,  2.0146039,  3.1696827,  3.9227483,
        4.630593 ,  4.9196973,  7.8030434,  4.6937394,  7.3885875,
        2.8876476,  2.835536 , 11.615102 ,  7.2431946,  4.8534517,
        4.589005 ,  8.613095 ,  7.836532 ,  6.3987947,  5.442833 ,
        2.86027  ,  2.89047  ,  8.209156 ,  5.5268   , 10.604799 ,
        8.273337 ,  2.8911946, 12.2819   ,  4.9643126,  8.403569 ,
        8.989892 ,  2.58203  , 11.241779 ,  3.8641331,  5.415591 ,
        5.312609 ,  2.4455006, 10.049779 , 14.631513 ,  2.4283788,
        4.030663 ,  6.1781425,  4.894914 ,  2.735283 ,  3.7920747,
       13.217054 , 11.167824 ,  4.7879496,  4.993199 ,  2.727329 ,
        4.195757 ,  3.0080168, 10.877218 ,  6.100291 ,  6.1053033,
        5.220572 ,  3.3487446, 10.221513 ], dtype=float32), array([[[[ 0.00259754,  0.06767087,  0.0124692 , ..., -0.0254796 ,
           0.04258056,  0.04225288],
         [-0.00409621, -0.04687381, -0.00136401, ..., -0.03108922,
           0.03660488,  0.0177922 ],
         [-0.02373713,  0.03075187, -0.03744604, ...,  0.0498066 ,
          -0.03360371,  0.0399999 ],
         ...,
         [ 0.00236464,  0.02246715,  0.03871128, ...,  0.04852345,
           0.02104296, -0.01594144],
         [ 0.05001929, -0.02273328,  0.03084471, ..., -0.0470151 ,
          -0.00963461,  0.05129233],
         [ 0.01489859,  0.02249444,  0.0095391 , ...,  0.00676483,
           0.05448733,  0.00608809]]]], dtype=float32), array([[[[-1.73660982e-02, -2.00861841e-02, -6.88928086e-03, ...,
          -2.79881060e-02, -2.38094721e-02,  2.44396999e-02],
         [ 2.67196894e-02, -3.16776498e-03, -3.68201616e-03, ...,
          -2.08067894e-03, -2.58546416e-02, -6.29542675e-03],
         [-3.75283472e-02, -3.43517400e-02, -3.23122628e-02, ...,
          -3.53708956e-03,  3.45040560e-02,  1.34819793e-02],
         ...,
         [-6.53299782e-03, -1.74176693e-02,  2.19812077e-02, ...,
          -1.70941018e-02, -1.20967962e-02, -9.00921319e-03],
         [-7.65523000e-04, -2.53727548e-02, -1.23920580e-02, ...,
          -3.35781053e-02,  1.33492937e-02,  2.28256471e-02],
         [-3.32508283e-03, -1.22920414e-02, -8.66854284e-03, ...,
          -2.57301815e-02,  3.87542471e-02, -9.63724218e-03]],

        [[-5.79156633e-03, -1.09429127e-02, -1.16490750e-02, ...,
          -2.70584989e-02,  3.25770164e-03,  8.88871215e-03],
         [ 2.28392333e-02, -2.06272826e-02, -1.99047681e-02, ...,
          -4.19437932e-03, -6.16310444e-03,  1.45106493e-02],
         [ 1.48416199e-02, -2.66403495e-03,  1.89320855e-02, ...,
          -3.55120469e-03,  1.04269702e-02, -2.31147418e-03],
         ...,
         [-2.45147087e-02,  1.19861374e-02, -2.95317210e-02, ...,
           2.71173101e-02, -1.79692246e-02,  1.98684894e-02],
         [ 1.75755576e-03,  2.04694849e-02, -2.68012490e-02, ...,
           2.26779329e-03,  1.26013895e-02, -2.11585648e-02],
         [-1.21093001e-02, -6.79788645e-04,  1.54182548e-02, ...,
           7.63274264e-03, -1.19859343e-02,  6.38252962e-03]],

        [[ 8.95701908e-03,  1.13352360e-02, -2.06858609e-02, ...,
           8.26324709e-03,  7.00074062e-03,  1.37532176e-02],
         [ 1.86330581e-03,  2.74583995e-02,  1.16368476e-02, ...,
           2.36482210e-02,  6.30194973e-03, -1.42626965e-03],
         [ 1.90690458e-02, -2.82141566e-02,  8.79012886e-03, ...,
          -8.27169232e-03,  1.81185827e-02, -5.28140180e-03],
         ...,
         [ 6.17670268e-03,  1.79551058e-02, -7.68679427e-04, ...,
           3.08996439e-02,  1.36680407e-02, -2.41866894e-02],
         [-2.93964818e-02, -3.31547260e-02, -2.83041354e-02, ...,
          -5.35885291e-03,  6.14168821e-03,  3.02150548e-02],
         [-1.60326958e-02,  1.75989754e-02, -1.40016861e-02, ...,
           3.43915611e-03, -1.37475850e-02,  2.36637867e-03]]],


       [[[-2.03987639e-02,  1.43127861e-02, -1.91340484e-02, ...,
           1.23069594e-02, -5.00335242e-04, -7.71587249e-04],
         [ 2.26212237e-02, -1.93226710e-02, -7.55825825e-03, ...,
           5.02974901e-04, -5.20296115e-03,  1.50180422e-02],
         [-3.67995799e-02, -2.22224388e-02, -3.24773006e-02, ...,
          -1.76431034e-02,  2.10319515e-02,  3.98568762e-03],
         ...,
         [ 2.47735195e-02, -1.70803331e-02, -1.23841604e-02, ...,
           2.05839910e-02,  5.51202009e-03, -1.37693072e-02],
         [-1.98226348e-02,  2.48160609e-03, -7.83485710e-04, ...,
          -1.46440938e-02, -1.12610718e-03,  3.32882665e-02],
         [-1.66190434e-02,  2.26240400e-02, -9.06804763e-03, ...,
           1.48837473e-02, -5.49496664e-03,  8.05830676e-03]],

        [[ 6.76232623e-03,  3.03531252e-03, -1.06790690e-02, ...,
          -2.80960239e-02,  3.77849117e-02,  2.04225928e-02],
         [-8.40146840e-03,  2.23469026e-02,  3.16301957e-02, ...,
           1.29576037e-02,  1.99425370e-02, -2.55169850e-02],
         [-2.38360167e-02, -1.24627706e-02,  6.47285953e-03, ...,
          -3.05467416e-02,  1.91519670e-02,  2.36120895e-02],
         ...,
         [ 2.28242902e-03, -4.20464948e-03, -1.27339484e-02, ...,
           1.70947891e-02,  1.97256170e-02, -2.60165893e-02],
         [-5.31044416e-03,  1.90036613e-02,  1.10346191e-02, ...,
          -2.27769203e-02, -1.32131120e-02,  1.54864714e-02],
         [ 1.02028484e-03, -1.45468314e-03,  6.71858527e-03, ...,
          -1.58799272e-02,  3.73982675e-02,  6.40758593e-03]],

        [[ 2.04722653e-03,  7.82152129e-05, -7.86949508e-03, ...,
           9.69479047e-03, -1.32377669e-02,  2.78410241e-02],
         [-2.23280434e-02,  1.52520388e-02,  1.62795298e-02, ...,
           2.92671937e-02, -4.22296626e-03,  1.14320600e-02],
         [-5.85375400e-03, -3.32953930e-02,  7.40526244e-03, ...,
           2.16323510e-02, -1.78403910e-02, -1.60482656e-02],
         ...,
         [-1.61768589e-02, -1.08756321e-02, -3.60364094e-02, ...,
           4.06223786e-04,  2.49701571e-02,  2.24501882e-02],
         [ 2.38497853e-02, -1.79398023e-02, -8.32736085e-04, ...,
           2.95097101e-03, -1.23601165e-02,  2.63562538e-02],
         [-2.96079516e-02,  1.47987446e-02, -1.63630862e-02, ...,
          -3.97554715e-04,  3.31229484e-03,  3.31435874e-02]]],


       [[[-1.72213893e-02, -7.77309947e-03, -1.56043693e-02, ...,
          -2.54546273e-02, -2.44529005e-02,  1.64183341e-02],
         [ 1.73999984e-02, -1.38003025e-02, -5.08849462e-03, ...,
          -2.60501243e-02, -1.12934951e-02, -3.49698239e-04],
         [-3.45934480e-02, -8.73666164e-03,  5.82589069e-03, ...,
           4.95220476e-04, -1.91551708e-02, -4.73206537e-03],
         ...,
         [ 3.06698941e-02, -1.88148133e-02,  1.07013192e-02, ...,
          -6.05358509e-03,  4.18234617e-03,  1.51386317e-02],
         [-3.30056855e-03,  1.71515997e-02, -1.57030709e-02, ...,
           5.96610457e-03, -1.81675702e-02,  2.05160305e-02],
         [ 1.28237847e-02, -4.40820633e-03,  2.46881298e-03, ...,
           4.78864321e-03,  3.03137936e-02,  3.13644707e-02]],

        [[-2.26929188e-02,  1.81095079e-02,  2.33986527e-02, ...,
           2.23257020e-02, -1.77221261e-02,  2.73753777e-02],
         [ 1.71676427e-02,  1.24139898e-02,  6.64839940e-03, ...,
           9.56059154e-03,  5.99023793e-03,  1.73115963e-03],
         [ 1.26068788e-02, -2.93427240e-03, -2.87812259e-02, ...,
          -1.94562543e-02,  2.17958242e-02,  1.17516173e-02],
         ...,
         [ 3.14574987e-02, -2.14255340e-02,  2.99807126e-03, ...,
          -5.58877829e-03,  3.19458209e-02, -3.08411624e-02],
         [ 1.88671704e-02,  1.63156297e-02, -8.91831517e-03, ...,
          -2.29643472e-02, -5.62931178e-03,  6.51122630e-03],
         [-2.12873723e-02, -3.60496156e-02, -7.51513382e-03, ...,
          -2.49753725e-02,  4.62974375e-03,  4.10700403e-03]],

        [[-4.88322868e-04, -1.92093663e-02, -3.33948922e-03, ...,
           1.85784120e-02,  2.03896612e-02,  1.09447795e-03],
         [ 7.94547610e-03,  6.06881734e-03,  2.63607949e-02, ...,
          -2.35914271e-02,  3.23650986e-02,  4.52681258e-03],
         [-1.65940467e-02, -2.94177979e-02,  1.99244563e-02, ...,
           1.27436966e-03,  1.55208064e-02, -4.97331470e-03],
         ...,
         [ 2.18342077e-02,  1.81897860e-02,  1.61075220e-02, ...,
          -3.99730913e-03,  2.05375720e-02,  6.53314963e-03],
         [-1.64506938e-02, -5.47133572e-03,  4.93668066e-03, ...,
          -2.66321134e-02, -3.20701860e-02, -2.38660015e-02],
         [-2.84559764e-02, -3.46241519e-02,  1.35425553e-02, ...,
           6.29930897e-03,  7.22564477e-03,  9.47419496e-04]]]],
      dtype=float32), array([-5.52588515e-03,  6.73384685e-03, -1.01819485e-02, -1.52351903e-02,
        5.33283688e-03, -3.47980112e-03, -4.67434758e-03, -1.08940955e-02,
       -1.62426960e-02, -2.11785529e-02, -1.16581637e-02, -1.45848840e-02,
       -7.28331693e-03, -1.70550905e-02,  5.37825143e-03, -6.56454032e-03,
        2.08390504e-03,  5.19841723e-03, -4.10547655e-04, -2.46505206e-03,
       -1.59610584e-02, -9.15306062e-03, -3.86972702e-03,  3.77979036e-03,
       -1.22818165e-02, -9.67963785e-03,  8.68125411e-04, -7.73027493e-03,
        4.29937942e-03, -5.13956835e-03,  1.54696187e-04, -8.43330659e-03,
       -7.29248673e-03, -8.49218760e-03, -1.49963936e-02, -1.47079686e-02,
       -1.11477859e-02,  1.09145360e-03,  6.76560076e-03, -1.92952920e-02,
       -9.20829421e-04,  6.45097485e-03, -1.11450236e-02,  7.31588283e-04,
        3.07670864e-03,  9.39295162e-03,  3.70556535e-03, -2.36067083e-03,
       -3.41075915e-03,  4.27333545e-03, -6.65280095e-04, -3.22888780e-04,
       -7.60054495e-03, -1.26499580e-02, -1.05541553e-02, -9.93632944e-04,
       -3.83170764e-03,  9.77755524e-03, -1.51511282e-02, -8.79292656e-03,
       -1.04097743e-02, -1.74659363e-03, -1.56508815e-02, -4.95187519e-03,
       -1.78322997e-02, -1.02585508e-02, -2.36734562e-03,  4.63119987e-03,
       -1.64219423e-03, -9.56214033e-03, -1.63220835e-03, -6.82051899e-03,
       -8.49940721e-03, -8.49980582e-03, -1.61315072e-02, -2.49864627e-03,
       -1.07685439e-02, -2.44884426e-03, -9.47828963e-03, -5.21789724e-03,
       -3.31741106e-03, -1.04212137e-02, -9.57705453e-03, -1.07801072e-02,
       -1.27988886e-02, -4.82897600e-03, -1.15566817e-03, -5.73159987e-03,
        6.46848290e-04, -4.67276713e-03, -4.19661868e-03, -5.93236275e-03,
       -7.84538337e-04,  1.83392770e-03, -4.85809846e-03, -2.37437859e-02,
       -9.65384673e-03, -1.55098329e-03, -1.29053164e-02, -3.66039749e-04,
       -4.70916135e-03,  5.76215889e-03, -5.16965427e-03, -2.23575961e-02,
       -1.63085442e-02,  6.69310009e-03, -6.72562793e-03, -7.49133248e-03,
       -6.53351482e-04, -9.90642328e-03,  6.51560817e-03, -2.31777430e-02,
       -8.35485291e-03, -1.45488232e-02,  4.66971099e-03,  1.50162203e-04,
       -6.62086718e-03, -8.69366515e-04, -1.96267641e-03, -6.14139391e-03,
        2.97064823e-03,  8.15092959e-03, -2.20994116e-04, -1.02254711e-02,
       -1.37437442e-02, -5.70558291e-03, -1.24956723e-02, -6.89793145e-03,
        1.01634406e-03,  7.62203662e-03,  4.55507776e-03, -2.99960957e-03,
       -3.34216538e-03, -4.94375359e-03,  7.30873877e-03, -7.94789009e-03,
        2.48658354e-04,  1.65700875e-02, -2.15752237e-03, -1.71431918e-02,
       -6.77689491e-03, -1.97375026e-02, -1.41846966e-02, -4.67236154e-04,
        2.05796701e-03, -4.52944590e-03, -1.33975754e-02, -1.25546288e-02,
       -1.87229773e-04, -1.73518546e-02,  2.69216299e-03,  8.68647732e-03,
        3.05295456e-03,  2.23000324e-03,  3.96413542e-03,  2.21889815e-03,
        8.99433438e-03, -7.11974036e-03, -8.83623585e-03, -8.44948459e-03,
       -4.85321647e-03,  2.54919496e-03, -1.50141148e-02, -1.44207254e-02,
       -1.55236572e-02, -1.49440868e-02, -1.42542664e-02, -2.05544662e-02,
        4.73541114e-03, -3.00070527e-03, -5.93675580e-03,  1.29982329e-03,
       -2.60152575e-03, -4.13190899e-03, -1.53124910e-02, -3.96506255e-03,
       -1.17445877e-02, -7.45178619e-03, -1.02780340e-02, -2.37688534e-02,
       -1.79042444e-02, -6.68162527e-03, -1.91118848e-02, -4.78820060e-04,
        8.68169591e-04, -7.63362413e-03, -1.02309026e-02, -1.29869292e-02,
        4.05344274e-03, -1.27320429e-02, -2.33878717e-02, -3.43019655e-03,
       -1.80023611e-02, -1.34779094e-02, -2.00615115e-02, -1.19530112e-02,
       -4.98688407e-03, -7.00094458e-03, -1.51179009e-03,  3.20970808e-04,
       -1.50414612e-02, -9.51633975e-03, -1.13472920e-02, -1.58135928e-02,
       -2.80723511e-03, -9.67064500e-03, -1.28098102e-02, -5.46475593e-03,
       -9.67582036e-03,  5.31505700e-03, -4.74609248e-03, -1.36001920e-02,
       -1.59834235e-04, -1.82724502e-02, -6.41916180e-03, -1.16171250e-02,
       -2.22034063e-02,  4.14833985e-03, -4.36601928e-03,  9.36927740e-03,
       -8.73168372e-03, -9.36590787e-03,  1.47674307e-02, -2.28074957e-02,
       -6.01956202e-03, -5.40859997e-04, -3.58353113e-03, -1.60005428e-02,
        2.45370343e-03, -1.09912883e-02, -7.41208065e-03, -4.99411998e-03,
       -4.19550110e-03, -3.25765810e-03, -1.17538162e-02, -1.58134624e-02,
       -5.48170414e-03, -6.30298676e-03, -2.53826031e-03, -4.62675793e-03,
       -2.63009463e-02, -1.06599303e-02, -1.29843699e-02, -1.16267791e-02,
       -6.38578134e-03, -1.02078328e-02, -9.44565237e-03, -7.63872126e-03,
       -2.25402247e-02, -9.65392683e-03, -2.26599351e-03, -9.47606843e-03,
       -1.18842963e-02, -1.78466309e-02, -1.09701995e-02, -1.31846527e-02,
       -8.60441127e-04, -2.30833832e-02, -8.39760341e-03,  2.82676076e-03,
       -6.25083398e-04, -7.56055955e-03, -9.62097757e-03, -9.75280814e-03,
       -1.65584385e-02, -1.71868764e-02, -2.27716714e-02, -8.83561000e-03,
       -2.82133138e-03, -1.43703762e-02, -5.72939543e-03, -1.28880888e-02,
       -1.15700450e-03, -1.70694273e-02, -6.16648840e-03, -2.19896324e-02,
       -2.42375117e-03, -2.06688698e-03,  1.20862690e-03,  1.03767421e-02,
        2.15522363e-03, -6.31975243e-03,  4.15628863e-04, -9.98347811e-03,
       -4.02915012e-03,  3.94517928e-03, -8.98495410e-03,  2.91691162e-03,
       -1.05196210e-02, -8.29537213e-03, -8.37195421e-06, -2.97522661e-03,
       -8.63354933e-03,  7.58372946e-03, -9.29068122e-03, -1.39376065e-02,
       -1.90915707e-02, -1.32285361e-03, -2.95914849e-03,  6.72316318e-03,
       -5.72838774e-03,  1.06161945e-02, -6.90074265e-03, -1.83334742e-02,
       -3.93974828e-03, -8.46032519e-03, -4.05299710e-03, -9.80557036e-03,
       -1.27383061e-02, -1.53770931e-02,  2.56939814e-03, -1.39688922e-03,
       -2.09294818e-02, -3.98899941e-03, -3.66433850e-03, -1.29197710e-04,
       -3.74777662e-03, -1.16270715e-02, -2.14144848e-02, -1.52571844e-02,
        5.94646554e-04, -1.35914469e-03, -1.48063125e-02, -1.02411781e-03,
       -9.40812519e-04, -4.96310601e-03, -2.08830070e-02, -1.41452961e-02,
        6.26330171e-03, -1.63848978e-02,  1.59483496e-03, -5.95796527e-03,
        1.92163116e-03, -6.37822645e-03, -2.34085079e-02, -1.74002796e-02,
       -2.51418278e-02, -4.55767103e-03,  5.83649473e-03, -9.52354819e-03,
       -5.06486464e-03,  4.61050496e-03, -1.86082516e-02,  1.96928531e-03,
       -6.87120762e-03, -6.10894291e-03, -3.74657917e-03, -5.11424569e-03,
       -1.95836499e-02,  6.32507727e-04, -1.99757367e-02, -1.25890858e-02,
       -1.75791071e-03,  1.67540321e-03, -1.42654148e-03, -1.61319168e-03,
       -1.03500085e-02,  3.53126461e-03, -6.72511233e-04,  8.73800553e-03,
       -1.94265060e-02, -1.70996040e-02, -6.38547121e-04,  5.56294620e-03,
       -3.73419910e-03,  3.66945285e-04, -6.12570252e-03, -5.12595987e-03,
       -1.39482440e-02, -7.46807177e-03, -1.76810436e-02, -5.78955188e-03,
       -8.34271591e-03, -7.27493409e-03, -8.35547224e-03, -1.09916776e-02,
       -6.71826908e-03, -8.20118189e-03, -1.41265262e-02,  5.22940070e-04,
        2.22515850e-03, -1.31123345e-02, -7.91679602e-03, -1.00512821e-02],
      dtype=float32), array([-1.1948183e+00, -2.0290780e+00,  1.4274501e+00,  1.5931381e+00,
       -1.1320505e+00, -1.6447212e+00,  1.3091036e+00,  1.2698258e+00,
        1.8630720e+00,  1.4987895e+00,  1.2472980e+00,  1.8810142e+00,
       -8.9266586e-01,  1.6793852e+00, -8.6395180e-01,  1.8564210e+00,
       -1.6065356e+00, -1.7458909e+00,  1.1590689e+00, -1.2597747e+00,
        1.6779442e+00, -1.4940453e+00,  1.5656412e-02, -1.4919596e+00,
        4.3658301e-01, -1.3052244e+00, -1.3759362e+00,  9.9696302e-01,
       -1.2829117e+00, -8.9361787e-01, -2.0654957e+00,  5.0348216e-01,
       -1.2206826e+00, -1.3170395e+00,  2.1977191e+00,  1.0748802e+00,
        1.1757789e+00,  1.0027356e+00, -1.5271585e+00,  9.4976979e-01,
        1.0983130e+00, -1.6303582e+00,  6.4531571e-01,  6.0212451e-01,
       -1.3446931e+00, -9.5265692e-01, -7.6994765e-01,  1.5417060e+00,
        1.7987114e+00, -1.5884393e+00,  9.5208377e-01, -2.3172498e+00,
       -8.1779963e-01,  1.3420702e+00, -4.9381387e-01, -1.5146847e+00,
        1.4167718e+00, -1.9639946e+00,  1.3472674e+00,  9.7992599e-01,
       -1.8529004e+00,  1.2786759e+00,  1.2600621e+00, -1.8312031e+00,
        9.2335564e-01,  1.0330299e+00, -4.8452538e-01,  5.4611784e-01,
       -9.2337257e-01,  5.5652654e-01,  5.1892346e-01,  1.5943501e+00,
        7.5424200e-01,  1.3642572e+00,  2.1106076e+00, -1.2299047e+00,
        1.2288783e+00,  1.4235277e+00,  7.8698683e-01, -1.3057132e+00,
       -1.7179782e+00,  1.6336441e-01,  1.5161583e+00,  7.4763888e-01,
        9.7903246e-01,  1.3506089e+00, -1.6553329e+00,  7.0155269e-01,
        1.5289240e+00, -1.2354462e+00, -1.8851558e+00,  2.3091970e-01,
        1.6162695e+00, -1.9245406e+00, -1.0494099e+00,  1.3709670e+00,
        9.9877340e-01, -7.2013104e-01,  1.2112774e+00,  1.2999703e+00,
        2.5282604e-01, -8.7731433e-01, -1.8557310e+00,  8.2835186e-01,
        1.1415703e+00, -1.7081898e+00, -1.2531626e+00,  1.4949874e+00,
       -9.8547524e-01,  1.3651035e+00, -3.9727920e-01,  9.9835950e-01,
        1.3721427e+00,  1.1928471e+00, -1.3950162e+00, -1.6548411e+00,
       -3.3257508e-01, -2.2060995e+00,  1.6814778e+00,  1.0294875e+00,
        5.0602829e-01, -1.9735951e+00, -2.6378787e-01,  1.0192009e+00,
       -7.6878738e-01,  8.1920761e-01,  2.1937988e+00, -1.4811376e+00,
       -1.5342908e+00, -1.4533237e+00, -5.5999261e-01, -2.5420780e+00,
        1.1116914e+00, -1.0712860e+00, -1.0791229e+00,  1.6260325e+00,
       -1.1751316e+00, -6.2619269e-01, -8.6401403e-01,  2.1040709e+00,
        9.9164957e-01,  9.3232793e-01,  1.5110762e+00, -2.2803926e-01,
        1.1427902e+00,  9.0167594e-01,  1.5280772e+00,  3.8128957e-01,
       -1.3164332e+00,  1.2555916e+00, -1.5707066e+00, -1.8399571e+00,
       -2.0717051e+00, -1.1893271e+00, -6.9757968e-01, -1.2991067e+00,
       -9.4426757e-01,  1.1378090e+00,  1.9881519e+00,  1.7780145e+00,
       -8.7811565e-01, -1.6505477e+00,  1.9280263e+00,  1.7715557e-01,
        1.1135327e+00,  5.4535598e-01,  1.0795552e+00,  2.0927320e+00,
       -1.1707305e+00, -7.0664805e-01,  8.3205265e-01, -1.4741646e+00,
       -1.4792248e+00, -7.5077921e-01,  1.5864214e+00,  3.0649078e-01,
        1.8397260e+00,  1.3762519e+00,  2.0045317e-04,  1.0504315e+00,
        1.9417771e+00,  2.1852626e-01,  2.1591907e+00,  1.5307565e+00,
       -1.7433728e+00,  6.1780381e-01,  8.4177357e-01,  1.3991219e+00,
       -1.8144190e+00, -5.8988279e-01, -7.4996793e-01,  8.6196059e-01,
        1.7116591e+00,  1.0186157e+00,  1.0205734e+00,  7.0663834e-01,
       -1.5586388e+00, -1.5238032e+00, -1.9891056e+00, -8.4574062e-01,
        1.4751780e+00,  1.4320586e+00,  1.1965444e+00,  1.7402327e+00,
        4.0425482e-01,  1.3665663e+00,  1.4237282e+00,  1.2455662e+00,
       -7.5917208e-01, -1.7275454e+00, -9.8183441e-01,  1.5199927e+00,
       -1.1296479e+00,  1.4121264e+00,  2.3588419e+00, -2.2613902e+00,
        1.0640869e+00, -1.2828447e-01, -5.8240283e-01,  9.0880728e-01,
       -1.7821121e+00,  2.1246183e+00, -8.9408654e-01,  1.3486944e+00,
       -1.0811299e+00,  1.3567338e+00,  4.5393459e-02,  2.0828519e+00,
       -2.2822225e+00,  1.2283139e+00,  1.4568839e+00,  1.0589791e-01,
        6.8987870e-01, -1.2656389e+00,  1.7029848e+00,  2.0283892e+00,
       -1.4274510e+00, -1.4427875e+00, -1.2905917e+00,  7.7287894e-01,
        1.0673714e+00,  9.8192149e-01,  1.7311555e+00,  7.1435076e-01,
        9.9043226e-01, -4.3106694e-02,  2.6776102e-01,  1.4232218e+00,
       -8.5501480e-01, -7.8865731e-01,  1.7898020e-01,  1.0108113e-01,
        1.1818399e+00,  1.5385232e+00,  6.9348431e-01,  1.2509445e+00,
       -1.6587007e+00,  7.8409934e-01,  8.8458705e-01, -1.8651717e+00,
       -9.4879740e-01,  1.5539497e+00,  1.0907331e+00, -5.0162929e-01,
        1.0044810e+00, -1.2630008e+00,  1.5664296e+00,  6.8637687e-01,
       -4.1073355e-01,  2.0462303e+00, -1.7957822e+00,  1.9285032e+00,
       -5.8706117e-01,  1.3630712e+00, -1.8520138e+00,  1.6296078e+00,
        6.4659131e-01, -1.6812276e+00,  1.9852140e+00, -1.2024163e+00,
       -1.6638501e+00,  1.0357598e+00, -4.1581270e-01,  1.3036469e+00,
       -3.7105376e-01,  1.8919784e-01, -9.0431482e-01, -9.9454123e-01,
        1.9731429e+00,  1.6091939e+00, -1.0171016e+00, -1.1720272e+00,
        3.2380086e-01, -8.9140618e-01,  1.2712134e-01,  1.5395925e+00,
        1.7380549e+00,  1.1507817e-02, -1.0885113e+00, -9.7277588e-01,
        5.0324321e-01, -9.6549326e-01,  8.3416098e-01,  1.1845648e+00,
        1.5071511e+00,  1.2865628e+00, -8.4723717e-01, -2.6680878e-01,
        1.3083020e+00,  7.4000168e-01,  4.1334814e-01,  1.2653446e+00,
        6.9530404e-01, -1.3301185e+00, -1.2236794e+00,  5.7182956e-01,
        1.2757397e+00,  1.3510188e+00,  1.7579499e+00,  1.1623890e+00,
       -2.0316069e+00, -1.8229853e+00,  1.2416168e+00, -1.0924432e+00,
       -4.2004436e-01,  4.0681607e-01,  1.6796540e+00,  8.3222741e-01,
       -1.6409999e+00,  1.4221768e+00, -1.6768564e+00,  1.0552951e+00,
       -1.1042600e+00, -5.4731381e-01,  1.0403591e+00,  1.8478862e+00,
        1.1022998e+00, -1.3975331e+00, -3.7718493e-01,  9.0618956e-01,
       -1.4402168e+00, -1.0898181e+00,  9.3033153e-01,  1.7012587e+00,
       -1.1294099e+00, -1.1944003e+00,  1.8434982e+00, -1.7142184e+00,
        1.6730522e+00, -1.5442542e+00,  1.2152896e+00,  1.9851195e+00,
       -1.4321262e-01, -1.5704854e+00, -5.9631938e-01,  9.5885450e-01,
        1.9296006e+00, -1.7102401e+00, -2.0034630e-02, -7.4648196e-01,
        1.4933528e+00,  1.4226156e+00, -6.6900110e-01,  9.8205113e-01,
       -1.9729559e-01, -2.2081504e+00,  1.0726553e+00,  2.2557138e-02,
        1.3020997e+00, -1.0852947e+00,  1.2135509e+00,  1.5445627e+00,
        1.7753633e+00, -5.1912588e-01,  1.6570083e+00, -2.9173610e-01,
       -9.2490447e-01,  1.6511853e+00,  8.5732061e-01, -8.1995761e-01,
       -1.7099521e+00,  1.5954977e+00, -6.8632311e-01,  1.2006829e+00],
      dtype=float32), array([ 6.369941 ,  9.310303 , 10.535764 , 12.550786 ,  8.750925 ,
        8.54279  , 12.850692 ,  8.818404 , 13.83085  ,  5.057495 ,
        7.5048757, 14.934595 ,  7.5363955,  8.146812 ,  4.798524 ,
       12.1369295,  6.8182654,  9.035677 ,  9.540887 , 10.428083 ,
       19.805681 , 10.467528 ,  2.4846537,  9.800104 ,  2.1262395,
        7.130791 ,  5.3343363,  3.7872465,  4.7660365,  2.9696999,
       11.661229 ,  4.590646 ,  8.3081875,  6.932465 , 11.4732   ,
       15.138595 ,  8.604649 ,  6.2457213, 15.810076 ,  8.228791 ,
        9.415757 ,  4.7850013,  5.0536156,  4.3395567,  3.7040308,
        2.4061272,  3.6598234, 12.353577 ,  8.151338 ,  9.184734 ,
       10.39983  ,  7.487309 ,  6.178975 , 10.993051 ,  6.950018 ,
       10.603196 , 10.25436  ,  8.835134 , 13.659933 ,  4.6575413,
        4.370893 , 16.071167 ,  7.4526706,  7.6513343,  8.631673 ,
        6.6504555,  2.4562109,  3.8265862,  3.4659717,  7.7793183,
        6.8080807,  8.1944685,  6.7510295, 10.524517 , 10.924938 ,
       12.285613 , 14.3649845,  8.663177 ,  2.6343956,  6.264385 ,
       10.330816 ,  2.1595578,  4.518504 ,  3.0158741,  9.470023 ,
        9.696812 ,  6.7085266, 14.364763 ,  8.4382305,  5.7973614,
        9.73404  ,  5.43186  ,  8.072872 ,  8.26887  ,  7.7585278,
        6.088798 ,  5.3442636,  7.5371237,  6.7658367, 11.107178 ,
        2.079672 ,  3.7692578, 16.647438 ,  4.5355673,  8.26581  ,
       10.662606 ,  4.489018 ,  8.066748 ,  4.2542467, 11.632939 ,
        4.2986817,  5.1465063,  9.139827 ,  8.759101 , 10.473341 ,
        8.18267  ,  6.1163044, 10.471589 ,  8.354165 ,  8.062349 ,
        2.126164 ,  5.276038 ,  3.969927 ,  8.479123 , 13.2798815,
        5.691286 , 15.151905 ,  7.9282246,  6.865703 ,  7.0331826,
        1.2152553, 17.599922 ,  9.404389 ,  6.497529 ,  2.3780549,
        8.10745  ,  3.2819538,  3.2184136,  1.4867635,  8.152785 ,
        3.974267 ,  5.7487655,  6.2045503,  2.821115 , 13.025904 ,
        2.8721166,  7.157622 ,  3.5738976, 14.047505 , 10.964128 ,
        6.3735743, 14.333928 , 12.137917 ,  5.449024 ,  2.4089904,
        8.999049 ,  4.9992275,  8.28417  , 17.067028 ,  9.523061 ,
        5.3480177,  8.730021 ,  9.987648 ,  9.354733 ,  7.3224955,
        5.0768256,  8.193718 ,  9.503292 ,  8.82412  ,  7.7024193,
        5.4630303,  4.1406813,  5.752547 ,  7.018714 ,  6.9747224,
        1.8862786, 11.889884 ,  6.350456 ,  4.476689 , 10.383408 ,
       14.76841  ,  3.8054318,  9.535481 ,  6.5825725,  9.115008 ,
        2.840856 ,  7.394478 , 10.439873 ,  7.8892484,  8.813826 ,
        4.757224 ,  2.6825364, 10.224744 ,  8.882229 ,  6.3500986,
        6.995059 ,  7.94301  ,  3.2816582,  9.764872 ,  7.7666497,
        6.9752903,  5.5977807, 16.396961 , 10.909465 ,  1.4793409,
        8.910373 ,  4.964599 , 12.305722 ,  8.106563 ,  8.018534 ,
        7.382189 , 14.5058975,  3.7057164,  8.959434 , 16.774988 ,
        9.624908 ,  7.825689 ,  3.8843613,  1.9408351,  5.211051 ,
        6.1923614,  8.709294 ,  6.533938 , 11.545319 ,  6.578449 ,
        4.671922 ,  3.646265 , 11.498624 ,  7.2138023,  6.691799 ,
        6.8754573,  4.410807 ,  3.2224777,  4.27164  , 13.498445 ,
       11.0646925,  4.7378016,  4.346452 ,  3.4892182,  4.0055513,
        3.7107801,  7.4503255, 12.954595 ,  4.212692 ,  7.375867 ,
        3.4294832,  7.488452 , 15.497369 ,  4.388708 ,  8.298357 ,
        5.514798 ,  2.825534 ,  8.161754 ,  5.5042872, 11.255729 ,
        3.9795125,  6.846453 ,  9.180954 ,  5.9159966, 11.573967 ,
        2.9720612,  5.968565 ,  8.299813 ,  9.260461 ,  8.567265 ,
       10.574163 ,  5.8261147,  4.2470546,  1.6664748, 12.639823 ,
        7.300838 , 11.893057 ,  6.2764215,  4.999803 , 12.899044 ,
       10.005107 ,  2.9377098, 10.452881 ,  4.652603 ,  4.285392 ,
       15.222838 ,  3.119494 ,  2.6722448,  9.707292 ,  3.9682364,
        2.3360078,  6.620857 ,  3.654539 ,  9.8522835, 11.998667 ,
        6.5337286,  6.296991 ,  3.3433335,  2.3750267,  2.227086 ,
        7.2884173,  9.681312 ,  3.557726 ,  7.9723797,  9.815002 ,
        2.2736585,  4.792822 ,  5.1958866,  9.199072 ,  5.893926 ,
        8.908695 ,  3.120671 ,  8.919274 ,  6.595203 ,  6.7283325,
        6.2224984,  9.515752 ,  7.278678 ,  8.331125 ,  9.393928 ,
        3.6930993,  9.650565 ,  8.907475 , 11.278252 ,  7.415252 ,
       15.146325 ,  9.48776  , 11.067343 , 11.884753 ,  4.293282 ,
        8.708086 ,  6.4768143,  6.132145 ,  7.367241 ,  8.401098 ,
        9.280009 ,  6.3013196,  5.3892283,  2.861624 ,  7.971254 ,
       14.210183 , 12.597586 ,  6.1460686,  4.2710733,  4.147744 ,
        1.9223274,  3.9221945,  4.4232364, 11.638801 ,  4.179717 ,
        8.71811  , 15.126247 ,  4.517273 ,  9.620146 , 10.386201 ,
        2.717213 , 16.656439 ,  5.2852154,  9.803078 ,  3.099359 ,
        9.977049 ,  5.411855 ,  6.7721076, 12.2775   ,  2.9095256,
        6.437187 ,  8.560508 ,  7.2381067,  2.4323988,  5.0789237,
        8.850774 ,  7.3162313,  3.156581 , 11.87738  ,  4.407085 ,
        5.288528 ,  5.780266 ,  9.204802 ,  2.156086 ,  8.860617 ,
        2.040188 ,  4.2734265, 11.535987 , 10.51967  ,  6.515795 ,
       13.907404 , 13.005389 ,  2.4072874,  8.229278 ], dtype=float32), array([-6.21241797e-03,  7.15624820e-03, -9.73443326e-04,  1.14411185e-03,
       -1.31747145e-02, -1.46933109e-03, -9.54968110e-03, -2.47605611e-03,
       -3.86700453e-03, -8.07322282e-03, -1.89318527e-02, -7.09488941e-03,
       -9.33637843e-03, -1.01267789e-02, -2.58273724e-02, -1.72339957e-02,
       -1.68004036e-02, -7.87209719e-03, -2.96872039e-03,  1.64099620e-03,
       -7.17033353e-03,  1.14061532e-03, -1.16559537e-02, -9.04743653e-03,
        5.62955253e-03, -2.61895508e-02, -6.24278281e-03, -5.71374036e-03,
       -1.09352749e-02, -7.30319088e-03, -1.18526993e-02, -2.92356848e-03,
       -2.03081798e-02, -2.90366430e-02, -9.08629782e-03, -2.21049506e-02,
       -1.00720003e-02, -1.10213889e-03, -1.31150205e-02, -1.46597605e-02,
       -1.69375166e-03, -1.23619521e-02, -1.90543309e-02, -4.80882404e-03,
       -1.47913750e-02,  4.23962157e-03, -7.08876457e-03, -7.86206033e-03,
        5.79874171e-03,  6.38662092e-03, -2.79293545e-02, -4.36908886e-05,
       -6.23667333e-03, -2.47849561e-02, -1.35123888e-02, -1.12893269e-03,
       -1.72440261e-02, -4.18194383e-03, -9.73408762e-03,  1.84747553e-03,
       -5.75916050e-03, -1.27772689e-02, -1.92506295e-02, -1.29315630e-02,
       -6.71625929e-03, -6.06383104e-03, -2.07340457e-02, -7.08599389e-03,
       -1.48442406e-02, -3.41140246e-03, -7.74348574e-03, -5.40749356e-03,
       -1.77466199e-02, -1.58585161e-02,  2.78654648e-03, -1.30852740e-02,
       -7.88994879e-03,  1.24761311e-03, -4.29172767e-03, -1.64707433e-02,
       -1.15882093e-02, -6.44217106e-03, -7.29387486e-03, -7.92661868e-03,
        5.18358033e-03, -2.43389211e-03, -9.06722341e-03, -4.45312168e-03,
       -4.89155017e-03,  3.89676192e-03, -8.50879308e-03,  1.69566367e-04,
        6.12839707e-04,  5.55739040e-03,  2.33824784e-03, -1.02599082e-03,
       -1.53124901e-02, -1.49851367e-02, -8.08672979e-03,  3.06850323e-03,
        1.76696889e-02,  2.79367482e-03, -4.54195309e-03, -7.45923491e-03,
       -1.89841408e-02, -2.40674932e-02, -2.05972586e-02, -6.86331140e-03,
       -2.75927340e-03, -1.32062724e-02, -1.10650463e-02, -1.21821649e-02,
       -2.42124870e-03, -7.64863007e-03, -6.33427687e-03, -6.17819978e-03,
       -1.59909595e-02, -5.81635628e-03, -1.41838822e-03, -1.18185561e-02,
        1.48761400e-03, -5.86177129e-03, -1.17045362e-02,  3.20886914e-03,
       -1.38237635e-02, -7.49726128e-03,  5.91920782e-03,  8.40361789e-03,
        2.00347370e-03, -4.00866335e-03,  5.01341699e-03, -1.97469303e-03,
       -6.07055472e-03, -8.61765072e-03, -1.41968988e-02, -1.69308041e-03,
        1.84228446e-03, -1.01759331e-02,  6.45190850e-03,  1.48982822e-03,
        4.52562235e-03,  6.18871348e-03, -2.17892192e-02, -8.49644933e-03,
       -5.20658819e-03, -1.54923182e-03, -1.01690190e-02, -2.06418266e-03,
       -1.25790276e-02, -2.65399497e-02, -9.14363563e-03,  2.49648583e-04,
       -6.40913611e-03, -2.50212569e-02, -8.11029412e-03, -8.22962634e-03,
       -1.17676100e-02, -1.46186189e-03, -2.23371498e-02, -1.29441461e-02,
       -1.97192263e-02, -1.70764904e-02, -3.09067289e-03,  5.40559273e-03,
       -1.69208515e-02, -4.24449611e-03, -1.20229134e-02, -8.08623969e-04,
        3.47755454e-03, -8.82366300e-03, -8.34945403e-03, -4.03143186e-03,
       -1.16143459e-02, -2.45111529e-03, -9.31967702e-03, -2.98915221e-03,
       -1.36182075e-02, -1.87697634e-02, -1.13302318e-04, -5.43706678e-03,
       -1.67414416e-02, -7.27085071e-03, -7.47868791e-03, -3.06014791e-02,
        3.61144077e-03, -5.49764046e-03, -1.41065428e-03, -1.21516893e-02,
       -7.13594211e-03, -8.94737337e-03, -2.41541415e-02, -8.75911303e-03,
       -3.03321928e-02,  5.11817401e-03, -1.83398332e-02, -1.73022738e-04,
       -1.86803397e-02, -3.81146953e-03, -4.55198623e-03, -4.67215432e-03,
        4.32093861e-03, -4.14562924e-03,  3.07608140e-03,  3.54355131e-03,
       -6.41113380e-03, -1.16257952e-03, -3.89713282e-03, -1.09129818e-02,
       -5.72712207e-03,  5.00030164e-03,  3.10093397e-03, -1.19673582e-02,
       -4.28058347e-03, -4.79191076e-03, -1.67538933e-02, -5.92568656e-03,
       -1.03004733e-02, -2.91956263e-03,  4.84941201e-03, -1.69954672e-02,
        7.24583981e-04, -6.97383238e-03, -2.29175631e-02,  2.57060793e-03,
       -8.68443679e-03, -3.53687443e-03, -4.85255569e-03,  2.17842706e-03,
       -2.35911701e-02, -1.94531009e-02, -8.92368797e-03, -6.74425438e-03,
       -1.08081996e-02, -1.77997295e-02, -2.79776170e-03, -7.75265507e-03,
       -6.03876030e-03, -3.85641586e-04, -3.56665906e-03, -5.91285294e-03,
       -3.42984707e-03, -1.49695494e-03, -9.06717870e-03, -5.85390301e-03,
        1.19881881e-02, -2.33642268e-03, -1.75805073e-02,  4.05845232e-03,
       -4.75461734e-03, -8.04174598e-03,  2.36006477e-03, -2.77034310e-03,
        6.14667451e-03,  2.69773795e-04,  1.12461939e-03,  3.43594817e-03,
        5.71659906e-03, -6.91399956e-03, -9.51484125e-03, -1.93502568e-02,
        8.38837761e-04,  6.15421310e-03, -4.70974424e-04, -3.55129736e-03,
       -1.83133017e-02, -1.06888954e-02, -2.68550031e-03, -6.67266129e-03,
       -1.35695944e-02, -1.39796343e-02,  2.15306738e-03, -6.95630861e-03,
       -5.54751279e-03,  3.26837995e-03, -1.18065532e-02,  8.31231591e-04,
       -1.02627445e-02,  3.64892092e-03, -1.12397717e-02,  7.07718963e-03,
        2.80695735e-03, -7.57821021e-04,  4.17685928e-03, -7.74661684e-03,
       -8.40328541e-03, -1.07082073e-02, -6.05336670e-03,  2.89417035e-03,
       -1.88623574e-02, -2.01011524e-02,  4.00149147e-04, -7.58612109e-03,
        4.04423196e-03, -1.71959009e-02,  3.52887716e-03, -6.41573919e-03,
        1.38988427e-04, -1.09014725e-02, -3.97018902e-03, -1.55983400e-02,
       -7.92283844e-03, -5.68424910e-03, -1.09532941e-02, -1.01157380e-02,
       -1.36041082e-02, -1.10370545e-02, -9.30422451e-04, -4.58556041e-03,
       -1.96402567e-03, -6.19367231e-03, -1.50958095e-02, -2.51496211e-03,
       -8.62485729e-03, -1.29408007e-02, -1.38105417e-04, -3.29680275e-03,
        6.77589746e-03, -3.95770767e-04, -1.57248210e-02, -8.82166810e-03,
       -3.34362523e-03, -6.38731290e-03, -2.31479406e-02, -1.44632912e-04,
       -1.81938298e-02,  4.76375921e-04, -1.14551000e-02,  3.40110599e-03,
       -1.37553010e-02, -9.83729679e-03, -1.13640251e-02, -1.09931296e-02,
       -1.53570250e-02, -4.83016949e-04, -1.41469100e-02, -2.46518459e-02,
       -6.99528167e-03, -4.66535799e-03, -1.50314532e-02, -1.55254975e-02,
       -6.70240028e-03, -3.60366353e-03, -6.32907357e-03, -4.65663522e-03,
        5.06327488e-03,  3.00246803e-03, -1.38728227e-02,  2.49324366e-04,
       -1.65946782e-02, -7.69181270e-03, -9.15155374e-03, -5.91182569e-03,
       -6.99597038e-03, -2.43707001e-02, -7.41421292e-03, -1.19105238e-03,
       -4.24416130e-03, -5.41247334e-03,  5.68914507e-03, -3.89506994e-03,
        6.46062777e-04, -9.77211818e-03, -5.78432065e-03,  5.92957111e-03,
       -1.60584990e-02,  6.90923724e-03, -1.95185412e-02, -9.64413676e-03,
       -6.57329615e-03, -3.02047469e-03, -1.11193780e-03, -2.71561416e-03,
        2.87076086e-03,  2.45317293e-04, -2.14087088e-02, -1.95123150e-03,
       -2.57559819e-03,  8.34278471e-04, -1.63641069e-02, -7.38519011e-03,
       -5.31158643e-04, -4.41948418e-04, -1.67104993e-02, -6.50792383e-03],
      dtype=float32), array([-2.975535  , -3.124665  , -1.8884146 ,  1.9291909 ,  2.821199  ,
        1.4765222 ,  2.6546657 ,  1.6548268 ,  1.5445544 ,  2.3738852 ,
        3.1098757 , -2.0772698 , -1.8021744 ,  0.9163955 ,  2.782599  ,
        1.2423813 ,  1.3267565 ,  1.8929796 ,  2.4752333 , -1.9313682 ,
        2.1894019 ,  1.7490503 ,  2.5993044 , -1.3960525 , -0.97050864,
        2.8468037 ,  1.0532857 ,  2.0697746 , -1.9323618 , -1.7067025 ,
        1.8508894 , -2.402196  ,  2.5651853 ,  1.7757695 ,  1.7786341 ,
        3.2551239 ,  2.8443654 , -1.5697606 , -2.7870054 ,  1.4463484 ,
       -1.7260687 , -2.1401677 ,  2.811495  ,  1.1046796 ,  2.620897  ,
       -2.336405  , -2.794852  , -1.1823015 , -1.8565558 , -2.2417665 ,
        2.7079117 ,  1.8763663 , -0.79346496,  1.769712  ,  1.1378368 ,
        0.66680646,  2.3949788 , -2.388051  , -1.9893409 , -0.8207417 ,
        1.180252  ,  0.7835152 ,  1.4213957 ,  2.0080032 ,  2.001443  ,
        0.35809386,  3.057714  , -2.1770775 , -3.347063  ,  1.7685215 ,
       -1.3035244 , -1.4278369 ,  2.4684403 ,  2.2733805 , -1.9301652 ,
        1.3610431 , -1.8499277 , -1.6912347 , -0.06941272,  1.6849416 ,
        2.7695065 , -2.151012  , -2.1785579 ,  1.4646924 , -2.296359  ,
       -3.27849   , -0.6190072 ,  0.93229514, -1.723189  , -1.7692827 ,
        1.9232987 , -2.4727335 , -1.6144872 , -3.0453897 , -2.9036076 ,
       -2.637186  ,  1.7235276 ,  2.8929744 ,  2.6262734 , -2.5273466 ,
       -2.1778214 , -2.3737557 , -1.7796376 ,  1.784194  ,  1.9375596 ,
        2.5653524 , -1.3781233 , -2.605375  , -1.1153821 ,  2.0396085 ,
        2.8057246 ,  2.2043855 , -2.6061487 ,  1.4361855 , -2.862755  ,
       -1.969481  ,  2.474376  , -0.72103196, -1.5952569 ,  2.3409474 ,
       -0.6246254 , -1.6411585 ,  2.4728854 , -2.5219517 ,  2.014743  ,
        2.1397007 , -0.42040157, -0.82560706, -2.3441393 ,  1.9039451 ,
       -2.2559214 ,  2.3597744 ,  2.1970637 , -2.7456188 ,  1.3999982 ,
       -0.6701523 , -2.5054758 ,  2.087014  , -2.1600604 , -2.2763631 ,
       -2.1054163 , -1.9231468 ,  2.2505968 ,  1.6277673 , -2.4059157 ,
       -2.60052   ,  2.5661507 ,  1.8393011 , -1.0845984 ,  1.9040573 ,
        1.5694152 , -1.4552869 ,  1.9246106 ,  2.4806273 , -2.2289114 ,
       -1.5013199 ,  1.7410942 , -2.5579023 ,  1.7235368 ,  1.1216359 ,
        2.2048686 ,  1.9234022 , -2.6680925 , -2.5341623 ,  2.086441  ,
       -1.5052799 , -2.5622742 , -1.46623   , -1.0387938 , -2.9305654 ,
       -1.5582038 ,  0.781419  ,  2.3608189 , -1.3109556 , -1.2745421 ,
       -2.5799866 ,  1.9830687 ,  2.0016816 , -2.374214  , -1.6742765 ,
       -2.1781187 ,  1.39079   , -3.283737  ,  2.458567  , -1.6513652 ,
        0.92679495, -1.2996619 ,  1.8397595 ,  1.5622    ,  2.2098894 ,
        2.3609638 , -1.0569586 ,  2.6134794 , -2.3457482 ,  2.3949068 ,
        1.7487936 ,  1.969249  ,  0.40049997,  0.37426826, -0.9980007 ,
       -1.2644941 ,  0.68928146, -1.183197  , -2.2446156 ,  1.8674822 ,
        1.6594843 , -2.9070246 ,  1.2476571 ,  1.8820232 , -0.8664122 ,
       -2.2951205 , -2.641134  ,  1.4806993 ,  1.0436019 ,  2.2151132 ,
        0.913333  , -2.9827302 , -0.34721962, -0.74470204,  2.7820683 ,
       -1.8243904 ,  1.8903261 ,  3.0473092 , -2.1960478 ,  2.6881056 ,
        3.2747037 ,  2.1311924 , -2.2464876 ,  2.0591187 ,  3.175143  ,
        2.1266346 ,  1.6038651 ,  1.5078155 ,  2.4520955 , -2.1151567 ,
       -1.1972026 ,  1.3774009 , -0.5626745 ,  1.1377659 , -2.0442512 ,
       -1.4194376 ,  3.459923  , -3.3887298 ,  1.6427188 , -1.1326905 ,
        0.68852407,  2.6053517 , -0.9930694 , -1.945639  ,  2.771412  ,
       -0.98493356,  1.4654408 , -1.8611816 ,  1.7852973 , -2.7003896 ,
       -2.6758509 , -2.0631351 , -2.6623964 , -1.2638271 ,  2.708078  ,
        0.3252473 ,  1.5271647 , -2.4472404 ,  2.6328168 ,  1.3074383 ,
       -2.503821  ,  1.7007687 ,  1.0429497 ,  2.1445599 ,  2.1620183 ,
       -1.054269  ,  0.73057353, -0.9733625 , -2.6432092 ,  1.0729083 ,
       -2.2790618 ,  2.01999   , -2.2148974 ,  2.7044716 , -2.4804354 ,
       -1.3711404 , -2.5326543 , -1.6537111 ,  0.96803236, -2.237074  ,
       -1.2360055 , -3.2451541 , -2.5002902 ,  3.0751598 ,  1.6372955 ,
       -2.4007509 ,  1.5961078 ,  1.0908941 , -2.650202  , -2.5068665 ,
        1.6446958 ,  2.0215719 ,  3.21222   ,  0.49942547,  2.2557728 ,
       -2.9880252 , -2.2060528 ,  2.6998937 ,  1.9034704 , -0.8936226 ,
        1.5272598 ,  1.023244  , -1.7208644 ,  0.7236711 ,  1.6990248 ,
        2.6611779 , -2.6788476 ,  1.7203884 , -2.4610903 , -1.7353547 ,
        2.0599952 , -3.0312135 , -0.9654812 , -2.4957113 , -2.6036055 ,
       -2.9372058 ,  0.6573548 ,  2.6986818 , -3.2647922 ,  2.483951  ,
        1.4731053 , -0.47970676, -1.0265577 ,  1.8639193 ,  2.866204  ,
        2.6276188 ,  1.9257529 ,  2.7063859 ,  1.54314   ,  2.7320719 ,
        1.6124737 ,  3.0647311 ,  1.2330122 ,  1.1344882 ,  2.9585302 ,
       -2.9582672 ,  0.6888224 ,  0.8080126 ,  2.3839207 , -2.5723186 ,
       -1.4436207 , -1.8744131 , -0.7819766 ,  1.211287  , -2.7766097 ,
        2.5984547 ,  1.9743443 , -3.0020208 ,  1.4027734 ,  3.0519564 ,
       -1.9077122 ,  1.2821648 , -2.2808022 , -2.439535  , -0.11002903,
       -2.1487    , -1.1065923 , -2.4658375 , -1.6344225 ,  1.4863139 ,
       -2.3275402 ,  1.2998046 ,  3.3492188 , -2.6857429 ,  0.9854288 ,
       -2.3358388 ,  1.6098863 , -1.9066359 ,  0.91876125,  2.1004627 ,
       -0.5545487 ,  1.7656842 ,  1.2815372 ,  1.3770995 ,  2.035444  ,
       -2.0079465 , -2.2089045 ,  3.037436  ,  2.0123358 ], dtype=float32), array([ 86.56285  ,  92.63472  ,  60.343826 ,  42.769676 ,  35.53479  ,
        33.90682  ,  35.59015  ,  28.34006  ,  28.329754 ,  23.001625 ,
        54.647293 ,  22.217972 ,  36.373505 ,  19.06599  ,  49.21565  ,
        30.828056 ,  29.665512 ,  30.923836 ,  45.468792 ,  60.094727 ,
        21.52587  ,  42.01252  ,  44.115864 ,  38.382046 ,  28.694893 ,
        35.925632 ,  30.282957 ,  53.391815 ,  50.296623 ,  38.61543  ,
        28.260712 ,  50.88135  ,  47.774036 ,  27.197397 ,  32.7604   ,
        49.889317 ,  44.02401  ,  43.72761  ,  66.55051  ,  26.378191 ,
        42.687893 ,  51.173676 ,  48.35877  ,  16.88575  ,  48.683033 ,
        60.93698  ,  42.123077 ,  29.531143 ,  49.10476  ,  50.434975 ,
        50.196568 ,  47.32193  ,  32.943386 ,  26.931313 ,  29.520983 ,
        25.475552 ,  28.828362 ,  51.932804 ,  46.32201  ,  34.310646 ,
        18.397915 ,  13.541392 ,  38.531918 ,  23.533493 ,  28.019253 ,
         6.4820275,  46.976254 ,  25.247007 ,  48.04296  ,  39.812454 ,
        40.446526 ,  20.3939   ,  33.436634 ,  49.26369  ,  58.618343 ,
        39.465763 ,  29.588655 ,  37.15521  ,  17.256723 ,  27.639948 ,
        40.27241  ,  52.528267 ,  52.396053 ,  42.5789   ,  70.81417  ,
        75.29428  ,  15.47795  ,  25.700678 ,  47.705048 ,  41.925438 ,
        44.427944 ,  83.19336  ,  28.470905 ,  86.71709  ,  76.86259  ,
        52.0972   ,  42.094215 ,  55.53104  ,  55.338463 ,  73.53479  ,
        31.75883  ,  71.13357  ,  15.793057 ,  45.93935  ,  37.709465 ,
        30.827797 ,  39.842766 ,  68.90841  ,  41.882633 ,  24.08715  ,
        49.592594 ,  29.217121 ,  55.02202  ,  18.56594  ,  52.744816 ,
        53.934505 ,  33.751163 ,  26.621777 ,  46.01101  ,  16.420738 ,
         9.44888  ,  23.335136 ,  32.2443   ,  96.248184 ,  42.365513 ,
        23.002247 ,  13.940429 ,  24.015364 ,  75.13264  ,  38.91512  ,
        66.925476 ,  51.0463   ,  47.75387  ,  55.492664 ,  35.140633 ,
        29.310226 ,  49.060284 ,  25.682278 ,  52.203266 ,  35.115467 ,
        62.417324 ,  59.151455 ,  43.612732 ,  32.43674  ,  44.306797 ,
        50.979446 ,  47.868366 ,  52.36657  ,  32.819443 ,  34.9624   ,
        15.898534 ,  12.647897 ,  48.16355  ,  45.635815 ,  52.60102  ,
        34.789875 ,  17.187048 ,  54.832962 ,  24.664669 ,  17.899391 ,
        26.040802 ,  34.27681  ,  68.86547  ,  58.144516 ,  36.6554   ,
        48.057144 ,  51.209297 ,  39.51737  ,  24.543863 ,  53.89     ,
        42.59783  ,  25.652403 ,  76.460846 ,  29.096045 ,  22.694153 ,
        66.59683  ,  17.82527  ,  41.15696  ,  76.98473  ,  21.719318 ,
        56.822807 ,  31.624714 ,  72.82975  ,  37.14036  ,  46.249523 ,
        27.618797 ,  38.93908  ,  37.06216  ,  26.073584 ,  37.66728  ,
        48.190247 ,  32.802753 ,  53.643585 ,  46.005833 ,  44.7762   ,
        28.650898 ,  31.145826 ,   6.445175 ,  13.952132 ,  25.673763 ,
        25.927982 ,  23.449762 ,  36.192513 ,  49.2465   ,  26.1223   ,
        34.972027 ,  34.705738 ,  13.946995 ,  36.77148  ,  27.287024 ,
        48.862186 ,  48.284317 ,  34.45193  ,  25.366524 ,  31.408068 ,
        17.183056 ,  63.026043 ,  24.651358 ,  14.384176 ,  35.39402  ,
        53.836086 ,  26.687746 ,  45.584293 ,  50.621334 ,  42.323586 ,
        40.417114 ,  26.441484 ,  65.4368   ,  41.45316  ,  56.698215 ,
        42.18708  ,  34.290085 ,  33.638523 ,  42.43612  ,  33.706154 ,
        18.41327  ,  24.123857 ,  18.412771 ,  10.982417 ,  46.67624  ,
        41.06215  , 113.37116  ,  89.2388   ,  66.49249  ,  31.164627 ,
        33.48441  ,  51.94055  ,  38.562607 ,  57.71322  ,  46.359173 ,
        23.258432 ,  30.23561  ,  49.079742 ,  20.812912 ,  66.04296  ,
        42.801624 ,  57.241028 ,  61.269806 ,  31.47822  ,  50.590214 ,
        30.436232 ,  16.537254 ,  52.63074  ,  38.44098  ,  29.052216 ,
        71.702446 ,  25.848013 ,  28.568113 ,  23.471317 ,  26.443909 ,
        60.119312 ,  14.689765 ,  32.30019  ,  67.35898  ,  21.401857 ,
        58.954857 ,  30.34213  ,  62.407906 ,  51.955517 ,  73.51999  ,
        43.671864 ,  34.407722 ,  44.075214 ,  13.005118 ,  60.48201  ,
        53.86223  ,  77.92593  ,  75.03456  ,  60.95631  ,  20.518326 ,
        39.832882 ,  24.582733 ,  27.702267 ,  42.042454 ,  64.349365 ,
        39.71238  ,  60.405018 ,  54.310207 ,   4.523284 ,  31.520073 ,
        50.707787 ,  40.44642  ,  38.823906 ,  48.27364  ,  26.912346 ,
        33.11463  ,  28.404415 ,  46.8196   ,  16.410965 ,  40.26224  ,
        37.582157 ,  49.3256   ,  34.691727 ,  58.635143 ,  56.844105 ,
        36.971344 ,  69.47255  ,  29.64969  ,  57.487206 ,  44.70185  ,
        69.08543  ,  30.639338 ,  44.834267 ,  56.108494 ,  34.90001  ,
        13.753873 ,  14.240004 ,  34.098175 ,  37.64705  ,  44.380013 ,
        36.747368 ,  21.68379  ,  43.13363  ,  27.089308 ,  40.49151  ,
        35.42233  ,  38.63698  ,  18.42427  ,  21.06795  ,  51.432755 ,
        58.83399  ,   6.7813926,  25.75032  ,  43.743137 ,  84.97165  ,
        61.619278 ,  22.995949 ,  16.586777 ,  26.028082 ,  40.33558  ,
        36.761234 ,  41.760063 ,  65.32079  ,  21.114676 ,  54.256104 ,
        56.3812   ,  23.800697 ,  52.594006 ,  47.268883 ,  12.519834 ,
        59.839035 ,  28.107697 ,  40.420345 ,  26.208452 ,  35.331703 ,
        79.33528  ,  17.81165  ,  63.886192 ,  65.525696 ,  18.602915 ,
        58.922443 ,  26.397076 ,  40.775917 ,  27.547916 ,  31.339315 ,
        17.37396  ,  22.251753 ,  29.187334 ,  16.080069 ,  40.175964 ,
        54.15908  ,  75.339096 ,  42.82859  ,  46.463657 ], dtype=float32), array([[[[-3.4770425e-02,  3.2948544e-03, -8.8019129e-03, ...,
           9.3201706e-03, -4.0575646e-02,  6.1251265e-03],
         [ 2.8365476e-02, -2.4095474e-02, -5.5342175e-02, ...,
           3.2446910e-02, -1.3153347e-02,  5.7440877e-02],
         [ 4.5409873e-02, -1.7302891e-02, -5.7909980e-02, ...,
           2.4557620e-02, -4.8346750e-02,  1.9518882e-02],
         ...,
         [-4.3982886e-02,  3.0681913e-04, -4.4495925e-02, ...,
          -3.1393003e-02,  2.8318994e-02,  3.7642114e-02],
         [-3.8513351e-02, -3.8539808e-02,  5.2662216e-02, ...,
          -4.4542842e-02, -4.0983625e-02,  1.6796645e-02],
         [-6.8774084e-03, -5.1873680e-02,  3.0800264e-02, ...,
           3.9849501e-02, -3.0362558e-02,  2.7730623e-02]],

        [[ 2.1759946e-02,  4.1008893e-02,  1.2714299e-02, ...,
           5.6922901e-03,  1.7151353e-03, -9.4390679e-03],
         [ 3.1119710e-02,  6.1539514e-03, -3.5587016e-02, ...,
           2.9690696e-02, -7.7329376e-03,  1.3746718e-02],
         [-7.5266273e-03,  3.4049928e-02, -5.8398884e-02, ...,
          -1.7264483e-02, -1.3649188e-02,  2.1387905e-02],
         ...,
         [-4.5780625e-02,  2.9129939e-02,  1.1291942e-03, ...,
           2.2466602e-02,  4.0362615e-02,  3.4913797e-02],
         [-2.3139233e-02,  1.0164798e-02,  3.4887426e-02, ...,
           4.3547686e-02, -4.4074945e-02, -1.7804066e-02],
         [ 2.0933082e-02, -4.4845641e-02, -6.8733883e-03, ...,
           4.7344049e-03, -4.7802549e-02,  3.5096165e-02]],

        [[ 4.3013923e-02,  2.4024732e-03,  2.8307417e-02, ...,
           8.4587289e-03, -2.6445547e-02,  3.6436722e-02],
         [-1.1633083e-02,  2.2086328e-02,  3.1309009e-02, ...,
           4.4042621e-02, -3.1041337e-02, -3.7153490e-02],
         [ 3.1565742e-03,  3.0756623e-02, -2.0109190e-02, ...,
           4.5458749e-02,  2.3145607e-02, -1.4900456e-02],
         ...,
         [-4.1717339e-02,  4.9646744e-05,  2.8734934e-02, ...,
           1.6161129e-02, -1.6724613e-02, -4.9240381e-02],
         [ 1.1573512e-02,  2.0195751e-02,  8.4705139e-03, ...,
           1.4854934e-02, -9.4074459e-04, -5.4962225e-02],
         [-3.7075595e-03, -1.7815802e-02, -1.4109231e-03, ...,
          -4.6817120e-02,  1.5572194e-02,  1.7445710e-02]]]],
      dtype=float32), array([[[[-2.2671057e-02,  3.0525170e-02,  3.3022944e-02, ...,
          -3.0932637e-04, -2.6278535e-02,  4.9775269e-02],
         [ 2.0748118e-03,  3.0418834e-02,  5.7163291e-02, ...,
          -5.4645422e-03, -2.7205421e-02,  3.6862079e-02],
         [ 5.5388995e-02,  1.7478056e-02,  4.9650799e-02, ...,
          -8.8200355e-03,  2.6227675e-02, -3.3634018e-02],
         ...,
         [ 1.1845131e-02,  4.4436031e-03,  3.5127841e-02, ...,
          -2.4027949e-02,  4.4043981e-02,  5.5782184e-02],
         [-8.1870994e-03, -5.3589839e-02,  2.3835368e-02, ...,
          -3.9945669e-02, -4.2138726e-02,  1.7748786e-03],
         [ 1.1186172e-02, -8.6539872e-03, -2.8307835e-02, ...,
          -2.4432112e-02,  3.5494268e-02, -4.3027021e-02]]],


       [[[ 4.5869511e-02,  1.4120177e-02,  3.2727476e-02, ...,
          -1.3529729e-02,  4.7210865e-02, -2.7092325e-02],
         [-2.9024230e-02, -3.8747840e-02, -1.8758429e-02, ...,
          -1.7480364e-02,  3.9628405e-02,  2.1199550e-02],
         [-3.7932887e-03, -5.6032505e-02, -2.6174633e-02, ...,
           6.2133279e-03,  1.1190846e-02,  2.6557114e-02],
         ...,
         [ 2.6193716e-02,  3.0509541e-02, -4.2704293e-03, ...,
          -1.7804133e-04,  6.7379330e-03, -2.4817165e-02],
         [ 4.3221503e-02, -5.2186225e-02, -1.6953716e-02, ...,
           3.0430475e-02, -5.5164983e-03, -1.9615961e-02],
         [ 5.4925513e-02, -3.1250168e-02,  2.7847307e-02, ...,
          -3.8529830e-03,  2.6850211e-02,  9.1504678e-03]]],


       [[[-1.0529197e-02,  1.8827537e-02, -3.5163805e-02, ...,
          -3.8063884e-02,  3.5965517e-02,  1.8480375e-02],
         [ 3.5040289e-02,  4.5554668e-02, -3.3585459e-02, ...,
           7.9613440e-03,  3.8952511e-03, -1.4639991e-02],
         [ 4.0136091e-02,  2.1625325e-02, -1.7625835e-02, ...,
          -4.6738591e-02,  4.8717357e-02,  1.6457854e-02],
         ...,
         [ 1.3243132e-02, -1.0740215e-02, -2.4016276e-02, ...,
           4.2014249e-02, -4.9994916e-02,  2.8624441e-03],
         [-3.6926307e-02,  2.7083885e-02, -4.7252577e-02, ...,
          -2.8149810e-02, -7.1978298e-05,  1.9840539e-02],
         [-2.2936437e-02, -1.8819161e-02,  2.9445579e-02, ...,
          -5.1231314e-03, -2.9090829e-02, -2.8257966e-02]]]],
      dtype=float32), array([[[[ 0.00688543,  0.02613619, -0.03079872, ...,  0.01459148,
           0.02179022, -0.04081403],
         [ 0.04506595, -0.00809902, -0.03012348, ..., -0.02840548,
           0.0492401 ,  0.01458311],
         [-0.01458128,  0.0449672 ,  0.02287069, ..., -0.01511727,
          -0.02521144,  0.03269901],
         ...,
         [-0.02743504, -0.01301449,  0.0004992 , ..., -0.01783819,
          -0.02047618,  0.00776548],
         [-0.01877733, -0.04223151, -0.03130023, ..., -0.020681  ,
          -0.04683091,  0.0055038 ],
         [-0.03181034, -0.02672157,  0.01442333, ...,  0.02872873,
           0.0080783 , -0.03809471]],

        [[ 0.01255825,  0.03613948, -0.02999133, ..., -0.01105798,
           0.00794362, -0.0390447 ],
         [-0.00856701,  0.00976813,  0.01146085, ...,  0.0163759 ,
          -0.02289153, -0.01261887],
         [ 0.00590767, -0.02325511,  0.03729314, ..., -0.02947943,
          -0.02715399,  0.01764173],
         ...,
         [ 0.03795312, -0.0191088 ,  0.023238  , ...,  0.00782004,
           0.01387526, -0.0464923 ],
         [-0.03480192, -0.02112579,  0.03875331, ..., -0.01586703,
          -0.01939324,  0.00379444],
         [-0.0184868 , -0.01798405,  0.03495056, ..., -0.00437598,
          -0.01691099, -0.01624686]],

        [[ 0.03684385, -0.03671639, -0.04974756, ...,  0.02775659,
          -0.00524509, -0.03746474],
         [ 0.03960369, -0.00171511, -0.00496398, ...,  0.00164628,
           0.03772683,  0.00061278],
         [-0.01300083,  0.02011915,  0.00803382, ..., -0.04208602,
          -0.02590594, -0.0150842 ],
         ...,
         [-0.05004523, -0.00233177, -0.00912528, ...,  0.00708984,
           0.05276992,  0.01991291],
         [-0.05204609,  0.0569079 , -0.0288045 , ...,  0.00980709,
          -0.05376537,  0.02055016],
         [ 0.03211906,  0.05312886, -0.00281017, ...,  0.04256432,
          -0.01730145,  0.03919016]]]], dtype=float32), array([[[[-0.0391867 , -0.0180403 , -0.00256142, ...,  0.03297805,
           0.02172004, -0.01717289],
         [ 0.00551428,  0.02046539, -0.01190551, ...,  0.01565893,
          -0.03544045, -0.00935789],
         [-0.02093369,  0.05608944,  0.02918256, ...,  0.05110661,
          -0.02708112, -0.02668848],
         ...,
         [ 0.02461432, -0.01662575,  0.03138826, ..., -0.02970242,
          -0.03909415,  0.00337838],
         [-0.0446964 ,  0.02163889, -0.00578011, ...,  0.00385379,
          -0.02911195,  0.04057612],
         [ 0.02161328, -0.00614013, -0.00923805, ..., -0.0373325 ,
           0.00164968,  0.05060137]]],


       [[[-0.02522632,  0.0244936 ,  0.03215376, ..., -0.0327905 ,
           0.00438255, -0.00367966],
         [ 0.02578101, -0.00621558, -0.02475665, ..., -0.0004192 ,
          -0.02391498, -0.00018923],
         [ 0.04231235,  0.0531323 ,  0.01160633, ...,  0.03616595,
          -0.02585099, -0.00988813],
         ...,
         [-0.04921869,  0.02334226, -0.01571149, ..., -0.0381586 ,
          -0.01339654, -0.00368062],
         [ 0.02745989, -0.00868479,  0.00094447, ..., -0.02723902,
           0.00270966, -0.04290302],
         [-0.00985666,  0.00221656,  0.0547087 , ...,  0.0340596 ,
          -0.02934406, -0.02005522]]],


       [[[-0.00696676,  0.00055555,  0.00038848, ..., -0.02726924,
           0.04302194, -0.03254059],
         [-0.00958342, -0.00398674,  0.05708809, ...,  0.04127396,
          -0.01974818,  0.02808452],
         [-0.05132353,  0.00983079, -0.03364148, ..., -0.03209685,
          -0.01506475, -0.02329987],
         ...,
         [-0.04763919, -0.01077537, -0.00213503, ...,  0.05531097,
           0.03756045,  0.01935026],
         [ 0.00192231,  0.06170239, -0.00670581, ..., -0.012156  ,
           0.0265858 ,  0.00739843],
         [ 0.02488879, -0.0126458 , -0.03551678, ..., -0.00648741,
          -0.02145904,  0.00904405]]]], dtype=float32), array([[[[ 0.00156657, -0.02893143,  0.03656496, ...,  0.00306752,
           0.04277752,  0.04637482],
         [ 0.05104493,  0.06816839, -0.05715744, ..., -0.06119078,
           0.00097072, -0.00771941],
         [ 0.00908216, -0.02130989,  0.02299037, ..., -0.03560061,
           0.05017182, -0.0547209 ],
         ...,
         [ 0.02352538, -0.01518873,  0.01769   , ...,  0.05075013,
          -0.02683169, -0.03845472],
         [-0.02732421,  0.02432954,  0.03142777, ...,  0.04364791,
          -0.04250728,  0.01727427],
         [-0.01741271,  0.04476508,  0.01525741, ..., -0.04955146,
           0.05154169, -0.00234688]]]], dtype=float32), array([-6.06318470e-03, -3.00805154e-03, -6.50456734e-03, -1.42085133e-02,
       -5.26522333e-03, -1.28050745e-02,  4.39793710e-03,  3.06857750e-03,
       -7.96079356e-03,  2.24312884e-03,  3.35548236e-03, -1.07487466e-03,
       -4.33124555e-03, -1.51954368e-02, -2.34090979e-03, -5.05070202e-04,
       -5.51879685e-03, -5.44967270e-03, -1.15617579e-02, -1.50061594e-02,
       -5.62847871e-03,  5.79809723e-03, -6.04410842e-03, -3.30346730e-03,
       -4.87526646e-03, -1.83526222e-02, -1.17698144e-02,  2.14510784e-03,
       -8.09884723e-03, -5.21645742e-03, -7.60832895e-03, -6.40739268e-03,
        1.24816594e-04,  2.80618225e-03, -7.79152429e-03, -5.69699658e-03,
        2.54228851e-03, -1.73625406e-02, -1.41730672e-02, -6.73989905e-03,
       -7.76661513e-03,  2.08119140e-03, -5.39841224e-03,  1.58420466e-02,
       -2.81286892e-03, -6.38256874e-03, -5.15324669e-03, -4.64763585e-03,
        4.49241372e-03, -1.43499440e-02,  1.16621284e-03, -1.84088480e-03,
       -6.28711889e-03, -3.69893177e-03,  3.41000012e-03, -7.34981243e-03,
       -4.69875988e-03, -1.65749509e-02, -1.85692236e-02, -6.61890581e-03,
       -6.70948625e-03, -7.60461576e-03, -8.08634236e-03, -2.33804458e-04,
       -1.80682410e-02,  1.93436525e-03, -9.71840788e-03, -2.69651064e-04,
        5.26122656e-03, -5.33981016e-03, -8.02791398e-03, -9.45266709e-03,
       -1.07492954e-02, -2.18061148e-04, -6.12677354e-03, -3.38246813e-03,
       -8.72878172e-03, -9.38889571e-03, -5.88174863e-03, -8.71822797e-03,
       -1.50445243e-02, -1.48324447e-03,  5.82707347e-03, -2.13744696e-02,
        3.84303741e-04, -3.05033136e-05,  2.34592031e-03,  1.44091574e-03,
       -1.03062894e-02, -1.08288564e-02, -5.80459973e-03, -2.21631955e-03,
       -4.07263171e-03, -8.47097673e-03, -8.58000945e-03, -7.91958254e-03,
        1.07919229e-02, -8.51233862e-03, -5.70173748e-03, -4.93514305e-03,
        4.46474226e-03, -2.85754260e-03, -1.26620885e-02, -4.80957795e-03,
       -4.42846306e-03, -9.33927111e-03, -2.18542689e-03, -2.00838335e-02,
       -9.27637704e-03, -8.61242414e-03,  1.11002277e-03, -2.39156443e-03,
       -1.13781253e-02,  2.44847545e-03, -1.50397783e-02, -3.26450751e-03,
       -9.83376708e-03, -3.31630837e-03,  3.06469185e-04, -5.74447401e-03,
       -1.18475445e-02, -3.65691376e-04, -5.60284732e-03, -1.03605501e-02,
       -1.05714370e-02, -6.81110541e-04, -1.65078733e-02,  4.02073981e-03,
        4.55218076e-04, -1.78529799e-03, -2.25073937e-03, -9.60490387e-03,
       -1.18478937e-02, -1.50076896e-02, -7.84218963e-03,  2.66637653e-03,
       -1.94145367e-02,  1.51043257e-03, -1.83870587e-02, -1.54085010e-02,
       -5.58179803e-04, -1.08849267e-02, -1.49172125e-02, -1.53512345e-03,
       -8.85132421e-03, -8.85655079e-03,  8.42901412e-03, -1.26268957e-02,
       -1.14325369e-02, -6.16002246e-04, -4.35428414e-03, -3.92936449e-03,
       -5.23354067e-03, -7.96058122e-03, -6.78979699e-03, -1.21380789e-02,
       -6.55476542e-05, -1.66667486e-03, -5.00335824e-04, -6.36773091e-03,
       -1.99812055e-02, -5.34025952e-03, -5.59371663e-03, -2.48917919e-02,
       -4.49453527e-03, -1.82419512e-02, -1.47365024e-02, -7.34484708e-03,
       -1.48458611e-02, -1.20154982e-02, -7.95596093e-03, -5.06324926e-03,
        1.02249463e-03,  8.02522153e-03, -6.27505174e-03,  2.25341110e-03,
        3.42545798e-03, -1.33377630e-02, -3.96439340e-03, -6.20310847e-03,
       -5.22908010e-03, -2.39607738e-03, -9.20439418e-03, -2.45204545e-04,
       -7.89048709e-03, -6.25182642e-03, -8.26898403e-03, -4.27911431e-03,
       -1.02229398e-02, -1.06506599e-02, -8.12223181e-03, -2.59804516e-03,
       -8.94206204e-03, -8.86744633e-03, -3.68901435e-03, -6.50929101e-03,
       -3.96903697e-03, -1.40727507e-02,  3.42241651e-03, -8.43117665e-03,
       -1.49483727e-02, -1.15354089e-02, -1.51073104e-02, -4.98280441e-03,
       -1.15430309e-02, -8.42871517e-03, -6.93544716e-05, -1.25319511e-02,
       -9.06494504e-04,  2.84527126e-03, -1.29575944e-02, -5.30897500e-03,
       -9.81323607e-03, -5.85431512e-03,  2.53022695e-03, -1.21837500e-02,
       -2.30413526e-02, -8.07101093e-03,  1.49595540e-03, -1.03409868e-03,
       -2.21147146e-02, -2.78358953e-03, -9.25322471e-04, -2.26663495e-03,
       -4.83284751e-03,  9.93839698e-04, -1.59847885e-02, -1.04287022e-03,
       -8.39398056e-03, -7.81370979e-03, -1.03014614e-02, -3.37632187e-03,
        2.23306846e-03,  7.31149397e-04, -8.61780904e-03, -1.38572874e-02,
       -3.27665010e-03,  3.05627706e-03, -1.29717095e-02, -4.78377799e-03,
       -2.04343945e-02, -1.28393993e-02, -1.10970866e-02, -3.04508558e-03,
       -4.21179179e-03, -1.35389166e-02, -1.06082596e-02, -4.76208655e-03,
       -6.99746795e-03, -1.94800775e-02, -3.66372289e-03, -2.84739188e-03,
       -1.27040260e-02, -1.99694484e-02, -1.49596878e-03, -1.36268409e-02,
       -2.03243997e-02, -6.13648305e-03, -9.07455944e-03, -1.39543251e-03,
       -8.66054185e-03, -9.94537864e-03,  5.58656233e-04,  9.62849800e-03,
       -7.38423131e-03,  4.23221383e-03,  1.26948173e-03, -1.32548288e-02,
       -1.26278475e-02, -1.28100356e-02, -1.32768210e-02, -8.71300697e-03,
       -2.58218450e-03, -1.87568727e-03, -1.01899402e-03, -1.12909311e-02,
       -3.16622597e-03, -8.79329350e-03, -7.15430267e-03,  6.33995223e-04,
       -1.47674317e-02, -1.59700830e-02, -1.26772886e-02, -6.79323869e-03,
        2.52811238e-03,  4.10008617e-03, -1.74982026e-02,  2.95319594e-03,
       -1.64390216e-03, -9.88655910e-03, -1.67934448e-02, -1.85631216e-02,
        1.03163125e-03, -1.18707411e-03, -5.24489500e-04, -1.73802786e-02,
       -6.90263137e-03,  3.05938628e-03, -7.89505523e-03, -8.42135213e-03,
       -1.44593436e-02, -8.95054429e-04, -9.57510993e-03, -1.52750630e-02,
       -3.39363702e-03, -8.20879079e-03, -3.90723674e-03, -5.06699830e-03,
        4.64807358e-03,  3.29739810e-03, -5.51834982e-03, -1.49409110e-02,
       -2.10239813e-02, -1.47690540e-02, -9.23270546e-03, -8.58823489e-03,
       -3.02278844e-04,  3.50770331e-03, -5.05860476e-03, -9.92236100e-03,
       -3.26958369e-03, -1.84738114e-02, -1.22352261e-02, -8.71167611e-03,
       -9.99554433e-03, -1.45609342e-02, -1.01509131e-02, -6.45049009e-03,
       -9.84597113e-03, -5.29809529e-03, -2.79349764e-03, -1.56876147e-02,
       -4.76249043e-05, -1.17403930e-02, -2.31792382e-03, -8.62193480e-03,
       -1.01139471e-04,  7.83035241e-04, -5.96441422e-03, -8.79820995e-03,
       -2.15136241e-02, -1.76116619e-02,  1.13416603e-03, -2.90639699e-03,
       -6.57054270e-03, -4.64953249e-03, -6.19808445e-03, -6.02933997e-03,
       -2.39536222e-02,  6.41440554e-03, -1.22420322e-02, -1.46357259e-02,
       -2.23835558e-03, -2.28116242e-03, -4.27397201e-03, -4.07113694e-03,
       -3.37297376e-03, -1.61216762e-02, -1.06204220e-03, -2.72769504e-03,
       -4.21835575e-03, -6.64634630e-03, -9.24484711e-03, -4.26220987e-03,
       -9.84917395e-03, -1.63127352e-02, -1.11424169e-02, -2.00124364e-02,
       -9.80983488e-03, -1.27533730e-02,  7.64522608e-03, -1.11907888e-02,
        1.37605262e-03, -3.21693905e-03, -3.42838559e-03, -4.28501330e-03,
       -5.99947572e-03, -4.92580514e-03,  2.36497354e-03, -4.80604498e-03,
       -1.70019660e-02, -1.97947938e-02, -6.33309409e-03,  8.88994764e-05],
      dtype=float32), array([ 0.6368157 , -0.78077984, -1.104554  ,  0.44373104,  0.99013233,
       -0.42967555,  0.48042142, -1.1530753 , -0.9873502 , -0.66842765,
       -0.7966014 ,  0.4854771 ,  0.7476649 ,  0.82571125,  0.5465549 ,
        0.8153939 , -1.1693377 , -1.0369769 ,  0.574184  ,  0.34093133,
       -1.0582186 , -0.97335243, -0.91488475, -0.75203633, -0.81935763,
       -0.5794012 , -0.75872767, -0.9418396 , -1.327041  , -0.37807867,
       -0.3845564 ,  0.43902698, -0.46070603, -0.71976393,  0.95030373,
       -0.6688985 ,  0.77825636,  1.0976182 ,  1.1735493 ,  0.83468425,
        0.5401047 ,  0.5326362 , -0.48109543, -0.53869605, -0.86374307,
        0.864194  ,  0.5465002 ,  0.97956777, -0.18412456,  1.162642  ,
       -1.0629407 ,  0.11263238, -0.6770876 ,  0.70350087, -1.3572328 ,
        0.95590746,  0.7831851 ,  0.38933656, -0.62374467,  0.60467875,
       -0.635905  ,  1.0311534 ,  1.4265552 ,  0.97333825,  0.9770265 ,
       -0.16731746,  1.1335804 , -0.47266138, -1.0151688 ,  0.2024856 ,
        0.9692427 , -0.9792037 , -0.5396206 ,  0.29115307, -0.6858027 ,
        1.3479043 ,  1.0387295 ,  0.66272134,  1.0105728 ,  0.7757472 ,
        0.7293858 , -0.8312407 , -0.2221169 , -1.1143581 , -0.8645635 ,
       -0.79161984,  1.1930381 ,  0.7839177 , -0.92822367, -0.96171737,
       -0.58617616,  0.95171404,  0.69979656,  1.092969  ,  1.2892829 ,
        0.66437715, -0.7234166 ,  1.1368626 ,  0.7532603 , -0.9021958 ,
       -0.30213386,  1.2641853 , -0.59176856,  0.8785791 ,  0.48694003,
        0.12467199, -0.41604936, -0.9138367 , -0.6085072 ,  0.3586882 ,
       -0.592984  ,  0.9454538 ,  0.68236494, -0.6690249 ,  0.9162402 ,
       -0.7695471 , -0.82896644,  0.42432454, -0.56064665, -0.5589376 ,
        0.9926113 , -0.53761375,  1.1450498 , -0.613316  ,  0.9994713 ,
       -0.7016824 ,  0.7404025 ,  1.0766367 , -1.2633972 , -0.43210545,
       -0.59952915,  1.3037864 ,  0.7184703 ,  0.43666142,  0.57138103,
        0.5993566 ,  0.5374971 ,  0.6452466 ,  1.3303832 ,  1.1865454 ,
       -0.42354932, -0.8681932 ,  1.3392372 , -0.9830607 ,  0.9580372 ,
       -0.71002924, -0.7613386 , -0.77413666,  0.709748  ,  0.8984774 ,
        1.4376922 ,  0.56756514,  1.0511181 , -0.90322363, -0.7059229 ,
        0.5992051 ,  0.9224207 ,  0.8924185 , -0.32438964, -1.0334468 ,
        0.71805656, -0.35922527, -0.42869294,  0.45233262,  1.0361654 ,
        0.8635288 ,  0.3367812 , -0.4937274 , -0.83764946,  0.19909959,
        1.3121191 , -0.98162866,  0.6033627 , -0.8050148 ,  1.0905414 ,
       -0.74108505, -0.3089526 ,  0.8227085 ,  0.69226515, -0.86417115,
        0.4157859 , -0.6139699 , -0.31114972, -0.4200775 , -0.7032357 ,
        1.131049  ,  0.44074568, -1.5120238 ,  0.8594184 , -0.8844458 ,
       -0.58278304,  0.38312522, -1.039789  , -0.83348966, -0.71498203,
       -0.40123335, -0.43190584, -0.6785225 ,  0.60773075,  0.5430685 ,
        0.69221854,  1.0675347 ,  0.7025939 , -0.71462834, -0.25707975,
        0.47820437, -0.3287223 , -0.01484436,  1.0373455 , -0.56455463,
        0.26315662,  0.7919542 , -0.84481084, -0.66521335,  0.5987861 ,
       -0.01562978,  1.0136546 ,  0.29488206,  0.7179655 ,  0.30692667,
        0.77017546,  0.44878462, -0.7220943 ,  0.6343121 ,  0.66229075,
        0.79858387,  0.89757586, -0.5577949 , -0.60288244,  0.70448023,
       -1.353449  ,  0.4770722 , -0.97271866,  0.60416424,  1.2960266 ,
        0.2777044 ,  1.3323466 ,  0.5090853 ,  0.710085  ,  0.87742096,
        0.8514632 , -0.93126416, -0.7436334 ,  0.3628266 ,  0.8596858 ,
        1.1468055 ,  0.5212603 , -0.93811846,  0.7817169 ,  1.07606   ,
       -0.7442193 , -0.9505001 ,  0.4368146 ,  1.3087697 ,  0.7029683 ,
        0.6171678 ,  1.2422682 , -0.72003984,  0.79444146, -0.74426526,
        0.33502638,  0.35666373, -1.0057504 ,  0.32906643, -0.60360885,
       -0.8607089 , -0.7277788 ,  0.87134874,  0.87661237,  1.0079309 ,
        0.7359368 , -0.5525783 , -0.9781778 ,  0.7164794 , -0.35668564,
        0.6679148 ,  0.39133286,  0.18912771,  0.97739804, -0.69605374,
        0.95962065,  1.3910621 , -0.6468424 ,  1.1690656 , -0.84242666,
       -0.836531  ,  1.206706  , -0.88109297, -0.39927062, -0.9702386 ,
        1.2612511 ,  0.6602736 ,  0.99397945, -0.6475298 ,  0.9091328 ,
       -0.6080356 ,  0.3429193 , -0.7334156 , -0.89267635, -0.48439106,
        0.6397976 , -0.6864503 , -0.9464567 ,  0.58883756,  0.86418045,
       -0.6839726 , -0.95508283, -0.58352935, -0.56319267, -0.7451088 ,
       -0.63438   , -1.1153555 ,  0.42551348,  0.97727644,  0.741539  ,
        0.65342975,  0.56226665, -0.76896834,  0.55039114,  0.4819916 ,
        0.85080284,  1.258654  , -0.16504203,  0.7788819 ,  0.76607615,
        0.65733314,  1.0782175 , -0.5371192 , -0.8233019 ,  0.35431567,
       -0.55381274, -0.62311023, -1.1678535 ,  0.6443007 ,  0.55146253,
       -0.6254533 ,  0.7855339 ,  0.82600075, -0.7036994 ,  1.1406114 ,
       -0.86821234,  0.3939664 , -0.79611087,  0.68445116, -0.36122558,
        0.9141416 ,  0.5053277 ,  0.4824853 ,  0.7208194 ,  1.0223877 ,
       -0.7634632 , -0.70881325,  0.30202413,  0.9887484 ,  1.2308232 ,
       -0.9009222 ,  0.85995626,  1.0409756 ,  0.34924   ,  1.195114  ,
        0.48727146, -0.70040184,  0.99540174,  0.0436713 ,  0.8322371 ,
       -0.9096406 , -0.73086256,  0.9922898 ,  0.5484334 ,  0.80632097,
        0.74901164, -0.9742161 , -0.6287809 , -0.91456026, -0.6429299 ,
       -1.1970433 , -0.4917051 ,  1.0525658 , -0.8762946 ,  0.69249314,
        0.66218644,  0.877702  , -1.0036923 , -1.1178637 ], dtype=float32), array([ 5.153361 , 10.461093 , 15.044227 ,  4.1164494,  7.5374093,
        3.9713228,  5.0518885,  9.513625 , 15.0776415, 11.99331  ,
       11.847353 ,  4.1432385,  5.7537475,  5.6784797,  4.1118894,
       12.977307 , 13.539531 ,  8.170286 ,  3.0549202,  5.791061 ,
        8.653526 , 13.956286 , 17.95898  , 16.718094 , 12.279397 ,
        8.229477 ,  4.52117  , 13.399509 , 20.842745 ,  9.37384  ,
        5.0639596,  3.7036176,  6.299579 ,  5.12099  ,  5.652348 ,
        6.0262756,  6.3549724,  5.9774995,  7.151998 ,  4.6843147,
       11.684332 ,  5.661979 ,  5.627856 ,  3.6037948,  9.215984 ,
        8.363371 ,  7.5147514,  8.866125 ,  3.4612176,  9.074653 ,
        9.764306 ,  4.328657 ,  8.646533 ,  4.344091 , 11.107017 ,
       11.780231 ,  2.1454384,  4.4726067, 13.263668 ,  8.293195 ,
       10.214607 ,  5.7571983,  9.174106 ,  5.673905 ,  7.7669234,
        1.9001265,  4.552543 , 10.601981 , 16.074486 , 10.252593 ,
        6.3871293,  6.120899 ,  6.5969133,  5.3034716,  7.799052 ,
       15.87329  ,  9.074837 , 10.096831 ,  8.49537  ,  5.786932 ,
        7.745039 ,  9.920892 ,  6.6665645,  5.9686327,  9.094607 ,
       10.293551 ,  6.1926813,  5.545205 , 14.375427 , 15.204068 ,
       12.48217  ,  6.6596484,  6.0696616,  5.396559 ,  7.7706714,
        6.902988 ,  7.179774 ,  5.3955746,  6.4508934, 12.309806 ,
        4.9336495,  7.870469 ,  6.114932 ,  6.8133802,  2.9917378,
        5.207392 ,  8.065806 ,  8.00867  ,  9.617051 ,  1.9096036,
        9.124418 , 10.210327 ,  2.8797293,  6.866812 ,  4.5091414,
        8.965354 ,  7.5505395,  1.4587182,  6.317359 ,  5.574343 ,
        5.971184 ,  7.3650937,  8.593477 , 11.335712 ,  7.7982764,
       11.549423 ,  4.092125 , 11.995967 , 15.238441 ,  2.863239 ,
        5.776392 ,  7.199657 ,  5.4990444,  4.269999 ,  2.9369104,
        2.9518652,  6.855526 ,  3.5278425,  5.936008 ,  5.7043476,
        7.166855 ,  4.838805 ,  7.055109 , 17.228508 , 12.509878 ,
       10.213423 ,  6.3883753,  7.3018904,  3.4557052,  6.814538 ,
       10.300232 ,  4.730798 , 11.308538 ,  8.579136 ,  7.4320655,
        7.8560066,  9.24943  ,  4.3611693,  4.8685045,  6.5754457,
        5.714193 ,  8.854635 ,  9.64722  ,  4.1953278,  6.9202504,
        4.3410563,  2.7534974,  5.2175756, 10.185057 ,  2.490318 ,
        8.193123 ,  6.332597 ,  3.47532  ,  6.3200765,  6.2432885,
       14.507591 , 11.002761 ,  5.5898194,  5.048029 ,  6.873572 ,
        2.0242946,  5.365938 ,  2.2824647, 13.655067 ,  3.9760082,
        4.634729 , 14.032381 , 20.621761 ,  9.671834 , 17.592003 ,
        6.7669683,  5.5263557, 15.898223 ,  8.250446 ,  9.109099 ,
        3.5611444,  7.2854605, 10.055672 ,  6.1898603,  5.3858747,
        5.2181425,  3.6102886,  6.2362766,  6.4609256,  2.3257785,
        6.3922143,  3.8289793,  1.6614594, 10.479373 , 13.676436 ,
        4.0223823,  7.208681 ,  7.7869844, 10.210798 ,  3.255526 ,
        3.1497655,  7.358404 ,  5.922731 ,  3.9399242,  4.197999 ,
        7.1876054,  4.533334 , 10.928848 ,  7.7476673,  6.5287457,
        5.0175886,  5.9839616,  5.7212305,  6.5462775,  3.1250715,
       12.1720085,  9.80848  ,  8.537377 ,  5.9643517,  8.597087 ,
        7.1208553, 10.901263 ,  6.0226035,  5.3881307,  9.154025 ,
        5.5843782,  9.369761 ,  7.828073 ,  5.3813577,  6.0354853,
       15.145086 ,  2.176437 , 13.245323 ,  4.251142 ,  6.2639256,
        7.9762135,  9.846231 ,  4.1143208,  9.05952  ,  9.709814 ,
       10.073694 ,  6.8732195,  9.101654 ,  5.4974627, 10.466475 ,
        4.6302056,  3.734386 ,  9.893996 ,  7.843694 ,  5.3168154,
        8.518636 ,  7.3418417,  5.813201 ,  4.024436 ,  4.326115 ,
        7.6232457,  7.963293 , 14.669978 , 10.700654 ,  5.46409  ,
        7.1631885,  3.2628398,  6.3606057,  6.1436534,  7.2208815,
        5.3834515,  7.0325284, 11.381199 ,  8.013786 , 14.09194  ,
       12.3040085,  9.297404 , 12.129724 ,  3.5523868, 16.909468 ,
       11.122283 ,  6.07378  ,  9.207793 ,  3.295812 ,  7.143139 ,
        4.254651 ,  7.685293 ,  8.224762 , 13.737434 ,  3.4980197,
        3.7785678,  3.66929  ,  8.131601 ,  6.2419233,  6.085339 ,
       16.75677  ,  9.83198  , 11.287092 ,  7.4101753,  8.720088 ,
        6.994519 ,  8.79441  ,  2.4885178,  4.9369245, 10.721656 ,
        4.6979017,  4.3378234, 12.058808 ,  5.132292 ,  4.6230254,
        5.4739666,  8.308347 ,  2.4239728,  4.878287 ,  4.725277 ,
        4.993453 , 10.36393  , 10.071406 , 10.003897 ,  2.7013772,
        9.962892 ,  9.668311 , 14.324473 ,  6.583889 ,  1.637262 ,
        4.8494473,  5.60013  ,  6.675427 ,  8.81287  ,  6.673196 ,
       10.224641 ,  4.5641956,  5.8311353,  4.85632  ,  9.177399 ,
        4.1536937,  6.481847 ,  6.109935 ,  4.3780646,  9.861036 ,
        5.7836337, 13.476411 ,  7.1858463,  5.1370287, 14.648852 ,
       20.789646 ,  7.2074585,  4.033915 ,  7.703086 , 10.456478 ,
        5.8887477,  5.1468644,  6.7036767,  2.9337769,  9.714613 ,
       16.186487 , 11.633759 ,  9.952162 ,  5.359196 ,  3.6978168,
        3.7204785, 12.235346 ,  9.706185 , 14.430788 ,  4.6116476,
       17.22649  ,  8.546291 , 10.894219 , 14.912088 ,  4.310582 ,
        8.406825 ,  6.673072 , 16.888924 , 11.764654 ], dtype=float32), array([-9.64399800e-03, -1.38305202e-02, -1.11579187e-02, -9.21455119e-03,
       -4.05982789e-03, -1.09769050e-02, -3.90124228e-03, -2.67813355e-03,
        9.74971554e-05, -1.10367462e-02, -1.07190805e-02, -5.06329350e-03,
       -1.54396594e-02, -1.92286723e-04, -7.29701482e-03,  4.46141884e-03,
       -1.88951809e-02,  7.13231449e-04, -7.43514346e-03, -5.94712561e-03,
       -1.36659555e-02,  6.97252527e-03, -7.04933750e-03, -1.34789692e-02,
       -7.94393104e-03, -2.77326163e-03,  7.25854281e-03, -1.30691938e-03,
       -8.60513654e-03,  4.00339668e-05, -1.57967373e-03, -3.91036784e-03,
        1.67245581e-03, -1.04722772e-02, -6.30096393e-03, -1.09533165e-02,
       -6.18935190e-03, -1.37077607e-02,  2.48637958e-03, -1.11437077e-02,
       -9.29106586e-03, -8.59611016e-03, -7.35881459e-03, -4.39131493e-03,
        2.33639008e-03, -9.43586510e-03, -8.73722881e-03, -1.11686923e-02,
       -7.21314223e-03, -9.07254126e-03,  2.97872256e-03, -1.02478303e-02,
        3.43299645e-04,  9.51425987e-04, -6.80680294e-03,  3.13380919e-03,
       -1.09606022e-02, -9.80253797e-03, -3.88733996e-03, -9.62899765e-04,
       -1.33806430e-02, -7.28542451e-03, -8.91121104e-03, -1.67334862e-02,
       -1.48542169e-02, -8.67009442e-03, -8.58875457e-03, -8.28032847e-03,
       -1.55832060e-02, -6.71869656e-03, -1.39931627e-02, -3.68824834e-03,
       -1.34098064e-02, -6.26334629e-04, -1.49147799e-02, -2.12208219e-02,
       -5.50198462e-03, -9.28177871e-03, -2.33410508e-03, -8.81605130e-03,
        7.50059960e-03, -1.44971395e-02, -5.26149012e-03, -1.98026677e-03,
        7.22261379e-03, -6.49929326e-03, -1.95805170e-03, -3.66988848e-03,
       -1.68100942e-03, -7.88768567e-03, -1.13682114e-02, -4.18113777e-03,
        2.14009616e-03, -1.08620431e-02, -4.82498808e-03, -4.96575236e-03,
        3.80720524e-03, -2.16640383e-02, -1.57950055e-02, -1.29435780e-02,
       -6.68681273e-03, -1.18741384e-02, -1.90044362e-02,  1.32064580e-03,
        3.07762367e-03, -3.11660557e-03, -7.07663083e-03, -6.85688108e-03,
        1.38047457e-04, -3.64185963e-03, -1.13784233e-02, -1.03589124e-03,
       -3.64431902e-03, -1.71361538e-03, -7.96485168e-04, -1.30553758e-02,
       -1.64901260e-02, -1.40264183e-02, -8.25552084e-03, -2.56002834e-03,
       -1.41593367e-02,  2.26594717e-03, -5.68601536e-04,  1.13302399e-03,
        1.33696152e-03,  1.46205747e-03, -3.04875663e-03, -1.42809264e-02,
        8.37512128e-03, -1.03466744e-02, -3.71099613e-03,  9.79325920e-03,
        1.75711652e-03, -1.02631804e-02, -9.99795180e-03, -5.36866765e-03,
        3.16715683e-04, -9.95730050e-03, -2.90650642e-03, -1.13423765e-02,
       -4.23306460e-03, -2.29050778e-02, -9.39373276e-04,  2.75753046e-05,
       -2.62275599e-02,  3.75639019e-03, -4.81723528e-03, -8.33744742e-03,
       -9.59038269e-03, -9.13325977e-03, -1.26061328e-02, -2.96129822e-03,
       -7.04321591e-03,  3.47343856e-03, -1.62490811e-02, -8.33676104e-03,
        4.07691952e-03,  1.35425269e-03,  1.31154165e-03,  3.95182427e-03,
        1.80277042e-03, -2.80108899e-02, -9.81078018e-03,  7.85912736e-04,
        4.34331782e-03, -6.56873127e-03,  1.99155440e-03, -1.08322399e-02,
       -1.18537676e-02, -4.63383924e-03, -6.79867622e-03, -1.07442308e-02,
       -4.28582495e-03, -1.76533044e-03, -5.63298305e-03, -2.18677009e-03,
       -1.27508836e-02, -1.49504310e-02, -7.04949629e-03, -1.20357517e-02,
        4.46097041e-03, -6.46380591e-04, -1.51364249e-04,  3.96684697e-03,
       -1.28862029e-03, -4.14702715e-03,  4.09285247e-04, -2.16412004e-02,
       -4.45598084e-03, -1.05061857e-02,  6.23354688e-03, -7.56517472e-03,
       -9.99190193e-03,  8.69127223e-04, -9.11835377e-05, -1.17340079e-02,
        6.39988983e-04, -1.72278639e-02, -2.73872982e-03, -8.11796635e-03,
       -7.02823233e-03, -7.78154284e-03,  1.36578856e-02, -4.18289937e-03,
       -6.80231350e-03, -2.13401043e-03, -1.31047908e-02, -1.09543344e-02,
        2.86886445e-03, -5.15740598e-03,  3.81199853e-03, -2.46077292e-02,
       -1.70621425e-02,  3.81812395e-04, -4.73784516e-03, -8.92220996e-03,
        1.42103864e-03, -1.09698577e-02, -1.02484776e-02, -7.41536636e-03,
       -1.04483245e-02, -5.05382102e-03, -6.83131395e-03, -1.20813865e-03,
       -4.82689962e-03, -1.87166631e-02, -3.60406167e-03, -1.37952417e-02,
       -6.15169900e-03, -1.76534206e-02, -3.51078622e-03,  5.20469202e-03,
       -1.51281543e-02, -6.55626785e-03, -7.07919197e-03, -9.95730422e-03,
        5.71548444e-05, -8.70077289e-04, -1.96062047e-02, -5.97897731e-03,
       -6.46008831e-03,  3.77338706e-03, -7.07484316e-03, -1.48556679e-02,
       -1.16390013e-03, -4.77681402e-03,  2.75243679e-03, -1.44176297e-02,
       -1.12151750e-03, -2.73794611e-03, -8.93705152e-03,  4.09028353e-03,
       -1.26318214e-02,  9.93055291e-04, -9.62644815e-03, -2.26847380e-02,
       -8.63079540e-03, -6.60647545e-03, -2.30218703e-03, -1.86672825e-02,
       -1.56879351e-02, -5.71554387e-03, -8.42589419e-03, -9.85122402e-04,
       -1.98868550e-02, -7.07123242e-03, -6.37341756e-03, -6.38477132e-03,
       -1.64748393e-02, -3.25926114e-03,  2.08348432e-03, -2.33822851e-03,
       -4.11165226e-03, -1.01609407e-02, -1.20431297e-02, -3.00225918e-04,
       -3.93129699e-03, -3.09068593e-03, -8.22295994e-03, -4.70230263e-03,
       -5.37822768e-03, -1.11415414e-02, -7.80852698e-03, -9.07400250e-03,
        4.37218742e-03, -3.86792328e-03, -3.44059383e-03,  1.33154026e-04,
       -6.70052134e-03, -4.48444393e-03,  1.55629846e-03, -1.18771410e-02,
       -7.54190097e-03, -2.44906708e-03,  5.56294993e-03, -1.62887312e-02,
       -2.83749250e-06,  2.69609876e-03, -9.45642777e-03, -8.87627713e-03,
        3.89649742e-03, -8.09174776e-03, -8.80204048e-03, -1.23754656e-02,
        7.14489433e-04,  1.42120905e-02, -5.49537409e-03, -1.38247211e-03,
       -1.07035665e-02, -1.72009524e-02, -1.69305392e-02,  8.32721218e-03,
       -1.81462653e-02,  3.19229439e-03, -7.06063537e-03, -7.46888574e-03,
       -1.41458362e-02, -1.15263890e-02, -1.41170211e-02, -5.29958124e-05,
        5.38927130e-03, -1.23356432e-02, -8.77466146e-03, -1.98874436e-03,
       -1.02162370e-02, -9.36326757e-03, -9.48900916e-03, -7.76928384e-03,
       -6.10279059e-03, -7.46390875e-03, -8.39724671e-03, -1.71458423e-02,
       -1.55028263e-02, -1.06926449e-02, -1.12797394e-02, -1.18250987e-02,
       -7.09031709e-03, -1.16607780e-02, -7.47369276e-03, -7.05564581e-03,
       -1.86554622e-04, -1.11666797e-02,  2.15585902e-03, -4.90725553e-03,
       -1.74922682e-03, -4.91413567e-03, -1.82102267e-02, -2.13174452e-03,
       -7.62555457e-04, -8.29574559e-03, -6.34785928e-03, -1.68205947e-02,
        2.45862198e-03, -1.59130562e-02, -1.63293176e-03, -4.84785298e-03,
       -1.48194414e-02, -1.11336997e-02, -1.16301803e-02, -6.70083426e-03,
       -6.76684594e-03,  1.86548533e-03, -5.02850953e-03, -7.64043769e-03,
       -6.68500504e-03, -7.51371868e-03, -9.93734971e-03, -6.90847542e-03,
       -4.57848795e-03, -1.27160326e-02, -8.32725130e-03,  4.20985185e-03,
       -3.50214657e-03, -8.60757660e-03,  2.71761767e-03, -2.52839830e-03,
        6.06120564e-03, -7.69620761e-04, -1.11275027e-02, -5.29153924e-03,
       -1.09198680e-02, -2.00031269e-02, -7.25111645e-03, -9.37873218e-03],
      dtype=float32), array([ 0.66087645, -1.0059191 ,  0.68684644, -1.3437194 , -0.784154  ,
        0.6697989 , -0.798208  , -0.9711694 ,  0.40446854, -0.6172867 ,
        0.53320026,  0.9127388 ,  0.9559092 ,  0.8106686 ,  0.445255  ,
       -0.83330345, -1.1721841 , -0.637039  ,  0.44309488, -0.06645428,
        1.1998969 , -0.37022054,  1.3411211 , -0.70441276,  0.83656615,
        0.73518574, -0.93575144, -0.44068667,  0.76128364, -0.5087642 ,
        0.79335624, -0.8001882 , -1.083155  , -0.9920467 , -0.7025865 ,
        0.86550945,  1.1440364 ,  0.49842536,  1.081693  , -0.959653  ,
       -1.1319456 ,  1.1965209 , -0.89928716, -0.7363327 , -0.9689675 ,
        0.47817096, -1.1241422 ,  0.94240487, -0.5593441 , -1.0096498 ,
        0.6731386 ,  0.45865706, -0.63448685,  0.6560805 ,  0.9837965 ,
       -0.5005897 ,  0.20386429, -0.37306032, -0.5498077 , -0.91582847,
       -1.0652465 ,  0.43885672, -0.83801013, -0.59522456, -1.0560672 ,
       -0.6224964 , -0.65340793,  0.09958229,  1.0577445 ,  0.5820511 ,
       -0.7479956 , -0.79009503,  1.2281636 , -0.9443491 , -0.85134333,
        1.1695045 , -0.33002505,  0.94468224,  0.5785345 , -0.960141  ,
       -0.9486322 ,  1.1201391 ,  0.89746356,  0.87044907,  0.30561414,
       -0.5497075 , -0.12360901, -0.66337746, -0.76054794, -0.9185789 ,
        0.5491652 ,  0.93534905, -0.4648208 , -0.7728769 , -0.59213537,
        1.3231244 , -0.6594797 ,  0.12817015, -0.70914346, -0.95937616,
        0.648251  , -0.68326104,  0.8669681 , -0.36339787,  0.6636444 ,
       -0.56626797, -0.82493925, -0.8532923 , -0.26811427, -0.48104915,
        0.5803703 , -0.77780473, -0.783931  ,  0.33156526, -0.2727393 ,
        0.71041685,  0.93217075, -0.70859915,  1.2401694 ,  1.0679227 ,
       -0.6458712 , -0.76901174,  0.8317034 , -0.75714123,  0.22926326,
        1.0449795 , -0.8245941 , -0.5354505 , -0.4600411 ,  0.8805775 ,
       -0.79176676, -0.9348005 , -1.2218043 ,  0.91049224,  0.8288253 ,
       -0.9557108 ,  0.45729485,  1.169098  , -0.51856923,  0.6140467 ,
       -0.94884455,  0.02369883, -0.4016294 , -1.4212602 ,  1.3318349 ,
        0.5579053 , -0.7364907 , -0.4927569 ,  0.36197484,  1.0252405 ,
        0.52361184,  0.55909497,  0.03192761,  0.4952666 ,  0.17969829,
        1.1621264 , -0.5681596 ,  0.68973976, -0.51051116, -0.571487  ,
        0.25929993,  1.0266854 ,  0.64856964, -0.16283806, -0.89755785,
        0.5196813 ,  0.5135525 , -0.52800775, -0.84740174,  0.71856046,
       -1.0890601 ,  0.75096357,  0.87676793, -0.46846566,  0.6837342 ,
       -0.9224721 ,  0.60571766, -0.7165975 , -0.1701341 ,  0.9575061 ,
       -0.73530823, -0.0944382 ,  0.86112404, -0.5923369 , -0.77672327,
        0.66351837, -1.0713075 ,  1.1184374 , -1.1011004 ,  0.91477746,
       -0.72963953,  0.8105592 ,  0.3040489 ,  0.76629704, -0.8071781 ,
       -1.1304567 , -1.0049487 ,  0.364109  , -0.76992136, -0.7389974 ,
       -0.8849502 , -0.5267068 , -1.2871104 , -0.9048827 ,  0.9466703 ,
        0.6181792 ,  0.6301028 , -0.5930128 , -1.0696259 , -0.6853796 ,
        0.26382795, -0.9733477 ,  0.87727964,  0.79362786,  0.574042  ,
       -0.5998048 ,  0.32503816,  0.7007982 ,  1.0670066 ,  1.4428052 ,
        0.3529774 , -0.6876935 ,  0.84554595,  0.1238434 ,  0.2587219 ,
        1.1417464 , -1.0477433 , -0.4037662 , -0.65408987, -1.2688828 ,
        0.6753676 , -0.8442098 ,  0.7372777 ,  1.0447812 ,  0.82892436,
        0.80583656, -0.9603871 , -0.76025826, -0.7165587 ,  0.98551977,
        1.0916655 , -0.91996306,  0.6988268 ,  0.6338112 ,  0.48724824,
       -0.48791403, -0.3585463 ,  1.1055946 ,  0.2507675 ,  1.219544  ,
       -0.400763  , -0.7676144 ,  0.628534  , -0.82402855,  1.1385654 ,
       -0.26349026, -0.3979754 ,  0.20821697, -0.39949346, -1.0904218 ,
        0.4205809 ,  0.5860521 , -0.873958  ,  0.56224656, -0.962637  ,
        0.08906458,  0.48975712,  0.7522245 ,  1.1855686 ,  0.82306135,
        0.71284103, -0.84311074, -0.75796753, -0.48165563, -0.9786504 ,
       -0.59368086, -0.73679626, -0.92633045,  0.60153526, -0.58172166,
        0.45620903,  0.9164711 , -0.8657112 , -1.2773226 ,  0.61771613,
        0.5945538 , -0.9390483 , -0.717823  ,  0.41701546,  0.89103174,
       -0.76757526,  0.65164995, -0.38689938,  0.7766789 , -0.54680043,
        0.9595428 , -0.75775224,  0.64336777,  0.7196654 , -0.41468164,
        1.0879902 ,  0.52286935,  1.0121237 ,  1.0138923 , -0.9868733 ,
       -0.39246503, -0.77782106, -0.5769917 , -0.72772557, -0.9538889 ,
       -0.42696577, -0.3658799 , -1.1772822 ,  0.7791422 ,  0.56201947,
        0.8103638 ,  0.9245244 , -0.552301  ,  0.9179787 , -0.701546  ,
        0.25846738,  0.3892787 ,  0.38514295,  1.211325  , -0.60908777,
        0.77143633, -0.70492244, -0.9166703 , -0.912068  ,  0.64494437,
        0.18943337,  0.64512   ,  0.48642495,  0.4723819 ,  1.1759945 ,
       -0.64545244,  0.41855672,  0.39098966, -0.9229272 ,  1.040009  ,
       -1.1741627 ,  0.49487984, -1.0281804 ,  0.57041234, -0.22478385,
       -1.002683  , -0.6696344 , -0.38893172,  0.7323639 , -0.38665044,
       -0.52860826,  0.75119025, -0.63870835,  0.29799342,  0.61102015,
        0.2801391 ,  0.84581125, -1.0117737 , -0.44517803,  0.56666327,
        0.65548915, -0.8283319 ,  0.7529377 ,  0.49849072,  0.46402562,
       -0.8699214 ,  0.39763823,  0.65592295, -1.1791315 ,  0.8589176 ,
        0.3490243 ,  0.76426655, -0.79854673,  0.6354326 , -0.4190352 ,
       -0.21300349, -0.58488417,  0.6350809 , -1.0865682 , -0.5370822 ,
        0.6896333 , -0.7115719 ,  1.0848333 ,  0.50244623], dtype=float32), array([11.999907 ,  8.489597 ,  3.6494195, 13.685599 , 11.923744 ,
        4.8110404,  8.115614 ,  4.8870792,  7.770532 ,  7.866085 ,
        4.699454 ,  8.9677925,  5.689721 ,  4.714422 , 12.181787 ,
        6.7457075, 16.86342  ,  6.482412 ,  6.414466 ,  3.6896951,
       10.208083 ,  7.2497845, 10.581057 ,  4.169729 ,  8.655906 ,
       10.399302 , 11.4157715,  5.8098536,  5.326533 ,  6.772337 ,
        9.503961 ,  7.6923   , 14.85301  ,  9.967995 ,  6.703975 ,
        8.673395 ,  7.076387 ,  7.3960757,  7.116052 , 14.084873 ,
       22.112621 ,  8.307611 , 13.046779 , 12.544423 , 10.922282 ,
        4.191734 ,  8.472825 ,  3.5366957,  4.258569 ,  9.399344 ,
        4.850692 ,  4.336272 , 12.693686 ,  5.184959 , 14.139491 ,
        7.135456 ,  5.8595333,  5.619926 ,  7.607895 ,  8.367626 ,
       16.090582 ,  7.834953 , 11.510345 ,  3.5958233, 11.440097 ,
        7.3390875, 12.694333 ,  3.0013454,  5.319789 ,  5.0362043,
        4.6013107, 12.415064 ,  9.769754 , 12.551712 ,  8.569805 ,
        8.264944 , 10.277103 ,  4.027475 ,  4.1389003, 13.354079 ,
       10.937598 , 13.456488 ,  5.727375 ,  8.596037 ,  4.135403 ,
        5.9801054,  2.4759283,  5.993445 ,  9.920596 , 11.685224 ,
        4.564324 ,  4.8047056,  4.29429  ,  7.153116 ,  5.206113 ,
       10.803688 ,  7.496922 ,  3.042704 ,  6.304179 , 12.8483515,
        6.0882664,  4.7430983,  8.940446 ,  5.5672574, 10.978147 ,
        7.5387416, 15.739277 ,  7.3394485,  8.413656 ,  6.5320177,
        4.2327657,  6.8521414, 14.914573 ,  4.2658668,  2.9721785,
        5.8249307,  7.8269577, 15.689991 ,  5.332929 ,  4.859569 ,
       13.721869 , 11.32978  , 10.147388 , 14.451353 ,  4.682961 ,
        8.929146 ,  7.5428257,  5.177612 ,  7.4137297, 11.300322 ,
       17.733198 , 10.754652 , 23.810364 ,  6.7747216,  6.1629906,
        7.4890795,  3.7765718, 11.703745 , 11.775001 ,  8.293786 ,
        6.2636514,  1.9256079,  4.2059417, 25.992706 , 15.552538 ,
        6.17098  ,  8.291565 ,  8.732157 ,  6.2957153, 10.1208105,
        4.9151993,  3.5208838,  3.9091227,  7.541611 ,  6.1180887,
       10.446166 ,  9.62005  ,  7.1236567,  6.0591536,  9.142346 ,
        3.1185403,  5.0666275, 11.69224  ,  3.0706193,  6.2248344,
        4.4952703,  5.1585994,  5.582137 ,  9.010442 ,  8.403219 ,
       11.39314  ,  8.975343 ,  4.4079127,  6.85704  ,  4.339331 ,
       11.838038 ,  6.8830247, 14.086361 ,  3.7733943,  7.509872 ,
       12.193013 ,  1.1036937,  6.763076 ,  4.487065 ,  8.693673 ,
        6.8926105,  9.535304 ,  4.605828 , 12.081113 ,  6.558263 ,
       13.3987665, 13.706363 ,  1.8528879,  6.457754 , 14.782927 ,
       15.834624 , 13.540649 ,  2.0635679,  6.0971847,  9.013592 ,
       15.838596 ,  4.6473827, 15.538962 , 13.793066 ,  5.9873366,
        3.7206573,  4.6672773,  5.7752237, 17.117992 , 12.798867 ,
        2.7104464,  6.5518613,  8.492982 ,  6.616241 ,  1.5714648,
        6.9126115,  3.8731391,  8.91068  ,  7.533408 , 10.806236 ,
        3.0306637,  7.854118 ,  3.5468283,  5.778549 ,  4.0684366,
        9.364927 , 15.010571 ,  5.760897 ,  4.4140997, 11.121063 ,
        1.8609939,  6.830747 ,  5.9610558,  4.682006 ,  8.59284  ,
        8.719471 ,  6.1066246,  9.901182 , 10.0924225,  4.908756 ,
       10.60975  ,  9.77332  ,  3.142519 ,  5.1256604,  2.5977688,
        4.510734 ,  7.878722 ,  8.00731  ,  3.1995602, 12.105076 ,
        9.478273 ,  9.121881 ,  6.2580667,  9.429318 ,  6.093927 ,
        2.1504185,  5.4175115,  2.2419572,  6.970781 ,  7.8035197,
       10.612161 ,  2.1216793,  6.4280715,  4.985594 ,  9.55299  ,
        3.4589553,  5.887341 ,  2.3894083,  5.971799 ,  5.0112786,
        7.7081623, 12.161936 ,  9.848668 ,  2.7971385,  8.605116 ,
        4.2580824,  5.1733065,  5.646149 ,  8.729059 ,  8.616445 ,
        5.551813 ,  4.382507 ,  6.493346 , 15.186956 ,  5.57446  ,
        3.5636435, 12.360182 ,  6.3892817,  4.553248 ,  6.9357357,
       12.859273 ,  4.847212 ,  4.290651 ,  4.0615735,  7.8584156,
        3.8075774, 11.429582 ,  4.6817384,  8.110293 ,  5.8855042,
       10.2820425, 10.352552 ,  6.855721 ,  6.600652 , 12.637306 ,
        7.79764  ,  7.7867055, 12.24508  ,  7.306188 , 11.312925 ,
        5.58114  ,  3.3480787, 12.327635 , 12.66854  ,  5.1242213,
        2.2318316, 11.187451 ,  1.7615798,  5.1415734,  9.577103 ,
        3.4585974,  3.3891063,  4.2889085,  8.732223 ,  7.0900784,
        5.639544 ,  1.5023389,  7.8125668, 15.008638 ,  7.5731134,
        4.5885262,  5.695322 ,  4.9921956,  6.870942 , 13.767498 ,
        6.855979 ,  2.168043 ,  1.8506452,  9.827538 , 12.437861 ,
        7.5187283,  5.1521893,  9.506555 ,  2.6155243,  5.893005 ,
       15.811852 ,  6.078783 ,  8.761541 ,  5.0708666,  3.999206 ,
        3.0313797,  5.0440216,  6.576054 , 11.310795 ,  7.0447254,
        3.4149005,  9.607401 ,  9.0305395,  7.8097014,  5.027434 ,
        5.6228447,  9.963664 ,  3.6610744,  8.093397 ,  3.1353166,
        3.9248593,  3.088094 ,  8.574722 , 11.346634 ,  8.556118 ,
        3.6164675,  4.111392 , 10.8658085,  4.014237 ,  5.9512796,
        6.7214756, 10.369036 ,  8.91096  ,  8.901579 ,  8.394714 ,
        4.0847583,  4.404817 ,  8.969246 ,  3.8476946], dtype=float32), array([-3.43925436e-03, -8.29563010e-03, -9.25452355e-03,  4.52781701e-03,
        1.49168661e-02,  1.72141043e-03, -1.32772396e-03, -1.66787468e-02,
       -1.32645210e-02, -1.07015371e-02, -7.60897202e-03, -6.88181119e-03,
       -7.71901291e-03,  2.05646665e-03,  3.61518796e-05, -1.49483047e-02,
       -2.49987585e-03,  1.41537446e-03, -1.07713854e-02, -1.35319971e-03,
       -6.32323930e-03, -6.41083578e-03, -2.11352762e-03, -6.01430517e-03,
       -2.61710468e-03, -1.36584556e-02, -4.89773974e-03, -4.06221859e-03,
       -8.24375823e-03, -6.57649571e-03, -1.90894853e-03,  3.03121837e-04,
       -2.82549346e-03, -8.36132094e-03, -1.02588059e-02, -1.54350215e-04,
        6.09007897e-04, -6.11594087e-03, -7.56062986e-03, -6.62135519e-03,
       -6.95433328e-03, -2.01499043e-03, -5.07111894e-03, -9.54690482e-03,
       -1.08746178e-02, -3.50440829e-03, -3.54411150e-03,  3.19988606e-03,
       -6.25194330e-03, -1.16623268e-02,  9.12825693e-04, -3.44391121e-03,
       -6.07881695e-03, -6.26742432e-04,  3.04399109e-05,  5.82145061e-03,
       -1.45107750e-02, -1.27463918e-02,  1.15891604e-03, -7.88870081e-03,
        2.87989504e-04, -3.50391027e-03, -1.01787578e-02, -1.02159670e-02,
       -1.30491378e-02, -1.34215290e-02, -6.34663645e-03, -2.19714385e-03,
       -2.91936705e-03,  3.73773975e-03,  5.95254311e-03,  4.51594684e-03,
       -1.10190324e-02, -6.96762931e-03, -7.61382747e-04, -1.07178539e-02,
       -6.42242841e-03, -5.02760382e-03,  3.63053026e-04, -9.70933028e-03,
       -9.88208316e-03, -1.26856258e-02, -5.13065606e-03,  6.97601959e-03,
       -1.26719242e-03, -2.60190666e-03, -1.20759045e-03, -1.23975649e-02,
       -8.89979862e-03, -6.61813701e-03, -3.62221780e-03, -6.66157482e-03,
       -4.47729416e-03, -1.34318890e-02, -5.96356019e-03, -2.79073673e-03,
        4.81338007e-03,  2.86081282e-04,  4.97862464e-03, -8.57623108e-03,
       -1.06667131e-02, -3.59516335e-03, -2.00928818e-03, -6.71954546e-03,
        2.25421181e-03, -1.22043006e-02, -4.55651013e-03,  2.02801122e-04,
       -6.68763230e-03, -9.20475088e-03,  4.01351415e-03, -5.51479915e-03,
       -1.21656694e-02, -2.87617510e-03, -4.53235814e-04,  5.22568822e-03,
       -2.56822747e-03, -1.12651661e-02, -5.95218176e-03, -1.40238442e-02,
       -3.08135455e-03, -5.97981177e-03, -1.21647818e-02, -5.94762154e-03,
       -1.26202153e-02, -8.06799810e-03, -6.62683044e-03, -9.34669655e-03,
        2.41507590e-03, -5.10345213e-03, -4.56291204e-03,  2.68806070e-05,
       -6.63033780e-03, -1.60596222e-02, -9.85717122e-03, -3.91248800e-03,
       -1.31079489e-02, -4.35472419e-03,  3.38723417e-03, -3.79677885e-03,
       -7.99484085e-03, -2.90915300e-03, -6.75576832e-03, -1.18909422e-02,
       -1.26002524e-02, -5.63986832e-03, -5.70025900e-03,  3.16989771e-03,
       -8.15645698e-03, -5.67877479e-03,  2.00824090e-03, -4.29273210e-03,
       -5.99050568e-03, -2.38966849e-03, -1.02649890e-02, -8.91753286e-03,
       -5.03064506e-03, -1.97537505e-04, -6.02569804e-03, -3.10813397e-04,
       -5.45593025e-03, -8.83178785e-03, -8.10449384e-03, -5.90783218e-03,
       -9.27156210e-03, -4.93361987e-03, -4.59424173e-03, -1.33225357e-03,
       -3.03053483e-03, -1.51469922e-02,  2.81567057e-03, -8.77933577e-03,
       -8.30584299e-03, -1.76474154e-02, -1.33228593e-03,  1.09317526e-03,
       -4.18066222e-04,  3.37805552e-03, -5.49652195e-03, -3.51675134e-03,
       -2.67137354e-03,  6.48953626e-03, -8.34504887e-03, -1.57886441e-03,
       -1.07439328e-03, -7.52810994e-03,  6.21476164e-03, -6.90007862e-03,
       -1.16829667e-03, -8.14474560e-03, -6.35828776e-03, -8.40049703e-03,
       -7.44567299e-03, -4.13609017e-03, -1.25686927e-02, -1.85512472e-03,
        7.23580655e-04, -2.25360964e-05, -8.20868276e-03, -9.30406712e-03,
        4.22985386e-03, -8.22765566e-03, -4.72324109e-03, -5.17983735e-03,
        1.25985658e-02, -2.82856473e-03,  3.40617518e-03,  3.72052798e-03,
       -9.07013379e-03, -1.14865275e-02, -1.02682756e-02, -7.40699936e-03,
       -7.60842254e-03, -8.24085064e-03, -9.59708355e-03, -4.87677194e-03,
       -4.22620215e-03, -1.10351332e-02, -5.54344198e-03, -7.82359857e-03,
        1.50451309e-03,  1.74555660e-03,  5.57983201e-03,  6.03416795e-03,
       -7.39626586e-03, -2.49714637e-03,  1.67472044e-03, -2.05683559e-02,
       -1.43721132e-02,  3.40103218e-03,  4.86063119e-03, -1.76621452e-02,
       -1.65933929e-02, -1.33325700e-02, -1.11063542e-02, -6.09117234e-03,
       -1.81823364e-03, -4.70456202e-03, -8.85381550e-03,  1.86681328e-03,
       -1.23208417e-02, -1.37726506e-02,  3.67861683e-03,  3.89862270e-03,
       -1.14522632e-02,  6.29714108e-04, -6.39013341e-03, -1.43266853e-03,
       -5.74985286e-03, -5.43523859e-03, -1.37957158e-02,  4.63205623e-03,
        7.49839877e-04, -5.13542211e-03, -4.90128901e-03,  3.57059715e-03,
        2.22453359e-03, -1.96970138e-03, -8.85221548e-03, -7.11860880e-03,
       -3.13816639e-03,  1.85807119e-03, -5.87428967e-03, -6.35428168e-03,
        5.39244665e-03, -7.51377083e-03, -1.28124189e-02, -4.88914130e-03,
       -1.15458597e-03, -5.52055333e-03,  1.12273712e-02,  6.37230789e-03,
       -7.57969264e-03, -6.44692313e-03, -2.56557227e-03, -3.62077868e-03,
        3.21045378e-03, -2.05658740e-04, -4.31191782e-03, -2.63910508e-03,
       -1.28579251e-02, -9.84896068e-03, -9.85323917e-03, -1.09152617e-02,
       -1.92688277e-03, -8.44058022e-03, -7.52689026e-04, -1.65359385e-03,
       -1.21661378e-02, -6.07243972e-03, -9.98634286e-03,  9.62701684e-04,
       -9.47215781e-03, -1.54145149e-04, -1.97593775e-03,  3.59665533e-03,
        9.19326209e-04, -3.46106640e-03, -8.16167984e-03, -7.49156065e-03,
       -8.81578680e-03, -6.92273956e-03, -9.62591358e-03, -1.18345637e-02,
       -3.74528021e-03, -7.25881942e-03,  6.92926813e-03, -3.50054586e-03,
        3.77886347e-03, -3.32467677e-03,  1.33562670e-03, -8.46040994e-03,
        1.07307453e-03, -7.84058310e-03, -7.76307133e-04, -1.85059523e-03,
       -6.80728815e-04, -2.92835780e-03, -1.19656110e-02, -3.73091782e-03,
       -1.06208688e-02, -1.30230431e-02, -1.06237456e-02, -1.38134381e-03,
       -8.48796032e-03, -5.37579879e-03,  6.52848557e-03, -7.33486656e-03,
       -3.80653469e-03, -4.76315711e-03, -4.98809246e-03, -3.14864470e-03,
       -1.18414098e-02,  1.60456693e-05, -1.16499262e-02,  1.69480554e-04,
       -8.60923028e-04,  3.13503318e-03, -3.87261086e-03, -1.57102570e-02,
       -1.14196651e-02,  1.33495196e-03, -9.95417591e-03, -5.45391859e-03,
       -4.38797055e-03, -1.06388936e-02, -8.09761044e-03, -1.63563248e-02,
        2.00605090e-03, -2.64014059e-04,  3.03109176e-03, -7.72877643e-03,
       -5.71411103e-03, -3.88298929e-03, -6.19448628e-03, -2.86837900e-03,
       -2.96735181e-03, -1.10861287e-02, -2.93479156e-04,  1.15975004e-03,
       -1.39904236e-02,  2.12018960e-03, -2.39682430e-03, -1.59597571e-03,
       -9.15882736e-03,  1.86132698e-03,  3.29315756e-03,  2.23518326e-03,
       -2.46693962e-03, -1.14383921e-02,  3.99885466e-03, -6.06094021e-03,
       -1.02633471e-02, -5.62232977e-04, -8.32381286e-03, -1.02277547e-02,
        7.50109321e-04,  4.29208420e-04, -4.92618512e-03, -6.49907626e-03,
        9.85817751e-04,  1.78569439e-03, -3.00678588e-03, -8.89116526e-03],
      dtype=float32), array([-1.05460572e+00,  7.31600702e-01,  8.00767422e-01, -7.67261505e-01,
       -9.59875703e-01,  4.15067524e-01,  9.95804906e-01,  1.47866595e+00,
        1.11973274e+00, -3.04726243e-01,  1.02124548e+00,  9.66189206e-01,
       -4.22396421e-01, -5.62560022e-01, -6.61418259e-01,  7.23518550e-01,
        3.48024994e-01, -3.46222699e-01,  6.57463610e-01,  6.10445499e-01,
        1.02602184e-01, -5.16249061e-01,  9.45589304e-01,  6.38044298e-01,
        8.20056736e-01, -6.04547441e-01, -1.32821465e+00,  6.90113187e-01,
        9.29751098e-01, -1.05859637e+00,  8.88216496e-01, -1.03443789e+00,
       -5.93732536e-01, -6.12217903e-01,  7.27273881e-01, -7.13687360e-01,
       -1.22378063e+00,  8.22509944e-01,  9.20894206e-01,  7.86133289e-01,
       -5.99329293e-01, -8.76034141e-01, -3.85666072e-01,  4.38232154e-01,
       -6.33967042e-01, -1.05149496e+00, -3.38461906e-01, -2.51055300e-01,
        3.87780815e-01, -3.93585205e-01, -1.08653307e+00, -1.02238250e+00,
       -6.35925829e-01, -3.49605262e-01, -6.04342341e-01, -4.63869691e-01,
        1.19401598e+00,  1.28787315e+00, -1.01717162e+00, -7.77615726e-01,
        5.51367164e-01,  5.56081593e-01,  5.35623252e-01,  5.03253162e-01,
       -6.13200784e-01,  8.28659356e-01,  7.49959826e-01, -7.26270914e-01,
       -7.37733603e-01, -8.06297243e-01,  9.82007146e-01, -1.11595786e+00,
        1.11580944e+00, -7.92790949e-01,  5.99522829e-01,  3.21291685e-01,
        8.11832964e-01, -5.80015957e-01,  1.10631287e+00,  8.98641825e-01,
        4.22616631e-01, -1.71826005e-01, -5.22218645e-01, -5.00298977e-01,
        2.53334492e-01, -4.09896344e-01,  9.21589375e-01,  4.01718765e-01,
        7.45000541e-01,  1.41079915e+00,  5.93937635e-01, -7.50504971e-01,
       -5.21834731e-01,  3.62588197e-01,  1.09932923e+00,  9.84464526e-01,
        8.07785392e-01,  1.05209839e+00,  8.87601972e-01, -3.75936925e-01,
       -7.78793335e-01,  8.30812037e-01, -8.71678472e-01,  8.68633747e-01,
       -9.64478314e-01, -6.01853907e-01,  1.02911913e+00,  8.47994328e-01,
        5.26253462e-01,  8.73463869e-01, -5.27700424e-01, -5.92189312e-01,
       -5.48279285e-01,  8.70322227e-01,  2.11008728e-01, -7.32353747e-01,
       -9.29384649e-01,  4.51781005e-01, -8.24511707e-01, -1.23115766e+00,
        5.82742572e-01, -3.12692732e-01, -1.78777039e-01, -7.51158535e-01,
        8.18284214e-01,  1.19823968e+00, -5.21023154e-01,  6.92368507e-01,
       -6.99416697e-01,  4.71690655e-01,  7.58555055e-01,  1.43228382e-01,
       -5.00633776e-01, -8.05008109e-04,  7.95086503e-01,  7.48374164e-01,
       -2.91648388e-01, -7.73011088e-01,  9.90408301e-01,  3.06303620e-01,
        7.44232118e-01,  9.94692624e-01,  7.56226122e-01,  5.52300811e-01,
        1.66112280e+00, -1.08635497e+00, -2.82268316e-01,  4.21911210e-01,
       -9.39557076e-01, -1.02817297e+00, -4.24862206e-01, -4.66600031e-01,
       -6.43745720e-01, -8.80761892e-02,  1.05292678e+00, -5.35808325e-01,
       -4.34625864e-01, -7.76188493e-01,  4.99921799e-01,  3.51638258e-01,
       -1.81550324e-01,  1.01198423e+00,  1.20909381e+00, -5.63820243e-01,
       -7.47241020e-01,  8.85108232e-01, -1.20931363e+00, -1.19938076e+00,
        1.12413859e+00,  9.22187209e-01, -4.98857021e-01,  1.06675828e+00,
       -1.60382226e-01,  8.69178355e-01, -1.02727973e+00,  6.39725327e-01,
        8.11245501e-01, -6.08337641e-01,  8.57873976e-01,  5.49524009e-01,
        7.97383010e-01,  9.37530935e-01,  4.58318889e-01, -1.21222889e+00,
       -8.72456610e-01,  5.95790982e-01, -5.07394373e-01, -3.58466387e-01,
       -7.26942539e-01,  1.06684506e+00,  9.38635945e-01,  6.69780731e-01,
        8.18446100e-01,  8.23050618e-01, -5.13252795e-01,  1.24268544e+00,
       -3.17790508e-01, -6.94646716e-01,  7.57597983e-01,  7.31674254e-01,
       -7.70526230e-01, -6.03793740e-01,  1.02133930e+00, -6.46309674e-01,
       -4.49293286e-01, -7.96574116e-01, -1.14172924e+00, -1.07769668e+00,
       -7.47400284e-01,  2.38566101e-01, -1.11448479e+00, -6.96168423e-01,
       -1.05480969e+00,  9.09312189e-01,  5.90494692e-01,  9.87388313e-01,
        9.31126118e-01,  3.24297667e-01, -5.06211162e-01,  8.78120363e-01,
        5.77286363e-01, -6.02685928e-01, -6.63363278e-01,  3.56924772e-01,
        1.11600995e+00,  8.93996358e-01,  3.37924898e-01,  6.33037150e-01,
        3.97000998e-01, -5.57865620e-01,  5.75562179e-01,  1.10130024e+00,
        8.53394449e-01,  3.78087699e-01,  9.61704552e-01,  1.17873216e+00,
        7.51499116e-01,  7.91726708e-01, -3.24481845e-01, -1.16848683e+00,
        1.03120899e+00,  7.33483016e-01,  3.64490896e-01, -1.07304966e+00,
        8.23720038e-01,  1.10889828e+00, -5.60528696e-01,  1.18044817e+00,
       -8.86610210e-01,  6.00571215e-01,  4.62566763e-01, -6.57678127e-01,
       -8.13779056e-01, -3.20088327e-01,  5.17340451e-02, -3.48205447e-01,
       -6.83298171e-01, -1.12352216e+00, -9.20015156e-01,  1.02606881e+00,
       -8.32979262e-01,  1.19478905e+00,  7.63533115e-01,  1.19613945e+00,
       -3.13376248e-01, -9.45611775e-01,  6.77487612e-01,  9.79007185e-01,
       -8.26195598e-01, -7.48553455e-01, -7.78519392e-01, -8.78256619e-01,
       -6.02053344e-01,  7.77098954e-01,  4.39642034e-02,  3.41479540e-01,
        9.16423023e-01, -2.91180432e-01, -4.57492381e-01,  7.70508826e-01,
        1.24302471e+00,  7.59467304e-01,  1.02722740e+00, -4.66778457e-01,
       -8.65655601e-01, -4.14741367e-01, -8.76064062e-01,  6.79124415e-01,
        6.88271523e-01, -5.92095852e-01, -1.15963447e+00, -8.88882101e-01,
        1.36854517e+00,  8.46302390e-01, -2.62684286e-01, -9.32519138e-01,
        2.89035767e-01, -6.40132904e-01,  1.15187633e+00,  7.39905119e-01,
       -6.01996481e-01,  9.63375509e-01, -5.20949841e-01,  5.84126651e-01,
        1.05349743e+00, -7.81746626e-01, -9.42548156e-01,  8.90500307e-01,
       -1.12119269e+00,  9.39535797e-01, -7.48922348e-01, -1.14849520e+00,
        1.03306822e-01,  1.02186990e+00, -1.17757380e+00, -6.75313294e-01,
       -6.42277360e-01, -3.84247303e-01,  7.39101589e-01, -2.95461416e-01,
        9.09986258e-01, -1.03497851e+00, -6.77939057e-01,  3.82831782e-01,
        8.02289844e-01,  1.08347940e+00, -5.49130321e-01,  1.24026012e+00,
       -7.65661120e-01,  6.99133337e-01,  9.41702366e-01, -4.33132559e-01,
       -8.75539780e-01, -1.29655063e+00, -5.85518360e-01, -5.97074986e-01,
        9.95996892e-01, -9.92552996e-01, -8.59992504e-01,  8.86988699e-01,
       -1.25003898e+00,  7.47288525e-01, -5.88013887e-01, -7.42725611e-01,
       -2.18268663e-01,  3.86328429e-01, -4.65102613e-01,  8.82187724e-01,
       -7.75644183e-01, -6.63053751e-01,  8.96458030e-01, -5.34913301e-01,
        5.44197500e-01,  5.24065197e-01,  5.01913726e-01,  9.93168175e-01,
        9.50942814e-01, -7.45361745e-01, -6.28893256e-01, -8.19029570e-01,
       -1.41297996e+00, -1.01192582e+00,  7.78046727e-01,  3.60045493e-01,
        1.00315320e+00, -9.74274874e-01,  1.00577629e+00,  7.08039522e-01,
        8.78555179e-01, -8.32847416e-01,  6.97628438e-01,  7.42109239e-01,
        9.79607522e-01, -9.91490901e-01, -5.77231169e-01,  8.26010406e-01,
       -6.44195557e-01, -3.42861265e-01,  7.66883075e-01,  8.35159004e-01,
       -3.03713828e-01, -4.47170824e-01, -8.12975645e-01,  9.26318586e-01],
      dtype=float32), array([11.131186 ,  7.062081 ,  5.9964204,  5.7781982, 17.264503 ,
        2.7247941,  5.5322204,  8.534626 ,  7.7700896,  6.1081862,
        5.657226 ,  3.247337 ,  6.0109515,  5.9222493, 10.688091 ,
        2.872782 ,  5.2993   ,  7.0399275,  5.3284335,  9.28836  ,
        3.832425 ,  8.904585 ,  3.6247313,  4.973313 ,  7.5682216,
        4.5089016, 16.773876 ,  3.460038 ,  6.219471 , 14.068503 ,
        5.5741587, 11.381276 ,  6.3535776,  3.744201 ,  2.3319685,
        7.2783504, 12.914929 ,  4.0374727,  5.233227 ,  5.2781234,
        5.0314727, 17.88932  ,  4.813821 ,  7.0503926,  5.149893 ,
       16.97594  , 11.947992 ,  4.494893 ,  4.097657 ,  5.833051 ,
       12.29142  , 12.254184 ,  5.3456254, 12.076823 ,  4.914153 ,
        3.3103204,  8.247122 , 11.699062 , 14.995953 ,  7.881612 ,
       12.584122 ,  2.480816 ,  9.430507 ,  5.152929 ,  5.256631 ,
        6.83757  ,  4.785598 , 16.50658  , 11.842306 ,  5.8776526,
        3.8070717, 14.094938 ,  8.846492 ,  5.7556458,  2.5344632,
        4.1193295,  2.288281 ,  8.236213 ,  4.2965517,  6.9631486,
        3.4233866,  5.1407433,  8.368472 ,  7.1411533,  8.490683 ,
        6.8034987,  6.3976054, 11.910184 ,  7.469367 ,  8.608881 ,
        7.136878 ,  9.671304 ,  5.8813076,  3.3980641, 10.477319 ,
        7.965635 ,  8.251558 ,  7.466618 ,  6.759927 ,  8.565174 ,
        6.5802293,  5.2003727, 10.16117  ,  4.1870866, 10.091711 ,
        6.211292 ,  3.0134313,  5.757652 ,  3.1291378,  4.3289046,
        4.883572 ,  7.232691 ,  6.3598413,  4.9454784,  4.7868176,
       11.095877 , 11.08335  , 11.009672 , 14.135898 ,  8.923592 ,
        2.8199403,  3.113731 ,  2.703894 ,  9.466039 ,  6.395619 ,
        7.615977 , 11.491979 ,  6.7203364,  8.643015 ,  5.9449077,
        4.946116 , 12.101299 ,  3.268141 ,  5.1278358,  6.867213 ,
        4.079565 ,  3.9084125,  6.49969  ,  6.6089263,  3.3431306,
        6.2910585,  5.9577966,  6.999036 ,  4.887107 ,  8.633104 ,
        8.085873 ,  4.512892 ,  6.465368 ,  3.4581814, 14.093401 ,
        9.258095 ,  5.4017143,  9.657974 ,  3.2604196,  5.3053904,
        4.7991114,  3.5898385, 10.56256  ,  4.9125066,  2.6505146,
        2.8304596,  5.2062683,  6.1701303,  6.509203 ,  8.564156 ,
        4.496936 , 14.546224 , 14.077965 ,  8.78628  ,  2.873174 ,
       10.154721 ,  4.8933544,  6.371826 ,  3.7721217, 12.597905 ,
       10.864488 ,  4.3913784,  5.956962 ,  6.2866983,  6.5072565,
        6.1146665,  8.948338 ,  6.1828976,  7.169425 ,  7.7574186,
        4.7864847,  5.640252 ,  6.6924777, 10.360151 ,  3.3398967,
        9.456277 ,  5.19876  ,  4.891945 ,  6.0868993,  5.554488 ,
        7.9626875, 10.021241 , 15.993492 ,  3.789734 ,  6.624338 ,
        8.039737 ,  6.680904 ,  4.3422155, 13.182407 ,  7.9717484,
        7.81261  , 15.298166 , 12.773742 , 10.507921 ,  3.709106 ,
       14.5052185,  9.919802 , 12.307059 ,  6.893952 ,  6.383233 ,
        6.2284102,  5.7123804,  5.5518923,  2.5894132,  3.7599907,
        5.4454837,  6.382026 , 10.311956 ,  2.2203329,  7.3842564,
        4.592559 ,  3.000012 ,  2.7367628,  6.8591475,  5.8986464,
        7.6976795,  5.934007 ,  5.50291  ,  8.098455 ,  5.33729  ,
        4.8217893,  1.9329246,  7.7933164,  7.5824656, 14.973156 ,
        6.901768 ,  5.1741605,  4.205323 , 10.975903 ,  4.9508214,
        5.530796 ,  9.674001 ,  5.224526 ,  6.7688904, 11.568623 ,
        3.145323 ,  8.027978 ,  8.264929 ,  2.0512617,  3.4617953,
        5.0930505,  5.863179 ,  9.382518 ,  5.693045 , 13.148137 ,
       10.258611 ,  7.5992193,  4.849907 ,  7.0730443,  5.251574 ,
       10.757442 ,  3.7279828,  4.6967034, 11.372472 ,  9.776266 ,
        7.9264045,  9.677911 ,  9.750763 ,  8.01763  ,  4.893971 ,
        6.534476 ,  7.348205 ,  3.7023222,  6.477779 ,  1.6959624,
        7.334618 , 12.169534 ,  6.344025 ,  2.6058125, 14.183547 ,
        6.7517047,  8.117531 , 11.389386 ,  3.5044327,  5.505685 ,
        8.807588 , 11.982608 ,  6.1675224,  4.653993 , 10.841275 ,
        7.8529243,  5.935948 ,  6.698832 ,  3.7319424,  3.6118653,
        4.248552 ,  5.455693 ,  7.8581214,  9.040991 , 10.726893 ,
        8.885447 , 13.553831 , 10.400959 , 12.974989 ,  6.791303 ,
       12.617241 ,  7.828535 ,  2.8241913,  6.815071 , 19.502052 ,
       16.713444 ,  9.152032 ,  9.854679 ,  2.1152635,  6.998437 ,
       14.953658 , 15.428274 , 10.565127 ,  5.0262485,  4.765643 ,
        7.756045 ,  9.241207 , 10.311603 ,  9.499318 ,  2.880365 ,
        4.7899427,  6.0037704,  8.708436 , 16.70768  ,  3.6224992,
        5.8617444,  7.9939704, 12.1311   ,  7.19025  ,  8.63294  ,
       15.131501 ,  2.7564666,  9.636563 ,  9.630454 ,  4.649117 ,
        3.4504008,  4.501033 ,  4.678237 , 11.720965 ,  8.0202   ,
        6.7524643,  6.8829165,  2.4914083,  4.211095 ,  5.6414676,
        3.2288494,  5.1164775,  6.8114657, 15.373567 ,  8.031471 ,
       14.446887 , 11.191013 ,  2.7789178,  2.7572656,  4.018931 ,
       10.3868   ,  4.9720035,  5.40688  ,  5.240242 ,  6.2462125,
        4.8583984,  4.796528 ,  4.6740713, 12.612329 ,  5.437073 ,
        2.8703609,  5.1938806,  4.4468284,  2.5319715,  2.586337 ,
        7.533225 ,  3.3268137,  7.97068  , 14.940135 ], dtype=float32), array([-6.62883511e-03, -2.33234209e-03, -1.34480409e-02, -6.39246404e-03,
       -7.89192505e-04, -3.25422199e-03, -9.14767291e-03, -8.06530751e-03,
       -9.07247141e-03, -4.53295326e-03, -6.73276186e-03, -9.40215029e-03,
       -8.92556738e-03, -6.85966248e-03,  3.60473641e-03,  2.43176520e-03,
       -8.11994821e-03, -1.12201087e-02, -1.44303532e-03, -2.64738849e-03,
       -1.03211300e-02,  1.44273099e-02, -1.08413817e-02, -1.27224368e-03,
       -5.78674022e-03, -9.99973062e-03, -2.97237514e-03,  2.74855504e-03,
       -5.05421311e-03, -5.50545380e-03, -4.05311910e-03,  6.73163624e-04,
       -6.31388556e-03, -6.37198857e-04, -1.68855791e-03,  9.09097202e-04,
        2.48710462e-03, -3.62382154e-03, -6.90865330e-03,  2.92743999e-03,
        5.07335365e-03, -5.18997293e-03, -9.02860332e-03, -7.90723320e-03,
       -1.41097307e-02, -9.60336160e-03, -1.12169245e-02,  2.07514875e-03,
       -5.69769926e-03,  6.53368142e-03, -3.26852431e-03, -1.27905961e-02,
       -5.61930425e-03, -5.18843811e-03, -1.15447287e-02, -1.76742375e-02,
       -3.53718875e-03, -1.09839337e-02, -6.58638636e-03, -1.55045232e-03,
       -8.96758866e-03, -3.13060032e-03, -3.84134287e-03, -8.27373099e-03,
       -2.44661793e-03,  2.84594507e-03,  9.17027518e-03, -9.08700284e-03,
        4.64700954e-03, -8.08823202e-03, -1.54993674e-02, -9.19413380e-03,
       -2.51324079e-03,  2.40130047e-03, -3.33878002e-03,  5.42687485e-03,
       -1.19949994e-03,  1.53159327e-03, -1.70869136e-03, -9.82216652e-03,
        5.27078239e-03, -7.57989194e-03, -7.60116056e-03, -2.03961078e-02,
       -3.79398721e-03, -5.29546198e-03, -1.30001717e-06, -4.13467595e-03,
        2.50431825e-03, -8.70626140e-03, -3.74919735e-03, -2.73399102e-03,
        3.81225953e-03, -2.63913441e-03,  3.80344642e-03, -1.98845565e-02,
       -7.15456437e-03,  4.41040844e-03,  2.54483544e-04, -5.63812722e-03,
       -8.51572305e-03, -3.45284468e-03,  5.73525345e-03, -7.08487909e-03,
       -8.26820917e-03,  1.87045417e-03, -4.85884259e-03, -9.59339179e-03,
       -6.80838129e-05,  1.52807189e-02, -1.18612708e-03, -1.49707994e-05,
       -7.74521567e-03, -6.17843075e-03,  6.65882183e-03, -8.52358900e-03,
       -5.48055395e-03, -2.06514611e-03, -1.11718224e-02, -2.66646757e-03,
        9.89903230e-04,  4.13024519e-03,  2.19783839e-03, -1.72541440e-02,
       -4.41254256e-03, -6.34898478e-03, -6.02285750e-03, -8.12885351e-03,
        1.01341843e-03, -4.58009029e-03, -3.78063694e-03, -7.04353023e-03,
       -2.55187787e-03, -1.35831069e-02,  3.12523101e-03, -7.64289778e-03,
       -7.27496389e-03, -8.36202037e-03, -6.79498212e-03, -4.74702986e-03,
        3.67089221e-03,  3.36998934e-03, -1.01383300e-02, -2.81923637e-03,
        7.26488139e-03, -3.17649264e-03, -1.35434158e-02, -2.95416405e-03,
       -1.23542193e-02, -9.36187338e-03,  3.91019508e-03, -8.06609262e-03,
        7.77299609e-03, -1.12022758e-02, -2.60693673e-03, -3.88506358e-03,
       -2.19482137e-03, -2.04865402e-03, -1.33131631e-03,  3.13022966e-03,
        2.06225179e-03,  5.14690066e-04, -2.42103892e-03,  1.91096857e-03,
        4.45070490e-03,  6.53122843e-04, -4.98061348e-03,  6.46646658e-04,
       -1.05592757e-02, -8.74713436e-03, -5.83335478e-03, -1.03908284e-02,
       -1.04885257e-03, -3.52788530e-03, -6.74389675e-03, -1.93819613e-03,
       -1.63273178e-02,  4.76243382e-04, -3.30649462e-04,  7.97798298e-03,
       -5.96558349e-03, -6.48388034e-03,  1.11893266e-02,  7.52440561e-03,
       -1.04534132e-02, -5.98706165e-03, -9.10036266e-03,  1.59581960e-03,
       -7.98796676e-03,  5.71244350e-03, -9.16409586e-03,  1.09410344e-03,
       -1.92152697e-03,  3.32170376e-03, -7.97994807e-03,  4.55143070e-03,
       -5.69554232e-03,  2.89218035e-03, -6.70663454e-03, -5.84211884e-05,
       -1.24424864e-02, -5.13977092e-03, -3.40026082e-03,  4.77479218e-04,
       -6.03534095e-03, -6.31970307e-03, -5.70794614e-03, -3.01242061e-03,
       -7.23328162e-03,  2.46728514e-03,  8.36272445e-03, -1.46903459e-03,
       -5.97079890e-03, -9.95689817e-03, -1.09888939e-02, -3.16744065e-03,
        1.16082896e-02, -2.24965028e-02, -4.99596726e-03,  1.28795030e-02,
       -2.27834005e-03, -1.56493783e-02, -3.44558549e-03, -4.21902817e-03,
       -1.17380582e-02, -1.20041585e-02, -3.58159002e-03, -5.57786366e-03,
       -6.56268327e-03, -1.17819998e-02, -4.23071487e-03, -1.09271845e-03,
       -2.47020228e-03, -1.23242429e-02, -3.01267137e-03, -8.87419377e-03,
       -8.58580600e-03, -5.53023769e-03,  5.81427710e-03, -4.39161202e-03,
       -7.62591558e-03, -8.00893083e-03, -1.28919957e-02, -9.14288126e-03,
       -6.05727965e-03,  2.53705378e-03, -9.35987104e-03, -4.53647086e-03,
       -1.74172432e-03, -4.46424994e-04,  6.07582880e-03,  4.10733558e-03,
        1.26392208e-03, -4.08552960e-03, -5.03123458e-03, -4.16227616e-03,
       -6.66488800e-03, -1.04091791e-02, -1.24616073e-02, -7.70568429e-03,
       -9.16274358e-03,  5.56550338e-04, -9.01784934e-03, -1.33086415e-03,
       -7.79505726e-03, -1.62007997e-03,  3.42883472e-03, -9.97876935e-03,
       -1.61962435e-02, -8.32032133e-03, -4.00159229e-03, -5.36492467e-03,
       -1.41676543e-02, -1.40444282e-02,  7.83370284e-04, -6.49571093e-03,
        4.82320553e-03, -7.17812171e-03, -4.03621653e-03, -1.29374415e-02,
       -9.00337659e-03,  7.93633051e-03, -9.35437903e-03, -3.27249360e-03,
       -3.49081028e-03, -7.18862470e-03, -4.47865995e-03, -1.02174245e-02,
       -1.33784711e-02, -3.43961222e-03, -9.92837828e-03, -4.42300318e-03,
        3.00231366e-03, -4.01588064e-03, -1.51123770e-03, -9.05287825e-03,
       -6.75201695e-03, -2.06527882e-03,  2.37142411e-03, -1.48895951e-02,
       -3.07864771e-04, -6.41416293e-03, -1.30198998e-02, -4.64321347e-03,
       -3.15262121e-03,  2.09875434e-04, -7.41479639e-03, -1.67161063e-03,
       -1.62263983e-03, -8.01337603e-03, -4.19502100e-03, -8.51997454e-03,
       -1.28653960e-03, -4.20150813e-03, -1.19088972e-02, -1.34555856e-03,
       -1.66164525e-03,  4.11141617e-03, -7.13823223e-03,  3.80065199e-03,
       -3.19810072e-03, -9.34425741e-04, -1.02943452e-02, -1.42575540e-02,
       -4.20082361e-03,  5.04609430e-03, -7.60846213e-03, -4.03839070e-03,
        9.89613240e-04,  1.24501949e-03, -2.25250144e-03, -3.42811411e-03,
       -1.31376386e-02, -1.05603738e-02, -1.59515720e-03, -5.40126208e-03,
       -3.90236499e-04, -4.25595045e-03, -1.32207917e-02, -1.79508221e-04,
       -8.93301331e-03, -7.40084471e-03, -1.13310618e-02,  5.24368882e-03,
       -1.19357612e-02, -5.27132489e-03, -6.25573983e-03, -8.49214289e-03,
       -8.09953175e-03, -1.64018769e-03, -8.95645376e-03, -1.92909874e-03,
       -1.21799903e-02, -3.69347865e-03, -1.12312064e-02, -1.62625266e-03,
       -7.16575049e-03, -4.61986754e-03, -1.23000806e-02, -8.95059854e-03,
       -2.24790303e-03, -5.60704293e-03, -1.27834156e-02, -1.26518765e-02,
       -1.02368696e-03,  1.11440616e-03, -1.09432405e-02,  3.13037215e-03,
       -4.53381595e-04, -1.98450871e-03, -1.15170227e-02, -7.15982867e-03,
       -2.28629890e-03, -4.37949970e-03, -1.16328597e-02, -1.23999529e-02,
       -6.26828754e-04, -6.67966297e-03, -1.07899411e-02, -4.95923730e-03,
       -2.26859027e-03,  1.07183009e-02, -7.71612767e-03, -2.11209431e-03],
      dtype=float32), array([-1.0719093 ,  1.2103297 , -0.43927273, -0.43116295,  0.5643457 ,
        0.5734518 , -0.43061593,  0.61452806, -1.4158508 , -0.990304  ,
       -0.8346583 ,  1.3152276 ,  0.8334301 , -0.5667507 , -0.6750037 ,
        1.0659177 ,  0.77396345,  0.45319837, -1.1422219 , -0.5647119 ,
       -0.8528816 , -0.3699879 ,  0.99939084, -0.86632407, -0.34294719,
        0.98367107, -1.3861572 ,  0.7094153 ,  0.21552832,  1.2236844 ,
       -0.74847066,  1.1472294 , -1.0656391 ,  0.53451943,  0.5688832 ,
        1.0162464 , -0.7583088 ,  0.8881041 ,  0.9864518 ,  0.8901244 ,
       -0.75050706, -0.86673903,  0.38798335,  1.191662  ,  1.2806835 ,
        0.99864095,  1.1164519 ,  1.0369962 ,  0.16883571, -0.577525  ,
       -1.0313549 ,  0.6452189 ,  1.0775392 ,  0.27655116,  0.7567865 ,
        0.7313167 , -0.469208  ,  0.02061445,  0.5328499 , -0.17221574,
        0.35367367,  0.7509708 , -0.75780183,  0.9974492 ,  0.4376685 ,
       -0.34932348, -0.48291606,  0.7123808 ,  0.20201223,  1.4234352 ,
       -0.4490729 ,  1.457122  ,  0.86697143, -0.5221174 , -0.65019596,
       -1.145752  ,  0.52451086,  0.8061726 , -0.5845063 , -0.44581544,
       -1.0620433 ,  0.73881805, -0.15241037,  0.9738709 ,  0.56245786,
       -0.6657245 ,  1.0252838 ,  0.7403115 , -1.1269628 , -0.3659174 ,
       -1.0207514 , -0.796087  , -0.9249421 , -0.6265046 ,  0.65927964,
       -0.6207941 , -0.71042985,  0.45402268, -1.0569583 ,  0.82826984,
       -0.785568  ,  0.16205063,  0.4978111 ,  0.16514762,  0.47270864,
       -0.57370967, -0.7934707 , -0.8501644 , -0.7096659 , -0.61149174,
        0.78600556,  0.7088451 , -0.4954102 ,  0.94199526, -0.04244884,
        1.3744885 , -1.2262592 ,  0.8381667 ,  0.03479014,  0.9807524 ,
       -0.85248387, -0.9050263 ,  0.523867  ,  0.95158356, -1.1768014 ,
       -1.1140425 ,  0.94394785, -0.64673954,  0.8666155 , -1.0171081 ,
        0.86338854,  0.80619794, -0.8870955 , -0.45486203,  0.6589165 ,
        1.2043021 ,  0.4307797 , -0.1582736 , -0.7926832 , -0.5531155 ,
        0.9967619 ,  0.32985118,  0.70604753,  0.78513086, -0.2057302 ,
        0.82005346,  0.94536126, -0.6313581 ,  0.7221641 ,  0.6726039 ,
       -1.0392612 , -1.1227567 , -1.3087008 , -0.7833537 ,  0.5375325 ,
        0.56859535, -0.68346727,  0.7977299 ,  1.1130387 , -1.0783907 ,
       -0.38652903, -1.0933377 ,  1.0019555 ,  1.4918276 ,  0.17242461,
        0.7508011 , -1.1511922 , -0.8834209 ,  0.6431616 ,  0.67875725,
       -0.9268567 ,  0.4848144 , -0.51943386,  0.25990486,  0.45113894,
        0.70422333,  0.7565264 , -0.5090143 , -0.38772815, -0.6568969 ,
        0.78639054,  0.74752367, -0.39430282, -0.6667538 , -0.87808394,
       -1.5233443 ,  0.56605804,  0.6159729 ,  1.1621187 ,  1.0037428 ,
        0.9109708 , -0.07646251, -0.6842871 ,  0.6938834 ,  1.0132254 ,
        0.6420659 ,  0.3542362 ,  0.45290768, -0.07999756, -0.2670393 ,
        1.2027805 ,  0.443322  , -0.51591337,  0.20695536, -0.43771413,
       -0.26187792,  0.21000476, -0.73682404, -0.91214263,  0.74326944,
       -0.73490244, -0.8421597 , -1.2421236 ,  0.9797594 , -0.7874773 ,
        0.4390639 , -0.5792772 ,  1.0527875 ,  0.22655974, -0.7307818 ,
       -0.4796092 , -1.3504672 ,  0.57626975,  0.42194474, -0.24151072,
       -1.0888226 ,  0.42330313, -0.8239459 , -0.83051854,  0.43288288,
       -0.97641593,  0.9422374 ,  0.8919423 ,  1.3810135 ,  1.2046207 ,
        0.63233906,  1.0740864 , -0.63242656, -0.46879634, -1.2704196 ,
        0.5580814 , -0.54188627,  0.8221936 , -0.7859883 ,  0.7280335 ,
       -0.98484915,  0.45026946,  0.15180787, -0.55098635, -0.59684354,
       -0.23400587, -1.3059946 , -0.7102346 ,  1.136717  ,  0.64716923,
        0.800577  ,  1.0288343 ,  0.9802458 , -0.43879598, -0.17627664,
        0.7117825 , -0.19305152,  1.1115721 , -1.1454924 , -0.32037053,
        0.6164238 , -0.68174565,  0.8457202 ,  1.29269   ,  1.077369  ,
       -0.34382176,  0.6645952 , -0.89176065,  0.28876066,  0.94387114,
        0.54846   , -0.5169352 ,  0.5140272 , -0.69479084, -0.97971123,
       -1.0741968 , -0.2544865 ,  0.6467555 , -0.5784074 , -1.1135759 ,
        0.29921353,  0.19914098,  0.65734386,  1.2018886 , -0.65897244,
        0.89140344,  0.41270387,  0.800238  , -0.30319926,  0.99422157,
       -0.52998084,  0.24341384, -0.7705151 ,  0.69423723,  0.8810376 ,
        0.8460086 , -0.6383995 , -0.99808776, -0.6380975 , -1.0363305 ,
        0.39975783,  1.0021822 , -0.68454015, -0.92378473, -0.3570637 ,
        1.0086533 ,  1.2529811 ,  1.0595146 , -0.91246545,  0.7742452 ,
        0.9919014 , -0.65908295,  0.9082318 , -1.4268312 , -0.72681665,
       -0.6854996 , -0.8643968 ,  0.3900604 ,  1.1528493 ,  0.8716303 ,
        0.51606935, -1.4659268 ,  0.5769805 ,  0.93937635, -1.0484359 ,
       -0.38459012, -1.092773  ,  0.34998825,  1.0573268 , -0.794852  ,
       -1.0102714 ,  1.1945889 ,  0.55966973,  1.1762697 , -1.0369207 ,
        1.3184599 , -1.2193023 ,  1.0423926 , -0.67424417,  0.7946224 ,
       -0.84103185,  0.39424852, -0.73134583,  1.3701499 , -1.2230093 ,
       -0.5174153 , -0.5537185 ,  0.88747245,  0.73223853,  0.38226873,
       -1.0759277 ,  0.560969  , -0.46874502, -0.37313402,  0.92300624,
        0.9372522 , -0.84370035,  1.2221875 ,  0.22583912,  0.5462446 ,
       -0.2519481 ,  0.98324895, -0.57088375, -0.9644226 , -0.8853631 ,
        0.07559098,  0.41862726, -0.9649617 , -0.5831235 ,  0.9203604 ,
        0.8567689 ,  0.7622051 ,  0.97819847,  0.43945238, -0.733195  ,
       -0.56037855, -0.57791305,  1.0043004 , -1.1199334 ], dtype=float32), array([10.09133  , 10.122841 ,  5.614087 ,  5.559186 ,  4.0694294,
        3.9105442,  4.1565666,  4.4904113, 13.540815 , 12.752252 ,
        8.60038  ,  6.592005 ,  5.353084 ,  6.5345855,  9.868612 ,
       16.00303  ,  6.80119  ,  3.8105736, 10.6394825,  9.91003  ,
        8.748503 , 11.170736 ,  4.1998844, 14.985564 ,  6.3545647,
        3.8355238, 22.486542 ,  6.365235 ,  4.5318666,  7.696424 ,
        7.102765 ,  7.4370933, 12.2642765, 10.416923 ,  6.871899 ,
        3.4747598,  9.281838 ,  9.297492 ,  4.291255 ,  5.313606 ,
        9.396843 ,  5.651807 ,  4.451094 ,  4.1567316,  6.7559466,
        5.6705356, 10.616221 ,  5.089532 ,  4.3259034, 12.681594 ,
        7.191071 , 25.984596 ,  7.149029 ,  4.3398232,  3.7205467,
        4.9188   ,  4.984356 ,  2.2852561,  8.293297 ,  1.4866256,
       10.962425 ,  7.6316433,  8.549723 ,  5.3050394,  7.017232 ,
        3.1304598, 11.126241 ,  9.756711 ,  1.9532498, 17.782232 ,
        5.642221 ,  8.0677805,  9.230669 , 10.234346 ,  9.957742 ,
       19.583279 ,  2.8098216,  3.7904072,  7.3730273,  1.9924604,
       16.509977 ,  2.2206583,  5.6858644,  4.922169 ,  9.259407 ,
        7.2189026,  4.6241984,  6.273299 , 16.529629 , 10.128997 ,
       12.516021 , 10.649847 ,  9.152263 , 13.323406 ,  4.615737 ,
        5.148611 , 11.784145 , 11.131148 , 12.502922 ,  4.134848 ,
        3.8895192,  3.6229224,  2.7020338,  2.5380042,  6.0802693,
        6.9900184,  7.1406317,  5.7654114, 11.182996 ,  9.980144 ,
        7.434391 ,  4.990169 , 11.101612 , 13.7621355,  9.42342  ,
        6.4359646,  7.7454786, 14.63942  ,  3.3802874,  4.2391186,
       10.482577 , 13.6712675,  4.6917543,  3.9323041, 17.220669 ,
       16.166735 ,  5.921308 ,  4.7895937,  4.0215917,  8.929549 ,
        4.926151 ,  3.3056862, 15.721953 ,  6.6108193, 12.241176 ,
        5.1315   ,  3.372356 ,  4.324231 ,  9.598183 , 11.270032 ,
        4.171994 ,  5.216628 ,  5.8013835,  6.064144 ,  4.741892 ,
        7.321055 ,  5.025943 ,  5.9156375,  2.9517212,  4.654353 ,
        9.357776 , 12.405668 , 12.960461 ,  4.7660995,  3.9562075,
        4.7742105,  9.626884 ,  6.591161 ,  5.7029915, 11.542558 ,
        9.265356 , 14.852738 ,  5.1937203, 10.120405 ,  4.1903305,
        8.088164 , 14.767329 ,  5.9414186,  3.4071507,  6.1199265,
       10.537446 , 12.87839  ,  8.388071 ,  5.774124 ,  3.698869 ,
        4.230624 , 10.684614 ,  6.788614 ,  7.242422 ,  6.7398887,
        3.51467  ,  7.8890715, 10.553606 , 15.65322  ,  3.4190958,
       26.52584  , 10.908422 ,  5.6617165,  4.7383127,  6.4459987,
        3.803183 ,  8.486331 ,  6.4501066,  5.233414 ,  6.978461 ,
        6.7129226,  3.2263536,  7.390043 ,  4.6278305,  6.576205 ,
        5.823803 ,  7.0528407,  5.5050626,  6.20927  ,  6.0389247,
        1.9318902,  6.9719625,  8.174145 ,  7.625771 ,  7.410001 ,
        4.4144735,  8.186909 , 14.929927 ,  3.0899212,  6.721067 ,
        2.2186003, 12.797861 ,  5.192813 ,  5.9381   ,  6.641343 ,
        8.2913885, 11.4882145,  4.8914623,  3.7663841,  6.9635763,
        6.534268 ,  7.590242 , 13.653549 , 10.182732 ,  2.8207607,
        9.236214 ,  6.443303 ,  4.085832 ,  9.84289  ,  4.5701694,
        2.6942797,  4.086512 ,  6.5353403,  4.9451165, 21.116894 ,
        3.723775 ,  7.30479  ,  2.1972206,  6.945641 ,  3.307556 ,
       16.267788 ,  5.521291 ,  2.907544 ,  7.942117 , 12.892995 ,
        4.0547986, 14.375108 ,  7.7190075,  7.9990425,  6.0793333,
        3.1878815,  5.260392 ,  5.658102 ,  3.8283467,  5.701583 ,
        5.1090546,  3.5448065,  7.2254157, 12.662538 ,  6.609689 ,
       12.40417  ,  5.2579103,  3.2805908,  4.7610006,  5.0879197,
        5.6254725,  3.1847951, 12.47113  ,  2.9749713,  4.7837563,
        7.0211964,  7.3838444,  8.090877 ,  4.5156136, 13.611877 ,
       12.387796 ,  5.516745 ,  5.4048285,  7.244079 , 12.85327  ,
        2.8209963,  9.1923065,  5.284101 ,  6.5889707,  8.700206 ,
        5.519954 ,  4.049385 ,  3.4272683,  4.191778 ,  3.9110248,
        4.1477623,  3.2109082, 10.060144 ,  2.4352987,  2.5866253,
        6.398082 ,  3.291001 , 15.399345 ,  4.6424966, 10.197116 ,
        6.6513863,  5.49728  , 10.376393 , 11.091155 ,  3.7074747,
        6.686374 ,  6.605409 ,  6.0041595, 16.334423 ,  3.74952  ,
        6.132194 ,  8.517208 ,  3.4843786, 26.535816 , 10.201232 ,
        7.982408 ,  8.044276 ,  3.8553066,  6.208773 , 10.308377 ,
        3.0620003, 14.049331 ,  3.6652327, 10.909262 ,  8.27892  ,
        5.2918725, 11.620335 ,  7.7728915,  4.540578 ,  9.470146 ,
       20.50415  ,  5.248106 ,  5.038202 ,  8.6466255,  6.517255 ,
        7.053175 , 12.333393 ,  4.9993873,  9.681747 ,  4.245151 ,
        4.6441684,  2.7445457,  8.095049 ,  7.4251657, 13.619916 ,
        3.4294176,  6.8688517,  5.0805645,  5.1392403,  3.3345473,
       15.466526 ,  3.3484235,  6.5537405,  4.68934  ,  4.973448 ,
        5.360168 ,  4.9589205,  5.346698 ,  2.3993073,  3.1473222,
        5.4113774, 19.71429  , 10.770353 , 20.784945 ,  7.2968264,
        1.6882436,  6.174577 , 12.627096 , 13.221728 ,  5.6129932,
        9.974019 ,  2.7881927,  7.402869 ,  4.7828035,  4.00258  ,
        6.137206 , 10.607601 ,  5.0664854, 16.50549  ], dtype=float32), array([[[[ 0.01507684,  0.04236711,  0.03963081, ...,  0.04750595,
           0.0157094 ,  0.03132897],
         [ 0.03118467,  0.03871415, -0.06154601, ...,  0.05865197,
          -0.05660259,  0.04028301],
         [-0.01457999, -0.04875394,  0.00031069, ..., -0.00189334,
           0.04860318, -0.02224509],
         ...,
         [-0.02440293, -0.02048716, -0.01966832, ...,  0.03825992,
          -0.03535025, -0.05952654],
         [ 0.05047182, -0.0096452 ,  0.0030299 , ..., -0.01074048,
           0.05633856, -0.01313962],
         [-0.01039426,  0.01247785,  0.02497771, ..., -0.00926785,
          -0.0198687 ,  0.00160521]]]], dtype=float32), array([-7.66521366e-03, -1.43211940e-03, -2.04450195e-03, -1.90239912e-03,
        5.22065349e-03, -1.06093669e-02, -8.99870787e-03, -1.59768686e-02,
        3.28359776e-04, -1.08540077e-02, -1.85417105e-02, -1.34061910e-02,
       -1.16878795e-02,  3.96063479e-05,  1.52799790e-03,  2.31591356e-03,
       -1.68059822e-02, -1.39909964e-02,  1.35964202e-03, -5.62319439e-03,
       -1.38170719e-02, -1.06998524e-02, -1.33139836e-02, -2.38459706e-02,
       -1.39675094e-02, -1.56986841e-03, -3.95168870e-04, -1.03973206e-02,
       -1.14437127e-02,  5.84310503e-04, -2.38120276e-02, -1.80148315e-02,
       -3.83047666e-03, -1.76847354e-02, -6.30147289e-03, -2.94747250e-03,
       -1.15688760e-02, -2.10540686e-02, -1.45834601e-02, -1.83847509e-02,
       -1.53442780e-02, -1.17254932e-03,  7.08978216e-04, -1.67803075e-02,
       -7.28788180e-03, -1.51305720e-02, -1.62523948e-02, -5.68810990e-03,
       -1.65234413e-02, -1.70605239e-02, -5.72524557e-04, -5.86789940e-03,
       -1.64969340e-02, -8.56526289e-03, -1.30495112e-02, -8.27118848e-03,
       -1.24584709e-03, -8.46056361e-03, -1.76869407e-02, -1.74370967e-02,
       -1.35680400e-02, -2.20930483e-03,  1.28756429e-03, -1.24907997e-02,
       -3.35662416e-03, -7.64126983e-03, -1.75119424e-03, -1.16991224e-02,
       -3.47336801e-03, -7.99418148e-03, -6.81412825e-03,  3.04398709e-04,
       -1.04703521e-02, -2.31736396e-02, -7.33151147e-03, -1.60957556e-02,
       -1.20489616e-02, -1.99769177e-02,  4.75965411e-04, -1.62379686e-02,
       -1.27766235e-02, -1.70209892e-02, -2.69183633e-03, -1.33140506e-02,
       -2.00517084e-02, -9.31190141e-03, -1.63295362e-02, -3.24392517e-04,
       -8.35065637e-03, -1.22089060e-02, -7.70478602e-03, -1.37039367e-02,
       -1.08124577e-02, -4.08983650e-03, -2.30529625e-03, -9.07508831e-04,
        6.81316061e-03, -8.17958545e-03,  1.20296120e-03, -1.90578066e-02,
       -3.73741309e-03, -1.11846691e-02, -6.34751003e-03, -3.49941151e-03,
       -1.06286332e-02, -1.54122729e-02, -1.20129092e-02, -6.42369967e-03,
       -1.36438496e-02, -1.76088884e-02, -3.83710978e-03, -1.03833182e-02,
        3.09790112e-03, -5.86425466e-03, -4.91135521e-03, -1.46128694e-02,
       -1.59122900e-03, -1.22376448e-02, -9.23082605e-03, -6.03138888e-03,
       -1.16445962e-02, -2.08268594e-02,  3.68930079e-04, -1.21561894e-02,
       -6.84929732e-03, -1.60164200e-02, -5.24356076e-03, -7.99302943e-03,
       -6.54905709e-03, -5.26602194e-03, -1.63664054e-02, -1.63266677e-02,
       -8.66579264e-03, -7.56880175e-03, -1.66501645e-02, -1.25619490e-02,
       -5.59717929e-03, -1.39547661e-02, -2.00411659e-02,  4.59789904e-03,
       -3.05368844e-03, -1.38210086e-02, -1.22388247e-02, -2.52163429e-02,
       -1.28045930e-02, -1.03364103e-02, -1.27592161e-02,  3.51323251e-04,
        2.78332504e-03, -6.18030876e-03, -1.67924985e-02, -2.20585288e-03,
       -8.62404518e-03, -5.12270676e-03, -7.54616689e-03, -2.21765935e-02,
       -1.42039908e-02, -7.90956244e-03, -1.18911900e-02, -8.35918728e-03,
       -1.94814801e-02, -9.27386899e-03, -1.77321117e-02, -1.62006114e-02,
       -1.97407659e-02, -5.48875146e-03, -1.20838666e-02, -1.95762757e-02,
       -1.59087721e-02, -1.76459923e-02, -1.46210408e-02, -3.97222256e-03,
       -1.04623409e-02, -1.10473400e-02, -1.46708554e-02, -6.27668807e-03,
       -3.89969582e-03,  7.90357962e-03, -1.27641736e-02, -8.11334513e-03,
       -5.83901303e-03, -4.92475322e-03, -6.71915431e-03, -1.09739527e-02,
       -5.26626734e-03, -1.22107044e-02,  1.24475965e-03, -1.04959859e-02,
       -4.54501668e-03, -4.45801672e-03, -7.37936283e-03, -2.95181619e-03,
       -1.48027744e-02, -7.16131786e-03, -7.98781309e-03, -1.34049952e-02,
       -1.24036744e-02, -1.81290526e-02, -3.05552082e-03,  2.33656750e-03,
       -6.95503596e-03, -1.16992295e-02, -9.60775279e-03, -1.03241317e-02,
       -1.57309603e-02, -1.13962786e-02, -1.10701611e-02, -1.74237322e-02,
       -2.97464966e-03, -2.03168746e-02, -6.80716895e-03, -4.50702338e-03,
       -1.13972323e-02, -2.07043588e-02, -1.50057077e-02, -1.34152025e-02,
       -1.34282792e-02,  1.04731498e-02,  2.71032960e-03, -1.98592544e-02,
       -9.07988753e-03, -9.39533394e-03, -1.35768419e-02, -1.22309038e-02,
       -1.12925302e-02, -8.05585738e-03, -5.70219476e-03, -8.74151941e-03,
       -6.01822464e-03, -1.00628668e-02, -1.63506214e-02, -1.47438217e-02,
       -9.81097296e-03, -1.80508140e-02, -8.30308069e-03, -1.28043732e-02,
       -9.00421664e-03, -2.16182065e-03, -9.62470938e-03, -2.39307107e-03,
       -4.72472981e-03, -3.41863441e-03, -8.02774634e-03, -7.21425004e-03,
       -7.89779611e-03, -1.09953461e-02, -5.47013897e-03, -8.63307901e-03,
       -1.63752493e-02, -1.20921647e-02, -1.94409781e-03, -7.44733727e-03,
       -1.88758634e-02, -3.42045748e-03, -1.63301360e-04, -1.09994309e-02,
       -4.42623813e-03, -2.03244598e-03, -1.79615635e-02,  3.29581182e-03,
       -8.26745294e-03, -4.36615199e-03, -1.05181951e-02, -6.54790504e-03,
       -1.74326655e-02, -8.04466940e-03,  2.67634937e-03, -1.13642020e-02,
       -1.32837454e-02,  2.87239905e-03, -9.87471081e-03, -8.96444451e-03,
       -1.07512521e-02, -1.05927978e-02,  4.28708084e-03, -7.11309630e-03,
       -1.26324706e-02, -7.64730759e-03, -7.50298146e-03, -2.21659150e-02,
       -6.04931312e-03, -1.19746767e-03, -1.07683055e-02, -4.24676668e-03,
       -1.14425113e-02, -8.19853973e-03, -6.08524634e-03, -1.87859926e-02,
       -5.55793382e-03, -7.70811411e-03, -1.58221368e-02, -7.11543998e-03,
       -8.45796987e-03, -1.12679657e-02, -1.18022887e-02, -1.77957322e-02,
       -1.07819093e-02, -5.12080081e-03, -9.50293709e-03, -1.56207411e-02,
        8.24519782e-04, -2.98955641e-03, -1.55155808e-02, -7.76840467e-03,
       -1.84114166e-02, -4.37125703e-03, -1.89583525e-02, -2.04300974e-02,
       -3.13074770e-03, -1.75283197e-02, -1.18927425e-02, -1.09765038e-03,
       -6.35971222e-03, -1.49856815e-02, -1.35988109e-02, -1.39596099e-02,
        2.23228475e-03, -9.00327973e-03, -1.87539589e-02, -1.23685030e-02],
      dtype=float32), array([-1.1866307 ,  0.03644595, -1.9851972 ,  1.7299563 ,  1.6472993 ,
       -1.4693068 , -1.5710207 ,  1.3288743 ,  1.2875162 ,  0.21206617,
        1.8997182 ,  0.7328723 ,  1.9111863 ,  1.047344  ,  1.6582632 ,
        2.2794046 ,  1.8542923 ,  1.1857886 , -1.422731  , -0.32421583,
        0.9361233 ,  1.7904562 ,  1.304395  ,  2.5177715 , -1.4481547 ,
        1.3269364 ,  0.25801793,  0.68441725,  1.2341841 , -1.6230024 ,
       -1.3665614 , -1.8953508 ,  2.1298254 ,  0.7938142 , -1.1613401 ,
       -1.3184597 , -1.0269867 , -1.8726372 , -1.7806777 , -0.3613173 ,
       -0.37935904, -0.93413794, -1.3218231 , -1.0355258 ,  1.3155346 ,
        1.8329477 ,  1.7324551 ,  0.40286076,  1.3234282 ,  1.0120876 ,
       -1.4684672 , -0.76938206,  1.795101  ,  1.0131066 ,  1.4015614 ,
        0.48562422,  0.6147719 , -1.2724994 ,  1.7302114 ,  1.09546   ,
        2.445783  ,  1.9238735 ,  0.0151778 , -1.4338124 ,  1.450113  ,
       -1.9716734 ,  0.7881022 ,  0.440433  ,  1.139317  ,  2.0327592 ,
        1.3545498 , -2.036567  ,  0.3032324 ,  1.8832257 ,  1.2603241 ,
        1.4693732 ,  1.7581531 ,  1.912772  ,  1.0440894 ,  1.4827081 ,
       -0.42910612,  0.3726163 , -1.0619954 ,  1.9405544 ,  0.91733414,
       -1.1055489 ,  0.80968326,  1.211309  , -1.5974075 , -1.143003  ,
       -1.0368521 ,  1.3376433 , -0.90485835,  1.3507762 ,  0.63862616,
       -1.9060333 , -1.141279  ,  2.2918706 ,  0.8246423 , -0.65216565,
        2.3566768 ,  1.5841266 ,  1.1915658 ,  0.43563822,  2.1725368 ,
       -2.2085495 ,  1.9955782 , -1.0156072 , -1.219662  ,  1.6969634 ,
       -1.1280316 ,  1.231975  , -1.2103429 ,  2.2320747 ,  1.053619  ,
        1.1688838 , -1.6098653 , -1.8416423 ,  1.0342567 , -1.4824156 ,
       -1.1307476 , -1.8969885 ,  1.7140568 ,  1.2516165 , -1.28245   ,
        1.0613173 , -0.55283916, -1.6825753 ,  1.646624  , -1.9964324 ,
       -0.86112165, -0.09071486, -1.7142661 , -1.7449865 , -0.8011553 ,
       -1.7768046 , -2.0393019 ,  1.3305141 ,  2.2284927 , -1.0863941 ,
        1.7758223 ,  1.3627354 , -1.5752114 ,  1.1845788 , -1.4981078 ,
       -1.5941814 ,  1.3299578 ,  1.4447329 , -1.073847  , -1.0413706 ,
        0.35022953, -0.98907644, -1.5834728 , -1.7950821 , -0.9647544 ,
       -1.5632938 ,  1.323799  ,  0.6894264 ,  0.7301713 ,  1.3347267 ,
        0.5711498 ,  1.4621263 , -1.3604314 ,  2.1076028 ,  1.3138785 ,
       -0.11274118,  1.0732678 , -1.7741514 ,  0.92033553,  1.4062936 ,
       -1.4330465 ,  0.94356716,  1.4029241 , -0.6992671 ,  1.8038102 ,
        0.7371893 ,  1.7977098 , -2.104573  , -1.6753845 ,  0.8383599 ,
        0.8848916 ,  0.42660984,  0.82347727,  2.0493972 , -1.2569522 ,
        2.1003284 ,  0.1973738 ,  1.188559  ,  0.9214946 ,  1.7326586 ,
        1.3006248 ,  0.77192926,  1.4249673 , -1.4646695 , -1.4031544 ,
       -0.5579419 ,  0.9459484 ,  1.0260952 , -1.1234077 , -0.04236395,
       -0.9970653 , -1.5181981 ,  0.09014044,  1.0156473 , -0.3325405 ,
        1.3857927 , -1.8492004 ,  0.80387086,  0.9395976 ,  1.4817832 ,
        1.4498085 , -1.4572047 , -1.1732318 ,  1.7718276 , -1.0371497 ,
        0.54203534,  1.393299  ,  1.5596724 , -1.2075471 ,  1.4362545 ,
        2.0943658 , -0.7546952 ,  0.89913666,  0.7389367 , -0.88431174,
        1.7805468 , -0.94614273,  1.0507705 , -1.160575  , -2.0489678 ,
        0.81658417,  1.6645372 ,  0.90462744, -1.3231417 ,  1.0429044 ,
        1.4528544 , -1.8910675 ,  2.0057685 , -1.6566659 , -1.1281406 ,
       -0.5833657 , -0.988241  ,  1.3161521 , -1.1170235 ,  1.5849637 ,
        2.221361  ,  1.4061652 ,  2.747597  , -0.9542997 , -1.2953944 ,
        1.4819833 ,  2.346806  ,  1.3023306 ,  2.0521748 ,  1.6141284 ,
        1.7368613 ,  1.3101671 ,  2.2299283 ,  1.1922282 ,  0.10658257,
        0.8280576 , -0.7556868 ,  2.2567205 , -1.1387732 ,  0.84138286,
       -0.9103527 , -1.5134041 ,  1.7207283 ,  1.4779079 ,  0.1663379 ,
        1.2779651 ,  1.9726943 , -1.4274076 , -0.9580871 ,  1.239153  ,
        0.24348132, -1.2961282 ,  0.65131783,  1.8329089 ,  1.587658  ,
       -2.0086627 ,  1.2045622 , -1.6244773 , -1.7485704 , -1.504518  ,
        2.3272054 , -1.0523626 , -2.3348033 ,  1.7031908 , -0.59268636,
        1.3794806 ,  2.2017488 , -1.2061632 , -1.3820615 , -0.859229  ,
        0.5777155 ,  1.9427711 ,  0.528175  , -1.3988625 , -1.3235769 ,
       -0.6271634 , -0.5631553 ,  1.3910205 ,  1.8569031 , -0.51757693,
       -2.2254539 , -1.3335637 ,  1.6186349 ,  1.4085388 ,  1.5088353 ,
        2.0614083 , -0.48352894,  0.57903856, -1.1376692 , -1.410958  ,
       -1.4796178 ,  1.7203329 ,  1.0162059 ,  1.0817014 ,  0.04017982],
      dtype=float32), array([ 9.72779  ,  8.912132 , 12.34521  , 12.816311 ,  7.5907226,
        9.539232 , 16.339952 ,  6.9823337,  6.701725 ,  3.883491 ,
        9.871243 ,  7.7278934, 10.325431 ,  3.6067235, 12.164184 ,
        6.638004 , 10.324284 , 10.997705 , 12.839448 ,  4.0286584,
        8.532297 ,  6.0147214,  5.4502997, 15.908043 ,  6.7520084,
        6.7812862,  4.8205504,  4.446495 ,  6.584571 , 13.557023 ,
       13.580947 , 13.244971 ,  7.740211 ,  4.6169596, 15.409658 ,
       11.573096 ,  5.1855936, 19.072104 , 12.917586 ,  1.6596787,
       12.676416 ,  9.897152 ,  7.3417687,  2.535997 , 11.95622  ,
       11.960351 , 10.63941  ,  5.0547576,  8.884932 ,  5.439802 ,
       12.464743 ,  2.8707209, 16.27401  , 10.7822075,  8.383813 ,
        8.035791 ,  3.2883034, 10.431315 , 14.242097 ,  8.9435   ,
       12.75237  , 13.106354 ,  5.659929 ,  5.513728 , 12.137445 ,
       13.256524 ,  2.6809845,  7.1692047,  4.014475 , 11.073552 ,
        5.1863413,  4.9251585,  4.3288374, 13.757956 ,  8.388079 ,
       11.041569 ,  8.9930315, 10.167702 ,  5.85222  ,  8.573329 ,
        4.158351 ,  7.388745 ,  2.9164412, 15.611345 ,  6.3526073,
        5.4169564,  8.542522 , 11.489281 , 12.564525 ,  8.640499 ,
        8.287739 ,  8.171201 , 12.839317 , 10.259983 ,  6.190325 ,
       19.04548  ,  5.812741 , 11.75659  ,  6.3622584,  4.5349154,
       17.73707  ,  8.41547  , 10.514568 ,  7.350628 , 19.400267 ,
        6.587453 , 10.760512 ,  7.0621357, 20.057919 , 10.789878 ,
        9.5710535,  8.811082 ,  8.823785 , 12.643928 ,  6.298178 ,
        9.059795 , 16.225918 ,  8.311927 ,  7.6483817,  9.012304 ,
       11.615616 ,  8.731688 , 11.822505 , 13.181315 ,  8.021547 ,
        5.835224 ,  4.7228317,  8.024076 , 12.872443 ,  9.359798 ,
        3.2286537, 10.693714 ,  7.1406884,  9.025225 ,  3.9506176,
        5.9790416, 11.164124 , 10.454923 , 15.865874 ,  9.8125305,
       10.0351305, 12.877368 ,  7.509431 ,  7.8048196, 10.337099 ,
        4.9134617, 10.265463 , 11.23573  , 10.077164 ,  6.9281173,
        3.8767734, 23.831898 , 11.587732 , 17.961517 , 18.698923 ,
        7.2288685, 11.587938 ,  5.0379405, 11.103807 , 10.266904 ,
        4.5521955,  5.8928595,  5.0782046,  9.241321 ,  8.6128645,
       13.683339 ,  5.3218284, 15.881024 , 10.805076 ,  9.516088 ,
       18.780624 ,  8.392792 , 12.3219595,  3.7834618, 11.785533 ,
        5.3970375, 11.123996 , 11.46018  , 15.303876 ,  4.228498 ,
        9.633416 ,  4.0810404,  9.043238 , 10.952105 ,  5.121667 ,
       20.369667 ,  9.452814 ,  8.5755205,  6.743348 ,  7.5269175,
       13.546909 , 13.235268 , 10.422584 , 16.705944 , 16.304752 ,
        3.6376371,  7.5682077, 12.155692 ,  6.7951856,  3.0299745,
       10.681267 ,  8.64744  ,  3.6254587,  9.122166 ,  7.4241633,
        7.1592445, 16.596298 ,  5.2789764,  8.229079 , 12.087859 ,
        6.46646  , 10.861424 ,  9.985589 , 12.381478 ,  3.9715598,
        3.9622633, 11.545713 , 11.512813 ,  7.089727 ,  6.9349113,
       20.957956 ,  1.6569502, 10.368203 ,  6.1277137,  4.17182  ,
        8.445292 ,  4.514085 , 12.539454 ,  4.9922986,  8.677236 ,
        5.762479 , 11.576101 ,  4.390488 , 11.800086 , 13.62878  ,
       16.653803 ,  3.3172784, 14.45608  , 12.89613  ,  5.59788  ,
        4.8974013,  5.672881 , 12.354912 , 10.574786 ,  8.710016 ,
       14.132656 ,  7.0535307, 25.08884  ,  9.20958  , 11.734021 ,
        7.3620043, 18.179195 ,  7.6328516,  9.934672 ,  7.118391 ,
       11.293327 ,  6.5438123, 15.619769 , 11.081197 ,  2.3283472,
        7.415002 ,  9.225244 , 13.418993 , 10.08851  ,  9.415645 ,
        8.283818 , 10.511436 ,  6.927779 , 13.760009 ,  3.745463 ,
       11.302026 , 15.305818 ,  5.7150617,  6.9109187, 13.857973 ,
        3.3054261,  6.1825376,  7.2459064,  8.870722 ,  8.471766 ,
       23.37526  ,  8.920546 , 10.715065 , 24.5441   ,  8.481632 ,
       23.036764 ,  8.739916 , 20.169556 , 10.078719 , 11.429542 ,
        7.6757126, 18.368868 ,  9.3654585, 13.291355 ,  3.7647212,
        2.7580338, 11.466427 ,  6.314056 ,  4.805145 ,  2.6664445,
        2.7327838,  6.329536 ,  9.552118 , 16.301931 ,  3.429408 ,
       22.332413 ,  7.439097 , 14.763117 , 11.466787 , 12.381899 ,
       19.801163 ,  3.346295 ,  6.1631627,  9.188799 ,  7.5667   ,
        8.466116 , 11.598254 ,  7.3485327, 12.398292 ,  4.4698887],
      dtype=float32), array([-1.19797164e-03, -9.35482979e-03, -1.48439938e-02, -7.29812169e-03,
       -1.10896667e-02,  3.56789446e-03, -1.38969757e-02, -1.44137824e-02,
       -8.65169242e-03, -1.22447005e-02, -1.21144932e-02, -7.88202044e-03,
       -9.01277456e-03, -1.97524969e-02, -1.22233639e-02, -4.92511690e-03,
       -9.15750023e-03, -1.00215087e-02, -1.45732164e-02, -1.31457755e-02,
        5.60213160e-03, -1.31864715e-02,  3.00260307e-03, -7.80052366e-03,
       -1.13441665e-02, -1.12506207e-02, -7.42372405e-03, -6.97514461e-03,
       -5.59312617e-03, -1.26796709e-02, -1.02252150e-02, -1.46871256e-02,
       -1.19870622e-02, -2.77707842e-03, -1.70615725e-02, -1.14157712e-02,
       -1.73477866e-02, -1.24949766e-02, -5.56154596e-03, -4.89512319e-03,
       -7.91617390e-03, -5.74367400e-03, -1.13870781e-02, -2.19747629e-02,
       -8.33242666e-03, -1.43635636e-02, -1.12794843e-02, -6.26580464e-03,
       -4.46670828e-03, -1.20236110e-02, -4.37891204e-03, -9.83288512e-03,
       -1.23073878e-02, -1.47906085e-02, -8.33069999e-03, -1.38388323e-02,
        4.52069053e-03, -2.76665334e-02, -1.64427217e-02, -8.70088488e-03,
       -2.66704918e-03, -8.54184944e-03, -1.20647028e-02,  8.48338823e-05,
       -3.59341473e-04, -1.03196707e-02, -7.05404393e-03, -8.08265153e-03,
       -7.36959558e-03, -1.21320300e-02, -6.48370385e-03, -7.56178331e-03,
       -6.07448304e-03, -1.41048953e-02, -2.15843301e-02, -1.82783175e-02,
       -1.05665959e-02, -6.59148628e-03, -2.71446165e-03,  2.60129781e-03,
       -1.37440907e-02, -9.49424598e-03,  2.52447883e-03,  5.09909733e-05,
       -1.02888104e-02,  1.58006023e-03, -3.84524511e-03, -1.98603375e-03,
       -1.44360960e-02, -1.39062367e-02, -1.75402407e-02, -1.05215786e-02,
       -2.76793749e-03, -1.07052028e-02, -2.20351899e-03, -9.96136293e-03,
       -1.33063374e-02, -7.76521908e-03,  5.56405517e-04,  4.38638264e-04,
       -7.75207207e-03, -1.20982025e-02, -6.62825117e-03, -1.56588163e-02,
       -1.03029842e-02, -1.51469531e-02, -8.32971651e-03,  4.11811424e-03,
        1.09533803e-03, -1.49497259e-02, -5.91621501e-03,  8.95634294e-03,
       -1.78801715e-02, -8.51489417e-03, -2.28733458e-02, -9.14477918e-04,
       -8.36486369e-03, -1.84738021e-02, -1.90105923e-02, -6.41082833e-03,
       -5.96164027e-03, -1.00203436e-02, -1.16012208e-02, -3.78354709e-03,
       -1.00838449e-02, -1.28863696e-02, -4.99797845e-03, -4.51434928e-04,
       -1.30456602e-02, -8.38879682e-03, -1.00266663e-02, -1.04470027e-03,
       -6.31079543e-03,  8.82178266e-03, -1.57414917e-02, -4.62215161e-03,
        1.52917666e-04, -9.53194872e-03, -1.34094749e-02, -3.03783198e-03,
       -5.04827313e-03, -1.71528310e-02, -1.51606584e-02, -8.00140947e-03,
       -1.40340365e-02, -1.42446654e-02, -1.21566821e-02, -1.64844766e-02,
       -8.08324106e-03, -1.21642221e-02, -1.17010120e-02, -4.74269176e-03,
       -5.12493216e-03, -9.87486914e-03, -1.69859491e-02,  1.45568454e-03,
       -5.52048581e-03,  5.14603045e-04, -1.07439216e-02, -1.27025396e-02,
       -7.81095820e-03, -1.24988370e-02, -2.95987446e-02, -1.14623718e-02,
       -1.71828810e-02, -1.20232981e-02, -7.72703532e-03, -1.89617127e-02,
       -9.05837584e-03, -1.28647982e-04, -1.73807759e-02, -1.15601961e-02,
       -9.49935243e-03, -3.63278529e-03, -4.87210881e-03, -9.99551453e-03,
       -4.77489736e-03, -7.10804807e-03, -6.61230646e-03, -1.52673768e-02,
       -2.58847512e-02, -1.27663696e-02, -8.36201943e-03, -1.50733385e-02,
       -7.26811634e-03, -1.27718840e-02, -3.93215520e-03, -2.02840492e-02,
       -2.44438853e-02, -1.05804903e-02, -1.13935610e-02, -8.98535922e-03],
      dtype=float32), array([ 1.5010818 , -1.940124  , -2.7839696 ,  1.8572032 , -1.268944  ,
        0.27503696,  0.36484158, -1.6454601 , -1.7148762 ,  1.196129  ,
       -1.7419366 , -1.2420365 ,  1.1823046 , -1.4999226 ,  1.1815282 ,
       -1.8197465 , -1.0686793 ,  1.146754  , -0.9080217 ,  2.0709417 ,
       -0.81015044, -0.19655326, -1.2936485 , -1.9046154 ,  2.3227055 ,
       -1.2763531 ,  0.7257551 ,  0.60027   , -1.7406975 , -1.1466027 ,
       -0.94403166, -2.0261729 ,  0.9955609 , -1.332394  , -1.1422714 ,
       -1.0785625 ,  1.4657085 ,  1.7209225 , -1.5604649 ,  1.5213078 ,
        1.1159163 , -1.6389823 ,  1.6405163 , -1.5679564 ,  0.94663733,
        0.43712246, -1.5476993 ,  0.8960624 , -1.7819904 , -0.6784088 ,
       -1.6338512 ,  1.8256459 , -0.7371674 , -2.7145722 , -1.7106283 ,
       -0.68280536, -1.1117833 , -0.9098711 , -1.0451972 , -1.4393132 ,
        0.22692893,  1.5875018 ,  1.2599354 ,  0.20423372, -1.4754649 ,
       -1.7301215 , -0.7808139 ,  1.461664  , -1.1700912 ,  1.3675567 ,
       -1.0792135 , -1.2611619 ,  1.244524  ,  1.1274333 ,  1.861805  ,
        2.51394   , -0.830638  ,  2.2902699 ,  1.0627456 , -1.9130925 ,
       -1.1986353 ,  1.2958266 , -2.4221776 ,  1.7999941 ,  2.0197046 ,
        0.43111256, -1.3308827 , -2.378894  ,  1.4305005 ,  1.53874   ,
        0.97106385,  1.3819251 , -1.4504843 , -2.1750152 , -1.8378017 ,
        0.927944  ,  1.1939236 ,  1.4182168 ,  1.7861407 , -1.4871715 ,
       -1.5159544 , -0.50834864,  0.83804715,  1.0047857 ,  0.61821777,
        1.3010218 ,  1.4256368 , -0.9913967 ,  1.6407542 , -0.8034415 ,
        2.0496948 , -2.247014  ,  1.5746571 , -1.8843462 ,  2.277534  ,
        1.7590978 ,  1.0430652 ,  2.4363308 , -2.2199485 , -0.48528373,
        1.5482345 ,  0.01918492,  1.8940616 , -0.5034192 , -1.152699  ,
        1.2210324 , -2.1812575 , -1.8196583 ,  0.9092871 , -1.0568126 ,
       -1.1368825 ,  1.0579797 , -1.9332789 , -1.3081733 ,  1.7676383 ,
       -0.39299855,  0.82964987, -1.4565047 ,  1.8675153 , -0.94176555,
        0.48365945,  1.069108  ,  1.2015934 ,  1.4809844 ,  1.1638099 ,
        0.9672667 ,  0.7336731 ,  1.2533004 , -1.232315  ,  0.5696774 ,
        0.47111234,  0.86705977,  1.7125924 ,  1.9224674 ,  0.98715526,
        1.0693754 , -0.22214581,  0.85029626,  1.8820572 ,  1.282612  ,
       -1.9926378 , -1.1490304 ,  1.103456  ,  1.1527867 ,  1.7120988 ,
       -1.1268585 ,  1.3107976 ,  1.496888  , -2.0954757 ,  1.970632  ,
       -1.9085901 , -1.4084188 , -0.9082097 , -0.278629  ,  2.984939  ,
       -0.9402674 , -0.8755458 ,  1.9759632 , -1.6152109 ,  1.6613755 ,
       -2.0485783 , -0.8572992 , -1.6674355 ,  1.4729708 ,  1.2058097 ,
       -2.0409362 , -1.6001887 ,  1.6068629 ,  1.5593144 , -1.6622933 ,
       -1.154508  ,  1.4103296 ], dtype=float32), array([ 6.9700217,  7.2797503, 25.254313 , 11.911222 , 14.210536 ,
        5.1534104,  3.7458634,  8.436576 , 14.758264 ,  4.743689 ,
        9.725005 ,  7.2976494,  7.098472 ,  8.14267  ,  7.1889453,
       12.938171 , 17.554068 ,  9.32574  , 10.698523 , 10.190443 ,
        7.3368187,  5.1702685,  7.1657577,  6.80152  , 10.32271  ,
        6.375706 ,  7.109476 ,  3.7014909,  7.075343 , 16.770008 ,
        1.8117948, 21.085361 ,  4.9977474,  9.854352 , 13.342974 ,
        3.1119943,  7.933928 ,  8.502778 ,  6.5867667,  9.379299 ,
        9.88467  ,  7.510721 ,  4.6047735, 12.625824 ,  3.8443325,
        7.662087 ,  7.8856745,  1.8153156,  4.0921664,  7.2202797,
       13.114753 ,  6.9553576,  4.5868235, 14.090693 ,  7.573644 ,
        9.655466 ,  6.365486 ,  2.336236 ,  5.5089693, 16.87597  ,
        0.9179913,  8.699214 ,  4.6783977,  5.979319 ,  7.343066 ,
        9.2498255,  5.3280916,  5.998303 ,  7.8449993,  6.764052 ,
        5.7020354,  3.093676 ,  6.335897 ,  7.486369 , 11.063813 ,
       14.640857 ,  4.8432894, 11.984497 , 12.614977 ,  4.8316426,
        3.538613 , 10.779922 ,  7.4379077, 11.849605 ,  4.796203 ,
        3.349726 ,  6.1185493, 14.545115 , 12.097574 ,  9.306374 ,
        7.3714805,  8.044151 ,  5.9546485, 12.563983 , 20.057339 ,
        9.473882 ,  8.189969 ,  4.39603  ,  9.250266 ,  5.7929044,
        9.68306  ,  2.3480163,  7.1994886,  7.3152113,  5.0144258,
        9.104552 ,  7.083662 ,  5.178471 ,  5.4416447,  7.027939 ,
       11.8460245, 13.668066 ,  8.412097 , 15.951962 , 14.567319 ,
       10.961199 ,  8.565159 , 11.182145 , 13.525653 ,  3.7775857,
       11.294178 , 10.229336 ,  6.498356 ,  3.942894 ,  7.408244 ,
        5.2087774,  8.891474 , 13.060361 ,  3.418475 , 12.367422 ,
        3.8585577,  7.8475995,  7.375094 ,  8.585145 , 10.119594 ,
        3.416598 ,  4.2498927,  5.322613 ,  6.1824274,  5.8354945,
        2.538108 ,  6.6019993, 10.347823 ,  7.9835653,  5.328929 ,
        7.9311147,  5.7246213,  8.178059 ,  4.619894 ,  2.5271735,
       14.431734 ,  7.932059 , 10.26726  ,  9.862233 ,  7.8551164,
        3.5248597,  6.373506 ,  6.774139 , 10.103738 ,  8.029836 ,
       11.178613 ,  3.9196422,  7.0378957,  9.39788  ,  8.679942 ,
        7.049543 , 12.04518  , 15.927422 ,  6.7377033, 10.708141 ,
       10.245118 ,  7.23119  ,  8.975251 ,  6.2624016, 19.830635 ,
        2.248569 ,  9.09777  ,  9.938704 , 16.42377  , 12.525195 ,
       10.072273 , 11.851345 , 16.80813  ,  4.527202 ,  3.6450105,
       10.954517 ,  7.561649 ,  5.875348 ,  6.630857 ,  8.610536 ,
        9.250275 ,  9.9715395], dtype=float32), array([[[[ 0.03824848, -0.04513322, -0.04412028, ..., -0.04812806,
          -0.00667929,  0.01443307],
         [ 0.00981962,  0.05217533, -0.01238753, ..., -0.03712395,
           0.0582062 ,  0.02306977],
         [-0.04293659,  0.02270682,  0.00440877, ..., -0.0342926 ,
          -0.01246664,  0.01019673],
         ...,
         [-0.0504725 ,  0.05416413, -0.03915357, ...,  0.02859883,
           0.03296903,  0.02437702],
         [ 0.02917245,  0.04842818, -0.01381702, ...,  0.03241796,
           0.00552326,  0.04584365],
         [-0.00437578, -0.02385178, -0.02005715, ...,  0.03848523,
          -0.02220561,  0.0303963 ]]]], dtype=float32), array([ 2.11387104e-03, -1.36394892e-02, -6.18599867e-03,  1.17923077e-02,
       -6.88507408e-03, -1.60779734e-03,  4.42766491e-03, -1.87353864e-02,
       -2.33350811e-03,  1.54546893e-03, -2.20394507e-03, -1.48036098e-02,
        1.04438039e-02, -7.93047249e-03, -5.21103991e-03, -4.06785123e-03,
       -5.86766331e-03, -2.30004289e-03, -2.99505959e-03, -9.54743155e-05,
       -1.64939603e-03, -8.99478793e-03, -2.16201097e-02, -1.04310615e-02,
       -2.17525521e-04,  1.46424829e-03, -1.24239549e-02,  9.39965394e-05,
       -1.06541421e-02, -6.00059936e-03,  1.38876063e-03, -4.08511842e-03,
       -7.84751144e-04, -2.16719508e-02, -9.98985581e-03, -5.51867625e-03,
       -1.68390721e-02,  3.10627208e-03, -6.53363159e-03, -7.09186122e-03,
       -2.50246027e-03, -4.30835673e-04, -3.00101261e-03, -8.33754893e-03,
        4.71400563e-03, -2.81478511e-03, -2.44101719e-03,  1.76093169e-03,
        2.18658545e-03,  2.27896054e-03,  1.08052845e-04,  8.05626158e-03,
       -9.46064945e-03, -1.75011088e-03, -6.41671754e-03, -4.55275876e-03,
        3.80822225e-03, -4.67492593e-03, -1.18728653e-02, -9.65393428e-03,
       -4.10514604e-03, -1.45865586e-02, -4.42131516e-03, -1.11327786e-02,
       -9.32912249e-03, -2.19027465e-03, -1.42026003e-02, -7.13728182e-03,
       -9.35902912e-03, -9.04824119e-03, -1.12946387e-02, -1.33265099e-02,
       -2.32390780e-03,  4.08247067e-03, -6.03385409e-03,  1.43631629e-03,
        5.49588120e-04, -1.28282337e-02, -9.96944681e-03, -1.49931693e-02,
       -7.92898424e-03, -1.04236957e-02,  6.40088739e-03, -6.12585619e-03,
       -1.06813610e-02, -1.41610568e-02, -3.45345587e-03, -1.09355794e-02,
       -6.95199752e-03, -1.47963110e-02,  3.41246044e-03, -5.50750643e-03,
       -1.26374383e-02, -7.75207859e-03, -3.51460907e-03, -3.50685767e-03,
       -1.45389605e-02, -1.30988844e-03, -7.56026013e-03, -2.45978474e-03,
       -1.14382664e-02,  2.90418114e-03, -1.07448036e-02, -7.22809834e-03,
        2.54856446e-03, -3.30271828e-03,  1.54283980e-03,  2.05096090e-03,
       -7.41379522e-03, -1.11586126e-02, -1.76185637e-03, -1.48241492e-02,
       -1.39594078e-02, -1.39783062e-02, -5.65289333e-03, -3.05540045e-03,
       -4.86236066e-03, -2.08353586e-02, -1.03343092e-02, -5.45533979e-03,
       -6.83517335e-03, -3.46499938e-03, -1.28694512e-02, -4.24292684e-03,
       -1.28808878e-02, -9.23963264e-03, -1.33992648e-02, -7.41167599e-03,
       -1.14777880e-02, -9.51058511e-03, -4.45093960e-03, -1.74157321e-02,
        3.63689917e-03, -1.13591319e-02, -1.57082006e-02, -1.01967668e-02,
        5.09670237e-04, -1.15643675e-02, -3.28518171e-03, -9.53101646e-03,
       -1.41197499e-02,  1.52249879e-03, -2.75692041e-03, -1.03886286e-02,
       -1.10694850e-02, -1.14090536e-02, -1.87092293e-02, -6.98769372e-03,
       -1.09064477e-02,  5.48989919e-04,  4.16017231e-03, -5.10390988e-03,
        4.55156187e-05, -5.99949015e-03,  1.08264736e-03, -1.10902926e-02,
       -1.16802547e-02, -5.97492326e-03, -9.36659332e-03, -1.26613416e-02,
       -8.89325235e-03, -4.57277813e-04, -1.04264459e-02, -5.65079693e-03,
       -7.44369254e-03, -6.48814626e-03, -6.19627116e-03, -4.31909086e-03,
       -5.10260416e-03, -4.94145229e-03, -7.80990021e-03, -9.09647439e-03,
       -2.02336581e-03, -1.96703114e-02, -1.05180265e-02, -8.94883368e-03,
       -2.81369104e-03, -2.00930946e-02, -9.12355259e-03, -1.77971162e-02,
       -2.57865456e-03, -6.96020317e-04, -4.05121641e-03, -1.20988376e-02,
       -8.45260918e-03,  1.73379434e-03, -1.09981671e-02, -1.05688432e-02,
       -7.67072244e-03, -1.53464370e-03, -1.22317215e-02, -2.86272056e-02,
       -3.10222642e-03, -1.05996141e-02,  1.93875562e-03, -8.67987401e-04,
        2.77478574e-03, -2.08365964e-03, -2.47556460e-03, -5.94036281e-03,
       -7.00240606e-04, -1.19632133e-03, -1.43488012e-02, -1.31108798e-03,
       -6.49675122e-03, -1.61778033e-02, -4.78134910e-03,  2.55633588e-03,
        1.13544590e-03, -7.52063282e-03, -3.92430415e-03,  1.14376680e-03,
        8.50582845e-04,  5.94968768e-03,  4.97252273e-04, -9.38475411e-03,
       -1.12474635e-02, -2.35344050e-03,  3.85038764e-03,  9.69091197e-04,
       -1.01236310e-02,  1.33753335e-03, -7.88643677e-03, -7.04611419e-03,
        6.51338324e-03, -1.30211422e-02, -6.20170170e-03, -2.74065579e-03,
       -1.00707877e-02, -8.48380476e-03, -7.85679463e-03, -5.88462548e-03,
       -1.11903083e-02, -7.95371085e-03, -4.45403019e-03, -3.29917623e-03,
       -3.29963164e-03, -5.15410956e-03, -1.11989705e-02, -3.79294786e-03,
       -1.52449794e-02, -2.24261289e-03, -4.10583010e-03, -7.69956037e-03,
       -1.34368232e-02,  5.54518600e-04, -2.11093370e-02, -1.34249469e-02,
       -1.00705901e-03, -5.02117584e-03,  6.25039858e-04, -1.02835428e-02,
       -5.30148900e-05, -7.48060178e-03, -2.63005332e-03,  5.02924481e-03,
       -2.09897920e-03,  1.74078513e-02, -3.30565521e-03,  1.92427833e-03,
       -8.06106068e-03, -5.04048681e-03,  7.46887992e-04, -9.63223260e-03,
       -7.49798212e-03, -6.35971921e-03, -1.41325581e-03,  4.99895541e-03,
        1.78643898e-03, -1.48104792e-02,  2.35223770e-03,  4.95784159e-04,
       -1.01203229e-02, -1.30537115e-02, -1.34113729e-02, -1.51322242e-02,
        4.38464805e-03, -1.12383328e-02,  4.73467866e-03, -1.49762966e-02,
       -1.89245921e-02, -1.17573468e-02, -1.07713416e-02, -7.26815965e-03,
        4.96685086e-03,  1.02366286e-03,  9.31499409e-04, -1.15040373e-02,
       -1.22584933e-02, -1.06401350e-02, -1.41671207e-02, -2.42725131e-03,
       -4.05000942e-03, -6.73052482e-03, -1.24963867e-02, -3.77349555e-03,
       -8.31488054e-03, -1.67880226e-02, -1.03816353e-02, -5.00731310e-03,
       -9.89687070e-03, -1.03038587e-02, -1.00212079e-02, -9.46236588e-03,
       -2.33784923e-03, -1.00944191e-02, -1.03865925e-03, -2.69375485e-03,
       -5.04123466e-03, -4.56222286e-03, -1.51502760e-02,  2.42066081e-03,
       -1.02668749e-02, -7.11903162e-03, -4.52481862e-03, -1.09967394e-02,
       -6.49684761e-03,  2.92270444e-03, -8.18384439e-03, -7.20104761e-03,
       -3.10096191e-03, -9.70393047e-03, -7.79146422e-03, -1.11111244e-02,
       -2.01493558e-02,  7.40979193e-03,  1.94563938e-03, -1.52265569e-02,
       -4.25038068e-03, -2.08920762e-02, -9.67069808e-03, -7.57526187e-03,
       -7.99455214e-04, -1.58675257e-02, -1.48975337e-02, -1.24693019e-02,
       -2.91969604e-03, -1.86008923e-02, -8.98286048e-03,  1.59787305e-03,
        2.83937482e-03, -5.51313767e-03, -4.49819677e-03, -5.09804068e-03,
       -1.00507904e-02, -9.53069422e-03,  2.44989828e-03, -2.16194964e-03,
       -1.07057963e-03, -2.49292864e-03, -1.68891493e-02, -1.27365235e-02,
       -3.55457934e-03,  3.25006619e-03, -2.05201074e-03,  4.49931389e-03,
       -1.87024777e-03, -1.18341614e-02, -3.27760959e-03,  2.97640986e-03,
       -2.08759244e-04, -8.48030392e-03,  2.03172537e-03, -2.80210306e-03,
       -8.51551350e-03, -1.48326745e-02, -1.43632211e-03, -5.92043297e-03,
       -7.16144033e-03, -1.16790384e-02, -6.50426280e-03, -2.60066241e-03,
        3.20121180e-03, -1.09964842e-02, -3.35317978e-04,  2.69917934e-03,
       -1.64895132e-02, -1.87510159e-02,  5.98086417e-03,  9.22332576e-04,
       -1.01013668e-02, -7.38681573e-03,  3.02789849e-03, -6.10487722e-03,
       -3.57612665e-03, -1.32430270e-02, -4.13182238e-03, -8.43591709e-03,
        2.64058297e-04, -1.48110595e-02,  1.48655812e-03, -8.16692691e-03,
       -6.88625732e-03, -6.89770328e-03,  3.80936521e-03,  9.95512935e-04,
       -1.27352839e-02, -1.10600526e-02, -1.86176859e-02, -5.13838790e-03,
       -8.05146620e-03, -1.26176588e-02,  4.07969439e-03,  1.65404024e-04,
       -1.82802435e-02,  2.29023094e-03, -2.18873750e-02, -9.79908556e-03,
       -1.02451369e-02, -1.19410427e-02,  3.28768278e-03, -1.06285401e-02,
       -7.71563267e-03, -2.73854611e-03, -4.11734916e-03, -9.87971667e-04,
        6.41534384e-03, -3.95995239e-03, -5.83184930e-03, -1.33905932e-02,
       -5.46602486e-03, -5.62469009e-03,  3.07755196e-03, -1.24998931e-02,
       -1.09386630e-02,  7.15384074e-03, -1.47366906e-02, -8.60256981e-03,
       -2.39871349e-03, -1.21738240e-02, -1.19236419e-02, -2.36646435e-03,
       -1.30091906e-02, -9.63388197e-03, -4.25036764e-04,  1.11005886e-03,
       -1.16907842e-02, -4.36014822e-03, -4.44058422e-03, -8.44906643e-03,
       -4.93313000e-03,  5.31228550e-04,  9.42545664e-03, -1.27393296e-02,
        1.26692827e-03,  1.20293081e-03, -1.02519272e-02, -6.73328619e-03],
      dtype=float32), array([-1.204184  ,  1.8893402 , -1.8639778 , -1.2515662 ,  1.8362895 ,
        1.4743478 , -1.5063037 ,  1.5324376 ,  1.2020953 , -0.95276195,
       -2.2099986 ,  2.2904618 , -0.4443217 , -0.58856606, -1.4256572 ,
        0.6457477 , -1.322589  ,  1.2536808 , -1.158312  , -0.97701246,
        1.2589945 , -1.3479862 ,  1.832697  ,  1.1400071 , -1.1871897 ,
       -1.5429572 , -1.7061481 , -1.0546    ,  1.9656576 ,  1.0527934 ,
       -0.96713513,  0.7410391 , -0.80284166,  2.029205  ,  1.1824462 ,
        1.0890121 ,  1.9496449 , -1.923262  , -1.4363225 ,  1.4252701 ,
        1.7708025 , -0.7649215 ,  0.7667193 ,  1.3316487 , -0.9895607 ,
        1.097996  , -1.8981514 , -0.8709916 , -1.0343858 , -1.0797799 ,
       -0.7657952 , -0.75330055,  2.100409  , -1.1628284 , -1.6720085 ,
        1.1742172 , -0.7796444 , -0.90018183,  2.0627668 , -0.9055139 ,
        1.9117783 ,  1.4126239 ,  0.8905291 ,  1.9667683 ,  1.7439709 ,
       -1.6179652 ,  1.5549085 , -1.8636186 ,  2.053625  , -1.0555038 ,
        1.1604004 ,  1.8839862 , -0.9941882 , -2.0655181 , -1.4735678 ,
       -0.81495106,  1.1500336 ,  0.9361062 , -0.8738617 ,  1.5061947 ,
        1.2764226 , -1.2364123 , -0.5487362 , -1.2048162 , -0.8148421 ,
        1.3911041 , -1.7323631 ,  0.88887495,  1.1179774 ,  1.2425209 ,
       -1.6520582 ,  1.0064996 ,  1.2512598 , -0.77579653,  0.9171847 ,
       -1.0691171 ,  0.5808492 , -1.2571337 , -1.1811094 ,  1.86853   ,
       -1.8052546 ,  1.1447644 ,  1.0607781 , -1.0643045 , -1.2939786 ,
       -1.0244288 , -1.3680731 , -0.81296146,  0.6997238 ,  1.7770729 ,
       -1.1288805 , -0.02087975,  0.73673093, -1.7592146 , -1.5589875 ,
        1.654326  ,  1.040216  ,  1.9193068 , -1.1906115 ,  1.649454  ,
       -0.71735173, -1.408466  , -1.4510494 , -0.81902546,  1.6443465 ,
       -1.1260186 ,  1.1789747 ,  1.8290606 ,  1.0846105 ,  1.2227359 ,
        1.3213636 ,  1.7829834 , -0.6901561 ,  1.7777194 ,  1.6056689 ,
       -0.00709617, -1.5590512 ,  1.4024097 ,  0.67529076, -1.1163667 ,
       -1.2214005 , -1.7420911 , -1.7502309 , -1.0394151 , -1.0822674 ,
       -0.8417962 ,  2.3636363 ,  1.1816764 ,  1.5829973 , -0.9841389 ,
       -1.02764   , -1.3480159 ,  0.72792214,  1.1250131 , -1.5910317 ,
        1.0632718 ,  1.9829882 , -0.36007497,  1.184729  ,  0.95317745,
        1.7169873 , -0.97233087,  2.2053328 , -1.0789803 ,  0.67038727,
        0.8991516 , -0.94116974,  0.9177436 ,  0.9604916 , -1.403339  ,
        1.9371656 , -1.4888333 ,  0.6068872 ,  0.96188956,  1.4874513 ,
        0.45916417, -0.74712473,  1.4683814 ,  2.1252873 ,  0.9792746 ,
        1.618759  ,  0.90868986, -0.8773923 ,  1.0913424 ,  1.588761  ,
       -0.9615981 ,  1.9549716 ,  0.8127172 , -2.0103602 , -1.2478144 ,
        1.6104046 ,  1.3757821 , -1.2776483 ,  1.560878  , -0.7241382 ,
       -1.562609  , -1.1007345 , -0.7418383 ,  1.7835988 ,  1.7478151 ,
       -1.7107738 , -1.3714075 ,  1.6721966 , -0.7099746 ,  0.03759692,
        0.56825584, -1.0388983 , -0.92583275,  0.75649804, -1.9057919 ,
        1.4800636 , -1.4366634 ,  0.69102484, -1.3729407 ,  0.78040236,
        1.7177607 ,  1.2895974 , -1.3698864 , -1.7101293 , -0.7520202 ,
        1.118867  , -1.1041282 ,  1.0012603 ,  0.5341262 , -1.6598238 ,
        1.0763487 ,  1.0137876 , -1.2198002 , -1.6342672 ,  1.8883475 ,
        0.785249  , -0.90889305,  0.25970638,  0.594951  , -1.3424054 ,
        1.1090611 ,  0.8752992 , -0.84084934,  0.98559374,  0.23943709,
       -1.6724328 , -1.4868702 , -0.58469576,  1.1348225 ,  1.1911385 ,
       -1.682691  ,  1.2208987 , -1.5467341 , -1.7119479 ,  0.9763349 ,
       -1.116123  ,  1.636616  , -1.1391131 , -0.3991672 , -1.3328085 ,
       -0.9356381 , -1.619377  , -0.8447451 , -1.771995  , -2.0144265 ,
        0.46992278, -0.40940812, -1.4442819 ,  1.1294689 , -1.5027858 ,
       -1.1519266 , -1.4830683 , -1.0429978 , -1.4134561 ,  1.0997119 ,
       -1.3959067 , -2.2111888 ,  1.9563456 ,  1.5699706 ,  2.1138475 ,
        1.2998253 , -1.4081515 , -1.2771332 , -1.2618065 ,  1.6081563 ,
        1.6521077 ,  1.1784239 ,  1.394648  ,  2.0300932 , -1.6263524 ,
       -1.5746464 ,  0.8858478 ,  0.53823924, -1.0023521 ,  1.3297366 ,
       -1.9537661 , -2.0130196 ,  0.31160852,  0.70965415, -1.1927286 ,
        0.3261475 ,  2.1759398 ,  1.7833964 ,  1.8223085 , -0.938058  ,
        1.9081634 , -1.1624173 ,  1.6469228 ,  1.5073119 , -0.6578519 ,
       -1.6252358 , -1.4696974 , -0.95299345,  0.6831697 ,  1.1769181 ,
        2.1464133 , -1.8353336 ,  1.6798283 , -1.6453105 ,  0.5665452 ,
       -1.4448551 , -1.6338857 , -1.5122818 ,  0.31505996,  1.2167635 ,
       -1.2824852 ,  1.2939296 , -1.0934423 , -1.341157  ,  1.9169024 ,
       -1.0170164 , -1.6866901 ,  1.1822708 ,  0.6601513 ,  1.5226382 ,
        2.4220977 ,  1.622213  , -0.8301274 ,  1.6445427 ,  0.8832251 ,
       -0.971875  ,  1.0969408 ,  1.8336419 ,  1.9146245 ,  1.0050813 ,
       -1.0549834 ,  1.2843246 ,  1.0512322 ,  1.2932227 ,  1.2996742 ,
        1.4020479 , -1.7677823 , -1.0704584 ,  1.7358011 , -1.1925938 ,
        0.94882613,  1.6632575 , -1.5149494 , -0.44087198, -0.04807453,
       -1.6782495 , -2.0553222 ,  1.9231886 ,  1.524027  ,  0.6113978 ,
       -1.7991316 ,  1.6684036 , -1.2988739 , -1.0266774 , -2.285889  ,
        1.7174069 ,  0.9408022 ,  1.2540375 ,  1.5095661 ,  1.418918  ,
        0.6558014 , -1.1237354 ,  0.24906093,  0.8759172 , -1.7649161 ,
       -1.409616  ,  1.2859015 ,  1.9593836 ,  0.6858673 , -2.0065763 ,
        1.6055881 ,  0.10596312, -1.5606853 ,  1.7165731 , -1.7329061 ,
       -1.2587019 ,  1.508271  , -1.5730847 ,  1.4958314 ,  1.3508182 ,
       -0.6786421 ,  1.3270319 , -1.4228916 , -0.9148742 , -1.168945  ,
       -1.0224375 ,  1.5854489 , -2.0035179 ,  0.9392485 ,  0.3260633 ,
       -1.0433654 ,  0.90260386, -0.8775455 ,  1.8294013 ,  0.85295135,
       -1.5016154 ,  2.7030442 ,  1.8643725 ,  1.9444079 ,  1.7257489 ,
       -1.369268  ,  1.2046643 ,  1.8559786 ,  0.9293095 ,  2.0303626 ,
       -1.7557029 , -0.49476138, -1.8584297 , -1.1947466 ,  1.8642701 ,
       -1.4145391 , -1.8291776 , -1.9467016 , -1.1861031 ,  2.0525658 ,
       -0.7303713 ,  1.3271557 ,  1.1930224 ,  2.1674016 ,  2.26686   ,
        1.6920491 , -1.3405378 ,  2.0665727 , -0.5329725 , -1.8322002 ,
       -0.7477894 ,  1.653731  , -1.006564  , -1.8581924 ,  1.4696826 ,
        1.5497904 ,  1.8004804 , -1.2343801 ,  1.2292553 , -1.6317501 ,
       -1.7178333 ,  1.8251089 ,  1.3949803 ], dtype=float32), array([34.990097 , 19.68492  , 39.82107  , 43.668503 , 14.653016 ,
       19.359972 , 37.652267 , 13.855831 , 31.794289 , 14.995984 ,
       74.58488  , 32.194656 , 13.1899   , 10.734181 , 38.19398  ,
        7.1921997, 20.044466 , 11.052127 , 16.924732 , 21.341095 ,
       32.52182  , 12.061641 , 23.814108 , 14.663148 , 24.244041 ,
       26.80744  , 26.468092 , 17.345146 , 17.671814 , 29.228077 ,
       30.756454 , 16.53445  , 22.76658  , 18.889208 , 14.3310795,
       14.887308 , 24.024893 , 32.20959  , 29.630754 , 12.092453 ,
       10.827751 , 31.459911 ,  8.560913 , 11.131446 , 34.379787 ,
        7.6966076, 29.565104 , 22.639444 , 12.755467 , 22.421062 ,
       20.676636 , 27.993547 , 16.720352 , 20.46798  , 21.437532 ,
        8.555474 , 24.765919 , 37.22929  , 16.591618 , 30.834297 ,
       13.901145 , 17.691547 , 12.146523 , 29.390934 , 17.045868 ,
       19.063698 , 15.208789 , 44.020523 , 20.834753 , 29.570486 ,
       16.25864  , 25.95943  , 19.288479 , 38.84115  , 10.902586 ,
       22.39922  , 11.613983 ,  7.8883095, 23.45441  , 21.003021 ,
        9.725851 , 10.039316 , 17.37935  , 23.034954 ,  7.2012863,
       17.380497 , 29.725504 ,  7.0971313, 11.680553 , 12.738955 ,
       32.02245  ,  8.074421 , 28.49036  , 23.720814 , 20.445335 ,
       31.836803 ,  5.944519 , 21.084375 , 18.851976 , 17.162962 ,
       26.238789 , 12.730859 , 24.8713   , 33.17743  , 25.690205 ,
       12.478042 , 31.769476 , 23.43913  ,  3.7592554, 13.347623 ,
       28.971592 , 40.62439  ,  8.881839 , 31.616837 , 34.832516 ,
       17.451862 , 20.468416 , 29.477272 , 21.427809 , 28.566475 ,
       19.819984 , 24.820026 , 17.477852 , 40.377342 , 17.46391  ,
       55.519714 , 13.746012 , 17.39624  , 21.747139 , 13.957982 ,
       23.679447 , 16.880682 , 19.938559 , 24.069166 , 21.649878 ,
       23.198046 , 24.453194 , 10.185266 ,  7.7420497, 24.990793 ,
       23.307909 , 33.71815  , 33.32129  , 26.253468 , 22.38965  ,
       23.497005 , 23.825092 , 17.682846 , 12.83876  , 34.032528 ,
       23.586592 , 21.93888  , 13.625635 ,  9.8868885, 22.685368 ,
        6.498657 , 20.667109 ,  9.680613 , 21.98596  , 14.569482 ,
       12.00302  , 27.743538 , 33.114872 , 11.448964 ,  3.211207 ,
       21.049902 , 24.697027 , 21.063656 , 20.922955 , 22.491013 ,
       18.680784 , 27.055006 , 17.017044 , 24.022818 , 15.70055  ,
       21.801165 , 17.203056 , 16.491009 , 20.54128  , 13.994511 ,
       15.731751 , 18.81648  , 17.352072 , 16.562426 , 16.998621 ,
       39.369656 , 24.77372  ,  8.232364 , 26.925098 , 22.400383 ,
       13.776914 , 12.098104 , 24.88474  , 12.886714 , 11.518597 ,
       34.10055  , 29.717129 , 18.10171  , 16.614738 , 14.44953  ,
       28.205591 , 25.377277 , 12.529263 , 11.645641 , 13.832597 ,
        9.449383 , 35.41273  , 22.254362 , 15.191062 , 52.12471  ,
       12.846203 , 27.316845 ,  8.7956295, 45.00825  , 36.07308  ,
       18.3402   , 14.916395 , 30.162354 , 43.217434 , 10.706028 ,
       12.359459 , 38.022663 , 14.171778 , 19.724142 , 51.94198  ,
        7.8124313, 27.053064 , 24.437426 , 20.767189 , 19.874722 ,
        8.256804 , 19.349613 , 26.175837 , 16.545628 , 28.923735 ,
       14.141994 ,  7.4557667, 10.993108 ,  9.7799835, 11.1397915,
       31.040546 , 29.798187 , 29.817663 , 30.681671 , 14.9938135,
       22.932974 , 16.877195 , 22.781696 , 26.676218 , 17.914776 ,
       29.20082  , 13.639144 , 26.396416 , 17.900799 , 34.936752 ,
       21.831638 , 51.282547 , 21.16646  , 35.952114 , 42.84059  ,
       23.084646 , 12.985213 , 30.118084 , 13.557068 , 39.106655 ,
       29.471127 , 22.19015  , 25.851963 , 34.677055 , 11.748508 ,
       36.88498  , 61.558132 , 21.134016 , 13.118557 , 30.113813 ,
       16.077637 , 36.651    , 19.241682 , 25.14369  , 16.618979 ,
       16.25773  ,  8.9792185, 19.243904 , 33.936646 , 34.42248  ,
       42.480186 , 24.569534 , 21.588915 , 25.398485 , 22.335388 ,
       43.562016 , 33.511375 , 10.12421  ,  6.861956 , 24.473753 ,
       17.291332 , 22.532335 , 17.521221 , 21.233969 , 24.259918 ,
       17.495514 , 30.936304 , 15.733296 , 11.485067 , 12.080663 ,
       30.849537 , 24.294447 , 33.640556 ,  8.720468 , 16.417597 ,
       36.326015 , 42.288982 , 24.783598 , 23.910992 , 16.207075 ,
       30.54552  , 17.174538 , 40.41585  ,  6.5126686, 36.854107 ,
       18.468187 ,  9.748396 , 22.325455 , 33.838108 , 32.045895 ,
       39.978386 , 51.385468 , 18.485786 ,  9.953495 , 25.271103 ,
       35.39809  , 12.2005205, 20.598616 , 19.15372  , 10.346338 ,
       18.720966 , 14.855974 , 21.6212   , 16.805788 , 17.619781 ,
       21.14665  , 35.062527 , 23.251486 , 17.547697 , 18.700283 ,
       13.348049 , 49.112755 , 25.377897 , 12.802777 , 29.0007   ,
        7.489496 , 20.678179 , 25.062994 , 18.650082 , 23.123112 ,
       41.029205 , 33.51641  , 17.184626 , 22.8841   , 10.597356 ,
       51.96804  , 22.861794 , 26.370459 , 14.702381 , 62.85296  ,
       17.945768 ,  8.554367 , 18.222187 , 17.979515 , 13.27265  ,
       18.592096 , 27.08463  ,  8.342993 , 26.372572 , 42.49134  ,
       45.988144 , 12.997105 , 18.324104 ,  4.8542914, 32.416077 ,
       16.744183 , 15.483382 , 38.143093 , 11.984926 , 21.082197 ,
       32.73794  ,  9.836196 , 33.05385  , 15.497178 , 12.082204 ,
        9.7443075, 23.393057 , 11.152986 , 16.006184 , 28.756107 ,
       22.976765 , 24.83889  , 65.28784  ,  8.709635 , 13.258924 ,
       30.632145 , 17.246653 , 20.500345 , 19.931751 ,  8.201139 ,
       35.16941  , 54.600437 , 18.46039  , 20.467411 , 14.520184 ,
       25.37468  ,  9.639987 , 17.418055 , 23.095192 , 19.277807 ,
       65.41865  , 10.959785 , 29.42072  , 20.59856  , 22.638172 ,
       16.568514 , 36.529602 , 49.292435 , 24.20179  , 20.953064 ,
       49.836044 , 30.089973 , 15.111865 , 17.716166 , 22.067295 ,
       19.857847 , 17.367552 , 16.050116 , 25.54378  , 23.99277  ,
       31.940508 , 16.942842 , 20.331001 , 31.418142 , 24.87196  ,
       16.541039 , 14.856987 , 18.58707  , 29.613754 , 25.541384 ,
       33.111378 , 21.162792 , 15.436049 ], dtype=float32), array([[[[-0.05125399, -0.03467436,  0.03828564, ..., -0.04679527,
          -0.0029028 ,  0.03577878],
         [ 0.03235846,  0.04595323, -0.02229211, ..., -0.03350353,
          -0.00705059, -0.03442148],
         [-0.01267493,  0.04091897, -0.05662012, ..., -0.04837273,
           0.00200239,  0.0169547 ],
         ...,
         [ 0.02282842, -0.03452669, -0.00417672, ..., -0.02873399,
          -0.01160671,  0.00201593],
         [ 0.04959936,  0.03304236,  0.0391477 , ...,  0.02809604,
          -0.0216055 ,  0.04093154],
         [ 0.04092402,  0.01917949, -0.02687544, ...,  0.01383535,
          -0.03644315,  0.01629624]]]], dtype=float32), array([[[[-2.92455824e-03,  1.05746584e-02,  6.76845011e-05, ...,
          -5.90130035e-03, -5.70758432e-03, -1.09186582e-02],
         [ 4.50291019e-03,  2.43631937e-02, -2.39869114e-02, ...,
           6.31422037e-03,  3.27114575e-02, -1.52055256e-03],
         [-2.68982016e-02, -3.73336934e-02,  2.04884429e-02, ...,
           1.02181928e-02,  2.05125902e-02,  2.66386885e-02],
         ...,
         [ 2.63232794e-02, -1.26198493e-02,  5.26025484e-04, ...,
          -2.66480148e-02, -8.91851727e-03,  7.22447457e-03],
         [-1.54166861e-04, -2.04511024e-02,  7.58176483e-03, ...,
           1.59452017e-02, -1.53429350e-02,  2.01639999e-02],
         [ 3.81978080e-02,  3.73287387e-02, -9.37049370e-03, ...,
           7.68610928e-03,  2.27144696e-02,  1.68213863e-02]],

        [[ 2.40718778e-02, -7.89604243e-03, -7.18860002e-03, ...,
           8.00782815e-03, -2.18948014e-02, -2.23981384e-02],
         [ 3.77876498e-02,  3.08246575e-02,  2.32857373e-02, ...,
          -9.77021456e-03, -7.39254989e-04,  1.15119200e-02],
         [ 1.72339361e-02,  1.21456804e-02,  1.65499169e-02, ...,
          -3.21500673e-04,  1.70823671e-02,  6.50060177e-03],
         ...,
         [-1.01906736e-03, -1.57378067e-03, -1.05060637e-03, ...,
          -7.97020458e-03, -4.32693679e-03, -1.57390896e-03],
         [-2.16424335e-02,  3.14527452e-02, -3.09037566e-02, ...,
          -2.51980741e-02, -1.74699333e-02,  1.49981829e-03],
         [-1.44442981e-02,  2.83498149e-02, -2.83367895e-02, ...,
           1.64206438e-02,  2.10365672e-02, -1.40370736e-02]],

        [[ 1.72714088e-02, -3.11731528e-02, -2.42677107e-02, ...,
          -2.37313285e-03,  2.01088283e-02,  9.36080329e-03],
         [-2.02885717e-02, -2.41979565e-02,  2.27206387e-02, ...,
          -2.81762164e-02,  3.36202607e-02, -3.16119678e-02],
         [ 1.80872157e-02,  2.59011541e-03, -2.38971598e-02, ...,
           1.15487818e-02,  2.10166723e-02,  2.57314276e-02],
         ...,
         [-8.07701843e-04,  1.81409866e-02,  3.68089112e-03, ...,
          -7.92161375e-03,  2.62729991e-02, -1.71070639e-02],
         [ 1.14454348e-02, -1.28450757e-02,  2.06732210e-02, ...,
          -2.58073164e-03, -1.82905644e-02, -1.67512726e-02],
         [ 3.24760191e-02, -1.91256646e-02,  2.07759161e-03, ...,
           3.97899793e-03,  6.75982563e-03, -3.16520184e-02]]],


       [[[-1.55080678e-02, -1.58588719e-02,  1.06300190e-02, ...,
           1.80862676e-02,  3.97939933e-03,  4.24745400e-03],
         [ 1.30385133e-02,  7.33116036e-03, -3.38704027e-02, ...,
          -4.94731590e-03,  1.81318279e-02, -1.41602950e-02],
         [-8.22110381e-03, -2.78904773e-02,  7.82411546e-03, ...,
           2.83010677e-02, -3.37329879e-02, -6.53611403e-03],
         ...,
         [ 1.04931053e-02,  1.15083093e-02, -1.12166060e-02, ...,
           1.86764225e-02,  2.21281741e-02,  1.91393215e-02],
         [ 1.30585171e-02,  3.14940611e-04,  1.19463112e-02, ...,
           6.16607955e-04,  3.15984525e-02, -1.19160337e-03],
         [-5.00328257e-04, -2.63443962e-03,  2.16170456e-02, ...,
          -3.08626774e-03, -1.33097460e-02, -7.90242665e-03]],

        [[-3.29964049e-03, -1.08890114e-02, -2.05152147e-02, ...,
           8.11933074e-03,  1.14253117e-02,  7.53378868e-03],
         [-8.18990637e-03, -1.73320081e-02, -4.06984473e-03, ...,
          -1.98179875e-02,  4.50922456e-03, -2.53296718e-02],
         [ 2.34535728e-02, -5.51699195e-03,  2.58884113e-02, ...,
           1.99300628e-02, -2.14899424e-02,  4.70008794e-03],
         ...,
         [-1.72778498e-02,  2.66647022e-02, -1.37003111e-02, ...,
          -1.19116744e-02,  3.04683428e-02,  1.32188192e-02],
         [ 1.01441797e-02,  3.07715833e-02, -1.97118204e-02, ...,
          -7.43146846e-03, -8.12072493e-03,  1.68712791e-02],
         [-7.86653534e-03,  2.33562775e-02,  3.21613159e-03, ...,
           1.96132865e-02, -1.39966635e-02,  1.13816187e-02]],

        [[ 2.60775872e-02, -2.42238548e-02, -1.29242251e-02, ...,
           1.76280215e-02,  6.71890040e-04, -3.12038492e-02],
         [ 3.91044095e-03, -9.47008934e-03, -3.06754280e-02, ...,
          -5.65143442e-03,  1.67394150e-02, -7.22777285e-03],
         [ 8.36051442e-03,  1.67113158e-03,  1.99394953e-02, ...,
           9.18143429e-04, -2.42027845e-02,  1.21705970e-02],
         ...,
         [-1.94054060e-02, -1.42871160e-02,  8.14360473e-03, ...,
           1.31886797e-02,  2.91548502e-02,  2.48392299e-02],
         [-8.91415228e-04, -9.33128595e-03, -1.15199694e-02, ...,
           2.09559426e-02, -6.02333574e-03,  1.11045688e-02],
         [-1.29340487e-02,  3.37726763e-03, -5.94685925e-03, ...,
           1.73031189e-03,  4.35109111e-03, -1.14049865e-02]]],


       [[[ 2.66755167e-02,  2.14172434e-02, -9.71069559e-03, ...,
           7.65210669e-03,  1.68186128e-02, -2.30746642e-02],
         [-1.01457182e-02, -9.56640486e-03, -3.16133201e-02, ...,
          -8.60360265e-03, -1.60013624e-02,  1.55444387e-02],
         [-9.63827223e-03, -2.56756623e-03, -1.49234273e-02, ...,
          -3.08414712e-03, -3.10214590e-02,  8.51044897e-03],
         ...,
         [ 2.20692195e-02,  2.21037935e-03,  6.99559739e-03, ...,
          -1.57820154e-02,  9.00602061e-03, -1.69703364e-02],
         [-4.91224742e-03,  2.39941906e-02, -3.15646753e-02, ...,
           1.75345838e-02, -6.65584230e-04,  1.56223085e-02],
         [-1.59595869e-02,  1.26050971e-03, -2.73631029e-02, ...,
           1.69016737e-02, -1.50821544e-02,  2.07293071e-02]],

        [[ 2.57501807e-02,  8.25578440e-03,  1.11994576e-02, ...,
           1.62329189e-02,  1.07731810e-02,  5.49893547e-03],
         [-6.44575711e-03,  3.30447443e-02, -2.26564743e-02, ...,
           1.13695785e-02,  1.68605261e-02, -3.31372884e-03],
         [ 2.25973707e-02, -2.74843536e-02, -1.59582812e-02, ...,
          -6.87372359e-03, -1.18144890e-02, -1.88437756e-03],
         ...,
         [ 1.21597499e-02,  1.81835331e-02,  5.67740900e-03, ...,
          -1.60023328e-02, -1.03705255e-02, -3.38002145e-02],
         [-2.79219486e-02, -1.63451899e-02, -2.88128462e-02, ...,
          -2.70912098e-03,  2.02707872e-02, -7.01531814e-03],
         [-1.40810888e-02,  1.27332192e-03, -9.89663787e-03, ...,
          -1.23498952e-02,  1.02479821e-02, -7.76592409e-03]],

        [[ 2.94237267e-02, -2.69241501e-02,  9.41052288e-03, ...,
          -2.94589642e-02,  1.02565857e-02, -3.34472954e-03],
         [-1.87079534e-02,  1.15024224e-02,  9.89673566e-03, ...,
           5.42209111e-03, -2.48600356e-02, -1.23731676e-03],
         [-2.48184819e-02, -1.22886207e-02, -1.02576322e-03, ...,
           1.90213528e-02,  2.36072019e-02, -2.29983665e-02],
         ...,
         [ 2.75024772e-02,  1.09702367e-02,  1.07233645e-02, ...,
           2.03734040e-02, -2.34389119e-02, -2.12614555e-02],
         [-1.99680049e-02,  9.52328264e-04,  8.55566934e-03, ...,
          -5.93968015e-03,  3.25198006e-03,  2.03643013e-02],
         [-1.41158188e-02,  1.33423107e-02,  8.52766854e-04, ...,
          -1.74055491e-02,  6.32932223e-03,  1.19893467e-02]]]],
      dtype=float32), array([-9.24657192e-03, -8.50949530e-03, -2.25286875e-02, -1.25013674e-02,
       -5.96465589e-03, -4.53527644e-03, -1.48885166e-02, -1.55677572e-02,
       -7.84160290e-03, -5.71088074e-03, -3.18542239e-03, -7.74859451e-04,
       -1.06367059e-02, -6.53828774e-03, -8.56283214e-03, -8.39816686e-03,
       -3.80286045e-04, -1.61458377e-03, -8.05790443e-03, -8.44885129e-03,
       -3.80233419e-03, -6.46873284e-03, -6.69105956e-03, -5.61756222e-03,
       -1.30653717e-02, -9.00248718e-03, -1.02512054e-02, -8.74165166e-03,
       -5.05872676e-03, -3.39858932e-03, -2.47931457e-03, -4.92501538e-03,
       -8.79030675e-03, -4.63897968e-03, -6.61944796e-05, -9.61523689e-03,
       -1.34766996e-02, -5.36679197e-03, -8.18814151e-03, -3.11056385e-03,
       -7.26041244e-03, -1.15386751e-02, -1.23257590e-02, -5.25076175e-03,
       -2.81258067e-03,  5.30417310e-06, -8.27501470e-04, -6.61697378e-03,
       -1.21572092e-02, -9.47402604e-03, -1.45794423e-02, -4.50713979e-03,
       -1.19211636e-02,  2.96039274e-03, -1.35269603e-02, -2.02878807e-02,
       -7.68013473e-04, -7.93817174e-03, -6.37472095e-03, -3.50428256e-03,
       -5.86559996e-03, -6.30526757e-03, -2.33474583e-03, -3.64092714e-03,
       -1.14197591e-02, -9.22133774e-03, -9.84389428e-03, -8.91497638e-03,
        2.78369203e-04, -8.23396724e-03, -8.48290976e-03, -8.03497620e-03,
       -8.53457302e-03, -5.00666676e-03, -4.40357253e-03, -3.91665520e-03,
       -4.89240373e-03, -7.39494432e-03, -2.35411280e-04, -3.31710419e-03,
        1.00301369e-03, -6.40516635e-03, -7.49074668e-03, -8.07068031e-03,
       -1.45191082e-03, -4.98094270e-03, -3.67955351e-03, -1.09163728e-02,
       -9.11079720e-03, -9.82829835e-03,  1.09617854e-03, -1.13495970e-02,
       -2.35383492e-03,  5.87343611e-03, -1.86798989e-03, -2.31493358e-03,
       -2.82583712e-03, -1.17561175e-02, -4.25153691e-03, -3.15789972e-03,
       -1.32956961e-02, -1.59278251e-02, -1.32507440e-02,  2.17761076e-03,
       -1.38121946e-02, -2.52565229e-03, -2.87450757e-03, -7.85168447e-03,
       -8.97605158e-03, -6.53800974e-03, -7.11863441e-03, -5.25788590e-03,
        3.04144551e-03,  3.19546263e-04, -4.70559206e-03, -7.22267758e-03,
       -9.97356791e-03, -9.27554350e-03, -8.61991488e-04, -2.77942605e-03,
        7.80107733e-03, -4.36676247e-03,  1.97442314e-05, -9.43101756e-03,
        7.57609867e-03, -4.61429683e-03, -6.05972949e-03, -6.23546820e-03,
       -6.66403817e-03, -6.08919561e-03, -6.93546515e-03, -3.64544266e-03,
       -1.13769732e-02, -1.31157450e-02,  2.56278226e-03, -1.20437574e-02,
       -6.76287571e-03, -6.82289293e-03, -1.37071451e-02, -4.24225116e-03,
       -1.74281355e-02, -9.09951236e-03, -3.33014969e-03, -1.87431846e-03,
       -4.17093979e-03, -6.71071885e-03, -3.44522018e-03, -5.98774338e-03,
       -6.53069094e-03, -5.39795030e-03, -3.06252716e-03, -7.59132719e-03,
       -9.19319782e-03, -1.29038543e-02, -2.98197963e-03, -2.58371234e-03,
       -6.13297243e-03, -4.17655380e-03, -6.18937239e-03, -7.39390403e-03,
       -7.50495959e-03, -8.13442655e-03, -1.35603771e-02, -1.37511445e-02,
       -1.67455070e-03, -1.47951068e-02, -1.22904936e-02, -2.80173263e-03,
       -2.33881827e-03, -1.78401300e-03,  2.66239885e-03, -9.09415726e-03,
       -7.84183014e-03, -1.05354013e-02, -3.61173949e-03,  6.86378544e-03,
       -2.12555332e-03, -8.82277358e-03, -7.19520869e-03, -3.94455250e-03,
       -1.45467871e-03, -7.95888714e-03,  1.07185147e-03, -6.25708187e-03,
       -2.10546199e-02, -6.38039131e-03, -1.99828367e-03, -8.65133293e-03,
       -1.55215859e-02, -7.88076408e-03, -6.91314181e-03, -9.88143403e-03,
       -7.28764059e-03, -1.17484136e-02, -2.18868651e-03, -1.75020434e-02,
       -6.76091295e-03, -7.68925808e-03, -6.07077871e-03, -4.27996181e-03,
       -6.95729628e-04, -4.59933514e-03, -3.88064957e-03, -1.30215548e-02,
       -5.38502634e-03, -1.12144137e-02, -5.22892224e-03, -4.63811029e-03,
        2.50629359e-03, -9.89590306e-03, -7.51327956e-03,  4.55363261e-05,
       -1.47921694e-02, -1.14357276e-02, -4.11155960e-03, -1.03870351e-02,
       -5.11889020e-03, -1.17290486e-02, -6.01971010e-03, -5.53235644e-03,
       -3.76326195e-03, -8.96363333e-03,  4.15005314e-04, -1.07862579e-04,
        5.59797557e-03, -4.60866932e-03, -9.84616484e-03, -5.75113390e-03,
       -7.28484010e-03,  1.17749383e-03,  1.39963266e-03, -6.22248650e-03,
       -4.17632423e-03, -2.82083778e-03, -1.34662003e-03, -5.56111895e-03,
       -2.58061779e-03, -9.35236551e-03, -4.30869078e-03,  2.65416666e-03,
       -7.52583425e-03, -2.62946123e-03, -9.28783510e-03, -1.61231356e-03,
       -1.88100282e-02, -9.58862621e-03, -1.36364205e-03, -1.33347120e-02,
       -8.83971993e-03, -1.81788281e-02, -9.31887701e-03, -3.54244490e-03,
       -7.65689183e-03, -8.53136927e-03, -1.22336904e-02, -4.31961240e-03,
       -8.48589838e-03, -5.16471406e-03, -3.66257690e-03, -2.12882948e-03,
       -7.60761788e-03, -7.71794887e-03,  4.06801002e-03, -1.10258227e-02,
       -3.16762901e-03,  1.94967072e-03, -7.54436431e-03, -2.38935207e-03,
       -1.20035857e-02,  7.49509363e-03, -1.62569212e-03, -4.29223245e-03,
       -1.40145076e-02, -1.45253139e-02, -1.07322931e-02, -1.29711144e-02,
       -8.32052901e-03, -4.09685820e-03, -9.68423765e-03, -9.35321499e-04,
       -1.10797882e-02, -7.51919392e-03, -6.10972801e-03, -5.05812606e-03,
       -4.91322484e-03, -5.29062422e-03, -1.80096610e-03, -9.72216297e-03,
       -9.98238288e-03, -1.06342519e-02, -7.62796309e-03, -7.54889287e-03,
       -6.69594109e-03, -1.88343320e-02,  2.69614626e-04, -1.46235398e-03,
       -4.83675348e-03, -1.12857623e-02, -5.99953346e-03, -6.86273491e-03,
       -9.37339384e-03, -8.13605636e-03,  3.31708638e-04, -1.02829188e-02,
       -1.76005792e-02, -6.02440024e-03, -6.59747468e-03, -7.13398308e-03,
       -1.46585638e-02, -1.15071032e-02, -1.62243545e-02, -5.33910794e-03,
       -1.07464297e-02, -8.77950166e-04, -2.54238443e-03, -4.96436609e-03,
        1.22941751e-03, -8.70858040e-03, -3.38198128e-03, -1.55893220e-02,
       -9.21854097e-03, -6.90061413e-03, -5.07672830e-03, -1.21908262e-02,
       -2.09996919e-03, -4.35283175e-03,  5.32807969e-03, -5.70154702e-03,
       -1.87633524e-03, -1.21143982e-02, -9.73598752e-03, -5.98996994e-05,
       -1.56775545e-02, -4.87518078e-03, -8.01191106e-03, -5.35914395e-03,
       -6.76698051e-03,  5.48459939e-05, -6.24533650e-03, -4.72328672e-03,
       -1.06862476e-02, -8.20809696e-03, -7.06777256e-03, -6.14283560e-03,
       -8.14771559e-03, -1.06266392e-02, -1.08752949e-02, -1.59092341e-03,
       -5.25445584e-03, -6.41460158e-03, -8.29392765e-03, -7.36953178e-03,
       -1.01842806e-02,  5.11585828e-03, -5.69808017e-03, -2.49333843e-03,
       -9.01203416e-03, -1.77904926e-02, -8.61713290e-03, -3.46096535e-03,
       -6.03396771e-03, -6.89828023e-03, -5.88780269e-03, -2.86695501e-03,
       -7.43898936e-03, -4.46170382e-03,  1.33136334e-03, -4.57557710e-03,
       -6.66758628e-04, -2.64994893e-03, -6.97220210e-03, -1.43467532e-02,
       -9.11139604e-03, -7.43902987e-03, -5.54476585e-03,  4.16775933e-03,
       -2.10652873e-02, -1.36393271e-02, -8.80014244e-03, -3.32391262e-03,
       -5.67208277e-03, -6.20592898e-03, -6.08081650e-03, -1.04089770e-02],
      dtype=float32), array([-1.759053  , -1.5063322 , -1.0984639 , -1.3842953 ,  1.1334414 ,
        1.5015581 , -1.8830912 ,  0.96832013, -1.3696793 , -1.3838955 ,
        1.9828894 , -1.5869882 , -1.1340305 ,  1.053107  , -1.3364466 ,
        1.1230665 , -1.1713156 , -1.184772  ,  1.6803377 , -1.4031749 ,
       -1.6400656 , -1.2061018 ,  0.63136715, -1.1366322 , -1.5178212 ,
        0.6528437 , -1.3015742 ,  1.0856912 ,  0.8629894 , -1.0552236 ,
       -1.1361004 ,  1.45364   ,  1.5334706 , -1.3397462 ,  2.0916448 ,
       -1.4281727 , -1.0818667 , -1.3267926 ,  1.4395273 ,  1.9296361 ,
        1.6017008 ,  0.74145675,  1.6524795 , -1.3134022 , -1.2316506 ,
        1.8130065 ,  2.0276272 ,  1.1387137 , -0.9921163 , -1.1427083 ,
       -1.7619932 ,  1.0508276 ,  1.7747873 , -2.176557  , -1.5577341 ,
       -1.1274155 , -1.732524  ,  0.81679034, -1.2670474 ,  1.7853959 ,
       -1.7892877 , -2.0363693 , -1.9953898 ,  0.9951898 ,  1.3779246 ,
        0.7000362 , -1.2646694 ,  1.0779383 , -1.8774666 ,  1.9950354 ,
       -1.022941  , -1.1789672 ,  0.5839066 , -1.2873908 ,  1.5352286 ,
        1.2951006 , -1.9386264 ,  1.1946307 , -1.622265  ,  1.1594127 ,
       -2.4661398 ,  1.5228648 ,  1.8000323 ,  1.171109  , -2.0387652 ,
       -1.283613  ,  2.0054753 ,  0.8171273 ,  1.6320512 , -1.3754617 ,
        1.9071938 ,  1.9757224 , -1.8083727 ,  0.8947101 , -1.82464   ,
        1.6459295 , -1.4344543 ,  0.2572529 ,  2.0982802 , -1.3005074 ,
        1.7969315 ,  1.7695483 , -1.334072  ,  1.3228997 , -1.2150973 ,
        1.4076271 , -1.9953471 , -1.5490276 ,  1.4059709 , -1.5540061 ,
        1.7341084 ,  1.9804827 ,  1.4847003 ,  0.90555936, -1.4359006 ,
       -1.3974063 ,  1.0811187 ,  1.7786748 ,  1.6172304 ,  1.2974397 ,
       -1.728149  , -0.98343146,  1.4887924 ,  1.0917692 ,  1.935528  ,
       -1.8772247 , -1.4837201 ,  0.9425092 , -1.4415395 ,  1.0937572 ,
        1.5800445 ,  1.6309053 , -1.3376795 ,  1.7668915 ,  1.8884459 ,
       -1.6157547 ,  1.7974557 ,  1.4314075 ,  1.731556  ,  1.8807029 ,
        1.6540974 , -1.7805299 ,  1.3024415 ,  0.76512736, -1.8424044 ,
        1.2123353 ,  1.2729896 ,  1.124477  , -2.0130367 , -1.270795  ,
        1.9391317 ,  0.8360544 ,  1.0141091 ,  1.5517147 ,  0.970964  ,
       -1.6350251 ,  1.498135  , -2.048716  , -1.7976707 , -2.0004041 ,
       -1.486658  , -1.3024416 ,  0.98049617,  1.5623184 ,  1.0597163 ,
        1.1195465 , -1.6765046 ,  1.9765984 , -1.9138156 , -1.6500261 ,
        1.4217378 ,  1.3734558 , -1.4615549 , -1.3763795 , -1.8043989 ,
        2.1467214 ,  1.217919  ,  1.1616275 , -1.9360412 ,  1.6876441 ,
        0.6229884 ,  1.0438884 ,  1.4754062 , -1.5211433 , -1.1447237 ,
        1.393551  ,  1.4029924 , -1.5507417 ,  1.2306372 ,  1.5094979 ,
        1.2280799 ,  1.9989625 ,  2.116117  ,  0.76663595, -1.3590631 ,
       -1.6548195 ,  1.6156124 , -1.5223426 , -1.3250927 , -1.607462  ,
       -1.7338978 , -1.0577956 ,  0.8902968 , -2.2683241 , -2.0703084 ,
        1.2921693 ,  1.127199  , -1.6805418 ,  1.7452142 ,  0.7822518 ,
        0.45540234, -0.89781296, -1.4295777 , -1.6021266 ,  1.8192508 ,
       -1.5053005 , -1.4767299 ,  1.1981831 , -1.9034764 , -1.7988104 ,
        0.9831851 ,  1.3064862 , -2.0224874 , -1.65411   ,  1.9342421 ,
       -1.7055467 ,  1.1621435 , -1.3299257 ,  0.04008209,  1.327519  ,
       -1.7378683 ,  1.564913  ,  2.09426   ,  1.0188309 ,  1.2205595 ,
       -1.8826824 , -1.7685658 ,  1.6391907 , -2.310784  , -1.7414705 ,
        1.1943938 ,  1.9183116 , -1.0179147 , -0.7293723 ,  0.8570537 ,
       -1.0774894 ,  1.4053285 , -1.4809964 ,  1.2760332 ,  1.3324999 ,
       -1.029112  , -1.9193228 , -1.143891  ,  1.3444114 , -1.4056554 ,
       -1.3197516 , -1.2506764 ,  1.5905068 ,  1.8115042 ,  1.0943685 ,
       -1.3556131 ,  1.9770601 ,  2.110346  ,  0.9507993 ,  1.7089821 ,
        1.7978171 ,  1.0495092 ,  1.4465557 , -1.3254529 , -1.2316642 ,
        1.5636903 , -0.8518442 ,  1.5433898 ,  1.0164587 ,  1.0617763 ,
        1.7768581 , -1.5852338 , -1.7539546 ,  0.791578  ,  0.95876426,
       -1.5964639 ,  0.9303417 ,  0.87323326, -1.2488918 , -1.3101631 ,
        0.85350305,  1.92567   , -1.3875716 , -1.0875552 , -1.2116011 ,
        2.0556703 ,  1.5334398 , -1.0955529 ,  0.830341  ,  1.1772829 ,
       -1.6072822 ,  1.606872  , -1.365993  , -1.807512  , -1.1095667 ,
       -0.79356915, -1.349833  , -1.6195484 , -1.1297939 ,  1.6647805 ,
       -1.8952832 ,  0.96197444, -1.787632  ,  2.1308115 , -1.257088  ,
        1.716394  , -1.7818228 ,  1.6281277 ,  1.3253208 , -1.3308908 ,
       -1.2434051 ,  1.6005027 ,  1.2175852 ,  1.9965001 , -1.216019  ,
       -1.4501966 ,  1.375527  , -1.1375351 , -1.2895433 ,  1.3545704 ,
       -1.7079746 ,  1.6288456 ,  0.52104264, -1.7933828 ,  1.8880572 ,
       -1.6118131 , -1.4114403 ,  0.84701866,  1.6861659 , -1.8752427 ,
        1.0751764 , -1.081747  , -2.22379   ,  0.74602646,  1.7999254 ,
       -1.2576609 ,  0.69009453, -1.8014774 ,  1.8076472 ,  1.3709263 ,
        1.2026286 , -1.9964334 , -1.4235344 , -1.0167637 , -0.969492  ,
        1.1944152 ,  2.0191507 ,  1.8040736 , -2.2411811 ,  1.2288085 ,
        1.3819394 , -0.92498463, -1.1677237 , -1.9598348 ,  1.6821499 ,
        0.98146796,  1.2066029 , -1.1869674 ,  1.3051537 , -1.1798128 ,
        1.4433572 ,  1.4486339 ,  1.5903003 ,  1.7827805 , -1.8234216 ,
        1.3268665 ,  0.8889682 , -1.6543331 , -1.0994265 , -1.4225212 ,
       -2.097917  ,  1.1627331 , -2.314553  ,  0.77349794, -1.3875751 ,
        1.1183681 , -1.8159735 , -1.6841747 ,  1.0966955 ], dtype=float32), array([33.845547 , 46.34076  , 20.090094 , 24.190094 , 20.562874 ,
       32.155018 , 43.625954 ,  6.0279574, 37.64309  , 19.85588  ,
       36.81702  , 38.865166 , 30.511795 , 35.691227 , 31.593927 ,
       31.796522 , 35.249424 , 32.036217 , 28.048962 , 43.070705 ,
       50.879402 , 37.356083 , 30.056768 , 26.545723 , 36.689312 ,
       15.099563 , 60.35661  , 21.483923 , 23.180511 , 45.190205 ,
       41.339348 , 29.676386 , 20.85597  , 61.15188  , 29.36895  ,
       39.432762 , 34.97971  , 36.660633 , 17.521374 , 12.899702 ,
       32.23035  , 31.750288 , 30.184092 , 36.32931  , 25.15858  ,
       39.59025  , 23.648125 , 25.626165 , 25.848011 , 36.91746  ,
       36.605507 , 14.828853 , 12.684645 , 74.87172  , 29.04835  ,
       31.012293 , 44.01269  , 15.919914 , 33.110855 , 14.024355 ,
       45.85068  , 63.82031  , 59.879505 , 21.725674 , 35.77862  ,
        6.259414 , 40.808323 ,  8.849942 , 57.1743   , 17.497007 ,
       20.491106 , 24.115643 , 10.319886 , 29.580328 , 31.732222 ,
       15.19499  , 38.623695 , 35.89446  , 39.92544  ,  4.6857233,
       88.71944  , 20.474081 , 38.83581  , 13.241702 , 79.00637  ,
       21.18297  , 26.247633 , 36.638813 , 21.385187 , 50.91258  ,
       20.255228 , 25.85661  , 48.69995  , 20.269974 , 73.91854  ,
       22.998447 , 56.28764  , 20.516296 , 30.480402 , 54.33924  ,
       39.236557 , 31.895803 , 22.630167 , 28.174751 , 26.744287 ,
        9.9646635, 45.152702 , 25.683895 , 10.135325 , 35.523056 ,
       12.08362  , 19.723093 , 13.095946 , 19.16752  , 41.75606  ,
       48.01155  , 19.468342 , 27.112823 , 36.365753 , 14.551524 ,
       52.3721   , 39.333237 , 25.82255  , 26.123337 , 21.716616 ,
       50.55192  , 30.624762 , 32.368973 , 21.114552 , 16.799824 ,
       15.206629 , 20.897482 , 29.28776  , 22.296022 , 44.976486 ,
       39.374916 , 26.531595 , 24.42217  ,  8.764954 , 24.628544 ,
       18.266106 , 30.44015  ,  9.885632 , 15.576914 , 52.099125 ,
       38.659927 , 34.27009  , 23.701208 , 74.28976  , 25.712685 ,
       35.627182 , 18.8317   , 15.420477 , 11.375715 , 27.986525 ,
       70.40797  , 11.40019  , 48.763084 , 58.5645   , 52.798195 ,
       60.955902 , 36.074974 ,  4.718494 ,  9.676996 , 28.031088 ,
       24.019627 , 48.52291  , 43.96057  , 84.93397  , 52.922344 ,
       25.952478 , 12.154297 , 44.797173 , 31.709259 , 56.014397 ,
       26.01215  , 11.074886 , 31.292744 , 50.91706  , 32.64169  ,
       18.322567 , 18.579357 , 39.36435  , 32.608746 , 37.12724  ,
       27.92102  , 30.289513 , 44.505455 , 20.746155 , 42.182545 ,
       12.820197 , 10.600493 , 19.91027  , 17.991096 , 32.34701  ,
       40.48885  , 10.451149 , 65.91677  , 43.8952   , 35.79753  ,
       61.242493 , 44.54278  , 27.800892 , 51.619797 , 63.745358 ,
       17.66609  , 13.13983  , 29.840633 , 41.27865  , 10.265599 ,
       14.381763 , 38.58309  , 45.64256  , 42.7706   , 36.15564  ,
       27.146578 , 38.47052  , 15.353577 , 40.296738 , 43.416718 ,
       14.81933  ,  5.9033556, 68.282326 , 51.24975  , 10.99446  ,
       55.752754 , 13.871759 , 27.118687 , 32.884483 , 40.848133 ,
       55.763397 ,  9.530268 , 21.741781 , 23.362862 , 19.430588 ,
       55.963463 , 64.26213  , 47.733063 , 75.26025  , 46.823143 ,
       37.636833 , 12.949863 , 27.494791 , 39.492027 , 11.003917 ,
       31.258665 , 22.415714 , 49.092575 , 50.677807 , 16.258984 ,
       37.071453 , 68.28252  , 19.630983 , 26.939201 , 31.121326 ,
       31.6027   , 20.90222  , 12.215254 ,  9.630171 ,  7.5156684,
       31.497097 , 15.781202 , 25.994236 , 15.419831 ,  7.4788685,
       21.31021  , 42.155952 , 46.15726  , 44.65751  , 53.61943  ,
       48.117435 , 15.354969 , 12.927607 , 11.372453 , 14.63435  ,
        9.909877 , 65.3444   , 47.4819   ,  8.108892 , 10.511108 ,
       25.065672 ,  9.943793 , 13.471034 , 33.616123 , 33.176598 ,
        9.394085 , 17.540663 , 22.389849 , 29.523605 , 25.11887  ,
       19.398417 , 30.184216 , 22.792862 , 30.039854 , 13.552332 ,
       21.125175 , 22.321589 , 27.792624 , 31.231285 , 24.203197 ,
       12.6046295, 44.298405 , 44.13007  , 38.41654  , 14.360999 ,
       51.64146  , 27.49178  , 66.7318   , 17.845974 , 30.32016  ,
       10.068014 , 55.224083 , 16.511908 , 23.221806 , 24.7588   ,
       45.81726  , 22.538683 , 27.269184 , 38.03336  , 20.96835  ,
       51.024693 , 14.316087 , 38.095276 , 33.757614 , 14.97071  ,
       44.899597 , 24.36683  ,  5.619952 , 36.791798 , 31.070547 ,
       35.55942  , 32.25632  ,  9.692226 , 43.29922  , 42.72215  ,
       36.626617 , 16.611923 , 60.807037 ,  3.4621098, 40.97424  ,
       31.198116 , 25.288183 , 41.39973  , 35.822746 , 10.031762 ,
       35.06993  , 33.325737 , 38.077656 , 17.316511 , 20.519611 ,
       18.465113 , 28.745712 , 33.036774 , 81.09306  , 25.129288 ,
       52.362003 , 16.845201 , 23.780148 , 52.48764  , 14.775444 ,
        6.1062903, 12.813082 , 17.21952  , 26.574028 , 24.55311  ,
       18.573923 , 43.41817  , 34.579067 , 10.87987  , 66.271034 ,
        9.55482  , 21.327274 , 47.139244 , 25.46367  , 48.81147  ,
       54.949425 , 17.076197 , 51.660748 , 12.649515 , 54.44082  ,
       25.622423 , 60.985897 , 49.472977 , 31.060556 ], dtype=float32), array([-5.59741119e-03, -8.23046546e-03, -2.67419755e-03, -9.82988067e-03,
       -1.12691764e-02, -7.44463922e-03, -8.61541275e-03, -1.42876348e-02,
       -8.39445926e-03, -2.22250447e-02, -4.30955272e-03, -1.55645879e-02,
       -6.41516037e-03, -9.84811876e-03, -9.01383720e-03,  2.24535237e-03,
       -1.16764624e-02, -1.49154458e-02, -3.42529383e-04, -8.72370414e-03,
        1.32113905e-03,  3.07940342e-03, -6.91224355e-03, -7.89148454e-03,
       -2.97990721e-03,  3.20520927e-03, -2.03637592e-03, -9.12832748e-03,
       -1.97594403e-03, -7.22343521e-03, -7.43413577e-04, -3.73213808e-03,
       -2.00814800e-03, -1.31487781e-02, -1.34855574e-02, -7.25893350e-03,
       -7.35725602e-03, -5.22769056e-03, -8.85884557e-03, -8.82701110e-03,
       -8.22763704e-03, -1.61007065e-02, -1.65353020e-04, -6.98703714e-03,
       -7.73881935e-03, -2.93102511e-03, -1.13028642e-02, -4.96106921e-03,
       -7.24444166e-03, -3.45682172e-04, -2.35839281e-03, -6.91521121e-03,
       -1.77191140e-03,  2.28460249e-03, -7.99719337e-03, -3.97208100e-03,
        3.48644145e-03,  6.94751367e-03, -1.56903025e-02, -1.93188828e-03,
       -1.45937782e-02, -1.47239333e-02, -1.23798111e-02,  8.15506792e-04,
       -2.76619336e-04, -9.01614223e-03, -9.32879455e-04, -4.82915947e-03,
       -4.71126009e-03, -1.23052550e-02, -1.46694249e-02, -1.99983250e-02,
        4.22234973e-03, -6.99485978e-03, -3.24698724e-03, -2.83027790e-03,
       -9.63240024e-03, -3.18040769e-03, -1.77906523e-03, -4.15793993e-03,
        2.84087006e-03,  2.29391456e-03, -1.31822592e-02, -1.50069036e-03,
       -3.86265176e-03, -1.25661325e-02, -9.29984823e-03, -1.26729924e-02,
        3.37756821e-03, -5.78139396e-03,  1.95220963e-03, -1.87658407e-02,
        3.66110471e-03, -2.50676158e-03, -1.30761294e-02, -1.18747633e-02,
       -5.95837412e-03,  4.60662413e-03, -1.18859811e-02, -1.02352658e-02,
       -1.31900944e-02, -3.04365833e-03, -9.55651142e-03,  8.07135948e-04,
       -9.03177541e-03, -1.04941549e-02, -9.77437571e-03, -1.91457607e-02,
       -5.22477133e-03, -8.15448072e-03, -6.27028663e-03, -3.45037435e-03,
        9.00430430e-04, -8.47564917e-03,  3.93499294e-03,  8.04226438e-04,
       -2.26947028e-04, -2.76045711e-03, -1.09160366e-02, -1.19889239e-02,
       -5.52759925e-03, -6.15747739e-03, -1.74902678e-02, -8.25620629e-03,
        2.16759904e-03,  2.30861199e-03, -1.13090072e-02, -3.28164361e-03,
       -7.11764768e-03, -4.67040902e-03, -7.20972475e-03, -1.45313926e-02,
       -6.25397777e-03, -9.34606325e-03, -1.69687159e-02,  9.74045543e-06,
       -1.54590216e-02, -2.30871923e-02, -8.35729879e-04, -2.38044932e-03,
       -1.20726349e-02, -4.00409847e-03, -1.12277418e-02,  1.14867184e-03,
       -1.70234237e-02, -6.82020979e-03, -2.08206754e-03, -1.35111436e-02,
       -9.62754805e-03, -4.67140647e-03, -5.40538412e-03, -3.35111306e-03,
       -7.72635313e-03, -1.78503012e-03, -4.31710435e-03,  1.22136530e-03,
       -5.52064506e-03, -9.11384821e-03, -8.42797849e-03, -3.51947942e-03,
       -5.03083924e-03, -1.11623965e-02, -6.12286851e-03,  3.34681268e-03,
       -1.37398271e-02, -4.26599430e-03, -1.05434107e-02,  2.95840291e-05,
        8.98993458e-04, -7.45296385e-03, -1.01937409e-02, -1.01434523e-02,
       -6.43295702e-03, -1.55408969e-02,  2.19665142e-03, -4.91726771e-03,
        3.53347510e-04,  2.23940052e-03, -5.92082832e-03, -8.03411938e-03,
        2.04903586e-03, -1.30569050e-02, -7.69750820e-03, -2.61348044e-03,
       -6.68061106e-03, -7.39813084e-03, -8.94088671e-03,  5.10630896e-04,
       -1.03418902e-02, -1.99653814e-03, -4.90093917e-05, -1.24143409e-02,
       -1.71666572e-04, -1.85390320e-02, -2.79048528e-03, -4.22742916e-03,
       -4.37701261e-03,  2.13806424e-03, -5.35897911e-04, -9.80541762e-03,
       -6.08033733e-03, -1.33404564e-02, -1.10511808e-02, -6.86821528e-03,
       -1.89508297e-04, -2.93427403e-03, -4.93819360e-04,  1.07547769e-03,
       -1.30375708e-03, -5.16181439e-03,  2.32845967e-04, -3.48848035e-03,
        3.63536389e-03, -5.27687836e-03,  1.68252701e-03, -1.04529597e-02,
       -4.56929393e-03, -1.42874438e-02, -4.49218135e-03, -4.10689088e-03,
       -4.00790060e-03, -2.59367842e-03, -6.44020271e-03, -7.36245466e-03,
       -7.46627850e-03, -2.56691268e-03, -7.56093254e-03, -1.19781597e-02,
        4.72617103e-04, -1.88019667e-02, -2.09350698e-02, -1.04484539e-02,
       -1.42228846e-02,  3.51764704e-03, -8.47867969e-03, -1.80227729e-03,
        1.52289483e-03, -3.39250691e-05, -3.32235359e-03, -3.00813263e-04,
       -7.57480739e-03, -6.16149418e-03, -4.93625458e-03, -8.65385961e-03,
       -7.99982902e-03, -9.65101272e-03, -1.44923208e-02, -4.71893605e-03,
        2.20861961e-03, -1.87879596e-02, -7.26882881e-03,  1.07284542e-03,
       -3.30869108e-03, -7.33994180e-03, -7.21521955e-03, -7.51953386e-03,
       -8.40089563e-03, -9.30088293e-03,  2.85937870e-03, -7.30908883e-04,
       -1.14138033e-02, -4.45255137e-06, -9.22293309e-03, -2.33777682e-03,
       -8.33184645e-03,  4.36311774e-03, -5.24280593e-03, -5.12697455e-03,
       -4.67669871e-03, -8.11061542e-03, -2.25003925e-03, -8.77897907e-03,
       -2.97951000e-03, -4.87118680e-03,  3.07660364e-03, -7.17842532e-03,
       -3.97624355e-03, -6.43263245e-03, -4.88774013e-03, -4.10716934e-03,
       -5.39360708e-03, -1.08048264e-02, -1.48589639e-02, -5.92194917e-03,
       -6.09044498e-03,  4.92143398e-03, -4.02536429e-03,  1.73796434e-03,
       -1.05594769e-02, -8.68856255e-03, -1.19061489e-02, -4.13342239e-03,
       -2.35480792e-03, -9.71596688e-03, -3.19328695e-03, -9.92019195e-03,
        5.02592360e-04, -9.86068323e-03, -5.72966179e-03,  4.22032783e-03,
       -1.18207047e-02, -1.24700442e-02,  1.62213249e-03, -4.16477351e-03,
       -9.13774408e-03, -3.94790247e-03, -3.23508959e-03, -9.17911157e-03,
        5.32032980e-04, -1.45778982e-02, -7.21065328e-03, -1.65217218e-03,
       -6.45935629e-03, -2.95391143e-03, -6.73510181e-03, -3.70211178e-03,
        6.92944741e-04, -1.18735358e-02, -7.07529392e-03, -2.88329856e-03,
       -1.06703425e-02, -9.73024406e-03, -1.44941695e-02, -8.29355884e-03,
       -4.96961549e-03, -4.23481315e-03,  5.22484258e-03, -3.70033691e-03,
       -1.41259097e-02, -8.68566334e-03, -8.67345952e-04, -5.18686231e-03,
       -7.79234897e-03,  4.99672751e-05, -5.29109826e-03,  2.01399554e-03,
       -5.20256814e-03, -2.60503823e-03, -6.63871085e-03, -1.41747799e-02,
       -7.62811350e-03, -4.36698273e-03,  2.21576239e-03, -1.10785000e-03,
       -7.65759614e-04, -9.78951156e-03, -3.63376201e-03, -2.08187732e-03,
        3.35260108e-03, -4.34865756e-03, -1.29588163e-02, -7.53214210e-03,
       -5.37744351e-03, -5.01266634e-03, -3.91843350e-04, -4.78602387e-03,
       -4.06609336e-03, -1.10986307e-02,  1.60088262e-03, -8.79025646e-03,
       -4.75074071e-03, -7.28861941e-03, -1.48870214e-03, -2.49325973e-03,
       -2.38881260e-03, -2.83751776e-03, -8.80269706e-03, -4.81327157e-03,
       -7.85555132e-03, -3.85490502e-03, -1.86443003e-03, -1.04972962e-02,
       -4.19735303e-03, -1.13027338e-02,  2.77964049e-03, -1.03183684e-03,
       -8.72089062e-03,  1.13002129e-03, -8.53172038e-03, -5.99191990e-03,
        8.63382127e-04, -3.52636538e-03, -2.16924027e-03, -3.12194997e-03],
      dtype=float32), array([ 2.8703387 ,  1.722504  , -2.263707  ,  1.5994649 , -2.3267105 ,
       -3.0314565 ,  1.61727   ,  1.5166901 , -2.2957873 , -3.2519317 ,
       -2.6408808 , -1.8490705 , -3.0490625 , -2.4743116 ,  2.782666  ,
        2.3433821 , -2.2936428 ,  1.724761  , -2.5109084 ,  2.4468267 ,
       -2.3504026 , -3.289879  , -2.2087257 , -1.610162  ,  2.05658   ,
       -3.0357206 ,  1.7098451 ,  1.4896593 ,  2.234742  , -2.7036257 ,
       -1.5106804 , -2.2618718 ,  1.3143169 , -1.2950915 ,  2.0154598 ,
        2.7014399 ,  2.1815014 , -2.6119783 , -2.3594413 ,  2.2085698 ,
       -1.881061  ,  1.700924  , -1.9452646 , -2.0857732 ,  2.19679   ,
       -2.027431  , -0.2348441 ,  1.9526143 , -1.7139882 ,  2.876198  ,
       -2.1770115 ,  1.4304497 ,  2.3020012 ,  1.9170736 ,  0.9284166 ,
        2.182176  , -2.201326  ,  2.391921  ,  1.1888739 ,  1.4858767 ,
       -1.6947544 , -2.1346064 , -2.7007856 , -2.7353132 ,  2.215343  ,
        2.0951192 , -1.8230159 , -1.48372   , -1.3233762 ,  2.1794033 ,
       -1.9139161 ,  1.9367311 ,  1.6437922 ,  1.3747685 , -2.941479  ,
        2.541497  ,  1.5264331 ,  2.2860124 , -2.6918309 , -2.644259  ,
       -2.7646222 , -2.8298354 ,  1.2914605 ,  2.544934  ,  2.8357382 ,
       -2.262641  , -0.9060582 , -2.6312532 , -2.6775198 , -3.2612045 ,
       -2.0152664 ,  1.598332  , -2.3316536 ,  2.4862463 ,  2.208142  ,
        2.8144639 ,  1.7265608 , -3.119397  ,  1.4301699 , -2.6518533 ,
        0.909555  ,  2.9330804 , -1.2607772 ,  2.060514  , -1.9303733 ,
        1.6655089 ,  2.0340228 ,  1.6927102 ,  2.010968  ,  2.6734393 ,
        2.2607532 , -2.0287087 , -2.8365643 , -2.3110127 ,  3.0885882 ,
       -2.5548387 , -2.9006426 ,  1.8128892 , -1.192998  ,  1.4665545 ,
        2.0071895 , -3.0829904 , -2.4736507 ,  3.14489   , -2.5129154 ,
       -2.4535654 , -1.0230074 , -2.246904  , -2.9282866 , -2.0189195 ,
        2.9719393 ,  1.5138004 , -2.0731375 , -0.94278276,  1.7375603 ,
       -1.4797249 ,  1.9551055 ,  0.82756835, -2.4919307 ,  2.776849  ,
        1.9392827 , -2.2248595 ,  1.335653  ,  3.1091275 ,  1.2813605 ,
        2.110331  , -2.5194266 ,  1.7400211 ,  1.9790195 , -2.3431182 ,
        2.3898606 ,  2.4526927 ,  1.9773778 , -2.3972945 ,  2.0048437 ,
        2.261478  ,  1.7855843 , -2.4085536 ,  1.2944458 , -2.675224  ,
       -2.2034059 , -2.2462616 ,  2.4407701 , -2.6453948 ,  1.4910796 ,
        1.6847776 , -3.106891  ,  1.3480595 ,  2.0838995 , -2.4054327 ,
       -1.1242579 , -1.8997535 ,  1.8057568 ,  2.0399005 ,  2.1626148 ,
       -2.0622365 ,  2.7490811 ,  2.1818733 ,  1.5831437 , -2.2836335 ,
        2.345873  ,  1.133564  ,  1.8513641 ,  2.2313774 , -2.3917294 ,
       -3.0546677 ,  2.019312  ,  1.9300288 ,  1.7151055 ,  1.4964166 ,
       -2.42997   ,  1.4788392 , -1.8350683 ,  1.7260672 , -2.26004   ,
       -2.424634  ,  2.3627698 , -3.4001522 ,  1.7587991 ,  1.6237236 ,
        1.9258208 , -2.298381  ,  1.4852717 , -2.0332541 ,  2.3888776 ,
        2.6156273 , -1.9048502 , -1.2723188 ,  2.8643386 ,  2.8626382 ,
       -3.1111624 ,  1.6325431 ,  2.8370707 ,  1.911918  , -3.105358  ,
        2.0219839 , -2.4402575 ,  1.3475173 , -1.9669946 ,  1.8024709 ,
        1.7840393 ,  1.2803673 , -3.0396314 , -2.3843927 ,  2.280935  ,
        2.4136882 , -2.3869789 ,  1.0674678 ,  2.3702564 , -2.0638301 ,
        1.930385  , -1.9028207 ,  1.7425534 , -2.8438869 ,  2.440682  ,
        1.6377063 ,  1.755993  , -2.6342585 ,  2.2024775 ,  1.7123845 ,
        1.4000082 , -2.123437  , -1.1740566 ,  2.092856  , -1.9304857 ,
       -2.652264  ,  1.1217535 ,  1.8235819 , -2.0856369 ,  1.6143365 ,
       -1.9069918 ,  1.5866886 , -2.4758744 ,  2.4134405 , -2.0176318 ,
        1.7643453 , -3.1041749 ,  1.1007631 ,  1.667157  ,  2.1803153 ,
       -1.8864412 , -2.4370728 ,  1.7079738 ,  2.332975  ,  1.9295063 ,
        1.9478838 , -2.4645927 , -2.8569438 ,  2.2461386 ,  2.030146  ,
        0.65894175,  1.3560082 , -2.30602   , -2.3646674 ,  2.4713092 ,
        2.6206052 ,  1.7958535 , -0.06948549, -2.369795  , -1.2847034 ,
        2.5251398 , -1.6657562 , -1.4366739 , -1.7877617 ,  2.097244  ,
        1.4308863 ,  2.5284212 ,  2.262375  , -2.6535747 ,  2.723639  ,
       -2.3352273 ,  2.3621109 ,  2.2882767 ,  1.6988237 ,  2.7767215 ,
       -1.7766547 ,  1.7782791 , -2.9128728 ,  2.1014626 , -2.0558257 ,
       -1.622364  ,  1.6055216 , -2.591154  ,  2.6202972 , -0.5171448 ,
       -2.987718  ,  1.3410817 , -1.6392907 , -2.4129174 ,  1.6176062 ,
       -0.1654937 , -2.9991157 ,  2.4238591 , -2.8607047 ,  1.3612312 ,
       -1.7540574 , -2.7113044 ,  1.8181589 ,  1.7388777 , -2.2871835 ,
        2.4452724 , -1.9389284 ,  1.883276  ,  1.5041153 ,  2.3973007 ,
        2.224721  ,  2.4587073 ,  1.5875098 , -2.6730936 ,  2.1478992 ,
        1.8634733 ,  2.1117692 ,  1.6132799 , -2.6382523 ,  2.0519733 ,
        2.3903944 ,  1.9730392 ,  2.1028843 , -2.0499034 , -1.6819987 ,
        1.9439889 , -2.1658826 , -2.14999   , -2.6932206 ,  2.6014917 ,
       -2.6583345 , -2.2192056 , -2.4042602 ,  1.8466842 ,  1.2087595 ,
        1.247206  , -2.1818616 ,  2.1391962 , -1.8422105 ,  2.1443076 ,
        1.926372  , -2.0670955 , -2.045039  , -2.018608  , -2.4457455 ,
        2.8803258 , -2.6204526 ,  2.446101  ,  2.159817  , -2.3332887 ,
        2.249829  ,  1.5478393 ,  2.022767  , -2.8910694 ,  1.2357236 ,
        1.900715  , -3.135542  , -2.7473223 , -2.760418  ,  2.651152  ,
        1.7512561 ,  2.052591  ,  2.3130255 , -0.09859336,  2.6848273 ,
       -2.610877  , -1.9138165 ,  1.9484725 , -2.9993432 ], dtype=float32), array([ 60.312958,  42.80536 ,  72.03099 ,  51.07889 ,  56.79501 ,
        79.22551 ,  55.72396 ,  38.79593 ,  68.829384, 128.05594 ,
        91.19627 ,  56.620804,  85.9304  ,  79.09566 ,  81.92186 ,
        51.576862,  48.69142 ,  36.226524, 114.30793 ,  44.156876,
        69.15287 , 124.0007  ,  59.95579 ,  57.680428,  51.70159 ,
       108.53726 ,  53.540585,  35.525547,  64.76907 ,  69.31354 ,
        56.8032  ,  64.85525 ,  48.863026,  36.794567,  50.459423,
        49.24656 ,  30.300829,  81.27476 ,  56.872112,  31.390205,
        68.21508 ,  32.85888 ,  77.38596 ,  61.41174 ,  43.19326 ,
        76.48574 ,  44.90402 ,  56.718895,  35.869892,  68.81994 ,
        51.63852 ,  41.918247,  34.98046 ,  58.533752,  67.983   ,
        25.050917,  66.281525,  53.130554,  55.48825 ,  30.685534,
        69.465744,  68.59567 ,  74.18036 , 103.36775 ,  62.75093 ,
        57.539867,  82.150986,  33.783234,  48.999184,  57.50874 ,
        42.382957,  49.65999 ,  58.840126,  79.29929 , 109.27878 ,
        44.902885,  64.98294 ,  25.946283, 112.62328 , 101.54412 ,
       112.43885 , 100.96537 ,  28.33698 ,  36.236908,  54.667934,
        66.614944,  58.80575 ,  67.82725 , 102.6774  , 116.24818 ,
        55.34536 ,  31.316496,  83.47215 ,  63.227   , 102.627174,
        47.951817,  78.6667  , 131.45618 ,  69.52745 , 107.40172 ,
        25.864794,  69.01085 ,  42.317734,  49.463795,  46.081455,
        35.55933 ,  43.582718,  43.953644,  68.33243 ,  53.570084,
        32.916355,  76.32476 , 155.70345 ,  58.48589 ,  52.19132 ,
        86.22998 ,  94.07355 ,  34.31261 ,  51.80994 ,  16.758333,
        14.74453 , 114.370255,  63.4443  ,  39.671856,  66.78302 ,
        98.24673 ,  38.16338 ,  82.36638 ,  84.04672 ,  89.64125 ,
        47.325294,  61.01424 ,  95.694275,  55.514256,  70.58987 ,
        54.20507 ,  34.017464,  36.82385 , 113.78174 ,  35.579563,
       108.55054 ,  45.94125 ,  36.3913  ,  77.07001 , 119.59361 ,
        59.685463,  72.62857 , 102.3768  ,  29.498787,  72.92713 ,
        31.528109,  57.55916 ,  20.287642,  94.87918 ,  39.865955,
        60.99265 ,  25.360966,  62.073544,  35.65454 , 102.325325,
        74.04871 ,  67.77381 ,  63.790634, 106.754425,  39.574497,
        38.23168 , 108.55767 ,  41.67422 ,  53.437508,  64.94546 ,
        55.137463,  92.75136 ,  30.84409 , 105.03907 ,  50.479767,
        67.851715,  36.24881 ,  58.251274,  64.49789 ,  74.304794,
        66.56689 ,  87.549065,  61.76058 ,  27.469868, 100.704384,
        74.12939 ,  61.667004,  61.054928,  41.372772,  31.942606,
        80.34241 ,  31.074526,  54.629715,  45.811512,  72.25932 ,
        70.86874 ,  32.563843, 151.98122 ,  48.544064,  32.247105,
        47.659874,  78.39241 ,  56.902523,  81.878075,  58.385113,
        57.262703,  48.99606 ,  47.231686,  62.960567,  57.06042 ,
        88.16814 ,  45.404247,  68.54113 ,  92.82788 , 104.201225,
        76.002144,  84.113464,  29.959608,  68.03906 ,  48.255337,
        37.946983,  36.18054 ,  90.06786 ,  46.681484,  36.644558,
        51.16904 ,  59.304485,  81.61843 ,  58.353226,  87.32527 ,
        38.985416,  56.326267,  95.35878 , 119.181175,  71.52071 ,
        31.425634,  40.85953 ,  86.332695,  23.999336,  39.749306,
        35.69841 ,  75.2069  ,  44.124302,  77.7944  ,  58.28409 ,
        84.94624 ,  65.27063 ,  54.06261 ,  64.72087 , 114.30689 ,
        50.981068,  43.932766,  67.9857  ,  58.222973,  49.20118 ,
        60.427315,  96.663895,  63.22107 ,  46.521618,  51.922546,
        71.54218 , 119.678825,  65.49588 ,  73.9398  ,  44.991226,
        63.972416,  79.68196 ,  90.471825,  20.394518,  33.734337,
        29.942772,  44.274044, 122.35897 ,  64.25445 ,  66.206   ,
        34.396095,  50.705704,  41.41092 ,  91.255745,  34.48771 ,
        49.207584,  67.65149 ,  64.33747 ,  65.51039 ,  41.82954 ,
        46.703445,  47.150818,  32.03504 ,  81.62259 ,  55.082176,
        58.54142 ,  44.143307,  24.928823,  44.33027 ,  41.440323,
        61.750942,  49.55039 ,  90.87481 ,  44.48739 ,  56.053955,
        67.38722 ,  74.85511 ,  99.07851 ,  37.015602,  32.734856,
       101.778534,  21.768766,  56.526237,  88.539635,  28.539715,
        46.000935,  90.210785,  36.477535, 110.61728 ,  72.08019 ,
        74.79329 ,  96.88818 ,  38.29977 ,  33.500057,  80.172104,
        27.579891,  57.4752  ,  27.674036,  37.84222 ,  63.925358,
        63.356262,  59.468094,  34.67211 ,  90.12682 ,  42.71473 ,
        48.028896,  26.821314,  68.06883 ,  75.00744 ,  49.054684,
        49.031662,  58.172356,  24.959051,  87.40954 ,  54.880558,
        29.773026,  80.972305,  70.62953 , 108.20953 ,  67.05317 ,
        75.93053 ,  64.30742 ,  86.98098 ,  49.69716 ,  91.02731 ,
        68.02869 ,  94.32399 ,  65.87158 ,  64.10592 ,  59.7173  ,
        41.43182 ,  89.147385,  64.924805,  72.03723 , 100.00673 ,
        45.69973 ,  84.62999 ,  52.47029 ,  43.427986,  93.13755 ,
        48.813927,  35.731907,  28.357267,  93.44556 ,  58.12653 ,
        50.696323,  94.48214 ,  94.22891 ,  91.60883 ,  48.253407,
        32.888332,  40.07673 ,  63.917557,  34.760742,  33.57478 ,
       154.13197 ,  58.028187,  54.793274, 109.6349  ], dtype=float32), array([[[[-0.03897645, -0.02231768, -0.02695194, ...,  0.04299952,
          -0.00393037,  0.02281723],
         [ 0.03157222, -0.0133183 , -0.01646147, ..., -0.00098372,
           0.03424387,  0.0288277 ],
         [ 0.04048816, -0.00668267, -0.02697616, ...,  0.03916841,
          -0.03311545, -0.00173258],
         ...,
         [-0.03552635,  0.01501651, -0.00081414, ...,  0.02102403,
           0.01914348,  0.03429329],
         [ 0.02801408,  0.03444119,  0.02279696, ...,  0.0104487 ,
           0.01183149, -0.01200006],
         [-0.05167096, -0.00668751,  0.03563121, ...,  0.04212338,
           0.00107116,  0.01354427]],

        [[-0.05428067, -0.005639  , -0.01262222, ...,  0.01099756,
           0.04875153,  0.0050298 ],
         [ 0.04806502, -0.03237404, -0.0261944 , ..., -0.02642758,
          -0.02836367,  0.03064927],
         [ 0.0180924 , -0.01348377, -0.04532587, ..., -0.02270733,
          -0.03366432,  0.05090689],
         ...,
         [ 0.00894122, -0.01819575, -0.01487992, ...,  0.00017955,
           0.04811282, -0.00109295],
         [ 0.02675533, -0.02622541, -0.01013462, ..., -0.04766005,
           0.03387731, -0.03194722],
         [ 0.02548955,  0.02317393,  0.03623461, ...,  0.01188816,
          -0.02287742,  0.01353929]],

        [[ 0.03457501, -0.01034566,  0.00914903, ...,  0.02419034,
           0.01168284,  0.00543803],
         [ 0.03110635, -0.02353304,  0.0367275 , ..., -0.01613709,
          -0.02779353,  0.01251717],
         [ 0.01187676, -0.00245542,  0.04165356, ..., -0.04861609,
           0.03157727,  0.0116567 ],
         ...,
         [ 0.00229453,  0.02616594,  0.03516779, ..., -0.05435447,
          -0.05081569,  0.02471286],
         [-0.00912553,  0.0130838 , -0.0203263 , ...,  0.02153   ,
          -0.0431917 , -0.03483747],
         [ 0.01564069, -0.01653809, -0.04889231, ..., -0.03576542,
          -0.04079715, -0.02372624]]]], dtype=float32), array([[[[ 0.03916048,  0.0168418 ,  0.03296315, ...,  0.0302785 ,
           0.01597225,  0.0460899 ],
         [ 0.04924092, -0.03468488, -0.02341856, ...,  0.05159743,
          -0.02580943, -0.02881814],
         [-0.02292151,  0.0030381 ,  0.00010144, ...,  0.04444372,
           0.03559884,  0.03092859],
         ...,
         [ 0.03946035,  0.02148925,  0.02127172, ..., -0.04388268,
          -0.04769154,  0.01637744],
         [ 0.03623247, -0.00138321,  0.01306103, ..., -0.04214659,
          -0.00097955,  0.03890439],
         [-0.03128807,  0.05646484,  0.00748322, ...,  0.01107906,
          -0.04200334,  0.03306385]]],


       [[[ 0.04683545, -0.01457342, -0.03907061, ..., -0.0461498 ,
          -0.05187163, -0.04134503],
         [ 0.0214129 ,  0.0261586 , -0.01258133, ...,  0.05199177,
           0.01921509, -0.05354451],
         [ 0.05293426, -0.02459467, -0.00669425, ...,  0.02325012,
          -0.02563876,  0.0211107 ],
         ...,
         [-0.05063485, -0.01376062,  0.01676938, ...,  0.0318287 ,
          -0.01802315,  0.03889167],
         [-0.03209545,  0.02603018,  0.05008926, ...,  0.02532771,
          -0.02106217,  0.04712844],
         [-0.0340003 ,  0.05467047,  0.02260074, ..., -0.05152223,
          -0.02537706,  0.02694175]]],


       [[[-0.02855579,  0.0129893 , -0.01108578, ..., -0.01528474,
          -0.03875504, -0.04466684],
         [ 0.04739366, -0.01451514, -0.0295121 , ...,  0.04421552,
          -0.03772475,  0.0341329 ],
         [ 0.04803155,  0.04578867,  0.05003266, ..., -0.01083344,
           0.01981686,  0.02010995],
         ...,
         [-0.02926684, -0.02226751,  0.03833086, ..., -0.02961694,
          -0.01962938,  0.00368611],
         [-0.03886713, -0.04882919, -0.02911916, ...,  0.05100343,
           0.05097369,  0.04269668],
         [-0.03634662, -0.0415338 ,  0.04802689, ...,  0.01901574,
           0.01920346, -0.0179758 ]]]], dtype=float32), array([[[[ 3.28534506e-02, -1.54668335e-02,  4.68237251e-02, ...,
           3.94355506e-02,  4.04240973e-02, -4.83186282e-02],
         [ 2.48079421e-03,  2.55283061e-02, -2.48618219e-02, ...,
           1.79246943e-02,  4.84356470e-03,  3.79841961e-03],
         [ 5.32267019e-02, -1.37847513e-02, -2.58352458e-02, ...,
          -2.64129514e-04, -2.26670410e-02,  1.04927318e-02],
         ...,
         [ 3.15906927e-02, -2.91567203e-02,  4.34446847e-03, ...,
           4.34829779e-02, -4.13384996e-02,  3.59809957e-02],
         [-2.19720639e-02, -3.92429270e-02,  9.20012826e-06, ...,
          -4.37180512e-02,  2.50531286e-02,  7.54435174e-03],
         [-1.10608526e-02, -1.05444121e-03,  1.14407996e-02, ...,
          -4.27878760e-02, -6.71783881e-03,  1.27270566e-02]],

        [[-1.27106570e-02,  4.58485633e-02, -1.92918014e-02, ...,
          -3.43026109e-02,  1.15664024e-03,  4.76162881e-02],
         [-3.20154242e-02, -1.35245882e-02, -9.80053376e-03, ...,
           2.36875862e-02,  5.02112284e-02, -2.85354480e-02],
         [-1.88274067e-02, -8.54592118e-03, -4.26608510e-02, ...,
          -3.43297645e-02, -4.10373509e-03,  9.90539975e-03],
         ...,
         [-2.58119795e-02,  3.64287496e-02,  3.96070480e-02, ...,
           2.66144164e-02, -7.67628476e-03,  3.54687311e-02],
         [-1.49077363e-02,  1.49978204e-02, -9.98215191e-03, ...,
           6.94564916e-03, -1.56043675e-02, -1.20146954e-02],
         [ 4.22675572e-02, -1.25546986e-02,  1.48549359e-02, ...,
          -4.07537855e-02, -3.38496789e-02, -1.00663025e-02]],

        [[-3.45410481e-02, -1.27209555e-02,  3.67119722e-02, ...,
           2.00311709e-02,  3.18559520e-02,  9.47207958e-03],
         [ 5.07169068e-02,  3.22166756e-02,  8.24317150e-03, ...,
          -4.17870916e-02, -3.75459008e-02, -8.33577570e-03],
         [ 5.72274812e-02, -1.40745156e-02,  1.43872770e-02, ...,
          -1.63489170e-02,  2.61630192e-02,  3.68653908e-02],
         ...,
         [ 3.19842063e-02, -1.70690697e-02,  2.73975674e-02, ...,
          -4.25895937e-02,  1.78523008e-02, -1.83963235e-02],
         [-2.40705665e-02,  3.87897864e-02, -5.06964736e-02, ...,
           4.76115085e-02,  5.53053841e-02, -2.16152379e-03],
         [-5.30629158e-02,  4.50697429e-02, -1.24962749e-02, ...,
           3.99766788e-02, -1.70358773e-02, -1.45589514e-02]]]],
      dtype=float32), array([[[[-0.03849855,  0.00752949, -0.00619091, ...,  0.03808971,
          -0.01830601, -0.03306573],
         [ 0.03629701, -0.02272169,  0.03764306, ...,  0.00333999,
           0.0348743 ,  0.03090584],
         [ 0.01501365, -0.04809401,  0.03645379, ..., -0.00130534,
           0.04757961, -0.04622891],
         ...,
         [ 0.01770117,  0.00153311,  0.05519985, ..., -0.0289374 ,
           0.00470759,  0.05294674],
         [ 0.00181037,  0.04067799, -0.0384353 , ...,  0.01502636,
           0.04128685, -0.01039132],
         [ 0.04584964, -0.03982772,  0.02403573, ...,  0.02775275,
          -0.01343147, -0.03173939]]],


       [[[-0.00197241,  0.04443651,  0.03695391, ...,  0.03265424,
          -0.04327224,  0.03078249],
         [-0.00798609,  0.05522624,  0.02502184, ...,  0.04162463,
           0.04286822,  0.00060734],
         [ 0.01038061, -0.04328358, -0.02176818, ..., -0.01534185,
          -0.02662749,  0.00323011],
         ...,
         [-0.03020301,  0.03293817, -0.03716851, ..., -0.04543469,
           0.02754591, -0.01142952],
         [ 0.03702005,  0.04445308,  0.00712333, ...,  0.0294297 ,
          -0.02595791,  0.02342044],
         [ 0.03482435,  0.01528215, -0.00348027, ..., -0.01748958,
          -0.00754879, -0.03091754]]],


       [[[ 0.00832038,  0.03985178,  0.01931044, ...,  0.00158254,
          -0.01648294,  0.04965823],
         [ 0.01729937,  0.04948964,  0.02594577, ...,  0.03723378,
          -0.03982568,  0.0098904 ],
         [ 0.03749245,  0.01818176, -0.00500607, ...,  0.0203301 ,
           0.03214616,  0.01785581],
         ...,
         [-0.04168836,  0.03413543,  0.02488582, ..., -0.00324994,
           0.02230728, -0.02442346],
         [ 0.04408707,  0.01560616,  0.01698323, ...,  0.00181098,
           0.03004367,  0.01888999],
         [-0.03096843, -0.03111693,  0.00161404, ...,  0.01744211,
          -0.04426417,  0.01480144]]]], dtype=float32), array([[[[ 0.04676325, -0.0485062 , -0.00801378, ..., -0.02420733,
          -0.01008571, -0.01406579],
         [-0.04489361, -0.03216608,  0.02427018, ...,  0.02424162,
           0.04808204,  0.02469729],
         [ 0.0282949 ,  0.02998634, -0.00454088, ...,  0.04031778,
           0.03562331,  0.03030902],
         ...,
         [-0.01320572,  0.02442379, -0.04853677, ...,  0.05380606,
           0.0404169 , -0.01295482],
         [ 0.03602022, -0.03326286,  0.02157928, ..., -0.04058376,
          -0.049282  , -0.03870591],
         [ 0.02750126,  0.03838563,  0.00415858, ...,  0.0351617 ,
          -0.05164016, -0.03667459]]]], dtype=float32), array([-3.00820805e-02, -4.60859248e-03, -9.38450266e-03, -3.13654105e-04,
       -1.34978956e-02, -4.62726224e-03, -1.14545431e-02, -1.06645469e-02,
       -7.68418377e-03, -3.03690825e-02, -5.09825395e-03, -1.63958743e-02,
       -1.41131058e-02, -9.08524822e-03, -3.65075059e-02, -1.03506213e-02,
       -8.30998924e-03, -1.49683263e-02, -1.61406206e-05, -1.55444425e-02,
       -1.01155750e-02, -6.52822480e-03, -3.33581399e-03, -4.99647576e-03,
       -3.56110861e-04, -1.09036500e-03, -1.15805566e-02, -5.08714505e-02,
       -9.89780203e-03, -1.46086013e-03, -3.16189118e-02, -3.70991370e-03,
       -2.05319133e-02, -1.64832955e-03, -9.70026292e-03, -7.24952947e-03,
        5.17365523e-04, -7.10928859e-03,  2.05691031e-04, -1.35393091e-03,
       -3.95668857e-03, -2.55234167e-02, -1.76586937e-02, -7.22956471e-03,
       -9.32718534e-03, -4.06660233e-03, -1.80797663e-03, -8.28455016e-03,
       -8.29365849e-03, -3.35159432e-03, -2.12154933e-03, -8.11729021e-03,
       -2.43601445e-02, -6.04453795e-02,  1.43622397e-03, -1.32701481e-02,
        2.00975477e-03, -5.57726808e-03, -4.76472341e-02, -1.56005146e-02,
       -2.35654018e-03, -3.09690047e-04, -2.92588375e-03, -5.36354026e-03,
       -8.44973885e-03, -1.79343075e-02, -8.77566077e-03, -2.44848104e-03,
       -6.20887522e-03, -1.28347464e-02, -4.99962643e-03, -4.00136597e-03,
       -2.77295010e-03, -5.57917543e-02, -7.65729044e-03, -2.30370555e-03,
       -2.27732416e-02, -1.94675494e-02, -2.87254131e-03, -6.76584663e-03,
       -3.73055256e-04, -8.16082675e-03, -1.34967151e-03, -9.51941777e-03,
       -4.24452610e-02, -1.51334060e-02, -1.26201389e-02, -4.40697744e-02,
       -1.39248250e-02, -9.77075286e-03, -6.07042108e-03, -3.08067701e-03,
       -1.25410846e-02, -1.02187302e-02, -4.56871605e-03, -3.31045724e-02,
       -7.94678833e-03, -1.28113925e-02, -2.72317119e-02, -6.15487481e-03,
       -7.01404596e-03, -5.88303339e-03, -4.57769167e-03, -3.28285899e-03,
       -7.97937810e-03, -3.34116518e-02, -8.63770954e-03, -5.78395277e-03,
       -7.22364150e-03, -1.24023966e-02, -3.68040651e-02, -6.75520627e-03,
       -1.00931618e-02, -6.49988977e-03, -2.08377047e-03, -1.22742439e-02,
       -4.43803370e-02, -9.21926927e-03, -5.36580849e-03, -1.25931501e-02,
       -8.72680172e-03, -4.33348864e-02, -1.03041893e-02, -2.33892002e-03,
       -1.03425272e-02, -2.22179061e-03,  2.04335502e-03, -1.16762007e-03,
       -4.66650166e-03, -2.92604063e-02, -1.23787615e-02, -1.02363322e-02,
       -5.13619045e-03, -9.26529523e-03, -8.23014230e-03, -7.35190813e-04,
       -6.87452173e-03, -6.94329571e-03, -2.73564225e-03, -9.40865837e-03,
       -5.60217202e-02, -8.12967680e-03, -5.36079006e-03, -8.81142542e-03,
       -3.19386981e-02, -1.05256652e-02, -8.62420816e-03, -1.19285993e-02,
       -1.61352977e-02, -8.94536637e-03, -2.71624234e-02, -2.49648094e-03,
       -5.09860134e-03, -1.31698875e-02, -1.39266672e-03, -6.55475818e-03,
       -1.68702379e-02, -3.28338356e-03, -3.17665655e-03, -8.56704731e-03,
       -2.65047457e-02, -5.57432091e-03, -4.31344006e-03, -8.30306578e-03,
       -1.45421410e-02, -1.52113265e-04, -2.69452035e-02, -4.31748759e-03,
       -4.02426720e-03, -3.53887603e-02, -9.63498838e-03,  1.45922229e-03,
       -8.49332102e-03, -9.69190523e-03, -4.61881561e-03, -5.60485991e-04,
       -1.30818430e-02, -2.35592555e-02, -1.37981884e-02, -5.15351305e-03,
       -1.36231096e-03, -4.55430709e-03, -2.33948245e-04,  2.44436273e-03,
       -3.81396785e-02, -1.44262258e-02, -5.00189466e-03,  8.70365038e-05,
       -9.24576167e-03, -4.80877422e-02, -4.44088243e-02, -2.78167278e-02,
       -4.64071296e-02, -2.55443598e-03, -6.16945210e-04, -2.35430058e-03,
       -6.31216448e-03, -6.64040446e-03, -1.09485947e-02, -1.40992925e-02,
       -1.15606664e-02, -4.84425854e-03, -2.89545860e-03, -3.25476821e-03,
        3.18589713e-03, -1.07875774e-02, -9.71715432e-03,  1.91999297e-03,
       -9.66036227e-03, -5.48593700e-04, -2.36012437e-03, -1.06275233e-03,
       -1.33980985e-03, -4.62091295e-03, -4.31683147e-03, -2.53955717e-03,
       -1.81345583e-03, -7.25314254e-03, -3.47231911e-03, -1.03723621e-02,
       -1.83744133e-02, -3.28601375e-02,  1.77364249e-03, -1.46936551e-02,
       -2.34680483e-03, -5.01161702e-02, -4.88077523e-03, -1.37423566e-02,
       -3.65458466e-02, -8.88699107e-03, -5.83661068e-03, -7.90438522e-03,
       -3.95899126e-03, -1.77723367e-03, -3.02684447e-03, -9.52448510e-03,
       -8.91708676e-03, -9.17407311e-03, -5.05927019e-03, -1.28098298e-03,
       -5.97022995e-02, -1.05984304e-02, -3.73858260e-03, -4.37832298e-03,
       -4.41585109e-02, -1.12670416e-03, -8.20071157e-03, -5.97538194e-03,
       -1.35946588e-03, -2.69023217e-02, -3.48556638e-02, -2.55380236e-02,
       -8.87481030e-03, -8.67479108e-03, -3.65599757e-03, -9.76971630e-03,
       -9.44818836e-03, -1.00457948e-02, -4.50061634e-03, -2.33436152e-02,
       -1.31237991e-02, -1.12906592e-02,  1.30573648e-03, -1.60849513e-03,
       -1.62439537e-03, -2.12620571e-03, -4.94583184e-03, -1.40686799e-03,
       -4.84759640e-03, -8.02102312e-03, -5.23876923e-04, -5.34143485e-03,
       -7.92276673e-03, -1.63624983e-03, -3.70636396e-02, -3.91532481e-02,
       -4.48754383e-03, -2.85355956e-03,  1.49044310e-04, -8.73548444e-03,
       -7.62342382e-03, -1.16310539e-02, -8.40248354e-03, -8.41074437e-03,
       -5.57631161e-03, -9.59267095e-03, -2.51181796e-02, -2.78313328e-02,
       -1.54873135e-03, -2.28895131e-03, -6.54697325e-03, -4.17881086e-02,
        2.19384721e-03,  1.24509935e-03, -3.63067277e-02, -1.93816668e-03,
       -1.97775685e-03, -1.01109240e-02, -9.55206621e-03, -3.18931080e-02,
       -4.51106904e-03,  2.35718209e-03, -5.80378659e-02, -4.22381274e-02,
       -3.87580581e-02, -1.90296732e-02, -7.47889804e-04, -1.19243972e-02,
       -4.46278229e-02, -1.60432737e-02, -1.09554995e-02, -1.05443876e-02,
       -1.11326948e-02, -1.47579871e-02, -7.73598440e-04, -3.66518348e-02,
       -9.77740809e-03, -5.66036534e-03, -5.99164655e-03, -1.58968959e-02,
       -5.80983615e-05, -2.00729165e-02, -5.03299385e-03, -9.40495823e-03,
       -5.48804784e-03,  2.82862084e-03,  1.84073730e-03, -1.59423947e-02,
       -9.19817667e-03, -2.30846857e-03, -9.61160753e-03, -1.48225864e-02,
       -7.61537394e-03, -1.70216653e-02, -5.12603521e-02, -5.18234819e-03,
       -5.52260643e-03, -7.92434718e-03, -9.95896291e-03, -5.68359671e-03,
       -1.08459834e-02, -2.80320067e-02, -3.64068337e-02,  6.52216841e-06,
        8.86236667e-04, -7.94911943e-03, -2.39312518e-02, -3.73078557e-03,
       -6.04463229e-03, -1.31049752e-02, -7.59801921e-03, -6.09801803e-03,
       -1.89177727e-03, -1.09075168e-02, -1.85792018e-02, -1.19789140e-02,
       -6.80878945e-03, -2.16800943e-02, -1.05234850e-02, -1.77433025e-02,
       -3.32203065e-03, -1.11739412e-02, -7.73839839e-03, -1.01192771e-02,
       -3.96972373e-02, -1.31704216e-03, -1.36797503e-02, -5.28939143e-02,
       -1.11226570e-02, -5.08566853e-03,  1.76183705e-03, -3.13514732e-02,
       -1.13160233e-03, -1.16335992e-02, -7.83383660e-03, -9.24797263e-03,
       -7.13061681e-03, -9.84014478e-03, -7.25695305e-03, -7.75398687e-04,
       -2.91743129e-02,  1.43683667e-03,  8.83656263e-04, -9.58667789e-03],
      dtype=float32), array([-0.51604867, -0.97728914, -0.6200875 ,  0.5808939 , -0.5683828 ,
       -0.60247064,  0.9154309 , -0.39484426,  0.47454968, -0.5578912 ,
       -0.76583135,  0.8130961 ,  0.9585907 ,  0.8076187 , -0.21120498,
        0.39847183,  0.8532441 ,  0.43277654,  0.5224386 , -0.21100348,
        0.7872283 , -0.60261714,  0.6484407 , -0.8756606 ,  0.5319823 ,
       -0.82723176, -0.32109058, -0.8010352 ,  0.81049585, -0.36800715,
       -0.6879043 , -0.6448084 , -0.83912504,  0.74635524,  0.5832458 ,
       -0.91589534,  0.52430904, -0.73150903, -0.6390361 , -0.5844551 ,
       -0.43143648, -0.6112672 ,  1.0941713 ,  0.8789457 ,  0.8024475 ,
       -0.58383876, -0.5179515 ,  0.9771561 ,  0.75463444, -0.51542133,
       -0.70636815,  0.9111003 , -0.7408024 , -0.48872018,  0.5423409 ,
        0.6303439 ,  0.73039144, -0.5883415 , -0.7611556 ,  1.0961275 ,
        0.88152236, -0.7578295 ,  0.2317516 , -0.5753162 ,  0.6517953 ,
       -0.12885612,  1.2494153 , -0.5249034 , -0.5306657 , -0.9283698 ,
       -0.9658426 , -0.76073796, -0.31595057, -1.327762  , -0.75802064,
        0.60978395,  0.78660816, -0.5410714 ,  0.722923  , -0.7755799 ,
        0.9671815 , -0.2809089 ,  0.60117084,  0.6979968 ,  0.08451193,
       -0.70024073,  0.6810236 , -0.44233766,  0.97078186, -0.8044847 ,
       -0.55088   ,  0.7150827 , -0.48784333,  0.6507735 , -0.8954163 ,
       -0.96935546,  1.0662903 , -0.88121367, -0.6237999 , -0.63003886,
       -0.7475809 ,  0.60084075, -0.71045685, -0.3920473 ,  0.7791017 ,
       -0.620147  , -0.27219212, -0.5311829 ,  0.71456707,  0.86325985,
       -0.2302743 , -0.8404463 ,  1.0405633 ,  0.35921693, -0.9531613 ,
       -0.7309875 , -0.9927779 ,  0.72714067, -0.55107486,  0.9392209 ,
        0.6370242 , -0.78909594,  0.78608763, -0.4421926 ,  0.854977  ,
        0.38381642,  0.56072634, -0.4585855 , -0.6550284 , -0.09767345,
        0.9998347 ,  1.0191238 , -0.6989557 ,  1.0038786 ,  0.6469747 ,
        0.56020164, -0.5742077 , -0.5861949 , -0.44051266,  0.18781485,
        0.04901278, -0.47593087, -0.6848278 ,  0.7340648 , -0.65328777,
        0.7382814 ,  0.45865735,  0.4654311 ,  0.91701555,  0.9605976 ,
        0.6730892 , -0.8859663 , -0.6196032 , -1.1359909 , -0.876995  ,
       -0.88186806, -0.36351994, -0.53728986, -0.32135466,  0.9548221 ,
       -0.41145983, -0.7781456 , -0.36034793, -0.5774518 ,  0.84533787,
       -0.62562746,  0.20956986, -0.6978677 , -0.9044059 , -0.11701601,
        0.8764343 ,  0.4913213 , -0.41365206, -0.5452228 , -0.9251923 ,
        0.6595473 ,  0.70646423, -0.21920905, -0.41625872, -0.7729615 ,
       -1.0528717 , -0.5991911 ,  0.47873846,  0.64657545, -0.36249954,
       -0.60357213,  0.5746265 ,  0.8603751 ,  0.26815656, -0.77731985,
       -1.0926309 ,  0.81469965,  0.11550663, -0.13286443, -0.6148764 ,
       -0.5529497 , -0.8214789 , -1.0054222 , -0.10888159, -0.47547346,
       -0.5329315 ,  0.77901673, -0.6426297 , -0.19351192,  0.48400977,
        0.80280524,  0.8493269 ,  0.74727994,  0.9009095 ,  0.6571546 ,
        0.7663998 , -0.45167467, -0.71113485, -0.5828552 , -0.3789445 ,
       -0.5711543 , -0.758916  , -1.0233449 , -0.2929973 ,  1.1999202 ,
       -0.58001304, -1.066529  ,  0.5799443 , -0.6970565 , -0.8528534 ,
       -0.7509877 , -1.1010348 ,  1.156963  , -0.5666611 ,  0.3873792 ,
       -0.737325  ,  0.98830473, -0.51663655, -0.50032175, -0.6576626 ,
       -0.44795677,  0.99054563,  0.2007309 , -0.82017565,  1.0708537 ,
       -0.19909468, -0.70479107, -0.49561456, -0.89130306,  0.4041693 ,
       -0.46546164,  1.0539249 , -0.35897994,  0.8897238 , -0.8628727 ,
        0.10585501,  1.0647242 ,  0.3913936 ,  0.26557738,  0.6575545 ,
        0.5374599 ,  0.37248048,  1.0189433 , -0.6317716 , -0.4440343 ,
        0.46203235,  1.1300236 ,  0.6001717 ,  0.5129178 , -0.7007618 ,
       -0.39304972,  0.45083746, -0.7212037 , -0.4350752 ,  0.86464167,
       -0.8556419 , -0.6400815 , -0.7010694 , -0.75069773, -0.69384277,
       -0.14185737, -1.0820612 , -0.8279821 ,  0.8146904 , -1.0453632 ,
       -0.9301019 , -0.78310096, -0.87097806, -0.19611417, -0.4725321 ,
        0.34992793,  1.4577771 , -0.6809844 , -0.5044174 ,  0.59580886,
        0.85734105, -0.2803274 ,  0.41365644,  0.6120963 , -0.8071628 ,
       -0.4185782 ,  0.7691986 , -0.87158686,  0.4634854 ,  0.5035835 ,
       -0.71330935,  0.67777234, -0.62308943, -0.908506  , -0.564359  ,
        0.8739507 , -0.50623494,  0.74883014, -0.9310176 ,  0.5215078 ,
        0.89963907,  0.9882246 , -0.5886809 ,  0.43899146,  0.41587046,
       -0.4197157 , -0.8598048 , -0.69786453, -1.158865  , -0.12204628,
        0.6126784 , -0.92768615, -0.3961219 , -1.0411847 , -1.1188855 ,
        0.63159627,  0.34014666,  0.8036195 , -1.1800306 , -0.6646052 ,
        0.43035275,  0.7231546 , -0.73852026, -0.56614697,  0.13202688,
       -1.1759831 , -0.4392977 , -0.5375671 , -0.41914693, -0.92471087,
       -0.8257678 , -0.8174827 , -1.0383806 ,  0.6576369 ,  0.6299042 ,
        0.32960033, -0.63661295, -1.2811528 , -0.78405225,  1.0490661 ,
       -0.1844513 , -0.8102797 ,  0.6553175 ,  1.2179393 , -0.94779813,
       -0.46630263, -1.0271866 , -0.18746428,  0.7943932 ,  0.9206744 ,
       -0.5933425 ,  0.68018323,  0.8360623 , -0.7996558 ,  1.1666776 ,
       -0.7503517 , -0.6964841 ,  0.01230229,  0.92521745, -0.5907787 ,
        0.5059622 ,  1.2750609 , -0.8268998 , -1.035809  , -0.59947526,
        0.98170763, -0.7413827 ,  0.865033  , -0.6548801 ,  0.44315687,
       -0.5522688 ,  0.7047237 ,  0.61512417, -0.70251876], dtype=float32), array([14.855249 , 19.770452 ,  7.934514 ,  5.1430817,  7.9402685,
       10.611819 , 10.5648365,  5.586368 ,  5.7529807, 10.687568 ,
       11.272769 ,  6.158777 , 12.562769 , 12.638545 , 12.477556 ,
       10.1552   , 13.34221  ,  3.9525304,  8.009949 ,  6.4192033,
       11.3024845,  8.763658 ,  9.428719 , 13.524619 ,  8.754835 ,
        9.113356 ,  3.2406745, 18.076462 , 12.241323 ,  8.485511 ,
        4.094979 ,  7.001802 ,  9.609823 ,  7.602644 ,  6.6249   ,
       23.35582  ,  8.919744 , 12.888747 , 15.612983 ,  7.1574125,
        6.7454457,  9.331761 , 15.426937 , 16.221731 , 11.426266 ,
       10.59362  ,  8.588522 , 15.480281 , 16.585896 ,  8.752361 ,
       13.399878 , 19.030521 ,  8.874346 ,  7.8490767,  7.0260773,
        5.222012 , 14.46439  , 12.74302  ,  7.898407 ,  8.674943 ,
       11.743641 , 10.737226 ,  5.1075606,  7.2210093,  9.709779 ,
        2.5488539, 14.412183 ,  7.1877484,  5.7136545, 12.074183 ,
       11.598921 , 10.780769 ,  5.9721355, 24.783567 ,  5.7199574,
        8.881929 ,  3.0268946,  9.48874  ,  6.6806183, 11.761922 ,
       10.630238 ,  5.3203917, 11.485297 ,  9.329632 ,  3.784865 ,
        4.333565 , 11.433114 ,  5.9870243, 10.4963665,  7.223025 ,
        8.254018 ,  5.7166915,  6.491525 , 14.245026 , 17.734617 ,
        8.825565 , 16.00756  , 11.490497 ,  9.397185 , 14.185936 ,
       11.241383 ,  6.8759604, 11.880736 ,  8.430411 , 12.656033 ,
        3.100576 ,  7.709133 ,  8.517972 ,  5.981341 ,  8.5702305,
        4.274046 , 10.052114 , 17.870066 ,  5.8137565, 10.342579 ,
       10.872172 , 17.455732 , 12.060958 , 11.6422415, 12.294598 ,
       11.356729 , 10.2726755, 12.946656 ,  8.096612 , 10.407669 ,
        3.0882251, 10.123241 ,  9.570662 , 12.026681 ,  6.3896646,
       11.073533 , 11.694138 ,  8.0170765, 12.653355 ,  3.3738422,
        7.889851 ,  9.438893 ,  9.362758 , 11.160493 ,  4.4736047,
       15.447438 ,  5.396846 ,  8.430517 , 18.567932 ,  3.3189957,
        8.849704 ,  4.862317 ,  6.6240654,  5.175954 , 12.834917 ,
        2.632727 , 12.2215395, 10.153268 , 13.976183 , 12.337697 ,
       12.406161 ,  5.506725 ,  5.826445 ,  9.724257 , 11.055164 ,
        8.253732 ,  9.667198 ,  4.6532702,  6.462927 ,  8.009991 ,
       14.676719 ,  4.4133296,  8.131058 , 15.755978 , 15.991571 ,
        8.814561 ,  7.018285 ,  8.329596 , 10.100507 , 14.766035 ,
        9.78581  ,  8.493915 ,  2.494712 ,  9.33669  ,  7.7920957,
       14.989626 , 11.9119835,  7.6165586, 10.6438675,  6.5679493,
       10.498112 ,  5.8307652,  9.18147  ,  4.620117 , 10.565756 ,
       22.904358 ,  1.1274455,  2.2272956,  5.948204 , 12.143922 ,
        9.036504 , 15.236446 , 12.080846 ,  5.835697 ,  4.7436733,
        9.504565 ,  8.663921 ,  8.530734 ,  6.8675594,  9.0106325,
        8.518025 , 10.319687 , 10.400887 , 12.922173 ,  9.619788 ,
       11.311524 ,  6.9203467, 11.684242 , 11.039977 ,  5.8145275,
        9.838318 ,  8.9702   , 17.97337  ,  6.1816025, 16.924986 ,
        5.805386 , 13.649196 ,  7.9527903,  8.946684 , 10.402687 ,
       10.17385  , 18.960573 , 12.708885 ,  4.839409 ,  4.219203 ,
       11.96335  , 16.165665 , 11.985852 ,  7.950012 , 10.002171 ,
        6.258825 , 11.16457  ,  3.717373 , 11.684479 , 13.479316 ,
       10.294008 , 13.849691 ,  9.982923 , 10.740434 ,  3.0610251,
        6.610886 , 14.338846 ,  7.2462115,  8.392014 , 13.146225 ,
        4.3049846, 19.203617 ,  7.156723 ,  6.806071 , 11.862789 ,
        7.9263835,  2.5575736, 16.625034 ,  9.861812 ,  9.942429 ,
        4.2283506, 16.934292 ,  7.7393193,  5.37909  ,  9.653453 ,
        8.489632 ,  4.976827 , 12.77283  ,  8.103345 , 10.348748 ,
       18.4115   , 11.466319 ,  7.6230497, 11.864832 ,  6.105899 ,
       11.89491  , 19.704124 , 13.930423 ,  9.695935 , 14.179475 ,
       12.679476 , 10.842945 ,  4.1224656,  5.9506006,  6.9495215,
        7.7316465,  9.859969 , 10.924889 ,  9.066647 ,  8.359609 ,
       10.405174 ,  2.4594183, 11.885644 ,  8.806923 ,  6.561959 ,
        7.5426316,  8.918597 ,  9.493432 ,  6.8213267,  8.943657 ,
        9.725536 ,  9.248315 ,  2.4275465,  8.596446 , 16.871212 ,
        8.12259  ,  8.124118 ,  7.6879253,  9.913339 ,  5.791207 ,
       10.335947 , 15.6775465, 12.63287  ,  4.198888 ,  5.6909237,
        4.5762978, 11.155545 ,  9.181983 , 22.14402  ,  4.507014 ,
        8.344002 ,  4.771243 ,  8.444474 , 11.668121 , 22.79532  ,
        7.717892 ,  8.645262 ,  7.255167 , 23.259766 ,  9.072074 ,
        3.7806728,  3.6474059,  7.798428 ,  9.09562  ,  5.453174 ,
       20.082968 ,  5.213826 ,  4.7739205,  7.9393826, 10.270626 ,
       10.108034 ,  5.4740243, 16.06712  ,  8.185584 ,  9.349008 ,
        4.081946 ,  4.6181164, 16.927341 ,  9.998108 , 11.160006 ,
        7.749229 , 10.806425 ,  7.70132  , 15.583922 , 14.818047 ,
        5.3547587, 14.494999 ,  5.006998 , 10.435654 ,  8.290817 ,
       14.522291 ,  6.414767 , 11.765551 , 13.2071   ,  2.4099991,
       14.393865 ,  8.080654 ,  7.815647 , 11.403538 ,  9.094333 ,
       13.292794 ,  2.323006 , 12.798692 , 19.187447 ,  9.551006 ,
       14.512658 , 13.366739 , 13.081359 ,  8.8062   ,  7.285558 ,
        9.701283 ,  9.124354 ,  7.2576284, 11.481172 ], dtype=float32), array([-2.66502204e-04, -3.85153247e-03, -9.82167106e-03, -4.89501003e-03,
       -1.83822289e-02, -7.46256020e-03, -2.69284518e-03, -1.22796493e-02,
       -5.10050403e-03, -2.85417493e-03, -5.19812433e-03, -5.72982570e-03,
       -5.35853431e-02, -1.32379783e-02, -5.02122100e-03, -1.71063468e-02,
        1.25588709e-03, -1.07950736e-02,  9.42105195e-04, -7.08364183e-03,
       -8.40652362e-03, -1.36291585e-03, -3.94458044e-03, -8.35270341e-03,
       -3.42466906e-02,  8.07453354e-04, -7.31842080e-03, -3.99785396e-03,
       -1.59538332e-02, -2.14945413e-02,  2.91238772e-04, -7.59738125e-03,
       -4.82241763e-03, -1.85832605e-02, -1.30419172e-02, -8.31738207e-03,
       -3.88804190e-02, -9.76025499e-03, -3.05841919e-02, -7.34567456e-03,
       -4.57137190e-02, -4.90381047e-02, -5.15050963e-02, -8.69469903e-03,
       -1.85610373e-02, -1.15876896e-02, -5.33842528e-03, -1.38503360e-02,
       -2.70967348e-03, -1.17901163e-02, -1.16298636e-02, -4.14228067e-02,
       -7.17897806e-03, -1.10849421e-02, -7.55000068e-03, -6.61654258e-03,
       -1.04047812e-03, -1.38076628e-02, -8.81799322e-04, -6.63733901e-03,
       -5.37445478e-04, -2.98642255e-02, -2.92340387e-03, -8.33510980e-03,
       -1.83997434e-02, -6.40824670e-03, -4.12964961e-03, -2.91705900e-03,
       -9.94656049e-03, -9.02376417e-03, -1.25118671e-02, -1.65058803e-02,
       -1.76445418e-03, -4.99533629e-03, -1.03594223e-02, -7.03595905e-03,
       -5.92900161e-03, -4.90545388e-03, -2.62506539e-03,  2.21395254e-04,
       -9.50388890e-03, -1.21025778e-02, -9.91223496e-04, -8.26472999e-04,
       -8.85254052e-03, -1.90548729e-02, -5.32404426e-03, -3.26838493e-02,
       -2.42610672e-03, -6.86285598e-03, -2.41815764e-02, -5.99706406e-03,
       -1.10642267e-02, -4.55173068e-02, -2.73022847e-03, -1.28761330e-03,
       -1.98593875e-03, -3.73550830e-03, -1.38714593e-02, -7.65353814e-03,
       -5.69105893e-03, -1.50825102e-02, -4.05992474e-03, -7.93500710e-03,
       -5.36592957e-03, -4.49893810e-03, -7.87888747e-03, -1.79036113e-03,
       -5.53498976e-03, -1.11549173e-03, -9.93630663e-03, -1.09213579e-03,
       -1.36162108e-02, -1.12389242e-02, -7.63940066e-03, -3.51052010e-03,
       -6.17764378e-03, -1.22020803e-02,  5.29409153e-04, -1.13315070e-02,
       -9.76772886e-03, -9.57828667e-03, -8.16448766e-04, -8.39582924e-03,
       -2.28637058e-04, -7.88637344e-03, -2.32038042e-03, -5.51763400e-02,
       -2.42226571e-02, -7.23014772e-03, -1.24185672e-02, -2.12513423e-03,
        1.00575970e-03, -1.57076307e-03, -4.92562391e-02, -2.41836123e-02,
       -8.02340917e-03, -2.21446576e-03, -7.58034550e-03, -1.30547145e-02,
       -1.05242878e-02, -3.90011328e-03, -5.29239662e-02, -7.48890685e-03,
       -2.67383899e-03, -3.91546078e-03,  2.28641962e-04, -8.31272360e-03,
       -4.32224907e-02, -1.00995433e-02, -8.46180040e-03, -2.12468039e-02,
       -1.07883243e-02, -3.17656696e-02, -1.13012902e-02, -5.97911933e-03,
        5.48885000e-05, -5.95578738e-03, -5.01910411e-03, -3.91430408e-03,
       -2.06458028e-02, -6.21950207e-03, -8.55513941e-03, -4.49462654e-03,
       -1.08549779e-03, -9.50674294e-04,  3.22234526e-04, -1.01883635e-02,
       -1.15549378e-03, -1.89898033e-02, -3.12010981e-02, -7.75845256e-03,
       -3.32472241e-03, -1.50206890e-02, -2.15823092e-02, -1.17396358e-02,
       -3.53977969e-03, -7.17352494e-04, -1.54391220e-02, -1.69376284e-02,
       -8.46341066e-03, -3.29065719e-03, -8.49471055e-03, -1.17877852e-02,
       -2.78480514e-03, -7.65742268e-03, -1.01659736e-02, -4.74391365e-03,
       -6.25285599e-03, -4.50992864e-03,  1.84814053e-05, -5.16683646e-02,
       -1.01320194e-02, -2.84842798e-03, -7.91761559e-03, -9.12909675e-03,
       -3.64905153e-03, -2.55282712e-03,  1.01856398e-03, -2.96265981e-03,
       -6.15544617e-03, -7.19977356e-03, -9.24997777e-03, -9.54908226e-03,
       -6.40998455e-03, -7.28688017e-03, -2.74965987e-02, -6.05711387e-03,
       -1.53313612e-03, -9.32453852e-03, -3.19541059e-02, -1.44240260e-02,
       -4.74544875e-02, -1.37163363e-02, -9.62904363e-04, -2.89487652e-04,
       -4.80198599e-02, -1.70526821e-02, -4.66783671e-03, -6.32090634e-03,
       -6.09502979e-02, -5.49323484e-03, -1.21395541e-02, -1.14151053e-02,
       -5.17024025e-02, -2.82478868e-04, -1.96891166e-02, -5.85699361e-03,
       -8.83686636e-03, -6.04802556e-03, -1.28674181e-02, -8.45919456e-03,
        1.60061195e-03, -7.88161997e-03, -4.15117526e-03, -3.60504203e-02,
       -8.12449120e-03, -1.18361181e-02, -4.57941834e-03, -1.44472960e-02,
       -2.30969079e-02, -7.20461458e-03, -7.58973835e-03, -4.72651096e-03,
       -1.30684562e-02, -7.01244455e-03, -1.11758625e-02, -1.17955368e-03,
       -1.01711061e-02, -4.56820838e-02, -3.80017725e-03, -8.51393677e-03,
       -3.37670534e-03, -3.36954673e-03, -4.91967462e-02, -3.31538096e-02,
       -2.12627323e-03, -8.34576506e-03, -4.98766731e-03, -5.35935760e-02,
       -1.13102281e-02, -1.35913845e-02, -3.54849957e-02, -4.82892953e-02,
       -2.58551911e-02, -1.00187715e-02, -3.85029521e-03, -1.14750173e-02,
       -1.24399187e-02, -7.41320662e-03, -7.31987995e-04, -4.47260123e-03,
       -3.56047601e-02, -6.68951403e-03, -3.66992806e-03, -8.47992208e-03,
       -2.44522118e-03, -8.57986684e-04, -1.42626781e-02, -1.61537132e-03,
        2.04414455e-03, -9.17929597e-03, -1.20920492e-02, -8.68426170e-03,
       -2.83911382e-03, -4.66078287e-03, -7.97252357e-03, -1.41541585e-02,
       -4.83749807e-03, -4.09118133e-03, -3.43968570e-02, -4.76784771e-03,
       -8.25875718e-03, -6.02502434e-04, -1.50784878e-02, -4.59839677e-04,
       -8.84553883e-03, -1.12913055e-02, -1.33435829e-02, -2.04411671e-02,
       -1.83489546e-03, -5.25837066e-03, -2.48744749e-02, -4.20118496e-03,
       -1.50913028e-02, -1.22449556e-02, -6.54446939e-03, -4.57654009e-03,
       -1.66886393e-03, -5.62513294e-03, -7.37717666e-04, -3.85222249e-02,
       -7.65468134e-03, -7.87866674e-03, -4.48378734e-02, -8.23538564e-03,
       -3.01460642e-03, -9.82433930e-03, -3.21262702e-02, -3.55389193e-02,
       -6.13492448e-03, -3.82331735e-03, -1.07290754e-02, -3.14822374e-03,
       -3.11932061e-04, -5.58920344e-03, -2.67776253e-04, -3.44081572e-03,
       -1.37919281e-02, -6.09930381e-02, -9.36383940e-03, -1.34490170e-02,
       -9.12590232e-03, -2.92979833e-03, -2.64474424e-03, -1.23059805e-02,
       -8.45873263e-03, -4.25629457e-03, -3.05417273e-03, -2.79937554e-02,
       -6.24064310e-03, -2.54250458e-03, -7.28057581e-04, -6.37658918e-03,
       -3.72178794e-04, -1.06039853e-03, -5.44923649e-04, -2.63343519e-03,
       -8.19636974e-03, -1.01820920e-02, -2.32299161e-03, -2.95768883e-02,
       -7.55874952e-03, -3.03675351e-03, -9.10340995e-03, -1.60520559e-03,
       -2.78566573e-02, -3.57538555e-03, -5.51469345e-03, -1.46459034e-02,
       -2.85915914e-03, -1.99073963e-02, -3.76296137e-03, -7.42115453e-03,
       -2.69488944e-03, -2.33079493e-03, -1.29903425e-02, -1.45712227e-03,
       -5.52805094e-03, -7.56467087e-03, -4.61696647e-02, -3.88081074e-02,
       -3.20014656e-02, -9.40462295e-03, -4.48528789e-02, -8.36771331e-04,
       -2.53927223e-02, -5.12730377e-03, -2.59550707e-03, -7.99213815e-03,
       -1.13038858e-02, -7.79589871e-03, -6.04945719e-02, -4.08041142e-02],
      dtype=float32), array([ 0.5740825 ,  0.81053746,  0.893255  , -0.5866675 ,  0.25097218,
       -0.10882282, -0.5173122 ,  1.0627795 , -1.0126307 ,  0.8443763 ,
       -0.5579092 , -0.7674349 ,  0.10117018, -0.84972847,  0.65785   ,
       -0.7872217 ,  0.75576204,  0.84318113,  0.672333  ,  0.9143236 ,
       -0.8517398 , -0.6235518 ,  0.8820824 ,  1.0390112 , -0.92317945,
        0.58818203, -0.20003964,  0.720351  ,  1.0606276 , -0.8570777 ,
        0.60581946,  0.8512025 , -0.4426699 , -0.50511825,  0.8049396 ,
       -0.514852  , -0.5480598 ,  0.8863192 , -0.59772563, -0.26497635,
       -0.7429999 , -0.76014227, -1.220275  ,  0.54488117,  1.0616868 ,
        0.90264827,  0.61917675, -0.51842433, -0.8637348 ,  0.48630744,
       -0.8456436 ,  0.24341312, -1.0211481 ,  0.8591257 ,  1.0639037 ,
       -0.36641198, -0.32460397, -0.7799226 ,  0.21306095, -0.92748016,
       -1.1017001 , -0.81603867, -0.38038802,  1.0957149 ,  1.0932678 ,
       -0.97620606, -0.6154119 , -0.60609215, -0.5092807 , -0.32457605,
        0.5372904 , -0.32848728, -0.45612586, -0.6924346 , -0.6227344 ,
       -0.6531631 , -0.47345358,  0.5035665 , -0.40496153,  0.46311545,
       -1.0221751 , -0.771466  , -0.6687349 ,  0.68807846,  0.6906502 ,
       -0.81768525, -0.898627  , -1.16665   , -0.6732534 ,  0.76580274,
        0.11363731, -1.0779581 ,  0.96669775, -0.640284  , -0.6988106 ,
       -0.34156492, -0.8828887 , -0.7788623 ,  0.61243176, -0.7126441 ,
       -0.95245975,  0.71563965,  0.44547662,  0.831923  , -0.71432364,
        0.8002473 ,  0.58136934, -0.9322333 ,  0.6361292 , -0.3696091 ,
       -1.2457628 ,  0.76132804,  1.0321794 ,  0.9226628 , -0.9951837 ,
       -0.7246534 , -0.91235864,  0.75597876,  0.74246824,  1.1471081 ,
       -0.8855575 ,  1.0732377 , -0.46691847,  0.8678129 , -0.27683643,
        1.1393752 , -0.3416225 , -1.2618519 , -0.6595562 ,  1.3415779 ,
        1.0839528 ,  0.5135321 ,  1.1820743 , -0.523272  , -0.5819099 ,
       -0.91978   ,  0.2063419 , -0.3903919 ,  1.1762668 , -0.78379357,
       -0.8618432 ,  0.44670835, -0.7192373 , -0.5757126 ,  0.6706586 ,
       -0.78594744,  0.7367704 ,  0.82283264, -0.46778718,  0.7824068 ,
        0.45123112,  0.23642975,  0.90549403, -0.78078955,  0.9623884 ,
        0.45353445,  0.44144735, -1.002567  , -0.7328256 , -0.97576815,
        0.49365538,  1.2628461 ,  1.1908219 ,  0.5375159 , -0.62448204,
       -0.90178454,  0.7884165 ,  0.91423607,  0.5898857 ,  0.8825627 ,
        0.7587281 ,  1.1064976 , -0.7453038 , -0.7381517 ,  0.87294614,
        1.0708236 , -0.5171306 , -0.7736991 ,  0.50393534, -0.8307575 ,
       -1.272435  , -0.6784494 , -0.3164172 ,  1.3146214 , -0.35035297,
       -0.6435846 ,  0.71679974,  0.5650496 , -0.55794746, -0.54096204,
        0.5619483 , -0.6431233 ,  0.9261098 , -0.5674348 , -0.81194174,
        0.62500507, -0.6551536 , -0.36286855,  0.4630275 ,  0.39833766,
       -0.7806037 , -0.4877051 ,  0.7791392 ,  1.1840694 ,  0.70135045,
       -0.9327578 , -0.33869866, -0.6826936 , -0.77523476,  1.2491875 ,
       -0.7197362 ,  0.23710404, -0.6076359 , -0.7118879 , -0.8187619 ,
       -0.57255423, -0.3853269 , -0.88239545, -0.8653318 , -0.40958345,
       -0.73095065, -0.9890317 , -0.4224623 , -0.62501985, -1.5682203 ,
        0.7147924 ,  0.8826802 , -1.0627416 ,  0.58680326, -0.37843588,
        0.4725316 ,  1.0363395 ,  0.6297345 , -0.6436008 , -0.7816124 ,
       -0.02866719,  1.0381312 , -0.198343  , -0.67708784, -1.0171779 ,
       -0.99749285, -0.5313221 , -0.70228237, -0.8020675 ,  0.75606626,
        1.1542046 ,  1.04287   ,  0.5663614 , -1.1355025 , -0.88219965,
       -0.44322225,  0.68678474, -0.6062644 , -0.45260778, -0.49687636,
       -0.47369748, -0.4381564 , -0.80083245, -0.5048931 , -0.78241557,
        0.62569225, -0.78539306, -0.22319196, -0.77024823, -0.5444284 ,
       -0.72468066, -0.57340133,  0.35706294, -0.7822164 ,  1.2185404 ,
        0.5703899 , -0.51177734,  1.4071599 , -0.52115124,  0.68821   ,
        1.0395687 ,  0.771948  ,  0.34880543,  1.0485876 , -0.93352526,
        0.43895417,  0.4839355 , -0.2919156 , -0.76354104, -0.53632003,
       -0.42305258,  1.0686128 , -0.6013903 , -0.47783843, -0.5760783 ,
       -0.688057  , -0.6554114 , -0.4299699 , -0.8226112 , -0.8774038 ,
        0.65032715, -0.7961783 ,  0.7349621 ,  0.92478126, -0.6510893 ,
        0.6019895 , -0.670877  , -0.4798031 , -0.7196006 , -0.92516094,
       -0.72332704,  0.9793197 ,  0.65024096, -0.54785657,  0.15222222,
       -0.9056903 ,  0.748654  ,  0.80310345,  0.734638  , -0.5113086 ,
        0.980604  ,  0.7174089 , -0.6255893 , -0.6923298 , -0.46992952,
       -0.5605178 , -0.6924193 , -0.7268716 , -0.70515364, -0.42922497,
       -1.2988652 ,  0.5705313 , -0.5495962 ,  0.7736273 , -0.46822426,
       -1.1905919 , -1.1868522 ,  0.4883779 , -0.63349146, -0.6336776 ,
        1.1249923 , -1.0283902 , -0.5159598 , -0.69725466,  0.63605833,
        1.2026243 , -0.3768407 , -0.69808924, -0.90035623,  0.6384516 ,
       -0.65280604,  0.61416924, -0.4883937 ,  1.1137213 ,  0.3672443 ,
       -0.7228436 , -0.5351423 ,  0.777743  , -0.71259844,  0.01643531,
       -0.80674803, -0.26068085, -0.5570981 , -0.4355231 , -0.9170064 ,
        0.589356  , -1.0107203 , -0.5481426 , -0.34143734, -0.6034273 ,
       -0.50369316, -0.39449212,  0.5199915 , -0.26357582,  0.84328496,
       -1.0446669 ,  0.14825809, -0.30055553,  1.2109286 , -0.97598803,
       -0.62156117, -0.7650435 , -0.45507473, -0.8410231 ,  1.183633  ,
        1.1591848 ,  0.80693215, -0.81476206, -0.6466515 ], dtype=float32), array([ 8.983982  ,  8.615449  , 12.81132   ,  5.9653053 ,  2.7965963 ,
        4.0305943 ,  5.7796526 ,  8.558931  , 12.243948  , 11.454056  ,
        6.4322205 , 12.54934   ,  9.7851715 , 10.373445  ,  9.396609  ,
        8.702946  , 10.841627  , 11.799004  , 11.07849   , 12.2762375 ,
       15.070656  , 13.39889   ,  8.83311   , 16.182085  , 12.761559  ,
       10.914739  ,  8.994366  ,  6.6405644 ,  9.307172  ,  9.500322  ,
       12.921488  , 17.744703  ,  7.330506  ,  7.242826  , 11.136649  ,
       10.062242  ,  7.4989476 , 12.088753  ,  6.289483  ,  7.0861025 ,
        5.189737  ,  5.536654  , 24.09884   ,  7.897008  , 10.736913  ,
       10.486223  ,  7.0493383 ,  4.7523427 , 15.625949  ,  5.139582  ,
        9.707674  , 25.930813  , 19.526104  , 13.229085  , 15.152584  ,
        7.0224466 ,  7.400683  ,  4.228528  ,  6.582238  , 19.289793  ,
       15.588858  ,  9.686889  ,  5.749987  , 14.626625  ,  9.737623  ,
       12.435495  ,  7.9681177 ,  8.896376  ,  5.6662383 ,  5.4126773 ,
        8.069235  ,  5.765298  , 10.319179  ,  9.984482  ,  8.802659  ,
        7.8084865 ,  9.866669  ,  3.7173746 ,  7.4730806 , 12.608763  ,
       17.388493  , 12.797726  , 10.175652  ,  7.5891986 ,  9.074486  ,
        7.16571   , 13.187997  , 16.354383  ,  9.329562  , 13.124801  ,
        0.98410296, 20.632498  , 12.342444  ,  7.142077  , 11.72413   ,
       12.065136  , 14.613042  , 10.585389  ,  3.8676438 ,  9.088229  ,
       27.527891  ,  6.8423557 ,  5.6667666 ,  6.878149  ,  9.411051  ,
        8.852702  , 11.756471  , 11.876183  ,  7.040834  ,  9.067177  ,
       13.589792  ,  8.705885  , 10.46335   , 10.489773  , 15.878952  ,
        9.887589  , 15.814594  ,  8.3795595 ,  8.01999   , 11.627417  ,
        8.659546  , 13.370023  ,  8.138148  ,  8.613666  ,  5.291836  ,
       17.20888   , 10.066253  , 13.687202  ,  4.384491  , 23.111721  ,
       15.039736  ,  7.7294836 , 23.362276  ,  8.8054695 ,  6.333058  ,
        7.7958093 ,  2.818662  ,  7.899046  , 23.762384  ,  6.9190073 ,
        5.328258  ,  6.06549   ,  2.2994523 , 11.384027  ,  9.468157  ,
       10.658179  , 10.545014  , 11.320579  , 33.408905  ,  8.609897  ,
        9.975946  , 12.061666  , 14.288199  ,  4.1421394 , 11.015642  ,
        6.3344827 ,  9.952257  , 11.287616  , 13.252387  , 10.844322  ,
        2.6635408 , 20.350538  , 19.037485  ,  1.6171347 , 11.121984  ,
       10.17098   ,  9.883446  ,  9.818379  ,  6.390862  ,  4.067392  ,
        6.5468745 , 19.779533  , 13.797876  ,  9.6943865 ,  3.4549415 ,
       12.5974655 ,  7.969026  , 13.875208  ,  5.5967    , 11.192293  ,
       29.180052  , 10.502458  ,  5.69627   , 17.298883  , 11.85967   ,
       10.246681  ,  8.76377   ,  5.905418  , 11.337882  , 11.649627  ,
        7.1998615 , 15.394143  ,  9.173523  , 12.335978  , 15.599609  ,
        9.607582  ,  8.425134  ,  7.5143266 , 12.644316  ,  5.9296255 ,
        7.22052   ,  5.516224  , 14.771587  , 19.367113  ,  7.63178   ,
       19.401976  , 17.824558  ,  8.21744   , 12.680305  , 29.353216  ,
        7.7326727 ,  7.253563  ,  9.460015  , 11.607362  , 11.254811  ,
       10.913408  ,  2.216473  , 10.620985  , 11.744619  ,  8.032342  ,
        3.5488873 , 17.98962   ,  4.697728  ,  4.7052135 , 23.87269   ,
        9.648023  ,  3.670714  , 12.302082  ,  8.7072935 ,  4.7965717 ,
        5.930157  , 13.181765  ,  9.403128  , 10.590022  , 12.111484  ,
        3.0479717 , 14.315333  ,  4.967994  ,  8.774959  , 10.482018  ,
        8.6532345 ,  6.132582  ,  7.771578  , 13.120803  ,  9.263341  ,
       20.959146  ,  8.709233  , 10.053432  , 22.138243  ,  5.820882  ,
        5.3015857 , 10.4510975 ,  9.752665  ,  6.8639545 ,  2.9285686 ,
        2.4842746 ,  9.035012  , 13.9159565 ,  7.291487  ,  7.673988  ,
       11.690091  , 12.933602  ,  3.1812816 , 10.020783  ,  4.2748275 ,
        7.7191887 ,  8.859324  ,  9.188189  ,  6.5606933 , 20.011538  ,
        8.849815  ,  9.281455  ,  5.177049  ,  6.9211383 , 10.7190895 ,
       14.094708  , 15.100579  ,  7.100536  , 11.570578  ,  8.957633  ,
       11.488822  ,  5.2296977 ,  5.5125875 ,  4.643247  , 10.29056   ,
        9.208183  , 18.264608  ,  6.3982525 ,  8.874004  ,  9.421025  ,
       10.095063  ,  9.295769  ,  6.516949  , 17.70879   , 10.281598  ,
        8.434093  , 13.656719  , 12.499196  , 10.648061  ,  8.292942  ,
       11.744472  , 13.6437645 ,  1.9918603 , 14.958524  ,  6.724526  ,
        7.508495  ,  7.1550384 ,  6.616514  ,  9.494653  ,  3.2368782 ,
       16.348368  ,  3.1798956 , 15.166796  , 14.863203  ,  5.742424  ,
       11.803159  ,  9.33418   ,  9.919721  ,  4.324499  ,  8.64995   ,
        7.945746  ,  9.244909  , 11.790726  , 10.83398   , 14.837874  ,
       29.70152   ,  6.215712  ,  8.147564  ,  6.0081086 ,  2.5701535 ,
       21.45671   , 22.859926  ,  5.4483395 ,  8.460182  , 10.596392  ,
       16.141684  , 10.944197  ,  8.149332  ,  9.074137  ,  7.082084  ,
       24.442507  ,  9.723169  , 11.967965  , 11.351065  ,  7.1385884 ,
        9.575329  , 13.787818  ,  8.559854  , 17.280514  ,  6.79451   ,
        8.682394  , 18.899534  , 12.698707  , 10.262217  ,  4.3382506 ,
       14.003133  , 16.150845  ,  7.873807  ,  8.648656  ,  7.7535877 ,
        8.130198  , 11.485149  ,  6.0062304 ,  9.334613  ,  9.588861  ,
       12.182942  ,  5.117924  ,  4.4668627 ,  6.1515827 , 13.645943  ,
       11.887126  ,  8.533431  , 26.901255  , 15.264551  ,  8.456073  ,
       13.411654  ,  7.319558  ,  5.9627795 , 11.736238  , 21.89718   ,
       14.221473  , 12.363499  ,  6.0263686 ,  4.94272   ], dtype=float32), array([-7.10751489e-03,  2.65447935e-03,  3.51335527e-03, -2.96853320e-03,
       -4.45040828e-03, -5.62559068e-03, -2.85236840e-03, -2.66969507e-03,
       -1.59248039e-02, -2.08526780e-03, -2.56309542e-03,  3.74767371e-03,
       -1.08057894e-02, -4.05208580e-02, -1.51172641e-03,  1.98513409e-03,
       -7.44208973e-03, -1.12486966e-02, -4.14930331e-03, -1.25520825e-02,
       -1.39965815e-02, -2.66770758e-02, -2.11628154e-03, -8.63447972e-03,
        2.71179597e-04, -3.37217189e-02, -9.92959272e-03, -8.99083726e-03,
       -4.12295386e-03,  3.56020348e-04, -9.46979318e-03, -1.47105632e-02,
       -2.87623587e-03, -1.16302129e-02, -2.59839129e-02, -4.58705314e-02,
        4.09282307e-04, -3.26768383e-02, -7.66017335e-03, -9.87193082e-03,
       -3.63186151e-02, -1.78408138e-02, -8.75030924e-03, -1.19720707e-02,
       -1.21257761e-02, -2.90887244e-02, -2.92961430e-02, -3.18148360e-02,
        1.04631193e-03, -9.63749178e-03, -1.56432614e-02, -5.15408963e-02,
       -1.18292766e-02, -9.79385339e-03, -5.04470570e-03, -5.83510482e-05,
       -1.00701293e-02, -4.95538116e-02, -1.49614317e-02, -1.06736710e-02,
       -9.80635826e-03, -5.49192028e-03, -1.21267466e-02, -1.24776149e-02,
       -2.70861052e-02, -1.06077502e-02, -1.00476537e-02, -1.25760371e-02,
        4.71906038e-03, -8.10210314e-03, -1.16134509e-02, -9.35514830e-03,
       -4.32658987e-03,  3.01794754e-03, -9.22080688e-03, -9.95457731e-03,
       -3.83735187e-02, -4.03122380e-02, -4.41375980e-03, -1.36791989e-02,
       -1.01192668e-02, -1.03506411e-03, -6.76295534e-03, -4.09449730e-03,
       -1.84680044e-03, -2.57746805e-03, -7.83928391e-03, -6.94307452e-03,
       -2.53693806e-03, -5.41428383e-03, -3.42047475e-02, -8.50947748e-04,
       -1.14051616e-02, -4.98382049e-03, -2.22572181e-02, -9.65601951e-03,
       -1.88399721e-02, -4.28383164e-02, -1.40184760e-02, -3.78304091e-03,
       -9.60405543e-03, -3.92179191e-02, -4.41408344e-03, -1.41490875e-02,
       -1.37040270e-02, -2.33150669e-03, -6.37989677e-03, -3.54083553e-02,
       -4.50079665e-02, -4.58291499e-03,  3.95068387e-03,  2.86946236e-03,
        1.38812989e-03, -1.85820577e-03, -1.69105991e-03, -8.91068298e-03,
       -6.77649304e-03, -3.61669064e-02, -1.18017578e-02, -6.60441164e-03,
        4.13976470e-03, -4.32269834e-02, -1.27596073e-02, -5.37326140e-03,
       -1.23397978e-02, -7.59194512e-03, -3.01251328e-03,  3.59947816e-03,
       -4.93518077e-03, -4.49273288e-02, -2.03994978e-02, -2.51043146e-03,
       -1.03486292e-02, -1.00854076e-02, -9.19144787e-03, -3.88033055e-02,
       -2.38638395e-03, -1.23288920e-02,  3.31933703e-03,  3.08916089e-03,
       -2.15245895e-02, -9.48388316e-03, -2.76636761e-02, -2.10103448e-02,
       -3.74672585e-03, -1.60858687e-02, -1.02772824e-02, -2.22300366e-02,
       -9.48025845e-03, -3.30488831e-02, -1.15607874e-02,  2.97776947e-04,
       -7.22505059e-03, -1.09391958e-02, -9.90289915e-03, -1.30484290e-02,
       -2.43015345e-02, -6.60066772e-03, -1.00235566e-02, -1.62525978e-02,
       -2.91154813e-03, -9.05804452e-04, -2.19222531e-03, -1.22403377e-03,
       -2.95596151e-03, -3.53477709e-02, -2.22777366e-03, -5.60915330e-04,
       -1.35053666e-02, -8.77868570e-03, -2.79301917e-03,  1.36353518e-03,
       -1.19832437e-02, -1.05818231e-02, -3.68173532e-02, -1.37997521e-02,
       -5.27338218e-03, -8.80950317e-03, -1.31381222e-03,  1.92861934e-03,
       -2.07377598e-03,  2.44689779e-03, -4.55642082e-02, -9.63127520e-03,
       -1.00985672e-02, -2.42889617e-02, -3.69543978e-03, -1.02121104e-02,
       -4.93542366e-02, -1.31254329e-03, -1.84363674e-03, -2.06720475e-02,
       -1.41644920e-03, -4.51607117e-03, -2.24531572e-02, -6.20182743e-03,
       -5.33619104e-03, -1.05898781e-02, -1.50071376e-03, -1.61551256e-02,
       -1.29244132e-02, -1.86995603e-02, -2.52635148e-03, -7.80444546e-03,
       -2.24306639e-02, -9.17293876e-03, -4.55862656e-03, -1.14206597e-02,
       -9.37941391e-03,  3.83854914e-03, -6.63789921e-03, -1.97532005e-03,
       -3.99178453e-03,  8.34496459e-04, -1.74019556e-03, -7.23094540e-03,
       -1.27325272e-02, -2.41817581e-03, -1.01167653e-02, -4.39464115e-02,
       -1.70287937e-02, -6.62841648e-03, -1.60415154e-02, -4.88367863e-02,
       -5.37026068e-03, -4.63104108e-03, -1.42964651e-03, -1.65173295e-03,
       -1.00921942e-02, -1.61840185e-03, -1.17405225e-02,  7.62138923e-04,
       -3.41236778e-03, -3.83184031e-02, -1.18940370e-02, -4.53162156e-02,
       -3.57619324e-03, -2.27856208e-02, -8.83836590e-04, -5.08284243e-03,
       -1.57934297e-02, -1.02316290e-02, -3.88315297e-04, -5.04638888e-02,
        3.66118678e-04, -1.20828524e-02, -5.53557277e-02, -7.95936037e-04,
       -3.53521667e-02, -1.98715348e-02, -9.31145065e-03, -7.80489435e-03,
       -2.28874292e-02,  3.41799110e-03, -4.56450228e-03, -1.04650063e-02,
       -2.13229135e-02, -1.27320187e-02, -2.88915429e-02, -2.24000216e-03,
        1.46723248e-03, -6.07306883e-03, -1.90203020e-03, -9.29464772e-03,
       -9.20419861e-03, -2.01600511e-03, -1.02322921e-02, -2.25738063e-02,
       -9.87345446e-03, -4.65350272e-03, -1.26600619e-02, -1.00322235e-02,
       -3.84854525e-03, -8.86118971e-03,  1.31556019e-03, -1.98675059e-02,
       -8.95470753e-03, -7.28783477e-03, -1.27205094e-02, -1.01352604e-02,
       -3.93226650e-03,  2.71166349e-03, -1.90097038e-02, -4.61132545e-03,
        1.40853552e-03, -1.07306195e-02, -5.41321700e-03, -2.25718338e-02,
       -1.27956392e-02, -5.39418161e-02, -4.21018228e-02, -2.42960732e-03,
       -4.35244478e-02, -3.70119438e-02, -5.48440311e-03, -1.52023071e-02,
       -1.00796055e-02, -1.12367305e-03, -6.27311086e-03,  3.98232369e-03,
       -1.43982032e-02, -2.04783515e-03, -3.41004021e-02,  9.77532356e-04,
       -1.13052437e-02, -9.52467695e-03, -9.09118634e-03, -2.17292085e-02,
       -1.15898130e-02, -4.27953200e-03, -1.24208052e-02, -9.47066117e-03,
       -1.26293127e-03, -4.68748324e-02, -5.58244577e-03, -9.04923212e-03,
       -5.63737471e-03, -4.86420840e-03, -7.34839868e-03, -7.78402388e-03,
       -9.14565101e-03, -2.56487378e-03, -9.95361805e-03, -7.35529093e-03,
       -8.76549631e-03, -9.78092570e-03, -1.53593451e-03, -1.09667992e-02,
       -1.91020186e-03,  4.19467036e-03,  4.19836072e-03, -7.86124729e-03,
       -1.00602740e-02, -7.81522598e-03, -1.27590483e-03, -1.53419850e-02,
       -8.37701838e-03, -1.98801747e-03, -5.64670283e-03, -1.26074383e-03,
       -4.87299971e-02, -1.89058632e-02, -7.36609986e-03,  3.99644254e-03,
       -3.29259112e-02,  4.28588688e-03, -9.84589383e-03, -2.27275048e-03,
       -1.01764556e-02, -8.23801011e-03, -2.19528447e-03, -2.82173697e-02,
       -4.04452644e-02, -1.19981449e-02, -1.17564620e-02, -2.46019126e-03,
       -7.62453722e-03, -2.95490236e-03, -5.17817680e-03,  2.16922420e-03,
       -2.73285359e-02, -1.49270836e-02, -1.30152944e-02,  3.43880197e-03,
       -3.20601314e-02, -3.93081307e-02, -5.38497698e-03, -2.37690154e-02,
        1.79253402e-03, -4.90917871e-03, -9.53139644e-03, -6.89398730e-03,
       -3.68005899e-03,  2.05097301e-03, -1.80876460e-02, -1.48766879e-02,
       -8.63081776e-03,  3.90700484e-03, -3.58555862e-03,  4.94492066e-04,
       -1.42657233e-03, -4.63274820e-03,  9.62325139e-04, -1.60556231e-02],
      dtype=float32), array([ 0.7533895 ,  0.36481112,  0.34581453, -0.6596039 , -0.50610393,
       -0.7773577 , -0.9788995 , -0.44515777, -0.16948463, -0.5949216 ,
       -0.7183596 ,  0.96870375,  0.7012389 , -1.0278764 ,  0.5952689 ,
        0.47678083, -0.50696415,  0.29564226, -0.8075241 , -0.64116925,
       -0.849938  , -0.7496664 , -0.7255419 , -0.6965569 ,  0.68412805,
       -0.73930913,  1.1443634 ,  0.92906135, -0.7196898 ,  0.9837131 ,
       -0.6908888 ,  0.6061503 , -0.5885739 ,  1.096466  , -0.61446255,
       -0.80504483,  0.36115828, -0.01124277, -0.81811595,  0.73657465,
       -0.906896  , -0.8680033 ,  1.2399397 ,  0.88014317, -0.8986815 ,
       -0.3292744 , -0.53033686, -0.88150126,  0.511948  ,  0.90813684,
       -0.67236465, -0.8154294 ,  0.6676355 , -0.6581453 , -0.8103641 ,
        0.5670275 ,  1.1388385 , -0.95209867, -0.7187751 ,  0.44514292,
        0.616639  , -0.5694173 ,  0.93613815,  0.9434562 ,  0.4455978 ,
        0.58601284,  1.1047527 ,  0.9961731 ,  0.60728383, -0.75889325,
        0.9545007 , -0.6049648 , -0.7078096 ,  0.29537115, -0.43423924,
       -0.59634864, -0.57896066, -0.5591524 ,  0.692206  ,  0.8320558 ,
        0.9500965 , -0.2434101 , -0.41897747, -0.6293837 , -1.217402  ,
        0.767339  , -0.12608029, -0.22698258, -1.0442827 , -0.4444875 ,
       -0.7072889 , -1.0096086 ,  0.75542325, -0.70315146, -0.66712356,
        0.96415824,  0.84020525, -0.41520843, -0.4218807 , -0.6861467 ,
        1.2027385 , -0.07800725, -0.44799957,  1.271555  , -0.5744095 ,
       -0.641248  , -0.7393478 , -0.6168543 , -0.7720666 , -0.7403934 ,
        0.6451513 ,  0.33447242,  0.82675666, -0.61662257, -0.8243059 ,
       -0.32056013, -0.8803418 , -0.61031115,  0.6457616 , -0.6385177 ,
        1.0109009 , -0.76129293,  0.5224658 , -0.3760923 , -1.0195422 ,
        0.45199883, -0.56275123,  0.49408826, -0.8282378 , -0.4927022 ,
       -0.54855675, -0.7171531 ,  0.7636312 ,  0.995061  ,  0.7619488 ,
       -0.27850187, -0.628215  ,  0.87429523,  0.7401695 ,  0.5709686 ,
       -0.8892912 ,  0.6709368 ,  0.02759285, -0.5251069 , -0.46201268,
        0.44316977,  0.891067  ,  0.90310127,  0.5006889 , -0.33412945,
       -0.6481863 ,  0.48664337, -0.84764934,  0.832879  ,  0.7936214 ,
        0.5959027 ,  0.46607053, -0.4566456 , -0.5514156 , -0.39866468,
       -0.5771381 ,  0.65996194, -0.39015982, -0.35467494,  0.58477616,
       -0.30777374, -0.43837953, -1.0411569 ,  0.4651193 ,  0.9499074 ,
       -0.54333526,  0.6604205 ,  0.8799809 ,  0.99240535, -0.48547688,
       -0.35111532, -0.9082112 , -0.9246801 ,  0.9623631 ,  0.74081963,
       -0.4343624 ,  0.7691614 ,  0.0361803 ,  1.0230385 ,  1.035373  ,
       -0.66097033, -0.9393791 ,  0.769079  , -0.9699539 , -1.0654992 ,
       -0.5976422 , -0.71639264, -0.9062731 , -0.8087742 , -0.87464386,
       -0.5998122 ,  0.42203614,  0.70004344, -0.49685633, -0.598551  ,
        0.64358187,  0.8983122 , -0.91084164, -0.66895425, -0.24554168,
        0.99958736, -0.66705173,  0.71054417, -0.54458314,  0.6933217 ,
       -0.6545151 , -0.6077418 , -0.6666716 ,  0.34677273, -0.75028133,
       -0.559881  ,  0.4756289 , -1.1004308 , -0.7139868 , -0.8723005 ,
        0.70231825, -0.5923462 , -0.4774441 , -0.85215914, -0.5104966 ,
       -0.8397286 , -0.89264023, -0.98321706, -0.9344288 ,  0.5625172 ,
       -0.23741056,  0.47046852, -0.57972974,  0.48396012, -0.5526896 ,
       -0.71030194,  0.4914051 , -0.55037254, -1.2958095 , -0.7932915 ,
        0.548874  ,  0.9155562 ,  0.48587134, -0.85838294,  0.8387856 ,
        0.9040443 ,  0.37317267,  0.44999886, -1.1849699 , -0.41553596,
        1.0239829 , -0.7867022 , -0.5008178 ,  0.60302746, -0.6594584 ,
        0.7593373 ,  0.735169  ,  0.42390788, -0.6359471 , -0.3771573 ,
        0.44996578, -0.85607606, -0.64783496, -0.45294204, -0.85670555,
       -0.6167535 ,  0.53013253, -0.8431883 ,  0.38128686, -0.7321707 ,
        0.67988396,  1.1409106 , -0.58948815,  0.67397267,  0.89056677,
        0.08328276, -1.1313317 , -0.4997638 ,  0.4886246 , -0.7404777 ,
       -0.55770576,  0.5462903 , -0.17382418, -0.9200261 ,  0.6389583 ,
        0.20031019, -1.101135  , -0.40514043, -0.9067729 , -0.41926226,
       -0.70052993,  0.23062865, -0.88385016, -0.0985718 , -0.40115502,
        0.8143074 ,  0.55851406,  0.46166515, -0.60693413,  0.4597377 ,
        0.26056558, -0.60124797, -0.7547919 ,  0.71356153,  0.60276014,
        1.1517546 ,  1.2024069 , -0.5277476 ,  1.0915029 , -0.70730567,
       -0.44185483,  0.8689458 , -0.76817447, -0.37642488, -0.74930495,
        1.1812485 , -0.5369933 ,  0.33873245, -0.6791787 , -0.39108932,
        0.7524725 , -0.7249127 ,  1.1307231 , -0.403555  , -0.67286634,
        0.6812588 ,  0.8270057 ,  0.4072227 ,  0.70938474,  0.6869897 ,
        0.5271738 , -0.551509  ,  1.2135739 , -0.40905064,  0.4513407 ,
       -0.68943983, -0.78064287, -0.6231746 , -1.0032183 , -0.47169888,
       -0.5090563 ,  0.22211136, -0.5008294 ,  0.3605994 , -0.43391448,
        0.9834253 ,  1.2143402 ,  0.68237436,  0.89830786, -0.20900115,
       -0.80061245, -0.52668315,  0.01541082, -1.0331119 , -0.8014963 ,
       -0.67826307,  0.6085407 ,  0.54352933, -0.5866564 ,  0.3884036 ,
       -0.7649342 ,  1.0132757 ,  1.2312942 ,  0.5563263 , -0.89606506,
       -1.0148504 , -0.4744523 , -0.557762  ,  0.48204076, -0.12901103,
        0.9992159 , -0.7765384 ,  0.78441346,  0.76981026,  0.8862904 ,
       -0.66200113,  0.7459139 ,  0.47447556, -0.8787795 ,  0.8152437 ,
       -0.58039427, -0.98675233,  0.48451498, -0.65141666], dtype=float32), array([10.093636 ,  4.725815 ,  7.617327 ,  9.298955 ,  8.640725 ,
        6.3452005, 18.24301  ,  4.222957 ,  9.796892 , 11.109096 ,
       12.014079 , 16.696592 , 10.309561 , 13.910951 ,  6.8251667,
        6.456025 ,  6.800906 ,  7.017531 , 14.434712 , 15.631297 ,
        7.825389 ,  9.46495  , 10.243639 ,  8.445923 ,  5.2679873,
        6.1291475, 15.098498 , 13.513434 , 10.139312 , 12.478902 ,
       12.174021 ,  2.9024546, 10.25461  , 14.955124 ,  4.056951 ,
        3.0278864,  6.4206476, 10.555576 ,  9.746022 ,  8.899972 ,
       16.100655 , 10.00317  , 15.219426 , 11.614013 ,  7.743579 ,
       10.287373 ,  5.835359 ,  6.805827 ,  7.2434955, 11.622432 ,
        8.906012 ,  4.116645 ,  8.539078 ,  6.585028 ,  8.002995 ,
        5.8493085, 13.33835  , 19.552855 , 10.463289 ,  7.988316 ,
       10.697173 ,  8.437618 ,  9.302525 ,  6.800994 , 27.015755 ,
       10.395016 , 13.670049 , 13.447548 , 11.520071 ,  6.708654 ,
       10.38462  ,  6.7989583, 12.180548 ,  5.7103343,  9.334788 ,
        9.352368 , 16.2071   ,  8.314201 , 12.240833 ,  7.226089 ,
       11.929937 ,  6.822628 ,  6.1687512,  8.880937 , 17.319649 ,
        7.965804 , 10.029059 ,  4.8948298, 16.58627  ,  7.677868 ,
        9.799148 , 11.52108  , 13.474139 ,  8.408796 ,  6.0620546,
       15.685731 ,  5.333128 ,  4.5189056,  4.8839083, 14.197622 ,
       18.760372 ,  3.9833465,  7.4544897, 15.643414 ,  5.502896 ,
        9.482288 ,  8.026605 ,  9.310636 ,  7.0644946, 14.919361 ,
       10.771628 ,  9.422902 , 13.136421 ,  9.710694 , 13.10284  ,
        7.930961 ,  8.139199 ,  6.604038 ,  9.410552 ,  8.047962 ,
       23.882374 ,  5.3475785,  7.5465775,  7.1902957, 11.5289755,
        4.2415113, 11.002751 ,  9.013926 ,  9.509144 , 10.146677 ,
        4.0937214, 11.871522 ,  8.917574 , 12.5019245, 10.465209 ,
        3.321856 ,  9.163935 , 11.24754  ,  7.8644695,  7.297884 ,
        9.031731 ,  7.490015 , 15.865399 ,  5.1699715,  4.7760363,
        5.2829313, 11.421822 ,  7.279635 ,  7.846628 ,  5.1638055,
        9.318067 ,  9.500334 , 14.795875 , 14.2599   , 12.31524  ,
        4.198182 ,  0.7893667,  7.730283 ,  6.853552 ,  5.8133373,
        8.25759  , 10.602628 ,  7.084547 ,  9.483402 ,  8.351665 ,
        7.7217045,  9.827356 , 14.170439 ,  2.9658518, 17.291323 ,
       13.6474085,  8.136412 , 15.920228 , 12.952017 ,  4.5253377,
        7.463994 , 10.346358 , 12.642897 , 19.15827  ,  8.8711   ,
        8.317242 , 10.892815 , 10.287692 , 15.963358 , 13.866701 ,
        5.4935083, 12.250117 , 11.468176 ,  5.4761667, 17.926735 ,
        9.944107 ,  6.0213175, 11.430176 , 10.196284 ,  7.735909 ,
        8.8778925,  4.443848 ,  8.672782 ,  9.170312 ,  9.052009 ,
        5.2627077,  5.40143  , 13.669779 , 10.531266 ,  4.7051406,
       16.325945 , 12.222138 ,  8.424087 ,  6.840626 , 15.0223465,
       10.205281 , 10.221995 ,  9.961953 ,  5.622782 , 11.797683 ,
        6.274805 ,  5.4535947, 18.003736 ,  6.772799 ,  9.8063   ,
        6.0742292,  9.350946 ,  6.9573   ,  4.257545 ,  9.878294 ,
       12.893548 , 14.296998 , 14.015777 , 12.2851095,  8.313173 ,
        7.5691257, 10.226875 ,  6.758504 ,  6.1482973,  6.759797 ,
        2.9147274,  4.1483555,  6.2666306, 21.387024 , 10.439735 ,
        4.709359 , 12.308471 , 11.639746 ,  6.9978085, 11.810289 ,
        8.896912 ,  2.691119 ,  7.3551645, 13.752629 ,  4.6928096,
       12.4222975,  9.297954 ,  8.434857 , 13.243687 , 11.372169 ,
        5.446478 ,  7.5658293,  3.8241518,  4.7756767,  9.012055 ,
        5.9351134, 11.99966  ,  9.660017 ,  6.543068 , 10.358917 ,
       10.820368 ,  8.681973 ,  6.461519 ,  4.8975096, 11.114106 ,
        6.514894 , 19.183159 ,  9.378194 , 13.843345 , 15.333579 ,
       16.86313  , 13.882904 , 12.030234 ,  5.0714407, 12.021887 ,
        6.240675 ,  7.7665353, 30.026508 , 17.213137 ,  7.900848 ,
        6.001837 , 18.156084 ,  9.190058 , 11.919121 ,  3.779337 ,
        7.5967445,  4.6373744, 17.86565  ,  2.541075 ,  4.968047 ,
       10.22174  , 11.16604  ,  6.7732716,  6.862656 ,  8.340574 ,
        2.6375027, 10.6022005, 10.942601 ,  7.09662  ,  9.905263 ,
       14.784869 , 15.324377 ,  3.9625971, 11.112487 , 12.508699 ,
        4.4234576,  9.065774 , 12.151105 ,  2.4992151,  8.532038 ,
       18.594954 , 11.876959 ,  4.2755384, 10.16656  ,  8.264047 ,
        8.891524 , 10.975885 , 17.486444 ,  4.3731065,  7.4871764,
        7.7134123,  9.792417 ,  5.5954785, 10.583792 , 15.002974 ,
       12.046569 ,  5.3397098, 13.76149  ,  5.0213423,  7.015765 ,
        7.0258293,  9.666543 , 11.190546 , 13.412966 ,  7.408719 ,
        5.177752 ,  4.342277 ,  9.576319 , 12.215872 ,  4.502901 ,
       19.788715 , 15.723788 ,  8.208956 , 11.262672 ,  4.8653855,
       10.206916 ,  8.113076 ,  9.752164 ,  8.928588 ,  9.847864 ,
       10.858795 ,  2.0173097,  5.1851935,  6.7972884,  9.7372   ,
        7.671152 ,  9.447702 ,  9.649983 ,  9.113427 ,  7.483012 ,
        7.2070885, 10.788096 ,  5.0562387,  8.933473 ,  7.671077 ,
       14.987818 , 15.580552 ,  8.688266 , 12.892186 ,  5.918339 ,
        5.9499955,  6.668898 , 12.998455 , 14.323573 , 11.712922 ,
       13.787131 , 15.095566 ,  8.23998  , 10.825963 ], dtype=float32), array([-9.42268595e-03, -1.48760285e-02, -8.99016950e-03,  1.59536794e-05,
        1.94779271e-03, -3.83327110e-03, -3.41521879e-03, -1.13689341e-02,
       -1.08186053e-02, -2.32885170e-04, -8.27471912e-03, -3.02970340e-03,
       -1.04138348e-02, -9.01838765e-03, -2.04100776e-02, -4.77138627e-03,
        2.73511745e-03, -6.10737363e-03, -2.24903016e-03, -3.84125416e-03,
       -6.97222492e-03, -1.47483377e-02, -7.44794845e-04,  1.88932032e-03,
       -1.74657023e-03, -3.20989043e-02, -3.05657759e-02, -6.28398592e-03,
        4.56455280e-04, -8.36615916e-03, -1.51979448e-02, -9.02743451e-03,
       -8.66850931e-03, -3.00086942e-03, -8.38772487e-03, -9.34254751e-03,
       -7.84087926e-03, -3.09663429e-03, -1.01955784e-02, -8.19125585e-03,
       -2.54061236e-03, -8.27057846e-03, -6.35466678e-03, -1.43014807e-02,
       -1.10704405e-03, -2.81962770e-04, -1.49523960e-02, -3.61360679e-03,
       -6.61739660e-03, -8.17487761e-03, -4.64658951e-03, -4.72411178e-02,
       -1.66719989e-03, -4.35993029e-03, -4.22483822e-03, -1.22604184e-02,
       -8.98066629e-03, -1.14930337e-02, -2.05455860e-03, -8.16955697e-03,
       -1.05303051e-02, -4.52305079e-02,  7.14056194e-04, -9.01687797e-03,
       -1.83486361e-02, -1.27326092e-02, -2.84175831e-03, -3.67670390e-03,
       -9.33993515e-03,  2.36274372e-03, -7.37107941e-04,  3.48418439e-03,
       -1.04582459e-02, -2.61602295e-03, -1.51229417e-02, -1.64988847e-03,
       -1.00845443e-02, -3.98092763e-03, -1.51046915e-02, -1.62752625e-02,
       -3.53408302e-03, -1.81331113e-02, -1.42357023e-02, -5.48261544e-03,
       -4.81961714e-03, -8.24061036e-03, -5.77381849e-02, -9.69666708e-03,
       -2.09759478e-03, -1.19133564e-02, -9.89694707e-03, -2.58227368e-03,
       -1.97737431e-03, -5.54291392e-03, -3.28599475e-02, -9.23257414e-03,
       -1.24622034e-02, -3.34551670e-02, -9.82291996e-03, -1.17420098e-02,
       -6.53692149e-03, -6.29957719e-03,  4.20029915e-04, -4.09997674e-03,
       -9.08435974e-03, -7.06822006e-03, -9.92365833e-03, -1.50616737e-02,
       -2.50835940e-02,  2.54056463e-03, -8.59642029e-03, -1.82417668e-02,
       -1.58565976e-02, -1.09735911e-03, -7.80802174e-03, -4.61992137e-02,
       -8.25820118e-03, -5.05486561e-04, -1.07475072e-02, -1.22844083e-02,
        1.81463594e-03, -1.61599480e-02, -6.04076358e-03, -1.83337857e-03,
       -3.88357206e-03, -9.16831754e-03, -4.97411191e-03, -3.95021550e-02,
       -7.60606118e-03, -1.72227882e-02, -1.96131645e-03, -1.71343945e-02,
       -5.92320133e-03,  3.07198521e-03, -1.31061226e-02, -3.26078967e-03,
       -5.60361473e-03, -5.78857446e-03, -8.05534050e-03, -1.41483648e-02,
       -6.16813730e-03, -5.58384322e-03, -5.63577330e-03, -1.21222539e-02,
       -2.04170425e-03, -3.24769947e-03, -1.35048870e-02, -4.93212193e-02,
       -3.88770830e-03, -1.15206148e-02, -8.82535358e-04,  8.55740684e-04,
       -1.83247647e-03, -1.77921343e-03, -1.12454807e-02, -4.95453225e-03,
       -1.66470297e-02, -2.14494057e-02, -5.39700221e-03, -3.93609982e-03,
       -3.09893321e-02, -2.32120156e-02, -4.36068065e-02, -2.94248061e-03,
       -9.78945196e-03, -1.14025958e-02,  7.73884996e-04, -4.94562462e-03,
       -4.42771614e-03, -3.33601562e-03, -1.75992139e-02, -8.67871195e-03,
       -1.53287239e-02, -3.86266178e-03, -4.21102019e-03, -1.00073952e-03,
       -2.13346514e-03, -1.05507858e-02, -3.09025240e-03, -2.06541009e-02,
       -2.08051759e-03, -4.68013575e-03, -6.27710903e-03, -9.70645063e-03,
       -8.90442263e-03, -6.16279580e-02, -8.48500337e-03, -8.44996143e-03,
       -5.79310814e-03, -4.52269129e-02, -1.36518497e-02, -6.69012871e-03,
       -4.66693472e-03, -8.42301361e-03, -4.35455889e-03, -8.73601437e-03,
       -3.06506306e-02, -5.08253984e-02, -8.06710403e-03, -3.50779679e-04,
        1.04220398e-03, -1.28973238e-02, -5.07228859e-02,  2.70233164e-03,
       -4.34540724e-03, -6.63802586e-03, -4.81505282e-02, -1.22012515e-02,
       -8.20075907e-03, -4.55846302e-02, -1.10876681e-02,  2.84119789e-03,
       -4.68351645e-03, -1.80289373e-02, -8.96938331e-03, -3.65089364e-02,
       -1.93819217e-03, -5.15009463e-03, -2.75211106e-03, -5.61812753e-03,
       -1.37600349e-02, -4.57466766e-03, -4.15432127e-03, -4.35349606e-02,
       -5.71007561e-03, -1.17637636e-02, -1.07207056e-02, -1.51342554e-02,
       -8.08049552e-03, -4.74556908e-03, -2.56625339e-02, -2.92651984e-03,
       -1.02865212e-02, -1.92082711e-02, -9.29608184e-04, -1.53921749e-02,
       -1.54045515e-03, -3.36802960e-03, -1.12610264e-02, -4.66634817e-02,
       -3.38919535e-02, -7.76891550e-03, -1.00089414e-02, -1.14613893e-02,
       -5.07092997e-02,  1.97102898e-03, -7.62649206e-03, -4.91482839e-02,
       -5.46069304e-03, -1.26057898e-03, -1.04199247e-02, -1.51183503e-02,
       -2.96446914e-03, -5.38573489e-02, -1.64764877e-02, -1.03617192e-03,
       -1.49330767e-02, -7.92334881e-03, -3.87653545e-03, -9.69402399e-03,
       -5.06486110e-02, -1.14028845e-02, -6.50859717e-03, -1.80219905e-03,
       -6.83547929e-03, -6.87886076e-03, -4.76555899e-03, -1.25969807e-02,
       -3.31597519e-03, -8.79422855e-03, -4.32311706e-02, -2.23906133e-02,
       -7.53281824e-03, -3.41700710e-04, -1.23003509e-03, -1.21375849e-03,
       -8.18986329e-04, -1.97747946e-02, -1.12479674e-02, -1.91345392e-03,
       -5.85249551e-02, -1.69817414e-02, -9.61188599e-03, -3.34288627e-02,
       -5.01394719e-02, -1.96621148e-03, -2.18072850e-02, -9.85793024e-03,
       -3.08614178e-03, -8.19649454e-03,  2.20100000e-03, -1.76783197e-03,
       -2.70951749e-03, -1.04554771e-02,  3.10752308e-03, -8.71023256e-03,
        3.62444716e-03, -4.66149440e-03, -1.07457431e-03, -1.10421060e-02,
       -1.58947613e-02, -1.07372887e-02,  1.61512604e-03,  2.15469766e-03,
       -5.98995620e-03,  2.80468143e-03, -1.02291731e-02, -2.35383329e-03,
       -1.37005923e-02, -1.52677912e-02, -5.43390354e-03, -3.14898454e-02,
       -1.10427188e-02,  3.42289452e-04, -2.34965440e-02, -1.08350720e-02,
       -6.64872257e-03, -1.81271620e-02, -1.57044240e-04, -2.44477913e-02,
       -4.19119932e-03, -9.20630340e-03, -1.08609442e-02, -5.46556330e-05,
       -3.24957329e-03, -5.12547325e-04, -8.74341466e-03,  2.32059835e-03,
        2.11688178e-03, -5.01290709e-03, -3.59029952e-03, -8.23400635e-03,
       -4.13395949e-02, -1.01519246e-02, -9.86351538e-03, -4.84989258e-03,
       -2.27923947e-03,  3.34237702e-03, -1.02461250e-02, -8.58577434e-03,
       -4.28399481e-02, -4.27679671e-03, -7.46290805e-03, -6.06315862e-03,
       -1.28247775e-03, -9.11040325e-03,  2.21473491e-03, -1.11280354e-02,
       -1.40056489e-02, -9.60920379e-03, -1.11994762e-02, -8.83108529e-04,
       -5.68329263e-03, -5.02689509e-03, -8.15009233e-03, -1.30131026e-03,
       -9.29168949e-04, -2.89459643e-03,  2.69821170e-03, -4.17177677e-02,
        3.32156150e-03, -1.48238977e-02, -1.42284976e-02, -5.97254466e-03,
       -2.91508734e-02, -9.51389316e-03, -4.23522033e-02,  1.13338069e-03,
       -7.67899258e-03, -7.15970527e-03, -5.58192050e-03, -9.95035563e-03,
       -1.60055980e-02, -1.31327682e-03, -7.98554718e-03, -6.02588756e-03,
       -1.00195641e-02, -1.26823755e-02, -8.42701551e-03, -2.38402723e-03,
       -2.52724309e-02, -4.47829254e-03, -4.27238131e-03, -1.62090082e-02],
      dtype=float32), array([ 1.0165431 ,  0.72392154,  1.1158653 ,  0.7653121 ,  0.809915  ,
       -0.62829185, -0.56025505,  0.42982963, -0.7731103 , -0.7133296 ,
        0.8833127 , -0.54549587, -0.681454  ,  1.1195525 ,  1.1414309 ,
        0.8398994 ,  0.7981539 ,  0.40408093, -0.8804039 , -0.6140511 ,
        0.8654193 ,  1.1106513 , -0.9704705 ,  0.81563264, -0.3822295 ,
        0.24631457, -0.93604   , -1.137864  ,  0.47144207,  0.968267  ,
       -0.6408931 ,  0.85117173, -0.8959693 , -0.41603997, -0.7329649 ,
        0.8520248 , -0.48868927, -0.6505477 ,  1.1160163 , -0.09199584,
       -0.7547851 , -0.4473353 , -0.5366019 , -0.5429391 ,  0.57627827,
        0.7559719 , -0.6676946 , -0.422992  ,  0.00853092, -0.2517754 ,
       -0.57274085, -1.1224211 ,  0.5862756 , -0.59255654, -0.5430437 ,
       -0.27917486,  0.90919536,  1.0081533 , -0.4024302 , -0.7904043 ,
       -0.7220132 , -0.39582342,  0.43740165, -0.7812206 ,  0.9294195 ,
        0.819593  , -0.8049425 , -0.46298695,  0.4078841 ,  0.6540717 ,
       -0.8289349 ,  0.31916404, -0.41634703, -0.5616031 , -0.74700916,
        0.6193796 , -1.2757624 ,  0.45526996, -0.7324658 ,  0.963979  ,
       -0.46459928, -0.77034706,  0.6075318 , -0.78536093,  0.4272561 ,
        1.0596882 , -0.6319226 ,  0.64280957, -0.6782914 ,  0.6776893 ,
       -0.65336865,  0.48269194,  0.53586227, -0.6794059 , -0.1351219 ,
       -1.0212531 , -0.8725067 , -0.64738315,  0.8112004 ,  1.087538  ,
       -0.7704337 , -0.73507273,  0.4322568 , -0.6778178 ,  0.5558217 ,
       -0.92202914,  0.950056  ,  0.75705117, -0.39035964,  0.47783455,
       -0.628015  , -0.8140696 , -0.71310234, -0.87676346, -0.30001655,
        0.94529337, -0.48475453,  0.54996246, -0.724449  , -0.4349642 ,
        0.5918213 , -0.26207432, -0.83075935, -1.4228711 ,  0.5858014 ,
        0.96559966, -0.62957126, -0.5581681 , -0.94413114,  0.9239938 ,
        0.67599154,  0.3542023 , -0.71736544,  0.13519426,  0.79598784,
       -0.36297596,  0.55376565, -0.75522673,  1.3105091 , -0.61336815,
       -0.7611118 ,  0.44678086, -0.6232417 , -0.65738493, -0.6841865 ,
       -0.5425674 ,  0.34229898, -0.6300455 , -0.36203578,  0.51306236,
        0.5785007 ,  0.79538244,  0.4988042 ,  0.8255375 ,  0.57739145,
       -1.1224482 ,  0.06584992, -0.6383884 , -0.5049958 , -0.83020663,
       -0.5880371 ,  1.4079152 , -1.165066  , -0.531508  , -1.1635745 ,
        1.3987375 ,  0.64805615, -0.72404414,  0.03506102,  0.35909247,
       -0.65796024,  1.1912483 ,  1.070138  , -0.419006  , -0.8614435 ,
        1.0341095 , -0.76375973,  1.2991126 ,  0.9321498 ,  0.84101117,
       -0.36169562, -0.9126736 , -0.5410593 , -0.63280064,  1.1327387 ,
       -0.5879453 ,  0.75457644,  1.1166134 , -0.6572693 , -1.180926  ,
       -1.0265119 , -0.39555624, -0.9400246 , -0.6271811 , -0.38635272,
        0.93017757,  1.0641524 , -0.12005387, -0.66181135,  0.72478986,
        0.65621245,  1.1096028 , -0.72457063,  0.3495119 , -0.47499755,
       -0.23514101, -0.99327743,  0.37977532,  1.324891  , -0.733123  ,
       -0.54534835,  0.19527927, -0.45229593,  0.74033743,  0.8576518 ,
        1.4331698 , -0.3273531 , -0.54428506, -0.650985  , -0.78060704,
       -0.83628064, -0.8175195 ,  0.5850529 , -0.6450667 , -0.5930854 ,
       -0.48755762,  0.8683399 ,  0.7896586 ,  1.2245668 ,  1.0722506 ,
       -0.7333142 ,  0.46824542,  1.3179247 ,  0.9073513 , -0.9225226 ,
        1.0479909 , -0.49707034, -0.5849481 ,  1.0939193 , -0.38646302,
        0.73224145, -0.9279073 ,  0.9310792 , -0.8067882 , -0.76761067,
        0.6001234 ,  0.6934783 , -0.9829965 , -0.615508  , -0.4841164 ,
        0.8622816 , -0.43372905,  0.7041477 , -0.70026475,  0.87318915,
       -1.1167936 ,  1.1879008 ,  0.47611418,  0.51870865,  0.65470505,
        0.91374505,  0.43191662, -0.6339025 , -0.9426617 , -0.82208157,
       -0.6173886 , -0.15839177, -0.6317987 , -0.61321276,  0.8152535 ,
        0.03599795,  0.43939498,  0.87821317,  0.6003046 , -0.88490516,
       -0.73817056,  0.7140186 , -0.83371764, -0.30998316, -0.7334557 ,
        0.19669074,  0.6223346 ,  0.8884572 , -0.9018218 , -0.7457522 ,
       -0.80469775,  0.8111939 ,  0.49888745,  0.36087263,  0.4387958 ,
        0.73606807,  0.71888894, -0.70438933,  1.0804458 ,  0.39771092,
        0.55383784,  0.5558176 , -0.4450032 , -0.7804126 ,  0.8547782 ,
       -0.76529837, -0.92946786,  0.4293817 ,  0.71893436, -0.34080306,
        0.37667435, -0.4912372 , -0.5209043 , -0.59756947, -0.78637224,
       -0.5476925 , -0.5477311 ,  0.5908757 ,  0.5960278 ,  0.97132117,
       -1.0329039 , -0.633526  , -1.10434   , -0.99568427, -0.7414832 ,
        0.45612463,  0.79952097,  1.1319963 ,  0.7072183 , -0.5221608 ,
       -0.7302751 ,  1.0965785 ,  0.6531458 ,  0.43978155, -0.37438616,
       -0.36235073,  0.79760057, -1.1144253 , -0.31383795,  1.1733873 ,
       -0.7839688 , -0.726029  ,  0.36381167, -1.1358634 ,  1.1489745 ,
        1.2537735 , -0.8373122 ,  0.9183217 , -0.8609766 ,  0.52640694,
        0.74512154,  0.23610862,  0.5795341 , -0.55694604,  0.8951347 ,
        1.0005407 , -1.2049726 ,  0.52832836, -1.0301629 ,  1.3159584 ,
       -0.8347996 ,  0.7799905 , -0.6241051 ,  0.6455912 , -0.4050713 ,
        0.45580345,  0.6316005 , -0.8680194 , -0.82244796, -0.90138465,
        0.79678565, -0.73832065,  0.54339075,  1.5197716 ,  0.39729384,
        0.58225185, -0.46793568,  0.8360996 , -0.44796908, -0.97337157,
       -0.66637605,  0.8268374 , -0.839961  ,  0.9834941 , -0.43319157,
        0.5824994 ,  0.30133456, -1.0669017 ,  0.955381  ], dtype=float32), array([10.289482 , 10.908272 , 16.77935  , 11.443134 , 10.445243 ,
        7.76748  , 13.103848 ,  7.838276 ,  7.6393757,  9.692662 ,
       10.839285 ,  8.213287 , 11.981551 , 18.43902  , 11.876716 ,
        6.7228737, 19.801828 ,  5.253409 ,  9.828268 , 11.413687 ,
       12.320183 , 13.492459 , 21.611408 , 15.799488 , 10.858305 ,
        3.2201283,  7.5772495, 19.832497 ,  6.5707545, 12.991086 ,
        5.4157257,  8.784309 ,  9.071698 , 11.757347 ,  9.603258 ,
        8.774639 ,  5.303157 ,  5.382178 , 15.136951 ,  8.623569 ,
       14.542195 ,  4.2433524, 11.530943 ,  7.7389636,  7.4909196,
        9.752502 ,  7.3571362,  6.909665 ,  3.1093524,  6.501135 ,
        9.753059 , 14.121678 ,  7.7228985, 11.59805  , 11.629751 ,
        4.959051 , 11.749619 ,  9.257474 ,  5.7941484,  7.113115 ,
        7.2724285,  7.629284 ,  8.498085 ,  8.273796 ,  5.392464 ,
       11.050883 , 10.000567 ,  8.46025  ,  6.636817 ,  9.6074095,
       12.904322 ,  8.932714 ,  6.582675 , 15.460284 ,  8.464738 ,
        7.8217206, 18.09057  ,  5.5564365,  5.158971 ,  9.030948 ,
       11.683519 , 15.343746 ,  6.0341887, 10.887139 ,  8.2392645,
       14.743151 , 10.147809 ,  9.021893 , 12.19545  ,  6.6872573,
        8.599765 ,  5.380442 ,  6.8597736,  6.8383627,  6.547231 ,
       13.2591   ,  8.725541 ,  7.652909 ,  8.817243 , 18.562433 ,
       11.493021 , 10.735734 ,  6.4137597, 10.169194 , 10.006894 ,
        8.16493  , 14.06806  ,  3.358652 ,  4.483352 ,  9.383301 ,
        7.821252 ,  7.545436 , 10.7451725, 11.03803  ,  4.058392 ,
        2.4435706,  4.857054 ,  6.050015 ,  5.0389795,  7.152134 ,
        5.9840326,  4.1698713, 11.006429 , 21.207079 ,  9.451136 ,
        9.532178 ,  7.6616178,  6.6155877, 10.824985 ,  7.188155 ,
        7.866185 ,  4.8255763,  4.7451563,  7.6398115,  4.4620895,
        8.927383 ,  8.6551285, 11.678154 , 17.224829 ,  7.8734746,
        8.891118 ,  4.2044573,  6.898408 ,  5.9319954,  6.8936324,
        9.954812 ,  4.3837843,  3.6426625,  4.572351 ,  7.3087   ,
        8.742311 , 13.684208 ,  8.6988325,  7.9387727,  6.012496 ,
       24.385761 ,  2.0027032,  4.9652014,  9.866361 , 11.370219 ,
       11.277909 , 15.359831 , 10.835348 ,  9.1541395, 12.375689 ,
       18.624092 , 11.465757 ,  6.52382  ,  2.3750625,  5.605412 ,
        7.7412343, 17.67362  ,  5.2281055,  6.353071 , 13.980155 ,
       10.3083725, 11.437313 , 14.875922 , 13.93533  ,  3.3364968,
        6.7254143, 10.84517  ,  8.720564 ,  4.9731183, 13.570395 ,
        3.4225805,  7.0429745, 13.872444 ,  9.736449 ,  8.349638 ,
       10.130936 ,  7.4299955, 12.54971  ,  4.612747 ,  9.119187 ,
       10.558015 ,  2.934399 ,  1.3368652,  6.0965943, 12.412392 ,
        9.70891  , 12.101709 ,  3.494158 ,  5.8835425,  9.03343  ,
        5.5124993,  7.222317 ,  4.283065 , 19.32955  ,  5.891614 ,
        7.0497937,  9.650407 ,  7.5335345,  3.3412373,  6.0617185,
        5.2257943,  9.287357 , 12.597468 , 11.302063 , 11.222944 ,
       11.129014 ,  9.092904 ,  9.006348 ,  7.1232452, 11.050508 ,
        5.441048 , 10.814687 ,  4.646303 , 16.586786 , 11.489183 ,
        9.831411 ,  6.7770658, 15.618943 ,  6.429815 , 13.820464 ,
        9.840618 ,  7.4095416, 13.137996 , 14.384495 ,  6.166518 ,
        1.9806967, 11.393851 , 12.318829 ,  7.243908 ,  5.7945423,
        7.0241237,  6.181674 , 10.069426 ,  7.1728806,  7.35321  ,
        9.266098 ,  5.4031205,  7.6319056, 25.878494 ,  5.2281384,
       14.49221  , 11.924377 ,  2.4284613,  5.456802 ,  8.885872 ,
        4.549474 ,  4.868931 , 11.038337 , 12.7917   , 13.660918 ,
       13.953669 ,  2.3673308, 12.824584 ,  7.679686 ,  9.566895 ,
       27.044914 ,  2.3049738, 13.994451 , 12.296818 , 14.627107 ,
       13.451325 , 10.357857 ,  4.838912 ,  7.017317 , 15.819851 ,
        7.770122 ,  8.923178 , 11.36348  , 19.180882 ,  3.4009345,
       11.213869 ,  6.472902 ,  3.2181034,  6.9387527,  4.901037 ,
       12.811119 ,  8.586317 , 10.690833 ,  9.82993  ,  7.57921  ,
        5.3201184,  9.604794 ,  5.8656774, 13.358154 ,  9.182237 ,
        7.8843007, 10.279341 ,  9.669651 , 10.19826  ,  3.704002 ,
        7.495102 ,  6.607149 ,  7.6819744,  7.7905383,  9.593051 ,
        7.65792  ,  7.7824597,  7.0966372,  8.285989 ,  7.2891254,
       17.100218 , 10.419009 , 13.775972 , 16.500843 ,  4.912565 ,
        6.3771706,  9.644428 , 11.772917 ,  8.374438 ,  9.355768 ,
       19.506275 , 15.431078 ,  8.326525 ,  8.769114 , 13.498621 ,
        9.008921 ,  5.1844053, 13.02915  ,  4.419926 , 14.587813 ,
       10.991751 ,  8.200476 ,  7.2666745, 17.068516 , 17.764389 ,
        4.5942097, 10.909634 ,  8.827063 , 14.521548 ,  8.226206 ,
       10.214337 ,  7.536214 , 13.7839   , 10.279644 , 11.04512  ,
       10.727521 , 17.585978 ,  6.160777 , 10.6289   , 19.405697 ,
       13.976049 ,  8.89988  , 11.026333 , 13.739792 ,  3.1965125,
        7.824554 ,  9.044691 , 15.015073 , 11.698151 , 15.473422 ,
       11.325386 ,  6.7196608,  6.5296116, 20.75325  ,  5.3964167,
       10.07746  ,  5.87991  ,  8.203309 , 16.711031 , 14.555169 ,
        9.163082 , 10.936666 , 11.550357 , 13.5031395,  8.328008 ,
        2.4281054,  3.121293 , 13.606451 ,  7.6368136], dtype=float32), array([[[[-0.03780276,  0.02563017, -0.00659388, ..., -0.03275755,
          -0.01454865, -0.02329278],
         [ 0.02138167,  0.03586375,  0.02795894, ..., -0.03351294,
           0.02344888,  0.01375864],
         [-0.02750286, -0.03433555,  0.01413615, ..., -0.05483347,
           0.05652162,  0.03047255],
         ...,
         [ 0.01673306,  0.01073448, -0.02510474, ..., -0.03182464,
           0.00320653, -0.03665301],
         [ 0.00454762, -0.03754226, -0.01868637, ...,  0.04786241,
          -0.01548551,  0.05552502],
         [ 0.03635993,  0.00070324,  0.03298835, ...,  0.0038222 ,
           0.00672913,  0.04408969]]]], dtype=float32), array([-3.57544459e-02, -9.03157145e-03, -1.94031384e-03, -2.15018336e-02,
       -1.30874163e-03, -2.45500891e-03, -7.11567514e-03, -6.50195172e-04,
       -4.93274741e-02, -7.15736113e-03, -9.08911880e-03, -8.77564494e-03,
       -4.49919468e-03, -6.38456317e-03, -4.71755816e-03, -2.21387204e-02,
       -6.62031583e-03, -5.28626936e-03, -5.80638163e-02, -1.10948309e-02,
       -6.40308857e-03, -1.00602750e-02, -2.47700606e-02, -2.20025089e-02,
       -3.60484701e-03, -9.38243419e-03,  1.00132986e-03, -7.21930852e-03,
       -5.68290753e-03, -9.76975448e-03, -2.58065946e-02, -5.12245717e-03,
       -6.45484449e-03, -3.67322862e-02, -4.19074250e-03, -3.48097943e-02,
       -8.23261961e-03, -5.96139464e-04, -9.26615950e-03, -2.53338255e-02,
       -5.32539142e-03, -3.15765128e-03, -4.99799987e-03, -7.03790691e-03,
       -1.66343560e-03, -2.56972201e-03, -1.28154345e-02, -9.40444414e-03,
       -4.38224301e-02, -3.21812462e-03, -7.23719504e-03, -1.96493842e-04,
       -1.08657114e-03, -6.44668797e-03, -4.50910884e-04, -2.76717567e-03,
       -8.93046707e-03, -8.16647708e-03, -5.46222180e-02, -9.40610096e-03,
       -2.64863670e-02, -4.33709193e-03, -1.04074180e-02, -4.53040935e-03,
       -1.09021328e-02, -7.65113998e-03, -1.24862008e-02, -6.76639229e-02,
       -6.17218995e-03, -2.04916745e-02, -2.77440678e-02, -6.72922004e-03,
       -6.36076380e-04, -6.41902350e-03, -1.72909361e-03, -1.25189582e-02,
       -3.58794071e-03, -1.64647063e-03, -1.54878357e-02, -8.78922269e-03,
       -6.45439280e-03, -1.60496635e-03, -6.11902622e-04, -9.60035529e-03,
       -1.16209155e-02, -6.76176418e-03, -1.70627027e-06, -9.60531551e-03,
       -4.58680699e-03, -3.31495814e-02, -1.89856603e-03, -4.66329465e-03,
       -5.40407933e-03, -8.46726168e-03, -6.52221171e-03, -2.23315675e-02,
       -1.67802977e-03, -1.13839731e-02, -4.22685771e-05,  1.94664206e-03,
       -1.98577368e-03, -1.76937450e-02, -2.35865973e-02, -4.52222973e-02,
       -9.86288302e-03, -7.23824976e-03, -1.68199957e-04, -5.34900057e-04,
       -1.30848866e-02, -1.41810980e-02, -8.43599811e-03, -7.01294234e-03,
       -2.61996668e-02, -2.39740442e-02, -2.31680763e-03, -1.63061153e-02,
       -7.10423803e-03, -7.37832719e-03, -5.77212572e-02, -1.50811742e-03,
       -1.35517521e-02, -1.13486378e-02, -2.03602179e-03, -5.27504459e-03,
       -3.03626596e-03, -1.36321643e-02, -1.29080620e-02, -1.33673055e-03,
       -3.08174510e-02, -1.12903607e-03, -4.55163717e-02, -2.56212521e-03,
       -2.70675272e-02, -2.30355858e-04, -4.58411034e-03, -6.62685838e-03,
       -9.59914550e-03, -8.39786604e-03, -1.81814947e-03, -6.33534091e-03,
       -5.20482510e-02, -8.44025984e-03, -3.29045579e-02, -9.44949128e-03,
       -1.64414439e-02, -9.11222491e-03, -7.01165991e-03, -8.41076486e-04,
       -5.00333589e-03, -8.07661377e-03, -6.82430947e-03, -4.05248851e-02,
       -1.10515766e-02, -3.45145352e-03, -6.44963887e-03, -9.01552197e-03,
       -9.78262164e-03, -2.14533927e-03, -8.82917736e-03, -2.07898230e-03,
       -4.88311844e-03, -5.92738669e-03, -4.61036293e-03, -7.09868642e-03,
        1.32707553e-03, -6.44279271e-03, -4.32949513e-03,  4.22597583e-03,
       -6.54828793e-04, -9.81361978e-03, -9.47449915e-03, -7.41692120e-03,
       -1.48761773e-03, -7.20941275e-03, -4.20068449e-04, -2.75754090e-02,
       -1.89793063e-03, -1.07638966e-02, -7.16492767e-03, -1.86801050e-02,
       -1.65988524e-02, -2.68864818e-03, -6.55868975e-03, -4.19647358e-02,
       -9.33745597e-03,  1.21551671e-03, -4.89100523e-04, -5.71262389e-02,
       -2.00126716e-03, -8.84640403e-03, -9.93654877e-03, -4.31595091e-03,
       -4.97881230e-03, -6.80440757e-03, -1.02926427e-02, -6.71626907e-03,
       -2.08839606e-02, -5.01983128e-02, -1.93455182e-02, -2.96608265e-03,
       -8.29453394e-03, -4.77962755e-02, -1.05441557e-02, -9.78921913e-03,
       -4.57894951e-02, -5.29825175e-03, -1.81464981e-02, -7.25673186e-03,
       -2.66371109e-03, -1.58023611e-02, -1.74528942e-03, -1.12206256e-02,
       -7.50480546e-03, -2.02056672e-02, -7.98332877e-03, -2.14993991e-02,
       -9.35561862e-03, -1.01811299e-02, -3.65865836e-03, -5.99504681e-03,
       -3.39563414e-02, -1.29316635e-02, -8.17797240e-03, -3.47508956e-03,
       -1.16476665e-04, -1.19790370e-02, -7.73849245e-03, -4.73705493e-02,
       -5.85890422e-03, -6.48721773e-03, -3.91099229e-03, -3.53872613e-03,
       -4.83516604e-02, -6.27215579e-03, -4.65626419e-02,  1.07620528e-03,
       -4.93646739e-03, -4.86675724e-02, -8.17952678e-03, -6.30115019e-03,
       -1.47270504e-03, -2.10106443e-03, -1.48834158e-02, -1.85149466e-03,
       -3.56202968e-03, -2.63376953e-03, -3.94003885e-03, -9.70982760e-03,
       -1.02361636e-02, -1.65266041e-02, -8.12181365e-03, -1.25442725e-02,
       -6.24035299e-03, -7.88437482e-03, -3.91733600e-03, -3.74431089e-02,
       -2.79682875e-02, -4.92919236e-02, -6.74081687e-03, -2.41530454e-03,
       -1.20200049e-02, -5.61765395e-02, -5.69201587e-03, -4.53087239e-04,
        3.19698913e-04,  1.10273475e-04, -3.70691121e-02, -5.91283850e-02,
       -2.89891474e-02, -3.63183673e-03,  3.07179580e-04, -3.26232472e-03,
       -8.21051374e-03, -6.41422858e-03, -6.93904748e-03, -3.87920270e-04,
       -6.55434327e-03, -4.79781441e-03, -2.67572654e-03, -1.50113227e-03,
       -5.72266104e-03, -2.60634790e-03, -1.07908696e-02, -5.17499708e-02,
       -5.98923478e-04, -8.16423621e-04, -2.26528477e-03, -2.72587128e-03,
       -4.03761119e-02, -7.97150377e-03, -1.13983415e-02, -7.03234039e-03,
       -4.95643076e-03, -1.54118249e-02, -9.42298211e-03, -4.55600722e-03,
       -8.80141929e-03, -4.30163054e-04, -6.40463363e-03, -3.69741651e-03,
       -8.03331786e-04, -2.19377340e-03, -1.42336078e-02, -2.96097565e-02,
       -8.70536361e-03, -5.74456854e-03, -3.81378233e-02, -7.37943035e-03,
       -1.05913896e-02, -4.09751013e-02, -2.73387437e-03, -8.44421890e-03,
       -3.23682069e-03, -2.88961139e-02, -1.19230023e-03, -3.32964794e-03,
        9.08139686e-04, -3.57821286e-02,  2.68090400e-04, -4.53232147e-04],
      dtype=float32), array([-1.1651446 ,  1.4371291 , -1.5534186 ,  1.2902395 , -2.0990593 ,
       -1.6999042 , -1.1917529 , -1.5406231 , -0.10918743,  1.8579788 ,
        1.4209142 ,  1.6202086 , -2.0850673 , -2.129161  , -1.4933056 ,
       -1.7553867 , -2.1835501 , -1.0465358 , -1.7024939 ,  1.3979168 ,
       -1.2635554 ,  0.8114113 ,  2.0809002 , -3.0644004 ,  1.5607765 ,
        1.1985244 ,  1.5749849 ,  2.043819  ,  1.0734272 ,  1.9946039 ,
       -1.5147794 , -2.632814  , -1.3602117 , -1.9997077 , -2.911353  ,
       -1.5683237 ,  1.1868827 ,  1.4877943 , -2.912953  , -1.5327151 ,
       -1.5881865 ,  1.6568906 ,  1.1289088 , -1.4516736 ,  1.6098375 ,
        0.9735602 ,  1.7990981 , -1.7447063 , -2.5692153 , -1.160678  ,
        1.7087228 ,  0.85634214,  1.2572976 ,  1.4221387 ,  1.3176473 ,
       -1.6288474 ,  1.6343144 ,  1.9898806 , -0.01231575,  1.7949238 ,
       -1.8534337 , -0.86680937,  1.0053009 , -1.386492  ,  1.6755862 ,
        0.8713294 , -0.8125195 , -0.9420894 , -1.3484545 , -1.3609987 ,
       -1.8836083 ,  2.1868486 ,  1.4222608 ,  1.8881438 ,  1.784175  ,
        1.1195298 ,  0.9907069 , -2.4915445 , -1.2654256 ,  1.770474  ,
        1.9881884 , -1.7092894 , -1.9390911 ,  0.634738  ,  1.9606477 ,
        2.0368967 ,  0.83148366,  1.2411394 , -0.90303236, -1.2737515 ,
       -1.3076323 ,  1.4902414 ,  1.3358188 , -2.4641395 ,  2.2882688 ,
        1.5591394 ,  1.6282291 ,  0.8553513 ,  1.4889207 ,  1.2316074 ,
       -0.90949464, -2.3033276 , -1.3939905 ,  1.1755971 ,  1.8777716 ,
        1.665509  ,  1.2036735 ,  1.1237544 ,  1.7142055 ,  1.8603115 ,
       -2.2732882 ,  1.3167549 , -1.8569726 ,  0.52847403,  1.5293015 ,
       -1.5359558 , -1.4137686 ,  1.4258579 , -1.5447108 , -1.2683688 ,
       -1.5781994 , -1.7761948 ,  1.6166084 , -2.7126944 ,  1.4383761 ,
       -1.406911  , -1.2301531 ,  1.3190362 , -0.9795262 ,  1.660679  ,
       -0.95008135,  1.2187505 , -1.2749867 ,  1.4154378 , -1.6654873 ,
       -1.4490374 , -1.1960152 ,  1.6148186 , -0.8119869 ,  1.5567406 ,
       -1.8124335 ,  1.6531192 , -1.4372396 , -0.76888   ,  0.53816926,
        1.3810949 ,  2.0879524 ,  1.4823246 , -1.515588  ,  1.9569477 ,
        1.964029  , -1.0741023 , -1.0990318 ,  1.3020047 ,  1.8049588 ,
       -2.0181475 , -2.1684184 , -1.7744269 ,  1.1833981 , -1.5896566 ,
       -1.7666246 , -1.2978976 , -2.4176412 ,  1.3672887 ,  1.2842331 ,
        1.868931  , -0.87568814, -0.9095255 ,  1.200894  , -1.5036249 ,
       -1.7515192 , -1.7794664 ,  1.5134711 , -1.0043889 ,  1.4964916 ,
        2.5824175 , -2.143595  , -1.9154179 ,  1.6994514 ,  2.0961013 ,
       -2.647733  ,  1.2977192 , -1.9010254 , -0.88237524, -1.8565044 ,
        0.9914571 ,  1.5723174 , -1.3904961 ,  0.9065695 ,  2.1652732 ,
        2.3734083 ,  1.7890568 ,  1.1769338 , -2.1711512 ,  1.4921248 ,
       -1.0681176 , -2.1387744 , -1.1477469 ,  1.9157438 ,  1.3101139 ,
        1.7750612 , -2.4359052 , -1.6956586 , -1.6794249 , -1.9065669 ,
       -1.2879931 ,  1.1231089 , -1.1216542 ,  1.4854419 ,  1.9451188 ,
       -1.894955  ,  0.9027419 ,  1.5070148 , -1.6424149 ,  1.1189044 ,
        1.7643796 , -1.5184094 ,  1.9765472 ,  1.1943296 , -0.9386907 ,
       -1.3981884 , -0.9141132 ,  1.926807  ,  1.504147  ,  1.9151828 ,
       -0.79783213,  1.666588  , -1.0264007 ,  2.00279   , -0.84829056,
       -1.8108577 , -1.7637115 , -2.591256  , -1.8956797 , -2.3883257 ,
        1.1363486 , -1.4377259 , -1.5370227 , -2.3022199 ,  1.9120977 ,
        0.9920542 , -1.4262866 , -2.6544306 , -1.0447454 , -1.1890258 ,
       -1.6105591 , -1.0969915 , -1.4570425 ,  1.6427526 ,  1.7339163 ,
       -1.352395  ,  1.8935443 ,  1.5479664 , -1.1326214 ,  1.4739283 ,
       -0.5985468 , -1.9953831 ,  0.19330089,  2.0150068 , -1.1077588 ,
       -0.7925799 , -2.0366473 ,  1.2889062 ,  1.1966933 ,  1.0517032 ,
        1.7937889 , -1.4346434 , -1.5145547 ,  0.09457267,  1.3829018 ,
        1.2541049 ,  1.4955204 ,  1.5451305 , -1.258083  ,  1.8792548 ,
        1.3399404 ,  1.1557473 , -1.9889057 , -1.304167  , -1.331329  ,
        2.004129  , -1.2411418 ,  1.5077658 , -2.350809  ,  1.6616503 ,
        1.345018  ,  1.000408  , -1.6963177 ,  2.2849138 , -0.9672594 ,
        1.608192  , -1.679804  , -1.0924503 , -1.342583  , -1.5997461 ,
       -1.1587532 , -2.1433132 ,  1.3569995 ,  1.1490402 , -1.494378  ,
        0.98611534,  1.5630908 ,  0.90227425,  1.6739347 ,  2.5422182 ,
        1.6002998 , -1.3586421 ,  1.5319955 ,  1.3644439 , -1.8910191 ,
       -1.2302094 , -1.4905062 , -1.8660421 , -1.5393052 , -1.2387333 ,
       -1.2613645 ,  1.2375811 , -1.8249544 ,  1.3631194 ,  1.4224745 ],
      dtype=float32), array([ 30.262712 ,  36.492226 ,  55.005062 ,  16.518564 ,  75.10518  ,
        37.49499  ,  44.57174  ,  42.447533 ,  35.39342  ,  51.342968 ,
        39.941196 ,  38.364185 ,  70.160645 ,  85.331314 ,  47.188213 ,
        62.221252 ,  85.589195 ,  34.415283 ,  12.452004 ,  23.210657 ,
        33.156567 ,  19.41903  ,  15.662014 , 119.36103  ,  22.665113 ,
        25.548372 ,  35.2425   ,  49.578743 ,  16.384611 ,  45.960598 ,
        26.706367 , 103.880356 ,  44.22127  ,  39.12816  , 106.33185  ,
        16.899557 ,  35.531555 ,  36.22562  , 129.20328  ,  45.398865 ,
        47.451756 ,  36.18169  ,  19.925426 ,  42.666183 ,  30.764399 ,
        21.245861 ,  27.683203 ,  35.89091  ,  64.58797  ,  31.783052 ,
        52.338226 ,  16.419125 ,  31.192055 ,  18.661709 ,  30.399446 ,
        39.059467 ,  39.882698 ,  45.367523 ,  35.613113 ,  37.522552 ,
        45.36836  ,  27.918697 ,  23.979605 ,  24.40685  ,  29.85474  ,
        40.59082  ,  22.163288 ,  32.252945 ,  47.015606 ,  23.066305 ,
        35.752655 ,  59.032978 ,  36.154613 ,  69.86468  ,  30.690958 ,
        10.906117 ,  34.111805 ,  80.54899  ,  30.142078 ,  46.425823 ,
        63.755436 ,  65.58791  ,  75.03538  ,  21.10959  ,  49.064964 ,
        62.775257 ,  33.528076 ,  41.642635 ,  13.2605915,  25.069662 ,
        39.630585 ,  29.17236  ,  22.442747 ,  70.424194 ,  79.14751  ,
        10.278664 ,  28.981287 ,  16.976847 ,  32.96126  ,  20.969667 ,
        26.680109 ,  65.34745  ,  17.582493 ,   8.119207 ,  51.788216 ,
        56.2716   ,  28.46418  ,  33.01955  ,  35.358418 ,  30.511166 ,
        64.14716  ,  25.843927 ,  22.832249 ,  21.037579 ,  21.421164 ,
        25.173819 ,  34.266125 ,  38.32776  ,  16.974472 ,  42.021904 ,
        49.185287 ,  40.886314 ,  26.183212 , 131.35725  ,  28.280819 ,
        21.28244  ,  37.073883 ,  22.069817 , 124.54074  ,  34.33615  ,
        17.643515 ,  17.749098 ,  21.322927 ,  25.630993 ,  52.908623 ,
        47.79462  ,  30.355453 ,  39.421333 ,  31.789888 ,  33.989872 ,
        28.556711 ,  40.459057 ,  14.554308 ,  22.891272 ,   3.2597706,
        37.22282  ,  53.234512 ,  43.034855 ,  51.794357 ,  60.335873 ,
        53.222885 ,  22.829298 ,  29.20873  ,  34.027737 ,  51.966324 ,
        45.552116 ,  82.767586 ,  53.145412 ,  34.785706 ,  49.339344 ,
        75.275314 ,  42.244907 ,  92.910835 ,  46.222282 ,  30.372345 ,
        69.51596  ,  18.679106 ,  98.99126  ,  30.051346 ,  42.716507 ,
        63.87749  ,  40.542706 ,  27.997896 ,  25.801666 ,  27.648016 ,
        26.814592 ,  83.08757  ,  56.1405   ,  52.663284 ,  20.49331  ,
       102.76599  ,  20.051098 ,  64.53211  ,  16.058968 ,  32.58763  ,
        28.61533  ,  31.6      ,  19.57711  ,  23.452414 ,  49.375298 ,
        54.25594  ,  25.788916 ,  21.397821 ,  70.27418  ,  30.561184 ,
        37.788425 ,  55.794743 ,  33.17566  ,  36.578625 ,  24.153008 ,
        55.24896  ,  73.047295 ,  34.85848  ,  43.773922 ,  33.165077 ,
        41.339733 ,  14.075429 ,  31.86004  ,  31.633188 ,  31.660885 ,
        52.71933  ,   7.655666 ,  38.448494 ,  26.247055 ,  32.414883 ,
        21.122168 ,  30.297333 ,  56.940037 ,  12.97436  ,  52.322105 ,
        21.944963 ,  15.704368 ,  64.817444 ,  24.226387 ,  56.184284 ,
        27.342312 ,  60.157272 ,  17.177486 ,  66.87112  ,  37.209442 ,
        45.112236 ,  43.521698 ,  93.433266 ,  73.53496  ,  85.45008  ,
        38.05419  ,  38.17424  ,  27.505272 , 103.2548   ,  60.946724 ,
        24.150959 ,  49.7728   ,  85.168396 ,  25.972143 ,  37.815277 ,
        37.1384   ,  23.050772 ,  56.75756  ,  29.251835 ,  20.012548 ,
        33.246906 ,  36.365322 ,  26.5821   ,  44.666935 ,  17.243828 ,
        10.530184 ,  45.46618  ,  74.77466  ,  69.29814  ,  34.23346  ,
        12.992788 ,  28.091288 ,  28.502811 ,  39.443325 ,  34.23054  ,
        34.528164 ,  12.538724 ,  17.458656 ,  91.03641  ,  25.467493 ,
        32.787357 ,  36.78303  ,  39.73837  ,  51.372337 ,  57.376423 ,
        30.047241 ,  19.541927 ,  94.32436  ,  48.97773  ,  41.82212  ,
        56.733833 ,  29.963959 ,  35.89045  ,  40.247665 ,  39.77696  ,
        32.336674 ,  31.41713  ,  54.140987 ,  14.65926  ,  23.605368 ,
        26.274248 ,  48.179672 ,  18.55577  ,  33.007698 ,  58.423676 ,
        36.682125 ,  80.2226   ,  30.531887 ,  19.063292 ,  52.39169  ,
        42.894615 ,  28.758282 ,  22.455765 ,  10.467609 ,  67.40182  ,
        48.38808  ,  22.296759 ,  50.137627 ,  44.769814 ,  40.696373 ,
        32.884525 ,  28.352695 ,  57.295517 ,  14.377281 ,  39.900593 ,
        30.222542 ,  21.312317 ,  37.443512 ,  42.039135 ,  29.866867 ],
      dtype=float32), array([-3.9209645e-02, -7.9228012e-03, -1.0838644e-02, -3.0051845e-03,
       -5.6633870e-03, -7.4681481e-03,  7.5893011e-04, -1.4335720e-02,
       -3.7724401e-03, -6.9753965e-03, -2.5007313e-03, -1.6463837e-02,
       -4.8911357e-03, -1.9430749e-03, -1.9227270e-03, -1.1445841e-02,
       -2.6527045e-03, -9.6129049e-03, -6.1178836e-03, -3.5313587e-03,
       -8.8801915e-03, -2.4943259e-03, -6.1901542e-03, -4.7123795e-03,
       -5.9861359e-03, -2.4579756e-03, -1.1741118e-02, -5.9071747e-03,
       -4.2820837e-02, -2.0108517e-02, -1.6982853e-02, -6.9205998e-03,
       -2.5495030e-02, -5.3525590e-03, -9.9869538e-03, -2.1128892e-03,
       -1.0125413e-02, -1.3149081e-02, -2.5457530e-03, -1.0547218e-02,
       -9.7524207e-03,  2.1541928e-07, -8.1754755e-03, -6.1666076e-03,
       -3.7441598e-03, -1.9169581e-03, -6.7534167e-03, -1.2379797e-02,
       -7.9136100e-03, -7.9427594e-03, -7.5958394e-03, -9.8013533e-03,
       -1.4769125e-02, -3.2189932e-02, -3.3323830e-03, -3.8270265e-02,
       -3.6906947e-03, -2.3030166e-02, -1.0872830e-02, -4.1715346e-02,
       -2.2254679e-02, -7.7347662e-03, -3.8617507e-03, -3.6058450e-04,
       -2.1427369e-02, -4.9375971e-03, -2.5874814e-02, -2.5555030e-02,
        1.3098669e-04, -2.3128768e-02, -3.7425715e-02, -2.9917805e-02,
       -3.1847332e-02, -1.0077802e-02, -6.9530397e-03, -1.5058927e-02,
       -1.2564054e-02, -1.3042305e-02, -8.7717250e-03, -1.2465077e-02,
       -3.0222556e-02, -7.0663285e-03, -1.0795686e-02, -3.4308612e-02,
       -7.0571299e-03, -3.9657657e-03, -9.4652995e-03, -6.6039381e-03,
       -4.5627564e-02, -9.2416047e-04, -2.8383425e-03, -6.2348135e-03,
       -5.0571188e-02, -9.5019275e-03, -3.6151778e-02, -9.9818790e-03,
       -1.6140444e-02, -1.2508043e-02, -2.7939570e-03, -1.0417003e-02,
       -5.4456189e-02, -1.3095882e-02, -8.2764374e-03, -9.0264948e-03,
       -2.5576733e-03, -2.2457516e-02, -1.6103582e-02, -4.9646040e-03,
       -1.8568288e-03, -8.6014485e-03,  8.6479908e-05, -2.2886155e-02,
       -2.2878258e-03, -5.7096668e-03,  2.8306716e-03, -1.5492586e-02,
       -1.2470544e-02, -6.2419013e-03, -2.3507092e-02, -1.1849414e-03,
       -1.5182120e-03, -9.0993037e-03, -1.0407050e-02,  1.4709274e-03,
       -7.2098174e-03, -2.0609869e-02, -1.1294620e-02, -3.3848222e-02,
       -9.4543388e-03, -5.6762346e-03, -2.4662171e-02, -8.2159489e-03,
       -8.7282863e-03, -3.2629278e-02, -5.5334736e-03, -7.6439027e-03,
       -9.2254533e-03, -5.9558265e-03, -1.1372200e-02, -2.9239852e-03,
       -8.3041713e-03,  4.5585225e-04, -8.7179355e-03, -1.4137707e-02,
       -8.6928774e-03, -1.1986298e-02, -1.0769237e-03, -8.6189983e-03,
       -1.9036522e-03, -4.5939409e-03, -8.1673916e-03, -1.0517681e-02,
       -4.6117702e-03, -2.0155257e-02, -3.9083753e-02, -1.2730272e-02,
       -2.0519313e-03, -8.7206298e-03, -1.6382687e-02, -4.0035974e-03,
       -4.7219165e-02, -5.3133625e-03, -7.6574339e-03, -3.7621379e-02,
        2.0710290e-03,  7.0308940e-04, -9.3565872e-03, -3.5852829e-03,
        1.0270906e-03, -1.2259146e-02, -3.1245502e-02, -7.0064580e-03,
       -8.0872616e-03, -1.4309424e-03, -3.4518747e-03, -4.2133126e-02,
       -2.5384363e-03, -3.7760739e-03, -7.6782391e-03, -2.9053440e-02,
       -9.7963186e-03, -1.1553202e-02, -8.5856719e-03, -2.7900162e-05,
       -5.2139256e-03, -7.4788579e-03, -1.3808636e-02, -8.1433980e-03,
       -3.0031889e-03, -1.7071793e-02, -3.5088785e-02, -1.2338947e-02],
      dtype=float32), array([-0.7689898 ,  1.8428894 ,  1.8617202 ,  1.2242354 , -2.139787  ,
       -1.7076465 ,  1.4748746 ,  0.5313781 , -0.88041925, -1.1254333 ,
       -1.737673  , -2.0321136 , -1.90843   ,  0.8689905 , -1.4776068 ,
       -1.176157  ,  1.1730341 ,  1.7662561 , -2.4461098 , -1.5561861 ,
        1.8659667 , -1.5669725 , -1.2606646 ,  0.8149953 , -1.8936217 ,
        1.4076016 ,  1.9108974 ,  1.5992725 , -1.684703  , -1.4270207 ,
        1.0967084 , -1.4928058 , -1.2508615 , -1.821202  ,  2.1497908 ,
       -2.4650567 ,  1.8776488 ,  2.0918345 , -2.3353434 ,  1.7514807 ,
       -1.177386  ,  1.047183  ,  1.2889665 , -1.8014983 , -1.6093473 ,
       -2.0349178 , -1.5258794 ,  1.2019022 , -2.212407  ,  2.2301705 ,
       -2.211697  , -1.7773635 ,  1.8038261 , -1.9419175 , -2.2171807 ,
        2.9198143 , -2.1340537 ,  1.4796401 , -1.3101989 , -2.545721  ,
        1.521827  , -2.0354354 , -1.3860809 , -2.388989  , -2.7892995 ,
        1.8252422 ,  2.3228374 , -1.5855666 ,  1.8726679 ,  1.598885  ,
        3.0886464 ,  2.058492  , -1.4674077 ,  1.4730346 ,  0.9993692 ,
        0.822907  , -1.9262764 ,  1.461494  ,  2.1900914 ,  0.8012025 ,
       -1.8732172 ,  1.4783673 ,  1.3364025 , -1.3344327 , -2.0084047 ,
        1.1653308 ,  1.1590537 , -1.167896  ,  0.08876556, -2.0149689 ,
       -1.032315  , -2.0956328 , -1.5084903 ,  2.0556936 ,  0.19932435,
        1.4140279 ,  1.1321459 , -1.7149287 ,  0.92686665,  1.1780436 ,
       -1.44183   , -2.2862349 ,  1.8285943 , -1.4477009 , -2.3633919 ,
       -1.3342016 , -1.8181906 , -1.6959621 , -1.6289265 , -2.17718   ,
       -1.0803212 , -1.3454373 , -2.1102571 , -1.9448154 ,  1.47143   ,
        2.145309  , -1.85628   , -1.3120565 ,  1.57438   , -2.5610824 ,
        2.3843899 ,  1.0254686 ,  1.9484941 ,  2.1921086 , -1.5168107 ,
       -1.4124343 ,  1.7441816 ,  1.318873  ,  1.5437145 ,  1.4045562 ,
        0.763876  ,  1.6672384 , -1.3201717 , -1.6446303 , -0.53215325,
       -2.1559677 , -1.7425058 , -1.150779  ,  1.5224434 ,  1.0354543 ,
        1.952224  ,  1.0089542 ,  2.110997  ,  1.872634  , -1.3234833 ,
        1.5647845 ,  0.65557474,  2.2772248 ,  1.3504615 , -1.5702766 ,
        1.8456957 ,  1.0971798 ,  0.70504135,  1.5476602 ,  2.5011852 ,
        0.99748015,  0.44504762, -1.5463926 , -1.1668378 , -1.9319862 ,
       -0.23794267,  1.8197464 ,  1.8443822 , -1.748141  ,  1.3821826 ,
        1.118038  ,  1.9732635 ,  1.2398994 ,  1.0923944 ,  2.1818001 ,
        1.5665829 , -1.4591777 ,  1.2982424 ,  0.7391749 ,  1.3585441 ,
       -2.559759  ,  1.1612284 , -2.1573505 , -1.7537634 ,  2.4646087 ,
        1.6069795 , -1.3086165 ,  2.0575392 ,  1.0988228 , -1.6928841 ,
        1.6559861 , -1.847882  , -2.5189807 ,  1.9378163 ,  1.2174836 ,
        2.4382117 , -1.4822975 ], dtype=float32), array([ 13.277567 ,  42.252235 ,  36.474094 ,  14.319179 ,  66.23392  ,
        31.529207 ,  29.263868 ,  12.972028 ,  20.541975 ,  22.632975 ,
        46.135593 ,  35.374    ,  60.61328  ,  22.174606 ,  46.17568  ,
        16.74266  ,  21.826656 ,  38.80584  ,  77.33854  ,  44.847725 ,
        34.294933 ,  43.730278 ,  29.791769 ,  16.49653  ,  48.16333  ,
        40.187756 ,  36.66204  ,  26.148746 ,  22.659502 ,  21.80005  ,
        17.989141 ,  36.865067 ,  10.3551235,  42.616436 ,  34.83441  ,
        59.410748 ,  32.47124  ,  34.3894   ,  62.809612 ,  31.141254 ,
        21.865446 ,  19.12211  ,  41.308865 ,  41.41193  ,  44.140232 ,
        49.792446 ,  31.480059 ,  25.110342 ,  66.16594  ,  42.41324  ,
        43.290195 ,  52.78524  ,  22.756008 ,  17.656763 ,  59.933037 ,
        22.408453 ,  60.635853 ,  17.11269  ,  18.837227 ,  82.23972  ,
        13.489774 ,  61.749126 ,  24.436903 ,  74.92937  , 105.27711  ,
        26.190008 ,  37.393513 ,  35.52313  ,  82.99916  ,   7.4326277,
        31.231852 ,  16.018942 ,  12.588527 ,  13.7223625,  33.69249  ,
        22.14259  ,  33.62536  ,  23.22204  ,  37.101013 ,  17.49417  ,
        35.302784 ,  32.669144 ,  26.552322 ,  17.77729  ,  54.19417  ,
        16.539524 ,  20.04844  ,  36.6077   ,  21.728218 ,  63.950504 ,
        38.95276  ,  69.786415 ,  18.794737 ,  37.349518 ,  13.564099 ,
        27.10166  ,  18.603716 ,  55.438362 ,  19.982199 ,  22.940016 ,
        14.741918 ,  40.35145  ,  40.07696  ,  33.31651  ,  61.001514 ,
        27.59093  ,  23.622442 ,  46.372818 ,  40.61252  ,  56.163475 ,
        98.294945 ,  13.682339 ,  67.93207  ,  56.203316 ,  34.01113  ,
        18.722698 ,  22.878963 ,  31.557003 ,  15.035276 ,  84.25146  ,
        71.00214  ,  27.582724 ,  32.963684 ,  44.060074 ,  37.483047 ,
        15.818163 ,  25.117435 ,  19.568638 ,  36.5716   ,  16.359072 ,
        48.682323 ,  38.1709   ,  32.258568 ,  44.110733 ,  15.22419  ,
        51.752865 ,  37.78429  ,  26.381926 ,  27.128256 ,  20.439735 ,
        48.48545  ,  26.036533 ,  36.308502 ,  30.822477 ,  17.037373 ,
        35.50425  ,  20.92905  ,  50.92425  ,  19.292349 ,  30.297672 ,
        39.025826 ,  31.567492 ,  12.5065565,  13.322307 ,   8.4063425,
        14.237995 ,  19.72172  ,  27.150084 ,  29.277185 ,  42.477768 ,
        65.400276 ,  39.42344  ,  50.028633 ,  17.1488   ,  37.75854  ,
        26.725075 ,  44.623875 ,  15.198351 ,  26.096315 ,  32.76852  ,
        27.04843  ,  40.76981  ,  35.489933 ,  19.222157 ,  23.756899 ,
        42.447163 ,  22.505207 ,  46.9933   ,  38.57846  ,  29.11777  ,
        39.052696 ,  29.935396 ,  50.422836 ,  25.474405 ,  43.59074  ,
        37.577934 ,  29.35811  ,  48.777256 ,  49.27768  ,  27.49027  ,
        15.380674 ,  30.590446 ], dtype=float32), array([[-0.03077035, -0.03195568],
       [-0.04367645, -0.0157644 ],
       [ 0.0151519 , -0.03705083],
       ...,
       [ 0.03446497,  0.04214482],
       [-0.02981261, -0.03264079],
       [-0.03754976, -0.02820024]], dtype=float32), array([ 0.00341947, -0.00341947], dtype=float32)]

weights_of_Xception = members[2].get_weights()
print(weights_of_Xception)

[array([[[[-1.17488310e-01,  8.78244415e-02, -9.69463512e-02,
           8.41298178e-02, -8.48944262e-02,  1.28823012e-01,
           8.18164945e-02,  1.18198253e-01, -9.14182737e-02,
           5.14779650e-02,  5.97841777e-02, -7.08708540e-02,
          -7.77865276e-02, -1.09768651e-01,  6.67753862e-03,
          -1.03893571e-01,  8.53586271e-02,  1.22633234e-01,
          -9.67103764e-02,  3.62222306e-02, -7.82847032e-02,
          -6.42976388e-02,  6.70142695e-02,  3.40189599e-02,
           1.12256587e-01,  5.68732657e-02,  1.03933819e-01,
          -6.65459707e-02,  6.27406612e-02,  5.81717528e-02,
           5.04815020e-02,  5.34032732e-02],
         [ 9.25258994e-02, -6.70461506e-02,  5.43344878e-02,
          -4.71341684e-02,  3.50611843e-02, -8.89188424e-02,
          -2.52543539e-02, -5.16853705e-02,  1.10110462e-01,
          -7.43136331e-02, -1.39060572e-01,  1.09551780e-01,
           1.05394505e-01, -8.58991072e-02, -1.02573164e-01,
           6.70035854e-02, -6.57301769e-02,  6.15862533e-02,
          -1.85751915e-02, -5.45990616e-02,  1.06150456e-01,
          -1.01645246e-01, -9.06303152e-02,  6.04473229e-04,
          -5.27442284e-02, -2.23623235e-02,  1.98035836e-02,
          -7.18054548e-02,  1.04503103e-01, -8.98113623e-02,
           2.59761512e-02, -1.11605376e-01],
         [ 1.15781873e-01,  1.31851390e-01,  3.42768691e-02,
          -1.22427113e-01, -1.04710191e-01, -3.27966437e-02,
          -6.40726089e-02,  2.02569924e-02,  9.95511785e-02,
          -2.96087731e-02,  1.13184705e-01,  5.28556891e-02,
          -7.31376410e-02,  4.05442454e-02,  8.37328210e-02,
           3.51606980e-02, -6.11733869e-02,  4.76906123e-03,
          -3.93019393e-02, -4.19736281e-02, -9.29443762e-02,
           1.53718248e-01, -1.42153561e-01, -1.17301449e-01,
          -8.51302072e-02,  7.39486068e-02, -9.54960510e-02,
           1.91197339e-02, -4.75770384e-02,  9.48464200e-02,
           1.79501325e-02,  6.48140833e-02]],

        [[ 1.28568649e-01,  2.60665140e-04,  1.32055640e-01,
          -4.25683409e-02, -1.15474556e-02, -1.35464221e-01,
          -1.15023814e-01,  1.14444807e-01, -1.18023537e-01,
           1.01988189e-01, -1.12210214e-01,  2.36013532e-02,
           5.42110652e-02, -6.02986924e-02,  1.36908859e-01,
           6.95981160e-02,  1.18389698e-02, -5.28577082e-02,
           1.58029459e-02, -4.82783653e-02, -1.23875745e-01,
           1.07486255e-01, -5.08619510e-02,  1.28958911e-01,
           9.28692743e-02,  1.32711962e-01, -3.89966369e-02,
           4.94930148e-03,  4.09337208e-02, -5.41693419e-02,
           7.08582252e-02, -8.20017383e-02],
         [ 4.52980250e-02,  3.37455608e-02,  7.49661326e-02,
          -9.74190533e-02, -9.98883173e-02, -2.60421503e-02,
           1.02509752e-01, -9.75140138e-04,  5.87040894e-02,
           1.26689717e-01, -1.26611367e-02, -2.52874140e-02,
          -6.77836463e-02,  6.29316419e-02, -1.66174956e-02,
           1.31313145e-01, -5.88417873e-02,  6.87373355e-02,
           1.19053707e-01,  1.25502208e-02,  1.39110652e-03,
           9.05393716e-03, -1.25723615e-01,  4.36954536e-02,
           8.74542817e-02, -5.69176897e-02,  1.00986876e-01,
           7.97431469e-02, -3.44135985e-02, -4.62014936e-02,
           1.45385817e-01, -9.25279111e-02],
         [ 1.31314605e-01,  1.44974947e-01, -1.53700532e-02,
           2.28141993e-02,  2.21475886e-04, -1.21257931e-01,
           1.05645917e-01,  2.05598995e-02, -1.49413673e-02,
          -7.21949264e-02,  9.08691511e-02,  3.77940573e-02,
           9.24783126e-02, -9.59060714e-02,  4.80933078e-02,
          -1.35002404e-01, -1.33255154e-01,  6.63927346e-02,
           1.27087444e-01, -1.39450595e-01, -1.15011381e-02,
          -8.87356400e-02, -1.40507862e-01,  1.90246776e-02,
           1.71896130e-01,  1.26211524e-01,  1.20572895e-01,
          -1.63737219e-02,  8.28028545e-02,  1.14787027e-01,
           1.34442210e-01,  1.07233174e-01]],

        [[ 7.60969818e-02,  8.60009063e-03,  1.80225577e-02,
          -6.99078739e-02, -2.98767351e-02, -1.02971025e-01,
           9.12841037e-02,  5.82656078e-02, -7.22621828e-02,
          -1.11763969e-01, -4.30400185e-02,  7.48588592e-02,
           4.52579260e-02,  1.00500342e-02,  6.05407730e-02,
          -5.55350855e-02,  2.14603773e-04,  8.94967467e-03,
           4.71735708e-02,  4.37538400e-02,  8.53346512e-02,
          -1.05151221e-01, -1.30041875e-02,  1.15700804e-01,
          -6.37342334e-02,  7.10500926e-02, -7.30818883e-02,
          -6.48618490e-02,  5.19926250e-02,  5.55103570e-02,
           9.79026258e-02,  2.40684059e-02],
         [-1.45083278e-01,  2.90229172e-02,  1.12951301e-01,
           1.92161035e-02, -4.10086736e-02, -9.18530673e-02,
           1.21129908e-01,  1.16860501e-01,  7.39439577e-02,
          -7.71104693e-02, -1.88174378e-02, -2.63475534e-03,
          -8.65702853e-02,  6.64028078e-02,  6.28460944e-03,
           1.20967505e-02, -5.55319637e-02, -6.96648611e-03,
           1.34995561e-02,  6.20558150e-02, -2.15444528e-02,
          -4.34316657e-02, -7.84338713e-02, -1.10049210e-01,
          -8.26965179e-03, -1.36002585e-01,  1.05500013e-01,
          -1.10235579e-01,  1.43232897e-01,  6.26533404e-02,
           1.39272332e-01,  1.07470736e-01],
         [-5.41575141e-02, -2.61704773e-02, -1.64422970e-02,
           1.51096908e-02, -1.94535628e-02, -2.03985609e-02,
          -7.89769217e-02, -4.80250865e-02, -9.11818594e-02,
           7.11755455e-02, -3.05066928e-02,  2.77863313e-02,
          -3.05372868e-02, -5.84635027e-02, -5.68229891e-02,
          -1.36421144e-01,  1.26525164e-01, -6.92592040e-02,
          -9.66097936e-02, -5.52836284e-02,  3.02254818e-02,
           1.27485290e-01, -4.98808362e-02,  1.02361076e-01,
           6.56685531e-02,  5.37940860e-02, -1.05255479e-02,
           9.09951106e-02,  4.92438748e-02,  5.21599092e-02,
          -2.67972983e-02, -9.70944911e-02]]],


       [[[-8.96245688e-02,  7.53717721e-02,  1.09901011e-01,
          -9.68347420e-04,  1.59320191e-01, -7.46099949e-02,
          -1.82709936e-02,  7.30058923e-02,  1.15869746e-01,
          -3.77250686e-02,  9.03161056e-03,  1.86406802e-02,
          -8.18404630e-02, -1.22114457e-01,  9.83292684e-02,
           5.83031997e-02, -4.08964977e-02,  1.53157890e-01,
           1.23844720e-01, -7.59516284e-02, -1.43217444e-01,
           1.13752112e-01,  8.20985250e-03, -2.71929018e-02,
           7.71816494e-03, -8.14292803e-02, -8.75269249e-02,
          -9.33023691e-02,  1.38963416e-01, -4.86192740e-02,
           6.19503669e-02,  2.75093727e-02],
         [ 1.33729363e-02, -3.57096456e-02,  9.71658528e-03,
           1.72123201e-02, -1.19434536e-01, -9.37817469e-02,
          -6.00347258e-02,  4.83573191e-02, -9.17300433e-02,
           3.17327268e-02,  6.96652159e-02, -2.10738368e-03,
           4.58463617e-02,  1.09961852e-01, -1.34794265e-01,
          -1.01706780e-01,  3.98284979e-02,  3.67995799e-02,
          -1.17263503e-01,  5.50674349e-02,  1.10076204e-01,
           6.98620966e-03,  6.38129637e-02, -6.99001700e-02,
          -4.92823534e-02, -5.83302118e-02, -2.74538086e-03,
          -2.23439303e-03, -7.86164999e-02, -6.77133128e-02,
           1.90843903e-02,  4.63850908e-02],
         [ 6.28044549e-03,  1.29338190e-01, -4.72434945e-02,
           1.04498684e-01, -1.46437883e-01,  8.61868486e-02,
          -1.74158290e-02, -7.24870712e-02, -9.37612951e-02,
          -3.70480400e-03, -1.07769594e-01,  9.98035744e-02,
          -7.90738538e-02, -8.35006461e-02, -1.30197734e-01,
           2.06103525e-03,  3.79728451e-02,  3.32219489e-02,
           1.07195742e-01,  3.31848972e-02, -5.38954549e-02,
          -1.07733466e-01, -6.22424297e-02,  8.94505084e-02,
          -6.91760108e-02,  1.33234262e-01, -2.95326468e-02,
          -5.53693473e-02,  5.34207560e-03,  1.23493850e-01,
           4.41556312e-02,  7.07621202e-02]],

        [[-4.61496823e-02,  3.06357332e-02,  5.27222045e-02,
           1.61800999e-02,  5.62365726e-02, -6.77387044e-02,
           2.82848217e-02,  5.76782785e-02, -9.95027795e-02,
          -5.40561602e-02,  7.62578249e-02, -1.53362984e-02,
          -9.60561633e-02,  6.15405403e-02,  1.18154660e-01,
          -4.17963117e-02, -1.24138266e-01,  9.07039940e-02,
          -5.52150607e-02,  1.49580017e-02,  3.37963365e-03,
          -5.07434038e-03,  1.04082368e-01,  1.29037574e-01,
           6.04669265e-02,  7.50386417e-02, -5.13752811e-02,
           1.17969267e-01,  1.27699077e-01,  5.79011478e-02,
           1.39996797e-01,  7.45457634e-02],
         [ 9.25804377e-02, -1.13015234e-01, -1.56014869e-02,
           5.10359742e-02, -9.90731865e-02, -1.00787163e-01,
          -4.02018707e-03,  4.56280187e-02,  4.66761328e-02,
           5.70429116e-02, -3.52554433e-02, -1.37732282e-01,
           1.00315800e-02,  4.37039789e-03, -1.62512790e-02,
           8.91958550e-02, -7.07938150e-02, -1.31486103e-01,
           1.06556259e-01, -8.11583474e-02,  4.98308875e-02,
          -9.83134145e-04, -1.64323840e-02, -1.18476175e-01,
          -4.25648205e-02,  6.80499198e-03, -2.92257033e-02,
          -5.30567439e-03, -1.18889399e-01, -1.09984413e-01,
           1.94466058e-02,  2.69359313e-02],
         [ 3.76130231e-02, -7.24901929e-02, -1.24421522e-01,
           5.78543618e-02, -1.93717126e-02, -1.12664968e-01,
          -6.22953437e-02,  8.59600902e-02,  1.26913488e-01,
           3.65905911e-02, -4.85459110e-04, -7.95541108e-02,
           1.00782529e-01,  2.00468451e-02,  7.34783635e-02,
          -1.40658632e-01, -1.33368850e-01,  1.14612244e-01,
           4.20429520e-02, -1.16545625e-01,  3.94094847e-02,
          -4.62900959e-02, -1.05120782e-02, -1.07415535e-01,
          -7.47653842e-02, -3.38866599e-02,  2.73026023e-02,
          -1.38627589e-01,  4.12709564e-02,  1.66359078e-02,
          -8.57847556e-02,  1.30624250e-01]],

        [[-1.18737109e-01, -1.41546845e-01, -5.02366982e-02,
          -3.35286930e-02, -5.91057725e-02, -8.03951696e-02,
           8.94663185e-02, -5.23353405e-02, -2.23766360e-02,
           8.32321420e-02,  1.20471880e-01,  1.48610128e-02,
           1.38625458e-01, -2.18308959e-02, -1.21454038e-01,
          -1.14979997e-01, -1.75616611e-02,  1.39939860e-01,
           4.33574691e-02, -9.30941775e-02, -4.03260216e-02,
           1.09038159e-01, -1.62976384e-02,  2.52458733e-02,
           8.31050128e-02, -5.30322865e-02, -1.02359252e-02,
           3.97717208e-02, -9.27761570e-03,  3.75951193e-02,
           3.79031599e-02,  4.36858870e-02],
         [-1.06545150e-01,  4.76507321e-02,  1.16313621e-02,
          -5.47092408e-02,  1.51265830e-01,  8.46203789e-02,
          -1.38599902e-01,  2.35099662e-02, -5.07282764e-02,
           5.35019711e-02,  1.11383259e-01, -1.29209191e-01,
           2.60863304e-02,  1.29665345e-01, -1.39170513e-01,
          -7.91528821e-02, -5.70546053e-02,  1.21262021e-01,
          -8.67699757e-02,  8.48051459e-02, -5.08679301e-02,
           7.35405833e-02,  2.78625195e-03, -1.18468359e-01,
          -2.28058770e-02, -1.11838020e-01, -9.63213816e-02,
          -1.35244831e-01,  6.33687004e-02,  1.08111955e-01,
          -3.63327824e-02,  3.07573006e-02],
         [ 6.07936867e-02, -9.75387245e-02,  9.03629512e-02,
          -1.38770416e-01,  3.66722532e-02,  7.24458694e-02,
           6.52429685e-02, -1.99822579e-02, -5.44167347e-02,
          -2.60172486e-02, -7.98207223e-02, -1.46387875e-01,
           9.37156677e-02, -4.21111658e-02,  3.94314043e-02,
           4.02625762e-02,  8.23771022e-03, -1.25685856e-01,
          -1.22426964e-01, -3.28899026e-02, -3.45731415e-02,
           1.09842278e-01, -4.49031666e-02, -1.38110548e-01,
          -7.40834698e-02,  1.12429202e-01,  1.32930532e-01,
           5.67611828e-02, -7.75542259e-02,  2.47756597e-02,
          -9.01095495e-02, -8.48061293e-02]]],


       [[[ 1.09387882e-01,  1.03671122e-02,  7.17323869e-02,
          -2.40694657e-02,  9.28723812e-02, -9.12281573e-02,
          -3.78850214e-02,  5.93833812e-02,  7.78586417e-02,
           3.94837670e-02,  5.95347732e-02, -1.41639942e-02,
           1.60736248e-01, -1.23969816e-01, -2.35827435e-02,
          -1.09685436e-01,  9.00952071e-02,  2.75214054e-02,
          -2.83043645e-02,  5.87050095e-02, -3.78549397e-02,
           6.59863651e-02,  1.74326971e-02,  1.30437970e-01,
          -6.87290281e-02,  2.57068574e-02, -1.02365091e-02,
           1.01958014e-01,  1.28706828e-01,  1.09422922e-01,
           2.04909351e-02, -9.32466462e-02],
         [-8.37426335e-02, -4.86507602e-02,  1.32183731e-01,
          -1.31982863e-01,  2.72108782e-02, -1.12567492e-01,
          -1.06875720e-02,  3.27646136e-02, -1.10435754e-01,
           1.32013127e-01,  1.20479144e-01, -6.90775216e-02,
           6.11817390e-02,  3.99755239e-02, -1.23521715e-01,
           1.28422501e-02,  1.05361760e-01,  7.39026489e-03,
          -4.27024215e-02, -5.51716099e-03,  5.47923055e-03,
          -1.17471613e-01,  8.00143555e-02, -7.38765672e-02,
           9.41206738e-02,  1.19310305e-01,  1.20599940e-01,
          -5.58295287e-02, -6.12353943e-02, -1.14503756e-01,
           7.68818334e-02,  6.69183284e-02],
         [-6.95795864e-02,  8.49508494e-02,  5.08893766e-02,
          -8.56544301e-02,  1.20673239e-01,  1.04294065e-02,
           1.21230468e-01,  2.60325596e-02,  1.30800933e-01,
           1.17575735e-01,  1.45197451e-01,  9.27762389e-02,
          -1.23709496e-02,  1.01554312e-01,  7.85257965e-02,
           7.68454000e-02, -3.78096662e-02,  9.76155028e-02,
           3.77061814e-02,  8.27119350e-02, -2.64843963e-02,
           8.32196549e-02,  9.70446737e-04, -5.92214763e-02,
           1.04987375e-01, -4.83146608e-02, -4.80242148e-02,
          -3.12273465e-02, -3.53131965e-02, -4.72390559e-03,
           9.45714209e-03,  1.06225960e-01]],

        [[ 1.06119543e-01,  9.10270400e-03, -3.17826457e-02,
          -1.32440090e-01,  6.83326051e-02, -2.75752675e-02,
           9.29440185e-02,  1.54312300e-02, -3.47829126e-02,
          -6.66433154e-03,  1.23974025e-01,  5.55147752e-02,
          -7.17114136e-02,  7.41475669e-04,  1.31919205e-01,
          -2.93954667e-02,  1.28442526e-01,  1.51668698e-01,
          -6.96490258e-02,  1.17179848e-01,  9.81893092e-02,
          -1.09312683e-01, -4.76967879e-02, -1.33193195e-01,
           7.29045644e-02,  1.07905887e-01,  6.16915077e-02,
          -5.88275678e-02, -3.43724377e-02,  1.07480571e-01,
           1.07979737e-01,  3.27233933e-02],
         [ 5.48551567e-02, -8.26240778e-02,  9.96942148e-02,
          -1.70964655e-03, -3.97638008e-02,  2.02121269e-02,
           1.22478567e-01, -3.49556841e-02,  1.33509636e-01,
           1.48609862e-01,  5.69810085e-02,  7.73247927e-02,
          -1.00037791e-01, -9.34119243e-03,  1.15779310e-01,
           7.88868638e-04,  9.12503165e-04,  8.98748264e-02,
           9.49503183e-02,  1.32039972e-02,  1.02127139e-02,
          -3.94151621e-02,  4.78716269e-02, -1.16040908e-01,
           2.32815873e-02, -6.81341486e-03,  1.02388717e-01,
           2.67140958e-02,  4.04027337e-03, -1.45485699e-01,
           4.69330214e-02, -1.03047580e-01],
         [ 6.89099208e-02, -2.34313402e-02, -4.46461402e-02,
          -1.26431286e-01, -6.17554188e-02, -9.56271961e-02,
           4.28930968e-02,  8.02683532e-02,  2.97677536e-02,
           3.63620929e-02,  1.03348725e-01, -2.89926659e-02,
           2.20212732e-02, -4.31136750e-02, -3.99099812e-02,
          -1.26435265e-01, -5.72079122e-02, -6.59433752e-02,
           5.35997674e-02, -5.77872135e-02,  1.29319772e-01,
          -2.06065681e-02,  1.07366323e-01,  5.79221286e-02,
           8.53767768e-02,  9.82006192e-02, -2.28766110e-02,
          -4.78173010e-02,  2.82965247e-02, -4.92205564e-03,
          -1.15706995e-01, -2.25301236e-02]],

        [[ 1.30394235e-01,  8.14559385e-02,  7.82020539e-02,
          -1.26031041e-01,  1.80606954e-02,  7.43926466e-02,
          -1.22673124e-01, -3.83179309e-03, -2.30143834e-02,
           6.44936040e-02,  5.47853932e-02, -7.94129074e-02,
           1.55040964e-01,  1.31559029e-01, -1.04193829e-01,
           4.05198924e-04,  6.60963282e-02, -1.12018779e-01,
           4.02921885e-02,  7.39540011e-02,  7.47313127e-02,
           8.85328501e-02, -6.18334301e-03,  1.40643686e-01,
           1.09721333e-01,  1.23764924e-03, -3.88979563e-03,
          -1.10784797e-02, -2.84614880e-02,  3.21045592e-02,
          -4.33189329e-03, -1.31590500e-01],
         [-1.21325798e-01,  6.63807094e-02,  9.05705616e-02,
           9.66121256e-02,  2.54968777e-02,  6.91774413e-02,
          -8.15435871e-02, -7.07335025e-02,  1.09587707e-01,
           1.01331711e-01, -1.39464974e-01, -6.18676394e-02,
           8.90646949e-02, -5.72309084e-02,  8.87861401e-02,
           1.02910906e-01, -5.62692899e-03,  1.87713187e-02,
           9.30052549e-02, -1.18367836e-01,  2.75553353e-02,
           8.33542459e-03, -3.20980772e-02, -1.37804627e-01,
           5.74664446e-05,  3.28669697e-02,  2.44777128e-02,
          -1.51387490e-02,  2.46107415e-03, -6.34632930e-02,
           1.38357073e-01, -1.18028566e-01],
         [-9.32438448e-02, -8.65155458e-02,  1.70819298e-03,
          -5.63128479e-02, -1.07633077e-01, -1.37130946e-01,
          -4.18601446e-02, -5.50708920e-02,  7.94304758e-02,
          -1.52212996e-02, -9.74766985e-02, -1.29304349e-01,
          -8.18509609e-02, -1.29466772e-01, -1.16587706e-01,
           1.70206651e-02,  3.70243005e-02, -2.66162865e-02,
          -1.19010881e-01,  7.05202222e-02, -1.15025178e-01,
          -1.13841854e-01,  8.86844546e-02,  1.03199661e-01,
          -2.74090879e-02, -5.92455305e-02,  3.44759529e-03,
          -2.53624581e-02,  1.88984182e-02, -9.41918418e-02,
          -4.84349653e-02,  1.35145962e-01]]]], dtype=float32), array([0.9965732 , 1.0037282 , 1.0113747 , 1.0097307 , 0.9914834 ,
       1.0056295 , 0.98262537, 1.0121353 , 0.98882455, 0.9893774 ,
       0.9943695 , 1.0012931 , 0.99996364, 0.9965621 , 1.0044479 ,
       1.0088491 , 0.9863023 , 0.9963008 , 1.0044732 , 0.9907977 ,
       0.98193896, 0.99742264, 1.0089015 , 1.0098653 , 1.0155481 ,
       0.98496884, 1.0115488 , 1.0125256 , 0.99543   , 1.0136869 ,
       0.9969937 , 1.0044681 ], dtype=float32), array([-0.00968324, -0.01663438,  0.00971088,  0.00777686, -0.01134738,
        0.01311333, -0.00615763,  0.00484053,  0.01253291,  0.00638111,
       -0.00204247,  0.0030129 , -0.00676699, -0.01153238, -0.03172311,
       -0.01362249, -0.02049145, -0.0078801 , -0.0182728 , -0.01891622,
       -0.02645307, -0.01884457,  0.00196513, -0.01986908, -0.01565399,
       -0.02230178,  0.01474196,  0.00846944, -0.0175964 , -0.01283297,
       -0.0146502 , -0.00339751], dtype=float32), array([ 0.07090507,  0.07142051,  0.40470436, -0.43665537, -0.14286219,
       -0.5937187 ,  0.17124811,  0.30841145,  0.03897068,  0.39895484,
        0.1429158 , -0.14820147,  0.07260169, -0.11754368,  0.00714337,
       -0.21413176, -0.04674086,  0.49001518,  0.05914746,  0.00621198,
       -0.01632605,  0.08364011, -0.15883344, -0.05539079,  0.12290769,
        0.36994517,  0.12728718, -0.23847106,  0.29813576,  0.1708004 ,
        0.58768076,  0.07827435], dtype=float32), array([0.0815478 , 0.08150583, 0.09050641, 0.09145297, 0.08499326,
       0.10202488, 0.08302564, 0.08592862, 0.08323803, 0.09272224,
       0.08252831, 0.08269612, 0.08177807, 0.0819097 , 0.08220151,
       0.08360031, 0.08296577, 0.09362466, 0.08144334, 0.08170772,
       0.08139417, 0.08158517, 0.08382473, 0.0857194 , 0.08284206,
       0.08953603, 0.08314059, 0.08521304, 0.08541128, 0.08276089,
       0.09926371, 0.08249872], dtype=float32), array([[[[-0.00650902, -0.06160188,  0.09029014, ..., -0.02354347,
           0.06063878, -0.02356833],
         [-0.07090817, -0.07214493,  0.09243553, ..., -0.02088021,
           0.04240385,  0.07594366],
         [-0.0593718 , -0.0331919 ,  0.05386875, ...,  0.03588113,
           0.00239643,  0.03909718],
         ...,
         [-0.07564735,  0.07150692,  0.06934506, ...,  0.06097834,
           0.06525605, -0.01987765],
         [ 0.03849384,  0.02747203,  0.0236361 , ...,  0.02582288,
          -0.03458977,  0.04227435],
         [-0.05089111,  0.05012205, -0.04020322, ..., -0.05209973,
           0.0225654 ,  0.05829976]],

        [[-0.00563335, -0.07267422,  0.00202728, ..., -0.04311345,
           0.0623377 , -0.03383551],
         [ 0.04077541, -0.02642661, -0.0085059 , ...,  0.08221092,
           0.01634701, -0.05647096],
         [ 0.09326943, -0.04421332, -0.07253941, ..., -0.03735618,
           0.04206863,  0.03330527],
         ...,
         [ 0.00734005, -0.03450297,  0.00434489, ...,  0.05516631,
           0.03107771,  0.0728543 ],
         [-0.02167138,  0.03052859,  0.02064287, ...,  0.01448322,
           0.06524717,  0.01777256],
         [ 0.05328418, -0.05767715,  0.05089037, ..., -0.07430404,
          -0.08547148,  0.06434131]],

        [[ 0.05510662,  0.0838963 ,  0.05717732, ..., -0.05848817,
          -0.09262154,  0.08606876],
         [ 0.03747747,  0.01631771, -0.02339344, ..., -0.07076384,
          -0.04743766,  0.00681296],
         [ 0.0322158 ,  0.03640801,  0.04173848, ...,  0.01532848,
          -0.03358894,  0.04075065],
         ...,
         [-0.05151092, -0.00468788,  0.04599583, ...,  0.0265833 ,
          -0.00737719,  0.00635205],
         [ 0.08909442, -0.00522221, -0.04421234, ..., -0.00807905,
           0.06788693, -0.00227923],
         [-0.02629405,  0.05958101, -0.03293993, ...,  0.0554607 ,
          -0.04234789, -0.04385087]]],


       [[[-0.05630887,  0.05267985, -0.00698929, ..., -0.04422018,
           0.00079874,  0.038755  ],
         [ 0.0379678 ,  0.05689053, -0.01944569, ...,  0.04357564,
           0.04904255, -0.03816516],
         [ 0.01925715,  0.03103234,  0.00244016, ...,  0.05500262,
           0.00545077, -0.03053741],
         ...,
         [ 0.04749074, -0.02405556, -0.05407167, ...,  0.02629129,
          -0.01259295,  0.03770465],
         [-0.01630806, -0.02514483,  0.07681423, ...,  0.0854575 ,
           0.05134536,  0.08479287],
         [-0.02199468,  0.03624674,  0.00711957, ...,  0.05940827,
           0.04223004,  0.06019781]],

        [[-0.07360972, -0.04771956, -0.02538696, ...,  0.02558106,
           0.06035627, -0.0262153 ],
         [-0.03916311,  0.08561408, -0.06388734, ...,  0.08605   ,
          -0.08429612, -0.03941548],
         [-0.02902733, -0.03585783,  0.03510578, ...,  0.04966367,
          -0.08428083,  0.08998588],
         ...,
         [ 0.06956479,  0.02944227, -0.01538868, ..., -0.01221475,
          -0.03121204,  0.05916366],
         [-0.04237065,  0.0306321 , -0.00577613, ...,  0.05601438,
           0.05333051,  0.04491643],
         [ 0.0434636 , -0.05436067, -0.06924342, ...,  0.05100257,
          -0.09367921, -0.0252592 ]],

        [[-0.051845  ,  0.06033972, -0.04334812, ...,  0.01643745,
          -0.05782946, -0.05560037],
         [ 0.02209629,  0.0810831 , -0.01193401, ...,  0.08702264,
           0.02776631,  0.00942827],
         [ 0.01137979, -0.01137062, -0.01565709, ...,  0.01988954,
           0.0671044 ,  0.01892642],
         ...,
         [-0.07217626, -0.02482276,  0.0057205 , ...,  0.04156138,
          -0.02165152,  0.0215324 ],
         [ 0.06391945,  0.05481605, -0.01572816, ..., -0.04605586,
          -0.09211374, -0.04997912],
         [ 0.0846011 , -0.02808794, -0.04969437, ...,  0.06907352,
          -0.09053151,  0.04730435]]],


       [[[-0.02291235,  0.07921559,  0.08434949, ...,  0.01732711,
           0.05022071,  0.0087134 ],
         [ 0.04607461, -0.06375724,  0.03667464, ...,  0.02921413,
           0.06519807, -0.03086423],
         [ 0.09136728, -0.05563309, -0.08046226, ...,  0.00129766,
          -0.07779413,  0.0389565 ],
         ...,
         [-0.08570251, -0.04877047, -0.06121685, ..., -0.01052107,
           0.05800504, -0.03126626],
         [-0.04082936,  0.06131198, -0.0597083 , ...,  0.07100098,
          -0.04959578,  0.00186049],
         [-0.05907141, -0.02005123,  0.04010023, ...,  0.03858871,
          -0.00328154,  0.00446769]],

        [[ 0.01049602, -0.03011162, -0.05281818, ...,  0.00272517,
          -0.01177149,  0.08794288],
         [-0.01641767,  0.05087269, -0.06352609, ...,  0.02120311,
           0.06167692, -0.0172342 ],
         [-0.0393962 ,  0.01327655, -0.06633867, ..., -0.04463574,
           0.01546187, -0.01243703],
         ...,
         [-0.08945993,  0.02814383,  0.04713496, ...,  0.03192858,
          -0.0146016 ,  0.02737595],
         [-0.02715693, -0.02650914,  0.02097983, ...,  0.05404575,
           0.03877816,  0.06823145],
         [ 0.06852494,  0.08325366, -0.04437007, ..., -0.06391659,
          -0.00309372,  0.01841164]],

        [[-0.05462486,  0.02486718,  0.04633377, ..., -0.04092406,
          -0.01529933, -0.0624547 ],
         [-0.01168842,  0.01250407,  0.02686137, ...,  0.01603281,
           0.04359126,  0.02329891],
         [-0.05759387,  0.08600314,  0.03213193, ..., -0.07293211,
           0.03369107,  0.01689391],
         ...,
         [ 0.05322615,  0.04633576, -0.02014198, ...,  0.02083077,
          -0.0695824 ,  0.07986915],
         [-0.0350066 , -0.07584428, -0.06790749, ..., -0.01161437,
          -0.06971816, -0.00444367],
         [ 0.03474038, -0.0508425 , -0.06055399, ..., -0.03196187,
          -0.00327157,  0.05337493]]]], dtype=float32), array([1.0106876 , 1.0086342 , 1.0053189 , 0.9860379 , 1.0019355 ,
       1.0074075 , 1.0111959 , 0.9961915 , 0.99800175, 1.0128366 ,
       1.0136156 , 0.98017484, 1.0007129 , 1.0089563 , 1.01016   ,
       0.993391  , 0.9869517 , 1.00012   , 1.0139779 , 1.001948  ,
       0.99889874, 1.0060177 , 1.0135943 , 0.9931983 , 0.99961835,
       1.008157  , 0.9751137 , 0.98755705, 1.027447  , 0.980716  ,
       1.0213491 , 0.98517513, 0.979514  , 1.0020697 , 1.0034989 ,
       0.99177015, 1.0004007 , 0.9958197 , 0.9931938 , 1.0116132 ,
       0.9859289 , 0.9979102 , 1.0005244 , 0.9932988 , 0.9871299 ,
       1.010568  , 0.9950166 , 0.99477583, 0.98988926, 1.0056452 ,
       0.97211725, 1.0211195 , 1.0051928 , 0.9946319 , 0.9984573 ,
       0.99054307, 1.0213329 , 1.0209821 , 0.9959369 , 1.0019816 ,
       0.9962908 , 1.0009704 , 1.0093029 , 0.9930557 ], dtype=float32), array([-1.62402950e-02, -2.97984784e-03,  7.33957160e-04, -2.31544953e-02,
       -3.71225644e-04, -5.80490055e-03, -2.20324937e-02,  3.31828697e-03,
       -4.31271121e-02, -3.22812833e-02, -4.43503540e-03, -8.63284711e-03,
       -1.38331985e-03, -2.45807543e-02,  5.22879139e-03,  2.18378613e-03,
       -2.55484115e-02, -6.15645293e-03, -1.09149944e-02, -4.59571136e-03,
        2.30295341e-02, -6.14551827e-03,  2.54610367e-02, -8.04199744e-03,
       -1.03997276e-03, -6.72606402e-05, -1.17136361e-02, -2.59431321e-02,
        6.61809323e-03, -1.72301345e-02,  3.97469196e-03, -1.48598142e-02,
       -3.18441018e-02, -2.31376197e-03,  8.36191513e-03, -1.02341343e-02,
       -8.27108882e-03, -7.02722371e-03, -1.14933467e-02, -7.91896693e-03,
       -1.21151106e-02,  1.43331457e-02, -8.66871607e-03, -7.80452229e-03,
       -3.31227034e-02, -8.04770365e-03, -1.42702917e-02,  1.18678715e-02,
       -4.04997915e-02, -7.76758930e-03, -1.99731998e-02, -5.02743432e-03,
       -2.89466847e-02,  6.34086202e-04, -1.32062314e-02,  2.62666843e-03,
        2.12195329e-02, -2.93630436e-02,  1.34487413e-02,  4.47291695e-03,
        6.97526848e-03, -5.07324003e-03,  2.95439013e-03, -7.16354977e-03],
      dtype=float32), array([ 0.14751448,  0.19008951,  0.03543789,  0.02160822,  0.2913647 ,
       -0.28328758, -0.06148181,  0.09571522,  0.28724566,  0.3371826 ,
       -0.21587202, -0.07857215,  0.06781913,  0.12807176,  0.10797592,
       -0.33814588,  0.3309041 , -0.25602326,  0.4844249 ,  0.45319256,
       -0.49596196, -0.12222501, -0.05034257, -0.44743353, -0.30762985,
        0.2750099 ,  0.21476033,  0.43798733,  0.23655526,  0.15793431,
        0.3633806 , -0.00779751, -0.5112468 ,  0.38946778,  0.13200594,
        0.5381226 ,  0.31783807,  0.05259726, -0.35553703,  0.3489123 ,
       -0.17416894, -0.33310357, -0.7984078 ,  0.28860897,  0.40011156,
        0.1531788 ,  0.03663221, -0.25995362,  0.42585272,  0.08191945,
        0.47517607,  0.6179235 ,  0.07552213, -0.3719491 , -0.29967874,
       -0.0711627 ,  0.01605355,  0.11875358, -0.34115133, -0.43251914,
       -0.25698668, -0.09698976, -0.50200367,  0.5012045 ], dtype=float32), array([0.27995634, 0.19136228, 0.23523624, 0.43335116, 0.7757421 ,
       0.4302611 , 0.40939915, 0.53795433, 0.2385428 , 0.6285519 ,
       0.49213707, 0.6222816 , 0.4547485 , 0.50392294, 0.574241  ,
       0.34805742, 0.63821226, 0.7041128 , 0.63334596, 0.40447524,
       0.38013017, 0.28810495, 0.8162349 , 0.45030236, 0.62755156,
       0.7799872 , 0.2100486 , 0.61585623, 0.4735154 , 0.4777526 ,
       0.4705976 , 0.7275127 , 0.51013476, 0.67704177, 0.49733633,
       0.7928064 , 0.4837612 , 0.48146406, 0.27381152, 0.37549546,
       0.6030938 , 0.5595552 , 0.52854264, 0.4562693 , 0.5215421 ,
       0.41697115, 0.44651425, 0.54276603, 0.6916971 , 0.61279   ,
       0.34729627, 0.65870607, 0.3626337 , 0.26203585, 0.21551855,
       0.93230385, 0.48761153, 0.49400488, 0.36917618, 0.5001667 ,
       0.41363016, 0.4208544 , 0.41909575, 0.4440157 ], dtype=float32), array([[[[ 1.45851346e-02],
         [-7.09491894e-02],
         [ 7.00787455e-02],
         [ 6.22255579e-02],
         [ 8.51586089e-02],
         [-8.67003351e-02],
         [-4.94192950e-02],
         [-1.13182580e-02],
         [-3.01562026e-02],
         [-1.95204914e-02],
         [ 3.93967517e-02],
         [ 6.41283169e-02],
         [ 1.48835713e-02],
         [-3.89734022e-02],
         [-7.84242228e-02],
         [-6.91711232e-02],
         [-3.05850971e-02],
         [ 5.75741474e-03],
         [-5.36308996e-03],
         [ 5.48001118e-02],
         [ 2.83206068e-02],
         [ 8.90637040e-02],
         [ 4.35592383e-02],
         [-9.62305535e-03],
         [-6.07676618e-02],
         [ 7.77979791e-02],
         [ 3.13154645e-02],
         [-9.78436992e-02],
         [-4.50557806e-02],
         [-7.73950294e-02],
         [-6.20370358e-03],
         [-6.51745573e-02],
         [-4.67017703e-02],
         [-8.74067768e-02],
         [ 6.45171553e-02],
         [-4.55882028e-02],
         [-2.74866391e-02],
         [ 7.50520965e-03],
         [ 1.68569107e-02],
         [-1.06649905e-01],
         [-5.77322096e-02],
         [-8.74877647e-02],
         [ 4.36103828e-02],
         [ 1.11391330e-02],
         [-7.28487000e-02],
         [-3.15847597e-03],
         [-3.75049300e-02],
         [ 2.91978219e-03],
         [ 8.90920907e-02],
         [ 1.05514722e-02],
         [ 2.28303019e-02],
         [ 9.40881148e-02],
         [-2.46843714e-02],
         [ 3.84803265e-02],
         [-2.86459979e-02],
         [-3.27838659e-02],
         [-4.79111746e-02],
         [-1.01234436e-01],
         [ 2.19844282e-03],
         [-6.57943487e-02],
         [ 2.00362019e-02],
         [-6.81891143e-02],
         [-7.81894773e-02],
         [ 5.74239641e-02]],

        [[ 2.41349731e-02],
         [-1.31223379e-02],
         [ 8.60626101e-02],
         [-1.44806961e-02],
         [ 5.58487251e-02],
         [ 8.18279982e-02],
         [-1.17661089e-01],
         [-2.79328115e-02],
         [-7.16357678e-02],
         [ 6.01334572e-02],
         [ 9.74868312e-02],
         [ 4.84442972e-02],
         [-1.19265048e-02],
         [ 4.73469421e-02],
         [ 5.99045232e-02],
         [-5.47737442e-02],
         [-6.44710287e-02],
         [ 4.02228050e-02],
         [-5.62175475e-02],
         [ 2.37383712e-02],
         [-6.54911157e-03],
         [ 7.20063001e-02],
         [ 5.40266670e-02],
         [-4.32584397e-02],
         [ 6.02830201e-02],
         [ 9.41959247e-02],
         [ 9.18323398e-02],
         [-7.90573061e-02],
         [ 4.96963672e-02],
         [ 4.93565947e-02],
         [-6.00830559e-03],
         [-5.44361845e-02],
         [-6.45518303e-02],
         [-7.99032450e-02],
         [-1.81547310e-02],
         [-2.59271041e-02],
         [ 1.50311450e-02],
         [ 4.63181995e-02],
         [ 2.64424682e-02],
         [-8.95168036e-02],
         [-5.44987805e-02],
         [-5.81778437e-02],
         [ 5.92897423e-02],
         [-8.20133239e-02],
         [ 3.11409496e-02],
         [-6.52384982e-02],
         [ 1.22015312e-01],
         [ 9.99599695e-02],
         [ 5.16392812e-02],
         [ 2.68819891e-02],
         [ 1.82599127e-02],
         [-7.40109533e-02],
         [-6.65988550e-02],
         [ 9.14234370e-02],
         [ 1.55449435e-02],
         [-3.46044563e-02],
         [ 1.32280933e-02],
         [-2.76641008e-02],
         [ 5.94586842e-02],
         [ 3.50743011e-02],
         [ 1.07934482e-01],
         [ 3.49133648e-02],
         [ 8.96042064e-02],
         [ 9.57693681e-02]],

        [[-4.86493260e-02],
         [ 7.77009875e-02],
         [ 8.25225115e-02],
         [-4.65679588e-03],
         [-5.37092658e-03],
         [-6.62693661e-03],
         [-5.28588183e-02],
         [-3.51178534e-02],
         [ 5.69571294e-02],
         [ 1.08535759e-01],
         [ 7.43366256e-02],
         [ 6.04589134e-02],
         [-3.14422399e-02],
         [-3.46572436e-02],
         [ 5.99422865e-03],
         [ 5.84479421e-02],
         [ 1.44714611e-02],
         [ 9.45075303e-02],
         [ 4.52584326e-02],
         [ 8.27563331e-02],
         [ 7.38577321e-02],
         [ 6.97388500e-02],
         [ 2.90556392e-03],
         [-3.88444811e-02],
         [-1.14908025e-01],
         [-7.33943135e-02],
         [-5.43066822e-02],
         [-9.15837847e-03],
         [-4.05891202e-02],
         [ 8.14561546e-02],
         [ 8.02510232e-02],
         [-1.45139834e-02],
         [-3.68597545e-02],
         [ 2.38082800e-02],
         [ 1.28218234e-02],
         [-5.67364693e-02],
         [-4.40345379e-03],
         [-2.80501600e-02],
         [ 2.39802655e-02],
         [ 4.18312475e-02],
         [ 6.56089410e-02],
         [ 7.07480088e-02],
         [ 4.74123433e-02],
         [-6.48156404e-02],
         [-4.23530117e-03],
         [ 9.11894664e-02],
         [ 2.25707199e-02],
         [ 1.87487621e-02],
         [-8.22111666e-02],
         [ 5.91288507e-02],
         [-5.23300469e-02],
         [-5.00858873e-02],
         [-8.36701319e-02],
         [-8.23835470e-03],
         [-2.59005912e-02],
         [-6.15529418e-02],
         [-8.03730711e-02],
         [ 1.80320125e-02],
         [-8.16041231e-02],
         [-7.14677572e-02],
         [ 5.42428903e-03],
         [ 4.19667289e-02],
         [ 5.77668399e-02],
         [-1.24609598e-03]]],


       [[[-2.91672107e-02],
         [ 9.92126390e-02],
         [-6.55679405e-02],
         [-8.83261636e-02],
         [ 4.45724055e-02],
         [ 1.96805922e-03],
         [ 2.08819453e-02],
         [ 5.94483763e-02],
         [-9.97259188e-03],
         [-3.47282700e-02],
         [ 8.50509405e-02],
         [-4.54738289e-02],
         [-6.59259036e-02],
         [ 6.44416139e-02],
         [-9.89713445e-02],
         [-7.60602131e-02],
         [ 3.66120934e-02],
         [ 7.53424317e-02],
         [ 3.02412063e-02],
         [-7.74414316e-02],
         [-1.02684215e-01],
         [ 1.21808462e-02],
         [-4.63371202e-02],
         [ 8.79838616e-02],
         [-1.82807837e-02],
         [ 7.47038200e-02],
         [-8.19418132e-02],
         [ 4.19751033e-02],
         [-1.07123248e-01],
         [-7.51314014e-02],
         [ 1.11742027e-01],
         [-3.39083709e-02],
         [-6.14283122e-02],
         [ 6.45370111e-02],
         [-9.34635326e-02],
         [ 1.84550043e-02],
         [-4.28435014e-05],
         [ 4.78250273e-02],
         [-3.11465338e-02],
         [ 8.94079264e-03],
         [-1.51242027e-02],
         [-3.44329588e-02],
         [-8.86397660e-02],
         [ 2.68888306e-02],
         [ 4.14087437e-02],
         [ 6.62287101e-02],
         [ 1.43478969e-02],
         [-6.17964193e-02],
         [ 5.16764075e-02],
         [-3.22136376e-03],
         [ 3.37383710e-02],
         [ 2.17787363e-02],
         [ 6.68189004e-02],
         [-2.84339208e-02],
         [-5.93963079e-02],
         [-7.79919103e-02],
         [-4.89797629e-02],
         [-3.32966819e-02],
         [ 3.36511545e-02],
         [-9.85255390e-02],
         [ 9.31100082e-03],
         [-7.70061836e-02],
         [ 6.47736192e-02],
         [-7.12597445e-02]],

        [[-7.00138658e-02],
         [-7.21731558e-02],
         [-6.71782196e-02],
         [-7.61671290e-02],
         [-8.44392180e-02],
         [-6.94355816e-02],
         [-6.43440112e-02],
         [-5.88637441e-02],
         [ 5.88665158e-02],
         [-4.88790832e-02],
         [ 1.40765653e-04],
         [-1.10005485e-02],
         [-7.66193196e-02],
         [-3.98255773e-02],
         [-4.49197106e-02],
         [-1.47528369e-02],
         [ 5.78189604e-02],
         [ 9.01131853e-02],
         [-2.78905146e-02],
         [ 5.64318411e-02],
         [-8.75577796e-03],
         [-6.76915348e-02],
         [ 1.50597538e-03],
         [-6.00784048e-02],
         [-8.20702091e-02],
         [-2.80973949e-02],
         [ 2.18776111e-02],
         [-5.47845801e-03],
         [ 2.55628247e-02],
         [ 1.06828995e-01],
         [ 5.63642532e-02],
         [ 1.84512930e-03],
         [ 5.46540245e-02],
         [ 6.52087200e-03],
         [-9.89204347e-02],
         [-4.30929661e-02],
         [-2.63319705e-02],
         [-5.55948503e-02],
         [-3.25504616e-02],
         [ 1.27328951e-02],
         [ 6.50591031e-02],
         [ 2.40867361e-02],
         [-1.09167378e-02],
         [ 7.13658556e-02],
         [ 8.91881734e-02],
         [-2.48791985e-02],
         [-7.04548880e-02],
         [-5.86080886e-02],
         [-1.00546964e-01],
         [-8.85854512e-02],
         [ 2.23735515e-02],
         [-8.72874781e-02],
         [ 4.58007343e-02],
         [-8.26398134e-02],
         [-5.01013920e-02],
         [-6.58514351e-02],
         [-6.80357590e-02],
         [-1.14238463e-01],
         [ 7.73794204e-02],
         [-9.58665274e-03],
         [ 7.67060206e-04],
         [-5.82970120e-02],
         [ 2.39839498e-02],
         [-3.13558336e-03]],

        [[ 7.13004125e-03],
         [ 2.53966432e-02],
         [-3.03249303e-02],
         [-6.80848807e-02],
         [-6.46320507e-02],
         [ 5.86646311e-02],
         [ 4.25832346e-02],
         [-1.47197181e-02],
         [-3.99374366e-02],
         [ 6.20117411e-02],
         [-3.17276083e-02],
         [-3.43862660e-02],
         [ 2.41742600e-02],
         [ 6.92291139e-03],
         [-2.95896232e-02],
         [-3.78459282e-02],
         [ 1.63758416e-02],
         [ 6.23942353e-02],
         [-4.65436690e-02],
         [-8.01064670e-02],
         [-2.85060108e-02],
         [ 2.08298359e-02],
         [-2.31961086e-02],
         [-1.22916326e-02],
         [ 4.51150611e-02],
         [ 2.30579302e-02],
         [-2.80831959e-02],
         [ 7.35237151e-02],
         [-2.67148893e-02],
         [ 6.71022311e-02],
         [ 5.55121861e-02],
         [ 9.96685922e-02],
         [ 5.56112453e-02],
         [-7.11292252e-02],
         [ 1.86205823e-02],
         [ 4.01445962e-02],
         [ 8.73507708e-02],
         [ 6.19889572e-02],
         [ 3.30547728e-02],
         [-7.76377842e-02],
         [ 6.20444864e-02],
         [ 6.38493896e-02],
         [-1.00125000e-01],
         [-2.57131867e-02],
         [ 8.14532712e-02],
         [-3.92224118e-02],
         [ 4.35377769e-02],
         [ 1.18930854e-01],
         [ 8.66958052e-02],
         [ 7.12404326e-02],
         [ 6.84689684e-03],
         [ 9.00011212e-02],
         [ 7.94579610e-02],
         [ 3.32917422e-02],
         [ 5.92314415e-02],
         [ 6.85088560e-02],
         [ 1.05959289e-02],
         [-1.05072267e-01],
         [-3.51244137e-02],
         [-6.61364496e-02],
         [ 8.20021257e-02],
         [-1.78363286e-02],
         [-2.70607844e-02],
         [-4.97883512e-03]]],


       [[[ 8.58194157e-02],
         [ 9.94467139e-02],
         [ 5.75737245e-02],
         [ 3.24124545e-02],
         [-1.14484401e-02],
         [ 7.28345895e-03],
         [-3.41074839e-02],
         [-7.82865956e-02],
         [ 7.02598505e-03],
         [ 2.80104019e-03],
         [-5.23554385e-02],
         [ 3.60149443e-02],
         [ 6.67532906e-02],
         [ 1.00936024e-02],
         [-9.50130373e-02],
         [ 7.61476606e-02],
         [ 2.01074872e-02],
         [ 8.30728039e-02],
         [-5.29692769e-02],
         [ 4.84321527e-02],
         [ 9.34773460e-02],
         [ 7.79642239e-02],
         [ 6.92225248e-02],
         [-7.90721923e-02],
         [ 5.83536588e-02],
         [-2.22456548e-02],
         [ 6.02130368e-02],
         [ 8.10215157e-03],
         [-7.86431059e-02],
         [-1.99418664e-02],
         [ 6.99150786e-02],
         [-2.00245492e-02],
         [ 6.70517981e-02],
         [-5.80042228e-02],
         [-5.74856810e-02],
         [-8.31956491e-02],
         [ 5.57735562e-02],
         [-8.66679251e-02],
         [-2.67330408e-02],
         [ 8.03026259e-02],
         [ 1.70809776e-02],
         [ 4.88385521e-02],
         [-2.67790668e-02],
         [-4.50485107e-03],
         [ 7.47549394e-03],
         [-1.28964679e-02],
         [-1.80911850e-02],
         [ 8.95228609e-02],
         [-5.95591702e-02],
         [ 1.11003350e-02],
         [-1.01822712e-01],
         [-9.31514800e-02],
         [ 2.25228742e-02],
         [-3.58302966e-02],
         [ 7.80851170e-02],
         [ 1.68630052e-02],
         [ 1.43293068e-02],
         [ 6.76160976e-02],
         [ 8.98073688e-02],
         [ 3.34327370e-02],
         [ 3.34569365e-02],
         [-2.94459928e-02],
         [ 6.78527579e-02],
         [ 1.07677691e-01]],

        [[ 1.06962174e-01],
         [-6.56085834e-02],
         [-9.78430435e-02],
         [ 1.08571947e-01],
         [ 3.33485790e-02],
         [ 3.12709808e-02],
         [-6.25699684e-02],
         [-3.31234559e-02],
         [ 7.57121369e-02],
         [-5.86459460e-03],
         [ 6.08206913e-02],
         [-6.97425157e-02],
         [-4.98640463e-02],
         [ 8.78452137e-02],
         [-7.22080395e-02],
         [-1.17180794e-02],
         [-8.80746767e-02],
         [ 9.57750157e-03],
         [-1.00852437e-01],
         [ 6.92433119e-02],
         [-8.78123641e-02],
         [-9.44303870e-02],
         [ 5.65835424e-02],
         [-8.14417377e-02],
         [-1.53752677e-02],
         [ 4.54057716e-02],
         [ 7.08471760e-02],
         [ 4.33116592e-02],
         [ 1.58416387e-02],
         [-7.37189082e-04],
         [-3.18019874e-02],
         [-3.36017832e-02],
         [ 3.40636857e-02],
         [ 3.43713686e-02],
         [ 3.17975096e-02],
         [-2.25937665e-02],
         [ 9.07762498e-02],
         [ 1.32371457e-02],
         [ 9.19453055e-02],
         [ 1.16196852e-02],
         [-5.93206212e-02],
         [-7.46333376e-02],
         [ 1.76918935e-02],
         [-2.28998810e-02],
         [-8.94226208e-02],
         [-9.47493389e-02],
         [-1.00552710e-03],
         [-5.22503480e-02],
         [ 8.37727264e-02],
         [ 3.85818295e-02],
         [ 2.21222006e-02],
         [-8.72950107e-02],
         [ 8.37734789e-02],
         [-3.58325318e-02],
         [ 2.99527403e-02],
         [ 1.14195840e-02],
         [-9.73725989e-02],
         [-2.09256280e-02],
         [ 1.39932111e-02],
         [-9.79926959e-02],
         [-6.75327424e-03],
         [ 7.30666071e-02],
         [ 5.30813374e-02],
         [-3.36250588e-02]],

        [[ 6.85271323e-02],
         [ 5.84586561e-02],
         [-2.40058489e-02],
         [-3.54323797e-02],
         [ 3.97075526e-02],
         [ 1.08109288e-01],
         [-1.76945701e-02],
         [-7.01557919e-02],
         [-1.29329301e-02],
         [ 7.01482743e-02],
         [ 8.08918402e-02],
         [-2.35358234e-02],
         [ 7.93043640e-04],
         [ 4.82924236e-03],
         [-9.30149406e-02],
         [ 7.15772882e-02],
         [ 5.94676100e-02],
         [ 2.38297991e-02],
         [-5.44114225e-02],
         [-6.68311343e-02],
         [ 6.91586286e-02],
         [ 3.62219964e-03],
         [ 3.24453935e-02],
         [ 6.56121150e-02],
         [-6.46865508e-03],
         [ 1.07620373e-01],
         [ 2.75247288e-03],
         [ 7.56656751e-02],
         [-6.12098128e-02],
         [-1.79886371e-02],
         [ 6.81265295e-02],
         [-7.30403960e-02],
         [ 1.35649592e-02],
         [ 8.07669759e-02],
         [ 2.75432635e-02],
         [-8.61740261e-02],
         [-3.93590517e-02],
         [ 6.01908751e-02],
         [-4.65607159e-02],
         [-4.21900526e-02],
         [ 8.87513161e-03],
         [-9.58093151e-04],
         [ 6.85681924e-02],
         [-2.64447853e-02],
         [ 3.80647369e-03],
         [-7.69057274e-02],
         [-5.99849746e-02],
         [-1.07148355e-02],
         [-1.46561526e-02],
         [ 9.88832191e-02],
         [ 2.45087575e-02],
         [ 3.82836685e-02],
         [ 5.54238260e-03],
         [ 8.08249861e-02],
         [ 1.74681246e-02],
         [-9.07611251e-02],
         [-1.18987523e-01],
         [-1.18525334e-01],
         [-1.82271823e-02],
         [ 7.99969882e-02],
         [-1.55580360e-02],
         [ 3.09103057e-02],
         [-7.79571012e-02],
         [ 7.66972005e-02]]]], dtype=float32), array([[[[ 0.06418534, -0.02210188, -0.07092976, ..., -0.06196206,
          -0.02740408,  0.07259986],
         [-0.09392843, -0.10617927,  0.07344745, ...,  0.12111524,
          -0.05085348, -0.0683969 ],
         [ 0.03770376,  0.16779177, -0.05619699, ...,  0.0728545 ,
          -0.15972008, -0.03564404],
         ...,
         [-0.04117445, -0.09980725,  0.006933  , ...,  0.08910838,
           0.13629194, -0.0761272 ],
         [ 0.13830428,  0.05574666, -0.16021937, ...,  0.117677  ,
           0.02448461,  0.17637381],
         [-0.15215167,  0.04731489,  0.15930563, ...,  0.14313443,
           0.05012947,  0.14088212]]]], dtype=float32), array([0.99986124, 1.0001823 , 0.9937394 , 0.99368036, 0.9961738 ,
       1.0135527 , 0.98999774, 1.0159323 , 0.98070264, 0.9980539 ,
       1.005647  , 1.0047346 , 1.0093185 , 1.0157833 , 1.0173268 ,
       1.0214269 , 1.045687  , 1.0015583 , 1.0132507 , 0.98337924,
       0.99762535, 0.985969  , 0.9979625 , 1.003736  , 1.0052655 ,
       1.0041921 , 0.9876711 , 0.9933876 , 0.9832483 , 0.99821055,
       0.9946136 , 0.9952606 , 1.0055306 , 1.0015029 , 0.99251896,
       0.9880302 , 1.015702  , 0.99934626, 1.0122497 , 0.9977518 ,
       1.0144099 , 1.0169446 , 0.99558127, 1.0095599 , 0.9942708 ,
       0.99013793, 0.99455297, 0.99951136, 1.0214461 , 1.0007924 ,
       1.0020031 , 0.98323137, 1.0025675 , 1.0204989 , 1.0333971 ,
       0.99004   , 0.99555504, 0.99006295, 0.9979708 , 0.9862468 ,
       0.9825055 , 0.994669  , 1.0026054 , 0.9928811 , 1.0000039 ,
       1.0194561 , 0.9948049 , 0.96965605, 1.0052109 , 1.0077124 ,
       1.0058897 , 1.0259657 , 0.9943398 , 1.0245552 , 0.98789084,
       0.99150115, 1.0032113 , 0.9955537 , 1.0043585 , 1.0145581 ,
       0.98600227, 0.997334  , 0.9934342 , 1.0027916 , 0.98121226,
       1.0040824 , 1.0070838 , 1.0051041 , 0.991676  , 0.99149305,
       1.0082595 , 1.0106493 , 0.98717   , 0.98518735, 0.9849322 ,
       0.984957  , 1.0118299 , 1.0170168 , 0.98220706, 1.0026633 ,
       0.99674743, 1.0098455 , 1.0070021 , 1.0167811 , 0.9975313 ,
       0.9955993 , 1.0004685 , 0.99716264, 1.0074279 , 0.9936194 ,
       0.99779105, 1.0216899 , 0.9960322 , 0.9852319 , 1.0090301 ,
       1.0222751 , 0.9930552 , 1.0123683 , 0.98972803, 1.0097628 ,
       1.0072409 , 1.0029737 , 0.987517  , 0.9864065 , 1.0088143 ,
       1.01295   , 1.0234298 , 1.0022709 ], dtype=float32), array([-6.91788644e-03,  1.02688074e-02,  1.79162819e-03, -1.01328762e-02,
       -3.41987261e-03, -1.64864343e-02, -6.59365533e-03,  1.70555264e-02,
       -3.06912302e-03, -5.85556263e-03,  1.42054986e-02,  2.47255117e-02,
       -1.20692626e-02,  3.05188801e-02, -1.81427263e-02,  1.27941612e-02,
       -7.14809401e-03,  1.88733600e-02,  1.15038753e-02, -9.49181523e-03,
       -1.31714884e-02,  6.75655622e-03, -7.86685478e-03,  1.88468453e-02,
        8.07627942e-03, -4.08479646e-02, -1.43671650e-02, -2.31732819e-02,
        4.04312275e-03,  7.59103685e-04, -7.09606614e-03, -1.68459304e-02,
       -9.14709643e-03, -1.38738016e-02, -8.23497865e-03, -7.84562342e-03,
        3.37286061e-03, -2.86224093e-02,  6.53529633e-03, -1.37004275e-02,
        7.58733461e-03,  1.08034806e-02, -1.13778627e-02,  1.98472408e-03,
       -2.00417396e-02,  1.03144697e-03,  3.03032598e-03,  7.21948966e-03,
        2.83282883e-02,  1.33807007e-02, -2.30209567e-02, -1.49781508e-02,
       -2.56079365e-03, -1.02705183e-02,  2.32416540e-02, -2.25987565e-02,
       -5.62344352e-03,  6.90493360e-03, -2.28380132e-02, -1.74532179e-02,
       -1.90696884e-02, -6.44195359e-03,  6.44522486e-04, -3.34434607e-03,
        6.88544149e-03,  3.11398339e-02, -9.52455960e-03, -2.95519847e-02,
        1.70388464e-02,  1.84415374e-02, -5.39071253e-03, -1.71510577e-02,
        1.17666461e-03,  2.16664337e-02, -1.41192265e-02, -5.14051598e-03,
       -3.98948602e-02, -1.39571643e-02,  2.76926886e-02,  3.00142784e-02,
       -5.88774262e-03,  1.03206286e-04, -6.60951575e-03, -9.33255907e-03,
       -8.43447912e-03, -2.73976494e-02, -7.36480625e-03, -5.80784981e-04,
        1.45985512e-02, -5.68670873e-03,  5.38333738e-03,  1.21147430e-03,
       -1.75634418e-02, -3.20566725e-03, -1.14959721e-02, -1.15485508e-02,
        6.99665817e-03,  1.16965054e-02,  8.66647635e-04,  2.72820378e-03,
       -2.96495366e-03, -2.38516908e-02, -9.74986982e-03,  1.68564599e-02,
       -2.75986530e-02, -3.82629782e-03,  6.56773569e-03, -5.66983968e-03,
        3.06618847e-02, -7.67486449e-03, -3.73529177e-03,  3.13558336e-03,
       -2.60139164e-02, -1.76303908e-02,  1.51151344e-02,  9.96471499e-05,
       -7.92926457e-03, -1.23640813e-04, -7.57209840e-04,  1.50240259e-02,
        1.42455045e-02, -1.24227833e-02, -1.19005535e-02, -1.59734394e-02,
       -3.62181365e-02,  7.22343801e-03, -2.94959173e-02, -1.21395523e-02],
      dtype=float32), array([-0.01027308,  0.12001525,  0.01094467, -0.00257624,  0.01999587,
        0.11064171, -0.09055879,  0.01053029, -0.00971408,  0.00686053,
        0.05152332, -0.03122949,  0.02066823,  0.0236022 , -0.0382162 ,
        0.03340717,  0.00168724,  0.00668983, -0.04138393,  0.03146535,
        0.04443001,  0.05178651,  0.00390031, -0.0003783 ,  0.01162352,
        0.11921851,  0.0011072 ,  0.04928462, -0.09167002, -0.01362896,
        0.02652374,  0.03662623,  0.04151268,  0.05624589, -0.0220158 ,
       -0.08415443,  0.03044318,  0.03288881,  0.02218582, -0.00614035,
       -0.02079174, -0.01724285, -0.00300617, -0.02119778,  0.02342754,
        0.01248212,  0.0246408 , -0.02126268, -0.06297465, -0.01566753,
        0.03346272,  0.00076471,  0.00680804,  0.04441391, -0.13170338,
        0.0027232 , -0.008006  , -0.04744601,  0.01913809, -0.01542259,
       -0.06058981, -0.03004414,  0.08709279,  0.07374027,  0.04772334,
       -0.06393712, -0.04679469,  0.01704771,  0.02184981, -0.04235923,
       -0.00518847,  0.11268491, -0.01835235,  0.05353304, -0.11027262,
       -0.03797044,  0.00869183,  0.00788837, -0.02528456, -0.04745083,
       -0.01368829,  0.00763491,  0.01060489, -0.02766903, -0.07081454,
        0.00377728,  0.09193863,  0.06941562,  0.05257672, -0.00460306,
       -0.02512701,  0.10878621,  0.02390851,  0.03954785,  0.0141765 ,
       -0.01203736, -0.08979879, -0.0417273 ,  0.02800202,  0.0120485 ,
       -0.06057758, -0.01229598,  0.04259705, -0.04151796,  0.05765416,
        0.0687244 , -0.06748562,  0.03715202,  0.04279958,  0.06453872,
        0.15258813, -0.00268417,  0.06006428,  0.04316728,  0.01091083,
        0.08308534, -0.03510166,  0.01207009,  0.06276518, -0.01412277,
        0.03021127,  0.0484082 , -0.09197544,  0.00291957,  0.11892211,
        0.01467327,  0.0365743 ,  0.08940282], dtype=float32), array([0.09050787, 0.0917585 , 0.08914102, 0.08498029, 0.09143752,
       0.09672239, 0.09415814, 0.08481853, 0.08692413, 0.09541958,
       0.08744743, 0.08809203, 0.09616125, 0.08477184, 0.08382854,
       0.09244338, 0.08932924, 0.09007388, 0.10383311, 0.08922766,
       0.08608851, 0.08932066, 0.08594751, 0.09021558, 0.083288  ,
       0.10926592, 0.08404723, 0.09251027, 0.09203735, 0.1008502 ,
       0.08348838, 0.09016467, 0.08445086, 0.08528167, 0.08714039,
       0.09302384, 0.08486342, 0.09250179, 0.08510182, 0.08349723,
       0.09554632, 0.08452681, 0.08689468, 0.08690035, 0.08514407,
       0.08388299, 0.08759769, 0.0882782 , 0.09066579, 0.09394851,
       0.08435529, 0.08477315, 0.09872708, 0.08838497, 0.10008784,
       0.08667997, 0.08523178, 0.08911948, 0.08924463, 0.08681621,
       0.08611895, 0.08695747, 0.09418475, 0.09214497, 0.08666863,
       0.09841647, 0.08710099, 0.08678295, 0.08852853, 0.08888   ,
       0.08798767, 0.09673291, 0.09815765, 0.09520054, 0.09175609,
       0.08946959, 0.08937029, 0.08921942, 0.08487613, 0.10943236,
       0.09077685, 0.08797337, 0.0857188 , 0.09029248, 0.08734997,
       0.08474162, 0.09314485, 0.08577121, 0.08556548, 0.09035464,
       0.09212365, 0.0985145 , 0.09360029, 0.08365264, 0.08510471,
       0.08335466, 0.09179506, 0.10081469, 0.08575348, 0.08804806,
       0.09014648, 0.08463023, 0.08612425, 0.09219902, 0.09094977,
       0.08887116, 0.0973324 , 0.08598948, 0.08998328, 0.09067883,
       0.10542203, 0.08586638, 0.08908844, 0.08618092, 0.09194481,
       0.08755895, 0.08548425, 0.09207465, 0.08469258, 0.08467476,
       0.09065449, 0.08472056, 0.09328924, 0.08892627, 0.10031765,
       0.08618496, 0.0885849 , 0.09821062], dtype=float32), array([[[[-0.04873934],
         [-0.03001213],
         [-0.02512937],
         ...,
         [ 0.07879747],
         [ 0.02818117],
         [ 0.01251972]],

        [[ 0.01492926],
         [-0.06860552],
         [-0.02207569],
         ...,
         [ 0.07117789],
         [ 0.03813791],
         [-0.04053863]],

        [[ 0.01470821],
         [-0.0135055 ],
         [ 0.04397482],
         ...,
         [ 0.01714758],
         [-0.05430909],
         [ 0.06945434]]],


       [[[-0.05377691],
         [ 0.0213938 ],
         [-0.03114984],
         ...,
         [ 0.03676362],
         [-0.05428564],
         [ 0.06719933]],

        [[ 0.06149739],
         [-0.05273988],
         [ 0.06010567],
         ...,
         [-0.05329046],
         [-0.02908431],
         [ 0.00839346]],

        [[ 0.03528215],
         [-0.06769048],
         [ 0.04023524],
         ...,
         [ 0.03840291],
         [-0.08231254],
         [ 0.01632265]]],


       [[[-0.04173745],
         [ 0.05723671],
         [ 0.04228947],
         ...,
         [-0.00609556],
         [-0.0831343 ],
         [-0.01088979]],

        [[-0.06209961],
         [ 0.0518676 ],
         [ 0.0639921 ],
         ...,
         [ 0.01862866],
         [-0.09248154],
         [ 0.03699109]],

        [[ 0.01357084],
         [-0.01373024],
         [ 0.00333575],
         ...,
         [ 0.03543967],
         [-0.04588273],
         [ 0.04833996]]]], dtype=float32), array([[[[ 0.14545268, -0.1149343 , -0.14495416, ..., -0.12947027,
           0.06597649,  0.06224193],
         [-0.12635033,  0.03586011,  0.0391552 , ...,  0.08608495,
          -0.14954051,  0.0414198 ],
         [ 0.09600654,  0.05436397,  0.03758529, ...,  0.05553903,
          -0.03809495, -0.06428216],
         ...,
         [-0.13640979,  0.0292301 , -0.02259275, ..., -0.11071134,
           0.05861098, -0.02194693],
         [-0.01054372, -0.07991666,  0.02397382, ...,  0.1144712 ,
           0.05345958,  0.13150506],
         [-0.09771445, -0.08027285, -0.12918581, ..., -0.15765408,
           0.13144815,  0.10380023]]]], dtype=float32), array([0.9876193 , 0.99184567, 0.99121773, 1.000578  , 1.0071629 ,
       0.9998896 , 0.99941784, 0.994403  , 0.98044187, 0.9976052 ,
       1.0217377 , 1.0118855 , 0.99548274, 1.0013971 , 1.0161436 ,
       0.99763364, 1.0023836 , 0.97253245, 1.0114588 , 1.0185232 ,
       0.9964606 , 0.99089926, 1.0339291 , 0.9809093 , 0.9869549 ,
       1.012674  , 1.0088588 , 1.0079037 , 1.0045782 , 0.98491776,
       0.9927252 , 0.99766976, 1.0003425 , 1.0062329 , 1.0096166 ,
       0.98582536, 1.0013837 , 1.0262709 , 0.9981478 , 0.9780628 ,
       0.9965501 , 0.9967341 , 0.98733073, 0.99269104, 1.0050315 ,
       1.0034097 , 0.99677455, 0.9879984 , 0.9977087 , 1.0164568 ,
       1.0003664 , 0.9865528 , 0.980365  , 1.0199062 , 1.0081217 ,
       0.9882895 , 0.9815476 , 0.99493843, 0.999475  , 1.0157835 ,
       1.0013847 , 1.0033406 , 1.010627  , 0.9884148 , 1.0131176 ,
       1.0032299 , 0.9952654 , 1.00038   , 0.99097747, 1.0157115 ,
       0.9967761 , 0.969537  , 1.0195414 , 0.99102575, 1.0016544 ,
       1.0062706 , 1.0022513 , 0.98903584, 1.022897  , 0.99529356,
       1.0115947 , 0.9733026 , 1.0013828 , 0.991216  , 0.9961523 ,
       0.98778486, 1.0190607 , 1.0113413 , 1.000438  , 0.9955672 ,
       0.9822729 , 0.98859143, 1.020473  , 1.0181346 , 0.9960215 ,
       0.98539746, 0.9870917 , 0.99279326, 0.9971677 , 0.98944414,
       1.0132983 , 1.0061784 , 1.0074962 , 1.009584  , 0.9851362 ,
       1.0006217 , 0.9831564 , 1.001614  , 0.9888557 , 0.9938146 ,
       0.99086773, 1.0032974 , 0.98888624, 1.000061  , 1.0234069 ,
       1.0199279 , 1.0000563 , 0.99479127, 1.0142324 , 0.98920965,
       0.97568715, 1.0151448 , 0.98270196, 0.99914855, 1.0146205 ,
       0.98471713, 0.98531866, 0.9942121 ], dtype=float32), array([-1.2506538e-02,  2.1635299e-03, -1.2075927e-02,  3.1418914e-03,
       -1.7225945e-02, -2.0920362e-02, -1.6628431e-02,  1.2666420e-02,
        4.5119277e-03,  3.7508521e-03, -1.7757878e-02,  4.0461444e-03,
        9.7130341e-03,  1.9875653e-03, -2.9657930e-03, -1.0735206e-02,
       -1.8515190e-02,  4.4958987e-03, -2.3247458e-02,  8.5452655e-03,
       -1.6729070e-02, -3.6090913e-03,  3.6934420e-02, -1.0431836e-02,
        1.0688543e-02,  1.3119157e-03, -8.6018973e-04, -9.4264057e-03,
       -4.1996306e-03, -2.1462481e-02, -2.0201676e-02, -9.0543292e-03,
       -7.4379984e-03, -1.0440819e-03, -9.6275005e-04,  4.8771827e-03,
        5.7029040e-03, -2.4449058e-02, -2.1844016e-02, -4.0200334e-02,
       -5.8636172e-03, -1.5608529e-02,  1.2650032e-02, -2.3685792e-03,
       -4.0577003e-03,  4.4038543e-03, -6.6647721e-03, -6.9565042e-03,
       -4.8476565e-03, -9.2449524e-03,  3.6248940e-03, -8.1991646e-03,
       -3.9984444e-03, -2.6622161e-02,  1.9829089e-02, -2.3677906e-02,
       -5.9766057e-03, -5.1394179e-03, -1.1258860e-02,  1.0500452e-02,
       -7.9085734e-03,  1.2724007e-04,  2.7576794e-03,  1.6142923e-02,
        1.7654065e-02,  8.7137939e-03, -1.9692896e-02, -2.8550779e-03,
        2.8291613e-02, -7.9289703e-03, -1.2192315e-02, -3.0425720e-02,
       -7.6491865e-03, -1.9051335e-05, -8.4839454e-03, -2.4672762e-02,
       -1.2321081e-02, -3.5575572e-02, -6.7101666e-03, -4.7565586e-04,
       -1.6142391e-02, -2.6947497e-03, -4.8053917e-03, -1.2311540e-02,
       -2.2773510e-02, -1.2576567e-02,  8.1220251e-03, -9.6358573e-03,
       -3.2988656e-02, -1.0330154e-02,  2.6554321e-03, -8.0413166e-03,
        1.8401874e-02,  3.5196319e-03,  3.3942594e-03, -4.0348670e-03,
        1.3232929e-02, -2.1753756e-02,  7.2411881e-03,  1.7999205e-03,
       -4.1534249e-03, -3.3519727e-03, -3.6149726e-03,  6.8358104e-03,
        9.1483109e-03,  1.2274981e-02,  8.7160077e-03, -3.4559786e-03,
        5.5821775e-03,  2.4174731e-03, -1.7464601e-02, -1.9961769e-02,
        6.5217912e-03,  1.8087467e-03,  1.0649215e-02, -1.7404990e-02,
       -3.2325763e-02,  7.9617760e-04, -4.1694508e-04,  2.0811275e-02,
       -5.4910551e-03, -2.1932308e-02, -4.0335217e-03, -2.5571750e-03,
       -8.7895440e-03, -1.5017551e-02,  8.4860940e-03,  1.9210553e-02],
      dtype=float32), array([-0.01163319, -0.01777064,  0.0098412 , -0.07654915, -0.00741468,
        0.02560001, -0.01594632,  0.02780763, -0.04062425,  0.06482976,
       -0.0618445 ,  0.00575686,  0.00130965,  0.06597658, -0.02946112,
        0.01068315, -0.01745141, -0.00206581,  0.04067932, -0.0421124 ,
        0.07953281, -0.0162798 , -0.08786651,  0.06834759,  0.05027026,
       -0.11047497, -0.00892446,  0.0794244 , -0.01318335,  0.05402734,
        0.05862032, -0.00242572, -0.01488946,  0.06716571, -0.011766  ,
        0.00557832, -0.02965662, -0.0488066 , -0.00852832,  0.02478849,
        0.05739608,  0.05275049, -0.04432551, -0.02491859, -0.00541216,
        0.04497426,  0.05742645,  0.06605534,  0.02437839,  0.0426436 ,
       -0.02591987, -0.07933668, -0.05268828, -0.00200451,  0.0074722 ,
        0.06292076,  0.00239028, -0.02383442, -0.02361141,  0.00661974,
        0.00890321, -0.03577441,  0.04312061, -0.05992278,  0.03862386,
        0.09407364, -0.04734738,  0.07903096, -0.00479888, -0.04090024,
       -0.0664684 ,  0.07985713,  0.05788595,  0.08022016,  0.06608548,
       -0.06592315, -0.03819156,  0.07993796,  0.02429762,  0.05533808,
        0.04339562, -0.03236873, -0.02839869,  0.11454384, -0.00917292,
        0.0292453 ,  0.03102972,  0.00221717,  0.04854747, -0.08232582,
       -0.00433452,  0.0787297 , -0.01103424,  0.00357722, -0.05419232,
       -0.13511872, -0.01444324,  0.02578887, -0.04636942,  0.04583384,
       -0.00633379,  0.09136836,  0.02932784, -0.04685629,  0.01630924,
       -0.08543842, -0.01093117, -0.00661036,  0.00196943,  0.02245366,
        0.02788241,  0.03533718, -0.02575297, -0.02617207,  0.04449331,
        0.01149331,  0.09452787,  0.08616421,  0.0035634 ,  0.06071575,
       -0.0845631 ,  0.07069593, -0.04730998, -0.05212347,  0.02441165,
       -0.02387311,  0.00940536, -0.0840494 ], dtype=float32), array([0.08709488, 0.09186769, 0.09487051, 0.08855084, 0.08543154,
       0.08554777, 0.08434378, 0.09515431, 0.08460948, 0.09933572,
       0.09128544, 0.08701814, 0.09453374, 0.09073596, 0.08897521,
       0.0853478 , 0.09020428, 0.09080726, 0.09177379, 0.0919756 ,
       0.10284703, 0.08649487, 0.09675231, 0.08830661, 0.08759374,
       0.09007999, 0.0907203 , 0.0939011 , 0.09378693, 0.08943743,
       0.08931817, 0.08994984, 0.09065302, 0.09014226, 0.10155643,
       0.08660573, 0.08871733, 0.08556407, 0.08367778, 0.09519088,
       0.09474996, 0.10033012, 0.08471282, 0.09145361, 0.09561161,
       0.09210717, 0.08769961, 0.09173869, 0.08565535, 0.0887017 ,
       0.08712149, 0.10102063, 0.09654304, 0.09197751, 0.09483478,
       0.08883657, 0.08732391, 0.10267821, 0.09420221, 0.08844472,
       0.08555394, 0.0969269 , 0.09989386, 0.09031292, 0.08866747,
       0.09055337, 0.08775745, 0.09500235, 0.08722983, 0.08374184,
       0.10177158, 0.09978974, 0.09329977, 0.08763605, 0.08628224,
       0.09065601, 0.09436885, 0.08735323, 0.09856879, 0.09315346,
       0.0967793 , 0.08665284, 0.09441233, 0.09597031, 0.09464076,
       0.0946206 , 0.09543195, 0.08602002, 0.08975179, 0.08876424,
       0.08641052, 0.08820873, 0.08910979, 0.08662048, 0.11149203,
       0.09925558, 0.09108398, 0.08649245, 0.09072839, 0.08766991,
       0.08623686, 0.09519973, 0.09187813, 0.08788303, 0.08809108,
       0.09030797, 0.08786595, 0.08918122, 0.09324069, 0.08648671,
       0.09786248, 0.08995958, 0.08759189, 0.08757892, 0.09020966,
       0.09310714, 0.09971422, 0.08480334, 0.08760712, 0.09263401,
       0.08731323, 0.09274368, 0.08516396, 0.09818693, 0.09071797,
       0.09338046, 0.08976641, 0.08956831], dtype=float32), array([[[[ 0.12942629, -0.10897984, -0.05724277, ..., -0.06798004,
          -0.10794454, -0.07317284],
         [-0.03310473, -0.08613043,  0.0487051 , ...,  0.10463955,
          -0.09048666,  0.13899972],
         [-0.09677933, -0.12876853, -0.02048804, ...,  0.01913343,
          -0.10545963, -0.0902391 ],
         ...,
         [-0.00511356, -0.1718288 , -0.03998976, ...,  0.09137902,
           0.12142166, -0.06886687],
         [ 0.03366548, -0.15443836, -0.05641896, ...,  0.13329032,
          -0.12392871, -0.19345832],
         [ 0.01678798,  0.07411554, -0.00749372, ...,  0.06471896,
          -0.08305176, -0.06787968]]]], dtype=float32), array([1.0021701 , 0.99298996, 0.9858318 , 0.9946506 , 0.9970222 ,
       1.0120542 , 0.99558693, 0.98882437, 1.003255  , 0.99320006,
       0.99421525, 0.9893004 , 1.0035876 , 1.0159756 , 1.0011066 ,
       1.0039915 , 0.9861813 , 1.0106044 , 0.99666595, 0.9755196 ,
       1.0212514 , 1.0012703 , 1.0140201 , 1.0056677 , 0.997773  ,
       1.0061852 , 1.0011677 , 0.9894614 , 0.9961887 , 1.006387  ,
       0.9933959 , 0.9899379 , 1.001001  , 1.0027196 , 0.99208695,
       1.0101397 , 0.99379355, 0.9980042 , 1.0064175 , 1.0129138 ,
       0.99808246, 1.0201806 , 1.0057064 , 1.0142281 , 1.0073724 ,
       1.0011206 , 0.9888846 , 0.9913695 , 0.9901727 , 0.99951833,
       0.99529123, 0.9878652 , 1.0073327 , 1.0195125 , 1.0291779 ,
       0.9952388 , 1.0152638 , 1.0032947 , 1.0151778 , 1.0111806 ,
       0.98092306, 0.9822644 , 1.0077219 , 0.99816996, 1.0031538 ,
       1.0063684 , 1.0097588 , 0.99979746, 1.0233816 , 1.0071427 ,
       0.9889641 , 0.9977268 , 1.0191122 , 0.99369794, 0.9854102 ,
       0.9970007 , 0.981517  , 0.9961858 , 1.0094506 , 0.99724513,
       0.9827535 , 1.0198818 , 1.0044773 , 1.0262918 , 1.0140961 ,
       0.9889994 , 1.003449  , 1.008109  , 0.9931701 , 0.98808557,
       1.0091652 , 1.0003227 , 1.0128956 , 0.9763541 , 1.0151477 ,
       1.0140393 , 1.0124748 , 0.9929831 , 1.0217904 , 1.0059938 ,
       1.006453  , 0.99037033, 1.0065619 , 1.0074809 , 0.97530437,
       1.032152  , 1.0219591 , 1.002813  , 1.011603  , 1.009389  ,
       1.0034294 , 1.0080935 , 1.0063999 , 0.9963266 , 0.9776609 ,
       1.003373  , 1.0132024 , 1.0089127 , 0.99126154, 0.983372  ,
       1.0003866 , 1.0055885 , 1.0048476 , 1.0062354 , 0.9867493 ,
       0.9930696 , 0.99574345, 1.0227633 ], dtype=float32), array([-1.25065502e-02,  2.16353149e-03, -1.20759131e-02,  3.14188632e-03,
       -1.72259919e-02, -2.09203772e-02, -1.66284312e-02,  1.26664117e-02,
        4.51196777e-03,  3.75085138e-03, -1.77578889e-02,  4.04612301e-03,
        9.71303973e-03,  1.98758719e-03, -2.96583213e-03, -1.07352138e-02,
       -1.85151640e-02,  4.49590618e-03, -2.32473928e-02,  8.54526833e-03,
       -1.67290680e-02, -3.60909151e-03,  3.69344205e-02, -1.04318401e-02,
        1.06885582e-02,  1.31193362e-03, -8.60219297e-04, -9.42644104e-03,
       -4.19961754e-03, -2.14624647e-02, -2.02016793e-02, -9.05431900e-03,
       -7.43799191e-03, -1.04407012e-03, -9.62751510e-04,  4.87717986e-03,
        5.70289930e-03, -2.44490523e-02, -2.18440257e-02, -4.02003452e-02,
       -5.86363021e-03, -1.56085324e-02,  1.26500502e-02, -2.36857194e-03,
       -4.05770447e-03,  4.40384448e-03, -6.66477391e-03, -6.95654284e-03,
       -4.84764529e-03, -9.24495328e-03,  3.62488278e-03, -8.19915161e-03,
       -3.99843929e-03, -2.66221557e-02,  1.98291000e-02, -2.36779135e-02,
       -5.97660383e-03, -5.13940863e-03, -1.12588769e-02,  1.05004515e-02,
       -7.90858455e-03,  1.27242587e-04,  2.75767478e-03,  1.61429066e-02,
        1.76540520e-02,  8.71381443e-03, -1.96928475e-02, -2.85507902e-03,
        2.82916110e-02, -7.92895816e-03, -1.21923070e-02, -3.04257218e-02,
       -7.64919864e-03, -1.90461615e-05, -8.48395936e-03, -2.46727392e-02,
       -1.23211360e-02, -3.55755873e-02, -6.71015866e-03, -4.75662091e-04,
       -1.61423869e-02, -2.69476185e-03, -4.80538374e-03, -1.23115517e-02,
       -2.27735471e-02, -1.25765689e-02,  8.12202413e-03, -9.63587873e-03,
       -3.29886600e-02, -1.03301676e-02,  2.65543908e-03, -8.04132223e-03,
        1.84018686e-02,  3.51964752e-03,  3.39396577e-03, -4.03487030e-03,
        1.32329315e-02, -2.17537526e-02,  7.24118855e-03,  1.79991138e-03,
       -4.15340485e-03, -3.35196778e-03, -3.61513090e-03,  6.83581689e-03,
        9.14835464e-03,  1.22749796e-02,  8.71602818e-03, -3.45598091e-03,
        5.58215240e-03,  2.41749315e-03, -1.74645931e-02, -1.99617594e-02,
        6.52180379e-03,  1.80874090e-03,  1.06492229e-02, -1.74049735e-02,
       -3.23257558e-02,  7.96246575e-04, -4.16948256e-04,  2.08113026e-02,
       -5.49105834e-03, -2.19323114e-02, -4.03349707e-03, -2.55718944e-03,
       -8.78954772e-03, -1.50175486e-02,  8.48610792e-03,  1.92105640e-02],
      dtype=float32), array([ 1.41909152e-01, -1.92819014e-02,  3.60422693e-02,  4.66629267e-01,
       -2.68881349e-03,  1.60161778e-01, -2.14827836e-01,  8.82964730e-02,
       -2.30377227e-01, -2.77134385e-02,  4.16947365e-01,  1.28796384e-01,
       -1.84421521e-03, -9.50490236e-02,  9.68675986e-02, -8.03105906e-02,
       -5.09130545e-02, -8.94063860e-02,  7.76851550e-02,  7.44911656e-02,
        8.85502920e-02,  2.23077059e-01, -4.85934541e-02,  1.00914121e-01,
        5.92888474e-01, -1.56515986e-02,  1.57304779e-01, -5.14597535e-01,
       -4.09946322e-01, -4.35316473e-01, -1.92245960e-01,  7.28231966e-02,
        2.68283397e-01, -3.11928503e-02, -2.70306051e-01, -1.41301349e-01,
        4.57200080e-01,  9.41794291e-02,  1.55824143e-03,  2.01207563e-01,
        1.03698723e-01, -2.13485196e-01,  1.09937698e-01,  3.54900479e-01,
        6.27708435e-02,  1.87933162e-01, -2.40500900e-03,  9.66468174e-03,
       -3.62115860e-01,  6.28299356e-01,  1.00318529e-02, -4.30715114e-01,
       -1.00889139e-01,  3.01316679e-01,  7.45623186e-02,  2.08380401e-01,
        3.92569192e-02, -2.74401426e-01, -4.21323895e-01, -7.83107132e-02,
       -1.13242768e-01, -2.23772004e-01, -4.19447035e-01,  3.58074605e-02,
        1.10430241e-01, -1.99430525e-01,  2.37426594e-01, -9.60039049e-02,
        4.62112352e-02,  1.35662973e-01,  1.18514955e-01,  1.97955579e-01,
        2.64888316e-01,  1.65330306e-01,  3.45621444e-02,  1.78431004e-01,
        1.09544627e-01, -4.02013570e-01, -3.77142698e-01, -3.26490670e-01,
       -8.53405222e-02,  2.44426042e-01,  3.13366026e-01,  3.89561206e-01,
       -4.49416451e-02, -5.11468500e-02, -6.69441223e-01, -1.46712363e-01,
       -2.45915037e-02,  2.57608056e-01, -5.08521140e-01, -3.49172354e-02,
        5.24577856e-01, -5.98631240e-02,  1.07072406e-01,  1.40974790e-01,
       -3.13549280e-01,  3.39581817e-01,  1.88250661e-01, -2.13790257e-02,
        2.12724209e-01,  1.89400807e-01,  1.30164742e-01, -3.08070242e-01,
        4.73317564e-01, -6.56963885e-01, -1.63643230e-02, -1.05161950e-01,
        3.40677738e-01, -1.64979827e-02, -3.52891628e-04, -2.20094442e-01,
       -1.67828098e-01, -9.06299874e-02, -1.24816690e-02,  2.88493961e-01,
        1.92940831e-01, -3.41916263e-01, -1.36224195e-01,  3.44256386e-02,
       -1.05574004e-01,  2.35413119e-01, -3.93399447e-01,  1.18231021e-01,
        5.39584793e-02, -2.50931710e-01,  2.69304067e-02, -2.22168729e-01],
      dtype=float32), array([0.22408165, 0.28145704, 0.17448713, 0.44099742, 0.31598935,
       0.22463636, 0.20062092, 0.21303506, 0.41150075, 0.39362   ,
       0.3871002 , 0.26712003, 0.38105312, 0.23146193, 0.33408093,
       0.29165804, 0.32225892, 0.24560907, 0.18129994, 0.2910153 ,
       0.25400266, 0.20385633, 0.18265529, 0.3620801 , 0.37273273,
       0.27082622, 0.35941854, 0.2964026 , 0.16026114, 0.44963744,
       0.23357742, 0.4269205 , 0.32392   , 0.5983409 , 0.32105178,
       0.34419876, 0.23887348, 0.21194044, 0.15152302, 0.24677052,
       0.3500119 , 0.3523608 , 0.2657461 , 0.4323955 , 0.41368997,
       0.29050437, 0.49684244, 0.13393588, 0.68052745, 0.24273345,
       0.24570845, 0.29508683, 0.393601  , 0.26874644, 0.19087434,
       0.3706808 , 0.2638288 , 0.43132153, 0.3078351 , 0.39173505,
       0.30569527, 0.20281023, 0.40268978, 0.34407368, 0.99883676,
       0.82371044, 0.336332  , 0.22709082, 0.29628074, 0.64909756,
       0.31568936, 0.14744918, 0.19159369, 0.4004416 , 0.18224066,
       0.3029936 , 0.37010866, 0.2430029 , 0.29552048, 0.8910294 ,
       0.24371588, 0.494246  , 0.28909764, 0.25677922, 0.47631207,
       0.18875706, 0.21370165, 0.35631987, 0.18546878, 0.16414918,
       0.33599353, 0.2454148 , 0.5663556 , 0.3360497 , 0.29190695,
       0.488318  , 0.19215214, 0.23402406, 0.20613244, 0.16178946,
       0.39323428, 0.23165403, 0.22774597, 0.2819658 , 0.5594347 ,
       0.33850285, 0.1778277 , 0.32856914, 0.34974703, 0.37431306,
       0.34625536, 0.36621508, 0.38125238, 0.5315957 , 0.30333713,
       0.44020438, 0.44410598, 0.29321685, 0.36781052, 0.23218401,
       0.2577725 , 0.3013207 , 0.44595236, 0.2508836 , 0.17561689,
       0.3632723 , 0.19314796, 0.30344412], dtype=float32), array([[[[-0.04729012],
         [-0.04439114],
         [ 0.05430793],
         ...,
         [ 0.00617322],
         [-0.03188805],
         [-0.04524027]],

        [[ 0.05060117],
         [ 0.00672833],
         [-0.00862178],
         ...,
         [ 0.05121124],
         [-0.02091862],
         [ 0.07180364]],

        [[-0.00023036],
         [ 0.06574487],
         [ 0.03602877],
         ...,
         [ 0.03610672],
         [ 0.01765032],
         [ 0.06385062]]],


       [[[-0.00426447],
         [-0.03327889],
         [-0.04821966],
         ...,
         [ 0.03071767],
         [-0.02716913],
         [ 0.00515889]],

        [[ 0.05607388],
         [-0.01252465],
         [ 0.01369851],
         ...,
         [-0.02532391],
         [ 0.03396611],
         [-0.02226286]],

        [[-0.0087808 ],
         [-0.06182253],
         [-0.01947834],
         ...,
         [-0.02593244],
         [ 0.06000236],
         [ 0.08742034]]],


       [[[ 0.00840081],
         [ 0.06357621],
         [ 0.02794834],
         ...,
         [-0.01003619],
         [-0.06424882],
         [ 0.09060925]],

        [[-0.03627579],
         [ 0.03001853],
         [-0.02753142],
         ...,
         [ 0.07594919],
         [ 0.05829753],
         [ 0.00903905]],

        [[-0.00659569],
         [ 0.06764939],
         [-0.03436017],
         ...,
         [-0.03811202],
         [-0.05414106],
         [-0.03049538]]]], dtype=float32), array([[[[-0.11053047, -0.10130033,  0.05328944, ...,  0.07393147,
           0.12702268, -0.01374921],
         [-0.00859838,  0.11712819, -0.06460136, ...,  0.00221184,
          -0.10564753, -0.09909639],
         [ 0.05550206,  0.04699682,  0.08565439, ...,  0.06331915,
           0.08576152, -0.09357981],
         ...,
         [-0.11451362,  0.12188017, -0.02278232, ...,  0.03320893,
          -0.0549906 ,  0.01626618],
         [-0.00937928,  0.05518362,  0.07028218, ..., -0.02583373,
           0.13491152, -0.0234754 ],
         [-0.11456392,  0.00555157, -0.1120914 , ..., -0.10403534,
           0.08498577,  0.04029407]]]], dtype=float32), array([1.0143521 , 0.99054605, 1.0022295 , 0.9920312 , 1.0033107 ,
       0.9966471 , 1.0000205 , 1.0195103 , 0.98895633, 0.99449563,
       1.0150658 , 0.9917931 , 0.993115  , 1.019566  , 1.0123519 ,
       1.0214694 , 1.0113626 , 0.99276054, 0.99351716, 1.004673  ,
       1.0002893 , 1.0037651 , 1.0138713 , 1.0182635 , 0.993285  ,
       0.99786156, 1.0204188 , 0.99293643, 0.9991121 , 0.9932085 ,
       0.99375075, 0.9963687 , 0.9988783 , 0.9917548 , 1.0018036 ,
       1.0124145 , 0.99637514, 1.0016803 , 0.98961085, 1.011574  ,
       1.0053587 , 0.998327  , 1.0031265 , 0.9949694 , 1.0021183 ,
       0.98933876, 0.9965902 , 1.0174057 , 1.0125313 , 0.9940155 ,
       0.9969469 , 1.038303  , 0.99497837, 1.004404  , 1.0145433 ,
       0.99493927, 1.0131668 , 0.9957941 , 0.9982451 , 1.0324482 ,
       1.0116484 , 0.9987796 , 1.0134639 , 0.99624956, 0.9976672 ,
       0.99429196, 0.9960202 , 0.9892484 , 0.9884887 , 1.0140177 ,
       0.9846149 , 1.0279951 , 1.027584  , 1.0014117 , 1.0096555 ,
       0.9862936 , 1.0004557 , 0.9802649 , 1.0142814 , 1.0127851 ,
       0.9919939 , 1.0040557 , 1.0043176 , 0.9854818 , 1.0037898 ,
       1.0102978 , 0.9980792 , 1.0085577 , 1.01564   , 0.99939793,
       1.0067319 , 0.99688256, 1.0036031 , 1.0106195 , 0.99933904,
       0.98227066, 1.01068   , 1.003765  , 0.99816567, 1.0255572 ,
       0.98959327, 0.99235785, 0.9791846 , 1.0204332 , 0.9788812 ,
       1.0069239 , 0.99333674, 0.9881765 , 0.99930704, 1.0235158 ,
       1.0033773 , 1.0007448 , 1.0135151 , 1.000529  , 1.0099952 ,
       1.0105277 , 0.98630583, 1.022602  , 1.0008075 , 0.9874232 ,
       1.0106622 , 0.9897636 , 0.9897744 , 1.0086191 , 0.98809487,
       1.0452485 , 1.0195136 , 0.990913  , 1.0036687 , 1.0129917 ,
       1.010742  , 0.99410474, 0.9970475 , 0.9927208 , 0.9985845 ,
       1.0059212 , 1.0012188 , 0.99396545, 0.998679  , 0.98815197,
       0.9939013 , 0.99265677, 1.0180945 , 0.99488777, 0.99711096,
       1.0110433 , 0.98852444, 0.98902637, 0.99956983, 1.0119188 ,
       1.0114926 , 0.99822026, 0.9965616 , 1.0121622 , 0.9916237 ,
       1.0083559 , 0.9953629 , 1.0130962 , 1.0064485 , 0.99437785,
       0.99614763, 1.0041778 , 0.9977285 , 1.0060328 , 0.990781  ,
       0.9821008 , 0.9912962 , 1.0003493 , 0.99453074, 0.9992069 ,
       0.9916508 , 0.99771625, 0.9986577 , 1.0013609 , 0.9857883 ,
       0.9853039 , 0.986477  , 1.0021516 , 1.0049763 , 0.9935422 ,
       0.99834716, 0.9996724 , 1.0007682 , 0.996287  , 0.9904456 ,
       1.0083458 , 0.99907506, 0.9893369 , 1.0099491 , 1.002251  ,
       1.0049013 , 0.99940085, 0.993962  , 0.99297094, 1.0109884 ,
       0.98684114, 0.99638677, 0.9966577 , 1.0245883 , 1.0212338 ,
       0.9932308 , 0.9948421 , 1.0038358 , 1.0004268 , 1.0013254 ,
       1.021341  , 0.9922887 , 0.9989651 , 1.0028595 , 1.0046289 ,
       0.9923256 , 0.9908157 , 0.99117374, 1.005124  , 0.99265224,
       0.99548745, 0.9924318 , 0.9991131 , 0.9938694 , 1.0011189 ,
       0.99703544, 1.0035973 , 0.99725753, 0.9874791 , 0.99257207,
       0.99596846, 1.0046275 , 1.0074662 , 1.0018257 , 0.99273753,
       0.9981499 , 0.99285525, 0.99514794, 0.9942607 , 0.99671364,
       1.0317378 , 0.998034  , 1.000736  , 0.98792285, 0.98852646,
       1.0101987 , 0.9943133 , 1.0087548 , 1.026214  , 1.018073  ,
       0.9979579 , 0.99770796, 0.99630743, 1.0142882 , 1.0000172 ,
       1.0200201 , 0.99258864, 0.986336  , 0.99604714, 1.0009892 ,
       1.0029979 ], dtype=float32), array([-0.00058998, -0.01063188, -0.0134462 , -0.00330343, -0.00331841,
       -0.00858334,  0.00634223, -0.00184231, -0.01167946, -0.0107017 ,
       -0.00426386, -0.00117704, -0.01194909,  0.02771143, -0.00771569,
       -0.00424627, -0.00247278, -0.00334148,  0.01035261, -0.02111848,
        0.01056191,  0.00628923,  0.03515912, -0.05248879, -0.00437703,
       -0.01087401, -0.03730639, -0.01765989, -0.00202419,  0.01560027,
       -0.02187196, -0.01744305, -0.00056382,  0.00029946, -0.01052488,
       -0.02868472, -0.00685648,  0.00283869, -0.00983551,  0.00701916,
       -0.03502383, -0.01173741, -0.00216632, -0.00535527,  0.00173404,
       -0.01088951, -0.01434424, -0.00256137,  0.01022453, -0.00873946,
       -0.00962129,  0.02742925, -0.00868577, -0.0122289 ,  0.02131604,
       -0.00192147, -0.00301802, -0.00639489, -0.00859553, -0.02378617,
       -0.0110882 ,  0.00282973,  0.00417193, -0.0003053 , -0.00480326,
       -0.00463825,  0.00366618, -0.00501765, -0.0082756 ,  0.00919398,
       -0.03030856,  0.03957823,  0.03160973, -0.00188204,  0.0074889 ,
       -0.02070777, -0.00496193, -0.01711992,  0.01605826,  0.00494812,
       -0.00638669,  0.00432442, -0.00654399, -0.00913509, -0.00237052,
       -0.00969364,  0.00582335, -0.00023978, -0.02726958,  0.00884644,
        0.01035181, -0.01525059, -0.03394303, -0.01508852,  0.00680134,
       -0.00617436, -0.01625675, -0.00257581, -0.00981725, -0.02823282,
       -0.01405116, -0.02697385, -0.01316604,  0.03753234, -0.01852506,
        0.01838692, -0.0031979 , -0.01509416, -0.00636806, -0.00905121,
        0.01117727, -0.00634357,  0.00935733, -0.02617676,  0.0127921 ,
       -0.01120302, -0.00241572, -0.01917008, -0.0075486 , -0.00360632,
        0.01027397, -0.00897891, -0.00626396, -0.03801011, -0.01263299,
        0.03485763, -0.01362183, -0.0036157 ,  0.0048645 ,  0.00920622,
        0.02030395, -0.01198296, -0.00411765,  0.0085195 , -0.01490174,
        0.02619233, -0.01049154,  0.00605136, -0.00776417, -0.01529183,
       -0.0165224 , -0.00274343, -0.02734205, -0.00695116, -0.01016343,
       -0.04180971,  0.00098983, -0.01113207, -0.01056704,  0.0209783 ,
       -0.00532417, -0.01399144, -0.00336372, -0.05780819, -0.00300839,
       -0.03468803, -0.00170716,  0.00274623,  0.00416982, -0.01402163,
       -0.01493836,  0.00276299, -0.00563132, -0.00797468,  0.00283478,
       -0.01799555, -0.00745731, -0.00571661,  0.00771909,  0.00483404,
       -0.00380351, -0.00124751, -0.00224748, -0.0019419 , -0.04221534,
       -0.04592617, -0.01394777, -0.00375468,  0.00131529, -0.00371201,
       -0.00813958, -0.01028021,  0.01488035, -0.00650497,  0.00122457,
        0.00153256, -0.00626862, -0.00970713,  0.00418043,  0.01882953,
        0.01171739, -0.00920684, -0.00250362,  0.01189564,  0.02194626,
       -0.00141397,  0.00656812, -0.0087729 ,  0.01592921,  0.04033351,
       -0.00379214, -0.0039423 ,  0.02605942,  0.00048302,  0.00932577,
        0.02477371, -0.01733716, -0.00696294, -0.00776754,  0.00692289,
       -0.00878338, -0.00230191, -0.01601455, -0.05058856, -0.01364311,
       -0.00921734, -0.01530636, -0.01798208,  0.02026442,  0.01136305,
       -0.00927051, -0.01099393,  0.00131554, -0.01071827, -0.01290595,
       -0.00662092,  0.00128409, -0.00461771,  0.0064262 , -0.03360783,
        0.00195936, -0.00581019, -0.01319824, -0.01247893, -0.01497885,
       -0.03811248, -0.02283844,  0.00268529, -0.0130198 , -0.00476302,
        0.00932811,  0.00722159,  0.00334764,  0.0247999 ,  0.01493031,
       -0.00257364, -0.0330906 , -0.00034636,  0.01428942, -0.00853538,
        0.02597866, -0.01479576, -0.01036259, -0.00781386,  0.01911984,
        0.00482151], dtype=float32), array([ 0.08137459, -0.06464666,  0.0420864 , -0.01099526,  0.06997824,
       -0.0294666 , -0.13340975,  0.02480463,  0.05410513,  0.0402789 ,
        0.1281596 , -0.02386722,  0.10669623, -0.13389382,  0.1154736 ,
        0.02712586,  0.06976724, -0.0569415 ,  0.05674676,  0.09294067,
       -0.10067359, -0.03856928, -0.11910608,  0.04609144, -0.08024716,
       -0.07224645,  0.10540513,  0.06816735,  0.00438458,  0.05812541,
        0.09125238,  0.0462236 ,  0.00979362, -0.02153347,  0.04609975,
       -0.01001817, -0.03726643, -0.061943  ,  0.10907199,  0.00954338,
        0.00896502,  0.09433322,  0.03593119, -0.02472063, -0.07737156,
        0.04837145, -0.09804744,  0.11388505,  0.02774193,  0.06016622,
       -0.08065607, -0.06268282,  0.07663252,  0.06684652, -0.04363129,
        0.006557  , -0.05772339,  0.050066  , -0.00470715,  0.11016703,
        0.06897506,  0.03638077,  0.03491928,  0.03236396,  0.07690423,
       -0.03812645, -0.07641073, -0.05144622,  0.11558738, -0.02045286,
        0.02737614, -0.03819215,  0.00431513,  0.00901346,  0.00708576,
        0.19058247, -0.11202861, -0.07078411, -0.14049047,  0.00176845,
       -0.0035784 ,  0.01528668,  0.07617012,  0.02081197,  0.02660299,
       -0.05945358, -0.08952886, -0.05276091,  0.09638827, -0.13034067,
        0.0801726 ,  0.06931117,  0.00426151, -0.03871555, -0.05168926,
       -0.05359969,  0.09505962, -0.01351639,  0.04141811,  0.13424799,
       -0.07411318,  0.11404625,  0.01461748, -0.13647644, -0.02536797,
        0.03184997, -0.06865414,  0.0237165 ,  0.05119149,  0.02029718,
       -0.09429288,  0.02106736, -0.05963358,  0.12151482, -0.03407179,
       -0.00029786,  0.07748851, -0.02624499, -0.11986683, -0.08316771,
       -0.05517814, -0.03937475,  0.00409282,  0.12007299, -0.06595359,
       -0.10184635,  0.13247742,  0.05687891,  0.01441116,  0.05630618,
       -0.09725282,  0.03396698,  0.00804103, -0.02747436,  0.02212592,
       -0.1042232 ,  0.02916875,  0.00433794,  0.10520181,  0.04500416,
       -0.02439372,  0.02143677,  0.1038816 ,  0.03175909,  0.06984656,
        0.07044195,  0.04941394,  0.02570981, -0.030409  , -0.06009378,
        0.06684988,  0.06334066,  0.01463604,  0.06879156, -0.0033504 ,
        0.05583882,  0.01262507, -0.04139482, -0.03049156,  0.05171483,
        0.10654802,  0.01498618,  0.0965401 ,  0.06313803, -0.04182186,
       -0.04613309,  0.00558239, -0.07278363, -0.03113636, -0.01429366,
       -0.08921649, -0.02708444, -0.14377145,  0.10319108, -0.00207644,
        0.0270602 , -0.13992572,  0.02645964, -0.05148007, -0.05629685,
        0.10899375,  0.0573148 ,  0.10759592, -0.12349647, -0.01852328,
        0.02523332,  0.10043501,  0.01117439,  0.07218222, -0.04250124,
       -0.04569686,  0.07797085, -0.03332116,  0.01077411, -0.07700112,
       -0.01064755, -0.0413889 ,  0.08200678, -0.0542091 ,  0.00834997,
       -0.04642635,  0.00298277,  0.02110884, -0.03920048,  0.05094374,
       -0.04566034, -0.03956619,  0.06154661,  0.17263477, -0.03233621,
       -0.05543723, -0.0323048 ,  0.04885786,  0.06739637, -0.11232624,
       -0.05289056, -0.03533956,  0.04975838, -0.03342275, -0.03558455,
        0.07478306,  0.01836765,  0.0662578 ,  0.01187854, -0.05991626,
       -0.0491375 ,  0.02963104,  0.03871789, -0.05599627,  0.04825727,
       -0.05258871, -0.03036188,  0.0363396 ,  0.02285682, -0.07246441,
        0.12474834,  0.0391342 , -0.07995273,  0.01911506,  0.00550321,
       -0.010558  ,  0.08970676, -0.05530439, -0.03271201, -0.09799643,
       -0.06904269,  0.09110895, -0.03305829,  0.01027377,  0.03603756,
       -0.01786155,  0.11444765,  0.08973102,  0.02990569,  0.0108398 ,
       -0.07365572], dtype=float32), array([0.09531728, 0.10094451, 0.08687499, 0.09103487, 0.09908271,
       0.08909395, 0.11687537, 0.09510493, 0.08726019, 0.08543118,
       0.11708818, 0.08821701, 0.1076348 , 0.09297986, 0.10793556,
       0.09809057, 0.08542439, 0.08748987, 0.10203971, 0.09855995,
       0.09628303, 0.09552994, 0.10177101, 0.10482165, 0.09977471,
       0.09824115, 0.1032238 , 0.08789161, 0.09325866, 0.10058761,
       0.09736345, 0.09649353, 0.08956876, 0.09353034, 0.09362641,
       0.09996412, 0.09285947, 0.09311944, 0.09895147, 0.09001058,
       0.09743312, 0.08991027, 0.08790411, 0.09238935, 0.08864861,
       0.08994585, 0.10540506, 0.11934587, 0.09112319, 0.08725952,
       0.0912474 , 0.10236783, 0.08706211, 0.09860252, 0.09103368,
       0.09850612, 0.09317633, 0.08923388, 0.08914103, 0.09439062,
       0.10371639, 0.09373957, 0.08834013, 0.08848186, 0.0908669 ,
       0.08571425, 0.09023371, 0.08573736, 0.09844252, 0.09139794,
       0.08848919, 0.09659572, 0.10508241, 0.08938562, 0.08642507,
       0.13117939, 0.1018067 , 0.08878747, 0.09464189, 0.10995775,
       0.08665518, 0.10510933, 0.10452828, 0.09137961, 0.08941931,
       0.08714997, 0.09169971, 0.09582164, 0.09772706, 0.10052361,
       0.09977322, 0.10014541, 0.09021384, 0.12031058, 0.08962326,
       0.08708203, 0.13549851, 0.0897359 , 0.09085646, 0.09794731,
       0.08720177, 0.09871018, 0.08790611, 0.10623489, 0.09918272,
       0.0863033 , 0.09061184, 0.09091163, 0.10743957, 0.09128935,
       0.09205943, 0.10219753, 0.08954772, 0.09692878, 0.09160621,
       0.10232391, 0.10476651, 0.11490569, 0.09438201, 0.08584546,
       0.09955961, 0.09011514, 0.08761326, 0.10550223, 0.09419291,
       0.09066244, 0.10913626, 0.09754986, 0.09112418, 0.10687181,
       0.13902317, 0.09891199, 0.08692738, 0.0908335 , 0.08808322,
       0.10632028, 0.08913656, 0.09465513, 0.09386368, 0.09155516,
       0.08860817, 0.0907049 , 0.09894845, 0.09405613, 0.08861114,
       0.12049419, 0.09027328, 0.0913869 , 0.08814885, 0.0963298 ,
       0.08694248, 0.09374602, 0.08529288, 0.10130563, 0.08758024,
       0.12365855, 0.09208375, 0.09011787, 0.09684457, 0.09021383,
       0.08849577, 0.09167779, 0.1069365 , 0.09320068, 0.1007887 ,
       0.11413866, 0.09408266, 0.08878357, 0.08870018, 0.08913527,
       0.09945326, 0.08761342, 0.10028961, 0.0913144 , 0.09180953,
       0.09313983, 0.09960566, 0.10668088, 0.08788034, 0.10851797,
       0.09317403, 0.09534525, 0.0968974 , 0.09539252, 0.09224619,
       0.09133673, 0.09346391, 0.08649132, 0.0927082 , 0.09127346,
       0.09673562, 0.09677678, 0.09010636, 0.0899563 , 0.08781385,
       0.08571708, 0.11222146, 0.10731197, 0.09069093, 0.10492039,
       0.08922973, 0.0918037 , 0.09265319, 0.09736837, 0.09241805,
       0.09235083, 0.08808616, 0.10380305, 0.09278738, 0.09457439,
       0.08885671, 0.10415566, 0.08747166, 0.1003179 , 0.10043005,
       0.09511676, 0.08983348, 0.0925412 , 0.08989419, 0.08680629,
       0.10372137, 0.08872981, 0.09234563, 0.09136966, 0.08939674,
       0.10354451, 0.08872682, 0.0995347 , 0.09253311, 0.09492169,
       0.09343874, 0.10643521, 0.0921225 , 0.09102974, 0.08906654,
       0.10650153, 0.11117294, 0.08791406, 0.10514155, 0.08684465,
       0.09491864, 0.09324644, 0.08955987, 0.09180693, 0.0930297 ,
       0.10355517, 0.09314915, 0.09933291, 0.09214296, 0.08586295,
       0.0918106 , 0.11664125, 0.10377524, 0.10135727, 0.10107047,
       0.09805547], dtype=float32), array([[[[-0.00393701],
         [-0.00270909],
         [ 0.02013107],
         ...,
         [-0.03593564],
         [ 0.03256051],
         [ 0.03748636]],

        [[-0.03770617],
         [ 0.01979103],
         [ 0.02818161],
         ...,
         [ 0.01890384],
         [ 0.00408796],
         [ 0.01903549]],

        [[ 0.0630284 ],
         [-0.00704442],
         [-0.01892928],
         ...,
         [-0.01608611],
         [-0.00117032],
         [-0.0069662 ]]],


       [[[ 0.00307557],
         [ 0.02158752],
         [-0.02930108],
         ...,
         [-0.05005573],
         [-0.00389116],
         [ 0.03662431]],

        [[ 0.04022529],
         [-0.03276556],
         [-0.02955567],
         ...,
         [ 0.03483487],
         [-0.03871701],
         [ 0.01770864]],

        [[ 0.00239904],
         [ 0.03367625],
         [-0.04385159],
         ...,
         [ 0.02170287],
         [-0.02525433],
         [ 0.05135577]]],


       [[[ 0.02622085],
         [ 0.03860089],
         [ 0.03071825],
         ...,
         [ 0.02495096],
         [-0.00936523],
         [-0.03609891]],

        [[ 0.01108334],
         [ 0.0246789 ],
         [ 0.01829283],
         ...,
         [ 0.03548231],
         [ 0.01981011],
         [ 0.02139443]],

        [[ 0.06125311],
         [-0.01154007],
         [-0.05030044],
         ...,
         [ 0.03327676],
         [-0.03329262],
         [ 0.03905157]]]], dtype=float32), array([[[[-0.10518339, -0.0184777 ,  0.11109068, ...,  0.04720643,
          -0.01840457,  0.07582069],
         [ 0.0645882 ,  0.02284097, -0.07677802, ...,  0.04365081,
           0.01511255, -0.06690302],
         [-0.02893897, -0.10181887, -0.07311218, ..., -0.13681865,
           0.09791011, -0.01492315],
         ...,
         [ 0.00258118, -0.05404719, -0.09973937, ..., -0.05876323,
           0.00206286, -0.09191468],
         [ 0.01567892,  0.05513608, -0.00528433, ..., -0.0226066 ,
          -0.0185648 , -0.04561553],
         [-0.1125366 , -0.06540448, -0.10850023, ...,  0.0149761 ,
          -0.02270192,  0.08038165]]]], dtype=float32), array([0.99799794, 1.000193  , 1.0077829 , 1.0127022 , 1.0030272 ,
       1.0042088 , 0.9992483 , 1.0075322 , 0.9938906 , 1.000062  ,
       1.0067317 , 0.99522054, 1.0198449 , 0.9737507 , 1.0015398 ,
       1.0060154 , 0.9990623 , 1.0101296 , 0.9940686 , 1.0097092 ,
       1.0017151 , 1.0118501 , 1.0011497 , 1.0128139 , 1.003461  ,
       0.9975792 , 0.9952929 , 1.0071723 , 1.0099963 , 0.9988943 ,
       1.0155501 , 0.9935127 , 0.9859196 , 1.0044127 , 1.0154346 ,
       1.022333  , 1.0060332 , 1.0051486 , 1.0082834 , 0.9889285 ,
       0.998123  , 1.003189  , 0.9945732 , 0.9947829 , 1.0040408 ,
       0.9979568 , 0.9850107 , 1.0044451 , 1.0158851 , 1.0041364 ,
       1.0055894 , 1.0008662 , 0.98309237, 0.9889724 , 0.98797894,
       0.9971868 , 0.99993855, 0.9964104 , 1.0103437 , 0.988277  ,
       0.9964279 , 1.0094147 , 1.0127985 , 1.0238315 , 0.98595923,
       1.0114777 , 0.99543464, 0.99009097, 0.99035895, 1.0077254 ,
       0.98566806, 0.9843616 , 0.99302477, 1.0106297 , 1.0086744 ,
       0.99608546, 1.0215646 , 0.988926  , 0.9909486 , 1.0085877 ,
       0.9900077 , 1.0005348 , 1.0058621 , 0.98500615, 0.99428433,
       1.0171278 , 0.97831124, 1.0047262 , 0.9876038 , 0.9965544 ,
       0.9967389 , 1.005112  , 0.9926604 , 1.0116023 , 0.99963844,
       1.0013958 , 1.0087056 , 0.99143964, 0.99515146, 0.99227667,
       1.0006796 , 1.0027896 , 0.9868583 , 1.0192627 , 0.9984014 ,
       1.007448  , 1.0060123 , 0.99680424, 1.0098497 , 0.9971775 ,
       1.0247319 , 1.0227454 , 1.0204756 , 1.0108819 , 1.0063064 ,
       0.9871646 , 0.9869374 , 1.0040393 , 1.0113618 , 1.0167673 ,
       0.99691975, 1.0012603 , 0.9857096 , 1.0062008 , 1.0123792 ,
       1.0021409 , 1.0277944 , 0.9996388 , 0.9945352 , 0.9994766 ,
       1.0189524 , 1.017912  , 1.0009451 , 1.0217495 , 1.0089736 ,
       0.99140936, 1.0089728 , 0.99588287, 0.99863374, 1.0027019 ,
       1.009033  , 0.99639124, 1.0030028 , 1.0083973 , 1.0108486 ,
       0.9898025 , 0.9927365 , 0.9998938 , 0.9973359 , 0.99475217,
       1.010458  , 1.004299  , 0.9976427 , 0.99370617, 1.0091017 ,
       1.0192745 , 1.0040451 , 0.99442744, 0.99414563, 1.0145423 ,
       0.99400264, 0.9979517 , 0.9920289 , 1.0178788 , 0.9915148 ,
       0.99025667, 0.9982211 , 1.0007677 , 0.9984153 , 1.0115085 ,
       0.99598837, 1.0001454 , 0.98594785, 0.98293406, 1.0040425 ,
       0.9946107 , 0.9928123 , 0.99331653, 0.9884448 , 0.99541163,
       1.0024995 , 0.9909505 , 1.0165755 , 0.9899369 , 0.9967385 ,
       0.98890275, 1.0156214 , 0.9943688 , 0.9907648 , 1.0082762 ,
       1.0178396 , 0.99608505, 1.0190365 , 1.0077804 , 1.0156437 ,
       1.0029119 , 1.0009677 , 0.9870437 , 0.9932437 , 0.9912892 ,
       0.9904257 , 0.9932    , 0.99044746, 0.9952944 , 1.0173146 ,
       1.0146201 , 0.99294287, 1.0156076 , 0.98191816, 1.0042231 ,
       1.0008883 , 0.9893897 , 0.9969279 , 1.0213797 , 0.9948287 ,
       0.9757668 , 0.9878999 , 0.9994353 , 0.9988242 , 1.0040271 ,
       1.0019393 , 1.0281509 , 0.99182826, 1.0143836 , 1.0060852 ,
       1.0095515 , 0.99009264, 1.0141805 , 1.0076847 , 0.99799526,
       1.0260054 , 0.9982479 , 1.0141994 , 1.0091363 , 1.003426  ,
       0.996742  , 1.0031377 , 1.0048214 , 1.0064921 , 0.998078  ,
       0.99264956, 0.9946519 , 1.007513  , 0.99806374, 0.9875877 ,
       1.0022633 , 0.98409593, 0.98241043, 0.99493563, 1.0197018 ,
       0.9883774 , 1.0117581 , 1.0020596 , 1.0071348 , 1.0070317 ,
       1.0010813 ], dtype=float32), array([-6.77676219e-03,  5.98215638e-03, -7.09798792e-03,  1.43393530e-02,
        3.27903847e-03, -1.44212379e-03, -1.33611551e-02,  3.60330404e-03,
        1.03049139e-02,  2.99621578e-02,  1.71738714e-02, -6.98473724e-03,
       -1.13713425e-02,  1.16415182e-02,  5.89883560e-03,  1.94076337e-02,
        1.38272531e-04, -2.49538049e-02, -5.37213497e-03,  5.87356510e-04,
        1.02658644e-02,  2.51390710e-02,  8.15592520e-03, -5.18935500e-03,
       -2.98891892e-03, -8.87345243e-03, -1.55126732e-02, -7.12656882e-03,
       -1.31468233e-02, -1.38730342e-02, -5.89218661e-02,  4.33590310e-03,
       -1.03806648e-02,  5.50402422e-03,  8.37993808e-03, -8.70869122e-03,
       -1.03712473e-02, -6.92251185e-03, -5.61963860e-03, -1.05103888e-02,
       -8.71610641e-03,  1.53272077e-02,  1.74393672e-02, -6.94079511e-03,
       -8.20576586e-03, -8.32388271e-03, -6.11157343e-03,  6.47231890e-03,
        1.26214474e-02,  1.43137109e-02, -2.10054195e-03, -4.68334323e-03,
       -1.26068396e-02, -1.26754940e-02,  6.91695372e-03, -5.42892702e-03,
       -1.17285224e-02,  1.51923404e-03, -1.11550372e-02, -1.40363863e-02,
       -5.02780732e-03,  1.89900200e-03,  2.74923779e-02,  1.99061595e-02,
       -6.68200431e-04,  1.89456698e-02, -1.49209062e-02, -9.43012442e-03,
       -6.27252925e-03, -3.92745994e-02,  1.60048399e-02, -2.03354117e-02,
       -4.69191186e-03,  2.02214234e-02, -8.48283619e-03, -4.42138035e-03,
       -6.88119093e-03, -7.74827553e-03, -1.54716168e-02, -7.84659013e-03,
        4.96695051e-03, -9.97148920e-03, -6.84413454e-03,  5.01934905e-03,
       -2.05039997e-02,  3.86040397e-02,  7.01396354e-03,  1.67000352e-03,
       -3.86870909e-03, -1.86131578e-02, -1.81777123e-02, -4.15391009e-03,
       -4.96943831e-04, -3.56900133e-03, -1.93440751e-03, -1.59345064e-02,
        1.02185169e-02, -7.82159157e-03, -3.58394254e-03,  8.07363633e-03,
       -8.77749920e-03, -3.79180722e-02, -6.67862874e-03,  2.19767038e-02,
       -1.50163667e-02, -1.10144755e-02, -6.73109060e-03,  1.63020622e-02,
       -2.71802470e-02,  1.55238556e-02, -1.16679315e-02, -5.18927090e-02,
       -2.90819574e-02, -2.98294500e-02, -1.96795049e-03, -2.12483661e-04,
       -1.06768487e-02,  1.97450332e-02,  4.30328399e-03,  1.58658763e-03,
       -2.62652598e-02, -2.01736134e-03,  7.22367491e-04,  3.81208514e-03,
        1.76925156e-02, -1.39649259e-02,  1.29325781e-02, -2.14754418e-03,
        9.45829786e-04, -2.51663011e-02,  3.13729569e-02,  4.91597317e-03,
       -3.71582992e-03, -5.16355364e-03, -1.11842304e-02, -1.38650490e-02,
       -2.42101364e-02, -1.16860606e-02, -2.63785161e-02, -7.22634979e-03,
       -1.36115616e-02, -5.82702784e-03,  6.21082843e-04, -2.19148546e-02,
       -2.25377269e-02,  8.85752030e-03, -2.39777053e-03, -7.41300499e-03,
       -5.41085983e-03, -1.10255061e-02, -1.72344632e-02, -1.06042195e-02,
       -1.76254846e-02, -5.98308444e-03, -2.95214209e-04, -2.68975385e-02,
       -4.84579755e-03, -2.26070508e-02,  6.77342387e-03, -7.31582893e-03,
       -1.60867814e-02, -7.49325845e-03, -1.23122651e-02, -4.49440267e-05,
       -2.37707440e-02,  1.74506661e-02, -1.16584348e-02,  3.36392527e-03,
       -1.98033964e-03,  2.27808394e-03,  2.87123527e-02, -7.25498539e-04,
       -1.49293523e-02, -1.18979942e-02,  8.84471554e-03, -2.20819842e-03,
       -1.87291559e-02, -9.37271398e-03, -7.80023751e-04, -6.25613425e-03,
        6.28172536e-04, -3.31041543e-03, -3.14603150e-02, -1.26652988e-02,
       -1.22500528e-02,  4.02529351e-03,  4.49953042e-02, -1.54350726e-02,
       -1.30719729e-02, -1.79340038e-02, -1.14798301e-03,  7.27109332e-03,
       -4.75886986e-02, -1.33183622e-03, -3.64258587e-02, -7.13114254e-03,
       -1.53833181e-02,  3.81894177e-04,  6.82121376e-03, -2.11710576e-02,
       -1.91066917e-02,  9.25847050e-03, -2.40042023e-02,  1.71471966e-05,
       -5.04899658e-02, -9.06917918e-03, -2.07546493e-03,  4.88812756e-03,
        9.49987490e-03,  1.10244071e-02,  2.44930722e-02, -3.11616692e-03,
        3.30678932e-03, -5.25660394e-03,  7.50274956e-03,  1.22955977e-03,
       -9.17556827e-06,  1.99074112e-02,  6.40537171e-03, -8.08543153e-03,
       -1.95861869e-02,  7.55055516e-04,  4.32951516e-03, -4.89155762e-03,
        3.08378991e-02,  8.17855704e-04,  7.89057754e-04, -3.22844554e-03,
       -2.37193261e-03, -1.14657655e-02, -4.93812701e-03, -9.75540606e-04,
       -1.73845589e-02, -6.19046018e-03,  4.71713021e-02, -1.09004590e-03,
        1.70708615e-02, -2.24358179e-02, -6.95722084e-03, -1.48487203e-02,
       -1.30387414e-02, -8.82736314e-03, -8.71577766e-03, -5.52008685e-04,
       -1.66770313e-02, -1.60846654e-02, -3.40068666e-03,  2.09102407e-03,
       -7.26474402e-03,  1.29911676e-02, -1.34668807e-02, -2.10068747e-03,
        2.71406933e-03,  1.52211199e-02,  1.07232016e-02, -4.53831628e-03],
      dtype=float32), array([ 4.32590656e-02, -9.89769120e-03,  1.09966367e-03, -3.78912091e-02,
       -7.52587290e-03, -6.61335215e-02, -4.05539274e-02, -2.48246491e-02,
        3.05598453e-02,  1.40422033e-02, -4.65376750e-02,  2.55948082e-02,
        4.98550609e-02, -6.80973902e-02, -7.99539760e-02, -7.99510479e-02,
       -2.69034132e-02,  8.24195594e-02,  1.81061905e-02,  4.62272763e-02,
       -3.13871428e-02,  5.38862310e-02,  1.51741449e-02, -2.84859184e-02,
        2.66125979e-04,  1.73010714e-02,  7.77960848e-03,  2.59819496e-02,
        4.13707048e-02,  3.95582803e-02,  7.73453116e-02, -3.51224584e-03,
        4.83490899e-02, -3.07333469e-02, -6.89109266e-02, -5.12290001e-02,
        1.25363590e-02, -1.84063166e-02,  1.56710017e-02,  7.48902559e-02,
        9.45271272e-03,  2.88357940e-02, -3.91186401e-02, -1.05111143e-02,
        2.45048366e-02,  2.04854105e-02, -5.29076345e-02,  3.37160677e-02,
        5.49210645e-02, -6.08809143e-02,  5.29031865e-02, -1.08810021e-02,
        1.88591871e-02,  2.25602593e-02, -6.11447245e-02,  3.72332446e-02,
        3.22513990e-02, -3.35481428e-02,  1.17451344e-02,  6.18194863e-02,
        4.74961847e-02,  1.22165270e-02, -2.80333087e-02,  7.58794136e-03,
       -7.44672318e-04,  2.88249296e-03,  2.51433272e-02, -2.20712759e-02,
       -3.20242681e-02,  2.70123146e-02,  3.33151482e-02, -3.66799012e-02,
        1.84461521e-03,  4.92835930e-03,  2.02391353e-02,  8.87599672e-05,
        2.21496541e-02, -7.08264858e-02,  6.83917776e-02,  9.53057781e-02,
        4.46773088e-03,  3.76198953e-03,  3.28685436e-03, -3.94174866e-02,
       -3.99008486e-03, -2.66047772e-02, -4.21892963e-02, -5.52670332e-03,
        2.27051843e-02, -1.34652993e-02,  3.33637856e-02,  5.52999564e-02,
        2.38313638e-02,  2.95144636e-02, -1.81070305e-02,  6.94611967e-02,
       -1.32693844e-02, -6.91499710e-02, -1.64021179e-02,  3.66912819e-02,
        3.93296555e-02,  2.90446859e-02, -4.35931608e-02, -9.29704309e-03,
        2.36322097e-02, -2.88180006e-03, -1.35042397e-02,  2.34046876e-02,
        7.66949579e-02, -3.43387425e-02, -2.79059634e-02,  2.54855882e-02,
        3.36346030e-02,  5.07825054e-02, -4.83476967e-02, -1.64844433e-03,
        4.39588679e-03, -1.14289578e-02,  5.58270002e-03, -7.17787966e-02,
       -7.11648085e-04, -4.57977923e-03,  6.37004094e-04,  6.66686101e-03,
        1.30330855e-02,  5.26813604e-02, -3.15588899e-02,  6.51199790e-03,
       -1.28188729e-02, -3.54665741e-02, -4.64515388e-02,  1.54506834e-02,
       -5.70249036e-02,  4.72555729e-03,  8.53832662e-02,  3.13244127e-02,
        6.76821470e-02,  4.15047929e-02,  6.02192171e-02, -2.05462109e-02,
        7.98430070e-02, -1.49230438e-03,  6.84218109e-02,  6.63421527e-02,
        3.28866690e-02,  1.73391066e-02,  2.67933961e-02,  4.36202548e-02,
        3.48548740e-02, -1.93535611e-02,  1.38764996e-02,  2.62905303e-02,
        2.16084463e-03, -6.03414315e-04,  3.74389514e-02,  2.81242896e-02,
       -3.26216593e-02,  8.43703002e-02,  4.23265062e-02, -1.00684527e-03,
        1.35690663e-02,  5.03034564e-03, -4.97777686e-02,  5.43188415e-02,
        1.83865335e-02,  3.39014195e-02,  3.95349301e-02, -3.91350649e-02,
       -2.31216522e-03,  7.82750398e-02,  1.61679406e-02,  1.65860855e-03,
        5.99247925e-02,  9.31654721e-02,  1.07329413e-02,  4.69409004e-02,
        1.70425847e-02, -4.29819897e-02, -8.28157552e-03,  2.17581983e-03,
       -7.13736238e-03,  8.29954594e-02,  2.81414483e-02, -5.72061772e-03,
       -2.48272363e-02, -1.70926619e-02,  2.98844185e-02, -1.89649053e-02,
       -1.88992545e-02,  3.85491736e-02, -1.48311593e-02, -3.97179797e-02,
        1.05874851e-01,  5.27746826e-02,  6.76057190e-02,  5.42188995e-03,
        5.56147955e-02, -2.61933394e-02, -3.19060870e-02,  1.82202086e-02,
        3.30126509e-02, -1.35995876e-02,  1.20532000e-03,  8.48453026e-04,
        1.09871909e-01,  1.90693121e-02, -3.78982052e-02,  4.93299998e-02,
       -5.90148056e-03,  1.67663805e-02, -1.61428039e-03,  4.03572136e-04,
       -4.53051645e-03,  9.38815773e-02, -6.86983299e-03,  1.71730090e-02,
        5.04791141e-02, -3.20726819e-02,  9.76141095e-02, -2.02975217e-02,
       -3.44438739e-02,  3.24065574e-02, -5.72341345e-02,  3.31202224e-02,
       -3.69465202e-02, -5.88254770e-03, -3.00965104e-02,  4.91549410e-02,
        1.91583429e-02,  1.42006036e-02, -9.91826598e-03,  2.43674815e-02,
        7.05073774e-02,  4.89740120e-03, -4.91455104e-03,  5.53171672e-02,
        4.32361895e-03, -4.23160382e-02, -1.43413823e-02,  5.31318597e-03,
       -2.92472169e-02, -2.08690483e-02,  4.14240099e-02, -6.81599453e-02,
        1.49557218e-02,  6.89275637e-02,  1.06293857e-02, -4.21604589e-02,
        2.09265482e-02,  6.72690861e-04,  3.36114727e-02, -4.43247892e-02,
       -1.53506473e-02,  3.47587019e-02,  5.21107875e-02,  3.91021222e-02],
      dtype=float32), array([0.08438862, 0.08333585, 0.08568893, 0.08491836, 0.08927228,
       0.08910821, 0.08575664, 0.08840678, 0.08739647, 0.0877694 ,
       0.08834815, 0.08491357, 0.10543685, 0.09312494, 0.09076286,
       0.08668864, 0.08500405, 0.09784203, 0.08855947, 0.09537745,
       0.08652988, 0.08706505, 0.08594182, 0.09081523, 0.0853668 ,
       0.08457633, 0.08842377, 0.08575778, 0.08977095, 0.08445941,
       0.10554459, 0.08816   , 0.08667155, 0.08603303, 0.10471078,
       0.08669522, 0.09344577, 0.08870238, 0.08468435, 0.09523522,
       0.09222411, 0.0863886 , 0.09243667, 0.08774998, 0.08437334,
       0.0855149 , 0.08555931, 0.0922455 , 0.09465428, 0.08538363,
       0.08471829, 0.08444164, 0.08566865, 0.08574203, 0.09237318,
       0.08620887, 0.08900006, 0.08312272, 0.09561431, 0.09268672,
       0.08655908, 0.0865029 , 0.09060314, 0.08654937, 0.08762345,
       0.08829891, 0.08552413, 0.08690904, 0.08716089, 0.09813444,
       0.08887512, 0.08632045, 0.08787858, 0.08294339, 0.0903128 ,
       0.08516841, 0.08644468, 0.09339245, 0.09150556, 0.09279902,
       0.08878735, 0.08568885, 0.09646961, 0.08940747, 0.08977707,
       0.08448539, 0.08776679, 0.0865823 , 0.08513035, 0.08443671,
       0.08834898, 0.0932292 , 0.08801641, 0.08721013, 0.08449662,
       0.08745294, 0.08709064, 0.08519875, 0.09029698, 0.09073249,
       0.08679695, 0.09013689, 0.08419086, 0.08768743, 0.09465682,
       0.0848351 , 0.08614208, 0.08684925, 0.09767257, 0.08918652,
       0.08524122, 0.10892443, 0.09737345, 0.09000253, 0.08479299,
       0.08594423, 0.08554641, 0.08455969, 0.0933696 , 0.09395612,
       0.08919102, 0.0856992 , 0.08925147, 0.08974864, 0.08417646,
       0.09552206, 0.08858687, 0.08619484, 0.08613001, 0.08638791,
       0.09465318, 0.10985114, 0.08870121, 0.09065752, 0.10415344,
       0.08328426, 0.09368875, 0.08690942, 0.09647918, 0.08356208,
       0.0849705 , 0.08386768, 0.09161775, 0.08950482, 0.1038823 ,
       0.08815105, 0.08705295, 0.09122267, 0.09252635, 0.08436972,
       0.08551081, 0.09792198, 0.08666486, 0.08540823, 0.08747979,
       0.09342943, 0.08920124, 0.0947492 , 0.08516579, 0.0844334 ,
       0.08750643, 0.08885661, 0.09046724, 0.09608951, 0.08588739,
       0.08801716, 0.08426379, 0.09398227, 0.08494484, 0.08600269,
       0.08717531, 0.08889793, 0.08824404, 0.08686364, 0.0872383 ,
       0.09380529, 0.08367004, 0.09052967, 0.08781647, 0.09283635,
       0.08345385, 0.11346053, 0.0996758 , 0.08384939, 0.08875033,
       0.08511658, 0.08625197, 0.09147459, 0.08475622, 0.08711199,
       0.08507072, 0.08333804, 0.10756256, 0.08601657, 0.09114858,
       0.08976362, 0.09297128, 0.0835848 , 0.08572736, 0.08861306,
       0.08724773, 0.08627812, 0.09231086, 0.08613234, 0.10167313,
       0.09551815, 0.08357882, 0.10144968, 0.09175108, 0.08705101,
       0.08717979, 0.0879665 , 0.08621722, 0.09783342, 0.08561524,
       0.08316498, 0.09673593, 0.09885069, 0.11406851, 0.08867253,
       0.08981139, 0.08717134, 0.0937662 , 0.0842013 , 0.08727244,
       0.0877905 , 0.08356546, 0.09706759, 0.08481765, 0.08695005,
       0.0863419 , 0.09213117, 0.08504918, 0.09161207, 0.09324385,
       0.09013438, 0.08940098, 0.08420242, 0.08876367, 0.08748543,
       0.09014888, 0.0887013 , 0.08833134, 0.09149947, 0.09130089,
       0.09759551, 0.08765053, 0.08830567, 0.08966152, 0.08604877,
       0.08983923, 0.0853304 , 0.08765564, 0.08865629, 0.08875972,
       0.08888241], dtype=float32), array([[[[-0.04426407,  0.03448167, -0.01129057, ...,  0.11635313,
          -0.05247269, -0.08149792],
         [ 0.03025533, -0.02414443,  0.04804034, ..., -0.10942657,
           0.00732162,  0.1224433 ],
         [ 0.09184635, -0.05433987,  0.01273179, ..., -0.05094935,
          -0.04250867, -0.08012627],
         ...,
         [-0.09153474,  0.06356487,  0.0933595 , ...,  0.12393064,
          -0.03491073, -0.02308372],
         [ 0.12864046, -0.00744384,  0.04020012, ...,  0.07702777,
           0.06601815,  0.01220165],
         [ 0.09500786,  0.05623405, -0.09670293, ..., -0.05539048,
          -0.08694744,  0.0445999 ]]]], dtype=float32), array([0.9890474 , 1.014541  , 0.9992691 , 1.0019261 , 0.9895823 ,
       0.9935852 , 1.0211194 , 1.0042337 , 0.99810094, 0.9953076 ,
       1.0088122 , 0.9894753 , 0.9996806 , 1.0164198 , 0.99258703,
       1.0065553 , 1.0054622 , 0.9701517 , 1.0054246 , 0.9910159 ,
       1.0040289 , 1.0080988 , 0.99827373, 1.0008593 , 0.99189776,
       1.0007609 , 1.0007356 , 0.9920632 , 0.9996645 , 0.98426855,
       1.0188786 , 0.9938318 , 0.9939235 , 1.0041671 , 1.0254786 ,
       0.97515744, 0.9955276 , 1.0041881 , 0.9967037 , 0.98756856,
       0.99478424, 0.9976353 , 1.0104169 , 0.98921543, 1.0028849 ,
       0.98978555, 0.9951953 , 1.0085697 , 1.0122304 , 0.9901599 ,
       0.9982949 , 0.97695583, 0.99892926, 1.0004997 , 0.9967422 ,
       1.0113034 , 1.0060316 , 0.9863871 , 1.0169028 , 0.9938871 ,
       0.986047  , 0.99190736, 1.0317427 , 0.9892753 , 1.004492  ,
       1.0182979 , 1.002461  , 0.97692615, 1.0076681 , 1.0175694 ,
       1.0228286 , 0.994917  , 0.9913439 , 0.98585176, 0.9834847 ,
       0.98503274, 1.0058775 , 0.9937466 , 0.9771375 , 0.9988672 ,
       0.9939234 , 0.9909632 , 0.9845798 , 0.99806255, 0.9929788 ,
       1.0054121 , 0.99869895, 1.0072384 , 0.9893668 , 1.0037698 ,
       1.0003424 , 0.979371  , 0.99790233, 0.9845887 , 1.0057911 ,
       0.98164225, 1.002455  , 0.9879666 , 1.0048152 , 1.0151205 ,
       0.9841068 , 0.9964544 , 0.9973422 , 1.0123578 , 0.9917976 ,
       1.004156  , 1.0017697 , 0.9951308 , 1.0049907 , 0.9983878 ,
       0.9697225 , 1.0020021 , 0.99315226, 0.99838376, 0.99198395,
       0.98901796, 1.0059205 , 1.0198653 , 0.98528004, 0.9993711 ,
       0.9856299 , 0.9938882 , 1.0016776 , 1.0098249 , 0.9918292 ,
       0.9965653 , 0.98660845, 0.99556047, 0.99121654, 1.0096216 ,
       1.032222  , 0.9898699 , 0.995347  , 1.0076718 , 1.0052162 ,
       0.990702  , 1.0027293 , 0.99160117, 0.9909696 , 0.9869401 ,
       0.99206704, 1.0001906 , 1.0019592 , 1.0052837 , 0.99977916,
       0.99961656, 1.0107257 , 1.0047559 , 0.99293095, 0.9959053 ,
       1.0109768 , 1.0048528 , 1.0081624 , 0.99228454, 1.001908  ,
       0.9912176 , 0.99262357, 0.98255724, 0.9943391 , 0.98636407,
       0.9978681 , 0.99969   , 1.0032562 , 1.0040658 , 0.9901822 ,
       0.9938412 , 0.98859704, 1.006353  , 1.0101779 , 1.0067518 ,
       1.0106379 , 0.9800593 , 0.99600786, 0.9888822 , 0.98904246,
       0.9944705 , 0.9875339 , 1.0109353 , 1.0077763 , 0.9993118 ,
       0.986019  , 1.0008463 , 0.99946946, 1.0136693 , 1.0000373 ,
       1.0186998 , 0.99009013, 0.9998589 , 0.9977954 , 0.9880649 ,
       1.00815   , 0.99817383, 0.9988093 , 1.0124702 , 0.9903899 ,
       0.99486566, 0.9991662 , 0.99883866, 0.9995466 , 0.9937546 ,
       1.0099286 , 1.0126983 , 0.9987601 , 0.9872432 , 1.0107833 ,
       1.0058305 , 0.9929877 , 1.0051454 , 1.0067964 , 1.0111907 ,
       1.0107483 , 0.9971421 , 0.98896277, 0.98041546, 1.0195286 ,
       0.9924327 , 0.9836873 , 1.0134599 , 0.9990403 , 1.0052823 ,
       0.98390174, 1.0186499 , 0.99770105, 1.0068259 , 1.012817  ,
       0.98981935, 0.9801766 , 0.98120177, 0.9880644 , 1.0009897 ,
       0.9864387 , 1.0153165 , 0.98765844, 1.0016907 , 1.021231  ,
       0.9788545 , 0.9932414 , 0.9987427 , 1.0129248 , 1.0031273 ,
       0.9978942 , 0.99335825, 0.98535776, 0.98876595, 0.98610014,
       0.9966415 , 0.9958622 , 1.007614  , 1.0185902 , 0.9971694 ,
       0.9813854 , 0.99155414, 1.0042769 , 1.0080538 , 0.9970176 ,
       1.0012622 ], dtype=float32), array([-6.77674217e-03,  5.98215591e-03, -7.09800376e-03,  1.43393548e-02,
        3.27902823e-03, -1.44212507e-03, -1.33611523e-02,  3.60331847e-03,
        1.03049083e-02,  2.99621653e-02,  1.71739180e-02, -6.98474422e-03,
       -1.13713499e-02,  1.16415098e-02,  5.89883653e-03,  1.94076430e-02,
        1.38271018e-04, -2.49538198e-02, -5.37214940e-03,  5.87356801e-04,
        1.02658700e-02,  2.51390617e-02,  8.15592427e-03, -5.18937549e-03,
       -2.98891938e-03, -8.87345336e-03, -1.55126769e-02, -7.12656975e-03,
       -1.31468186e-02, -1.38730286e-02, -5.89218624e-02,  4.33590403e-03,
       -1.03806481e-02,  5.50402328e-03,  8.37995112e-03, -8.70868936e-03,
       -1.03712669e-02, -6.92252349e-03, -5.61964605e-03, -1.05103757e-02,
       -8.71609338e-03,  1.53272077e-02,  1.74393635e-02, -6.94079790e-03,
       -8.20576400e-03, -8.32388923e-03, -6.11157250e-03,  6.47231797e-03,
        1.26214409e-02,  1.43137295e-02, -2.10054731e-03, -4.68324311e-03,
       -1.26068555e-02, -1.26754893e-02,  6.91695837e-03, -5.42897638e-03,
       -1.17285224e-02,  1.51922100e-03, -1.11550447e-02, -1.40363816e-02,
       -5.02780546e-03,  1.89902761e-03,  2.74923742e-02,  1.99061614e-02,
       -6.68198743e-04,  1.89456679e-02, -1.49208959e-02, -9.43012070e-03,
       -6.27251668e-03, -3.92745920e-02,  1.60048269e-02, -2.03354005e-02,
       -4.69191512e-03,  2.02214327e-02, -8.48283339e-03, -4.42137849e-03,
       -6.88118162e-03, -7.74826529e-03, -1.54716186e-02, -7.84657244e-03,
        4.96695051e-03, -9.97150131e-03, -6.84414292e-03,  5.01934718e-03,
       -2.05040015e-02,  3.86040173e-02,  7.01397145e-03,  1.67000340e-03,
       -3.86870722e-03, -1.86131708e-02, -1.81777123e-02, -4.15390218e-03,
       -4.96946101e-04, -3.56900692e-03, -1.93439005e-03, -1.59345139e-02,
        1.02185486e-02, -7.82155897e-03, -3.58393136e-03,  8.07363261e-03,
       -8.77749082e-03, -3.79180759e-02, -6.67865854e-03,  2.19767038e-02,
       -1.50163528e-02, -1.10144950e-02, -6.73108641e-03,  1.63020734e-02,
       -2.71802321e-02,  1.55238463e-02, -1.16679426e-02, -5.18926978e-02,
       -2.90819537e-02, -2.98294369e-02, -1.96796190e-03, -2.12491490e-04,
       -1.06768506e-02,  1.97450370e-02,  4.30324720e-03,  1.58653758e-03,
       -2.62652785e-02, -2.01735646e-03,  7.22392870e-04,  3.81208071e-03,
        1.76925119e-02, -1.39649203e-02,  1.29325669e-02, -2.14753952e-03,
        9.45849577e-04, -2.51663085e-02,  3.13729569e-02,  4.91596805e-03,
       -3.71583132e-03, -5.16355364e-03, -1.11842183e-02, -1.38650518e-02,
       -2.42101382e-02, -1.16860475e-02, -2.63785217e-02, -7.22634327e-03,
       -1.36116575e-02, -5.82704414e-03,  6.21071085e-04, -2.19148323e-02,
       -2.25377176e-02,  8.85752682e-03, -2.39777332e-03, -7.41296168e-03,
       -5.41086076e-03, -1.10255191e-02, -1.72344651e-02, -1.06041953e-02,
       -1.76254809e-02, -5.98308118e-03, -2.95212900e-04, -2.68975478e-02,
       -4.84580174e-03, -2.26070471e-02,  6.77341502e-03, -7.31585454e-03,
       -1.60867739e-02, -7.49325752e-03, -1.23122567e-02, -4.49374347e-05,
       -2.37707533e-02,  1.74506679e-02, -1.16584245e-02,  3.36393761e-03,
       -1.98033452e-03,  2.27808766e-03,  2.87123546e-02, -7.25499296e-04,
       -1.49293570e-02, -1.18980017e-02,  8.84468947e-03, -2.20821635e-03,
       -1.87291615e-02, -9.37274564e-03, -7.80006871e-04, -6.25602249e-03,
        6.28161011e-04, -3.31041194e-03, -3.14603150e-02, -1.26653090e-02,
       -1.22500490e-02,  4.02529351e-03,  4.49953079e-02, -1.54351033e-02,
       -1.30719524e-02, -1.79339983e-02, -1.14795729e-03,  7.27109425e-03,
       -4.75886986e-02, -1.33182912e-03, -3.64258513e-02, -7.13113649e-03,
       -1.53833199e-02,  3.81888065e-04,  6.82122028e-03, -2.11710706e-02,
       -1.91067085e-02,  9.25846770e-03, -2.40042135e-02,  1.71448573e-05,
       -5.04899658e-02, -9.06917732e-03, -2.07545562e-03,  4.88815736e-03,
        9.49987303e-03,  1.10244080e-02,  2.44930647e-02, -3.11616808e-03,
        3.30677233e-03, -5.25659882e-03,  7.50273000e-03,  1.22956303e-03,
       -9.17815123e-06,  1.99074093e-02,  6.40537031e-03, -8.08544178e-03,
       -1.95861552e-02,  7.55052664e-04,  4.32952587e-03, -4.89156554e-03,
        3.08379028e-02,  8.17848835e-04,  7.89044192e-04, -3.22844717e-03,
       -2.37193634e-03, -1.14657627e-02, -4.93812747e-03, -9.75547126e-04,
       -1.73845477e-02, -6.19046297e-03,  4.71712947e-02, -1.09005475e-03,
        1.70708578e-02, -2.24358067e-02, -6.95721526e-03, -1.48487184e-02,
       -1.30387349e-02, -8.82735197e-03, -8.71577486e-03, -5.52018755e-04,
       -1.66770387e-02, -1.60846524e-02, -3.40070692e-03,  2.09102104e-03,
       -7.26473844e-03,  1.29911583e-02, -1.34668704e-02, -2.10069632e-03,
        2.71409005e-03,  1.52211143e-02,  1.07232006e-02, -4.53831907e-03],
      dtype=float32), array([ 0.2927352 , -0.1684344 , -0.2551086 ,  0.33443052,  0.1384344 ,
       -0.12044702, -0.14589405, -0.18031968, -0.23502989,  0.08587912,
       -0.03056183,  0.14788747,  0.09296411, -0.33791426,  0.14625542,
        0.1216346 , -0.2900638 , -0.5821081 , -0.17156024,  0.0784958 ,
        0.29643455,  0.20344807, -0.49355036, -0.08486407, -0.08792497,
        0.18690759,  0.09978507, -0.0044741 ,  0.24067362,  0.36620286,
       -0.20281442, -0.02222267,  0.03177771,  0.00910649,  0.04005534,
       -0.05697608, -0.07062763,  0.1144262 ,  0.09036947, -0.26212272,
       -0.26088572, -0.22573665, -0.11247054, -0.16877417,  0.05270179,
        0.21045238, -0.05364168, -0.3952368 ,  0.04445476, -0.13690324,
        0.00938359,  0.05124998, -0.17239642,  0.1592705 , -0.00501048,
       -0.08672739,  0.42975792, -0.395086  , -0.1768199 , -0.3946886 ,
       -0.19863929, -0.03988539,  0.23775756, -0.20860884,  0.08574753,
        0.24441043,  0.11191501,  0.0852227 ,  0.47656792, -0.05782877,
       -0.27910122,  0.42423823,  0.13490203, -0.1438037 ,  0.09134437,
        0.27247852, -0.09630188,  0.03378915, -0.17255694,  0.21324766,
        0.40646192,  0.19554591, -0.25184703,  0.01263963, -0.00210768,
        0.08016711, -0.09306383,  0.2315597 ,  0.2794182 ,  0.13137107,
        0.10986036, -0.18336493,  0.16914384,  0.31223795,  0.22522125,
        0.30825338,  0.19693299,  0.15149802,  0.33673736, -0.23846707,
       -0.11165555, -0.1700897 , -0.0800143 ,  0.0800022 , -0.28775147,
       -0.05871726,  0.26619303,  0.04627355, -0.17499124, -0.23649226,
        0.14688514, -0.17626819, -0.21873263, -0.00962566,  0.03694522,
       -0.21694769,  0.14830835, -0.08502094,  0.15526377,  0.03754686,
        0.05765663, -0.19939643,  0.16451372, -0.06124165,  0.1102659 ,
       -0.17424724, -0.0447344 , -0.05041034,  0.10185001,  0.4163634 ,
       -0.1260308 ,  0.03674299, -0.19066602, -0.06565996, -0.03256553,
       -0.07827265, -0.32596585, -0.21084665,  0.06358796,  0.02448112,
       -0.1501168 , -0.10935032, -0.02367328, -0.15721358,  0.03689934,
       -0.28704605,  0.3769793 , -0.08243264, -0.00928307,  0.22488324,
       -0.08972631,  0.31877354, -0.11236268, -0.4388262 , -0.3210598 ,
        0.18204725, -0.16615714, -0.09940518,  0.04455309,  0.16877425,
       -0.17015897, -0.04712705, -0.30152097,  0.15692748,  0.3780202 ,
       -0.18730378, -0.01391768, -0.33555323,  0.18504068,  0.01757563,
        0.00529052, -0.05925952,  0.3656024 , -0.1413306 , -0.2956135 ,
        0.0077428 , -0.07623909, -0.22682734,  0.25297067, -0.07398366,
        0.04205219,  0.20037429,  0.12219205,  0.16078292, -0.07215478,
       -0.06027319, -0.05144249, -0.32271117, -0.02461466, -0.06404573,
        0.35914046,  0.05559114, -0.03091243,  0.18002103, -0.10546553,
       -0.0146849 ,  0.10766807, -0.15484482,  0.13144873, -0.04800864,
       -0.0307179 ,  0.47103783, -0.13167469, -0.03360518, -0.02669414,
       -0.09226094, -0.04456507, -0.13915214, -0.08523496,  0.28865016,
       -0.00724298,  0.10556719,  0.17484252, -0.05979805, -0.4783948 ,
        0.10520813,  0.4178862 , -0.28914377,  0.13724694, -0.17216133,
       -0.12684731,  0.01920197, -0.14082436,  0.02465692, -0.12823035,
        0.14352728,  0.08228755,  0.16435815,  0.08821569,  0.12303806,
       -0.23874664,  0.51087767,  0.25860456,  0.13722394,  0.118155  ,
        0.15229307,  0.10183218, -0.00671766,  0.00933184,  0.02900815,
        0.04876735, -0.17155744,  0.05954938, -0.44607672, -0.08512435,
       -0.03834608, -0.247751  ,  0.02528997,  0.3304824 ,  0.23947959,
        0.22913022,  0.10486852,  0.11213159,  0.19763987, -0.07192253,
        0.0320749 ], dtype=float32), array([1.3707105 , 1.219686  , 0.9293095 , 1.222805  , 1.1951128 ,
       0.88570035, 1.4186172 , 2.0459647 , 1.2109511 , 2.3624344 ,
       1.4578785 , 0.37601557, 2.5654657 , 2.9803307 , 1.99077   ,
       1.4697827 , 0.5550078 , 1.3033302 , 4.810805  , 2.0285242 ,
       1.5920999 , 1.5260849 , 1.5495325 , 1.8711107 , 2.0057461 ,
       2.389365  , 6.629106  , 1.9998394 , 2.213166  , 1.9097247 ,
       3.7061393 , 0.690609  , 1.7733065 , 2.18644   , 1.8184478 ,
       1.4285858 , 1.2429738 , 1.7353816 , 1.9038615 , 1.0866785 ,
       2.1744628 , 1.5582981 , 1.0185392 , 1.3470303 , 1.9188684 ,
       1.1696558 , 2.0682664 , 3.3038836 , 1.2742279 , 1.5446012 ,
       3.8301277 , 0.8064039 , 1.9075019 , 1.2828736 , 2.630444  ,
       1.5195045 , 1.8881959 , 1.0852677 , 2.599216  , 2.4923272 ,
       1.4472502 , 2.6798642 , 2.4609647 , 2.0762894 , 1.3762604 ,
       1.6329037 , 1.1045228 , 0.88230044, 1.0033498 , 1.744674  ,
       0.5462145 , 2.4680138 , 1.1855757 , 1.5450855 , 1.438658  ,
       0.7256173 , 1.586765  , 2.290772  , 0.64379203, 1.4284451 ,
       2.3913794 , 0.9777193 , 0.84957105, 2.177477  , 1.3092005 ,
       1.7412684 , 2.4618983 , 1.6665497 , 1.7817097 , 0.8780686 ,
       1.8907114 , 0.8516153 , 2.174898  , 2.091449  , 0.8840001 ,
       3.2168236 , 2.4741855 , 0.9304    , 1.5105431 , 0.72430444,
       0.8434365 , 1.4802151 , 3.8993893 , 1.8190353 , 3.004606  ,
       1.9605247 , 0.84007335, 0.6383499 , 6.0122724 , 1.3827441 ,
       3.2823522 , 3.8483195 , 1.575867  , 3.003617  , 0.7885246 ,
       0.83947784, 1.2973831 , 0.8449819 , 1.2233065 , 0.96067834,
       2.3822658 , 1.1337715 , 1.6914778 , 1.3844287 , 3.1015768 ,
       0.8427021 , 1.6700255 , 1.9098448 , 2.4481387 , 0.86554915,
       2.7863998 , 1.6169051 , 0.9649543 , 1.2802742 , 2.0880847 ,
       1.8340338 , 1.1504465 , 2.2391543 , 3.5200543 , 1.1808878 ,
       2.5978627 , 2.7865229 , 2.5443304 , 2.7666838 , 1.4544483 ,
       1.8394372 , 1.9786621 , 1.4814963 , 1.1401302 , 1.6556281 ,
       2.055168  , 0.9227525 , 1.3339636 , 3.1101334 , 2.690285  ,
       2.2715735 , 1.0903575 , 1.3562372 , 3.9118207 , 1.094021  ,
       2.9948032 , 3.3036792 , 1.3940672 , 2.417336  , 2.4769802 ,
       2.119569  , 1.223564  , 0.71309227, 4.1918564 , 1.2090573 ,
       1.5246084 , 1.7262144 , 2.2513087 , 1.7122552 , 2.1553383 ,
       1.3797748 , 2.320034  , 1.4345657 , 0.7869849 , 0.9320321 ,
       1.5727822 , 1.0084102 , 3.515118  , 1.2913011 , 1.5060738 ,
       1.6339184 , 1.9992764 , 1.0233359 , 2.3175285 , 0.8695676 ,
       1.7078248 , 1.8230805 , 1.3819603 , 2.15521   , 0.8969219 ,
       2.2185016 , 1.9820522 , 4.733775  , 0.83062655, 1.2711958 ,
       1.2375597 , 1.5527681 , 1.1403941 , 1.1337364 , 1.4073911 ,
       2.5297782 , 1.2799348 , 1.9129335 , 0.9576577 , 2.3198755 ,
       1.0508227 , 0.8071557 , 3.4642792 , 1.7829204 , 2.3000214 ,
       1.6680148 , 1.1595557 , 1.9744605 , 2.6278107 , 2.1885788 ,
       1.2701298 , 2.7033837 , 2.1150072 , 1.4450356 , 1.1548985 ,
       1.5549877 , 1.939419  , 1.0433853 , 2.380467  , 0.6818536 ,
       1.6927729 , 2.1682441 , 2.0214927 , 0.92125636, 1.032233  ,
       1.2188821 , 0.5710368 , 0.8242251 , 0.82336175, 2.171688  ,
       1.3183483 , 2.0096743 , 1.0400332 , 1.530827  , 1.5488743 ,
       1.1953586 , 2.3109033 , 1.0714798 , 1.1931202 , 1.3324454 ,
       1.4589444 , 1.2383822 , 1.3232987 , 1.9080584 , 0.5492957 ,
       1.851853  ], dtype=float32), array([[[[-0.02127564],
         [ 0.01084185],
         [-0.00215384],
         ...,
         [ 0.06155331],
         [ 0.03124547],
         [ 0.00589798]],

        [[-0.01253171],
         [-0.04217415],
         [-0.04436335],
         ...,
         [-0.01410129],
         [ 0.01921794],
         [ 0.02807781]],

        [[ 0.0468779 ],
         [ 0.02953025],
         [-0.03684644],
         ...,
         [-0.02749188],
         [-0.03707891],
         [-0.02321981]]],


       [[[-0.0071747 ],
         [ 0.04829217],
         [-0.02870525],
         ...,
         [ 0.01151004],
         [ 0.00860641],
         [ 0.00062308]],

        [[ 0.00487617],
         [-0.04804669],
         [ 0.04233092],
         ...,
         [ 0.04087646],
         [-0.0201133 ],
         [-0.04219899]],

        [[-0.00139381],
         [-0.02852293],
         [ 0.02189442],
         ...,
         [-0.00499577],
         [-0.00622703],
         [ 0.04048907]]],


       [[[-0.04718725],
         [-0.01252276],
         [ 0.00661266],
         ...,
         [ 0.03646699],
         [-0.0409431 ],
         [-0.02449944]],

        [[-0.01144911],
         [-0.04309849],
         [-0.04098889],
         ...,
         [ 0.06358836],
         [ 0.0406094 ],
         [ 0.02146741]],

        [[ 0.01616757],
         [-0.05505263],
         [-0.02455911],
         ...,
         [-0.02368582],
         [-0.03525038],
         [-0.04134016]]]], dtype=float32), array([[[[ 0.03282076,  0.00644428,  0.07834531, ...,  0.0315005 ,
          -0.0289962 ,  0.08347032],
         [-0.05413039, -0.06459798,  0.0187659 , ...,  0.019033  ,
          -0.03806467, -0.00306795],
         [ 0.00235039, -0.00219427,  0.01110974, ..., -0.05499326,
          -0.01289488,  0.04720382],
         ...,
         [-0.02890021, -0.02724046, -0.00681064, ..., -0.05229159,
          -0.06143891, -0.09478944],
         [ 0.00456511,  0.00447984,  0.03633755, ..., -0.03564067,
           0.04296124, -0.03003879],
         [ 0.03891617,  0.05052745,  0.03117809, ...,  0.02418935,
          -0.00180367, -0.01162309]]]], dtype=float32), array([1.0167472 , 0.99721324, 0.99560666, 1.0114355 , 0.999936  ,
       1.0009304 , 0.9931062 , 1.0129064 , 0.9991247 , 0.99585706,
       1.0231034 , 0.99551034, 0.9905717 , 1.0082061 , 0.9876065 ,
       1.0116183 , 0.99944276, 1.0069196 , 1.0029303 , 0.99056524,
       0.99098736, 0.99404156, 0.9983926 , 0.99553406, 1.0262268 ,
       1.009612  , 1.0013705 , 1.0020106 , 1.0006788 , 1.0074337 ,
       0.9968779 , 1.0037347 , 0.9935403 , 0.9947563 , 0.99007547,
       0.9919661 , 0.98016775, 0.9864973 , 1.002576  , 1.0126052 ,
       1.0006757 , 0.98890084, 1.0036676 , 1.0052221 , 1.0084302 ,
       0.9943941 , 1.0040929 , 0.985247  , 0.99528784, 0.9899625 ,
       1.0006884 , 0.9957688 , 0.9955204 , 0.99181736, 1.0172482 ,
       0.99851704, 1.004635  , 1.0022649 , 1.0105523 , 0.9921938 ,
       1.012992  , 0.9927611 , 0.9983199 , 1.0145063 , 0.97930485,
       0.99610347, 1.0056826 , 1.0093685 , 0.9931802 , 1.0148169 ,
       0.9958853 , 0.9956211 , 0.9993074 , 1.0014067 , 1.0098528 ,
       0.9994381 , 0.9994963 , 1.0120268 , 1.0069041 , 0.99887455,
       0.98714274, 1.0056398 , 1.0044938 , 1.00373   , 1.008015  ,
       1.0064414 , 0.99223787, 0.99727046, 1.0179061 , 1.0012194 ,
       0.9947814 , 0.99139655, 0.9848499 , 1.007229  , 0.9956755 ,
       1.0076437 , 0.9813845 , 1.0274444 , 1.0151191 , 1.0102702 ,
       0.9824901 , 0.9991058 , 0.9920029 , 1.005712  , 0.9987062 ,
       0.98881173, 0.99157035, 0.99028355, 0.99077135, 1.0063043 ,
       0.99405897, 0.99942863, 1.0124891 , 0.994185  , 0.99898934,
       0.99764395, 0.9844182 , 1.0100795 , 0.99666756, 0.993922  ,
       0.9975037 , 0.9883465 , 1.0081222 , 1.0195895 , 0.9965331 ,
       1.0019727 , 1.0027046 , 1.0072533 , 0.9986561 , 0.9863493 ,
       0.99615914, 0.9921463 , 1.012633  , 1.0016042 , 0.9890643 ,
       0.99903536, 0.9984315 , 0.9820218 , 1.0027567 , 0.9890742 ,
       1.012834  , 1.0006795 , 0.99996185, 1.0049409 , 1.0001879 ,
       0.9921143 , 1.0167857 , 0.9928919 , 1.0302008 , 0.9942703 ,
       0.99166876, 0.9954394 , 1.0037488 , 0.99681455, 1.0060817 ,
       0.9926265 , 0.9934389 , 0.9767546 , 0.99103886, 1.0122049 ,
       0.991766  , 0.99334323, 1.0032382 , 0.9926815 , 1.0146613 ,
       1.0045483 , 0.9928953 , 0.9936085 , 1.0172218 , 0.99773157,
       0.9945839 , 1.0086617 , 0.99603635, 1.0146855 , 1.0011222 ,
       1.010675  , 1.0172431 , 0.9956598 , 1.0308272 , 0.9937401 ,
       1.0057477 , 0.9947133 , 0.99419814, 0.9946845 , 1.0042425 ,
       0.990343  , 0.99994355, 0.9957227 , 0.994033  , 0.99051785,
       1.0158224 , 0.999391  , 0.99965256, 1.0124217 , 1.0029612 ,
       0.9969784 , 0.9987911 , 1.017179  , 1.0120014 , 1.0101708 ,
       1.0055189 , 1.0047289 , 1.0127815 , 1.0153921 , 0.9974903 ,
       1.0125543 , 1.0122741 , 0.97151315, 0.99823743, 0.9963263 ,
       0.98999685, 0.9960133 , 0.9887975 , 0.98963517, 1.0047975 ,
       0.9955243 , 0.99527836, 1.0036051 , 0.99643254, 1.0107181 ,
       0.9854617 , 1.0094271 , 0.99465865, 0.9853757 , 0.9995196 ,
       1.0100774 , 0.9906605 , 0.98734504, 1.0117275 , 0.98887736,
       0.9975904 , 0.9969769 , 0.99274063, 1.0027547 , 0.9911548 ,
       0.9949385 , 0.9936154 , 0.99265647, 1.0023303 , 1.0008444 ,
       1.0181653 , 0.99814475, 0.99677163, 0.998225  , 0.9964039 ,
       0.98057425, 0.988946  , 1.0082508 , 1.0265946 , 0.9961111 ,
       1.0107378 , 0.9906998 , 1.0010562 , 0.98619366, 1.0202816 ,
       0.9876239 , 0.99538326, 0.9966733 , 0.9822397 , 0.98964405,
       1.0076793 , 0.9914641 , 1.0141381 , 0.9972782 , 0.99577683,
       0.99251324, 0.9937841 , 1.0059116 , 1.0188293 , 0.9880965 ,
       0.9983344 , 1.0040622 , 0.9992164 , 0.9969605 , 1.0099326 ,
       1.0104293 , 0.99268657, 0.99688584, 1.0018964 , 0.99610984,
       1.0028888 , 0.985292  , 0.9879233 , 1.0107772 , 1.0000788 ,
       0.9974359 , 0.992658  , 1.0037193 , 0.99238   , 0.9951445 ,
       1.0038787 , 0.99297714, 0.97885406, 1.0037723 , 1.000006  ,
       0.9938132 , 0.99640083, 1.0027784 , 1.0134447 , 0.9959555 ,
       0.99799097, 0.98878884, 1.0208912 , 0.99786586, 0.99349266,
       0.9999561 , 1.0303792 , 0.987287  , 1.0317318 , 1.00328   ,
       0.9996563 , 1.0034628 , 1.012065  , 1.0039201 , 1.0094031 ,
       0.9944006 , 0.98079956, 0.9840359 , 0.9881789 , 1.0030729 ,
       1.0003265 , 0.99361414, 0.99614185, 0.9855412 , 0.9963045 ,
       0.9913756 , 1.0008992 , 0.9968239 , 0.9960925 , 1.0132575 ,
       0.992814  , 1.0057825 , 0.99689347, 1.001942  , 0.9875951 ,
       0.9958675 , 0.9956095 , 1.0001487 , 0.9947898 , 1.0181708 ,
       0.99045205, 0.9946118 , 0.999414  , 1.0095743 , 1.0011244 ,
       1.0031799 , 0.9997947 , 0.9947262 , 0.99307835, 1.0148656 ,
       0.9904275 , 0.99751157, 0.99821156, 0.9962357 , 0.99689794,
       1.0155632 , 1.0241578 , 0.99318194, 0.990369  , 0.99790853,
       1.0004444 , 0.9911724 , 1.0104527 , 0.9892857 , 0.99551255,
       1.0006404 , 1.0009139 , 0.99872476, 0.9999299 , 0.99561155,
       0.99296546, 0.99483544, 1.0032777 , 0.98048323, 0.99401736,
       0.99024695, 1.0015056 , 1.0032581 , 1.0184232 , 1.0007533 ,
       0.98747563, 0.9964346 , 0.98712265, 1.0016261 , 0.9928252 ,
       0.9894114 , 0.9989631 , 1.0041866 , 1.016841  , 0.9782678 ,
       1.0052959 , 0.9843457 , 0.99081266, 1.0111306 , 1.0096467 ,
       0.99922395, 0.9841649 , 1.0001959 , 0.9874198 , 1.0278904 ,
       0.9976674 , 1.010913  , 0.99399024, 1.0019248 , 1.0174954 ,
       0.99546385, 0.99513113, 1.0223485 , 1.0019579 , 1.0051599 ,
       0.98737884, 0.99749136, 0.988209  , 0.9952726 , 1.0057133 ,
       0.986845  , 0.99386394, 0.9981167 , 0.98847425, 0.99899286,
       1.0083212 , 1.0148089 , 1.0003495 , 0.9919742 , 1.0198331 ,
       0.99836874, 0.9940453 , 1.000953  , 0.995896  , 0.99755263,
       1.0074165 , 0.9874744 , 0.9900752 , 0.99830234, 0.99363375,
       1.0125005 , 1.0107971 , 0.98382825, 0.99295413, 0.99902666,
       0.9935031 , 1.0165228 , 1.0048468 , 1.0208626 , 0.9963954 ,
       0.986071  , 0.98516124, 1.0099933 , 1.0075054 , 0.9951824 ,
       0.9943803 , 0.99490386, 1.0089732 , 1.010723  , 1.0053296 ,
       0.9957852 , 0.9912775 , 0.99838114, 0.9911535 , 1.0078712 ,
       0.99174273, 1.020083  , 0.99266434, 0.99372476, 0.9984611 ,
       0.99543667, 0.98417246, 0.9979764 , 0.9967438 , 0.9949524 ,
       0.9971177 , 0.98214734, 1.0076518 , 0.99518746, 1.0039699 ,
       1.0112484 , 1.0028038 , 0.9893946 , 0.9972886 , 0.99654883,
       0.98978484, 0.9976404 , 0.99947464, 0.99959296, 0.9904267 ,
       0.9972045 , 0.99769205, 0.9984896 , 0.99824464, 0.99635345,
       1.0070292 , 0.99425554, 0.99392885, 0.9953789 , 0.9997201 ,
       0.9962084 , 0.9938409 , 0.9916556 , 1.0025074 , 0.99468833,
       1.0143077 , 0.9886731 , 1.0310196 , 1.0004148 , 0.99180204,
       0.99749815, 0.9994041 , 1.0182986 , 0.9842313 , 1.0006288 ,
       1.0108359 , 1.0009464 , 0.9985244 , 0.9989103 , 0.9940668 ,
       0.98710275, 0.99057853, 0.99954444, 1.0260236 , 1.0127153 ,
       0.99618006, 0.9904201 , 1.00624   , 1.0016623 , 0.9953084 ,
       0.9997556 , 0.9926077 , 0.9954339 , 0.9947115 , 0.9865094 ,
       0.9750857 , 0.9946432 , 0.9907037 , 1.0037096 , 0.9980988 ,
       1.0081213 , 0.9937215 , 0.9978343 , 0.990498  , 1.0009601 ,
       0.99491   , 1.006735  , 0.996861  , 1.0072455 , 0.9934006 ,
       0.99436474, 1.0050708 , 1.0130569 , 1.0003363 , 1.0002996 ,
       1.0035379 , 1.0156212 , 1.0081319 , 1.0001587 , 1.002224  ,
       0.99405533, 1.0082504 , 0.9917888 , 0.9967966 , 1.0013674 ,
       0.9947932 , 1.0160317 , 0.99714035, 1.0178449 , 0.9982115 ,
       1.0029044 , 0.9962514 , 0.99221325, 0.99387157, 1.007349  ,
       1.0075846 , 0.9912892 , 0.9940491 , 0.9855228 , 0.9959386 ,
       1.0043907 , 0.9988354 , 0.99611557, 1.0083326 , 0.99493533,
       1.0003159 , 0.99765766, 0.99905366, 0.990158  , 0.9987198 ,
       0.99872243, 1.0079296 , 0.9816714 , 1.0069898 , 0.9941192 ,
       0.9941188 , 0.99535584, 1.0028725 , 0.99192715, 0.9807902 ,
       1.0149184 , 0.9970927 , 1.0020655 , 0.99587667, 0.9812106 ,
       1.0090817 , 0.99389696, 0.99824715, 1.0072933 , 0.9958897 ,
       0.9897034 , 0.99937034, 1.0096462 , 1.0030401 , 0.99465966,
       0.9903412 , 1.0156888 , 0.9916135 , 1.001276  , 0.9834677 ,
       1.0295908 , 0.9989131 , 0.9933072 , 0.9866239 , 0.98231477,
       1.0165454 , 0.9973928 , 0.9845715 , 1.0018905 , 0.98582655,
       0.9910941 , 0.9884425 , 1.0022794 , 0.9950125 , 0.9807485 ,
       0.9915922 , 1.0030046 , 0.9930569 , 0.9833607 , 0.99734414,
       0.9989114 , 1.021787  , 0.99611276, 0.99386746, 0.9988173 ,
       1.0109482 , 0.99654746, 1.0013422 , 1.003032  , 0.9984134 ,
       1.0056531 , 1.0001192 , 1.0134597 , 1.0031022 , 0.99032277,
       0.99404025, 0.99983084, 0.9913796 , 0.992871  , 0.9991312 ,
       0.9950125 , 0.9857971 , 1.0046363 , 0.999665  , 0.99100214,
       1.0065079 , 0.9905725 , 1.005951  , 0.9907308 , 1.0274917 ,
       0.99451506, 0.9913982 , 0.9904776 , 0.9951523 , 1.0102044 ,
       1.003169  , 1.0016958 , 0.9912727 , 0.9945481 , 1.0070884 ,
       0.99197185, 1.0123681 , 0.99475515, 1.001176  , 0.9981238 ,
       1.002573  , 0.9851527 , 0.9981718 , 0.999253  , 0.9992944 ,
       1.0291516 , 1.0052761 , 1.0063666 , 1.0004499 , 0.99414676,
       1.0267035 , 0.9940617 , 1.0018892 , 0.99322563, 0.9889131 ,
       0.9990955 , 0.9942537 , 0.9977158 , 0.9917611 , 1.0308987 ,
       1.0035251 , 0.9899752 , 0.9876973 , 0.99337846, 1.0140321 ,
       0.99486226, 1.0075694 , 0.9911853 , 0.99008626, 1.0106874 ,
       0.98873407, 1.0032672 , 1.001366  , 0.99165857, 1.0120403 ,
       1.0268757 , 0.99058336, 1.0045017 , 1.0057086 , 0.98919815,
       0.99351203, 1.0003607 , 0.98636746, 0.9986688 , 1.0098281 ,
       1.0049614 , 0.9980368 , 0.9939079 ], dtype=float32), array([-5.34974504e-03,  8.46140552e-04, -2.29843485e-04, -2.19600601e-03,
       -2.81428713e-02,  8.81638099e-03, -1.13569312e-02,  5.71241486e-04,
        1.06685162e-02,  3.41020245e-03,  8.93094204e-03,  4.27276071e-04,
       -1.28191886e-02, -6.11066027e-03,  3.73951439e-03,  1.12495781e-03,
        9.18266270e-03, -1.62153393e-02,  8.01387522e-03, -7.13855552e-04,
       -1.75919547e-03, -1.84857135e-03, -1.15235639e-03, -6.44455617e-03,
        2.16167793e-02, -3.08393557e-02, -9.91887995e-04,  1.59946212e-03,
       -7.34804198e-03,  6.48338208e-03, -9.91097838e-03, -1.33206164e-02,
       -5.37942210e-03, -8.83699581e-03, -8.18410609e-03, -1.30868517e-02,
       -4.98999507e-05, -1.08450847e-02, -1.74981840e-02, -4.20260914e-02,
       -1.01822615e-02, -7.45297177e-03, -3.01641673e-02,  5.48369531e-03,
        6.42791297e-03, -8.63342267e-03, -7.27481162e-03, -1.50458477e-02,
       -5.54065802e-04, -1.36749428e-02,  6.34946208e-03, -4.37111082e-03,
       -3.89780151e-03, -1.45873521e-03,  9.58738197e-03,  2.93648173e-03,
       -5.16548101e-03, -8.83309357e-03,  7.31843198e-03, -3.95960268e-03,
       -4.59178425e-02, -8.66115466e-03, -4.41761734e-03,  7.83561356e-03,
       -5.10081090e-03, -8.94420780e-03, -1.45685989e-02, -1.27096502e-02,
       -1.15977053e-03,  1.63965896e-02,  3.03331879e-03, -4.47551720e-03,
        5.39653702e-04, -5.41515695e-03, -1.89811233e-02, -4.25503450e-03,
       -6.77606976e-03, -5.83270518e-03,  1.20184850e-02, -9.49857011e-03,
        3.83982458e-03, -2.10605338e-02, -5.02801612e-02, -2.75983065e-02,
       -2.41430365e-02, -4.55497252e-03, -9.79209784e-03, -2.05417704e-02,
        4.75685671e-03,  9.73722804e-03, -7.93743227e-03, -1.87286604e-02,
       -5.97646739e-03,  1.24990828e-02, -6.04061736e-03,  1.10344412e-02,
       -1.47960447e-02,  3.27158757e-02, -1.56817548e-02, -9.66458768e-03,
       -9.27999429e-03,  6.11303747e-03, -1.23024490e-02, -3.50722410e-02,
       -2.11300701e-03, -2.22094171e-02, -8.15968681e-03, -7.08650146e-03,
       -9.83438641e-03, -2.13593170e-02, -1.67000461e-02, -2.59699989e-02,
        1.31376795e-02, -1.81077234e-03,  9.13747493e-03, -4.58551385e-03,
       -5.77777950e-03, -2.62409355e-02, -9.11349710e-03, -4.38025268e-03,
       -8.48876126e-03, -1.20188417e-02,  7.26224016e-03,  1.97686329e-02,
       -1.20130479e-02,  2.20059548e-02,  1.77111407e-03, -1.23042148e-03,
        7.42286583e-03, -3.50568746e-03,  9.37092956e-03,  9.95813310e-03,
       -6.17418066e-03, -1.72423739e-02, -1.39440512e-02, -8.20771512e-03,
       -1.31721655e-03, -2.21187379e-02, -3.53103913e-02, -8.34210217e-03,
        3.85917653e-03,  1.63724832e-02, -6.98597357e-03, -1.38722714e-02,
       -1.56563949e-02, -8.61078501e-03, -5.75202107e-02, -2.85423710e-04,
        3.41557674e-02, -2.23470223e-03, -1.14829578e-02, -8.29517562e-03,
        4.18612827e-03, -9.18622967e-03,  1.42354975e-02,  1.76342065e-03,
       -6.10480085e-03,  2.90391559e-04, -1.73868495e-03, -2.20371652e-02,
        2.52176425e-03, -7.52225611e-03, -1.32744284e-02, -7.22162845e-03,
       -5.77997649e-03, -3.74500230e-02, -3.75878834e-03, -9.78114782e-04,
       -8.51008575e-03,  1.27608376e-03, -1.19310878e-02, -3.48167308e-02,
       -2.63079768e-04, -1.20720826e-02,  5.00209816e-03,  3.48865194e-03,
        2.15329770e-02, -1.70917362e-02,  1.04044145e-02, -2.28563393e-03,
        6.99532079e-03,  6.33111736e-03, -1.45052839e-02, -1.56253465e-02,
       -3.25392038e-02, -7.37245660e-03,  2.05838447e-03, -1.01721426e-02,
       -9.23253316e-03,  6.57322211e-03, -8.78350623e-03,  5.96034527e-03,
       -1.49503946e-02, -2.84790527e-02,  4.71809320e-03, -1.12631116e-02,
       -1.33050224e-02, -1.36946496e-02,  2.35190876e-02,  1.02164270e-02,
       -1.93654140e-03,  8.30741972e-03,  8.27017531e-04, -8.05418938e-03,
       -6.95598917e-03, -4.86621410e-02, -1.08030101e-03, -2.35487390e-02,
       -1.34343747e-03,  2.41649291e-03, -1.28661739e-02, -2.09473469e-03,
       -1.05108926e-02,  4.64010937e-03,  1.59755466e-03, -2.50746273e-02,
       -1.69941894e-04, -1.23971105e-02, -8.02064501e-03,  1.05625615e-02,
       -8.03547818e-03, -1.87494121e-02, -6.28529117e-03, -1.37589807e-02,
       -1.40809864e-02, -6.38344139e-02, -3.87822604e-03, -4.60195029e-03,
       -3.10671311e-02, -3.49478738e-04, -5.94427483e-03, -3.19327624e-03,
       -3.18831997e-03,  7.67594436e-03, -1.36536490e-02,  5.23540005e-03,
        6.96590869e-03,  3.36781435e-04, -5.03006671e-03,  1.44897180e-03,
       -2.64712237e-02, -4.79642535e-03, -6.24540215e-03, -3.69796809e-03,
       -7.78616406e-03, -2.17202981e-03, -9.71095360e-05,  2.73980619e-03,
       -3.28878090e-02, -3.37832887e-03,  1.68101606e-03,  8.13060149e-04,
        1.52776781e-02, -9.60866734e-03,  3.10814399e-02, -1.07178735e-02,
        1.04736947e-02, -4.00204863e-03, -1.29365511e-02, -4.20669699e-03,
       -1.71002671e-02,  1.91654731e-03, -7.63457315e-03, -9.42590274e-03,
        9.15240031e-03, -4.28646291e-03, -1.07310815e-02, -2.40170788e-02,
       -4.35113311e-02, -1.49794361e-02, -4.85706190e-03,  1.11428676e-02,
       -4.36794246e-03, -2.71885609e-03, -1.35189518e-02,  1.95934065e-02,
       -1.50524778e-02, -2.96414495e-02, -6.49178110e-04,  7.58364098e-04,
        6.73215650e-03,  1.65863184e-03, -7.72171980e-03, -1.62993707e-02,
       -6.32120715e-03, -2.44497531e-03, -1.29455817e-03,  7.25997658e-03,
       -3.67935225e-02, -8.75632744e-03, -2.36031730e-02, -4.40086937e-03,
       -1.79591589e-02,  3.90044507e-03, -9.00462968e-04, -1.73608307e-02,
       -1.28757199e-02, -9.45482403e-03,  1.19640969e-03, -1.06983967e-02,
       -7.09248520e-03, -1.41161913e-02, -5.85690746e-03,  6.75171008e-03,
        2.73647765e-03, -3.54724266e-02,  3.14209163e-02, -1.72934122e-02,
        3.06656566e-02,  4.83898772e-03,  2.29327101e-03,  1.25366868e-03,
       -1.41746337e-02, -1.25524346e-02,  1.01699121e-02,  9.07681417e-03,
       -8.55791382e-03, -1.45776826e-03, -2.90765557e-02,  3.00611742e-03,
       -2.42555211e-03,  1.28798038e-02, -9.72270034e-03, -1.14653772e-02,
       -7.93163548e-04, -9.20936652e-03, -2.19973456e-03, -1.80379301e-02,
       -2.45711789e-03, -9.05496906e-03, -3.95984948e-03,  7.21390639e-03,
       -1.00445619e-03,  1.62052899e-03, -1.99749451e-02, -5.06656291e-03,
       -5.92063647e-03, -2.64773425e-03, -1.63457096e-02, -3.48077491e-02,
       -4.29113163e-03, -4.90061659e-03, -4.99761524e-03, -4.05150242e-02,
        7.85915554e-03, -1.67183187e-02,  1.90595053e-02, -1.29488502e-02,
       -2.27376656e-03, -2.56119575e-02, -8.32084659e-03, -6.75840350e-03,
       -2.98114400e-03, -1.68271956e-03,  6.47717912e-04, -5.03267683e-02,
        2.17194278e-02, -5.26955677e-03,  6.11017924e-03, -3.42756044e-03,
        9.67197306e-03,  1.70978939e-03,  1.44869983e-02, -7.70760793e-03,
       -1.12601211e-02, -2.30103289e-03,  2.30567390e-03,  3.16859479e-03,
       -8.71133339e-03, -8.90849624e-03, -1.03533538e-02, -2.03312957e-03,
       -1.69249550e-02,  3.42271291e-03,  5.26953430e-04, -5.19717624e-03,
        3.12825888e-02,  2.92892335e-03, -3.01054399e-02,  8.42058193e-03,
        1.28221596e-02, -3.65445251e-03, -1.27063170e-02, -2.11992674e-03,
       -4.63823229e-03, -5.72369387e-03,  1.79562513e-02,  4.54885792e-03,
        1.63920484e-02, -3.01592704e-02,  5.17614884e-03, -1.77727714e-02,
       -8.32787436e-03,  1.45000294e-02, -1.83160603e-03, -1.34116353e-03,
       -1.46482754e-02, -1.22254677e-02, -1.51595380e-02, -6.96401484e-03,
        1.72882935e-03,  6.56281307e-04, -2.59720925e-02,  1.45758200e-03,
        3.54395024e-02, -1.36985583e-02,  1.49692921e-03, -3.96357328e-02,
       -8.09330307e-03,  4.83434973e-03, -1.08723864e-02, -3.76277529e-02,
       -3.08595854e-03, -1.87308714e-02, -1.14895701e-02, -1.49019826e-02,
       -7.72686722e-03, -7.04765646e-03,  1.46331696e-03, -9.84540489e-03,
       -1.23255923e-02,  1.81337204e-02,  1.91151933e-03, -1.61698386e-02,
       -2.38119978e-02,  4.35551908e-03, -1.30815785e-02, -2.63052490e-02,
       -6.57603331e-03,  5.67295915e-03,  5.39508276e-03, -1.57101769e-02,
       -1.04354089e-02, -1.27163678e-02, -3.04651093e-02, -1.54292779e-02,
       -4.29795496e-02,  1.21325767e-02, -8.33985303e-03,  6.63206680e-04,
       -4.12220620e-02, -7.98146147e-03, -7.73675600e-03,  2.22314671e-02,
       -8.28971714e-03, -1.28635475e-02,  5.59949130e-03,  1.94493551e-02,
        3.36082838e-03, -1.21340118e-02, -8.53031408e-03, -1.06205605e-02,
        2.56571416e-02,  1.07294954e-02, -7.30538415e-03,  7.76096131e-05,
       -2.71925493e-03, -1.38958800e-03, -1.04944622e-02, -1.07697556e-02,
       -2.79763830e-03, -8.45171046e-03, -3.67160863e-03, -8.26018397e-03,
       -2.09237132e-02,  2.12978193e-04, -8.87309480e-03, -4.21910640e-03,
        4.54788608e-03, -5.07326191e-03,  1.01294543e-03, -2.08344776e-02,
       -2.67254375e-02, -1.35047771e-02, -1.71164618e-04,  1.63335484e-02,
        7.14915339e-03, -2.33229510e-02,  4.70241718e-03,  1.51550258e-03,
       -7.21445400e-03, -8.74084607e-03,  7.34722707e-04, -2.47460557e-03,
       -5.70920715e-03, -1.50776794e-02,  1.12434672e-02, -1.07691460e-03,
       -6.38706377e-03,  6.23242231e-03, -3.93572263e-02, -3.41361202e-03,
       -4.06761002e-03, -8.92909151e-03,  8.05478264e-03, -5.29946643e-04,
       -4.95580537e-03, -1.05714826e-02,  6.28700713e-03,  5.71443979e-03,
        1.17754862e-02, -1.08152200e-02, -3.75864096e-02,  1.06074684e-03,
       -7.31956633e-03, -1.89859699e-02, -3.71288555e-03, -9.88540519e-03,
       -2.08826512e-02,  1.49518875e-02,  5.40773943e-03,  1.87016837e-03,
       -5.33270836e-03, -2.09654169e-03, -1.18904347e-02, -4.01547737e-03,
       -8.54145084e-03,  9.32700175e-04,  2.77091283e-03, -2.50253007e-02,
       -2.97097247e-02,  7.94337131e-03, -1.26134302e-03,  1.10493759e-02,
       -5.46286721e-03,  6.81887195e-03, -2.34246231e-03, -2.40413472e-02,
       -2.02310923e-02, -8.67326371e-03,  1.37391733e-03, -2.25317315e-03,
       -1.01587530e-02,  2.09190976e-03,  3.16533144e-03, -3.46485712e-02,
       -1.58181340e-02, -4.02729632e-03,  5.43080561e-04, -2.62296549e-03,
       -5.26962057e-03,  2.86708418e-02, -3.42459098e-04,  4.48317733e-03,
       -5.74260112e-03, -9.40608606e-03,  1.22972010e-02,  1.87877289e-04,
        3.90663464e-03, -1.73780287e-03,  3.03250179e-03, -1.21723162e-02,
        8.41751974e-03, -9.06527787e-03, -5.51161880e-04,  5.93963778e-03,
        2.92357113e-02, -1.05930958e-02,  1.31323989e-02,  4.63084131e-03,
       -4.06871084e-03, -2.42268927e-02, -6.50290120e-03, -1.41056776e-02,
       -6.38787309e-03,  2.73566548e-04, -5.17733395e-03, -7.46731600e-03,
       -1.07084936e-03,  8.42272211e-03, -1.82803138e-03, -1.17663918e-02,
       -2.16840697e-03, -3.44287092e-03,  3.19264061e-03, -5.42810140e-03,
        1.40097169e-02, -6.56603323e-03, -1.96300540e-02, -1.05221560e-02,
        7.67548161e-04, -7.83295929e-03,  3.93516943e-03, -1.93956513e-02,
       -7.15727964e-03,  8.84296279e-03, -5.72396582e-03, -2.01993175e-02,
       -1.34037260e-03, -4.79454873e-03, -1.06784850e-02, -1.53154777e-02,
       -3.25435102e-02, -9.71589703e-04, -1.11585110e-02,  1.96635094e-03,
       -3.18596698e-03, -8.77837837e-03, -5.51771745e-03, -7.13585457e-03,
        1.40372701e-02, -8.83729476e-03, -3.99038335e-03, -1.85941458e-02,
       -1.79460812e-02, -3.57366749e-03,  1.13337217e-02, -4.15847711e-02,
       -4.13961187e-02, -1.12156430e-02,  7.26141687e-03,  9.64151230e-03,
       -9.97493789e-03, -4.79016686e-03, -2.42548343e-02, -4.56311740e-02,
       -1.88428927e-02, -1.00696571e-02,  2.42480752e-03, -1.17742065e-02,
       -4.20483053e-02,  2.51096883e-03, -9.25035961e-03,  7.48449890e-03,
        9.86849656e-04, -2.11607199e-04, -1.31902006e-02, -1.53594809e-02,
        7.10834842e-03, -1.29344594e-02, -1.10077939e-03,  8.72323173e-04,
        3.59461992e-04, -4.26098704e-02, -3.17060715e-03, -1.55278342e-02,
       -2.32919725e-03,  6.22854521e-03, -3.38971149e-03, -6.15443336e-03,
       -2.26940289e-02,  6.71316753e-04, -8.18927586e-03, -3.77266295e-03,
       -2.37942673e-02,  6.43815892e-03,  3.52603453e-03, -3.20312306e-02,
        1.04604475e-02, -1.46170910e-02,  4.48218128e-03, -1.29070990e-02,
       -4.35436284e-03, -4.09873528e-03, -1.01740994e-02, -1.74072850e-02,
       -1.69123225e-02, -1.01132747e-02,  7.87242223e-03, -6.07745489e-03,
       -3.08616180e-03,  2.88702105e-03, -1.48870156e-03, -1.48114301e-02,
       -3.46543826e-03,  5.19618858e-03, -1.02970768e-02, -1.26556922e-02,
       -1.24667846e-02, -3.17752771e-02,  1.32234599e-02, -7.94400461e-03,
       -3.14302772e-04,  2.28967774e-03, -7.10713258e-03, -1.66530740e-02,
       -4.27434891e-02,  6.64042635e-03,  1.02386288e-02,  9.01530875e-05,
       -4.93829288e-02, -5.44105947e-04, -4.77525126e-03,  5.63555118e-03,
       -6.21561287e-03,  4.49570641e-02,  7.95036461e-03,  4.36565373e-03,
       -1.02674146e-03, -6.99159596e-03, -1.21846506e-02, -9.49620735e-03,
        2.76463432e-03, -7.50317145e-03, -1.03105260e-02,  1.83064456e-03,
       -7.46653788e-03,  6.73248246e-03,  3.26679554e-04,  1.92052349e-02,
       -5.47422934e-03, -5.59760770e-03, -1.65484454e-02, -7.89006520e-03,
        1.41710760e-02, -1.08680883e-02, -8.95147386e-04, -2.09909026e-02,
        6.03326783e-03, -2.18564142e-02, -8.03897437e-03, -1.49534782e-02,
        1.86428812e-03, -9.11504403e-03, -6.95751375e-03, -1.31821521e-02,
       -1.49212060e-02, -8.25694390e-03,  1.26684364e-02, -1.67291518e-02,
       -1.29211769e-02, -2.76519116e-02, -6.42160513e-03, -5.13450650e-04,
        2.07105447e-02, -6.99994946e-03, -3.23559949e-03,  7.43438024e-03],
      dtype=float32), array([ 0.13576639,  0.01669638, -0.05619092, -0.01948583,  0.10705191,
       -0.09867576, -0.00670509,  0.03682195,  0.00560377, -0.06881869,
       -0.03457554, -0.03103521,  0.01476688,  0.0050775 , -0.08515856,
        0.00083452, -0.05299852,  0.054181  ,  0.02322661,  0.01637505,
       -0.05847504, -0.01126718,  0.0240385 , -0.12356406, -0.09390914,
        0.04451917,  0.11680218,  0.0725247 , -0.08790716, -0.02670318,
       -0.05794987,  0.08398132, -0.03679094,  0.02439621, -0.01227276,
        0.0304587 , -0.02132497,  0.05526272,  0.06433665,  0.1090543 ,
        0.07286416,  0.00851226,  0.03647207, -0.01375245,  0.00822857,
        0.00228468,  0.07473749,  0.00301194,  0.06708544,  0.05879767,
       -0.01388482,  0.0125863 , -0.03747109,  0.02265938,  0.03546992,
       -0.11154275,  0.15600644,  0.04732947, -0.03754078,  0.06821834,
        0.1233458 , -0.06857254, -0.09024364, -0.0252865 , -0.04364527,
        0.06150956,  0.02710071,  0.05045265,  0.00798381, -0.08977316,
       -0.12931427,  0.03076708, -0.10367545,  0.05200357,  0.04776788,
        0.03060654,  0.08099981, -0.05742203, -0.02083898, -0.00243538,
       -0.04527238,  0.06058894,  0.1371966 ,  0.08113684,  0.06581367,
        0.03045829, -0.02768333,  0.0008594 ,  0.03859816, -0.01657638,
        0.08386541,  0.01497889, -0.01350789, -0.12926584, -0.06204409,
        0.00941202,  0.0026381 , -0.05934453,  0.11897   ,  0.09322713,
        0.00144408,  0.08145957,  0.01356192,  0.06208147,  0.03609541,
       -0.00265413,  0.03225759, -0.00129861,  0.0104575 ,  0.07244162,
        0.00474768,  0.01667845, -0.00860225, -0.01282848,  0.08793338,
        0.02561535,  0.09983146,  0.02782246,  0.01306115,  0.03741652,
       -0.03683006,  0.04225369, -0.03142444,  0.00377046, -0.0903409 ,
       -0.11064603, -0.11747829,  0.07923473,  0.0129514 , -0.03071488,
       -0.01464695, -0.05729533,  0.11321126,  0.12412009, -0.06892592,
        0.06573627, -0.02052803, -0.05366955,  0.09475007, -0.00228257,
        0.0874398 , -0.03398512,  0.05150024,  0.07197288,  0.08665917,
       -0.0683803 ,  0.05522123, -0.02066278,  0.01835347, -0.07332267,
        0.09179568,  0.07410732, -0.02880595,  0.03871044, -0.03963367,
        0.00558507, -0.04936299, -0.05105094, -0.03962127,  0.05527804,
        0.07683221, -0.02095625,  0.09458302,  0.01648156,  0.04106374,
        0.09031669, -0.00929534,  0.00851848,  0.11213885,  0.00478467,
        0.03598506,  0.08046266,  0.04183279,  0.00684163, -0.00698145,
       -0.00148364, -0.0660233 , -0.00218629, -0.11765512,  0.09882365,
        0.00790122, -0.04375517, -0.12532942,  0.11193648,  0.04294639,
       -0.03895965,  0.09355615,  0.05033743, -0.05501834, -0.03641133,
        0.04589906,  0.00611645, -0.00104126,  0.03974036, -0.02491857,
        0.08705271, -0.0963652 ,  0.04925367, -0.09110331,  0.03577401,
       -0.0765482 , -0.01633894, -0.02351574,  0.04800807, -0.01134435,
        0.1497137 ,  0.04779188,  0.02816729, -0.0528066 , -0.0537409 ,
       -0.07713249,  0.05289357,  0.04531094,  0.01425622,  0.07974138,
        0.12210166, -0.04485001,  0.11594805, -0.06716591, -0.04250419,
        0.06336518,  0.07065815,  0.03614533, -0.13298535,  0.01817607,
        0.0921331 ,  0.01537818, -0.0318989 ,  0.08065127, -0.05728219,
       -0.08821373,  0.05299439,  0.06456389, -0.00460963, -0.03316351,
       -0.03909744,  0.04436183, -0.03317681, -0.02204471, -0.11176809,
        0.08406908, -0.06234325,  0.04156156,  0.14438534,  0.04135919,
       -0.0333437 , -0.10758485, -0.06672911,  0.03960779, -0.01203388,
        0.00498988,  0.06106756,  0.00543744,  0.05725447,  0.03623818,
       -0.03188999,  0.02773011,  0.02098628,  0.00043171,  0.00588952,
        0.07803212, -0.01393835,  0.16742417,  0.05696953, -0.06244011,
        0.11398421,  0.10543344,  0.05186123,  0.06606734,  0.03927955,
       -0.04816272, -0.0190777 , -0.01552212, -0.02421099,  0.11859241,
       -0.02031706,  0.07758708, -0.03031478,  0.10494891, -0.04266217,
        0.01546472,  0.10740183, -0.0104019 ,  0.10698193,  0.01458229,
       -0.05674706,  0.00314979,  0.03261444,  0.02732434,  0.0739513 ,
        0.1179615 , -0.02615174,  0.14228137, -0.0433748 ,  0.08532047,
        0.02499277, -0.07458957,  0.12182654, -0.05429504,  0.10178995,
       -0.01464742,  0.09230254,  0.05084615,  0.04518838,  0.01149404,
        0.11699467, -0.03810479, -0.03227561, -0.05449941, -0.0380014 ,
        0.05163426, -0.00142501,  0.11082935,  0.0565607 , -0.05902486,
       -0.02642836,  0.08494899, -0.03799785,  0.05549231, -0.04278872,
       -0.04074372,  0.00152357,  0.05528261,  0.01693345, -0.05475273,
       -0.0438467 ,  0.04684453,  0.0041047 ,  0.01294779,  0.1554673 ,
        0.04095636,  0.06911578,  0.0307955 ,  0.06368393,  0.05657921,
        0.03414944,  0.01075386,  0.04777096,  0.02711328,  0.04022283,
       -0.07478731,  0.07489886,  0.05392638,  0.10189226,  0.04399296,
        0.06788035, -0.05604099,  0.11767805,  0.0134362 ,  0.06451399,
        0.02652297,  0.01055352, -0.04499985,  0.04773431,  0.0151308 ,
        0.11102325, -0.00034501, -0.04384232,  0.00562412,  0.02390221,
        0.01834423,  0.11884573,  0.04707238, -0.12250823,  0.05531349,
        0.10465056,  0.01106215, -0.0107355 ,  0.11907119, -0.0045483 ,
       -0.04077449, -0.00607214,  0.01920693, -0.03368189, -0.00833766,
       -0.05806097, -0.07617064,  0.12677416,  0.11065161,  0.06940871,
       -0.09521081, -0.06341793,  0.09216481,  0.03404938, -0.02760492,
        0.00721687, -0.05921417, -0.02238334, -0.12630871,  0.04346567,
        0.13610318, -0.05378977, -0.03025208,  0.02258324,  0.09704539,
        0.01244202,  0.10809531,  0.07657299, -0.02063946,  0.08078275,
        0.03918606,  0.16424735,  0.09923676, -0.04518094, -0.01633169,
        0.04188683,  0.00541031,  0.09499108,  0.11831679, -0.04441509,
       -0.01282408,  0.1041695 , -0.04581843, -0.08394656,  0.05508961,
       -0.03375651, -0.03202178, -0.1260726 ,  0.00757998,  0.14705646,
        0.00530398, -0.04280839,  0.02063484, -0.0890967 ,  0.11760777,
        0.02787499,  0.07311717,  0.07317508,  0.01969773, -0.00968056,
        0.06476954, -0.03245318, -0.01131449,  0.04570961,  0.01368086,
        0.04687465,  0.03246941, -0.06828448,  0.00261366,  0.07981283,
        0.09397183,  0.0527065 ,  0.01897805, -0.05881771,  0.12429908,
        0.04263265, -0.07556023, -0.04853828,  0.03553231,  0.07075933,
       -0.00748451,  0.07218751, -0.08116372, -0.04171851,  0.05280977,
        0.03042604,  0.00634645,  0.03891367, -0.03511215,  0.10707103,
        0.03790143,  0.0843114 , -0.04254389,  0.04946982,  0.06838068,
        0.05464681,  0.00527025,  0.00577681, -0.09952145, -0.03494357,
       -0.05491722,  0.03293999,  0.12019008,  0.04462871, -0.07288206,
       -0.09015194, -0.09216373,  0.10959891, -0.01266618, -0.03167926,
       -0.08713962,  0.05242041,  0.03379368, -0.02707925,  0.03294545,
        0.08530224,  0.00282477, -0.0332388 , -0.02396612, -0.03335121,
        0.0739601 , -0.03330776, -0.0457076 ,  0.06899429, -0.04196686,
       -0.02700393, -0.0014249 , -0.00987427, -0.05879338,  0.03253192,
        0.10257786,  0.11218898,  0.11388159,  0.03701768,  0.0231535 ,
        0.09071162,  0.04502437,  0.01313992,  0.02166946, -0.00229712,
        0.01105536,  0.032501  ,  0.00866399,  0.05563319, -0.10516011,
       -0.11921731,  0.01083204,  0.02708205,  0.02410921,  0.10419972,
        0.07481135, -0.03775141,  0.01921747,  0.00843747,  0.02084414,
       -0.09885618,  0.00476062,  0.04770408,  0.06229541,  0.00276681,
        0.03122535, -0.07378882,  0.06975896, -0.07696803,  0.00902718,
        0.09949818,  0.00482099, -0.00746854, -0.07938308,  0.04519632,
       -0.02679403, -0.08816468, -0.00688676,  0.07318875, -0.0556129 ,
       -0.08913846, -0.02949508,  0.12731372,  0.01028123,  0.05459752,
       -0.00691061,  0.14043206,  0.06266037,  0.03224174,  0.01900655,
       -0.09678537, -0.05718552,  0.01570653, -0.06916445,  0.03101808,
       -0.03967   ,  0.08702421, -0.04444912,  0.0746384 , -0.05647402,
        0.01431546,  0.03389955, -0.03006926,  0.06818644, -0.03130724,
        0.02934143,  0.02562401,  0.01796372, -0.0660925 ,  0.07578758,
        0.03167269, -0.02532392, -0.02403666,  0.04403531,  0.11242752,
        0.1434801 , -0.02258117, -0.14379752, -0.03177266,  0.01689671,
       -0.03521338, -0.05706073, -0.00395266,  0.0038199 , -0.01486707,
       -0.05108096,  0.03772675,  0.0874412 , -0.05159203, -0.10077964,
        0.09904879, -0.08023019,  0.08643157,  0.01781737,  0.07046095,
       -0.04414777, -0.07352498,  0.08067232,  0.08370817, -0.01276307,
        0.06005352, -0.02328447,  0.10211476,  0.02788153,  0.09121291,
       -0.07348543, -0.05956927, -0.05499742,  0.08447543,  0.05584245,
        0.11323815,  0.02593588,  0.08956484,  0.02252303,  0.03412688,
        0.07059471,  0.05032652, -0.00062355,  0.0367198 , -0.05313968,
       -0.09042367, -0.05000307,  0.00089096,  0.09052205, -0.05510868,
        0.05708016, -0.01136898, -0.06556609,  0.1111805 , -0.0047357 ,
        0.04276505,  0.11667681, -0.08216498, -0.00242232,  0.11715555,
        0.06565401,  0.01662907,  0.05125834,  0.025048  ,  0.02454244,
        0.04409337, -0.13621545,  0.08075366, -0.06982063, -0.00912212,
       -0.09385687,  0.01753964,  0.07836682, -0.05010835,  0.01823843,
       -0.03768053,  0.0124302 ,  0.07905713,  0.08147945,  0.05097202,
        0.0858695 , -0.0214359 ,  0.0601752 , -0.05900073,  0.03448028,
        0.00406212, -0.0387356 , -0.09150907,  0.07455435,  0.10409082,
       -0.07895141,  0.04369804, -0.10478333,  0.01130217,  0.05085941,
        0.05519348,  0.10539473,  0.11670569,  0.01580848,  0.0180435 ,
        0.04607646, -0.05782013, -0.07400326,  0.0265648 ,  0.10065391,
       -0.1206041 , -0.01162501, -0.04417552,  0.02772307,  0.03545675,
        0.03239915, -0.00379147,  0.02542533, -0.04695366,  0.00323804,
        0.01419629, -0.0780478 ,  0.04358262,  0.02313962, -0.04370207,
        0.05878236,  0.04358498,  0.00448566, -0.02027074,  0.02413712,
        0.07675631,  0.05059709,  0.06278199, -0.00965624,  0.10667661,
       -0.04207459,  0.07535693,  0.06450137, -0.04649458,  0.06881898,
        0.05863689, -0.06195748, -0.0415341 ,  0.02124424, -0.01306694,
       -0.05744688,  0.0410498 , -0.0135713 ,  0.04627466, -0.05813891,
        0.00261954,  0.03162824, -0.04417514], dtype=float32), array([0.09504008, 0.08550215, 0.09583427, 0.09341181, 0.13818017,
       0.11112741, 0.08483013, 0.09330347, 0.09487805, 0.08790053,
       0.0935818 , 0.08597141, 0.08545657, 0.11685211, 0.11524779,
       0.08431952, 0.10311503, 0.09365776, 0.0879457 , 0.09339853,
       0.10661804, 0.08770905, 0.08661313, 0.10070723, 0.10458709,
       0.14631005, 0.12147635, 0.09720032, 0.08653962, 0.08966342,
       0.09736314, 0.10638983, 0.08904209, 0.08798756, 0.08383818,
       0.08581782, 0.08560394, 0.09009405, 0.10928228, 0.11000037,
       0.08596215, 0.08988218, 0.11601128, 0.09247011, 0.08710547,
       0.09696466, 0.08885603, 0.08586315, 0.09128048, 0.08699721,
       0.09053807, 0.0872191 , 0.10838701, 0.0849977 , 0.09170449,
       0.09262833, 0.10255115, 0.0945074 , 0.11173543, 0.08745876,
       0.13022296, 0.08718894, 0.0944376 , 0.08986305, 0.08540198,
       0.08932411, 0.08687457, 0.09082013, 0.08526551, 0.09765711,
       0.10517173, 0.11730575, 0.10302462, 0.11400496, 0.0906194 ,
       0.08676989, 0.09146989, 0.09636992, 0.09449852, 0.10071552,
       0.08765565, 0.11536726, 0.11643815, 0.1005228 , 0.11123304,
       0.08590442, 0.09478457, 0.0920372 , 0.12402654, 0.08611227,
       0.08967537, 0.10189327, 0.08734512, 0.11481959, 0.08781669,
       0.08919903, 0.10826894, 0.09527345, 0.10607293, 0.11686984,
       0.09299759, 0.08664054, 0.09625328, 0.10886189, 0.09287457,
       0.08919764, 0.08647439, 0.08418299, 0.08408552, 0.12472122,
       0.08715134, 0.09942131, 0.09021309, 0.08900783, 0.08970858,
       0.08473445, 0.09983589, 0.15087868, 0.0868004 , 0.08704983,
       0.0867896 , 0.1017404 , 0.09320204, 0.08889971, 0.08855846,
       0.10740695, 0.09378985, 0.09336996, 0.09357703, 0.08504706,
       0.08734018, 0.08922545, 0.1129462 , 0.1134195 , 0.10022549,
       0.08497385, 0.08671432, 0.09408619, 0.09537213, 0.08953276,
       0.11870487, 0.09479284, 0.09348198, 0.1134757 , 0.10695752,
       0.08904117, 0.10110613, 0.09773111, 0.10355254, 0.10561487,
       0.1083346 , 0.09450936, 0.09902609, 0.09194651, 0.11519755,
       0.08921234, 0.08710174, 0.08912433, 0.08822738, 0.09292584,
       0.08787063, 0.08832405, 0.09561048, 0.08457483, 0.08929004,
       0.10951976, 0.08693798, 0.08560091, 0.09744362, 0.08863502,
       0.08639726, 0.1213461 , 0.09930833, 0.09549654, 0.08600181,
       0.09741209, 0.10282729, 0.09002792, 0.10122304, 0.08874363,
       0.09190746, 0.09075806, 0.11117367, 0.12763213, 0.09765497,
       0.09057444, 0.10544908, 0.09775206, 0.09382956, 0.09600326,
       0.10086747, 0.08523586, 0.10567661, 0.1088665 , 0.09875165,
       0.09736183, 0.08833735, 0.1168057 , 0.09521452, 0.08696809,
       0.1033307 , 0.10061397, 0.08643423, 0.09571188, 0.08605086,
       0.11982602, 0.10023246, 0.09766885, 0.09171396, 0.0887303 ,
       0.1108394 , 0.09433082, 0.08925684, 0.08634844, 0.08971342,
       0.13535887, 0.0854246 , 0.10496675, 0.09415603, 0.08762491,
       0.09955557, 0.08976257, 0.08442636, 0.09901734, 0.09947053,
       0.13697559, 0.08690043, 0.084554  , 0.11975136, 0.0913607 ,
       0.09265995, 0.08927125, 0.088257  , 0.08842073, 0.0876231 ,
       0.08551732, 0.0893254 , 0.08847806, 0.09427192, 0.12308653,
       0.10422602, 0.08800282, 0.08841648, 0.12073797, 0.10558134,
       0.08537248, 0.12226687, 0.09472682, 0.09202722, 0.09089485,
       0.09314281, 0.08476768, 0.08775417, 0.0934891 , 0.08690099,
       0.08657973, 0.10066843, 0.09040597, 0.09456629, 0.08777064,
       0.11586925, 0.0892828 , 0.1323096 , 0.10350868, 0.09702481,
       0.1054699 , 0.10102196, 0.11089964, 0.12105242, 0.09177597,
       0.09429873, 0.08529438, 0.08439238, 0.09554785, 0.11447485,
       0.09436467, 0.0960702 , 0.10645478, 0.09985261, 0.09659178,
       0.09564926, 0.1043632 , 0.0857213 , 0.09229474, 0.0852996 ,
       0.09022664, 0.08480934, 0.09071207, 0.09985313, 0.09854974,
       0.11454578, 0.085811  , 0.11749107, 0.09129588, 0.11982498,
       0.0931195 , 0.0986632 , 0.09385034, 0.09025599, 0.11529723,
       0.08756261, 0.12511879, 0.09171384, 0.08364715, 0.08440445,
       0.11731023, 0.12221643, 0.0897762 , 0.09582083, 0.09183211,
       0.0941403 , 0.08611885, 0.1010719 , 0.09712726, 0.0967929 ,
       0.10384008, 0.09729781, 0.09935373, 0.09593853, 0.09523203,
       0.08969962, 0.08911763, 0.0957065 , 0.09659726, 0.09010751,
       0.09523252, 0.08791798, 0.08541029, 0.08576215, 0.14459054,
       0.09692646, 0.09201819, 0.08633098, 0.08558817, 0.08657527,
       0.08490208, 0.08521424, 0.08933444, 0.0986226 , 0.10921836,
       0.08978927, 0.09972175, 0.09738857, 0.11762125, 0.09113699,
       0.08707842, 0.09583057, 0.09103202, 0.08915742, 0.10054047,
       0.08972864, 0.0912554 , 0.08919897, 0.08721454, 0.0902165 ,
       0.11813651, 0.0855623 , 0.08606017, 0.09437598, 0.11082856,
       0.08650006, 0.09478734, 0.09422836, 0.10193747, 0.09004544,
       0.10906398, 0.0870263 , 0.09185912, 0.09366753, 0.0866878 ,
       0.09923933, 0.08800843, 0.10455516, 0.09290114, 0.08625684,
       0.09751409, 0.0900272 , 0.09014671, 0.10442945, 0.08899399,
       0.08895251, 0.10353018, 0.10074033, 0.09001978, 0.08999117,
       0.0870466 , 0.1216685 , 0.0897439 , 0.0937752 , 0.09272799,
       0.09346355, 0.08539253, 0.08477677, 0.09424132, 0.12077965,
       0.08573361, 0.09529059, 0.09064285, 0.08511022, 0.13455041,
       0.08875653, 0.10813338, 0.09815056, 0.09427964, 0.11638951,
       0.10248917, 0.09815254, 0.10533892, 0.0883579 , 0.09435897,
       0.09100316, 0.10043713, 0.09176034, 0.08486719, 0.10366812,
       0.09075087, 0.08411115, 0.09873408, 0.08943132, 0.10516064,
       0.08530866, 0.10280654, 0.09859639, 0.09570371, 0.10850033,
       0.09400518, 0.1250271 , 0.10440066, 0.08814157, 0.08989751,
       0.0852844 , 0.08992092, 0.09196059, 0.09600912, 0.10164535,
       0.0935589 , 0.09701446, 0.09372754, 0.08807155, 0.10201778,
       0.10552417, 0.08955695, 0.08470044, 0.0961487 , 0.12929763,
       0.0957442 , 0.0949416 , 0.11546083, 0.09233148, 0.08712635,
       0.08449253, 0.09617887, 0.12134301, 0.12025277, 0.09354603,
       0.08823736, 0.08972893, 0.08742123, 0.08671337, 0.10234076,
       0.08552926, 0.14239573, 0.08548639, 0.08740337, 0.11172044,
       0.08670931, 0.09060794, 0.08401679, 0.09923206, 0.08664187,
       0.08589916, 0.08575758, 0.1285934 , 0.09828663, 0.09390186,
       0.1008179 , 0.10437544, 0.12619127, 0.09271415, 0.0910207 ,
       0.09547014, 0.10015716, 0.08781145, 0.0857755 , 0.08900482,
       0.10008363, 0.09016535, 0.09636968, 0.09592863, 0.08398432,
       0.10943616, 0.08508323, 0.09393905, 0.08930064, 0.09938065,
       0.08732511, 0.08429237, 0.08851291, 0.10399077, 0.08747847,
       0.08975028, 0.11293423, 0.1139634 , 0.08895142, 0.08712593,
       0.11847521, 0.08919478, 0.10003547, 0.09085464, 0.08519721,
       0.08845931, 0.08972402, 0.08455873, 0.10891541, 0.1182419 ,
       0.09563179, 0.08518453, 0.08356491, 0.09549072, 0.13374783,
       0.10627963, 0.08475507, 0.10736336, 0.08608461, 0.09592352,
       0.09432545, 0.08873624, 0.09019174, 0.12612788, 0.08650144,
       0.08717865, 0.1038676 , 0.09698346, 0.09847995, 0.08545927,
       0.10313626, 0.08687747, 0.08753139, 0.10120756, 0.09160035,
       0.08906756, 0.09903109, 0.08712543, 0.11147971, 0.08618718,
       0.09237648, 0.08531171, 0.11741853, 0.08533046, 0.09831725,
       0.08944308, 0.10111197, 0.09432262, 0.09329212, 0.08623145,
       0.10197926, 0.12071846, 0.10165806, 0.10519066, 0.09279237,
       0.08599286, 0.08933257, 0.08265033, 0.10612676, 0.08845143,
       0.08512668, 0.08562278, 0.08668222, 0.09156052, 0.08859092,
       0.08564546, 0.08474909, 0.08480414, 0.10315145, 0.09853186,
       0.09954625, 0.09822304, 0.08666415, 0.0904586 , 0.09067313,
       0.11257137, 0.08803046, 0.10536893, 0.09939869, 0.08722158,
       0.10629749, 0.08588552, 0.0847982 , 0.09790783, 0.09722336,
       0.08634876, 0.10560618, 0.12006559, 0.09145199, 0.10098413,
       0.10351631, 0.10547274, 0.1104911 , 0.08703522, 0.11679392,
       0.10196143, 0.09213299, 0.08722772, 0.09534723, 0.08983047,
       0.08430772, 0.0924976 , 0.12043032, 0.12359438, 0.10622574,
       0.09290569, 0.08639123, 0.09224305, 0.10526542, 0.08889769,
       0.11167519, 0.09412725, 0.09846883, 0.10120234, 0.10210224,
       0.10593328, 0.08685601, 0.08791112, 0.08876764, 0.08715676,
       0.10842023, 0.08538563, 0.08901103, 0.08723799, 0.08926089,
       0.08905677, 0.09342583, 0.0832904 , 0.11936007, 0.10213856,
       0.09794873, 0.12416729, 0.09166889, 0.083854  , 0.09404737,
       0.1282697 , 0.10725694, 0.08868766, 0.08701284, 0.09100565,
       0.09319319, 0.13804445, 0.11996113, 0.09181455, 0.08568621,
       0.09351449, 0.09182861, 0.08897427, 0.09028275, 0.13100912,
       0.08698604, 0.08562182, 0.1305023 , 0.10086326, 0.084738  ,
       0.10380439, 0.09339954, 0.09534737, 0.1027882 , 0.10746025,
       0.09739829, 0.08285034, 0.09236133, 0.08816013, 0.10406093,
       0.08909356, 0.10212009, 0.08861732, 0.09203337, 0.10279016,
       0.10749518, 0.12107743, 0.09920129, 0.09670586, 0.09006055,
       0.09305076, 0.08507407, 0.09259898, 0.09343213, 0.10807121,
       0.10239737, 0.08586866, 0.08815213, 0.08720572, 0.09182607,
       0.10787096, 0.08811666, 0.09241916, 0.08675719, 0.08520842,
       0.08463092, 0.10122001, 0.0950437 , 0.08519001, 0.10113081,
       0.10380454, 0.09064784, 0.09009529, 0.08592371, 0.09495541,
       0.09004265, 0.09171904, 0.1436637 , 0.08672903, 0.1018328 ,
       0.09646797, 0.10088845, 0.09896977, 0.10220522, 0.10645141,
       0.1246006 , 0.08928304, 0.08883931, 0.0874954 , 0.09704238,
       0.09355068, 0.09243726, 0.08635771, 0.08775187, 0.10111658,
       0.0873299 , 0.08608425, 0.08703624], dtype=float32), array([[[[-0.03104265],
         [-0.01836106],
         [ 0.0186182 ],
         ...,
         [-0.00368448],
         [ 0.01386286],
         [ 0.01523989]],

        [[-0.00690719],
         [ 0.00394885],
         [ 0.02062838],
         ...,
         [ 0.00850328],
         [ 0.02151141],
         [ 0.01563691]],

        [[ 0.00218439],
         [ 0.0045415 ],
         [-0.01285259],
         ...,
         [ 0.02887472],
         [-0.00592414],
         [-0.00693937]]],


       [[[-0.01974358],
         [ 0.02239968],
         [ 0.00423868],
         ...,
         [ 0.02900151],
         [-0.02799193],
         [ 0.03291197]],

        [[-0.03774428],
         [ 0.00154394],
         [ 0.0013689 ],
         ...,
         [ 0.00677969],
         [-0.02527963],
         [ 0.00490443]],

        [[-0.0329075 ],
         [-0.01607296],
         [-0.00088879],
         ...,
         [ 0.00905043],
         [-0.02906652],
         [-0.0059652 ]]],


       [[[-0.03529678],
         [ 0.01878464],
         [ 0.00676682],
         ...,
         [-0.00123055],
         [ 0.00093235],
         [ 0.01646396]],

        [[-0.01780619],
         [ 0.02574548],
         [ 0.00101742],
         ...,
         [ 0.01327721],
         [-0.00577967],
         [ 0.00982972]],

        [[-0.01016765],
         [ 0.00914773],
         [ 0.00952563],
         ...,
         [-0.01322439],
         [-0.02380263],
         [-0.00086637]]]], dtype=float32), array([[[[-0.03947673,  0.00228947, -0.01178334, ..., -0.01224415,
           0.05295612,  0.01953368],
         [-0.0088003 ,  0.03548535,  0.01171583, ..., -0.05298319,
           0.05508236, -0.03696086],
         [-0.01967508,  0.01691274,  0.02375487, ...,  0.04736317,
           0.04665393, -0.01810714],
         ...,
         [-0.04020133,  0.00053398,  0.01292828, ...,  0.04849393,
          -0.0643836 ,  0.0502896 ],
         [ 0.04269756, -0.0060812 , -0.03042902, ...,  0.04667711,
           0.00681563, -0.03936075],
         [ 0.00532374,  0.03261503,  0.01754627, ..., -0.0249979 ,
          -0.05665746, -0.00741125]]]], dtype=float32), array([0.9851647 , 1.0015838 , 0.97653854, 0.9938676 , 1.0120317 ,
       0.9793908 , 0.99131805, 0.9946565 , 1.0286978 , 1.0044621 ,
       0.99925077, 1.0093646 , 0.99808526, 1.0065161 , 0.98836595,
       0.9818524 , 1.0045111 , 1.0156513 , 0.9908324 , 0.99440753,
       1.0061728 , 1.006138  , 1.0037519 , 1.0068892 , 0.9805711 ,
       1.0013007 , 1.0067041 , 0.9931599 , 1.0081416 , 1.0034815 ,
       0.9966973 , 0.9965292 , 1.0023128 , 0.9919363 , 0.99666893,
       1.0001099 , 1.0128813 , 0.9874301 , 1.0183284 , 0.9981497 ,
       1.0034057 , 1.0011567 , 0.9895817 , 1.0035297 , 1.0066533 ,
       0.9878389 , 1.0033033 , 0.9995536 , 0.9983239 , 0.99803144,
       1.0040493 , 0.9972832 , 0.99162227, 0.99728936, 1.0092729 ,
       1.0086437 , 0.99450505, 0.9943444 , 0.98036414, 0.99565256,
       1.0004995 , 1.0112731 , 0.98407346, 1.0031177 , 1.0115902 ,
       1.0143566 , 0.9962445 , 0.9819196 , 0.9835369 , 1.0063375 ,
       0.9979613 , 1.0024005 , 0.99610287, 1.003693  , 0.98865354,
       1.0087806 , 0.9883947 , 1.0108382 , 1.0016081 , 1.0082513 ,
       0.9759696 , 0.9953314 , 0.98455817, 0.9965659 , 0.9901948 ,
       1.0007008 , 0.99060225, 0.9943582 , 0.9985725 , 0.9998488 ,
       1.0092987 , 1.0040715 , 1.0108509 , 0.99982214, 0.98886305,
       1.0081058 , 1.0008086 , 0.99110615, 0.994269  , 0.9994728 ,
       0.99606705, 0.98697317, 0.9887584 , 0.9759366 , 1.0002669 ,
       0.99877214, 0.9952882 , 1.0118185 , 1.020701  , 0.9953715 ,
       1.0110034 , 0.9953391 , 1.0105675 , 1.0039276 , 1.0105094 ,
       0.9852285 , 0.99197733, 1.001338  , 0.9995511 , 0.9867194 ,
       1.0061764 , 0.9901037 , 0.9854916 , 1.0084169 , 1.0016965 ,
       1.0125344 , 1.0009301 , 1.005883  , 0.9949417 , 0.9870042 ,
       1.0016471 , 1.021271  , 0.99679524, 0.9927244 , 0.9863795 ,
       1.0101624 , 0.98972625, 1.0018973 , 1.0261148 , 0.9839169 ,
       1.0135072 , 0.9985539 , 1.004723  , 0.99679536, 1.00145   ,
       1.0032554 , 0.99135554, 0.98922384, 0.99939245, 0.98396546,
       0.99653137, 1.0173888 , 1.0100279 , 0.99580574, 0.99297756,
       0.9926699 , 1.0048337 , 0.9959615 , 0.9942124 , 0.9923252 ,
       0.9892956 , 0.99271715, 1.0094821 , 0.97874874, 1.0015868 ,
       0.9815589 , 0.97903407, 1.0013509 , 1.001821  , 0.9922708 ,
       1.0130578 , 0.98929965, 1.0042658 , 1.0180085 , 1.0059242 ,
       0.9942602 , 0.9930527 , 0.99827373, 0.99916553, 0.99412096,
       1.0134073 , 1.0034826 , 1.0024318 , 0.9866019 , 0.98727864,
       1.0011928 , 0.99140614, 0.9953432 , 0.99139905, 1.0188985 ,
       0.9974236 , 1.0023421 , 1.0061436 , 1.0251184 , 0.9996972 ,
       0.98747665, 0.999497  , 0.98829645, 0.9924036 , 0.98535454,
       1.0000328 , 0.9899393 , 0.98113126, 0.9941387 , 1.0004842 ,
       0.993817  , 0.98965204, 1.0079358 , 0.99353576, 1.0113412 ,
       0.99958825, 0.99434525, 0.99220765, 0.9918043 , 0.9940131 ,
       1.0019236 , 1.0003436 , 0.9918621 , 0.9864151 , 1.0032108 ,
       0.98492074, 0.9899154 , 0.98977107, 0.99199814, 0.9905771 ,
       1.017316  , 0.9991351 , 0.9956716 , 0.99863774, 1.0152322 ,
       1.0154668 , 0.9793939 , 0.9753731 , 0.9938042 , 1.0074239 ,
       0.99473244, 1.0018231 , 0.9869945 , 0.99402124, 0.9888235 ,
       1.0096215 , 1.0114946 , 0.9914576 , 0.9864073 , 1.0144919 ,
       0.98512167, 0.99729913, 1.0218362 , 1.0036017 , 0.9879928 ,
       1.0200652 , 1.0097767 , 1.0094368 , 1.0257083 , 1.0144817 ,
       0.99131685, 0.99136907, 1.0013552 , 0.98598355, 1.0122932 ,
       1.0139736 , 0.99080896, 1.002766  , 1.000518  , 1.0047067 ,
       1.0009086 , 1.0176594 , 0.986836  , 0.99802226, 1.0038142 ,
       1.0020275 , 0.9858983 , 0.9889048 , 1.0113307 , 0.97928685,
       0.99330115, 1.0022442 , 1.0062888 , 0.98448133, 0.99348164,
       0.9990123 , 1.0028521 , 0.99746585, 1.0031217 , 0.9994462 ,
       0.98380435, 0.98918116, 1.0001583 , 1.007002  , 0.99376106,
       0.9934269 , 0.9884991 , 1.0018618 , 0.99067986, 1.0130777 ,
       1.0049627 , 1.0072528 , 1.0120282 , 1.0122129 , 0.9972784 ,
       0.9981977 , 0.9792896 , 1.001536  , 1.0064957 , 0.9909155 ,
       1.0017004 , 0.9974892 , 0.9957805 , 1.0026757 , 0.9997058 ,
       0.99246746, 0.99151266, 1.0076936 , 0.9931539 , 1.0220243 ,
       1.009871  , 0.9842987 , 0.99847704, 0.9979253 , 1.0015445 ,
       1.005784  , 1.0045222 , 0.9976557 , 0.99300826, 0.9939483 ,
       0.98946637, 0.99803793, 1.0031322 , 1.0018411 , 0.9907065 ,
       1.005339  , 0.99519837, 1.0036052 , 0.9888933 , 0.99274457,
       1.0050887 , 0.98364735, 0.97215813, 1.0050048 , 0.9892799 ,
       1.0054343 , 0.99845356, 0.99069405, 0.99473894, 1.0018977 ,
       1.0050088 , 0.9788846 , 1.0066369 , 1.0135467 , 0.9876991 ,
       1.0297794 , 0.99638504, 1.0177065 , 1.0100669 , 0.99659514,
       1.0154662 , 0.9945896 , 0.98632663, 0.9977077 , 0.9879699 ,
       1.0062233 , 1.0241644 , 1.0017552 , 1.0007157 , 0.99627304,
       1.0093551 , 0.9866162 , 1.0088751 , 1.0149987 , 0.9910046 ,
       0.98504126, 0.99032485, 0.9919873 , 1.0049928 , 1.0021312 ,
       0.98370254, 1.0021118 , 1.0126325 , 1.0016781 , 1.0026566 ,
       0.9782455 , 1.0018443 , 1.0075605 , 1.0074539 , 0.98622537,
       0.98251736, 0.98924935, 0.99104965, 0.9988793 , 1.0086316 ,
       1.000891  , 1.0171459 , 0.99740106, 1.002747  , 0.9844799 ,
       0.96512556, 0.9981363 , 1.0196832 , 1.0101277 , 0.9968363 ,
       0.97829306, 1.0092486 , 1.0164504 , 1.0173819 , 1.005388  ,
       0.99332625, 0.98819906, 0.9747257 , 0.99787706, 1.0071741 ,
       1.006499  , 0.9881076 , 0.9962589 , 0.9882158 , 1.0079402 ,
       0.9923992 , 1.0010972 , 0.98719984, 0.9958051 , 1.0099393 ,
       0.98636836, 1.0108339 , 1.0047166 , 1.0096102 , 0.99678975,
       0.99633384, 0.98531353, 0.9947862 , 1.0224335 , 0.9994946 ,
       1.0011523 , 1.0131153 , 0.9886724 , 0.9900056 , 1.0358577 ,
       0.9928839 , 1.0190471 , 0.9965607 , 0.9875784 , 0.99507546,
       0.99456424, 1.001519  , 1.0093467 , 1.0172328 , 0.99539965,
       0.9950559 , 0.98857415, 1.0055081 , 1.0110643 , 0.9860065 ,
       0.9873858 , 0.9981913 , 0.99913025, 1.0008013 , 1.0028893 ,
       1.005651  , 0.99201244, 0.9735313 , 0.99926096, 0.9956396 ,
       0.9945688 , 1.0098205 , 1.0073434 , 1.0003886 , 0.99074525,
       0.98649096, 1.011051  , 0.99587834, 0.99354   , 1.0148547 ,
       0.9866454 , 1.0001515 , 0.99300104, 0.9885138 , 0.9834184 ,
       1.0009847 , 0.99251384, 0.9923583 , 0.9916964 , 0.9899623 ,
       0.98055756, 0.9861977 , 1.0007945 , 0.98286355, 1.0016297 ,
       1.0111017 , 0.9948492 , 1.0012614 , 0.9908007 , 0.99143827,
       1.0110121 , 0.9891702 , 0.9921792 , 0.98749006, 0.99110895,
       1.0134534 , 1.0017165 , 0.9959785 , 1.0049093 , 0.98026067,
       0.9930686 , 1.013714  , 1.0058881 , 1.0094086 , 0.99937594,
       1.0126947 , 1.0088183 , 1.011184  , 0.989484  , 1.001506  ,
       1.0090215 , 0.9986391 , 1.0099006 , 1.0093216 , 1.00288   ,
       1.0071273 , 0.9903183 , 0.997009  , 0.9938587 , 0.9907271 ,
       0.97952634, 0.9852112 , 0.9955661 , 0.992124  , 0.99211264,
       1.0032595 , 0.9980562 , 0.9893932 , 0.98804414, 0.9967132 ,
       0.9850369 , 0.99818236, 0.9801327 , 1.0022168 , 0.99492526,
       1.003561  , 0.99129903, 0.9963817 , 0.98859733, 0.9708756 ,
       0.98552907, 0.995038  , 0.98653764, 0.9873991 , 0.9815212 ,
       0.98237556, 0.9774768 , 0.99314225, 0.98661214, 1.0284594 ,
       1.0085148 , 0.99968886, 0.9890918 , 0.98684186, 1.0135735 ,
       0.9994235 , 0.9893056 , 1.009841  , 1.0057092 , 1.0129308 ,
       1.0143551 , 1.0062844 , 0.9968328 , 1.0035642 , 0.9982309 ,
       1.0126244 , 0.99921906, 1.0115987 , 0.97108394, 1.0022525 ,
       0.99752116, 1.0020888 , 1.0202676 , 0.98183477, 1.002723  ,
       0.99351704, 1.0206769 , 1.0008274 , 0.9997465 , 1.0074548 ,
       1.0050763 , 0.98957914, 1.0079869 , 0.9922862 , 0.99747354,
       1.0134399 , 0.9861206 , 0.9985661 , 0.9883193 , 1.0180863 ,
       0.99948204, 0.9954612 , 0.99556977, 0.99247503, 1.0171005 ,
       1.0059524 , 1.0110666 , 1.0169755 , 1.0035286 , 1.0080671 ,
       0.9917873 , 0.9892677 , 0.99921536, 0.99637973, 1.0083082 ,
       1.0054947 , 1.0240256 , 0.9929408 , 0.98752916, 0.99608994,
       0.9801931 , 1.0055867 , 0.98355585, 0.9966315 , 0.988525  ,
       1.0070814 , 0.9946226 , 0.99617505, 0.9979259 , 0.9962306 ,
       1.00005   , 0.99708384, 1.0027229 , 0.9925825 , 1.0037055 ,
       1.0063682 , 0.99536324, 1.0103331 , 0.97875243, 0.9889284 ,
       0.99252737, 1.0027196 , 1.0098745 , 1.0057117 , 0.9873021 ,
       1.0019739 , 0.9964326 , 0.991524  , 0.99218524, 1.0132741 ,
       0.99993366, 0.98827773, 0.98775554, 0.9818815 , 1.0042709 ,
       1.0064969 , 0.99958986, 0.99990183, 0.99500114, 0.9848023 ,
       1.000285  , 0.99069107, 0.9981589 , 0.99659127, 0.9931038 ,
       0.9752433 , 0.99197817, 1.0037155 , 0.98396057, 1.0004064 ,
       0.9983429 , 0.9979339 , 1.000204  , 1.010605  , 1.0059975 ,
       0.99434346, 0.99116105, 0.9777938 , 0.995341  , 0.98599833,
       0.9995467 , 0.9861048 , 1.001907  , 1.0099725 , 0.98224205,
       0.99265856, 1.0115421 , 1.0030056 , 0.9767898 , 1.0102551 ,
       0.9860239 , 1.0235592 , 0.9832285 , 1.009493  , 1.0051215 ,
       0.9914397 , 0.98304754, 1.0018222 , 1.023954  , 1.0136529 ,
       0.9960359 , 1.0090837 , 1.0227581 , 1.0016798 , 1.0046253 ,
       1.0134609 , 0.9972353 , 1.0026802 , 0.99696743, 0.9797371 ,
       0.9875706 , 0.99646366, 0.99854136, 0.99625325, 0.98861396,
       0.9910557 , 0.9976012 , 1.0093576 , 1.0046543 , 1.0182623 ,
       0.9860681 , 0.99700326, 1.0102737 , 0.99504   , 0.99842006,
       1.0146732 , 1.0238347 , 1.0098811 , 1.0235298 , 0.98836523,
       1.0180297 , 1.0024724 , 0.9739533 , 1.001458  , 0.99508744,
       1.0046616 , 1.0173565 , 1.0090461 ], dtype=float32), array([-1.39614381e-02, -5.81551204e-03, -1.93449277e-02, -2.48935539e-03,
        1.69726592e-02, -1.26473419e-02, -3.33984126e-03, -3.81406620e-02,
        2.17611678e-02,  8.91285890e-05,  3.52388946e-03,  1.58185177e-02,
        5.05326502e-03, -3.30280163e-03, -1.60588662e-03,  1.36852944e-02,
        8.85461457e-03,  1.21405385e-02, -3.47706378e-02, -5.08802943e-02,
       -3.02116927e-02, -1.94199029e-02, -1.00421878e-02, -9.63760633e-03,
       -1.86174773e-02,  3.29841487e-02,  5.71567798e-03,  7.09037343e-03,
       -7.04682386e-03, -1.01836910e-03,  7.34711299e-03, -2.82430686e-02,
        1.36976782e-02, -1.84231550e-02,  1.13510154e-02, -1.55413924e-02,
       -5.86745935e-03, -1.00426069e-02,  2.20044120e-03, -7.10839033e-03,
        6.78005861e-03,  6.65193610e-03,  2.28213472e-03, -1.83604993e-02,
        1.75983608e-02, -3.32517661e-02, -1.78272650e-02, -1.08200628e-02,
       -3.98321226e-02,  5.97429695e-03, -9.81403980e-03,  1.13027440e-02,
       -3.32524702e-02, -5.60668297e-03, -3.67803010e-03,  8.93764198e-04,
       -9.95276030e-03, -8.14731792e-03, -5.15064970e-03, -3.89641384e-03,
        2.58724615e-02,  1.60708651e-03, -1.53305568e-02, -7.93535728e-03,
        2.75883526e-02, -3.53372889e-03, -9.60804150e-03, -4.33705514e-03,
        1.56637584e-03,  2.92357448e-02,  9.46766790e-03,  3.78556608e-04,
        5.15237823e-03, -3.88050312e-03,  3.92276049e-02, -1.06478687e-02,
        2.27220785e-02, -1.45255998e-02, -3.24592763e-03,  2.72182655e-02,
       -2.79838126e-02,  3.32846073e-04, -1.49315121e-02,  8.54388066e-03,
        1.30997729e-02,  1.97019152e-04, -6.91368990e-03, -6.58551371e-03,
       -5.51043870e-03,  2.58808080e-02, -5.62099088e-03, -1.25785889e-02,
       -1.25576854e-02, -2.87237996e-03, -6.26352942e-03,  3.36660258e-02,
        1.10509330e-02,  3.78066418e-03,  3.46547831e-03,  1.51160713e-02,
       -8.13135784e-03,  2.48278352e-03, -3.81579180e-03, -9.74698737e-03,
       -1.04727661e-02, -1.34524647e-02, -2.17922218e-02, -1.11688748e-02,
        2.75249174e-03, -1.12824002e-02,  4.44741268e-03, -3.01532093e-02,
        1.95616037e-02, -8.51834565e-03,  6.44895621e-03, -2.45366804e-02,
        3.41653149e-03,  1.22858947e-02,  1.68883167e-02,  2.95820050e-02,
       -9.37487278e-03, -2.66868360e-02, -1.47574646e-02,  2.58682519e-02,
       -1.13959713e-02, -1.42063871e-02,  8.22358765e-03,  3.34873013e-02,
       -2.47089583e-02, -4.40868968e-03, -2.96494793e-02,  5.68330213e-02,
       -3.01403063e-03, -1.71963982e-02, -1.71870477e-02, -1.99680924e-02,
        1.69491339e-02, -1.70971435e-02,  3.02034360e-03, -2.75021717e-02,
        2.08519921e-02,  2.05629785e-03, -2.68128375e-03, -1.14152357e-02,
       -1.29701057e-02,  8.49649590e-03,  1.68175362e-02, -1.67076103e-02,
       -2.54302416e-02, -1.51793826e-02, -1.35436868e-02, -6.39221864e-03,
       -2.41193995e-02, -1.86963864e-02,  3.51557368e-03,  1.14241466e-02,
       -1.22912582e-02, -5.87822543e-03, -1.09188491e-02, -1.58842257e-03,
       -7.46759679e-03, -1.11015970e-02, -2.17761975e-02, -2.13007014e-02,
       -7.51877436e-03, -2.63719410e-02, -8.81356094e-03,  7.29444996e-03,
        4.04542172e-03, -1.54177984e-02,  5.45252115e-02, -1.01035172e-02,
        1.52708841e-02,  1.54632181e-02, -3.17204483e-02, -1.46923894e-02,
       -1.16628353e-02,  1.29759852e-02, -1.00462558e-02, -7.20348815e-03,
       -2.23009312e-03,  1.94772554e-03, -1.22102201e-02, -2.19141133e-02,
       -2.71608643e-02, -2.94727343e-03,  4.96264838e-05,  7.95620144e-04,
       -1.54664489e-02,  2.11791194e-04, -7.50092044e-03,  1.17839910e-02,
       -8.52506422e-03,  2.63933111e-02,  1.07535040e-02, -1.16154896e-02,
        1.99835777e-05, -2.62132324e-02, -2.64369249e-02, -1.66289564e-02,
       -8.06570332e-03,  2.45632255e-03,  1.23006962e-02, -2.14579925e-02,
       -1.06633473e-02, -2.20459364e-02,  6.67430367e-03, -1.85501277e-02,
       -7.11816887e-04,  3.62515002e-02, -9.75816604e-03, -5.74724935e-02,
        3.96669703e-03, -7.32580759e-03, -1.96935069e-02,  4.90048248e-03,
        8.07799865e-03, -3.94169195e-03,  2.06069835e-02, -1.98846646e-02,
       -4.67433129e-03, -8.54180689e-05, -4.00431268e-03,  1.55556817e-02,
        1.29415700e-02,  9.10034962e-03,  7.70753110e-03,  3.07963192e-02,
       -5.81651321e-03, -5.61383413e-03,  5.32714799e-02, -1.25729199e-02,
       -9.22665279e-03, -6.03905739e-03, -3.44889946e-02,  3.45823879e-04,
       -2.30640005e-02, -2.41920701e-03, -3.17576975e-02, -1.70596261e-02,
       -1.44524612e-02,  2.59858873e-02,  2.48169545e-02, -1.18874852e-02,
        1.49424803e-02, -1.90052744e-02, -6.35116035e-03,  9.97806247e-03,
       -7.31694093e-03, -9.91819054e-03, -2.36362242e-03,  8.35738983e-03,
       -6.76478213e-03,  6.02287007e-03,  1.40729742e-02, -5.44181578e-02,
       -1.47682643e-02,  2.44530383e-02, -3.26253520e-03, -2.73663551e-03,
       -2.18911041e-02, -1.56087670e-02,  2.17368957e-02, -2.73842141e-02,
       -9.10122786e-03,  9.67017002e-03,  1.04112988e-02, -1.10717863e-02,
       -1.32111963e-02,  5.40718716e-03,  3.54697146e-02, -1.43445060e-02,
       -1.48891816e-02,  4.13747388e-04, -2.99238730e-02, -1.40121188e-02,
       -5.44475392e-03, -3.40579748e-02,  1.27658863e-02,  2.67535960e-03,
        5.40136825e-04, -1.49330997e-03, -8.82346416e-04,  1.37619488e-03,
       -2.26238780e-02, -2.27436926e-02, -9.72486939e-03, -2.15688813e-02,
       -8.95775203e-03, -2.40590107e-02, -4.43188008e-03, -1.72783679e-04,
        5.14533697e-03, -2.92784050e-02, -5.83078573e-03, -2.82159187e-02,
       -5.70896827e-03,  7.71640148e-03, -1.08441841e-02, -9.69553553e-03,
       -3.17083336e-02, -1.00014647e-02,  1.10071828e-03, -1.08580152e-02,
        5.41970413e-03, -1.77449230e-02, -4.46254350e-02,  4.95175738e-03,
        6.24028221e-03, -1.00381412e-02,  4.87363711e-03, -2.02649902e-03,
        6.20534364e-03, -5.55566105e-04,  2.87344866e-02, -2.00549774e-02,
       -1.72271617e-02, -3.71022932e-02,  7.97795132e-04, -1.04453936e-02,
       -1.07062934e-02,  8.66951235e-03, -1.71156488e-02, -2.28325818e-02,
        1.71247579e-03,  3.17971082e-03, -1.43784154e-02, -1.74623937e-03,
       -7.99599290e-03, -3.81055437e-02, -2.74238288e-02,  3.09039722e-03,
        1.15525723e-03,  2.60377824e-02,  3.91494774e-04,  2.03504483e-03,
       -6.95476728e-03, -1.35473022e-02, -9.65108722e-03, -2.50363047e-03,
       -1.15230517e-03, -2.05161907e-02, -8.68410245e-03, -1.66630633e-02,
       -3.19187320e-03,  1.80162303e-02,  8.14393722e-03, -3.50774499e-03,
        2.39449609e-02, -1.07272277e-02,  2.10286060e-04,  7.78029626e-03,
        1.63126234e-02,  2.79878173e-02, -9.39424429e-03, -1.42367706e-02,
       -1.51439698e-03, -1.33425621e-02,  4.54705115e-03, -2.40108883e-03,
       -8.20428226e-03, -3.84806916e-02,  8.43247492e-03, -2.91085429e-02,
        7.20825279e-03, -1.04642212e-02, -2.63562109e-02, -2.49456037e-02,
       -2.18829270e-02, -2.14108033e-04, -2.18616743e-02, -1.08206160e-02,
       -1.76815479e-03, -3.93270589e-02, -6.96437526e-03,  5.51827298e-03,
       -4.06754203e-04, -2.65797339e-02,  6.35730335e-03, -6.91301981e-03,
       -1.91005766e-02, -2.47909408e-02,  3.16893533e-02, -1.80883729e-03,
       -1.71670951e-02, -2.38500852e-02, -1.15540894e-02, -1.88629217e-02,
        4.52146074e-03, -7.75764696e-03, -7.10850442e-03, -1.99298821e-02,
       -9.01909173e-03,  5.31761674e-03,  4.41849185e-03, -1.51897334e-02,
        1.67024939e-03,  1.10710831e-03, -1.79772619e-02,  2.89087626e-03,
       -2.40814574e-02, -3.33037935e-02,  2.61048004e-02,  3.68973762e-02,
       -9.81280673e-03, -4.34468687e-03, -5.41110849e-03, -2.66863052e-02,
       -2.22589634e-02,  8.13679025e-03, -7.68415537e-03, -2.04563551e-02,
        1.27772531e-02, -3.42496447e-02, -1.88566372e-03, -1.94317438e-02,
       -5.97152859e-03,  1.83165830e-04,  3.79017391e-03, -4.96422201e-02,
       -3.76497838e-03, -2.73477612e-03, -3.38167744e-03, -1.88860092e-02,
       -4.15460905e-03, -5.83251566e-03, -3.64539959e-02,  1.12647598e-03,
       -1.54760443e-02,  4.69574705e-03, -1.59222614e-02,  2.85400376e-02,
       -4.69122548e-03, -4.15085591e-02,  4.19476517e-02, -4.90853749e-03,
        1.79117564e-02, -9.57667548e-03, -2.08856780e-02, -5.38750039e-03,
       -1.85356177e-02,  7.91898929e-03,  1.40151195e-03,  8.29201192e-03,
       -1.08601935e-02, -1.51026319e-03, -1.32686552e-02, -6.42957771e-03,
        9.78106749e-04, -1.94652472e-02, -1.90163516e-02, -1.88240837e-02,
       -2.53954553e-03, -3.71483783e-03,  7.90333096e-03, -8.29159096e-03,
       -3.41915060e-03,  1.02087660e-02,  1.91045310e-02, -1.79077534e-03,
       -6.95946766e-03,  2.41435133e-02,  1.66839920e-02, -6.60106027e-03,
       -1.57876778e-02, -1.18338577e-02,  4.90964344e-03, -1.00266682e-02,
       -1.43891294e-02,  1.59393009e-02, -1.00507820e-02, -2.33706255e-02,
        5.80194872e-04, -2.49824896e-02,  1.50707946e-03, -3.76268253e-02,
       -6.02123793e-03, -7.94462301e-03, -4.36635269e-03, -5.20825200e-03,
       -1.90470237e-02, -3.76671925e-02, -2.91371765e-03, -1.57944895e-02,
        2.06263717e-02, -2.11610273e-02, -2.10039885e-04,  5.83247165e-04,
        3.12101655e-03, -7.49974337e-04, -1.53163215e-02, -1.32331196e-02,
       -1.13631198e-02, -7.35540409e-03, -1.69375334e-02,  1.76687520e-02,
        9.17461002e-04, -1.57177541e-02, -1.46346688e-02, -3.44750993e-02,
       -1.32976007e-02,  2.11700238e-02,  1.15102818e-02, -2.49663205e-03,
       -1.41834915e-02, -2.26801466e-02,  4.77645895e-04,  1.87771711e-02,
       -2.75137108e-02, -5.12791425e-03,  1.10022146e-02, -1.11208279e-02,
        3.76072600e-02,  1.34809371e-02,  2.28452776e-02, -4.75648697e-03,
       -5.10217808e-03, -1.75357796e-03, -1.10706212e-02, -1.32323224e-02,
        6.56958390e-03, -1.38325375e-02, -1.45003782e-03,  7.35946931e-03,
        1.58127979e-03, -3.46534397e-03, -8.30937643e-03,  2.73388391e-03,
       -1.79466829e-02,  7.27309985e-03, -1.05871158e-02,  1.49333719e-02,
       -2.53745932e-02,  3.73084657e-02,  9.87319276e-03, -6.85920753e-03,
       -1.17218681e-02, -1.66167337e-02, -9.03985742e-03, -2.68593319e-02,
       -2.05838047e-02, -2.73714922e-02, -1.34500861e-02, -1.53098023e-02,
        6.67713815e-03,  2.24090591e-02,  2.41224538e-03,  1.46197178e-03,
       -1.06718419e-02, -1.26035996e-02,  2.69913357e-02, -2.37103142e-02,
       -1.61952842e-02, -6.97012153e-03,  2.10579615e-02, -2.23464612e-02,
       -5.09990528e-02, -1.86835807e-02,  2.32902402e-03, -1.28349317e-02,
        1.16915107e-02,  1.19210659e-02,  3.42740258e-03,  1.21362656e-02,
        2.45836154e-02, -1.09573789e-02,  1.12726521e-02, -7.64569035e-03,
       -4.01310017e-03, -6.21464429e-03, -1.86063293e-02, -3.27401720e-02,
       -3.77866626e-03, -3.62286926e-03, -1.44540854e-02,  1.05935605e-02,
       -9.98310000e-03, -9.40016378e-03, -6.12546271e-03, -3.39466035e-02,
       -6.28244272e-03, -9.93973808e-04,  1.28846206e-02, -4.12242347e-03,
        3.34230214e-02, -9.94953793e-03, -2.12654490e-02,  5.83615340e-03,
       -1.24945147e-02, -3.30986902e-02,  9.01854970e-03, -1.39192984e-04,
       -2.20326451e-03, -1.40127717e-02,  1.82796773e-02,  1.11079309e-04,
        1.48304328e-02,  1.19890377e-03,  1.18417526e-02,  1.76419914e-02,
       -2.44274270e-02, -8.72054696e-03, -2.38121091e-03, -2.59861071e-02,
       -9.63671505e-03,  5.82767418e-03,  7.86055718e-03, -2.46813428e-03,
       -2.44488847e-03, -1.79488268e-02, -7.84558896e-03,  2.32606567e-02,
       -3.00848056e-02, -1.49392616e-02, -1.24406405e-02, -1.72422323e-02,
       -4.24997173e-02, -2.22449098e-02,  7.45682605e-03, -1.92876831e-02,
       -1.67448875e-02, -1.35552054e-02, -1.38567770e-02,  9.22195800e-03,
        9.03626159e-03, -2.96410043e-02, -2.79360004e-02,  9.50827915e-03,
       -5.17024007e-03, -1.55076627e-02,  2.71287776e-04,  6.81554899e-03,
        6.32570125e-04, -1.27093485e-02, -7.66319130e-03,  2.24468503e-02,
       -1.46698495e-02,  3.50195728e-03, -5.79236215e-03,  1.28397886e-02,
        1.29558705e-03, -7.47702178e-03,  8.10229313e-03,  2.59948103e-03,
        2.64476007e-03, -7.14001479e-03,  1.38831167e-02,  9.63537674e-03,
       -5.07516880e-03, -1.75649393e-02,  7.02483987e-04, -1.79041922e-02,
        8.29496793e-03, -5.78187266e-03,  1.09614357e-02,  7.00233364e-03,
       -8.86694901e-03, -1.14969797e-02, -1.75290778e-02, -6.79227943e-03,
       -1.49072893e-02,  5.35681099e-03, -1.23324860e-02, -4.29322012e-03,
       -8.90846830e-03,  1.42626360e-03, -1.75826009e-02, -1.65615454e-02,
        2.27347706e-02, -7.90009182e-03, -1.69298630e-02, -5.92232170e-03,
        5.16685890e-03,  2.63512637e-02,  2.12248452e-02, -1.29718035e-02,
       -2.69322339e-02, -5.33367097e-02, -6.74542366e-03,  2.31302120e-02,
        7.72990461e-04, -7.99744669e-03, -1.27721550e-02, -5.01158554e-03,
       -1.56387910e-02,  7.01980246e-03, -5.68170846e-03, -5.43601252e-03,
        4.41032741e-03, -1.81341041e-02, -7.20952963e-03, -2.54737549e-02,
       -2.14485396e-02, -2.58451849e-02, -3.82662704e-03,  4.13331091e-02,
       -1.36502152e-02, -9.68330912e-03, -1.25746531e-02, -2.38495739e-03,
        9.44994506e-04, -1.46223791e-02, -2.50187293e-02,  7.18497671e-04,
       -2.73190788e-03, -8.48077470e-04, -2.09333859e-02, -6.10654196e-03,
        2.67562103e-02, -2.91530546e-02,  1.27114076e-02, -6.61820453e-03,
        1.55230807e-02, -2.20808201e-03,  1.77794397e-02,  2.86163017e-02,
        3.62843333e-04, -3.15674730e-02, -3.02546248e-02, -6.35645399e-03,
        2.90378532e-03, -4.19078283e-02, -3.64221931e-02, -2.33057700e-02,
       -5.11402322e-05, -2.87923850e-02,  2.80374102e-02, -8.97594262e-03],
      dtype=float32), array([-2.13893000e-02,  6.21968918e-02, -1.67480316e-02,  2.69516911e-02,
       -2.29324549e-02, -7.08517851e-03, -7.42829293e-02,  6.67091981e-02,
        6.28095528e-04, -6.94653466e-02, -5.95571771e-02, -4.36091572e-02,
        9.69196577e-03, -3.22396159e-02,  2.72755846e-02, -8.45288262e-02,
       -3.98244187e-02,  7.01737218e-03,  9.20644030e-02,  6.69011474e-02,
        2.91606877e-02,  8.65980834e-02,  3.66838761e-02,  4.24738377e-02,
        1.67590175e-02,  2.09405795e-02, -6.83427304e-02, -4.51035611e-02,
        2.11752504e-02, -1.96383591e-03, -1.13578036e-03,  7.07073212e-02,
       -5.72017543e-02,  3.31037566e-02, -4.61889990e-02,  8.53439793e-02,
       -1.26138134e-02, -1.80142913e-02, -6.07521534e-02, -5.00578023e-02,
       -2.18417794e-02, -4.35176007e-02,  3.74947935e-02,  1.10347457e-01,
       -1.01381361e-01,  2.85904724e-02,  3.28294262e-02,  6.80809394e-02,
        8.30164105e-02,  2.34349519e-02,  6.40130416e-02, -5.31105958e-02,
        7.65738264e-02,  6.35722801e-02, -3.40581685e-02,  8.80377367e-02,
        9.18389261e-02,  3.66737843e-02,  2.41076015e-02,  5.16483150e-02,
       -4.44498509e-02,  6.73363879e-02,  7.35266209e-02,  3.14223692e-02,
       -5.37314005e-02,  2.28958130e-02,  5.39306216e-02,  7.18068928e-02,
       -2.33336892e-02, -5.59127219e-02, -8.18359898e-04, -3.68133262e-02,
       -1.22811482e-03, -4.85431682e-03, -6.66607097e-02,  5.17737418e-02,
       -4.27610725e-02,  3.78013263e-03, -2.39597876e-02, -2.71300096e-02,
        7.62727410e-02,  5.94149157e-02,  7.11201504e-02, -7.51565844e-02,
       -4.41139527e-02,  3.94593831e-03,  1.97822656e-02,  3.24701220e-02,
        5.07006468e-03, -2.08484549e-02,  4.63824607e-02, -5.17490059e-02,
       -5.17614484e-02,  4.17814963e-02, -2.53922734e-02, -5.08119985e-02,
        1.90572673e-03, -4.42201085e-02, -4.11349460e-02, -1.74178500e-02,
        5.55989444e-02,  3.45486253e-02,  4.99532707e-02,  2.44552083e-02,
        5.27551360e-02,  3.63444467e-03,  4.17144001e-02, -2.97102649e-02,
        2.40957253e-02,  5.23037761e-02, -5.34860417e-03,  3.52355205e-02,
       -4.64279093e-02,  3.66526656e-02, -6.22065887e-02,  5.50596640e-02,
        4.81586754e-02, -3.41115370e-02, -3.96026745e-02, -3.32172327e-02,
        8.57724473e-02,  7.03878775e-02,  4.42208983e-02, -3.61121893e-02,
        3.54997329e-02, -2.61808876e-02, -5.63986301e-02, -8.16161558e-02,
        8.47553983e-02,  5.47338203e-02,  5.79531379e-02, -2.45937705e-02,
        4.45679063e-03, -6.17748536e-02,  6.48539215e-02, -4.47320193e-02,
       -7.04542845e-02, -5.76151647e-02, -5.85379787e-02,  4.28504944e-02,
       -2.24022176e-02,  4.60794345e-02,  7.26115853e-02,  6.46166354e-02,
        3.64561155e-02,  6.17655367e-02, -3.93653512e-02, -4.46796864e-02,
        8.42247829e-02,  3.59607972e-02,  6.45354986e-02,  1.43019743e-02,
        5.79386391e-02, -3.48922983e-02, -4.32717875e-02,  5.03346277e-03,
        3.00360210e-02,  4.47283313e-02, -6.24675117e-02, -9.75885093e-02,
       -2.70202644e-02,  4.27385196e-02,  4.26901579e-02, -5.45246191e-02,
        1.90877859e-02,  8.67817253e-02,  7.50692636e-02,  4.45314171e-03,
        2.22935248e-02,  5.59858382e-02, -2.29525231e-02,  5.43145575e-02,
        9.67372500e-04, -1.28883421e-02,  6.01077341e-02,  4.31809202e-02,
       -9.53191053e-03, -7.10672140e-02,  2.20188498e-02,  4.48053069e-02,
       -6.07739761e-02,  4.91807647e-02, -2.41643675e-02,  6.74856976e-02,
        8.61878097e-02,  2.56487411e-02,  1.08201988e-02,  3.99316587e-02,
        8.14377815e-02, -3.56956087e-02,  6.56725466e-02,  2.15379670e-02,
       -2.03882493e-02, -4.90931645e-02, -2.67469697e-02,  3.01298052e-02,
       -1.26003334e-02,  7.39782602e-02,  3.92986573e-02,  5.19386977e-02,
        7.70135149e-02,  5.13611287e-02,  1.90012231e-02, -2.74873786e-02,
        7.24390373e-02,  5.72253466e-02, -9.89611000e-02, -3.82838361e-02,
       -5.36265373e-02, -4.65447307e-02, -4.55655754e-02,  9.03769806e-02,
       -1.59487035e-02, -4.40280065e-02, -2.79502221e-03,  2.28265636e-02,
       -1.96443452e-03,  2.68853493e-02, -5.77819310e-02,  8.60635117e-02,
        1.23935444e-02, -7.24628568e-02,  3.15379761e-02, -2.34735403e-02,
       -2.00552978e-02,  2.47960985e-02, -3.75384428e-02, -9.30317119e-02,
        8.41862634e-02,  5.72558381e-02, -5.26864082e-02,  2.88367458e-02,
       -5.41634522e-02,  4.45144363e-02,  8.81928578e-02,  8.69726688e-02,
        3.37389223e-02,  5.46417907e-02,  5.08518144e-02, -5.65045960e-02,
        3.29076536e-02, -8.20124596e-02, -2.62383074e-02, -1.80670004e-02,
       -6.69809356e-02,  6.35544062e-02,  5.82052134e-02,  1.65037534e-04,
       -4.68037277e-03,  5.39061353e-02, -1.90737266e-02, -8.61978997e-03,
        6.55882880e-02,  5.08444123e-02, -1.81621537e-02,  6.87090755e-02,
       -5.67168407e-02, -2.37275604e-02,  2.65278090e-02,  4.74433713e-02,
       -2.46814284e-02,  2.28772592e-02, -2.59289090e-02,  6.62230924e-02,
        4.57906127e-02, -1.39082028e-02, -6.95104897e-03,  6.22608140e-02,
        3.22492160e-02,  2.29322463e-02, -8.31107572e-02,  5.06547987e-02,
        7.18905926e-02,  7.08300322e-02,  5.08415401e-02,  6.69202507e-02,
        5.57275824e-02, -7.14459792e-02, -4.05022539e-02,  3.26153375e-02,
        3.21334153e-02, -2.44188178e-02,  3.92474718e-02, -2.47218017e-03,
        8.81363526e-02,  1.41904457e-03,  3.37625444e-02, -5.24668954e-02,
        1.26441075e-02,  6.58525750e-02,  1.06608262e-02, -5.37964106e-02,
       -3.97962853e-02,  6.91498220e-02,  4.38853875e-02,  9.92739201e-02,
       -2.49006152e-02, -6.03124872e-02, -2.15718914e-02, -9.70925391e-02,
        5.27624078e-02,  4.28613871e-02,  1.07657146e-02,  4.55178954e-02,
        2.04298310e-02, -3.66976447e-02,  6.68648481e-02, -2.40712911e-02,
       -5.94259463e-02,  4.57521975e-02, -4.12352346e-02, -1.35207633e-02,
       -4.46272343e-02, -2.02153511e-02, -3.09699755e-02,  8.43508616e-02,
       -5.61149828e-02,  8.14871117e-02, -2.02861950e-02,  9.73095745e-03,
       -5.10276705e-02, -4.73992527e-02,  1.67425594e-03,  4.59637493e-02,
       -3.73721570e-02, -4.61225212e-02,  5.58492467e-02, -4.40420471e-02,
        3.84118445e-02,  5.01843877e-02,  9.14679468e-02, -5.61252870e-02,
       -6.32102489e-02, -4.16570678e-02,  6.59868494e-02, -4.17827815e-03,
        2.76288670e-02,  3.91106755e-02,  7.10780919e-02, -5.64814620e-02,
        5.50227426e-02,  3.43564223e-03, -6.87450916e-02, -1.38720144e-02,
       -9.68296900e-02, -2.10983828e-02,  4.61678356e-02,  1.60249770e-02,
       -3.95185240e-02,  6.62986785e-02,  3.99574973e-02,  2.85116341e-02,
        4.43906188e-02, -5.64401671e-02,  3.87165695e-02, -5.00028096e-02,
        1.90060996e-02, -2.08162349e-02,  3.07055470e-02, -2.72267479e-02,
       -4.39669117e-02,  2.65450627e-02,  1.31257251e-03,  6.99220523e-02,
       -6.55511245e-02,  6.84234574e-02,  6.68865740e-02,  1.03044488e-01,
        9.39237401e-02, -4.58909683e-02,  4.06315550e-02, -1.29470676e-02,
       -1.86758358e-02, -4.48180474e-02,  2.70311441e-02,  1.05170095e-02,
        2.69647036e-02,  1.06298648e-01,  5.39496355e-02, -7.03316554e-02,
        8.43649730e-02,  7.46859461e-02, -2.60358863e-02,  1.35557856e-02,
        8.18496123e-02, -4.54721563e-02,  5.72193898e-02,  7.12937787e-02,
       -3.57786780e-06,  4.09915410e-02, -3.39551009e-02,  1.04656003e-01,
        3.49148139e-02,  2.44199391e-02,  1.18568605e-02,  2.93556787e-02,
       -1.33334979e-04, -4.40472849e-02,  3.44518311e-02, -2.80971802e-03,
        7.76540264e-02,  5.09443767e-02,  1.91959664e-02, -1.02639692e-02,
        6.85129762e-02, -2.65044291e-02,  5.06452993e-02,  7.61736408e-02,
        1.02787111e-02, -2.52240915e-02, -2.99106222e-02,  4.87376414e-02,
       -5.04522882e-02,  7.57171661e-02,  7.61687905e-02,  3.96036282e-02,
        2.95046233e-02,  2.47801170e-02,  3.56195942e-02,  7.38470405e-02,
       -5.64252399e-02, -1.24716209e-02, -3.98136303e-03,  3.75179425e-02,
        3.47061194e-02,  1.76089313e-02,  4.35047783e-02,  4.88045551e-02,
        8.58532563e-02,  3.30227762e-02,  6.30064681e-02,  3.59933414e-02,
       -4.46805954e-02,  1.05478510e-01, -3.42591777e-02,  7.81537965e-03,
       -3.56032327e-02,  4.28092666e-02, -1.42090386e-02,  4.44104448e-02,
        5.89864030e-02, -6.08879440e-02, -4.27418090e-02, -3.67500260e-02,
       -1.31771769e-02,  3.12200747e-02,  1.92215256e-02,  2.16598101e-02,
        5.62477820e-02,  1.10554453e-02,  5.89312576e-02,  5.77453151e-02,
        7.78299663e-03,  6.14557788e-02, -4.19095010e-02,  1.00492397e-02,
        1.00996392e-02, -7.77878240e-02, -8.74316972e-03, -4.51555774e-02,
        1.85476318e-02, -4.85669635e-02, -3.21978368e-02,  7.19670728e-02,
       -4.20589633e-02, -2.17786450e-02, -2.16016211e-02,  8.02467093e-02,
        5.17778546e-02, -2.43351329e-02, -4.13860604e-02,  1.01445988e-03,
       -1.39239924e-02,  9.27764028e-02,  3.70644554e-02,  8.44126940e-02,
        4.25272882e-02, -4.49679419e-02, -1.61650218e-02, -4.05284986e-02,
       -5.09340130e-02, -2.89151482e-02,  8.20738450e-03, -4.23522256e-02,
        1.22618051e-02, -6.01229258e-02, -1.88235566e-02,  1.82865057e-02,
        3.19430716e-02, -1.75690725e-02,  2.19322853e-02,  3.35231498e-02,
        8.34490079e-03,  6.84868544e-03, -4.79331277e-02, -4.76090284e-03,
        6.07088907e-03,  4.15851735e-02,  5.61713614e-02,  6.30591363e-02,
        3.97295803e-02, -4.42976281e-02,  4.49996777e-02,  3.40118594e-02,
        4.73410115e-02,  5.72301634e-02,  1.18171023e-02,  3.55174653e-02,
        5.48553765e-02, -6.23329915e-02,  1.00972329e-03,  3.68703976e-02,
       -2.28558090e-02,  2.73749586e-02, -7.18383640e-02, -1.11446828e-02,
        4.25452664e-02,  6.01066872e-02, -6.32896200e-02,  8.61500129e-02,
        9.20650829e-03, -2.54855119e-02,  2.81188618e-02, -3.48532274e-02,
        2.73035504e-02,  1.38638010e-02,  4.08137254e-02, -4.91429754e-02,
        3.35097872e-02, -2.96583101e-02, -6.97094798e-02, -1.91261433e-02,
        7.39569589e-02, -6.21384904e-02, -2.58109458e-02, -3.84614877e-02,
       -1.24983592e-02,  3.35458703e-02,  3.31329331e-02,  6.47830740e-02,
        7.19305500e-02,  5.69147319e-02,  5.27786128e-02,  1.84235275e-02,
       -5.75230643e-02, -1.11016467e-01, -3.48459743e-02, -1.01849511e-01,
        6.66172057e-02,  8.93816054e-02, -3.78057063e-02,  3.10648736e-02,
        5.59579991e-02, -6.39894232e-02, -3.19460258e-02,  6.85236603e-02,
        9.21938196e-02,  7.61578307e-02,  3.71239558e-02,  5.44277579e-02,
       -5.12569770e-02, -4.53145616e-02, -3.61822476e-03, -5.15712099e-03,
       -3.12936045e-02, -6.46325499e-02, -5.78373075e-02,  4.08099815e-02,
        1.01150768e-02,  1.47878397e-02,  2.93319840e-02,  3.74801420e-02,
       -1.68329813e-02,  1.35875503e-02, -4.11278941e-03, -2.75599733e-02,
       -6.12005480e-02, -2.10765842e-02, -4.95747589e-02,  5.86200021e-02,
        4.44004461e-02, -4.05004509e-02, -1.47447139e-02, -2.57658418e-02,
       -5.18322960e-02,  3.43249887e-02,  8.64332020e-02, -1.02411777e-01,
       -8.93280357e-02,  8.22531432e-02, -2.66056098e-02, -3.64854820e-02,
        2.59638745e-02,  5.51547371e-02, -1.95351299e-02,  3.97742679e-03,
        1.70491841e-02,  5.99244982e-02, -1.83552261e-02,  1.36447861e-03,
        7.34215602e-02, -3.42460312e-02,  2.99513675e-02,  6.28783479e-02,
       -5.76150082e-02,  5.85572012e-02, -3.81212048e-02, -6.36486635e-02,
        6.42391369e-02,  1.87126938e-02,  7.39981607e-02, -3.18203159e-02,
        5.37442192e-02, -3.71810771e-03, -3.40917222e-02,  5.25658876e-02,
        6.62056804e-02,  3.48179676e-02,  4.21632603e-02, -3.12799439e-02,
       -9.21549201e-02,  3.17326486e-02,  7.26327896e-02,  1.14238197e-02,
       -2.74781007e-02, -8.54661688e-02,  8.95889997e-02,  2.18995139e-02,
        6.08780384e-02,  3.74561958e-02, -4.07120399e-02, -4.51614819e-02,
        4.66497466e-02,  4.30066064e-02,  3.69816907e-02, -4.33187373e-02,
       -1.00889569e-02, -3.36712375e-02,  2.82170027e-02,  1.22154085e-02,
        4.96776365e-02,  4.15071473e-02, -1.23992162e-02,  1.69520769e-02,
        3.16303074e-02, -1.82907805e-02, -3.32069993e-02,  4.59537422e-03,
       -1.08080776e-02, -2.50782203e-02, -2.63290033e-02,  3.79212722e-02,
       -9.43101943e-02, -1.20430607e-02,  2.13705432e-02, -6.70113694e-03,
        6.97829947e-02, -3.60930488e-02,  2.84020547e-02,  3.80009599e-02,
        7.62970224e-02, -1.47474809e-02,  6.39920160e-02,  5.79430424e-02,
        3.18359062e-02, -4.68289815e-02, -1.09683163e-03, -4.61031757e-02,
       -5.04527204e-02,  4.35944460e-02,  3.66289020e-02, -3.23432833e-02,
       -6.99490160e-02, -4.44986299e-02, -6.19979538e-02, -1.44855315e-02,
        7.00149387e-02,  9.59266499e-02,  3.27377096e-02, -3.59924622e-02,
       -4.57448326e-02, -9.60769132e-03,  1.28353536e-02, -5.47627732e-02,
        4.17290777e-02, -6.30211085e-02, -3.92173454e-02,  4.98466603e-02,
        2.24482752e-02,  6.48321360e-02,  4.26208824e-02,  4.25291248e-02,
        6.87810183e-02,  5.88088669e-02,  5.44474646e-02, -2.25907061e-02,
        4.03531864e-02,  2.67455056e-02, -6.77939728e-02,  5.32339588e-02,
        3.84097807e-02,  4.34783176e-02,  4.80699874e-02, -3.57140750e-02,
       -3.52908485e-02,  2.82587390e-03,  5.29813021e-02,  1.69353411e-02,
       -3.31761315e-02,  8.91850516e-02, -5.41265532e-02, -2.81651206e-02,
        5.75728603e-02,  1.26290033e-02, -3.12751196e-02, -1.66989136e-02,
        8.23979080e-02,  4.96003106e-02,  9.73664820e-02, -9.96034592e-03,
        2.32007317e-02,  8.10987726e-02,  7.20496848e-02,  6.37127757e-02,
        2.33923867e-02, -6.26938939e-02, -2.06800513e-02,  4.55713011e-02],
      dtype=float32), array([0.08515982, 0.11872733, 0.08577476, 0.09055589, 0.10130323,
       0.08482717, 0.09316514, 0.10952051, 0.0891239 , 0.11924896,
       0.11342493, 0.09637704, 0.08457712, 0.10181329, 0.09206991,
       0.10728005, 0.09468301, 0.08743124, 0.10894768, 0.12145414,
       0.09172549, 0.11686008, 0.10651015, 0.09040628, 0.08684266,
       0.08503155, 0.09406177, 0.09376922, 0.10078974, 0.08663089,
       0.08575328, 0.11210492, 0.09451642, 0.08848469, 0.08991446,
       0.1204593 , 0.09120537, 0.08694194, 0.10660417, 0.10079499,
       0.0851704 , 0.10050171, 0.09432425, 0.13489485, 0.13155095,
       0.095273  , 0.08895897, 0.11120474, 0.12099118, 0.0971337 ,
       0.09751494, 0.09919865, 0.10905928, 0.10591243, 0.1234628 ,
       0.1303909 , 0.12142383, 0.09265178, 0.08726572, 0.08705298,
       0.09705801, 0.09879144, 0.10683821, 0.08449528, 0.09172138,
       0.09695689, 0.08828001, 0.12802194, 0.08977467, 0.09495659,
       0.08506343, 0.08849074, 0.09223202, 0.0862895 , 0.10747134,
       0.09623175, 0.09996211, 0.0901203 , 0.08633154, 0.10609925,
       0.14300503, 0.1002074 , 0.10131171, 0.11055104, 0.09092538,
       0.08449486, 0.08726574, 0.08588929, 0.08871596, 0.09552504,
       0.09011871, 0.10351927, 0.09997243, 0.08423966, 0.0926968 ,
       0.09893829, 0.08804279, 0.09231874, 0.09961905, 0.10488787,
       0.11492972, 0.08691974, 0.08841565, 0.08902644, 0.09944378,
       0.08745202, 0.09661911, 0.10288643, 0.09290811, 0.09376638,
       0.08970525, 0.0989196 , 0.10939493, 0.09464969, 0.10755426,
       0.09493218, 0.09979429, 0.10187865, 0.09770876, 0.10230482,
       0.11484778, 0.10503725, 0.09101936, 0.0868815 , 0.08572864,
       0.08756726, 0.11330853, 0.11311419, 0.11397984, 0.11282018,
       0.10351788, 0.10009596, 0.08283094, 0.09098613, 0.08591671,
       0.10094527, 0.09686321, 0.09164029, 0.10222637, 0.09520171,
       0.09991845, 0.09876989, 0.10778846, 0.09208416, 0.08886817,
       0.0913841 , 0.09203323, 0.10184846, 0.11779509, 0.09105534,
       0.12483723, 0.08431926, 0.10932416, 0.08761885, 0.10943548,
       0.08491407, 0.12547456, 0.10641576, 0.09641775, 0.12019947,
       0.09793267, 0.10470682, 0.09044079, 0.09790421, 0.09197419,
       0.13458166, 0.10696179, 0.08437982, 0.08880047, 0.10537951,
       0.09942679, 0.1313401 , 0.08444019, 0.09083154, 0.09955608,
       0.09895957, 0.0889222 , 0.11065597, 0.08549575, 0.09711226,
       0.09586929, 0.10422797, 0.09695612, 0.10116705, 0.11054505,
       0.09298646, 0.09500895, 0.09381912, 0.11971238, 0.1285127 ,
       0.09724593, 0.09126293, 0.08655494, 0.09421436, 0.08998062,
       0.08567739, 0.09028351, 0.1117964 , 0.09411845, 0.09464934,
       0.11795831, 0.09381433, 0.08630655, 0.09555434, 0.10078111,
       0.10035286, 0.13881035, 0.08659539, 0.08986086, 0.11095957,
       0.09621382, 0.12400077, 0.08664215, 0.0957637 , 0.08586811,
       0.09375252, 0.0870149 , 0.09106961, 0.11227687, 0.13307653,
       0.08794122, 0.10201491, 0.08767973, 0.08778648, 0.08363948,
       0.09159547, 0.09535992, 0.14052293, 0.09577069, 0.10313205,
       0.1087149 , 0.09258905, 0.09475189, 0.10440326, 0.13157307,
       0.11648793, 0.09039472, 0.11839007, 0.11598542, 0.09907901,
       0.10015245, 0.13020545, 0.08892975, 0.08773744, 0.10258964,
       0.10957198, 0.09993297, 0.08886498, 0.09417943, 0.12228092,
       0.09427416, 0.09326839, 0.10067415, 0.09453443, 0.0984794 ,
       0.11113228, 0.09074838, 0.09620208, 0.09316404, 0.09092967,
       0.08818261, 0.09126367, 0.09991625, 0.10624686, 0.11543452,
       0.08956133, 0.08809841, 0.10521315, 0.09574714, 0.08526314,
       0.10482414, 0.09502001, 0.111385  , 0.10871273, 0.11459177,
       0.10999005, 0.10207897, 0.10977549, 0.09104654, 0.10792568,
       0.09085574, 0.08738674, 0.08807248, 0.09763669, 0.11534069,
       0.08727995, 0.08911977, 0.09162687, 0.09552591, 0.0929465 ,
       0.08328233, 0.08814581, 0.10355755, 0.12845893, 0.08846384,
       0.12575841, 0.09339556, 0.10136508, 0.11431632, 0.12005314,
       0.10499635, 0.08751003, 0.08476494, 0.09851711, 0.09187292,
       0.09689086, 0.1013513 , 0.08701814, 0.09069881, 0.08853421,
       0.09645028, 0.08386665, 0.10334502, 0.09080087, 0.1034943 ,
       0.10795521, 0.09848486, 0.1197563 , 0.08377276, 0.08562913,
       0.09286502, 0.0951697 , 0.0935913 , 0.09632024, 0.10182706,
       0.11191735, 0.10086617, 0.10593385, 0.09964963, 0.10611914,
       0.12855478, 0.09300026, 0.10376449, 0.10805365, 0.11117929,
       0.08422194, 0.09703073, 0.08800882, 0.0940083 , 0.11215119,
       0.09743314, 0.0940408 , 0.09772013, 0.08420172, 0.10598314,
       0.08591775, 0.08729261, 0.08319794, 0.10131486, 0.0987548 ,
       0.12472805, 0.09048175, 0.09729486, 0.10155372, 0.09731657,
       0.11920751, 0.09326306, 0.0828432 , 0.09365427, 0.09005573,
       0.11128451, 0.09141892, 0.0855739 , 0.0996704 , 0.10548941,
       0.09811501, 0.11138353, 0.12145156, 0.13092704, 0.10175753,
       0.11032235, 0.09244034, 0.08628269, 0.10253385, 0.09329281,
       0.08641686, 0.09302004, 0.12100578, 0.08807433, 0.11008181,
       0.13132335, 0.09604888, 0.09167341, 0.08484051, 0.09569581,
       0.08751602, 0.11645117, 0.0991193 , 0.08815423, 0.10056282,
       0.10167584, 0.14606299, 0.09818921, 0.09384439, 0.08505065,
       0.08796702, 0.08792735, 0.10020136, 0.09506282, 0.08674541,
       0.10311496, 0.09662876, 0.09801269, 0.08332338, 0.13017505,
       0.08882403, 0.09668464, 0.11743845, 0.08962583, 0.0905718 ,
       0.09714995, 0.09248879, 0.0975365 , 0.12851691, 0.11046342,
       0.09892636, 0.09012245, 0.09571743, 0.09072253, 0.1064405 ,
       0.10180463, 0.08585849, 0.09292673, 0.08755399, 0.11138219,
       0.08774737, 0.10051492, 0.08716651, 0.13196816, 0.08997485,
       0.10186458, 0.08978658, 0.09393992, 0.12178747, 0.09722936,
       0.08838868, 0.09537756, 0.09971738, 0.09185291, 0.10106637,
       0.10621233, 0.09780712, 0.09721099, 0.10013334, 0.08685227,
       0.09096999, 0.09072916, 0.09302569, 0.09986762, 0.08537941,
       0.10588389, 0.09143995, 0.09365848, 0.09794452, 0.09194558,
       0.08853888, 0.09114621, 0.10095888, 0.08382142, 0.09271606,
       0.08686313, 0.09987276, 0.08797875, 0.0908579 , 0.0934232 ,
       0.09300368, 0.09477499, 0.10216352, 0.10680982, 0.09080373,
       0.09045912, 0.08690721, 0.08919196, 0.11977079, 0.08870099,
       0.12272365, 0.09506158, 0.100938  , 0.09639922, 0.10659471,
       0.11262158, 0.08880723, 0.08645054, 0.10054511, 0.08278674,
       0.1158884 , 0.09656601, 0.08845717, 0.10079667, 0.08983243,
       0.09579809, 0.09761903, 0.09113611, 0.09132122, 0.09195211,
       0.0855699 , 0.08446693, 0.10259884, 0.09808291, 0.11077514,
       0.08839761, 0.0958849 , 0.08888194, 0.08554335, 0.09435679,
       0.10639016, 0.08725132, 0.09934756, 0.10685331, 0.1005654 ,
       0.08751456, 0.09521753, 0.0936808 , 0.09483451, 0.12317015,
       0.08567093, 0.09405214, 0.10429222, 0.1097701 , 0.10523011,
       0.08942229, 0.09448189, 0.0942771 , 0.0887583 , 0.08696041,
       0.0893831 , 0.0861854 , 0.09301987, 0.09873848, 0.10277229,
       0.1110489 , 0.08454847, 0.10912519, 0.10307667, 0.08945106,
       0.10112631, 0.08329551, 0.09627259, 0.09129906, 0.09333138,
       0.11618073, 0.10305254, 0.10171892, 0.09878386, 0.10364202,
       0.1467977 , 0.09461137, 0.15071279, 0.11921626, 0.11592489,
       0.11530917, 0.09764921, 0.09765176, 0.09982873, 0.09533413,
       0.10433927, 0.12622382, 0.10127993, 0.08467935, 0.10072973,
       0.10118184, 0.10474057, 0.08734035, 0.08657096, 0.0950563 ,
       0.10221928, 0.10980735, 0.1035592 , 0.09450851, 0.10146768,
       0.10284335, 0.09862921, 0.11597294, 0.09150007, 0.08748703,
       0.08955544, 0.09717143, 0.09206366, 0.09241413, 0.10705287,
       0.09506045, 0.0985611 , 0.0934844 , 0.09351526, 0.11683635,
       0.08786353, 0.10761674, 0.128096  , 0.1257611 , 0.12329616,
       0.09738792, 0.10376155, 0.09414663, 0.10274483, 0.09426045,
       0.08674128, 0.08918544, 0.10587753, 0.09630953, 0.1021312 ,
       0.09607588, 0.08893601, 0.09860758, 0.09559058, 0.11436594,
       0.10523959, 0.09522945, 0.09258167, 0.11257423, 0.08607391,
       0.0926339 , 0.10836362, 0.11026096, 0.08737393, 0.08665337,
       0.09344386, 0.11253387, 0.10484125, 0.10475792, 0.09469374,
       0.12021448, 0.09386618, 0.10892329, 0.08424184, 0.0889496 ,
       0.10532565, 0.11630581, 0.10175344, 0.09418201, 0.09833959,
       0.08883239, 0.09994277, 0.08923895, 0.10098381, 0.08765385,
       0.10564806, 0.0863674 , 0.08568057, 0.09732242, 0.08909406,
       0.10112695, 0.09149384, 0.09028108, 0.08585176, 0.09113751,
       0.08850981, 0.08885976, 0.09166225, 0.09283289, 0.08686601,
       0.088081  , 0.11031651, 0.12640841, 0.08537654, 0.09472448,
       0.08753721, 0.11120966, 0.09361823, 0.08936954, 0.09816085,
       0.09983115, 0.08940932, 0.1036792 , 0.09524172, 0.08527729,
       0.09335242, 0.08537243, 0.09849558, 0.0956127 , 0.11252601,
       0.10057843, 0.09455982, 0.11242772, 0.09959874, 0.09316517,
       0.08844025, 0.12163225, 0.13252847, 0.09141564, 0.0896226 ,
       0.09485936, 0.09155391, 0.08686008, 0.09138306, 0.09434579,
       0.10632674, 0.10936289, 0.09501816, 0.0875014 , 0.11148251,
       0.09453695, 0.11736822, 0.11223722, 0.11224419, 0.11665377,
       0.11297892, 0.08988145, 0.09577835, 0.12160652, 0.11138631,
       0.08778525, 0.11319414, 0.10054967, 0.10322029, 0.10963888,
       0.08487856, 0.09742451, 0.09591846, 0.10644496, 0.11773953,
       0.09290231, 0.09575771, 0.08813567, 0.09223199, 0.10253363,
       0.10099048, 0.10433348, 0.10521837, 0.11867931, 0.09020746,
       0.08562038, 0.12351464, 0.11376763, 0.10798758, 0.08676281,
       0.10444556, 0.0918824 , 0.09281506], dtype=float32), array([[[[-0.05317071, -0.0101697 , -0.00096964, ...,  0.00104407,
           0.0391256 ,  0.03030962],
         [ 0.06577645,  0.06882609, -0.08418758, ..., -0.08075408,
           0.04427528, -0.07277385],
         [-0.04619855, -0.02509934, -0.06698044, ...,  0.05108674,
           0.00939   ,  0.05770476],
         ...,
         [ 0.02600123,  0.06991948,  0.00872588, ..., -0.01930868,
          -0.00524721,  0.00618944],
         [ 0.02972341,  0.03337304,  0.01817921, ..., -0.04205913,
          -0.03957778,  0.0324915 ],
         [ 0.0730192 , -0.01729667, -0.02341782, ..., -0.01836735,
           0.01265845,  0.07168096]]]], dtype=float32), array([0.992966  , 0.9945495 , 0.98959184, 0.99096555, 0.99250275,
       1.0112501 , 0.9876051 , 0.9971403 , 0.9872225 , 0.99590296,
       0.99211264, 1.0053037 , 0.98174775, 1.0011675 , 1.0137626 ,
       1.0234381 , 0.99964064, 1.0000719 , 0.97590667, 0.9913196 ,
       0.98746115, 0.9820611 , 0.98431313, 0.99757564, 0.98901284,
       1.005959  , 1.0170116 , 0.99200255, 1.006851  , 0.98542374,
       0.99279565, 0.99708956, 1.0025516 , 0.99382573, 1.0109533 ,
       0.99647444, 0.9924991 , 0.99293125, 1.021455  , 0.9819414 ,
       0.98915774, 1.0057837 , 1.0066599 , 0.9980586 , 0.98716825,
       0.9886227 , 1.0028715 , 0.9984164 , 0.98310626, 0.9755932 ,
       0.9787673 , 0.99613345, 0.9907762 , 0.9933893 , 0.9909162 ,
       0.98617125, 0.98479337, 1.0036602 , 1.0084444 , 0.9944688 ,
       1.009246  , 0.9832744 , 0.9955809 , 0.99116045, 1.0035931 ,
       0.96979463, 1.000559  , 1.005386  , 0.9838889 , 1.0019981 ,
       0.9898758 , 0.99540144, 1.0080405 , 0.99403125, 1.0137556 ,
       1.0084087 , 0.9964826 , 0.9769316 , 0.9978501 , 1.014784  ,
       1.0263591 , 0.990435  , 0.9722002 , 0.9913483 , 0.9886255 ,
       0.9924645 , 1.0024021 , 1.0112196 , 0.9914014 , 1.0117123 ,
       0.98160213, 1.0012833 , 1.0023973 , 0.99252117, 0.99259794,
       1.0273538 , 0.99306947, 0.9877376 , 0.98403454, 1.0296704 ,
       1.0017359 , 0.9979268 , 0.99561065, 1.015992  , 0.9913615 ,
       0.9864514 , 0.9914087 , 0.9984991 , 1.0062876 , 0.98484   ,
       0.9966316 , 0.99206215, 0.99790066, 0.99660546, 1.01031   ,
       0.9931503 , 0.9837179 , 1.0026199 , 1.0045955 , 1.0214046 ,
       1.0060663 , 0.9944754 , 0.99864614, 1.0123435 , 1.0011848 ,
       1.0002517 , 1.0029263 , 1.0192804 , 1.0265325 , 1.0193644 ,
       0.99077874, 1.0195328 , 0.9958902 , 1.0091922 , 0.9848875 ,
       0.9807434 , 1.0041406 , 0.98362285, 0.99610955, 0.9941636 ,
       1.0233546 , 1.0026639 , 0.99324197, 1.0027419 , 0.9797445 ,
       0.9927049 , 1.0013111 , 0.9984169 , 0.9869856 , 1.0003488 ,
       0.9942574 , 0.9959141 , 1.0031178 , 0.9983255 , 0.9832561 ,
       1.0171803 , 1.0069615 , 0.9989153 , 0.9957447 , 0.99176455,
       1.0023367 , 0.989238  , 0.9728611 , 1.0036936 , 0.99072963,
       1.0179014 , 0.99402755, 0.9903997 , 1.0006757 , 0.99937034,
       1.0295467 , 1.0034688 , 1.0016307 , 0.9900457 , 0.97964036,
       0.9897851 , 0.99409026, 0.99057394, 0.98297393, 0.9969669 ,
       1.012764  , 0.9887901 , 0.9913067 , 1.0076257 , 1.0109546 ,
       0.9897206 , 0.99029905, 0.9972999 , 0.9841977 , 1.0173025 ,
       0.9824955 , 0.9949973 , 0.9918671 , 1.0034496 , 0.9946804 ,
       0.99356425, 0.9994906 , 0.9953112 , 0.99033856, 1.0134995 ,
       1.0204185 , 1.0085496 , 1.0049281 , 1.0165344 , 1.0030448 ,
       0.98790354, 0.9875972 , 1.0026189 , 0.99596655, 1.0172054 ,
       0.99734926, 0.9978096 , 1.0018138 , 0.99833167, 0.98739946,
       1.0049922 , 0.9925818 , 0.9997052 , 1.0082005 , 0.9969782 ,
       0.99197465, 1.0007435 , 0.9880034 , 1.0010737 , 1.0052196 ,
       0.99563134, 1.0018106 , 1.019334  , 0.9897915 , 0.9803018 ,
       0.98781997, 0.9778474 , 1.0068291 , 0.9818958 , 0.99476105,
       0.9943164 , 0.99667555, 1.000101  , 0.9901371 , 1.0036014 ,
       0.9919992 , 0.98981786, 1.0028824 , 0.9910529 , 0.99945146,
       0.9989731 , 0.9953489 , 1.00898   , 0.9866387 , 0.9611656 ,
       1.0137199 , 1.0070177 , 0.9876499 , 0.98130953, 1.0171894 ,
       0.98937863, 1.0122365 , 1.006119  , 0.99194103, 0.9968904 ,
       1.0057276 , 0.99785507, 1.0223976 , 0.99262416, 0.9889005 ,
       1.0026069 , 1.0026894 , 0.99738747, 0.98604494, 0.98977375,
       1.0243045 , 1.0001318 , 0.98821175, 0.9915607 , 0.99606013,
       0.98521954, 0.9907229 , 0.9940964 , 1.0037941 , 1.0029167 ,
       0.98314625, 0.9958436 , 1.0035063 , 1.0036489 , 0.9958783 ,
       0.99841076, 0.9887087 , 0.9998239 , 0.9931895 , 0.9922519 ,
       1.0005798 , 0.9964197 , 1.0038904 , 1.0118363 , 0.98939276,
       0.9840192 , 1.0055586 , 0.9948356 , 0.99047893, 0.98908305,
       1.002022  , 1.0017723 , 0.99140364, 0.9942808 , 0.99533576,
       0.9976452 , 0.99956816, 0.98314613, 0.9851755 , 0.97967505,
       0.9930883 , 0.9980561 , 1.0082551 , 0.98851544, 1.0045621 ,
       0.9890518 , 1.0056943 , 0.99266344, 1.0007917 , 0.98708713,
       0.99281317, 0.9963469 , 1.0119374 , 0.98449934, 0.9769462 ,
       1.0070451 , 0.99442446, 1.0133365 , 0.99000144, 0.98196393,
       0.97042376, 0.9929395 , 0.984994  , 1.0141681 , 0.99750054,
       0.9773141 , 1.0018444 , 0.9907723 , 0.9935763 , 0.9928996 ,
       0.98416984, 0.9891419 , 0.9873367 , 0.9893426 , 0.9966683 ,
       1.0150714 , 0.9970684 , 0.99782956, 0.9885391 , 0.99679655,
       0.9961592 , 1.0121363 , 1.0107073 , 1.0050983 , 0.9799954 ,
       0.99952835, 0.99052906, 0.9922128 , 0.99459285, 0.9934793 ,
       0.98521584, 0.9869195 , 0.99754107, 0.9923207 , 0.9999915 ,
       1.0031017 , 1.0012199 , 1.0099417 , 0.9948461 , 0.9944149 ,
       0.9977334 , 0.9979556 , 0.9906683 , 0.9767973 , 0.97874   ,
       0.9949071 , 0.99294513, 0.9879852 , 1.0015316 , 1.0121106 ,
       1.0017852 , 0.9765497 , 1.0101993 , 1.0029695 , 0.9891522 ,
       0.99068725, 1.0050101 , 0.98280555, 0.99435997, 0.9968187 ,
       1.0033484 , 1.0044477 , 0.98840976, 0.992851  , 1.0082401 ,
       1.0051799 , 1.0135175 , 0.99371696, 0.9788959 , 0.98735636,
       1.0062348 , 0.9888547 , 0.98615456, 0.98958194, 1.0034293 ,
       0.9972748 , 0.99980503, 1.0016369 , 0.9864613 , 0.98205966,
       0.991742  , 0.99442303, 0.98897207, 1.01938   , 1.0014242 ,
       0.9875011 , 1.0061479 , 0.99416894, 1.017184  , 0.9730454 ,
       0.9979026 , 0.9882245 , 0.9931375 , 1.0071684 , 0.98907655,
       0.9951499 , 1.0283439 , 0.9827015 , 0.9868376 , 1.0072511 ,
       0.98561037, 1.0037853 , 0.9917275 , 0.99402815, 1.0435846 ,
       0.98953485, 1.020623  , 1.0003351 , 0.994329  , 0.99254507,
       0.9927659 , 0.9962294 , 1.000906  , 1.0029978 , 0.9873224 ,
       1.0024745 , 0.97787875, 0.99766266, 0.98214734, 0.9944146 ,
       0.9998396 , 0.97841007, 0.99466825, 0.99436766, 0.99504465,
       1.0053515 , 0.9991894 , 0.989505  , 1.004814  , 0.99486935,
       1.0022458 , 1.006886  , 0.99663913, 0.99440116, 1.0011052 ,
       1.0045437 , 0.9951681 , 1.0017048 , 1.0012304 , 1.0231774 ,
       0.99588376, 0.98792285, 0.99010795, 0.99865454, 0.9993138 ,
       0.97555715, 1.0003314 , 0.9857312 , 1.003653  , 1.0012258 ,
       0.99595344, 0.96603054, 0.9893444 , 0.9908514 , 0.99147815,
       0.9952595 , 1.0100657 , 0.9891202 , 1.0113641 , 1.0095353 ,
       1.0048314 , 0.9900895 , 0.98653233, 0.989483  , 0.98476976,
       0.9973778 , 0.99431354, 1.0086238 , 0.9770437 , 0.98854244,
       1.0159591 , 0.99802345, 1.0025145 , 1.0029312 , 1.0029752 ,
       0.9925793 , 0.99446654, 0.98641753, 0.9967131 , 1.006897  ,
       0.98967355, 1.0035896 , 1.0043138 , 1.0149132 , 0.9980118 ,
       0.98612314, 0.9934039 , 0.9871943 , 0.99403566, 0.98989147,
       1.0005901 , 0.9930517 , 1.0141803 , 0.99797934, 0.98529446,
       0.9928025 , 1.0027518 , 0.9973543 , 0.98682404, 1.012798  ,
       0.99559015, 1.0100323 , 0.98889995, 0.9996722 , 0.9975084 ,
       0.9888769 , 0.98916453, 0.9934619 , 1.0041143 , 0.9941709 ,
       1.0014004 , 0.97616595, 0.99592024, 0.98828125, 1.0104009 ,
       1.0123178 , 0.99637616, 1.0016629 , 0.9888358 , 0.98000187,
       1.0280243 , 0.9893476 , 0.99822295, 1.0147896 , 0.98672086,
       0.98109764, 0.9758236 , 0.99621785, 1.001291  , 0.9944007 ,
       1.0010583 , 0.9866465 , 0.9998118 , 0.9931596 , 1.0030872 ,
       1.0111885 , 0.9843053 , 1.0048745 , 1.0142128 , 0.99341625,
       0.992739  , 1.0074968 , 0.99245834, 1.0095695 , 0.9844299 ,
       1.0069016 , 1.0027238 , 1.0056943 , 0.9950864 , 0.99050105,
       0.98449147, 0.9916025 , 0.98615617, 0.9903977 , 1.0210558 ,
       0.984792  , 0.99571675, 0.9938213 , 1.003652  , 0.9828463 ,
       0.9995775 , 1.0022653 , 1.0084885 , 0.99087876, 1.0138264 ,
       0.9998203 , 0.9952825 , 0.98618525, 0.9974055 , 1.0011542 ,
       0.9901243 , 0.9884477 , 0.9891589 , 1.010223  , 0.9948314 ,
       0.99580675, 0.9925757 , 1.0031875 , 0.9975299 , 0.98692286,
       1.0149629 , 1.0042893 , 0.9901424 , 0.999866  , 0.991426  ,
       0.9778724 , 0.97660094, 0.9894029 , 1.00205   , 1.0024713 ,
       0.98420906, 1.003711  , 0.9868677 , 1.0125362 , 0.9944192 ,
       1.0012782 , 0.9943142 , 1.0178695 , 1.0035992 , 1.0056922 ,
       1.0015188 , 1.0157582 , 0.9814638 , 0.9842476 , 0.977463  ,
       0.99863106, 0.99235123, 0.99905694, 0.9941802 , 0.99119043,
       0.99827594, 0.993833  , 1.0042293 , 1.0052844 , 0.9846509 ,
       0.9958    , 1.0040574 , 0.99013007, 1.0051452 , 1.0065045 ,
       0.9940148 , 0.98733413, 0.99693936, 0.98731035, 1.0077357 ,
       1.0071036 , 1.00469   , 1.0071435 , 0.9902707 , 1.0009317 ,
       0.9970774 , 1.0019001 , 1.0091743 , 0.974824  , 0.9978984 ,
       1.0022918 , 0.9884711 , 1.0063574 , 0.9995483 , 1.0025641 ,
       1.0010144 , 0.9876347 , 0.9942582 , 1.0058999 , 0.99957716,
       0.99273443, 0.98593724, 0.9824121 , 1.0100721 , 0.9966221 ,
       1.0037444 , 0.96125346, 0.9956379 , 0.9723977 , 0.9900424 ,
       0.9959704 , 0.9952345 , 0.99487185, 0.9915692 , 1.0044473 ,
       0.99481833, 0.9959176 , 0.9852689 , 0.98286206, 0.9980262 ,
       1.0172867 , 0.99242425, 0.9982596 , 0.9952786 , 0.9819214 ,
       0.99323905, 0.9883031 , 0.9898062 , 1.0033505 , 1.0050973 ,
       1.0059457 , 0.98579985, 0.9923582 , 1.0039538 , 0.9922323 ,
       0.997246  , 1.0020621 , 0.99628294, 1.0006069 , 0.99055904,
       0.99895215, 0.99145657, 0.9926367 , 0.9975636 , 1.0008687 ,
       0.99502534, 0.977169  , 0.99419516, 0.9966636 , 0.99611545,
       0.984362  , 1.0130445 , 1.0188857 ], dtype=float32), array([-1.39614437e-02, -5.81551250e-03, -1.93449333e-02, -2.48935772e-03,
        1.69726554e-02, -1.26473401e-02, -3.33984406e-03, -3.81406546e-02,
        2.17611678e-02,  8.91273085e-05,  3.52389016e-03,  1.58185177e-02,
        5.05326502e-03, -3.30280396e-03, -1.60588895e-03,  1.36852926e-02,
        8.85462016e-03,  1.21405432e-02, -3.47706378e-02, -5.08802980e-02,
       -3.02116908e-02, -1.94198955e-02, -1.00421757e-02, -9.63760819e-03,
       -1.86174773e-02,  3.29841413e-02,  5.71567845e-03,  7.09037390e-03,
       -7.04682339e-03, -1.01836713e-03,  7.34711532e-03, -2.82430612e-02,
        1.36976810e-02, -1.84231624e-02,  1.13510173e-02, -1.55413896e-02,
       -5.86746307e-03, -1.00426143e-02,  2.20044120e-03, -7.10838754e-03,
        6.78006560e-03,  6.65193796e-03,  2.28213146e-03, -1.83605012e-02,
        1.75983626e-02, -3.32517736e-02, -1.78272594e-02, -1.08200591e-02,
       -3.98321263e-02,  5.97430440e-03, -9.81403980e-03,  1.13027543e-02,
       -3.32524776e-02, -5.60667971e-03, -3.67802801e-03,  8.93760007e-04,
       -9.95276030e-03, -8.14731419e-03, -5.15065249e-03, -3.89641454e-03,
        2.58724634e-02,  1.60707359e-03, -1.53305512e-02, -7.93535728e-03,
        2.75883526e-02, -3.53372749e-03, -9.60803684e-03, -4.33705002e-03,
        1.56637549e-03,  2.92357374e-02,  9.46766883e-03,  3.78561905e-04,
        5.15237730e-03, -3.88050289e-03,  3.92276049e-02, -1.06478715e-02,
        2.27220822e-02, -1.45255914e-02, -3.24592739e-03,  2.72182841e-02,
       -2.79838219e-02,  3.32842348e-04, -1.49315111e-02,  8.54387507e-03,
        1.30997738e-02,  1.97016663e-04, -6.91368990e-03, -6.58551510e-03,
       -5.51044010e-03,  2.58808173e-02, -5.62099740e-03, -1.25785880e-02,
       -1.25576770e-02, -2.87237996e-03, -6.26352988e-03,  3.36660296e-02,
        1.10509302e-02,  3.78066674e-03,  3.46548087e-03,  1.51160695e-02,
       -8.13135784e-03,  2.48278328e-03, -3.81578831e-03, -9.74698737e-03,
       -1.04727652e-02, -1.34524638e-02, -2.17922218e-02, -1.11688748e-02,
        2.75248638e-03, -1.12823984e-02,  4.44740755e-03, -3.01531982e-02,
        1.95616055e-02, -8.51834472e-03,  6.44896412e-03, -2.45366767e-02,
        3.41653149e-03,  1.22858938e-02,  1.68883130e-02,  2.95819994e-02,
       -9.37489420e-03, -2.66868323e-02, -1.47574646e-02,  2.58682519e-02,
       -1.13959741e-02, -1.42063890e-02,  8.22358299e-03,  3.34872976e-02,
       -2.47089509e-02, -4.40869061e-03, -2.96494793e-02,  5.68330176e-02,
       -3.01402737e-03, -1.71964001e-02, -1.71870459e-02, -1.99680850e-02,
        1.69491395e-02, -1.70971435e-02,  3.02034593e-03, -2.75021680e-02,
        2.08519883e-02,  2.05629924e-03, -2.68128375e-03, -1.14152366e-02,
       -1.29700899e-02,  8.49649403e-03,  1.68175120e-02, -1.67076048e-02,
       -2.54302360e-02, -1.51793854e-02, -1.35436924e-02, -6.39221724e-03,
       -2.41193995e-02, -1.86963826e-02,  3.51557950e-03,  1.14241578e-02,
       -1.22912573e-02, -5.87822543e-03, -1.09188547e-02, -1.58842211e-03,
       -7.46759539e-03, -1.11015970e-02, -2.17761975e-02, -2.13006996e-02,
       -7.51877343e-03, -2.63719428e-02, -8.81355908e-03,  7.29444670e-03,
        4.04542359e-03, -1.54178003e-02,  5.45251854e-02, -1.01035163e-02,
        1.52708814e-02,  1.54632246e-02, -3.17204483e-02, -1.46923857e-02,
       -1.16628353e-02,  1.29759833e-02, -1.00462558e-02, -7.20349001e-03,
       -2.23007798e-03,  1.94772566e-03, -1.22102201e-02, -2.19141096e-02,
       -2.71608680e-02, -2.94727017e-03,  4.96284920e-05,  7.95618980e-04,
       -1.54664479e-02,  2.11789913e-04, -7.50092138e-03,  1.17839910e-02,
       -8.52506608e-03,  2.63933130e-02,  1.07535124e-02, -1.16154971e-02,
        1.99849455e-05, -2.62132380e-02, -2.64369231e-02, -1.66289490e-02,
       -8.06571450e-03,  2.45632138e-03,  1.23006981e-02, -2.14579850e-02,
       -1.06633343e-02, -2.20459327e-02,  6.67430181e-03, -1.85501277e-02,
       -7.11813394e-04,  3.62514965e-02, -9.75816976e-03, -5.74724935e-02,
        3.96669982e-03, -7.32580759e-03, -1.96935069e-02,  4.90048341e-03,
        8.07800330e-03, -3.94168636e-03,  2.06069797e-02, -1.98846683e-02,
       -4.67433175e-03, -8.54193640e-05, -4.00431594e-03,  1.55556779e-02,
        1.29415644e-02,  9.10035148e-03,  7.70753529e-03,  3.07963174e-02,
       -5.81651693e-03, -5.61383506e-03,  5.32714874e-02, -1.25729199e-02,
       -9.22665652e-03, -6.03905506e-03, -3.44889909e-02,  3.45821492e-04,
       -2.30640024e-02, -2.41921260e-03, -3.17576975e-02, -1.70596316e-02,
       -1.44524593e-02,  2.59858910e-02,  2.48169508e-02, -1.18874870e-02,
        1.49424821e-02, -1.90052744e-02, -6.35116315e-03,  9.97805689e-03,
       -7.31694652e-03, -9.91819054e-03, -2.36361986e-03,  8.35738517e-03,
       -6.76478166e-03,  6.02287194e-03,  1.40729733e-02, -5.44181503e-02,
       -1.47682615e-02,  2.44530346e-02, -3.26253963e-03, -2.73663318e-03,
       -2.18911003e-02, -1.56087689e-02,  2.17369124e-02, -2.73842178e-02,
       -9.10122041e-03,  9.67017096e-03,  1.04112960e-02, -1.10717816e-02,
       -1.32112037e-02,  5.40718762e-03,  3.54697220e-02, -1.43445088e-02,
       -1.48891844e-02,  4.13747213e-04, -2.99238767e-02, -1.40121263e-02,
       -5.44475485e-03, -3.40579674e-02,  1.27658779e-02,  2.67535821e-03,
        5.40141133e-04, -1.49330986e-03, -8.82345310e-04,  1.37619465e-03,
       -2.26238798e-02, -2.27436963e-02, -9.72486846e-03, -2.15688851e-02,
       -8.95775203e-03, -2.40590125e-02, -4.43187635e-03, -1.72784406e-04,
        5.14533278e-03, -2.92784050e-02, -5.83078479e-03, -2.82159131e-02,
       -5.70897665e-03,  7.71640101e-03, -1.08441869e-02, -9.69553459e-03,
       -3.17083299e-02, -1.00014647e-02,  1.10072060e-03, -1.08580161e-02,
        5.41970786e-03, -1.77449249e-02, -4.46254387e-02,  4.95175924e-03,
        6.24027755e-03, -1.00381412e-02,  4.87363525e-03, -2.02649995e-03,
        6.20534085e-03, -5.55565464e-04,  2.87344977e-02, -2.00549774e-02,
       -1.72271505e-02, -3.71022858e-02,  7.97796762e-04, -1.04453946e-02,
       -1.07062943e-02,  8.66951328e-03, -1.71156581e-02, -2.28325762e-02,
        1.71247625e-03,  3.17970570e-03, -1.43784145e-02, -1.74623297e-03,
       -7.99599010e-03, -3.81055437e-02, -2.74238214e-02,  3.09039955e-03,
        1.15525571e-03,  2.60377880e-02,  3.91494774e-04,  2.03504623e-03,
       -6.95476402e-03, -1.35473004e-02, -9.65108536e-03, -2.50362372e-03,
       -1.15230505e-03, -2.05161888e-02, -8.68409872e-03, -1.66630633e-02,
       -3.19187064e-03,  1.80162266e-02,  8.14393722e-03, -3.50774708e-03,
        2.39449479e-02, -1.07272305e-02,  2.10286118e-04,  7.78029999e-03,
        1.63126308e-02,  2.79878173e-02, -9.39424522e-03, -1.42367687e-02,
       -1.51439756e-03, -1.33425584e-02,  4.54704929e-03, -2.40109116e-03,
       -8.20428133e-03, -3.84807102e-02,  8.43247399e-03, -2.91085448e-02,
        7.20825046e-03, -1.04642175e-02, -2.63562128e-02, -2.49455906e-02,
       -2.18829270e-02, -2.14112457e-04, -2.18616724e-02, -1.08206151e-02,
       -1.76815200e-03, -3.93270664e-02, -6.96437201e-03,  5.51827904e-03,
       -4.06752719e-04, -2.65797302e-02,  6.35730242e-03, -6.91302074e-03,
       -1.91005692e-02, -2.47909371e-02,  3.16893533e-02, -1.80883706e-03,
       -1.71670970e-02, -2.38500852e-02, -1.15540866e-02, -1.88629180e-02,
        4.52146027e-03, -7.75765534e-03, -7.10852444e-03, -1.99298784e-02,
       -9.01908986e-03,  5.31761767e-03,  4.41848673e-03, -1.51897362e-02,
        1.67024997e-03,  1.10711716e-03, -1.79772619e-02,  2.89087696e-03,
       -2.40814574e-02, -3.33038010e-02,  2.61048004e-02,  3.68973725e-02,
       -9.81280766e-03, -4.34468826e-03, -5.41111128e-03, -2.66863015e-02,
       -2.22589578e-02,  8.13678838e-03, -7.68414838e-03, -2.04563532e-02,
        1.27772503e-02, -3.42496410e-02, -1.88566581e-03, -1.94317438e-02,
       -5.97152859e-03,  1.83163385e-04,  3.79017135e-03, -4.96422127e-02,
       -3.76497605e-03, -2.73477705e-03, -3.38167837e-03, -1.88860167e-02,
       -4.15461138e-03, -5.83251379e-03, -3.64539996e-02,  1.12647575e-03,
       -1.54760461e-02,  4.69575077e-03, -1.59222558e-02,  2.85400413e-02,
       -4.69122175e-03, -4.15085554e-02,  4.19476517e-02, -4.90853935e-03,
        1.79117434e-02, -9.57667641e-03, -2.08856668e-02, -5.38749900e-03,
       -1.85356177e-02,  7.91897997e-03,  1.40151498e-03,  8.29201192e-03,
       -1.08601926e-02, -1.51025807e-03, -1.32686533e-02, -6.42957911e-03,
        9.78108146e-04, -1.94652472e-02, -1.90163534e-02, -1.88240800e-02,
       -2.53954390e-03, -3.71482340e-03,  7.90333189e-03, -8.29159562e-03,
       -3.41915037e-03,  1.02087613e-02,  1.91045273e-02, -1.79077452e-03,
       -6.95946440e-03,  2.41435207e-02,  1.66839901e-02, -6.60105841e-03,
       -1.57876797e-02, -1.18338512e-02,  4.90964344e-03, -1.00266701e-02,
       -1.43891405e-02,  1.59393083e-02, -1.00507839e-02, -2.33706199e-02,
        5.80196094e-04, -2.49824934e-02,  1.50707958e-03, -3.76268327e-02,
       -6.02123514e-03, -7.94462673e-03, -4.36635315e-03, -5.20825526e-03,
       -1.90470219e-02, -3.76671925e-02, -2.91371671e-03, -1.57944877e-02,
        2.06263755e-02, -2.11610273e-02, -2.10058861e-04,  5.83245885e-04,
        3.12101189e-03, -7.49991334e-04, -1.53163215e-02, -1.32331215e-02,
       -1.13631189e-02, -7.35540129e-03, -1.69375334e-02,  1.76687520e-02,
        9.17464145e-04, -1.57177523e-02, -1.46346707e-02, -3.44751067e-02,
       -1.32976025e-02,  2.11700294e-02,  1.15102679e-02, -2.49663042e-03,
       -1.41834924e-02, -2.26801466e-02,  4.77646943e-04,  1.87771693e-02,
       -2.75137108e-02, -5.12791751e-03,  1.10022109e-02, -1.11208260e-02,
        3.76072638e-02,  1.34809362e-02,  2.28452794e-02, -4.75649349e-03,
       -5.10218088e-03, -1.75357854e-03, -1.10706147e-02, -1.32323205e-02,
        6.56958204e-03, -1.38325365e-02, -1.45003665e-03,  7.35946745e-03,
        1.58128084e-03, -3.46534560e-03, -8.30937736e-03,  2.73388112e-03,
       -1.79466829e-02,  7.27310171e-03, -1.05871223e-02,  1.49333728e-02,
       -2.53745914e-02,  3.73084620e-02,  9.87319183e-03, -6.85920985e-03,
       -1.17218671e-02, -1.66167337e-02, -9.03985184e-03, -2.68593319e-02,
       -2.05838010e-02, -2.73714941e-02, -1.34500870e-02, -1.53098004e-02,
        6.67714374e-03,  2.24090479e-02,  2.41224701e-03,  1.46196864e-03,
       -1.06718456e-02, -1.26035996e-02,  2.69913338e-02, -2.37103067e-02,
       -1.61952861e-02, -6.97011920e-03,  2.10579559e-02, -2.23464593e-02,
       -5.09990565e-02, -1.86835788e-02,  2.32903194e-03, -1.28349373e-02,
        1.16915144e-02,  1.19210668e-02,  3.42740328e-03,  1.21362666e-02,
        2.45836191e-02, -1.09573705e-02,  1.12726521e-02, -7.64569221e-03,
       -4.01310530e-03, -6.21464569e-03, -1.86063293e-02, -3.27401571e-02,
       -3.77866998e-03, -3.62287019e-03, -1.44540910e-02,  1.05935503e-02,
       -9.98310186e-03, -9.40016191e-03, -6.12546410e-03, -3.39466110e-02,
       -6.28244225e-03, -9.93974274e-04,  1.28846252e-02, -4.12242347e-03,
        3.34230252e-02, -9.94953699e-03, -2.12654416e-02,  5.83615480e-03,
       -1.24945156e-02, -3.30986902e-02,  9.01854783e-03, -1.39181619e-04,
       -2.20326707e-03, -1.40127689e-02,  1.82796866e-02,  1.11080706e-04,
        1.48304328e-02,  1.19890564e-03,  1.18417591e-02,  1.76419988e-02,
       -2.44274288e-02, -8.72054789e-03, -2.38121301e-03, -2.59861071e-02,
       -9.63671040e-03,  5.82767604e-03,  7.86055159e-03, -2.46813218e-03,
       -2.44488870e-03, -1.79488249e-02, -7.84559082e-03,  2.32606623e-02,
       -3.00848056e-02, -1.49392607e-02, -1.24406423e-02, -1.72422361e-02,
       -4.24997099e-02, -2.22449098e-02,  7.45682558e-03, -1.92876812e-02,
       -1.67448893e-02, -1.35552054e-02, -1.38567816e-02,  9.22195520e-03,
        9.03626438e-03, -2.96409968e-02, -2.79360041e-02,  9.50827543e-03,
       -5.17023681e-03, -1.55076636e-02,  2.71289202e-04,  6.81554712e-03,
        6.32577750e-04, -1.27093419e-02, -7.66319316e-03,  2.24468429e-02,
       -1.46698505e-02,  3.50195775e-03, -5.79236867e-03,  1.28397858e-02,
        1.29557704e-03, -7.47702178e-03,  8.10229313e-03,  2.59948196e-03,
        2.64476170e-03, -7.14001432e-03,  1.38831204e-02,  9.63537674e-03,
       -5.07517019e-03, -1.75649412e-02,  7.02483871e-04, -1.79041922e-02,
        8.29496887e-03, -5.78187453e-03,  1.09614367e-02,  7.00233690e-03,
       -8.86696111e-03, -1.14969779e-02, -1.75290760e-02, -6.79227570e-03,
       -1.49072912e-02,  5.35681285e-03, -1.23324823e-02, -4.29321826e-03,
       -8.90846737e-03,  1.42626301e-03, -1.75826065e-02, -1.65615417e-02,
        2.27347724e-02, -7.90009461e-03, -1.69298556e-02, -5.92231937e-03,
        5.16686030e-03,  2.63512675e-02,  2.12248359e-02, -1.29718045e-02,
       -2.69322321e-02, -5.33366986e-02, -6.74542040e-03,  2.31302045e-02,
        7.72992033e-04, -7.99744576e-03, -1.27721559e-02, -5.01158927e-03,
       -1.56387892e-02,  7.01979548e-03, -5.68170846e-03, -5.43600647e-03,
        4.41032834e-03, -1.81341022e-02, -7.20952963e-03, -2.54737418e-02,
       -2.14485470e-02, -2.58451868e-02, -3.82662471e-03,  4.13331129e-02,
       -1.36502190e-02, -9.68330819e-03, -1.25746578e-02, -2.38495786e-03,
        9.44994041e-04, -1.46223800e-02, -2.50187349e-02,  7.18491210e-04,
       -2.73191277e-03, -8.48076888e-04, -2.09333785e-02, -6.10654568e-03,
        2.67562214e-02, -2.91530583e-02,  1.27114104e-02, -6.61820872e-03,
        1.55230816e-02, -2.20808177e-03,  1.77794416e-02,  2.86162943e-02,
        3.62851773e-04, -3.15674841e-02, -3.02546211e-02, -6.35645492e-03,
        2.90378300e-03, -4.19078283e-02, -3.64221968e-02, -2.33057663e-02,
       -5.11413818e-05, -2.87923850e-02,  2.80374177e-02, -8.97594355e-03],
      dtype=float32), array([ 4.47956651e-01,  3.18164468e-01,  1.09443516e-01,  2.34176308e-01,
       -2.55046219e-01,  5.17955273e-02, -1.38076931e-01,  1.06897421e-01,
       -3.31993476e-02,  1.12092599e-01, -1.74224824e-01,  2.45629221e-01,
        1.46860838e-01, -8.71640071e-02, -2.62963563e-01,  2.22094655e-01,
       -3.77913445e-01, -1.84554085e-01, -8.62841029e-03, -2.13932991e-01,
        1.89751238e-01,  1.53075114e-01, -2.71282703e-01,  3.65837485e-01,
        3.72222401e-02,  2.27332249e-01, -2.05810443e-01, -1.32661432e-01,
        3.72323068e-03,  6.71114981e-01, -9.06995311e-03, -5.14340401e-02,
       -1.15890719e-01, -1.83507711e-01, -2.84028262e-01,  4.47055489e-01,
       -1.26828834e-01, -1.52084529e-01,  6.46575019e-02, -2.78896660e-01,
        2.14705080e-01, -1.90045476e-01,  9.38230380e-03, -1.87010840e-01,
       -4.93909329e-01,  3.35999936e-01, -4.21965063e-01,  2.52117008e-01,
       -3.45052406e-02, -5.48707008e-01,  6.09871209e-01,  3.42995375e-02,
        2.69785106e-01, -9.41232219e-02, -2.21570805e-01,  2.96847019e-02,
        2.88540572e-01, -2.52101775e-02, -1.19555116e-01, -1.05288655e-01,
       -1.90110222e-01,  2.11624801e-01, -3.76415312e-01,  3.53302598e-01,
        5.98078445e-02,  7.98590779e-02,  4.44269091e-01, -1.20398141e-01,
        1.07634850e-01, -2.73679137e-01, -1.76218763e-01,  1.70293134e-02,
       -2.56216049e-01,  1.17431238e-01, -4.47614700e-01,  3.92268896e-01,
       -1.61467358e-01,  1.30633280e-01,  1.47485867e-01, -1.46713972e-01,
        4.08299118e-02,  2.94069737e-01,  3.71831834e-01, -1.52466357e-01,
       -3.05011928e-01, -2.63962567e-01, -1.67755678e-01,  1.81027278e-01,
       -5.94646707e-02, -2.20045537e-01, -2.13439956e-01,  2.33637672e-02,
       -2.83587009e-01,  1.77569672e-01, -2.52657235e-01, -3.88471156e-01,
       -2.21605420e-01,  2.10444387e-02,  4.05160114e-02,  1.38365269e-01,
       -2.60347277e-01,  1.87942028e-01,  3.37949321e-02,  1.31529942e-01,
       -1.05218597e-01, -8.05346817e-02,  5.32378912e-01,  2.74946243e-01,
        1.74282759e-01,  1.33062884e-01,  1.14726387e-01,  1.13591209e-01,
       -6.95298910e-02,  5.00317752e-01,  1.11825533e-01,  9.86222550e-02,
        1.48143694e-01, -1.14442438e-01, -2.31340811e-01, -2.42410913e-01,
       -2.67516285e-01,  4.16869521e-01,  1.64676651e-01, -3.41937505e-02,
        1.53738528e-01,  1.25572249e-01, -3.73090385e-03, -1.55184582e-01,
        1.10934913e-01, -7.98789710e-02,  2.69734085e-01, -2.85906587e-02,
        7.39478469e-02, -1.57613248e-01,  2.48018637e-01,  1.64500058e-01,
       -1.06813721e-01,  3.61223996e-01, -9.65088308e-02, -5.23260981e-02,
        2.03768298e-01,  1.39394701e-02,  3.68941337e-01,  2.71262497e-01,
        1.30252615e-01,  1.63409770e-01, -2.33250320e-01, -8.60196427e-02,
        1.56790409e-02, -1.96233228e-01, -2.24675640e-01,  3.37417215e-01,
       -2.06861749e-01,  2.82497197e-01, -5.11998162e-02,  5.34165464e-03,
       -2.37954259e-02, -1.09705128e-01, -2.35684887e-01, -3.02993298e-01,
       -1.98453605e-01, -7.40770483e-03, -9.82874036e-02,  2.15905771e-01,
        4.53475453e-02,  3.17776322e-01,  1.32297695e-01, -1.72152266e-01,
        1.87070474e-01,  1.99248374e-01, -7.40426034e-02,  4.33861375e-01,
       -2.96808004e-01, -2.91416675e-01,  1.54516429e-01,  9.44791138e-02,
        4.46490496e-02,  7.82561824e-02, -8.27679858e-02,  7.01407017e-03,
       -7.16816336e-02,  1.38007358e-01, -2.75368631e-01, -1.67851165e-01,
       -3.77489775e-01,  1.57454222e-01,  5.83035983e-02,  4.20763768e-04,
       -3.57995927e-02, -8.61768946e-02,  2.82561809e-01, -4.54088658e-01,
        1.68886557e-01, -2.22126111e-01,  2.97168158e-02, -2.21148387e-01,
        1.64652064e-01,  2.39215776e-01, -1.01169899e-01,  1.68323383e-01,
       -3.10315818e-01,  1.10214479e-01,  5.10187410e-02, -2.86355019e-01,
       -2.90333807e-01,  2.75699235e-02, -1.31067678e-01,  2.21895576e-01,
        3.26424278e-02, -4.15269136e-02, -1.52921617e-01, -2.50020623e-01,
        1.13938354e-01, -3.67992073e-01,  1.99488863e-01, -9.29531083e-02,
        2.25847319e-01, -1.10608816e-01, -2.90460199e-01, -4.04906034e-01,
        1.82870701e-01,  1.33081064e-01, -2.97837615e-01,  3.55499119e-01,
       -6.26471788e-02,  1.25431176e-02,  1.87875465e-01, -1.93063349e-01,
        2.88752854e-01, -1.96894988e-01, -2.86330223e-01, -7.98584223e-02,
        1.97132185e-01,  1.82956785e-01,  1.82198822e-01, -2.01324522e-01,
        3.61850947e-01, -5.07153049e-02,  1.60025299e-01,  1.29157789e-02,
        9.31041837e-02, -6.20081276e-02, -2.87632197e-01, -9.72933322e-02,
       -1.33459181e-01,  1.03878891e-02, -1.10698521e-01,  4.40301150e-02,
       -8.63606259e-02,  2.34656855e-02,  2.60023512e-02,  1.40992254e-01,
       -1.18872337e-01,  4.52043191e-02,  1.00535139e-01, -3.03043593e-02,
        2.46019125e-01, -4.92283031e-02, -3.70809913e-01,  6.68144375e-02,
        1.34798318e-01, -4.14493352e-01,  1.04968324e-02,  1.00392781e-01,
        1.36395901e-01,  2.91081011e-01, -2.32116193e-01, -1.85311720e-01,
       -1.36772960e-01,  1.03974655e-01, -4.72872823e-01,  1.38593405e-01,
       -9.64235589e-02,  3.23189259e-01,  5.19689083e-01,  2.46626958e-01,
       -5.29896133e-02,  2.18907759e-01, -6.74690073e-03,  2.19916791e-01,
       -1.71962559e-01,  2.08413735e-01,  5.01278825e-02,  1.21913001e-01,
        2.08962515e-01, -4.98322621e-02,  5.34575284e-02,  3.48764241e-01,
       -4.95917983e-02,  1.74872968e-02,  6.91125840e-02,  3.55129912e-02,
        2.07447499e-01,  4.59054485e-02, -1.20437250e-01, -1.54193500e-02,
        3.29369485e-01, -3.13422263e-01,  2.30968446e-01,  1.47249714e-01,
        9.68082529e-03,  1.22091986e-01, -6.61877077e-03,  1.66381627e-01,
        1.49834141e-01,  3.40510070e-01,  1.19590163e-02, -1.47090137e-01,
       -1.98612884e-02,  4.05604482e-01, -1.21506520e-01, -8.97451714e-02,
       -1.52092660e-02, -1.06201157e-01, -3.18795413e-01, -3.82911973e-02,
        5.50919548e-02,  3.43579985e-02,  1.31568134e-01,  3.20839971e-01,
        7.06912344e-03,  9.42878798e-02, -1.14698753e-01,  1.08088724e-01,
       -1.75279126e-01, -9.40181389e-02, -9.31765959e-02,  1.84179455e-01,
        2.04204485e-01, -3.13486993e-01,  2.30624706e-01, -5.03609590e-02,
       -3.10940444e-01, -4.36227381e-01, -3.21682155e-01,  2.02255189e-01,
        1.29989520e-01,  4.24858034e-01,  3.11744437e-02,  4.11614850e-02,
        1.53804734e-01,  3.36155266e-01, -1.05744176e-01,  3.81927758e-01,
       -3.52422476e-01,  9.10722092e-02,  1.34601131e-01,  8.56353715e-02,
       -2.10673884e-01,  4.30164903e-01, -1.03199184e-01,  1.62555099e-01,
        4.13061641e-02,  3.00413072e-01, -1.55059090e-02,  2.12399155e-01,
        2.69001544e-01,  3.90091799e-02,  1.66551024e-01,  3.89571190e-01,
       -6.56257290e-03, -3.16110961e-02,  1.93849802e-01,  6.96275309e-02,
       -1.14995949e-01, -8.81833658e-02, -3.17233890e-01, -2.51614541e-01,
       -7.94065818e-02, -7.36046359e-02, -2.61979640e-01,  2.41539344e-01,
       -3.20048071e-03,  2.88823754e-01,  7.02330023e-02, -8.42861459e-02,
       -1.89646587e-01,  2.51614422e-01,  1.80889472e-01,  6.09544963e-02,
       -2.05016732e-01,  9.94900148e-03,  2.04971969e-01, -2.35619441e-01,
       -1.62416995e-01,  1.94152251e-01, -5.54028153e-02,  5.19915298e-02,
        3.65024984e-01,  1.76352352e-01,  7.67429471e-02, -1.97261930e-01,
       -1.42713770e-01,  2.26612687e-01, -6.37907088e-02,  5.03448918e-02,
       -1.08034335e-01,  2.80480057e-01,  2.09587023e-01,  5.33872992e-02,
        6.31718412e-02,  2.59726699e-02, -1.09021470e-01, -9.48806331e-02,
        7.83324465e-02,  1.16429990e-02, -1.13213584e-01,  1.57053798e-01,
        1.17897065e-02,  1.41218290e-01,  3.35043341e-01,  7.22071826e-02,
       -6.88337758e-02, -2.11482972e-01, -2.11840123e-01, -3.28382015e-01,
        7.20179826e-02, -2.77999826e-02,  1.11564972e-01, -1.86336815e-01,
       -2.32301615e-02, -1.34180812e-02, -1.21824890e-01,  1.02778286e-01,
       -1.81069851e-01,  2.50870109e-01, -4.05001700e-01,  1.78294629e-01,
       -1.08242571e-01,  2.24475384e-01,  9.25317332e-02, -4.85016033e-02,
       -1.74155012e-01,  1.09156832e-01, -9.50368717e-02,  2.00260997e-01,
       -1.39989987e-01,  6.28461912e-02, -1.36995971e-01,  1.47646949e-01,
        4.39517260e-01, -1.45731553e-01, -5.95910475e-02,  4.41025406e-01,
        1.72877371e-01, -1.22640997e-01, -2.24750876e-01, -7.31348842e-02,
       -8.84861778e-03, -2.02348679e-01, -1.13384522e-01,  9.79736745e-02,
       -8.02099854e-02,  4.12517227e-02, -1.15326874e-01,  1.84167102e-01,
       -2.28384882e-02, -2.10059047e-01, -2.70522177e-01,  6.87801242e-02,
        1.84404954e-01, -1.43558621e-01, -1.24856852e-01, -6.57671094e-02,
        4.52529341e-01, -1.95897073e-02,  1.76131085e-01,  7.39118829e-02,
       -1.86032146e-01,  4.38233204e-02, -4.68402207e-02, -5.96423149e-02,
        1.55124471e-01,  1.01881526e-01, -9.08590853e-02,  7.32901990e-02,
       -2.91892111e-01,  4.58821863e-01, -3.25531475e-02, -1.84997022e-01,
       -1.48957402e-01, -2.80998386e-02,  1.41843176e-03,  2.41632208e-01,
        3.14523578e-01, -2.02091381e-01,  1.37355253e-01,  4.33235615e-01,
       -2.55288810e-01, -1.77969545e-01, -1.73466638e-01,  1.40560091e-01,
       -2.95170728e-04,  3.16252828e-01, -3.75150610e-03,  1.08666681e-02,
        8.38247538e-02,  2.83360273e-01,  6.92118099e-03, -1.81431353e-01,
        1.19822763e-01,  4.18149494e-02, -2.02914655e-01,  6.40898943e-02,
       -2.64059124e-03, -7.59860724e-02, -1.27168670e-01, -2.42973283e-01,
       -2.51178455e-04, -1.58925459e-01, -1.11540325e-01, -3.86745669e-02,
       -1.22211710e-01, -3.02613169e-01, -7.47996569e-02, -3.05561841e-01,
        3.88657227e-02,  4.78584796e-01, -3.19932640e-01, -2.60734856e-01,
       -1.38962761e-01, -6.84510311e-03,  1.71963990e-01,  1.09405853e-01,
       -2.02906597e-02, -4.92644310e-02,  3.64973903e-01,  3.77160311e-02,
        4.75500897e-02, -2.70616740e-01, -1.80732295e-01, -2.81459857e-02,
        3.30501527e-01, -4.66069616e-02, -4.77758497e-01, -1.10254008e-02,
        2.24240929e-01,  3.01528931e-01,  7.02958629e-02, -1.26261264e-01,
        1.37374654e-01, -7.00344816e-02,  3.86565104e-02, -6.12098128e-02,
       -3.40556264e-01, -1.59674034e-01,  2.93418914e-01,  1.41356170e-01,
       -1.41009018e-01, -2.64142245e-01, -3.32130283e-01,  6.36186302e-02,
        2.19432712e-01, -3.20886523e-01, -3.12085629e-01, -2.49084607e-01,
       -5.48420474e-02,  1.41026899e-01, -1.40554681e-01, -1.99887343e-02,
       -2.87156831e-02, -8.01366642e-02, -7.60063156e-02, -1.23665728e-01,
       -1.43797979e-01, -5.68763576e-02, -5.69800362e-02, -1.62888929e-01,
       -2.56398499e-01,  9.02711079e-02,  1.09432414e-01, -7.17325881e-02,
       -1.59949157e-02, -4.71524894e-01,  1.35604113e-01, -2.35705867e-01,
        1.60092697e-01,  1.47887737e-01, -1.26415759e-01,  1.92265317e-01,
        1.02505930e-01, -1.92670435e-01, -6.45261332e-02,  1.88226923e-01,
       -1.54322430e-01, -6.95202872e-02, -2.09303990e-01, -8.11762065e-02,
        6.55056685e-02, -2.32819200e-01,  1.46683171e-01, -1.13891140e-01,
        8.11503455e-02, -6.31628484e-02, -1.38148040e-01,  1.52356505e-01,
       -3.27236801e-01, -2.41805967e-02,  4.09331709e-01,  2.77115494e-01,
        2.24574476e-01,  1.23434328e-01,  2.36740664e-01, -7.01555088e-02,
        2.23620310e-01,  2.24746928e-01, -5.86962700e-01, -1.03892691e-01,
       -2.42694244e-01,  2.88259447e-01, -1.57965049e-01, -6.35083765e-02,
        3.77736211e-01, -1.41921267e-01,  4.11697552e-02, -6.97094724e-02,
        4.00240459e-02, -6.51293769e-02, -1.06318519e-01, -4.97946963e-02,
       -1.83825582e-01, -1.51132718e-01,  1.46036416e-01,  1.36365235e-01,
        1.60259455e-01, -1.57205001e-01, -3.91515344e-01, -1.85657784e-01,
        6.79946840e-02, -5.15461825e-02, -3.00625056e-01, -3.74121159e-01,
        2.26714119e-01, -3.42520833e-01,  1.97919130e-01, -1.53861940e-01,
       -7.59605840e-02,  1.00056186e-01, -1.49377957e-01, -3.76104355e-01,
       -3.29215407e-01, -1.38138428e-01,  3.79336588e-02,  4.76439856e-02,
       -8.58392566e-02, -2.71857679e-01, -3.77428196e-02,  1.19675644e-01,
        2.92834014e-01,  2.33426869e-01,  3.73181552e-01,  3.93320508e-02,
       -9.12529379e-02, -1.31711289e-01,  1.87698349e-01,  1.57325998e-01,
       -4.03674468e-02,  4.23068665e-02,  1.91818133e-01,  2.10390791e-01,
       -1.64102204e-03,  3.39709312e-01,  4.13001776e-02,  4.80409339e-03,
        1.10090964e-01, -1.50706142e-01,  3.10221314e-01, -1.15394324e-01,
        1.23061597e-01, -2.02931195e-01,  8.45161676e-02,  1.97312720e-02,
       -6.92132637e-02, -2.03006402e-01, -8.20030645e-02,  1.09351501e-01,
       -1.23551056e-01, -1.56376779e-01,  3.47914100e-02,  2.06857219e-01,
       -2.69069105e-01, -2.50848327e-02,  5.75661520e-03,  9.64440256e-02,
        1.59047782e-01, -7.90339932e-02, -5.54437302e-02, -1.47640407e-01,
       -7.13479593e-02,  4.20712382e-02, -1.93793491e-01,  2.44785100e-01,
       -2.37948984e-01,  1.43172979e-01,  5.92704900e-02, -1.57855064e-01,
       -5.45162186e-02, -8.90333299e-03, -3.49798739e-01,  1.74376994e-01,
        2.79742092e-01,  1.26501605e-01, -5.07941842e-02, -8.53231996e-02,
        3.08782429e-01, -3.46535891e-01,  2.30400443e-01,  7.29957521e-02,
       -3.31338793e-01, -2.42858723e-01, -1.44378757e-02, -8.99157524e-02,
       -2.18015224e-01,  7.33949477e-03,  3.03814877e-02, -1.08558595e-01,
       -1.88057020e-01,  1.61054611e-01, -1.94010794e-01,  1.01894550e-01,
        4.71782863e-01, -1.50478736e-01, -9.76440683e-02, -4.13362026e-01,
        2.15800151e-01,  1.99773327e-01,  7.64357150e-02, -3.30858827e-02],
      dtype=float32), array([2.043416  , 3.1472888 , 1.2894602 , 1.1260707 , 1.5694507 ,
       3.3698635 , 0.8571419 , 3.6505978 , 4.0644145 , 3.3313317 ,
       3.23069   , 3.328919  , 8.58522   , 4.41895   , 1.2291533 ,
       2.893439  , 2.9409497 , 3.2458143 , 5.593895  , 2.461621  ,
       1.5003023 , 3.5404577 , 1.6986657 , 3.1246552 , 1.8147203 ,
       5.5538373 , 1.7105547 , 2.03013   , 2.144888  , 1.0834639 ,
       2.5736527 , 2.4264514 , 1.6477555 , 1.5442497 , 1.5912609 ,
       3.2283332 , 1.4705409 , 2.5867453 , 3.1421957 , 4.636844  ,
       1.7203113 , 1.4915681 , 1.2545578 , 8.237031  , 1.2855604 ,
       2.69496   , 2.0659337 , 3.7583985 , 3.0315886 , 4.4631653 ,
       3.1821856 , 0.5708742 , 4.2979574 , 3.2305474 , 1.8694816 ,
       3.2839324 , 1.9095896 , 1.2539016 , 3.043269  , 1.395609  ,
       3.7142198 , 3.2283769 , 2.9005404 , 3.8487184 , 1.7544568 ,
       1.3987055 , 2.0079532 , 2.4812722 , 1.7018534 , 2.5491316 ,
       2.244447  , 2.1554246 , 3.187165  , 0.7839858 , 2.229057  ,
       2.8957355 , 2.9518852 , 2.9169273 , 3.092111  , 2.3158875 ,
       1.7255985 , 1.1940873 , 5.839564  , 1.575281  , 1.9534853 ,
       0.9875284 , 1.9594462 , 0.77419716, 3.9519029 , 6.422697  ,
       2.7965791 , 1.3062434 , 2.2669322 , 1.4708735 , 1.4008272 ,
       6.081688  , 1.6512818 , 2.466801  , 0.8410674 , 3.9204807 ,
       0.91274595, 0.89113027, 4.2801356 , 1.9309001 , 2.490559  ,
       4.4247427 , 2.2072265 , 3.0509458 , 1.7067556 , 2.1290252 ,
       1.7242776 , 3.8168795 , 0.63287926, 0.98559314, 3.1518219 ,
       1.6391972 , 1.2736791 , 1.9493145 , 5.6055284 , 1.808072  ,
       3.0823162 , 3.3860962 , 1.096095  , 1.8209052 , 2.0504377 ,
       3.2634392 , 1.5862782 , 1.05106   , 2.0106869 , 2.8032098 ,
       3.214958  , 2.943597  , 2.860296  , 1.0794114 , 1.3167664 ,
       4.5989165 , 1.1051646 , 2.8689995 , 2.7569695 , 1.6908579 ,
       2.095967  , 1.7231156 , 4.796992  , 2.0886486 , 2.1987352 ,
       2.6181562 , 4.1237335 , 3.3310611 , 3.5762086 , 5.651256  ,
       2.0828776 , 1.7279569 , 2.3476558 , 2.7748966 , 1.6112397 ,
       2.2946389 , 2.3333073 , 2.8687394 , 2.976544  , 2.4125414 ,
       1.635902  , 1.0763234 , 1.0881162 , 0.7794105 , 1.4379554 ,
       2.8617609 , 3.7458625 , 1.1232834 , 2.733479  , 3.5082014 ,
       2.6559992 , 2.127657  , 1.915497  , 1.9890447 , 3.1656387 ,
       3.4938736 , 2.2037776 , 3.4150236 , 1.3893247 , 2.0590837 ,
       1.8657587 , 0.9436745 , 1.7680165 , 1.7913023 , 2.6198175 ,
       2.614182  , 1.9997263 , 1.559529  , 2.4402456 , 5.259009  ,
       2.6445217 , 1.813367  , 1.5443621 , 2.862878  , 1.1053666 ,
       2.7062242 , 2.6388521 , 2.704783  , 5.008941  , 0.6386832 ,
       2.7359662 , 1.1418282 , 0.8646728 , 1.190505  , 2.0673246 ,
       4.2634263 , 2.1919026 , 1.5616633 , 1.2056767 , 2.4860942 ,
       1.4307537 , 4.9271235 , 3.207937  , 1.2156771 , 4.183996  ,
       1.6676171 , 1.1057838 , 1.4727811 , 3.4991121 , 3.5606163 ,
       2.6808484 , 1.49084   , 1.7668097 , 2.18021   , 1.5328584 ,
       1.2914401 , 1.9956523 , 1.4991689 , 2.5622046 , 2.5643198 ,
       3.1968493 , 1.6041214 , 3.1457324 , 1.9137828 , 7.7243423 ,
       2.6961775 , 1.2326312 , 4.312578  , 2.9129803 , 1.6907762 ,
       4.840341  , 5.0576835 , 0.93162155, 0.87793505, 2.378786  ,
       3.9252868 , 1.3101183 , 2.0336828 , 1.4925724 , 3.2901394 ,
       1.7550501 , 3.4529927 , 0.9852725 , 1.8525605 , 2.1290596 ,
       1.9051707 , 1.5085515 , 2.765191  , 2.971187  , 1.0545461 ,
       1.029623  , 2.564416  , 3.116963  , 4.095513  , 4.0708356 ,
       1.3343542 , 1.7259656 , 1.1242262 , 2.3842015 , 2.852595  ,
       2.676522  , 2.6999686 , 1.529917  , 2.2725332 , 2.5419555 ,
       2.712962  , 2.6343887 , 4.4243937 , 3.0346885 , 3.0421524 ,
       3.726406  , 2.0412817 , 2.3852808 , 1.1157168 , 4.4018764 ,
       2.4463563 , 3.1962376 , 2.9932303 , 4.4869885 , 4.166333  ,
       1.3486354 , 1.2823298 , 2.2020144 , 3.7392037 , 3.1825798 ,
       2.692542  , 1.411648  , 1.0871211 , 1.7667954 , 1.7297442 ,
       4.5492554 , 2.7571788 , 1.6441935 , 3.5498798 , 2.1228173 ,
       1.5462639 , 4.7668753 , 1.352572  , 2.8819814 , 3.3036442 ,
       1.6010407 , 3.0365982 , 2.1004312 , 3.0742047 , 6.0417995 ,
       7.0647388 , 3.3608577 , 2.7580652 , 3.270792  , 1.8551222 ,
       2.0130208 , 3.4138734 , 2.4860923 , 4.2475514 , 3.5318437 ,
       1.7231432 , 3.8196273 , 1.5528332 , 0.9123846 , 2.9716787 ,
       4.582323  , 1.043248  , 3.4541302 , 3.8979256 , 1.9029857 ,
       1.9029527 , 2.3965116 , 1.3572531 , 1.8190621 , 1.0350615 ,
       1.7417305 , 2.5021017 , 2.6357794 , 0.8153242 , 2.7290514 ,
       4.2182713 , 4.0463123 , 6.7460084 , 2.8237298 , 1.9800972 ,
       2.2031682 , 2.677546  , 5.0846357 , 2.1804585 , 3.0133839 ,
       2.0274677 , 2.0120115 , 0.90350384, 1.7633301 , 2.7565079 ,
       1.6258137 , 3.9925575 , 2.2396348 , 1.704205  , 4.192865  ,
       2.9233282 , 1.354396  , 5.2733316 , 4.8663554 , 1.5517852 ,
       2.394474  , 1.5239836 , 1.1898967 , 2.4803784 , 1.7851586 ,
       1.7142483 , 9.206827  , 2.588371  , 2.5526385 , 3.030994  ,
       1.9327425 , 3.995856  , 3.0023663 , 2.3837306 , 1.2358656 ,
       3.8123307 , 1.2214094 , 2.9531746 , 0.90663934, 4.49789   ,
       3.5096393 , 2.7210748 , 1.5355537 , 2.9125755 , 2.3566198 ,
       5.2510524 , 1.5889881 , 1.2655561 , 2.513959  , 2.109972  ,
       2.6182055 , 4.1617494 , 2.9425626 , 3.7343276 , 2.3219817 ,
       1.1022949 , 1.3912542 , 7.2202272 , 1.6467767 , 2.0905108 ,
       2.2751307 , 4.7487273 , 3.5998936 , 2.444102  , 2.3621192 ,
       0.88337874, 2.3919456 , 1.3313849 , 0.62747514, 3.2658296 ,
       1.8903242 , 1.8165891 , 1.579367  , 1.8719398 , 1.442571  ,
       1.4069043 , 5.419996  , 4.535298  , 3.6686995 , 5.392311  ,
       2.3901951 , 1.8508353 , 3.012938  , 3.5686424 , 4.3136272 ,
       2.4804385 , 2.4896417 , 1.728316  , 2.7765167 , 2.3892295 ,
       2.6910393 , 1.9910313 , 2.0564852 , 3.4587224 , 0.8683471 ,
       1.7962472 , 2.0429459 , 2.0915124 , 1.6858827 , 2.02444   ,
       0.9750614 , 2.907801  , 1.7412714 , 3.0496788 , 3.0047226 ,
       2.1696985 , 2.6334243 , 3.0746374 , 3.865691  , 1.0112005 ,
       2.1434464 , 3.6907363 , 1.1323984 , 2.3193767 , 2.071562  ,
       1.2384264 , 2.082964  , 2.520835  , 2.9858549 , 2.303774  ,
       2.8678586 , 2.5124977 , 4.85886   , 2.2087255 , 3.4897075 ,
       3.1692712 , 4.929295  , 1.368553  , 2.1395738 , 1.5985688 ,
       3.0813358 , 3.543032  , 1.0000764 , 1.8213496 , 2.6551497 ,
       0.8767847 , 1.3808995 , 1.7481033 , 4.620593  , 2.0227861 ,
       2.6009843 , 1.5363718 , 3.731027  , 2.2659156 , 2.0410047 ,
       2.1315575 , 0.72423476, 2.4702988 , 3.2078767 , 3.1724844 ,
       1.3368176 , 1.8091351 , 3.4605954 , 1.9155921 , 3.6917243 ,
       2.2978306 , 1.3750069 , 1.6206397 , 6.7070208 , 2.435739  ,
       2.3648174 , 2.6260502 , 2.4931378 , 1.6953707 , 0.790866  ,
       2.0795085 , 2.338053  , 1.7637823 , 2.3351839 , 1.6577469 ,
       1.7925482 , 3.050514  , 1.2822528 , 1.2048506 , 1.1503711 ,
       4.9215717 , 1.6732627 , 2.737428  , 1.927833  , 1.2917519 ,
       2.490631  , 2.3211334 , 1.5498567 , 2.6407657 , 2.3781168 ,
       2.1396923 , 1.8302636 , 5.358082  , 2.588512  , 2.5241299 ,
       0.89745224, 1.532057  , 1.9225951 , 1.5795126 , 1.9276682 ,
       3.6936471 , 3.9439225 , 1.8810618 , 2.5900345 , 2.7524805 ,
       2.2909663 , 2.7725487 , 1.2739325 , 2.2549715 , 4.0508184 ,
       3.5791264 , 5.656604  , 4.182573  , 1.5884777 , 3.6585581 ,
       2.7681942 , 1.3335149 , 1.5081456 , 4.118911  , 3.1096625 ,
       3.8623888 , 1.6509323 , 1.6642863 , 1.9505897 , 0.81621283,
       4.5817113 , 2.9943953 , 2.587283  , 3.0483854 , 1.6338679 ,
       1.8609997 , 2.8193138 , 1.5180292 , 2.2988012 , 2.9058924 ,
       1.3824133 , 1.4817455 , 2.9509258 , 1.9665991 , 5.788413  ,
       6.3307533 , 1.9860162 , 2.6932178 , 3.1827888 , 6.0789013 ,
       1.2694883 , 0.85830057, 2.3147626 , 1.1488322 , 5.209358  ,
       2.7017498 , 3.6890554 , 1.9054909 , 1.3953923 , 1.3871948 ,
       2.2057095 , 1.6713625 , 2.5660043 , 2.1781194 , 2.953856  ,
       3.119504  , 1.4483763 , 2.4864748 , 2.3572588 , 3.3394969 ,
       2.1877475 , 6.0967245 , 2.4929302 , 2.0947428 , 1.2877308 ,
       4.3107033 , 1.6355093 , 1.3812943 , 1.2504737 , 2.6160507 ,
       1.6430557 , 1.8085628 , 3.0675159 , 3.2975116 , 1.952509  ,
       1.5373021 , 4.39409   , 1.8359364 , 0.7504137 , 1.7665155 ,
       1.3706672 , 1.8152281 , 1.5998641 , 4.01535   , 1.8521675 ,
       3.1666338 , 0.9752172 , 1.3413637 , 1.1906213 , 3.4213102 ,
       2.520538  , 1.0144736 , 3.795493  , 1.8451649 , 2.0326478 ,
       2.048199  , 1.2446934 , 0.9734584 , 0.7280725 , 1.5574683 ,
       2.6824155 , 3.9501724 , 1.32812   , 1.2033317 , 2.1361318 ,
       4.2866735 , 3.8808348 , 2.3595104 , 0.8766816 , 1.427103  ,
       2.7668664 , 1.3429713 , 1.2038133 , 2.349691  , 1.1733238 ,
       1.7915696 , 2.3217006 , 2.8994882 , 2.6147673 , 1.5185384 ,
       1.4466493 , 2.6687505 , 3.2477298 , 2.8617167 , 2.2211552 ,
       1.1188217 , 5.141412  , 4.732524  , 1.2114631 , 4.9655147 ,
       2.5166523 , 2.499689  , 2.6091611 , 2.3301413 , 2.5946336 ,
       3.6365206 , 1.5346526 , 2.4185524 , 4.561431  , 2.8851671 ,
       3.3771029 , 3.3333972 , 6.3210807 , 2.269982  , 0.89139926,
       3.2887282 , 1.4634677 , 2.0073526 , 1.3968499 , 3.215978  ,
       2.3631527 , 2.1425028 , 1.1489016 , 3.7361848 , 1.0249907 ,
       1.4029891 , 1.81072   , 2.2108538 , 1.7554069 , 2.6904023 ,
       1.2004191 , 1.618629  , 1.8234761 , 1.6743479 , 2.7876675 ,
       3.2369747 , 2.7461696 , 3.3396373 , 2.8592134 , 1.017385  ,
       6.5201826 , 3.6552553 , 2.4184053 , 3.7380195 , 2.149432  ,
       1.5233037 , 1.721549  , 1.7716388 ], dtype=float32), array([[[[ 0.00191147],
         [-0.00337947],
         [-0.02283554],
         ...,
         [ 0.00211505],
         [-0.01775197],
         [ 0.00808066]],

        [[ 0.01865197],
         [ 0.00167158],
         [ 0.00432131],
         ...,
         [-0.01091264],
         [-0.03801456],
         [ 0.03782463]],

        [[ 0.01649512],
         [ 0.01938974],
         [-0.00015249],
         ...,
         [-0.00513291],
         [-0.02050464],
         [ 0.01961208]]],


       [[[-0.02813994],
         [-0.00865073],
         [-0.02617188],
         ...,
         [ 0.00553214],
         [-0.03942738],
         [ 0.04104214]],

        [[-0.00031456],
         [ 0.01030622],
         [ 0.0203555 ],
         ...,
         [-0.00606372],
         [ 0.00765204],
         [ 0.04501904]],

        [[-0.00858243],
         [ 0.02322269],
         [-0.00307515],
         ...,
         [ 0.0078194 ],
         [ 0.01381961],
         [ 0.00280319]]],


       [[[-0.00716874],
         [ 0.01469211],
         [ 0.00303205],
         ...,
         [-0.0078516 ],
         [ 0.0059261 ],
         [ 0.03406842]],

        [[ 0.01734586],
         [ 0.03981148],
         [-0.01404499],
         ...,
         [-0.00298108],
         [-0.01075274],
         [-0.00102006]],

        [[-0.033833  ],
         [ 0.02104132],
         [-0.016979  ],
         ...,
         [-0.01719185],
         [-0.04101286],
         [ 0.00084486]]]], dtype=float32), array([[[[-0.03574212, -0.03076041,  0.02504615, ...,  0.03653695,
          -0.04004629, -0.02874438],
         [ 0.01242035,  0.06604528,  0.00770264, ...,  0.01183989,
           0.03121096, -0.00606966],
         [ 0.04982934, -0.01342356,  0.0110082 , ...,  0.03460389,
           0.05501568, -0.0181989 ],
         ...,
         [-0.00728622, -0.06105953, -0.03582512, ..., -0.01637562,
          -0.02172961, -0.00042712],
         [-0.04866564,  0.03302221, -0.03258756, ..., -0.02412077,
          -0.01304631,  0.01910383],
         [-0.01755461, -0.01965874, -0.02332359, ...,  0.04882821,
          -0.00264653, -0.00139918]]]], dtype=float32), array([0.9951904 , 0.9871846 , 1.0212692 , 1.0025876 , 1.0029992 ,
       1.007867  , 1.0011939 , 1.0040853 , 1.01022   , 0.99334395,
       1.0089802 , 1.0014212 , 1.0007231 , 1.001047  , 0.9956012 ,
       0.9798411 , 1.0009093 , 0.99500674, 0.99695057, 0.9930335 ,
       0.9932702 , 0.9827385 , 0.9998505 , 0.9929224 , 0.9924874 ,
       1.0092195 , 0.9968323 , 0.98706377, 1.0023656 , 1.009268  ,
       1.0229471 , 0.99868244, 1.018471  , 0.99332494, 0.98439115,
       0.9898346 , 1.0075808 , 0.98596776, 1.0074943 , 1.0167893 ,
       0.9996076 , 1.0012455 , 0.9987123 , 1.007738  , 0.99352336,
       0.9729588 , 0.99339795, 0.9926363 , 0.99568236, 0.9798908 ,
       0.99679434, 0.9932648 , 0.9963888 , 1.0041227 , 1.0018387 ,
       1.0047874 , 0.9919649 , 0.98998463, 1.0097547 , 0.9920551 ,
       0.99403614, 1.0180433 , 1.0068557 , 0.9928629 , 1.0081472 ,
       1.0138847 , 0.99510765, 1.0145198 , 0.9951691 , 0.9983979 ,
       0.99918044, 0.9984746 , 1.0157013 , 1.004401  , 1.0149336 ,
       0.9983823 , 1.0030255 , 0.9905432 , 1.0172471 , 0.9996453 ,
       1.0300595 , 1.0117997 , 1.0033845 , 0.99418426, 1.0011201 ,
       1.0040239 , 0.9888731 , 1.0080909 , 0.98933494, 0.9936537 ,
       0.9934296 , 1.0038359 , 0.99199414, 0.98801845, 1.0090224 ,
       0.9951064 , 0.99519545, 0.9997038 , 0.99799305, 1.0145317 ,
       1.014411  , 1.0028548 , 1.0127901 , 1.0196178 , 0.99081033,
       1.0256691 , 0.9894968 , 1.0103352 , 0.97884995, 1.0020851 ,
       1.0067593 , 0.9943515 , 1.0048785 , 0.99939376, 0.9926552 ,
       1.0201793 , 1.0357276 , 1.0103312 , 0.990412  , 1.0037472 ,
       0.99821687, 1.0018635 , 1.0085118 , 0.99511635, 1.0037304 ,
       1.0028282 , 0.9920203 , 0.99568576, 1.0066745 , 0.99524504,
       0.99599767, 0.99435425, 0.9966293 , 1.0186348 , 0.9996095 ,
       0.9982948 , 0.99275506, 0.9964992 , 0.9914202 , 1.0152833 ,
       0.99620986, 0.9967022 , 0.9763552 , 0.99466515, 1.029431  ,
       0.99165046, 1.0048785 , 0.98565495, 0.999182  , 1.023383  ,
       0.9928192 , 1.0008203 , 0.9948762 , 0.9805763 , 0.987973  ,
       1.0000055 , 0.9892898 , 1.0223911 , 0.99657196, 1.0107582 ,
       0.9897499 , 0.9991691 , 0.9916084 , 0.9862142 , 0.9971818 ,
       0.992652  , 0.9996067 , 0.99984175, 0.99882025, 0.9938633 ,
       0.99566025, 0.991553  , 1.0007079 , 0.99521446, 1.0018042 ,
       1.0246004 , 1.0276011 , 1.0003035 , 1.0090313 , 1.0053321 ,
       1.0258708 , 0.9985567 , 0.99453264, 1.0016644 , 1.0127999 ,
       0.99655855, 0.99428064, 0.9912645 , 0.9808384 , 0.9982464 ,
       1.0006753 , 0.99036217, 0.9855725 , 0.99407744, 1.0011141 ,
       0.9884235 , 1.0215281 , 1.0139538 , 1.0090917 , 1.0007912 ,
       0.99742156, 1.0128781 , 0.9766032 , 1.0170972 , 0.99945337,
       1.003602  , 0.9980293 , 1.0036311 , 0.99293226, 0.9961278 ,
       1.0233766 , 0.9883041 , 1.0007327 , 0.99456346, 1.0034306 ,
       1.011156  , 0.99721605, 0.9925788 , 1.0175108 , 0.9983934 ,
       0.99352247, 0.99313784, 1.00018   , 1.0006471 , 0.98898476,
       1.0132117 , 0.99977106, 1.0159031 , 0.99956375, 1.0112575 ,
       1.0037969 , 0.9908322 , 1.0048544 , 1.0106343 , 0.9960902 ,
       1.0041411 , 0.9874963 , 0.9971262 , 0.99853265, 1.001077  ,
       0.99193895, 1.0063438 , 0.9921031 , 1.0022837 , 1.0072315 ,
       0.9963068 , 1.0133059 , 1.0026734 , 0.9915038 , 1.0110961 ,
       0.99906653, 0.9993971 , 0.99540323, 0.99689186, 1.0034084 ,
       0.99218667, 1.0236229 , 1.0090784 , 1.0022609 , 0.99107575,
       1.008906  , 0.9946283 , 1.0049998 , 0.9909683 , 1.0305485 ,
       0.99479747, 0.99444145, 0.99681765, 1.0020989 , 1.0035281 ,
       1.0020062 , 1.011599  , 0.9948303 , 0.99941325, 0.9974194 ,
       0.9993858 , 0.9971469 , 0.99379355, 1.0143135 , 0.99886006,
       0.99164927, 0.9908385 , 0.9864852 , 0.9998957 , 1.0004569 ,
       1.0001469 , 1.0083382 , 1.0087433 , 0.99104184, 0.9976633 ,
       0.9980493 , 0.9918531 , 0.9847331 , 0.9904957 , 1.007147  ,
       0.9910031 , 0.99240655, 1.0007169 , 1.0136521 , 0.98666453,
       0.99965864, 0.9988927 , 1.0039328 , 1.0112196 , 1.0087441 ,
       0.99645966, 0.99481434, 0.9943598 , 0.9973515 , 0.9990702 ,
       1.0104765 , 1.0000435 , 1.0060328 , 0.9974395 , 1.0166848 ,
       0.9948755 , 0.99445933, 0.9959024 , 1.0014335 , 0.99322164,
       1.0027757 , 1.0000951 , 0.99991894, 0.9835412 , 1.0134908 ,
       0.99134606, 1.0076222 , 1.0010328 , 0.99573654, 1.0066288 ,
       0.99819833, 1.0099832 , 0.99598503, 1.0033511 , 1.0001756 ,
       0.9980998 , 1.0013816 , 0.99947256, 0.9987454 , 0.9922034 ,
       1.0023464 , 1.0088865 , 0.99347043, 1.0006564 , 1.0071443 ,
       0.99305665, 0.995709  , 1.005029  , 0.99186563, 1.013018  ,
       0.9975651 , 0.9986689 , 0.9974136 , 0.9982042 , 1.0057557 ,
       1.0147378 , 0.9956069 , 0.9960261 , 0.99353856, 0.9990025 ,
       1.0072005 , 1.0014969 , 1.0060118 , 0.98895663, 0.9996364 ,
       0.99518204, 0.9851769 , 1.0158243 , 0.9943294 , 0.9858927 ,
       0.9908588 , 0.9906314 , 0.99399006, 0.99574125, 0.99886066,
       0.9996833 , 0.99365705, 0.998479  , 1.0381669 , 1.0015962 ,
       0.9857815 , 0.99982625, 1.0074675 , 0.9955456 , 0.9942039 ,
       0.99844974, 1.0029638 , 0.9794303 , 0.9990179 , 0.990144  ,
       0.9933603 , 0.99177974, 1.0203949 , 1.0005504 , 1.0240533 ,
       0.98837686, 1.0062376 , 0.99358493, 0.985542  , 1.0058146 ,
       1.0029556 , 0.98673207, 1.000288  , 1.0082507 , 0.9960139 ,
       0.9983168 , 0.9955289 , 0.9965447 , 0.98059094, 0.98787755,
       1.0159756 , 1.0001651 , 0.9977059 , 0.9839874 , 1.008137  ,
       1.0127395 , 0.991661  , 1.0088686 , 0.9830352 , 0.99152875,
       0.9983314 , 0.99249303, 0.9918731 , 1.0174415 , 1.0043148 ,
       0.9885508 , 0.9868889 , 1.0000304 , 0.98928946, 1.0006856 ,
       0.9923859 , 1.0004734 , 0.9995896 , 0.98117673, 0.9911065 ,
       1.0114473 , 1.0023093 , 1.0054656 , 1.0076767 , 0.9969691 ,
       1.0075852 , 1.0039496 , 1.0091932 , 0.9935168 , 0.9943668 ,
       0.9954539 , 1.0023878 , 0.9960659 , 1.0177748 , 1.0063078 ,
       1.0147501 , 0.99098605, 1.0000697 , 1.002755  , 0.97831815,
       1.0055234 , 0.99564886, 0.99311996, 0.984378  , 1.0051025 ,
       0.9992554 , 1.0032718 , 0.9945302 , 1.0015576 , 0.9844505 ,
       0.9951332 , 1.0007179 , 1.0024192 , 1.0044974 , 1.0072691 ,
       1.0006465 , 1.0271918 , 0.9971965 , 0.99141014, 1.0102333 ,
       1.0101897 , 0.98755294, 0.991291  , 1.0174001 , 0.99885297,
       1.0173048 , 1.0080975 , 1.0003994 , 0.9942829 , 1.0005076 ,
       0.98515224, 1.0100031 , 0.9895524 , 0.9915362 , 0.9851208 ,
       0.98988146, 1.021099  , 1.0266932 , 1.0048369 , 0.9931808 ,
       0.99052393, 1.0016001 , 1.0176103 , 0.9963355 , 0.9956403 ,
       1.0002608 , 1.0111005 , 1.0117291 , 0.9962176 , 0.98845255,
       1.0060238 , 1.0052562 , 1.0000558 , 1.0124922 , 0.9969942 ,
       0.9986412 , 1.001536  , 0.99501693, 0.9974877 , 1.0109031 ,
       1.0092801 , 0.98662746, 1.0031083 , 1.0003766 , 0.99582237,
       0.9942398 , 1.0097498 , 0.9940639 , 1.0125958 , 0.9973747 ,
       0.9958721 , 1.0260812 , 1.007693  , 1.0342149 , 1.0012907 ,
       0.99682   , 1.0037997 , 0.98791295, 0.9898563 , 0.9898541 ,
       1.0096871 , 1.009432  , 1.0241725 , 0.9956787 , 1.0014089 ,
       0.99289733, 1.0072834 , 0.997797  , 1.0062671 , 0.99112475,
       1.0121216 , 0.99622095, 0.98728937, 0.9979792 , 1.0005853 ,
       0.99914664, 0.98601604, 1.0023857 , 0.9935309 , 0.99715483,
       0.9978644 , 0.9953178 , 1.0028974 , 0.9873585 , 0.9986253 ,
       1.0122448 , 0.99019396, 1.0037884 , 1.0157262 , 0.9968691 ,
       0.9932769 , 0.99497783, 0.99508476, 1.0004207 , 0.9883822 ,
       0.9943831 , 0.98737127, 0.997287  , 0.9866602 , 1.005722  ,
       0.9740889 , 0.9858646 , 0.98407394, 0.99021447, 0.995395  ,
       0.9988067 , 1.0062764 , 1.0172865 , 0.99750274, 0.99920684,
       0.98880893, 1.0189023 , 0.9984657 , 0.998252  , 0.9975773 ,
       0.993275  , 1.0002956 , 1.0101414 , 1.0055524 , 1.0149618 ,
       1.0018241 , 1.0159336 , 0.99233156, 0.9896603 , 0.9984696 ,
       0.9938705 , 1.0150702 , 0.994276  , 0.98109293, 0.9931516 ,
       0.98280156, 1.0023339 , 0.9964665 , 1.0066348 , 1.0042614 ,
       0.9839893 , 1.0214306 , 0.99366385, 0.99460846, 0.9920741 ,
       0.99173105, 0.9947551 , 0.97993565, 0.98884714, 0.9974273 ,
       1.0155208 , 1.0013952 , 0.9948824 , 0.9869245 , 1.0045848 ,
       0.98840725, 1.009578  , 0.9916444 , 1.0088379 , 1.0093952 ,
       1.0047799 , 1.0069989 , 1.026509  , 1.0002743 , 0.9999713 ,
       0.9915405 , 0.9859185 , 0.99716264, 1.0156765 , 0.97865963,
       1.0025841 , 1.0049016 , 0.99927413, 1.0018287 , 0.99131346,
       0.9986054 , 0.9930686 , 1.0000701 , 0.99441135, 0.9910001 ,
       1.0037596 , 0.97760934, 0.98636   , 0.99963593, 1.0096815 ,
       0.9972615 , 0.99504274, 0.98896503, 0.99678016, 1.0170696 ,
       1.0109233 , 0.9887305 , 0.993808  , 0.9952503 , 0.99203193,
       1.0046289 , 0.99812293, 1.0030195 , 0.9836801 , 1.0039389 ,
       1.0037088 , 0.99280274, 1.0105678 , 1.0101695 , 0.99451196,
       0.9960538 , 0.9887241 , 0.9950233 , 1.0222057 , 1.0150024 ,
       0.99556977, 1.0044382 , 0.9877933 , 0.99819696, 0.9864343 ,
       0.9884638 , 0.99311167, 0.9943841 , 0.99501306, 0.99426407,
       0.99559665, 0.99160916, 0.9980729 , 1.0214095 , 0.9810781 ,
       1.0073605 , 1.024155  , 0.98650366, 1.0029383 , 1.0070764 ,
       0.997892  , 0.9935626 , 1.0105866 , 0.9952475 , 0.9947409 ,
       1.0131761 , 0.99955875, 0.9917938 , 1.004521  , 0.99706143,
       0.99527806, 1.0008278 , 0.99733293, 0.9972175 , 0.9980127 ,
       0.99003583, 1.0006675 , 1.0115973 , 1.0010773 , 1.0282103 ,
       0.9956722 , 1.0047156 , 1.0001521 , 0.99106735, 1.004576  ,
       0.9991369 , 0.99826205, 0.99505246], dtype=float32), array([-9.90069564e-03, -3.30409557e-02,  1.95977297e-02, -2.25003269e-02,
        3.82589689e-03, -1.50727546e-02,  1.01709384e-02,  9.71525721e-03,
       -3.15572023e-02, -2.68222243e-02, -1.76994242e-02,  6.68526627e-03,
       -1.35815833e-02,  5.83702466e-03,  1.95221766e-03, -1.88069902e-02,
       -8.94423854e-03,  2.16359254e-02,  2.34958008e-02, -5.03695849e-03,
       -3.20054498e-03, -1.19134663e-02,  2.31019948e-02, -2.55426299e-02,
       -2.15362925e-02, -1.41119557e-02, -4.46678372e-03,  2.68728100e-03,
        7.58542854e-04, -2.48117894e-02,  4.90591377e-02, -3.91217973e-03,
       -5.78312110e-03, -2.23380979e-02,  2.35876651e-03, -5.93126146e-03,
       -3.32569331e-03, -4.22991533e-03, -4.21467517e-03, -1.44879390e-02,
       -7.55548431e-03,  3.40328697e-05,  9.67093650e-03, -1.32969776e-02,
        7.23889191e-03, -2.72965226e-02, -2.38100737e-02, -5.67094889e-03,
        9.37361387e-04, -2.54722238e-02, -1.63902193e-02, -7.14408653e-03,
       -3.54276225e-03,  1.57836061e-02, -7.85916112e-03,  2.41347980e-02,
        2.74834177e-03,  2.97598937e-03,  1.12120453e-02, -5.04511828e-03,
        2.14340934e-03,  2.19822619e-02, -4.85267304e-03, -2.43696128e-03,
        2.40040757e-02, -4.40314524e-02, -1.43267466e-02, -4.83283773e-02,
       -7.84443412e-03, -3.31913773e-03, -1.06749358e-02, -6.92983950e-03,
        8.63017142e-03, -7.82161020e-03,  4.50054556e-02, -3.48464660e-02,
        1.53817777e-02, -1.08311912e-02,  3.11719277e-03, -1.49952238e-02,
        1.58938824e-03, -4.84634452e-02,  3.09520233e-02,  9.66149266e-04,
       -1.15358233e-02, -1.24579770e-02, -2.02626865e-02, -1.41482521e-02,
       -8.47085193e-03,  5.78052178e-03, -6.14015013e-03, -9.17290617e-03,
        1.64763872e-02,  1.37012340e-02,  1.26155773e-02, -2.29890198e-02,
       -1.97657794e-02,  3.09137697e-03,  1.43440801e-03,  1.61348619e-02,
        2.54012309e-02,  1.30034899e-02,  3.25482413e-02, -2.63586757e-03,
       -2.41165217e-02,  2.15887930e-02, -1.12506496e-02, -2.43702978e-02,
       -2.49464810e-02, -1.44509627e-02,  5.56317996e-03, -3.23489984e-03,
        1.88420806e-03,  1.25500597e-02, -3.93202156e-03,  9.99720115e-03,
        4.60591391e-02, -7.96238706e-03, -8.89726728e-03,  3.87099129e-03,
        2.54682545e-02, -1.54204865e-03,  1.75523497e-02, -7.81294052e-03,
        3.04463301e-02, -1.19048473e-03,  9.96677438e-04, -1.06858313e-02,
       -5.67018148e-03, -7.99390953e-03, -1.06003052e-02,  4.62249015e-03,
       -1.35208210e-02, -2.70134360e-02, -1.48533925e-03,  1.11954976e-02,
       -7.48320529e-03,  2.25746515e-03, -2.76184361e-03,  4.81294328e-03,
       -9.66261048e-03,  3.45227076e-03, -1.08612217e-02, -4.00620513e-03,
        2.61576045e-02,  1.17944442e-02, -3.58009507e-04, -1.63182802e-02,
        8.33554426e-04, -3.55149410e-03, -3.81590868e-03,  6.15409529e-03,
        1.18681882e-02,  2.32509524e-03, -1.52017456e-02, -4.73932642e-03,
        6.79729879e-03,  2.08370970e-03, -1.23867567e-03, -1.47791905e-02,
        5.74237434e-03, -2.63439827e-02, -2.55498150e-03, -2.25305799e-02,
       -1.79630332e-02, -1.96774788e-02, -4.84657678e-04, -4.34763497e-03,
        2.55331909e-03, -1.80042107e-02,  8.92540847e-05, -4.16735467e-03,
       -1.16938353e-02,  4.40782448e-03,  6.92302827e-03, -9.24892817e-03,
       -1.18316365e-02, -1.96930580e-02, -2.05368102e-02,  1.37437768e-02,
        3.66749795e-04, -1.00882417e-02,  4.60111629e-03,  2.92198412e-04,
        8.03048443e-03, -6.69495808e-03, -1.37854125e-02,  5.45003265e-03,
       -2.04685777e-02,  1.94003689e-04,  2.07045563e-02,  1.06828101e-03,
       -1.16383182e-02, -4.27876040e-03,  1.39300926e-02, -8.91611446e-03,
        4.35437745e-04, -8.83434620e-03, -1.78404134e-02,  5.85132511e-03,
        1.27723510e-03,  2.21696291e-02, -9.64704063e-03, -2.97042285e-03,
        9.07960068e-03,  7.65628926e-03,  1.13154696e-02, -7.08662346e-03,
       -1.65215526e-02, -1.59286708e-02, -2.30016299e-02, -2.68862024e-02,
       -4.60342853e-04, -1.36507850e-03,  8.85103829e-03,  3.05790780e-03,
        3.10652284e-03,  9.75232571e-03,  3.86397205e-02, -7.25537585e-03,
        4.36192099e-03, -2.52030161e-03, -1.85866561e-02,  9.83090699e-03,
       -1.05449529e-02, -3.71175422e-03,  5.78743359e-03,  1.76082514e-02,
        4.99966613e-04,  1.39365662e-02, -9.01211053e-03,  1.77630596e-03,
       -1.99702531e-02,  5.68029191e-03,  6.18661335e-03, -1.77198220e-02,
       -1.48817645e-02, -3.61153064e-03,  8.28655716e-03, -9.74495139e-04,
        9.23594274e-03,  3.83219239e-03,  7.71166338e-03,  8.07351246e-03,
        5.79734892e-03, -7.71654164e-03,  5.54308388e-03,  9.88072995e-03,
       -6.42880844e-03,  1.76428221e-02, -1.80644058e-02,  1.23353209e-04,
       -6.13606162e-03,  2.45449739e-03, -4.27008793e-03, -9.76127479e-03,
       -2.76978081e-03,  5.18406788e-03,  1.01078916e-02,  3.55960219e-03,
       -3.06292474e-02,  1.07939299e-02, -3.64944991e-03, -3.05272359e-02,
       -3.75003205e-03, -7.66438199e-03, -8.83574504e-03, -2.47255573e-03,
       -2.10926402e-03,  1.37130124e-03,  5.57179330e-03,  7.45193684e-04,
       -2.22668820e-03, -7.88559299e-03, -2.56057410e-03, -2.30328576e-03,
       -4.76557855e-03, -1.64772328e-02,  3.36728012e-03, -4.81724851e-02,
       -1.85765349e-03, -1.10113649e-02, -4.49312571e-03,  5.83144370e-04,
       -8.80945940e-03, -4.99620568e-03,  6.86666812e-04,  8.60498985e-04,
       -1.37944787e-03, -8.73443391e-03, -3.91572830e-04, -2.98561226e-03,
       -1.43837612e-02, -4.74292645e-03, -3.93537711e-03, -9.61114187e-03,
       -1.46493120e-02,  3.65816802e-03, -9.43010207e-04, -2.10076347e-02,
       -2.37806514e-02, -1.38433250e-02, -7.21129170e-03,  7.92060234e-03,
        7.93655217e-03, -4.85456688e-03,  8.11103557e-04, -4.34544496e-03,
        1.48003921e-03, -6.99619390e-03,  6.11772295e-03, -2.35733502e-02,
       -4.40684371e-02, -3.09389434e-03,  1.46072526e-02, -2.61265365e-03,
       -1.10926805e-02,  6.71220478e-04, -9.89470258e-03,  4.35423851e-03,
        8.48412793e-03,  1.57376360e-02,  9.11548268e-04, -1.45386094e-02,
        2.27820799e-02, -6.19814126e-03, -2.72458550e-02, -2.38200705e-02,
        1.21589880e-02, -1.31533379e-02,  4.19837842e-03, -8.13460851e-04,
       -1.49843714e-03, -1.88045204e-02, -1.46174878e-02,  8.62331502e-03,
        3.19020706e-03,  1.39024090e-02, -5.77090494e-03, -3.01977107e-03,
        2.81542204e-02,  2.64457837e-02, -1.38165541e-02, -1.37781138e-02,
       -2.86827460e-02, -8.62120837e-03, -1.21869547e-02, -2.71931458e-02,
       -2.12642481e-03, -1.19165666e-02, -1.55473417e-02, -3.55158816e-03,
        1.94677152e-02, -9.01116244e-03, -2.02998072e-02, -4.15470637e-02,
        8.37202388e-05, -2.36622617e-03, -5.37302764e-03, -2.74133682e-03,
       -1.10911680e-02,  6.15317002e-03, -9.47915483e-03, -1.13728698e-02,
       -4.17593587e-03, -1.58835866e-03, -9.48123913e-03, -1.50446398e-02,
       -3.48493792e-02, -4.78238193e-03, -1.40973330e-02, -1.04264095e-02,
       -1.14439186e-02,  4.03217884e-04,  2.75343657e-03, -1.96211250e-03,
       -3.74089624e-03, -1.52189443e-02, -1.50869647e-03,  3.58161144e-03,
       -6.19494915e-03, -4.58028028e-03, -1.88273266e-02, -8.93262774e-03,
       -6.11301698e-03, -7.68211437e-03, -4.65716730e-04, -2.64205039e-02,
       -3.93757643e-03, -1.21832080e-02,  6.75555365e-03, -2.76998617e-02,
        1.23394495e-02,  1.09878033e-02,  1.70964412e-02,  2.31328909e-03,
        5.92371868e-03,  4.58795065e-03, -4.68437443e-04,  8.93060677e-03,
       -3.40151787e-03, -1.39716966e-02, -1.94990430e-02,  1.82801206e-02,
        2.39448231e-02, -9.08264611e-03,  5.15230885e-03,  7.45844911e-04,
       -3.72920011e-04,  4.67647240e-03, -4.01232042e-04, -1.41578456e-02,
       -9.16440692e-03, -2.78295763e-02, -6.87983818e-04, -1.83657724e-02,
       -1.01012448e-02,  1.38828307e-02, -2.04775222e-02, -1.30555416e-02,
       -1.13550900e-02, -6.01339480e-03,  8.59206356e-03,  4.28199116e-03,
       -2.52325088e-02, -7.43422611e-03, -3.39358971e-02,  4.56253998e-03,
       -6.54425006e-03,  4.70142858e-03, -1.13859735e-02, -2.92245904e-03,
       -1.11821685e-02, -1.30128181e-02, -6.43055700e-03,  1.25951124e-02,
        2.38172570e-03, -1.98196042e-02, -3.22663039e-02,  5.93661971e-04,
       -9.84846521e-03, -1.68647815e-03, -1.87607873e-02, -5.60256839e-03,
        4.69555816e-04, -7.88024813e-03, -1.28030060e-02,  4.30956512e-04,
        1.54496180e-02,  6.91869855e-03, -1.09897228e-05, -1.03398841e-02,
       -3.41822915e-02,  6.91306964e-03, -1.83203444e-02, -1.19088581e-02,
       -3.75089562e-03, -2.35754363e-02, -1.62991490e-02, -5.99633390e-03,
       -3.17746773e-02, -2.12765224e-02, -5.35747083e-03,  1.96356196e-02,
       -3.40558179e-02, -1.13433339e-02, -2.40342133e-03, -2.92553063e-02,
        1.67792942e-02,  1.30320536e-02,  1.02658514e-02,  8.28545727e-03,
       -4.91445558e-03,  3.07801820e-05, -3.45502310e-02,  5.97048886e-02,
       -2.68102391e-03, -2.00392865e-03,  2.25989893e-02, -1.02658095e-02,
       -2.65364014e-02, -2.47981865e-02, -4.36462928e-03, -1.12096621e-02,
        3.26318573e-03, -8.54677148e-03,  1.10217901e-02, -1.01007707e-02,
       -9.87802539e-03, -1.64097045e-02, -3.61165730e-04,  8.98039714e-03,
        1.60088595e-02, -2.04653814e-02,  1.49930278e-02, -7.22599169e-03,
       -4.05503213e-02,  1.90269835e-02, -3.30950529e-03, -1.89439990e-02,
        2.67733261e-03,  1.62539445e-02,  2.65817661e-02,  7.98225868e-03,
       -1.00447051e-02,  7.19925202e-03,  6.86097518e-03, -1.00042094e-02,
        3.17742670e-04, -6.25488348e-04,  6.52426807e-03, -2.06893776e-02,
       -1.62791647e-03, -3.07642110e-02, -7.24918628e-03,  1.54464133e-02,
       -3.14156082e-03, -4.29336214e-03,  4.23237309e-03, -2.90732505e-03,
       -1.35957813e-02, -3.02680433e-02, -6.16665324e-03,  1.91482734e-02,
        4.46921168e-03, -1.05438074e-02,  2.13872623e-02,  2.86526186e-03,
        4.48940508e-02, -1.40668801e-03, -4.74112667e-03, -2.56892852e-02,
       -9.57018789e-03, -4.39183926e-03, -7.62323057e-03, -1.57451034e-02,
       -6.55805925e-03, -1.64101478e-02, -8.58974177e-03, -6.10691402e-03,
       -1.32426918e-02, -1.52402706e-02,  1.66382780e-03, -2.81376056e-02,
       -5.45580266e-03, -2.10860409e-02, -3.49071063e-03, -1.23638837e-02,
       -6.72405120e-03,  1.61643419e-03,  3.02422722e-03, -1.01886585e-03,
        7.43317930e-03,  5.95205580e-04,  4.57514497e-03, -2.30289120e-02,
        2.50070207e-02, -8.15764442e-03, -1.90820079e-02,  7.03146402e-03,
        4.62999148e-03, -4.25668946e-03, -1.40167484e-02,  1.28721511e-02,
        4.73274849e-03, -2.77458597e-02, -2.88461894e-03, -4.77116322e-03,
        1.63543224e-02,  5.54502197e-03, -1.81410778e-02,  1.11341919e-03,
       -2.32730657e-02, -1.99854956e-03,  1.17828567e-02, -1.83266159e-02,
       -2.04530433e-02, -2.64724214e-02, -9.32169426e-03, -4.59820079e-03,
       -1.34356106e-02,  6.20649010e-03, -2.61535738e-02,  1.12080446e-03,
        9.26867314e-03, -1.54353399e-02, -2.13368591e-02, -1.70065667e-02,
        6.29623141e-03, -1.35819120e-02, -3.51130357e-03, -2.29043271e-02,
        1.25892484e-03, -7.20188778e-04,  3.63295414e-02, -3.64080304e-03,
        1.41251590e-02,  1.22788164e-03, -1.12673389e-02, -2.01597996e-03,
       -5.41556021e-03, -9.18751024e-03, -5.46555128e-03, -1.85969640e-02,
       -7.54438480e-03, -5.91553235e-03,  4.08094749e-03, -2.64993943e-02,
       -2.29394473e-02,  1.85823347e-02, -8.11103266e-03,  5.28657623e-02,
        1.45625952e-03, -1.40963076e-02, -5.64687513e-03, -1.46014383e-03,
       -1.13965198e-03,  1.79587980e-03, -7.36319507e-03, -1.42880082e-02,
        1.53380330e-04, -6.65644417e-03,  6.88430341e-03, -3.75297889e-02,
       -6.29962422e-04, -2.84565669e-02, -2.87011303e-02, -6.80035446e-03,
       -3.96137778e-03, -1.43095693e-02, -1.68835763e-02, -6.09714538e-03,
        1.09420950e-02, -2.70961598e-03, -1.31174701e-03, -3.97293177e-03,
       -1.59733593e-02, -1.67575553e-02,  5.15905768e-03, -1.56130828e-02,
        7.84497708e-03, -6.15380192e-03, -8.60717148e-03, -3.73163819e-02,
        1.44917937e-02,  7.24635413e-03, -1.31816082e-02,  7.35709723e-03,
       -6.54188404e-03, -6.62477827e-03,  2.95827109e-02,  1.30686129e-03,
       -2.03169021e-03, -5.30320592e-03,  6.68684347e-03,  2.23916247e-02,
        2.49789609e-03, -1.32292397e-02, -4.38649394e-03,  2.54429840e-02,
       -3.98633210e-03,  1.78454933e-03, -5.01259305e-02,  6.53275196e-03,
       -1.88012421e-02,  3.05076828e-03,  1.72030972e-03,  5.49345510e-03,
        3.56999808e-03, -1.53834606e-02, -1.99190415e-02, -8.11873470e-03,
       -2.78046709e-02, -1.12489320e-03,  3.84799496e-04,  9.33991047e-04,
       -1.08987121e-02, -1.91941415e-03, -3.23083289e-02,  1.90939922e-02,
       -1.35887126e-02, -4.09617126e-02, -1.26503818e-02,  1.25594400e-02,
       -2.28777304e-02, -1.25688165e-02, -1.25837931e-02, -4.86804266e-03,
        1.46966975e-03, -1.79312713e-02,  2.64290581e-03,  1.17806136e-03,
        9.58030391e-03,  3.89767736e-02, -1.34889660e-02, -8.57058447e-03,
       -4.19952311e-02, -5.03783487e-03,  1.02676367e-02,  7.70835765e-03,
        5.13597624e-03,  3.40764527e-03, -2.56461687e-02,  2.01812611e-04,
       -2.64017214e-03,  1.59301069e-02, -3.83666530e-03, -4.91565559e-03,
        4.47424920e-03, -3.65108741e-03, -7.02161063e-03,  6.80263108e-03,
       -1.48340110e-02,  5.92422578e-03, -7.95536954e-03, -1.10099558e-02,
       -6.16436172e-03, -3.80120426e-02,  3.48909688e-03, -3.22138928e-02,
       -1.42811406e-02, -6.78597670e-03,  5.45731885e-03,  3.42726475e-03,
       -2.44151782e-02, -4.73391323e-04, -5.46758715e-03,  4.10497235e-03],
      dtype=float32), array([ 0.0630701 ,  0.13108437, -0.006476  ,  0.14897491,  0.05582343,
        0.09123454, -0.06914376, -0.05005245,  0.12523034,  0.14299355,
        0.07238849, -0.00486816,  0.03801802,  0.02240054, -0.11204758,
        0.05968692, -0.08308528, -0.06735545, -0.03245121,  0.03894293,
       -0.06530719, -0.03478581, -0.08900597,  0.11487593,  0.10201473,
        0.0012438 ,  0.11753568, -0.02995706,  0.01391278,  0.07213143,
       -0.08396209, -0.09670357,  0.03808392,  0.08156518, -0.05911756,
       -0.07919093,  0.07580307, -0.03026949,  0.08300766,  0.0830581 ,
        0.06999543,  0.03270934, -0.12444836,  0.04127053, -0.08420542,
       -0.02346371, -0.06704359, -0.12370832,  0.04811983,  0.04411905,
        0.01875487, -0.1005659 , -0.07487677, -0.05067496,  0.1051548 ,
       -0.01843947, -0.0982119 , -0.04303975,  0.03390703, -0.02667929,
       -0.12551071, -0.00207967,  0.0642473 , -0.031353  , -0.01504596,
        0.0885857 ,  0.07010556,  0.1294271 ,  0.12721954,  0.02553098,
       -0.03425312,  0.05817578,  0.02020268, -0.02295432, -0.0895556 ,
       -0.06458482, -0.11519237,  0.06003831,  0.08057298,  0.00333088,
        0.00678267,  0.18656757, -0.05597841,  0.04305713,  0.07438362,
        0.06672351,  0.08783532,  0.08528166,  0.07150789, -0.08174633,
       -0.08373298,  0.08046506, -0.12372386, -0.07843406,  0.01999587,
       -0.05387323,  0.0931806 , -0.12375989, -0.0193949 , -0.02382781,
       -0.04910921, -0.04261604, -0.11352132,  0.04929207,  0.09338156,
        0.09414447,  0.03881387,  0.12712373,  0.12777099,  0.14229499,
        0.06595933, -0.08069594,  0.05537638, -0.10724305,  0.03798263,
        0.08483995, -0.02292078,  0.11607689,  0.08835647,  0.11096332,
       -0.16546153,  0.08920274, -0.05821276,  0.14417396, -0.10839857,
       -0.01820418,  0.03747595,  0.09648577,  0.08517225, -0.01358672,
        0.1785591 , -0.0575255 ,  0.05752886,  0.19151036, -0.01719202,
       -0.02329183, -0.01199821, -0.09656206, -0.06352798, -0.02392982,
        0.03626329, -0.02215227, -0.09303223,  0.01183838,  0.02932343,
       -0.05567335,  0.03383519, -0.04766187, -0.08860064,  0.04541652,
       -0.02737434, -0.07621413,  0.00406288, -0.06463405,  0.09258895,
       -0.07260254, -0.06967791,  0.03369331,  0.00580745,  0.11444139,
        0.01539383,  0.04031081, -0.00188166,  0.14310548,  0.1593075 ,
        0.13993217,  0.04777681, -0.02332154, -0.08164203,  0.1566943 ,
       -0.0295346 ,  0.06517179,  0.07786179, -0.04245047, -0.0706482 ,
        0.05026511,  0.16355391,  0.10023799,  0.07511473, -0.13350657,
        0.10332371,  0.13294749,  0.07459357,  0.01071329, -0.00160793,
        0.09001841,  0.06594131, -0.00091166,  0.10781472, -0.08588561,
       -0.10389353, -0.05092147,  0.06981223, -0.09206714, -0.09068845,
       -0.04925789, -0.06713277,  0.11963519,  0.1681815 , -0.05783877,
        0.00772451,  0.02187921,  0.02110584,  0.07465161,  0.11418883,
       -0.01362835, -0.08987271,  0.07248885,  0.0869769 , -0.05674818,
        0.08622338,  0.1037456 , -0.06004333, -0.04904823, -0.00840787,
        0.12415873,  0.04058539, -0.11536851, -0.09926807,  0.03747877,
       -0.05754863, -0.05763735,  0.13355593, -0.04122566,  0.01570183,
        0.08196843,  0.04856239,  0.01123735,  0.02715936,  0.04206042,
        0.1462175 , -0.04317256,  0.09350164, -0.00640967,  0.00338803,
       -0.08345767,  0.00156199, -0.07056478, -0.09735226,  0.0662391 ,
       -0.00731351, -0.04190532, -0.01286176,  0.02260612,  0.02668405,
        0.1053428 ,  0.0692031 ,  0.0133573 ,  0.07258724, -0.04708869,
        0.07973821,  0.14231677, -0.06282001, -0.06065552,  0.00990892,
        0.11581066,  0.0622367 ,  0.10286281, -0.0457121 , -0.16735692,
        0.15884474, -0.06960908,  0.1083754 ,  0.0804783 ,  0.08289123,
       -0.03847867,  0.05388315, -0.11985946,  0.11979541,  0.03120953,
       -0.08750337,  0.02862875,  0.04207205,  0.03277526,  0.06339154,
       -0.00317798,  0.0245114 ,  0.0685857 ,  0.00813291,  0.12220731,
       -0.04195746, -0.02103592, -0.0849112 , -0.0064792 , -0.05154702,
       -0.06362688,  0.04624605,  0.10580382,  0.06786039,  0.00936301,
        0.00523722,  0.14934166,  0.05374648, -0.02055661,  0.06639068,
       -0.0342272 ,  0.0855476 , -0.07620416,  0.05066295, -0.07234453,
        0.14008613,  0.02896392,  0.08193039, -0.07342468, -0.00038161,
        0.0746109 , -0.00394266,  0.07480284,  0.01061782,  0.03665284,
        0.06786695,  0.09533982,  0.20810129, -0.01142795,  0.00951428,
        0.01930788, -0.01410774, -0.10505307,  0.11133809,  0.02024446,
       -0.0816363 , -0.05651921, -0.04070698, -0.06123184, -0.03089842,
        0.01662188,  0.18028861, -0.07770909, -0.07783404,  0.06962905,
       -0.15244702,  0.09905696,  0.11449832,  0.0798241 ,  0.0151143 ,
        0.04748902,  0.05091949,  0.06621917,  0.05476566,  0.0010504 ,
       -0.07662535, -0.0136764 , -0.09962329,  0.07366824,  0.09907532,
        0.01098229, -0.04207305,  0.13215055, -0.0542913 ,  0.03285357,
        0.18658148,  0.08299481,  0.06784226, -0.00261451,  0.10182798,
        0.20811002, -0.07967415, -0.08274175,  0.005221  , -0.11139508,
        0.13240516, -0.02432522,  0.11448513,  0.13384531,  0.10258542,
       -0.04831291, -0.0980044 ,  0.05715453,  0.18216537, -0.11566183,
        0.04794266, -0.04227834, -0.1298435 , -0.13568172, -0.01576215,
       -0.05732242, -0.06043486,  0.07548525,  0.01257806, -0.05118832,
        0.06665546,  0.06593512,  0.09115678, -0.01527954,  0.00803976,
        0.04244114,  0.02348295,  0.11218788, -0.03418874, -0.06765685,
        0.01498983,  0.14755389,  0.05039515, -0.04519275, -0.06012163,
       -0.0661373 , -0.1394083 , -0.09977552,  0.0192129 , -0.04480888,
       -0.0134538 , -0.02916894,  0.10858224, -0.1597123 , -0.01657645,
        0.14043015, -0.09028974,  0.11286409, -0.01742224, -0.00713646,
        0.03231592,  0.10585138,  0.08442157,  0.1561684 , -0.00062297,
        0.14199826, -0.10670678,  0.0386903 ,  0.06085316, -0.00126103,
       -0.0188899 , -0.02065091,  0.00492197, -0.01482722,  0.13914265,
        0.00699822,  0.12617464,  0.05622263, -0.09343618,  0.06886701,
       -0.04010581,  0.04104186,  0.07741517, -0.02187132,  0.0143957 ,
       -0.01851299,  0.03650488,  0.13367246,  0.16535985, -0.00649019,
        0.01199849, -0.14335541,  0.11970911, -0.06151467,  0.00551564,
        0.08856633,  0.08282022, -0.09754484, -0.01669572, -0.11859015,
        0.06234194,  0.02992102,  0.10458791,  0.00757828,  0.07050912,
        0.03429939,  0.01590129,  0.1520058 , -0.05126731, -0.02138727,
        0.2124306 ,  0.16665214, -0.02607016, -0.01758435,  0.14862946,
       -0.04471355,  0.01625843,  0.12194196, -0.09216965,  0.01957177,
       -0.00494477, -0.02186091,  0.13118453, -0.10285679,  0.15501751,
       -0.06677334, -0.10214501,  0.09707294,  0.02052889,  0.07016177,
        0.14851595,  0.07482812, -0.01987799,  0.019852  , -0.10497575,
       -0.01067507, -0.0567569 , -0.00818593,  0.09971529,  0.02483717,
       -0.08019127,  0.05641356,  0.02698375,  0.14924414, -0.07262351,
       -0.012216  ,  0.10893986, -0.00523349,  0.07975756,  0.1511529 ,
       -0.04843637, -0.04046179, -0.01582337,  0.03569401, -0.04250367,
       -0.12273259, -0.02378781,  0.09638661,  0.01536683, -0.02253333,
       -0.07391823,  0.07872008, -0.08305634,  0.09701783, -0.02272852,
        0.05616387, -0.09156993,  0.05492495,  0.04697051,  0.11432741,
        0.1418694 ,  0.12295382, -0.0815974 , -0.04879197, -0.03685945,
       -0.01527543, -0.06606152,  0.01462874, -0.06680746, -0.01149942,
        0.01277957, -0.0896953 , -0.00024425, -0.03726431,  0.05397104,
        0.16159897,  0.07836013,  0.03903857,  0.10751728,  0.07966854,
        0.10641185,  0.07795967, -0.01677335,  0.12210507, -0.04264265,
        0.0788107 ,  0.0496127 , -0.00299146,  0.15035562, -0.06959797,
       -0.05333349, -0.01840548,  0.06207168, -0.05173279,  0.00580431,
        0.11146256, -0.03997248,  0.05196286,  0.02012225, -0.04928975,
        0.14485016, -0.01912364,  0.14310384,  0.03355813,  0.08110157,
        0.11212762, -0.17252286,  0.051522  , -0.01060207, -0.10462312,
        0.07916546, -0.03395212,  0.12897728, -0.06224689,  0.02598766,
        0.00509466, -0.09549806,  0.03858424,  0.01214946, -0.0424897 ,
        0.01157205,  0.12692401,  0.12234899,  0.02330925,  0.00222749,
        0.09306372,  0.1366834 ,  0.1533274 , -0.01982288,  0.12838545,
        0.0594383 ,  0.10314192,  0.08039729,  0.0866259 , -0.04383398,
        0.0197271 ,  0.00759656,  0.01881054,  0.05847578,  0.0098643 ,
       -0.09933353,  0.13752909,  0.0130325 , -0.07725951,  0.071386  ,
        0.09771656, -0.11337137,  0.07061579,  0.12092828, -0.08594625,
       -0.06057339, -0.03161015, -0.05281814, -0.00024339, -0.05584606,
        0.08805836,  0.07945546, -0.01566737, -0.02545136,  0.06491761,
        0.07565014, -0.02795423, -0.08737858,  0.03385298, -0.02037596,
        0.06784133,  0.13849595,  0.01289638,  0.04468402,  0.15898491,
        0.10865913, -0.01762098, -0.00047969,  0.0559938 ,  0.11101077,
       -0.11181609,  0.0023335 ,  0.04760297,  0.12344933, -0.03002788,
       -0.04195243,  0.03946868, -0.01159611,  0.15580976, -0.0789788 ,
       -0.04695588, -0.07054886, -0.05144178,  0.09254647, -0.02545518,
       -0.11336954, -0.07676981,  0.00497898,  0.0949771 ,  0.03465794,
       -0.0385973 , -0.11026578,  0.01213326,  0.04904366, -0.02582027,
        0.0874805 , -0.06254861,  0.13076511, -0.081683  , -0.03175127,
       -0.04441869, -0.05379308,  0.04766648, -0.03381612,  0.13148808,
        0.09499579, -0.02344685,  0.19121477,  0.11349421, -0.07083564,
       -0.09412164, -0.01862027, -0.09917971,  0.14241453, -0.04176728,
        0.10365007,  0.18863891, -0.00807191, -0.09893271,  0.13306385,
       -0.11375628,  0.11468328,  0.09885719, -0.02320595,  0.08807383,
       -0.04549048, -0.09111479, -0.05509892, -0.10572753, -0.03903887,
        0.10045254,  0.1100463 , -0.05788843, -0.0353197 , -0.05208166,
       -0.07455125, -0.04310594,  0.11752381, -0.00087052, -0.11250246,
        0.03576643, -0.08888219,  0.06011822,  0.02740488, -0.08368167,
        0.02012235, -0.13321717,  0.043586  ,  0.05333372,  0.05647763,
        0.0367625 , -0.00085075,  0.13474344,  0.08726349,  0.12152085,
       -0.02786387,  0.09034737,  0.12276842,  0.05655494,  0.13361923,
       -0.04058047, -0.11805962, -0.11833291], dtype=float32), array([0.1062368 , 0.1291265 , 0.10129224, 0.14898954, 0.09657143,
       0.11315481, 0.10921194, 0.10223313, 0.14728598, 0.15205441,
       0.15365879, 0.12149676, 0.09197792, 0.09868297, 0.11058527,
       0.1277007 , 0.10089337, 0.10601903, 0.11911493, 0.09317307,
       0.09460375, 0.08677674, 0.1227585 , 0.11866102, 0.11490978,
       0.0922437 , 0.12214202, 0.09324753, 0.09556149, 0.10835894,
       0.12709843, 0.11865462, 0.11982345, 0.13623905, 0.09102079,
       0.09619407, 0.14250913, 0.091538  , 0.11383237, 0.13417114,
       0.10057855, 0.08691725, 0.10657921, 0.10025556, 0.1232128 ,
       0.08840161, 0.09563445, 0.09790865, 0.17488758, 0.12368575,
       0.12353288, 0.09485478, 0.10902023, 0.13093244, 0.2012632 ,
       0.10390421, 0.09759413, 0.09641412, 0.10974345, 0.1003518 ,
       0.142376  , 0.10126588, 0.10487094, 0.09504972, 0.11673639,
       0.13392659, 0.09942023, 0.16060945, 0.1507596 , 0.08523411,
       0.09643827, 0.08935579, 0.1082365 , 0.09279627, 0.1498593 ,
       0.09416535, 0.14664015, 0.1014398 , 0.1278579 , 0.10691524,
       0.12927924, 0.16103265, 0.10951774, 0.13798292, 0.12264182,
       0.16083494, 0.17086694, 0.1330259 , 0.1170184 , 0.10002404,
       0.11111796, 0.13541003, 0.11978733, 0.09445018, 0.16814657,
       0.09449889, 0.12442786, 0.12126854, 0.09635071, 0.10437296,
       0.10244964, 0.0929357 , 0.13403215, 0.13499382, 0.16007411,
       0.19633596, 0.12814876, 0.10486247, 0.14529072, 0.138126  ,
       0.10893171, 0.10460689, 0.11527952, 0.12487748, 0.0850869 ,
       0.11750256, 0.11815504, 0.11392116, 0.10807196, 0.12341326,
       0.1162755 , 0.10193442, 0.09116822, 0.11763585, 0.11322674,
       0.09643289, 0.08734342, 0.09522074, 0.10662847, 0.09370635,
       0.12958048, 0.09879147, 0.11641025, 0.19256467, 0.08887854,
       0.08970629, 0.09600978, 0.1049461 , 0.10348009, 0.19769813,
       0.09238419, 0.09986729, 0.13385184, 0.08878595, 0.12518612,
       0.13030005, 0.10962914, 0.08923287, 0.09734843, 0.1316093 ,
       0.09280168, 0.10977438, 0.12895918, 0.11190473, 0.10519812,
       0.11290786, 0.10541239, 0.19561559, 0.08584444, 0.145316  ,
       0.08995274, 0.10382313, 0.08953945, 0.17026865, 0.17328548,
       0.1378344 , 0.09000783, 0.09565194, 0.0873559 , 0.12210537,
       0.11079668, 0.10328992, 0.10370543, 0.09548319, 0.11591001,
       0.13056123, 0.14519364, 0.11664335, 0.13779263, 0.10245441,
       0.13730292, 0.09481879, 0.09604571, 0.08700891, 0.09301397,
       0.09922355, 0.12611122, 0.09379198, 0.12328828, 0.13713224,
       0.17339672, 0.1050149 , 0.11176927, 0.09223   , 0.09525972,
       0.08859299, 0.09892165, 0.11227299, 0.16105387, 0.10321331,
       0.09558067, 0.10303907, 0.12113792, 0.10892885, 0.11375399,
       0.11270826, 0.12172499, 0.13298872, 0.09940975, 0.09195578,
       0.19169019, 0.16745783, 0.09928374, 0.13100854, 0.13613395,
       0.10937163, 0.11860256, 0.110555  , 0.11131984, 0.10701405,
       0.09781437, 0.10628928, 0.13456005, 0.13411173, 0.10130254,
       0.10306302, 0.09814709, 0.09717941, 0.09763084, 0.09395428,
       0.12090389, 0.09156153, 0.12706338, 0.09098142, 0.12613204,
       0.10540049, 0.08431903, 0.08729589, 0.11429634, 0.12525348,
       0.13315405, 0.09806528, 0.09744723, 0.09878551, 0.09167793,
       0.09470569, 0.09917865, 0.09209025, 0.10013307, 0.1323949 ,
       0.12982781, 0.14972197, 0.09068721, 0.09765744, 0.0885959 ,
       0.15190637, 0.13811083, 0.10539412, 0.10699096, 0.16932537,
       0.14424613, 0.09684142, 0.11114558, 0.11891931, 0.13710324,
       0.09002443, 0.09188412, 0.12390601, 0.12453933, 0.10383034,
       0.09948431, 0.1325003 , 0.09164701, 0.08795229, 0.10657447,
       0.10065066, 0.09235875, 0.11360911, 0.11632713, 0.16766468,
       0.10091243, 0.10173139, 0.08933011, 0.08606689, 0.09305085,
       0.11039441, 0.09647256, 0.1209176 , 0.10901393, 0.09581856,
       0.08556169, 0.13818532, 0.09908822, 0.08639621, 0.12236221,
       0.08427524, 0.14112638, 0.0984139 , 0.1336553 , 0.09574784,
       0.15716968, 0.09474739, 0.12478115, 0.09865082, 0.1547969 ,
       0.11945831, 0.0922211 , 0.12187673, 0.0930422 , 0.091419  ,
       0.10544799, 0.17577498, 0.133479  , 0.09320692, 0.10440025,
       0.08521937, 0.09062347, 0.10326602, 0.10576884, 0.10765364,
       0.13671643, 0.15980811, 0.0853895 , 0.08873322, 0.09550713,
       0.08756965, 0.15115702, 0.0950788 , 0.12432638, 0.12381139,
       0.1544979 , 0.10759834, 0.12108462, 0.12982664, 0.08929715,
       0.09137036, 0.10428931, 0.08572724, 0.1208374 , 0.09295481,
       0.11884412, 0.10489029, 0.124828  , 0.09416767, 0.13396278,
       0.08932026, 0.09346726, 0.11993135, 0.10522537, 0.10673127,
       0.17673033, 0.1103982 , 0.11276784, 0.09104203, 0.09649581,
       0.18275853, 0.09325203, 0.10873669, 0.08848377, 0.08935326,
       0.13414422, 0.10318042, 0.12454369, 0.1276938 , 0.09598781,
       0.09609135, 0.13576646, 0.11375922, 0.14604245, 0.1120272 ,
       0.09457424, 0.10610265, 0.13232021, 0.11045159, 0.09379137,
       0.0913992 , 0.08767053, 0.08915178, 0.11273945, 0.10197851,
       0.10343073, 0.08989914, 0.13558996, 0.10648273, 0.08444232,
       0.09652867, 0.11562306, 0.15999348, 0.10605074, 0.08668456,
       0.11115575, 0.11844458, 0.10646366, 0.12476036, 0.10498118,
       0.10370624, 0.12560678, 0.13159163, 0.10396306, 0.10388754,
       0.12126884, 0.10549793, 0.13206352, 0.15771331, 0.10425389,
       0.11926431, 0.09848475, 0.1350587 , 0.10331501, 0.09140544,
       0.14225031, 0.11668574, 0.1127461 , 0.13480811, 0.08576381,
       0.1201162 , 0.13284448, 0.10278001, 0.09760661, 0.09563303,
       0.09429191, 0.1008857 , 0.0918192 , 0.11139707, 0.12354946,
       0.0877655 , 0.14765874, 0.10725997, 0.10344946, 0.11693513,
       0.09654945, 0.1345699 , 0.14105584, 0.09269695, 0.10172795,
       0.09318328, 0.09384818, 0.11269473, 0.15667468, 0.09048107,
       0.09426168, 0.11219146, 0.13420264, 0.11600441, 0.11617354,
       0.11310123, 0.14333928, 0.10073412, 0.10129669, 0.12727462,
       0.09889802, 0.08838073, 0.1464787 , 0.08802259, 0.15231062,
       0.11642824, 0.08355857, 0.13355865, 0.11113308, 0.10000043,
       0.21260643, 0.19319786, 0.09555092, 0.10598341, 0.1421944 ,
       0.14359587, 0.13042194, 0.10910782, 0.10746336, 0.09654924,
       0.10339465, 0.13172357, 0.12910455, 0.09638023, 0.15678243,
       0.1677955 , 0.10149483, 0.12093083, 0.11263165, 0.10216092,
       0.12228643, 0.11037591, 0.1242025 , 0.08624876, 0.11031625,
       0.0884411 , 0.10401347, 0.0971097 , 0.1226217 , 0.09077315,
       0.10378685, 0.12766409, 0.1391322 , 0.14271027, 0.11571549,
       0.10315074, 0.11476348, 0.11961721, 0.11193684, 0.18384859,
       0.12012852, 0.09669487, 0.11469822, 0.09866787, 0.10029624,
       0.14560844, 0.09428747, 0.11253066, 0.10868985, 0.13222541,
       0.12785217, 0.11384882, 0.11808434, 0.15361507, 0.092212  ,
       0.09609002, 0.13500023, 0.11170185, 0.10756372, 0.12903678,
       0.14273404, 0.17237453, 0.09111055, 0.10485855, 0.13126804,
       0.10953586, 0.10319319, 0.09662369, 0.12990639, 0.08944519,
       0.09161558, 0.12124424, 0.08995561, 0.09135956, 0.10218892,
       0.11497704, 0.14062986, 0.13103253, 0.1057537 , 0.12716517,
       0.12290215, 0.10841169, 0.09921754, 0.12056842, 0.0994501 ,
       0.10762125, 0.08567683, 0.09359322, 0.13980058, 0.09629139,
       0.09956332, 0.08706537, 0.10220564, 0.09203195, 0.10878048,
       0.1251647 , 0.17546971, 0.10363397, 0.09409625, 0.11582316,
       0.11004169, 0.10866524, 0.13193339, 0.11654508, 0.0999446 ,
       0.1349022 , 0.13112472, 0.09642798, 0.11932953, 0.10615692,
       0.10386778, 0.09783014, 0.1350014 , 0.11683273, 0.08978919,
       0.10860962, 0.10914019, 0.12000738, 0.08618689, 0.09810064,
       0.08582322, 0.13935745, 0.1309223 , 0.09059481, 0.09794733,
       0.09402064, 0.137492  , 0.12392697, 0.08981343, 0.15557267,
       0.09115626, 0.12791505, 0.18366826, 0.13892539, 0.11148996,
       0.09911164, 0.15807347, 0.08618929, 0.10229971, 0.09374546,
       0.09655051, 0.15527302, 0.08903442, 0.1081701 , 0.11412492,
       0.10889083, 0.10630383, 0.13446322, 0.14473338, 0.11072423,
       0.094855  , 0.13297082, 0.0992583 , 0.10369581, 0.08835137,
       0.10057704, 0.10837527, 0.10170932, 0.09058325, 0.09858859,
       0.10456172, 0.09368373, 0.0930731 , 0.1142531 , 0.0923854 ,
       0.11899735, 0.18366319, 0.09513009, 0.09579671, 0.11514638,
       0.1120336 , 0.09399133, 0.11782088, 0.0899548 , 0.12107246,
       0.14695677, 0.08703332, 0.13920105, 0.1543028 , 0.09463812,
       0.0869571 , 0.09581951, 0.08770832, 0.14704208, 0.10223102,
       0.12335769, 0.09272788, 0.1251139 , 0.11778073, 0.09945228,
       0.13703144, 0.10517268, 0.08983138, 0.09692512, 0.09683544,
       0.09737978, 0.120377  , 0.0875932 , 0.09054802, 0.11248734,
       0.10558113, 0.10271761, 0.15014373, 0.11317025, 0.10664131,
       0.09058461, 0.11374148, 0.08870815, 0.10154381, 0.11685231,
       0.12284751, 0.09448656, 0.18325496, 0.10344413, 0.08595786,
       0.10371672, 0.08482841, 0.10223232, 0.13689536, 0.09613653,
       0.10443545, 0.17337191, 0.09218056, 0.1359922 , 0.11211287,
       0.11024052, 0.11494977, 0.10500475, 0.10248091, 0.0956504 ,
       0.10320379, 0.11105818, 0.11364499, 0.15642776, 0.08820053,
       0.1455524 , 0.13202605, 0.10845741, 0.13442075, 0.12163185,
       0.10096032, 0.09958732, 0.11839841, 0.0943318 , 0.12914526,
       0.10854666, 0.11056353, 0.12525393, 0.09212712, 0.08654214,
       0.10114243, 0.1398362 , 0.12586865, 0.09773762, 0.10765333,
       0.11480377, 0.10320654, 0.12264665, 0.09674516, 0.10228346,
       0.08647571, 0.12220811, 0.13750562, 0.144485  , 0.14801748,
       0.09874871, 0.14562188, 0.12435065], dtype=float32), array([[[[ 0.01563038],
         [ 0.01271809],
         [ 0.04969181],
         ...,
         [-0.0169505 ],
         [-0.00024443],
         [-0.00084328]],

        [[ 0.01841378],
         [-0.01611397],
         [ 0.0215678 ],
         ...,
         [ 0.0179865 ],
         [-0.01081854],
         [ 0.02172927]],

        [[ 0.03051118],
         [-0.01822679],
         [ 0.01530925],
         ...,
         [ 0.00244259],
         [-0.01170349],
         [ 0.01576437]]],


       [[[-0.00189686],
         [ 0.00771315],
         [ 0.0166514 ],
         ...,
         [-0.02149926],
         [ 0.02045964],
         [ 0.02542704]],

        [[-0.00982836],
         [ 0.00914608],
         [ 0.01005324],
         ...,
         [ 0.01218121],
         [ 0.02667357],
         [ 0.02482081]],

        [[-0.01281828],
         [ 0.01114579],
         [-0.02246714],
         ...,
         [ 0.02605099],
         [ 0.01139912],
         [-0.03252032]]],


       [[[ 0.00513605],
         [-0.02077445],
         [ 0.03818076],
         ...,
         [-0.01575942],
         [-0.017638  ],
         [ 0.02346363]],

        [[ 0.02471781],
         [ 0.00467011],
         [ 0.02206653],
         ...,
         [ 0.02494863],
         [ 0.0194739 ],
         [-0.00616399]],

        [[-0.01753354],
         [-0.00080238],
         [-0.01979772],
         ...,
         [-0.01092939],
         [-0.03202905],
         [-0.00114744]]]], dtype=float32), array([[[[ 3.7728264e-03, -1.9812070e-02,  4.0385831e-02, ...,
          -4.0768933e-02, -6.8455011e-02,  3.8094610e-02],
         [-1.0909954e-02, -4.7831919e-02, -1.0765447e-02, ...,
           5.4050010e-02,  4.2848233e-02, -5.4187361e-02],
         [-3.5810519e-02,  4.3679822e-02, -4.1093513e-02, ...,
          -1.0356106e-02,  2.1269219e-02,  8.5120555e-05],
         ...,
         [ 3.3078119e-02, -2.0879507e-02, -4.8402704e-02, ...,
           5.7039135e-03, -3.2176543e-02, -5.3583782e-02],
         [-5.9781082e-02,  3.3204824e-02, -2.1859528e-02, ...,
          -9.1766696e-03,  6.9372959e-02, -2.2063658e-02],
         [ 6.5168701e-02,  6.7424171e-02, -5.6405574e-02, ...,
          -2.2212580e-02,  5.6914881e-02,  1.6416181e-02]]]],
      dtype=float32), array([0.99358463, 1.002963  , 1.0224869 , 0.98943824, 0.9971712 ,
       1.0076228 , 1.0042226 , 0.997075  , 1.0043304 , 0.9931172 ,
       0.9952715 , 0.99829483, 0.9966468 , 0.99324846, 0.994483  ,
       0.99508226, 0.9929418 , 1.0014915 , 0.9930212 , 0.9915046 ,
       0.9848722 , 0.9982554 , 1.0105157 , 0.99472463, 0.9909753 ,
       1.0293626 , 1.0220789 , 0.9897201 , 0.9999309 , 0.99920154,
       1.0069536 , 0.98684615, 0.99675   , 1.0019794 , 0.9955654 ,
       1.003303  , 0.99322265, 0.9996344 , 0.99630916, 0.9893755 ,
       0.9868558 , 1.0113003 , 1.0082723 , 0.99856395, 0.99265236,
       0.9898141 , 0.98988444, 0.99297816, 0.9983673 , 1.0119969 ,
       0.99659085, 0.9953185 , 0.99885696, 0.9858727 , 0.9850732 ,
       0.9861756 , 1.0041764 , 0.9912564 , 0.9792771 , 1.0032237 ,
       0.9761477 , 1.0044357 , 1.0028703 , 1.0060915 , 0.9865757 ,
       1.0029004 , 0.99521846, 1.0057634 , 1.0226297 , 0.99636924,
       0.9928716 , 0.9869051 , 1.0020905 , 0.9952339 , 0.994945  ,
       0.98830974, 0.9920329 , 0.9917432 , 0.98718697, 0.9822903 ,
       0.9947685 , 0.99443555, 1.0007879 , 0.99385136, 1.0207926 ,
       1.0273154 , 1.0008632 , 0.9969618 , 1.0005932 , 0.9836475 ,
       0.9980612 , 1.0006671 , 0.9827811 , 0.99377453, 1.0109383 ,
       0.99401534, 0.98828995, 1.0324107 , 1.0131276 , 0.99957263,
       0.9947569 , 0.9988037 , 1.0105377 , 1.0170689 , 0.997972  ,
       0.9932389 , 0.99713945, 0.9885653 , 0.99837744, 0.99607617,
       0.985494  , 0.9881958 , 0.9907137 , 1.0056026 , 1.0262535 ,
       0.98516196, 0.998827  , 1.0036805 , 0.9974581 , 0.9905907 ,
       1.0194838 , 0.99186826, 0.97482634, 0.97872955, 1.0016772 ,
       1.0007097 , 0.99994355, 1.0096998 , 1.0085987 , 1.0119214 ,
       0.99968076, 0.9940774 , 1.0206219 , 0.99324316, 0.99343395,
       0.994966  , 0.9910729 , 1.0067748 , 0.9934224 , 0.9873741 ,
       1.0244149 , 1.0339693 , 0.9863031 , 1.023725  , 0.9956774 ,
       0.98207426, 1.0064597 , 1.0021099 , 0.98795676, 0.9928708 ,
       0.99588144, 1.0013924 , 1.0028346 , 1.0002685 , 1.0053568 ,
       0.99627316, 1.0154518 , 1.0128248 , 0.997345  , 0.9944144 ,
       0.99108297, 0.998664  , 1.0126381 , 0.99424404, 1.0131352 ,
       0.9876351 , 1.0002773 , 0.98755515, 0.98641807, 1.0013595 ,
       0.9877148 , 1.0055404 , 1.0215905 , 0.9994011 , 0.9995461 ,
       1.0003301 , 1.0079591 , 1.0004224 , 0.9974731 , 0.9975868 ,
       1.0035559 , 0.99422246, 1.0193762 , 0.98341185, 0.9996126 ,
       0.99293494, 0.99685615, 0.99403214, 0.99105895, 1.005673  ,
       0.99865556, 0.9975645 , 1.0129915 , 0.9916591 , 0.99557066,
       1.0096304 , 0.9854807 , 0.98990697, 0.9981833 , 0.99647075,
       1.0182662 , 0.9973825 , 0.9996979 , 1.0126835 , 1.0012914 ,
       0.9998323 , 1.008788  , 0.99329233, 1.009986  , 1.0010209 ,
       1.0039302 , 0.99734086, 0.9942003 , 0.98955667, 1.0077598 ,
       0.9864384 , 1.0024073 , 1.0055867 , 0.99392354, 1.0016258 ,
       0.9973967 , 1.0021459 , 1.007308  , 0.9893987 , 0.98561305,
       0.99798584, 0.9940236 , 0.98724854, 0.99499583, 0.9872038 ,
       1.0128788 , 0.9947665 , 0.99928313, 1.001792  , 0.9953288 ,
       0.9896023 , 0.9940351 , 0.99397266, 1.0107486 , 1.0060406 ,
       1.0166627 , 0.9988623 , 1.0358014 , 0.9904163 , 1.0110798 ,
       0.9851431 , 0.99241894, 1.0277866 , 0.99041885, 0.99355936,
       1.0036955 , 0.9894106 , 0.997488  , 0.9993647 , 0.9826567 ,
       1.0093307 , 0.9897167 , 0.99850106, 0.9920703 , 0.99736565,
       0.9973774 , 0.9944609 , 1.0075691 , 0.9878012 , 0.994389  ,
       1.0179672 , 1.0087335 , 0.9912455 , 0.99785835, 1.0016199 ,
       0.998572  , 1.0135899 , 0.9959849 , 1.0111831 , 1.0148599 ,
       1.0048094 , 0.9977356 , 0.9958617 , 1.0163071 , 0.99152803,
       0.99330866, 1.0005838 , 1.000527  , 0.9934114 , 0.9856925 ,
       1.002641  , 0.9985234 , 0.99066037, 1.0070378 , 0.9822844 ,
       0.99928737, 1.0036658 , 1.0035665 , 1.0009811 , 0.9914703 ,
       1.0013363 , 0.9918458 , 0.9977179 , 0.98920906, 1.0106657 ,
       0.9819223 , 1.0016205 , 1.0060489 , 0.98704606, 0.9944319 ,
       1.0155404 , 0.997484  , 0.99834913, 0.9900043 , 0.99220985,
       1.0208786 , 1.0093236 , 1.0111849 , 0.9912246 , 1.0054419 ,
       0.99591684, 0.98269266, 1.0072325 , 1.0284868 , 0.99974394,
       0.9963371 , 1.0031056 , 1.0145212 , 0.99320126, 0.9938702 ,
       0.98439056, 0.98545617, 0.9964949 , 0.9909055 , 0.9926029 ,
       1.0004567 , 0.9954677 , 0.9888751 , 0.990881  , 0.99851084,
       0.9915628 , 0.9842076 , 0.98989487, 0.99430245, 0.9961012 ,
       1.0038413 , 0.99652815, 1.0084381 , 0.99605644, 0.99259573,
       0.98042494, 1.0007048 , 0.9997672 , 0.9876205 , 1.0120778 ,
       0.98977983, 0.9830768 , 0.9864494 , 0.99530137, 0.98972505,
       0.9909233 , 1.0100768 , 0.9896106 , 1.0036666 , 1.0071038 ,
       1.0215169 , 0.9956258 , 1.0123596 , 0.9866507 , 0.99580276,
       0.9975293 , 0.99988806, 0.9977591 , 0.98978645, 0.99505424,
       0.99139094, 0.99272275, 1.0200993 , 0.9888135 , 1.0023887 ,
       1.0019246 , 1.0001228 , 0.99486125, 1.0201197 , 0.9902086 ,
       1.0094616 , 0.9919491 , 1.0040113 , 1.0031327 , 0.9952816 ,
       0.9979025 , 1.0141999 , 1.0011977 , 0.9922834 , 0.9975483 ,
       0.9937857 , 0.9798517 , 1.000085  , 0.98771757, 0.99079597,
       1.0319052 , 1.0070612 , 1.0015775 , 1.0015785 , 1.0139282 ,
       0.9961666 , 0.99750304, 1.0088696 , 0.9955494 , 1.0171887 ,
       1.0068865 , 1.0023288 , 1.0121413 , 0.99620754, 0.9979078 ,
       0.9987998 , 0.9989018 , 0.9903099 , 1.0012844 , 0.9932726 ,
       1.0092719 , 0.9920279 , 0.9833891 , 1.0003319 , 0.9933428 ,
       0.98910266, 1.0014565 , 0.9898156 , 1.0130231 , 0.9851621 ,
       0.9936452 , 0.9899908 , 0.987638  , 0.985834  , 1.025978  ,
       1.0037229 , 0.9883305 , 1.001702  , 1.0017341 , 0.98091763,
       0.9999199 , 0.9974317 , 1.001008  , 0.9914835 , 0.99617577,
       0.9829077 , 0.9966077 , 0.99302614, 1.0033803 , 0.9896396 ,
       1.0254666 , 0.9955459 , 1.0023916 , 0.9898251 , 1.0165604 ,
       0.98096824, 0.982458  , 0.99474454, 0.9968588 , 1.0042785 ,
       1.0111948 , 1.0005996 , 1.0020311 , 1.0054914 , 1.0155929 ,
       1.0036328 , 1.0074668 , 0.9802822 , 0.9949404 , 1.0037806 ,
       1.005404  , 0.9921395 , 0.99229825, 1.000591  , 0.9981743 ,
       0.9990491 , 0.99653053, 1.0119327 , 0.98654336, 1.004844  ,
       1.0091797 , 1.003668  , 1.0178058 , 0.9898484 , 1.0042487 ,
       0.9968885 , 0.99173033, 0.9947786 , 0.99299425, 0.99269897,
       0.9879506 , 0.9944875 , 1.0062337 , 1.0027095 , 1.0031142 ,
       0.99609786, 0.9928582 , 0.99360704, 1.0045418 , 0.99889547,
       0.97933674, 0.99147934, 0.98322487, 0.9980604 , 1.000341  ,
       1.0133011 , 1.0226257 , 0.9871711 , 1.0171789 , 1.0014503 ,
       0.98968744, 1.005761  , 1.0236202 , 0.9980201 , 0.99049187,
       0.991878  , 0.98899245, 1.0152649 , 0.9833956 , 1.0300786 ,
       1.0045638 , 1.0177608 , 0.9839869 , 1.0274174 , 1.0019971 ,
       0.9904935 , 1.0327241 , 1.0090435 , 1.0017428 , 1.001029  ,
       0.9893567 , 0.99467885, 0.9843199 , 0.9872005 , 0.9924584 ,
       1.0094393 , 1.0062641 , 0.9931298 , 0.99538225, 0.99547106,
       1.025322  , 0.9980979 , 0.99138975, 0.9970121 , 1.0052054 ,
       0.9837651 , 0.9987948 , 0.98791033, 1.0218166 , 0.9931805 ,
       0.99672836, 0.97845453, 0.9903643 , 0.99580705, 0.9987049 ,
       0.98935616, 0.98431057, 0.9933547 , 0.9909072 , 1.0030622 ,
       0.9946775 , 1.0011897 , 0.99436796, 1.0029452 , 0.9835932 ,
       0.9985531 , 0.999637  , 1.013615  , 1.0101974 , 1.0046788 ,
       1.0303425 , 1.0197458 , 0.9986119 , 1.0062474 , 1.0019981 ,
       0.9883453 , 1.0108162 , 1.0251728 , 0.996648  , 0.99521786,
       0.99789184, 1.0281998 , 0.99558586, 0.9940962 , 1.0081991 ,
       0.9992651 , 0.9915365 , 0.99220425, 0.99121404, 0.9840081 ,
       1.0075917 , 0.9938093 , 0.99073845, 0.99780446, 0.9988733 ,
       0.99905527, 0.9875929 , 0.9994776 , 0.99271744, 0.9971122 ,
       1.0090516 , 0.9916865 , 1.0042028 , 1.013623  , 0.99149513,
       1.0033791 , 0.9936859 , 1.017456  , 1.0059028 , 0.97612524,
       1.0075542 , 0.9987268 , 1.0048131 , 1.0007218 , 0.9805029 ,
       0.99933237, 0.99506265, 0.998854  , 0.99961567, 1.0026782 ,
       1.0069555 , 0.99514234, 0.9936043 , 1.0108409 , 1.0267857 ,
       1.0251889 , 0.99278426, 1.006849  , 1.0133401 , 0.9995197 ,
       0.99310607, 0.9859083 , 0.9914563 , 1.0149516 , 1.0012553 ,
       0.9952458 , 0.9972644 , 0.998856  , 0.9788923 , 0.9972211 ,
       1.0054901 , 1.0026689 , 1.014448  , 0.9970827 , 1.0012637 ,
       0.99020946, 0.99877244, 0.9988335 , 0.99397373, 0.99820924,
       1.0206361 , 1.0082477 , 0.99101835, 1.0061494 , 1.0408249 ,
       0.9958297 , 0.99181163, 0.98624164, 1.0039239 , 1.0061002 ,
       1.0004277 , 1.0020142 , 1.0215286 , 0.99600405, 0.99802625,
       1.0243744 , 0.99863744, 1.0160116 , 0.9985605 , 1.0218999 ,
       0.9745279 , 1.0011796 , 0.999549  , 0.99534506, 1.0219756 ,
       1.0022184 , 0.9951884 , 0.9933985 , 0.9946946 , 1.0088174 ,
       0.99735105, 0.9936358 , 1.0072758 , 0.99614364, 0.9879206 ,
       0.98504007, 0.9995773 , 1.0094928 , 1.0022006 , 1.0081298 ,
       1.0024525 , 1.0116087 , 1.0165789 , 1.000871  , 0.9931602 ,
       0.99676996, 0.9881226 , 0.99100804, 1.0271783 , 0.9994197 ,
       0.9896013 , 0.9970427 , 0.9885471 , 0.98788196, 0.98840606,
       1.0060571 , 0.9885234 , 1.0256172 , 0.9953615 , 0.990836  ,
       1.0160962 , 1.0104271 , 0.9936926 , 0.97755325, 1.0019692 ,
       1.0046444 , 1.023057  , 0.999559  , 0.99444157, 0.99319947,
       1.0057812 , 0.9911178 , 0.9968913 , 0.99430156, 0.9788207 ,
       0.9983626 , 1.0202346 , 0.9826993 , 1.0081301 , 1.0056211 ,
       0.99302906, 0.9817306 , 0.99620306], dtype=float32), array([-5.54162962e-03, -1.23602385e-02,  3.48005183e-02, -2.83572022e-02,
       -1.35382768e-02,  5.36452839e-03, -3.13280858e-02, -2.89128488e-03,
        1.72073394e-03, -1.23163173e-02, -6.65906677e-03, -2.05898937e-03,
       -7.81032140e-04, -7.63776246e-03, -1.83700642e-03, -7.76062394e-03,
       -1.38945458e-02, -3.02438289e-02,  2.37193354e-03, -5.46900276e-03,
        4.43151308e-04,  1.19554717e-03, -3.84648889e-03,  2.22190679e-03,
       -2.29441095e-03, -4.43104049e-03, -1.70550495e-03, -1.87786147e-02,
       -9.81971098e-05,  3.72787798e-03, -1.88557233e-03, -9.87867545e-03,
       -5.72691765e-03, -3.81446332e-02,  4.50454390e-05, -3.89903178e-03,
        1.55035546e-03,  1.80317508e-03,  1.09870743e-03, -1.55437947e-03,
       -9.67597589e-03, -8.77724681e-03,  2.58300430e-03, -2.16879696e-02,
       -3.00451973e-03, -4.23716614e-03, -6.70647249e-03, -1.11119784e-02,
       -1.05536415e-03,  1.04520982e-03, -2.01014639e-03, -8.07286426e-03,
       -4.88761999e-03, -1.32693136e-02, -7.70884333e-03, -1.50280437e-02,
        4.12266981e-03, -5.01825474e-03, -2.02031322e-02,  5.73970610e-03,
       -1.13219032e-02,  2.75412633e-04, -4.37270990e-03, -2.65460601e-03,
       -1.18721463e-02,  8.31861701e-03, -8.04742984e-03, -1.37597658e-02,
        2.28394140e-02,  2.69052805e-03, -7.19040772e-03, -2.20829691e-03,
        9.23778210e-03, -9.29016806e-03, -6.57439651e-03,  4.81817871e-03,
       -7.67299114e-03, -1.15174539e-02,  1.20815390e-03, -1.77770555e-02,
       -1.24768855e-03, -8.72444082e-03,  1.01105189e-02,  2.38404889e-03,
        1.65033787e-02,  2.19003540e-02,  1.03259068e-02, -5.33684506e-04,
        1.59133431e-02, -8.87979660e-03, -2.08275276e-03, -1.91242003e-03,
       -3.88867967e-03, -2.54393090e-03, -3.65904793e-02, -3.06326095e-02,
       -2.87361164e-02,  2.12611761e-02, -8.75265244e-03,  7.81563390e-03,
       -1.01622129e-02, -1.80255575e-03, -1.19772190e-02,  2.85827238e-02,
        5.49867237e-03, -8.39062408e-03, -4.76772198e-03, -8.46856367e-03,
       -8.63127783e-03,  1.28478706e-02, -4.74430248e-03, -1.19113484e-02,
       -8.31590127e-03, -8.33165552e-03, -2.06693192e-03, -2.71477178e-02,
       -1.30647775e-02, -1.71556361e-02,  5.33884997e-03, -2.11399514e-03,
        3.02254464e-02, -1.54215777e-02, -4.02518269e-03, -9.83386859e-03,
       -2.78681573e-02,  1.10306330e-02, -2.91494448e-02, -4.42104647e-03,
        4.87924973e-03,  1.37982210e-02, -1.14024971e-02, -1.57318898e-02,
       -5.91735058e-02, -2.90965708e-03, -6.29238738e-03,  1.54667879e-02,
       -1.41479773e-02, -1.80471353e-02, -2.50680745e-02, -1.30463978e-02,
        1.40061872e-02,  2.21432950e-02, -7.86892697e-03,  4.73979767e-03,
        3.65510653e-03, -1.89627036e-02, -1.97765231e-02, -6.80233864e-03,
       -1.15943309e-02, -5.02355443e-03, -5.99766569e-03,  4.03415738e-03,
        1.11576440e-02, -1.96147095e-02, -3.12029608e-02, -8.68519209e-03,
       -6.23659138e-03,  3.34582874e-03,  4.82833432e-03, -2.78149336e-03,
       -6.43080240e-03, -5.09212026e-03,  6.28104247e-03,  1.66784308e-03,
        2.19365805e-02, -5.62082091e-03, -3.94064700e-03, -1.43630113e-02,
       -1.93401724e-02, -2.44828220e-03, -7.01447017e-03, -4.52115340e-03,
       -1.38082914e-03, -1.52746001e-02, -5.59160206e-03, -1.78820491e-02,
        5.66635281e-03, -7.22809881e-03,  6.00869581e-03, -6.71065086e-03,
       -8.29948019e-03, -3.74367204e-03,  1.10782040e-02, -5.85728232e-03,
       -3.55549827e-02, -6.44603884e-03,  6.57970272e-03, -5.57538122e-03,
       -8.14716332e-03,  1.13073429e-02,  1.32103940e-03, -7.55861448e-03,
       -3.83714680e-03,  5.19749010e-03, -2.09964393e-03,  7.26258429e-03,
       -2.10420433e-02, -1.28601948e-02,  7.19706714e-03, -1.25779975e-02,
       -2.21596844e-02, -3.28291953e-03, -3.72724468e-03,  7.43951602e-03,
       -2.59516127e-02, -1.35142971e-02,  6.04009256e-03,  3.08894296e-03,
        4.22839727e-03, -1.64051093e-02, -1.92507338e-02, -5.36412327e-03,
       -2.22179154e-03, -6.06995495e-03,  4.80237696e-03, -5.37574897e-03,
        1.16948411e-02, -6.74976688e-03,  1.88703428e-03,  1.77494083e-02,
       -1.80622272e-03, -1.68811344e-02, -1.08512781e-04, -8.49158503e-03,
       -2.32517626e-03,  7.50305504e-03,  1.30275276e-03, -1.29038119e-03,
       -2.82384232e-02, -3.65698151e-02, -1.11092813e-02, -7.03103328e-03,
       -3.91372759e-03,  3.63344862e-03, -4.81715798e-03, -9.43905022e-03,
       -5.18494425e-03, -1.37972482e-03, -2.38880999e-02, -3.62550542e-02,
        1.97445285e-02, -2.04246938e-02,  2.54663490e-02, -4.63739969e-03,
       -6.15229877e-03, -2.53153574e-02, -6.29206421e-03,  1.05846152e-02,
        2.35829270e-04, -2.92128883e-02,  1.13057932e-02, -2.78217476e-02,
       -8.39104317e-03,  8.03131377e-04, -1.11957202e-02,  2.01311167e-02,
       -1.46633470e-02,  3.99565697e-03, -1.25464080e-02, -3.73361586e-03,
       -1.51065225e-03, -1.57997757e-02, -5.15621249e-03, -1.08179115e-02,
       -2.96246400e-03, -4.80548181e-02,  1.84383728e-02, -3.46097071e-03,
        3.13975802e-03,  8.38285498e-03, -3.51437926e-03, -1.30053684e-02,
       -1.01063289e-02,  1.19248405e-03, -1.86152663e-03, -4.65694640e-04,
        1.79279398e-03, -7.40871672e-03,  1.01570291e-02, -1.27502866e-02,
        1.21320952e-02, -1.26163745e-02,  1.49153569e-03, -1.77385495e-03,
       -9.23893042e-03,  8.03037640e-03, -1.14302081e-03, -1.02135092e-02,
        1.37024955e-03, -1.11140674e-02,  3.34287004e-04, -1.55986808e-02,
        4.95693553e-03, -1.97020732e-03, -1.16416933e-02, -2.26923004e-02,
       -8.95739440e-03,  5.69329783e-03, -1.82416067e-02, -2.63054832e-03,
       -1.06311897e-02,  7.45328562e-03, -1.22666277e-03, -8.75674561e-03,
       -6.96850941e-04,  1.96522428e-03, -2.12301873e-03,  8.20524804e-03,
       -1.18857305e-02, -1.19791357e-02, -2.49061566e-02,  5.45746740e-03,
       -8.00908264e-03,  3.79387662e-03, -1.82674527e-02,  5.28576039e-03,
       -1.57001999e-03,  2.31659841e-02, -3.42181996e-02, -1.12868799e-02,
        7.20869796e-03,  6.30793814e-03, -3.49208452e-02, -1.04434164e-02,
       -5.36533725e-03, -6.03355607e-03,  6.68174936e-04,  4.99262195e-03,
        5.85551432e-04, -1.04772942e-02,  3.41159501e-03,  6.35241996e-03,
        1.55175629e-04,  1.31161641e-02,  9.12236457e-04,  7.97618181e-03,
       -1.75657533e-02, -8.79766420e-03, -1.46538932e-02,  6.93751220e-03,
       -2.88502090e-02, -2.15823506e-03,  2.66093318e-03, -1.07464404e-03,
       -1.02615329e-02, -1.84605569e-02,  2.26922231e-04,  5.86062297e-03,
        8.78694336e-05,  1.72026586e-02, -8.55395384e-03, -1.32884551e-02,
       -5.50075155e-03, -2.41040755e-02, -1.54859815e-02, -3.61658703e-03,
        2.30805296e-02, -6.51242258e-03, -1.59136318e-02,  9.57555417e-03,
       -3.41273174e-02, -5.00360969e-03, -1.83041133e-02, -2.60817390e-02,
       -1.04333423e-02, -2.90385773e-03, -2.90153101e-02,  4.39770147e-03,
       -5.63178631e-03, -5.21219149e-03, -5.98890660e-03, -1.28006167e-03,
        2.59838207e-03, -1.31236687e-02, -4.27947147e-03,  1.02615096e-02,
        2.08032341e-03, -1.07788136e-02,  2.38045603e-02, -7.15346029e-03,
       -7.52251176e-03, -1.37817319e-02,  8.62684287e-03,  2.19498063e-03,
       -3.15822428e-03, -1.60090066e-02, -8.62957351e-03, -2.29924009e-03,
       -1.85951069e-02, -1.63546589e-04, -1.75781138e-02, -5.03432704e-03,
       -2.00517569e-03,  2.09262245e-03,  1.28371030e-05,  4.01542187e-02,
       -1.37440162e-02, -1.68764908e-02, -2.76290160e-02, -3.69533226e-02,
       -7.74585642e-03, -6.23174058e-03, -4.18565981e-02, -1.72692947e-02,
        1.17031904e-02, -1.27964886e-02, -2.45593116e-03, -2.10308959e-03,
       -2.53193229e-02, -3.99985583e-03, -2.75309640e-03,  6.51178276e-03,
       -3.60816121e-02, -2.74235699e-02, -1.61119383e-02,  6.57044305e-03,
       -1.47606768e-02, -6.30777981e-03, -9.58204642e-03, -1.73726752e-02,
       -8.56065564e-03,  1.02127169e-03, -1.25993481e-02,  1.75021086e-02,
       -9.26312711e-03, -1.42032262e-02, -2.85988394e-03, -9.18739941e-03,
       -1.68262026e-03,  3.37058422e-03, -2.68553626e-02, -7.08164088e-03,
       -6.87784422e-03,  1.83450012e-03, -2.34842096e-02,  2.52528535e-03,
       -5.06625324e-02, -1.51783163e-02, -7.82744959e-03, -1.13566602e-02,
       -1.23238480e-02, -9.29984543e-03, -6.51649712e-03, -8.03179480e-03,
       -1.27611822e-02,  2.84946226e-02, -8.81433114e-03,  8.04192969e-05,
       -9.77494381e-03,  2.10783463e-02, -2.25821808e-02, -2.67073885e-03,
       -2.52703135e-03, -2.84303986e-02, -8.05699546e-03, -3.02767777e-03,
       -2.15230659e-02, -3.65011720e-03, -1.06400121e-02,  1.24409469e-02,
       -1.13131071e-04, -1.10854870e-02, -1.92542619e-03, -1.79124787e-03,
        2.26832111e-03,  1.29015613e-02,  1.13004458e-03,  8.78936518e-03,
        3.80461034e-03, -1.86989754e-02, -2.84338892e-02, -3.29434611e-02,
        1.24522829e-02, -1.86659792e-03, -1.44916316e-02, -3.12311668e-02,
       -6.29340415e-04,  3.05003170e-02, -3.76078393e-03, -7.08888052e-04,
        7.63579039e-03,  7.69911567e-03, -2.45483848e-03, -1.08788628e-02,
       -5.76052442e-03, -1.15680452e-02, -2.66214292e-02,  2.09786128e-02,
        6.78742770e-04, -2.43443474e-02,  7.81223469e-04, -3.22849466e-03,
       -3.05276806e-03,  2.68165511e-03, -9.56948288e-03, -1.58738066e-02,
       -4.84558847e-03, -3.09333317e-02, -3.09757050e-03, -3.01538291e-03,
       -4.90625985e-02,  3.90162170e-02, -3.24107409e-02, -1.07466541e-02,
       -3.83706763e-02, -1.64910201e-02,  1.57756042e-02,  2.20032893e-02,
       -5.68921714e-05, -6.14986010e-03, -4.36564628e-03, -8.26697890e-03,
        1.69050898e-02, -1.80465472e-03,  1.73194949e-02,  1.46255139e-02,
       -1.64032131e-02, -5.42950584e-03,  2.07496751e-02,  9.85039119e-03,
       -1.46866618e-02,  3.87146473e-02,  2.06565838e-02,  1.71173811e-02,
        5.29077195e-04,  3.43812210e-03, -1.52367624e-02, -1.71884298e-02,
       -1.47237908e-02, -1.12906555e-02,  3.96402506e-03, -1.30142104e-02,
       -5.28361474e-04,  1.41515769e-03, -3.78769310e-03, -8.60660616e-03,
       -6.74767466e-03, -8.77142232e-03, -9.50420275e-03, -2.58517405e-03,
        2.95459200e-03, -5.09648933e-04, -2.17076614e-02, -5.07162549e-02,
       -6.71558222e-03,  1.01555325e-02, -2.52413079e-02,  1.66854858e-02,
       -1.91616137e-02, -3.10911797e-02, -8.65390617e-03, -8.60105082e-03,
       -4.53171553e-03, -7.95331504e-03, -3.75980744e-04, -5.37529215e-03,
        1.47354994e-02,  1.39851794e-02, -6.53370144e-03, -1.60861779e-02,
       -1.44567399e-03, -1.81863678e-03, -1.89785678e-02,  1.90179441e-02,
        9.41005256e-03,  2.51031350e-02,  1.88989043e-02, -2.60294648e-04,
       -2.71019302e-02,  1.07073849e-02, -2.58118031e-03,  1.59643963e-02,
        4.83682789e-02,  9.44588985e-03,  2.47621094e-03, -4.30741813e-03,
       -2.45709345e-02,  9.07340739e-03, -3.85697978e-03, -8.09939485e-03,
       -6.26981346e-05, -2.17093009e-04, -1.81218088e-02, -8.94054584e-03,
       -1.24517176e-02,  6.11743890e-03, -3.41038196e-03, -7.49167381e-03,
       -8.62880237e-03, -4.72325366e-03,  1.47463742e-03, -1.55167263e-02,
        3.68840271e-03, -4.72156005e-03, -1.03338296e-03,  1.48744956e-02,
       -1.21666035e-02, -8.87751929e-04,  8.62110220e-03, -3.66782993e-02,
       -6.20670384e-03, -5.72587783e-03,  1.24406898e-02, -3.26031446e-03,
       -2.07647104e-02,  2.66355462e-04,  7.87862297e-03, -1.26523674e-02,
       -2.53376514e-02, -1.67529490e-02,  1.69173442e-03, -7.52686011e-03,
       -1.21842511e-02, -4.26777202e-04, -5.03270105e-02, -1.81027446e-02,
       -7.50403712e-03, -1.37241473e-02, -1.64957892e-03,  1.37889553e-02,
        2.17407644e-02, -3.51977907e-02,  1.47502078e-02,  4.66429861e-03,
       -6.57768128e-03,  6.00811280e-03, -5.18603204e-03,  3.40931769e-03,
        1.03907846e-02,  1.09020006e-02, -2.37154006e-03, -3.49642220e-03,
       -1.20275458e-02, -1.47003466e-02, -2.09840224e-03, -8.83193128e-03,
       -6.78046793e-03, -1.87479090e-02, -2.24202825e-03,  4.13083564e-03,
       -9.64110531e-03, -5.21429675e-03, -2.66964231e-02, -4.03316841e-02,
       -1.38464728e-02, -1.49150286e-03,  1.87443346e-02, -9.32786427e-03,
        8.91125109e-03, -9.70342942e-03, -3.47607303e-03, -3.49156442e-03,
       -1.32695856e-02,  5.34201553e-03, -1.33748902e-02,  2.47120969e-02,
        3.45824938e-03, -1.08483145e-02, -1.56381764e-02, -4.55750804e-03,
        2.96960864e-03, -7.12026283e-03, -1.26891071e-04, -3.27486582e-02,
        3.23439501e-02, -5.29517001e-03, -1.06615080e-02, -2.90347030e-03,
       -1.16338534e-02,  2.97944751e-02, -1.86154619e-03, -3.29802511e-03,
        1.20382207e-02, -2.13536259e-06,  1.27764838e-02, -2.58932647e-04,
        4.28208848e-03,  1.42705208e-02, -3.05354502e-02, -1.05323503e-02,
       -1.96172390e-02, -9.92364809e-03,  9.04371589e-03,  9.65444185e-03,
        1.39464624e-03, -1.10230464e-02,  3.07049812e-03, -5.30786067e-03,
        1.02241654e-02, -1.06330663e-02,  1.78823844e-02,  1.28782040e-03,
        1.44222123e-03, -5.68511663e-03,  8.66916031e-03, -1.31826838e-02,
        1.22338440e-03, -1.03443414e-02, -5.05152391e-04, -2.49403995e-03,
       -1.09268883e-02, -5.20313997e-03, -2.27916948e-02, -8.09491903e-04,
       -1.31973606e-02,  1.20637110e-02,  2.54117362e-02, -5.85198263e-03,
       -3.11344955e-02, -3.63932294e-03,  5.48959011e-03,  2.70763994e-03,
       -1.07812928e-02, -1.91500224e-02,  8.94476485e-04,  1.63196903e-02,
       -3.23395478e-03,  1.47085800e-03, -4.31456305e-02, -6.33356394e-03,
        9.43821762e-03,  2.28506309e-04, -2.32442864e-03,  1.85440143e-03,
        4.56885807e-03, -4.93810279e-03, -1.38629349e-02, -2.76805442e-02],
      dtype=float32), array([ 1.57342572e-02,  2.94730756e-02, -2.84424145e-02,  2.78733224e-02,
        3.68545763e-02,  4.12211306e-02,  3.69412787e-02,  4.62167785e-02,
        1.33691663e-02,  9.17457882e-03, -4.09358554e-02, -1.40508087e-02,
       -1.89132653e-02,  7.96701945e-03,  3.45746838e-02, -9.98705905e-03,
       -6.88355882e-03,  1.05700739e-01, -3.81619893e-02,  2.57830862e-02,
       -1.61446668e-02,  2.58783903e-02, -3.58586462e-04, -4.45712693e-02,
       -5.14645353e-02,  2.36799605e-02,  5.85137904e-02, -3.03026680e-02,
       -2.73526050e-02,  3.45451618e-03,  3.48636806e-02,  3.36036906e-02,
       -2.10191663e-02,  5.86573482e-02, -7.46746268e-03, -3.65933664e-02,
       -1.16672209e-02, -6.47566095e-02, -4.38552089e-02, -1.91160105e-02,
        2.37177815e-02,  4.57603671e-02,  1.54269887e-02,  4.96819243e-02,
        3.69436964e-02,  3.39617883e-03,  2.81003267e-02,  6.67354465e-02,
        4.70167361e-02,  9.96992178e-03, -4.24800999e-02, -6.17218092e-02,
        7.67274126e-02,  4.55961898e-02,  2.83698328e-02, -5.17613478e-02,
       -8.55926350e-02,  2.86468435e-02, -4.53321896e-02, -3.08045372e-02,
        4.82961710e-04,  1.64125040e-02,  6.72085071e-03, -4.70592193e-02,
        4.35379520e-03, -2.99363839e-03,  1.67489611e-02,  3.04362364e-02,
        3.85623681e-03, -6.14526421e-02, -8.15287419e-03,  1.91658176e-02,
       -3.23524326e-02,  2.64048669e-02,  9.64413106e-04, -6.72295913e-02,
       -1.44514721e-02,  2.00315546e-02, -1.56554137e-03,  6.09969161e-03,
        4.46043834e-02,  3.80851291e-02, -3.08061652e-02,  3.60706337e-02,
        6.46995530e-02, -1.11826463e-02, -5.82779665e-03, -3.54477242e-02,
       -4.11066674e-02, -9.47162771e-05, -2.67184190e-02,  5.13631962e-02,
       -3.32741290e-02, -3.38824876e-02,  1.07281916e-01,  8.14340934e-02,
        8.96866545e-02,  4.41300087e-02,  2.28427760e-02, -4.09434736e-02,
       -1.64236389e-02, -2.55033243e-02,  6.08736612e-02, -4.60095704e-02,
       -3.36265587e-03, -2.61185840e-02,  5.54529727e-02, -1.67436264e-02,
        4.64142337e-02, -3.02727949e-02, -3.12383100e-02, -1.70858968e-02,
       -1.94741301e-02,  7.47201741e-02,  1.45096844e-02,  3.41717564e-02,
        3.27980109e-02,  3.38764265e-02, -1.17706601e-02,  3.79524827e-02,
        7.75890723e-02,  2.00084243e-02,  2.85997093e-02,  7.19018802e-02,
        3.65240909e-02,  4.73168492e-03, -6.71297014e-02,  4.75924015e-02,
        2.66371332e-02, -2.16669105e-02, -4.08845767e-02,  8.36082548e-02,
        7.95168206e-02, -1.90598778e-02, -3.01075615e-02, -3.69826183e-02,
        4.17081378e-02,  5.51204830e-02,  6.96967468e-02, -2.70224456e-02,
        2.82333349e-04,  5.11370972e-03, -3.89116630e-02,  1.75031498e-02,
       -5.74968457e-02, -5.51850051e-02,  5.32673411e-02,  2.13537104e-02,
       -1.77604686e-02, -8.41201190e-03, -1.13885365e-02, -2.91448142e-02,
       -2.18155738e-02,  2.84069702e-02,  6.41007721e-02, -3.86053100e-02,
        5.77452406e-02,  2.15478074e-02, -6.26086118e-03, -3.85004692e-02,
       -2.81068310e-02,  4.73451018e-02,  2.14890521e-02,  4.30776849e-02,
       -1.84350107e-02,  2.86993422e-02, -6.80205366e-03, -5.24000786e-02,
        3.54023166e-02,  2.28647497e-02, -1.60703920e-02,  4.88098040e-02,
       -3.42168696e-02,  1.71097256e-02,  1.93473231e-02,  6.62537888e-02,
       -2.45373361e-02, -3.59857380e-02,  4.35955934e-02,  1.08686881e-02,
        4.33432683e-02,  3.10299583e-02,  2.40236558e-02,  1.23975864e-02,
        9.63768512e-02, -1.22541459e-02,  1.82636250e-02, -2.15376932e-02,
        1.01909172e-02, -1.83393098e-02,  1.55553943e-03, -1.24556199e-02,
        1.48856714e-02, -3.51730399e-02, -4.29814830e-02,  3.08647472e-02,
        2.05103774e-03,  3.45321037e-02, -4.06223945e-02,  5.67850377e-03,
        2.31072549e-02, -3.76215056e-02,  2.96187457e-02, -3.98024321e-02,
        6.88269064e-02,  2.77646575e-02,  7.50641525e-03, -3.04656439e-02,
        1.47917140e-02,  7.24808723e-02,  2.79689077e-02,  3.05996202e-02,
       -1.22613739e-02, -3.57285626e-02, -6.35142578e-03, -2.34954488e-02,
       -3.67291272e-02,  2.78614536e-02, -2.92597879e-02, -3.34883966e-02,
       -2.02085450e-02,  5.80581054e-02,  6.42470270e-02,  7.80587737e-03,
       -2.63220686e-02, -1.98328197e-02, -1.23525842e-03, -2.41005179e-02,
        5.08257858e-02,  5.22559546e-02,  6.62579089e-02,  2.32916530e-02,
       -3.42500173e-02,  6.73861150e-03, -2.03218888e-02, -1.11322319e-02,
        1.56115089e-02,  6.21820427e-03,  5.70051111e-02,  5.50719686e-02,
       -4.40801568e-02,  5.99932782e-02,  2.51215938e-02,  2.36451998e-02,
        1.62863974e-02,  5.02374619e-02,  1.34011013e-02,  2.72863284e-02,
        5.10658026e-02,  6.83011040e-02, -1.46738281e-02,  3.95463854e-02,
        2.27813553e-02, -4.88788486e-02, -3.06784492e-02,  5.80533296e-02,
        9.42116044e-03,  1.28691327e-02, -5.44966257e-04, -7.03196041e-03,
        1.53649570e-02,  6.34478852e-02,  9.55004152e-03, -1.50754070e-02,
        4.34905402e-02,  1.23576351e-01, -3.64501327e-02,  3.81344035e-02,
       -3.35176289e-02,  4.17005382e-02, -3.40784155e-02,  6.28428254e-03,
       -1.75429266e-02,  1.00376485e-02,  1.01623423e-02,  4.00585234e-02,
        1.15454067e-02, -5.14528193e-02,  1.49746109e-02,  5.11870906e-02,
       -5.69986179e-02, -1.39461346e-02, -1.72067638e-02,  5.30652106e-02,
        5.28342016e-02, -6.20172694e-02,  5.08039584e-03, -1.62032824e-02,
        5.68244904e-02, -2.79608052e-02, -6.93009060e-04,  3.80537100e-02,
        4.26685512e-02, -1.27091659e-02,  1.06586097e-02,  1.01770952e-01,
       -3.64084877e-02, -2.98385248e-02,  4.57194773e-03,  5.65514900e-02,
       -8.19753017e-03, -2.70544682e-02,  2.12592259e-02,  2.84882877e-02,
       -5.55048650e-03, -5.17438017e-02,  2.92985085e-02, -4.68049794e-02,
       -7.69612705e-03,  1.14169233e-02,  9.61363502e-03,  2.72373594e-02,
       -2.68003647e-03,  3.60235907e-02,  6.45208508e-02, -9.22265276e-03,
        4.12490629e-02, -3.96162346e-02,  8.57949406e-02,  1.42770838e-02,
        2.43894849e-03,  3.18300240e-02,  6.11080527e-02,  5.93667515e-02,
        3.43257710e-02, -4.06018719e-02, -2.91258395e-02, -4.90940437e-02,
       -1.97657980e-02,  9.08017531e-03, -2.13430859e-02,  8.56922008e-03,
       -1.50713604e-02, -2.21764576e-02,  4.14512902e-02,  7.29268696e-03,
       -4.20584455e-02,  3.76141705e-02, -3.45445378e-03, -2.10597627e-02,
        5.93374930e-02, -1.94942355e-02,  3.29855420e-02, -4.08811122e-02,
       -1.50995562e-02, -7.45381787e-03,  5.15413936e-03,  6.67023705e-04,
       -6.44623339e-02, -2.18492057e-02, -6.07586605e-03, -3.30606885e-02,
       -2.71521304e-02,  5.79244085e-02, -6.44402159e-03, -1.17980819e-02,
       -3.80949378e-02,  4.03897427e-02,  5.47405668e-02, -2.02378668e-02,
        6.94728941e-02, -1.44346552e-02,  2.01889332e-02,  4.50045094e-02,
       -5.75180650e-02,  1.72990374e-02,  7.31954351e-02,  5.20626362e-03,
       -4.36494648e-02, -3.19006555e-02, -6.07861625e-03, -1.03797484e-02,
        3.64751592e-02, -3.08574773e-02,  4.56531160e-02,  4.55853976e-02,
        5.97284772e-02, -2.18146993e-03, -2.55448837e-02,  2.27257423e-02,
        3.96215767e-02, -4.63814400e-02,  6.42687231e-02,  9.01261624e-03,
        9.01781768e-02,  3.28675732e-02,  3.66213061e-02,  4.14781459e-02,
        2.03226935e-02, -5.18734800e-04,  3.01636010e-02,  2.45770942e-02,
        5.34386858e-02, -4.26333323e-02, -2.40160450e-02,  3.09032272e-03,
        3.44678201e-02,  3.95902917e-02,  7.41145685e-02,  8.33330825e-02,
        2.46125478e-02,  1.27314469e-02,  9.28809196e-02, -7.27166235e-02,
        2.96834912e-02,  6.79528713e-02,  5.32073788e-02,  4.81185839e-02,
       -5.92429452e-02, -2.10390557e-02,  1.78375151e-02,  1.54873133e-02,
        5.83878197e-02,  3.84202898e-02,  5.29750064e-02, -1.65133215e-02,
       -2.17977259e-02,  5.41573837e-02,  1.61268245e-02,  4.41834666e-02,
       -3.59994639e-03, -1.69310775e-02,  4.96398509e-02, -1.56960003e-02,
       -1.25429621e-02,  5.79162650e-02, -2.09836755e-02,  1.59512702e-02,
       -4.04012650e-02,  3.65490019e-02,  6.84925839e-02,  3.88962589e-02,
       -4.38184217e-02, -9.69639327e-03,  5.16611114e-02, -1.98703445e-02,
        7.99685195e-02, -3.13489549e-02, -4.19891924e-02,  3.23909186e-02,
        5.33530349e-03,  1.38749946e-02, -2.09628176e-02,  1.74809750e-02,
        2.37439331e-02, -2.46383473e-02, -5.24808839e-03, -2.47044507e-02,
        5.31510971e-02,  2.35466491e-02,  8.57377350e-02,  4.54704240e-02,
       -1.74574517e-02,  7.54343793e-02,  6.44879565e-02,  4.11840864e-02,
        2.21142024e-02, -4.54897322e-02,  1.37373507e-02,  1.50416549e-02,
        6.17342331e-02,  2.44682860e-02,  4.68229316e-02, -2.40279548e-03,
       -3.68395373e-02,  4.33162153e-02, -2.96513308e-02, -9.61857382e-03,
       -4.80277203e-02,  3.98375057e-02,  7.32228607e-02,  7.42940456e-02,
        7.54320621e-03, -9.01249796e-03,  5.63477874e-02,  7.28916675e-02,
       -2.85612438e-02,  4.63689975e-02, -2.94733010e-02,  3.32015231e-02,
       -3.48412767e-02, -4.12310585e-02, -3.66246291e-02, -2.37611346e-02,
       -3.97217311e-02,  3.03936824e-02,  7.23282248e-02, -5.33941276e-02,
        2.59195138e-02,  4.57470044e-02, -2.63139978e-03,  1.36580030e-02,
       -1.51385982e-02,  1.15052816e-02, -1.49585297e-02, -3.70883197e-02,
       -2.33935639e-02,  5.75385354e-02, -4.79776934e-02,  1.50936004e-02,
        9.41387191e-02, -4.02173586e-03,  8.28904361e-02,  5.95102608e-02,
        6.99694529e-02,  1.71977952e-02, -4.40821536e-02,  2.06718594e-02,
        2.48679556e-02, -2.25398932e-02,  4.74854298e-02, -1.42963091e-02,
        1.64835043e-02,  3.24682966e-02,  1.35732759e-02, -3.77407819e-02,
        3.06580439e-02,  2.26290012e-03,  3.51548521e-03,  2.42290460e-02,
        5.09748273e-02, -3.48731503e-03,  3.33296545e-02, -4.72921208e-02,
       -1.74589902e-02, -2.50408500e-02,  1.18068149e-02, -1.66129544e-02,
        3.90063897e-02, -5.61178960e-02,  1.90530382e-02,  4.86475267e-02,
        2.93939915e-02,  3.06571815e-02, -5.08109443e-02,  4.05176766e-02,
        6.80550560e-02, -8.84068199e-03,  1.81560572e-02,  4.98502292e-02,
       -1.45985307e-02, -6.64273947e-02, -2.74343565e-02,  3.52079980e-02,
       -3.54668498e-02,  5.81879914e-02,  2.96617392e-02, -2.84720305e-02,
        6.77227825e-02,  7.88384825e-02, -2.07890999e-02, -3.69496047e-02,
       -2.89493836e-02, -5.01740314e-02,  4.47692014e-02, -2.34854482e-02,
       -3.23018208e-02, -4.30673473e-02, -4.65533920e-02,  1.74367409e-02,
        1.51144238e-02, -1.46230329e-02,  5.83259240e-02, -3.05621773e-02,
       -1.17874295e-02, -4.88399947e-03,  2.64943074e-02, -2.98559703e-02,
        9.75646675e-02, -3.31700966e-02, -2.65441351e-02, -1.61093231e-02,
       -1.74290258e-02, -1.88685171e-02, -1.32215219e-02,  6.18336834e-02,
        5.00507280e-02,  7.56561197e-03, -1.83656961e-02, -1.19083782e-03,
       -2.17168890e-02,  9.75499395e-03,  3.95825095e-02, -4.92309555e-02,
        2.79058274e-02, -2.98974719e-02,  2.55520456e-02, -3.24075073e-02,
        1.52968159e-02, -2.41635181e-02, -4.70384061e-02, -2.49514338e-02,
       -3.21525708e-02, -2.31674407e-02, -5.51934987e-02, -3.81326079e-02,
        1.36740860e-02,  1.66307800e-02,  3.66706885e-02,  5.80900460e-02,
       -1.53026897e-02, -6.63457625e-03,  2.98307817e-02, -1.26044611e-02,
       -3.40856947e-02,  7.80393481e-02, -2.26349346e-02,  3.56441885e-02,
        5.62450141e-02, -1.75477620e-02, -7.38041103e-03, -1.04412334e-02,
        2.35273968e-02, -3.77285220e-02,  5.79331219e-02,  7.02589676e-02,
       -3.62022058e-03,  2.88026426e-02,  7.96288624e-03,  2.88649984e-02,
        2.11276393e-02,  7.41503909e-02, -2.41912808e-02,  2.99831200e-02,
        2.98843272e-02, -2.49586422e-02, -3.17606591e-02, -1.21474648e-02,
        1.44554172e-02, -1.83284618e-02, -4.86470992e-03,  3.78818959e-02,
        6.14865236e-02,  2.46663522e-02, -1.77388694e-02,  2.37743044e-03,
       -4.80737425e-02,  4.11548167e-02, -1.73013005e-02,  4.49747546e-03,
       -3.16556431e-02,  5.03069535e-02,  5.28354831e-02,  7.32997879e-02,
        4.40532379e-02,  5.41675352e-02, -2.61400025e-02, -2.46415157e-02,
       -6.83724582e-02,  7.46556967e-02, -4.24629115e-02, -3.31672169e-02,
        8.70468270e-04, -2.72613186e-02,  4.55906987e-02, -1.57130975e-02,
       -4.41348217e-02,  5.49976751e-02,  2.43047886e-02, -5.09051159e-02,
        5.32809906e-02, -6.13583513e-02,  4.21557352e-02,  4.39379402e-02,
       -1.59744136e-02,  1.04235671e-02, -3.71497981e-02,  1.81837622e-02,
        1.86863746e-02,  1.07491091e-02,  1.75358634e-02, -1.14975860e-02,
        8.39760061e-03,  2.48301886e-02,  1.25162452e-02, -1.93501618e-02,
        2.22339034e-02, -3.94691005e-02,  7.03876093e-02, -2.80338340e-03,
       -3.69796006e-04,  2.63573099e-02, -1.13054188e-02, -4.60884050e-02,
        1.40437931e-02,  6.97130337e-03,  2.51058619e-02,  6.85214028e-02,
       -6.28529936e-02,  3.03038340e-02, -1.41489608e-02,  7.28394911e-02,
       -2.95851063e-02,  3.79768051e-02,  1.51299341e-02, -1.49149299e-02,
       -1.64413378e-02,  3.74045484e-02, -6.63486198e-02, -4.69225310e-02,
        5.33510819e-02, -9.93271638e-03,  7.67823979e-02, -3.36201750e-02,
        4.61870097e-02, -4.44444492e-02,  2.46648286e-02, -5.64566907e-03,
       -1.07544765e-03, -4.29994939e-03,  1.37780150e-02,  8.00793339e-03,
        4.29238118e-02,  3.87257859e-02, -3.72304618e-02, -3.76334116e-02,
        1.56540778e-02, -3.54636684e-02,  5.26649281e-02,  1.73206422e-02,
        8.87448259e-04,  4.79097478e-02,  3.62585820e-02,  2.22430285e-02,
        1.08805308e-02, -2.67221164e-02, -1.91629976e-02,  4.86034416e-02],
      dtype=float32), array([0.08371846, 0.10281044, 0.0988948 , 0.10591667, 0.09394772,
       0.08696013, 0.09879629, 0.09283704, 0.08627153, 0.08624127,
       0.09677649, 0.0834644 , 0.09071626, 0.08536255, 0.09144548,
       0.0904692 , 0.08352404, 0.1119433 , 0.08804104, 0.08879372,
       0.09365401, 0.09337986, 0.0870043 , 0.09771825, 0.09626181,
       0.10732825, 0.10277601, 0.08920085, 0.09904522, 0.08389554,
       0.08863657, 0.09102511, 0.09027383, 0.1032883 , 0.0849454 ,
       0.08876111, 0.09120681, 0.09159693, 0.08967193, 0.08267774,
       0.08319098, 0.09306657, 0.0892542 , 0.09589141, 0.09116486,
       0.08352997, 0.08341213, 0.09436242, 0.09092442, 0.08825831,
       0.09790248, 0.0981302 , 0.12030234, 0.09298988, 0.08936299,
       0.08971677, 0.11560354, 0.08593468, 0.09015625, 0.09143615,
       0.08215704, 0.08832291, 0.08249642, 0.0927756 , 0.08659708,
       0.0876559 , 0.08388449, 0.08982398, 0.10577569, 0.09909865,
       0.08257074, 0.08613604, 0.09626289, 0.08961652, 0.08303481,
       0.10493945, 0.08304782, 0.08937189, 0.08819818, 0.08647248,
       0.09959016, 0.09047507, 0.08872274, 0.09996445, 0.11712318,
       0.09029185, 0.0932804 , 0.08574095, 0.09092633, 0.08378046,
       0.088952  , 0.09814017, 0.09898646, 0.09064884, 0.11300335,
       0.10134467, 0.11257508, 0.12200084, 0.09520759, 0.09674657,
       0.08526506, 0.0937889 , 0.09405338, 0.09961825, 0.08356605,
       0.08697508, 0.1044198 , 0.08706089, 0.09454601, 0.0915152 ,
       0.08283765, 0.08276413, 0.08367087, 0.10967354, 0.09507282,
       0.08919893, 0.08969771, 0.095654  , 0.09288127, 0.11150651,
       0.10716288, 0.08411225, 0.09907541, 0.10223778, 0.0983466 ,
       0.0889078 , 0.09284971, 0.11317072, 0.08904238, 0.08677766,
       0.0998644 , 0.0996011 , 0.11593661, 0.0844538 , 0.08524828,
       0.08862797, 0.08993178, 0.09438115, 0.10098242, 0.08722524,
       0.09410923, 0.09220181, 0.10357945, 0.09598531, 0.09537566,
       0.10304815, 0.10123493, 0.0957752 , 0.08698174, 0.08377954,
       0.08866788, 0.08745799, 0.0948304 , 0.08917858, 0.10991129,
       0.08631268, 0.09863167, 0.09717435, 0.08605845, 0.08485154,
       0.08176866, 0.09462512, 0.09152798, 0.08615955, 0.08984955,
       0.08259793, 0.08542023, 0.10344549, 0.09390476, 0.08671675,
       0.08906116, 0.10574015, 0.09064712, 0.09940159, 0.10971133,
       0.10005693, 0.08987794, 0.08969773, 0.08526279, 0.08504704,
       0.09080591, 0.0856229 , 0.11273431, 0.08489707, 0.11682614,
       0.09019408, 0.09133689, 0.08279665, 0.0877056 , 0.08472368,
       0.08860358, 0.08476616, 0.08524735, 0.09450216, 0.08768637,
       0.08561908, 0.08701584, 0.08910334, 0.09329808, 0.08728524,
       0.0986362 , 0.0848688 , 0.08868688, 0.0870615 , 0.09844612,
       0.09086348, 0.08511349, 0.08942753, 0.10365485, 0.10215901,
       0.1025465 , 0.0888841 , 0.08485661, 0.08822767, 0.084546  ,
       0.08659317, 0.09646954, 0.09180401, 0.08618264, 0.10800968,
       0.08671408, 0.10350689, 0.10492618, 0.08331724, 0.09087123,
       0.09372201, 0.08519978, 0.0863014 , 0.10737429, 0.0989883 ,
       0.08824525, 0.09141386, 0.09189333, 0.08387425, 0.08295984,
       0.087905  , 0.0842701 , 0.08458556, 0.1014212 , 0.09970874,
       0.08966947, 0.09423792, 0.08906418, 0.10858131, 0.08887079,
       0.09760421, 0.08450302, 0.09024503, 0.09685055, 0.10441434,
       0.08932776, 0.10272682, 0.08983047, 0.09257281, 0.09188256,
       0.10631652, 0.08347985, 0.0855311 , 0.08299165, 0.08482652,
       0.09589935, 0.10872269, 0.08769856, 0.09131572, 0.08838022,
       0.11577994, 0.08892299, 0.08761946, 0.08682793, 0.09525396,
       0.08247625, 0.08349146, 0.08971305, 0.09302334, 0.08389148,
       0.1299564 , 0.10052221, 0.09084471, 0.09678715, 0.0876677 ,
       0.11442332, 0.08462954, 0.08506434, 0.09188171, 0.10985927,
       0.09394872, 0.08584374, 0.08424238, 0.09515092, 0.08493056,
       0.08348828, 0.09223837, 0.10942756, 0.09540395, 0.08311319,
       0.10694373, 0.08639958, 0.08702287, 0.08283577, 0.0960812 ,
       0.09045547, 0.08933374, 0.09126698, 0.09784265, 0.08477394,
       0.08857305, 0.08858852, 0.09308696, 0.08673827, 0.08149761,
       0.09722323, 0.08819093, 0.0937846 , 0.08344303, 0.10163851,
       0.08875597, 0.08863566, 0.089646  , 0.10046005, 0.09109154,
       0.08957068, 0.09072367, 0.10454486, 0.09390292, 0.08614184,
       0.08334739, 0.08361843, 0.09901631, 0.08738979, 0.08364978,
       0.08526614, 0.08461367, 0.09016507, 0.09012229, 0.08875801,
       0.08632385, 0.09082071, 0.09368002, 0.08351992, 0.09403002,
       0.12081634, 0.09551755, 0.09116738, 0.09612714, 0.0860987 ,
       0.08370332, 0.08369374, 0.09043712, 0.10425416, 0.10211404,
       0.08306652, 0.08545524, 0.08376124, 0.10861306, 0.0866285 ,
       0.0845793 , 0.08949115, 0.09089132, 0.10881676, 0.09161812,
       0.10326154, 0.09092487, 0.08763778, 0.09847133, 0.09652996,
       0.09082831, 0.1013952 , 0.08481628, 0.09521038, 0.08597475,
       0.08276627, 0.08230148, 0.10409235, 0.08341409, 0.09062042,
       0.08928961, 0.08856855, 0.08420245, 0.09635978, 0.08317069,
       0.09779052, 0.09496643, 0.09972461, 0.08857871, 0.09889913,
       0.09702617, 0.10321104, 0.09091657, 0.08545589, 0.08271899,
       0.10475808, 0.08952274, 0.1005268 , 0.08661009, 0.08553728,
       0.08856028, 0.09282494, 0.09263709, 0.11192278, 0.10679659,
       0.09256048, 0.08484464, 0.10812933, 0.11643726, 0.09575419,
       0.10399597, 0.10219162, 0.09553333, 0.09945364, 0.0872414 ,
       0.09076034, 0.08888385, 0.09896515, 0.09716981, 0.09438391,
       0.08549252, 0.08647159, 0.09667102, 0.08647273, 0.09203325,
       0.08510233, 0.08438842, 0.08882707, 0.09553763, 0.08346881,
       0.10441536, 0.08681201, 0.08333426, 0.08483832, 0.09598906,
       0.09747408, 0.09515677, 0.10106647, 0.09253786, 0.09732189,
       0.08921412, 0.11323406, 0.08437234, 0.08653063, 0.08967614,
       0.09052595, 0.08652657, 0.08544877, 0.08953283, 0.09102408,
       0.08710175, 0.08319694, 0.08782069, 0.090138  , 0.08802206,
       0.12047801, 0.09803626, 0.08807379, 0.10932774, 0.1007966 ,
       0.09577809, 0.093986  , 0.0896263 , 0.09296895, 0.09350544,
       0.08862175, 0.09377436, 0.09126615, 0.08498482, 0.09510133,
       0.0975586 , 0.08826447, 0.09411827, 0.09570281, 0.09233416,
       0.10201346, 0.10292132, 0.08760764, 0.08606157, 0.09245742,
       0.12238976, 0.09004251, 0.0997316 , 0.09093452, 0.08964776,
       0.08660123, 0.11116572, 0.09665123, 0.08384985, 0.09462072,
       0.09168296, 0.09802863, 0.10874736, 0.08430993, 0.10116738,
       0.08555349, 0.08840457, 0.08862241, 0.08550137, 0.08721942,
       0.08816968, 0.08662087, 0.09713271, 0.09442071, 0.08304912,
       0.10965546, 0.08743429, 0.12153699, 0.14484815, 0.10681068,
       0.08504689, 0.0892262 , 0.0933603 , 0.08912636, 0.09024525,
       0.08801086, 0.08447737, 0.0994293 , 0.08617425, 0.08639511,
       0.09690674, 0.12311646, 0.08605574, 0.0975381 , 0.09253496,
       0.09500641, 0.09027673, 0.09004401, 0.11053842, 0.09054512,
       0.09892575, 0.08653393, 0.08363569, 0.09530795, 0.09549797,
       0.08379295, 0.08915996, 0.08716342, 0.09086125, 0.08581348,
       0.10089079, 0.10319827, 0.08236019, 0.08792573, 0.1010909 ,
       0.08308096, 0.10515446, 0.08391513, 0.10015534, 0.08439521,
       0.09282182, 0.08666711, 0.08791129, 0.10649166, 0.10910141,
       0.08654583, 0.09287271, 0.08880644, 0.08481123, 0.09977049,
       0.08889446, 0.09611984, 0.08815085, 0.08871397, 0.09922221,
       0.08490761, 0.08263553, 0.0922635 , 0.09796772, 0.08586395,
       0.09693268, 0.09321927, 0.09031817, 0.10901969, 0.09589922,
       0.09329787, 0.10209222, 0.09053294, 0.1023929 , 0.08780967,
       0.10674647, 0.09625699, 0.08754355, 0.08860637, 0.09341048,
       0.09128593, 0.09254432, 0.09382353, 0.10261305, 0.08939508,
       0.08212295, 0.08325343, 0.08311228, 0.08675808, 0.08434992,
       0.10604666, 0.08473147, 0.09327391, 0.08602609, 0.0966013 ,
       0.09885702, 0.08672994, 0.08250776, 0.09924202, 0.10707771,
       0.08416145, 0.08683103, 0.0955259 , 0.08482263, 0.08712512,
       0.10998945, 0.09024949, 0.09033539, 0.10604057, 0.08923643,
       0.09107591, 0.08412823, 0.09642521, 0.087575  , 0.11009552,
       0.11606256, 0.086586  , 0.08718854, 0.09884323, 0.08592154,
       0.09112838, 0.10465158, 0.08714782, 0.09250797, 0.08660281,
       0.09653997, 0.09047511, 0.08458465, 0.09726707, 0.08841497,
       0.08264732, 0.08529732, 0.11225726, 0.08801392, 0.08291512,
       0.09339727, 0.09257694, 0.09654516, 0.08843961, 0.08759921,
       0.09388996, 0.09916631, 0.09476285, 0.09660491, 0.11136927,
       0.11231327, 0.09307669, 0.08803207, 0.08958472, 0.09698663,
       0.09049543, 0.08437335, 0.08334386, 0.08476787, 0.10923885,
       0.09390632, 0.0891655 , 0.10371536, 0.088054  , 0.09368756,
       0.09434301, 0.11977498, 0.08758252, 0.10146644, 0.089344  ,
       0.08957428, 0.08811008, 0.08649334, 0.08914889, 0.08472441,
       0.09044566, 0.0856559 , 0.09447286, 0.08381063, 0.08602241,
       0.08356915, 0.08759163, 0.10833144, 0.10045203, 0.08489562,
       0.08383121, 0.09527342, 0.09085928, 0.0880786 , 0.10598647,
       0.08543614, 0.09007694, 0.09923157, 0.09891607, 0.0913403 ,
       0.08761027, 0.12143781, 0.10209908, 0.08941543, 0.08467385,
       0.08442957, 0.08340045, 0.09299595, 0.10052451, 0.09341372,
       0.1007885 , 0.08472839, 0.09587266, 0.08360069, 0.10184306,
       0.09123825, 0.09125644, 0.08593339, 0.08466882, 0.0839735 ,
       0.10237836, 0.09077292, 0.09051384, 0.09647849, 0.09633602,
       0.09692738, 0.08644688, 0.09729775, 0.09990686, 0.09050319,
       0.09629129, 0.09425147, 0.09876461, 0.09579784, 0.0876823 ,
       0.08578518, 0.09090003, 0.09759164], dtype=float32), array([[[[-0.00966382],
         [ 0.00138313],
         [-0.01536067],
         ...,
         [ 0.01276962],
         [-0.02310641],
         [-0.01133359]],

        [[ 0.00274641],
         [-0.02430454],
         [-0.01313395],
         ...,
         [-0.0009325 ],
         [ 0.01677124],
         [ 0.0164407 ]],

        [[ 0.01886458],
         [-0.02858962],
         [ 0.01072373],
         ...,
         [-0.01331473],
         [ 0.01614923],
         [ 0.02677903]]],


       [[[ 0.03341086],
         [ 0.02954072],
         [-0.00705308],
         ...,
         [ 0.00876327],
         [-0.00228702],
         [-0.02880057]],

        [[-0.0051037 ],
         [ 0.01725282],
         [-0.0310955 ],
         ...,
         [ 0.00689065],
         [-0.02197231],
         [ 0.00409761]],

        [[-0.00450212],
         [-0.00243729],
         [-0.04088166],
         ...,
         [-0.00042819],
         [ 0.00793687],
         [ 0.02014859]]],


       [[[-0.02041803],
         [ 0.01845242],
         [-0.01225286],
         ...,
         [ 0.02542223],
         [-0.00073863],
         [-0.01356989]],

        [[-0.00294006],
         [ 0.00189003],
         [-0.0139157 ],
         ...,
         [-0.02625563],
         [ 0.00582245],
         [-0.03456105]],

        [[-0.01726605],
         [ 0.03304042],
         [-0.02386427],
         ...,
         [-0.01504923],
         [-0.01968097],
         [ 0.01093122]]]], dtype=float32), array([[[[ 0.04244674,  0.03189551, -0.06418572, ...,  0.05450214,
          -0.02438055, -0.03332568],
         [ 0.02364254,  0.02452822,  0.05051214, ...,  0.00638511,
          -0.04561267,  0.0507519 ],
         [-0.05720939,  0.0078116 ,  0.01974991, ..., -0.04067177,
           0.0068884 , -0.00672103],
         ...,
         [-0.04542444, -0.03066052,  0.02126258, ..., -0.03800054,
           0.02330265, -0.01936592],
         [ 0.04641129, -0.01115616, -0.04631429, ...,  0.04591732,
           0.02533749, -0.02174044],
         [-0.00720708,  0.0186937 ,  0.05291527, ...,  0.07501035,
           0.04674683,  0.00611724]]]], dtype=float32), array([1.0051218 , 0.9896687 , 0.9990852 , 0.9987022 , 0.98177636,
       1.0049783 , 0.9936522 , 1.0005962 , 0.9890318 , 0.99166816,
       0.9999531 , 1.0034897 , 1.0058192 , 1.0101451 , 0.99371445,
       0.9939874 , 0.98042464, 0.9941805 , 1.0405105 , 1.0000685 ,
       0.9977461 , 0.9897065 , 0.9922856 , 0.9942324 , 0.9972432 ,
       0.9995277 , 0.99893   , 0.98757195, 1.009862  , 1.0004439 ,
       1.0173665 , 1.029015  , 0.9970075 , 1.0136888 , 1.0064071 ,
       1.0069039 , 0.9986801 , 1.0012875 , 1.0079961 , 0.9952766 ,
       1.020821  , 1.0114247 , 1.0077783 , 1.0093496 , 1.0068083 ,
       0.9922493 , 1.0082695 , 0.9875248 , 0.9812964 , 1.0122293 ,
       1.0144881 , 1.0078788 , 0.99266034, 0.98137146, 0.9857245 ,
       1.0380138 , 0.98525643, 1.0018361 , 0.9844706 , 0.99187803,
       0.9879209 , 1.025305  , 1.0114853 , 1.003841  , 0.99782264,
       1.0077735 , 0.99500996, 1.012362  , 1.0031703 , 0.9871703 ,
       1.0029193 , 1.0056378 , 1.0000999 , 1.0019925 , 0.9985627 ,
       0.9792755 , 0.9971254 , 1.0039768 , 0.9958184 , 0.9939158 ,
       0.9675469 , 1.018942  , 0.97537905, 0.9897752 , 1.0010777 ,
       0.9947766 , 0.9906894 , 1.0236902 , 0.994869  , 1.0248344 ,
       0.99331117, 0.98356026, 0.99244833, 0.99750054, 0.99923444,
       0.9957223 , 0.98780787, 0.99585575, 1.0116407 , 1.019204  ,
       1.0012941 , 1.0122888 , 0.98596376, 1.0095649 , 0.99754876,
       1.0021726 , 1.0052775 , 0.97948617, 1.0114713 , 1.0131315 ,
       0.9849627 , 0.9978136 , 1.0081605 , 0.995033  , 0.9990606 ,
       0.9960519 , 1.0065769 , 0.9919643 , 1.0146439 , 0.99928427,
       0.99662465, 0.990533  , 0.9733914 , 1.0010041 , 0.9951714 ,
       1.0013129 , 0.9906411 , 1.0031182 , 0.9708986 , 1.0027109 ,
       0.98565215, 0.9964292 , 1.0044326 , 0.9996635 , 1.0057635 ,
       0.9811719 , 1.0080785 , 0.9606169 , 0.99536073, 0.99526775,
       0.96396065, 0.985807  , 1.0140195 , 0.9970857 , 0.98780966,
       0.98927027, 1.0094143 , 1.0189016 , 1.0031241 , 0.9934533 ,
       0.9879077 , 1.0063108 , 1.0098069 , 0.98063135, 0.9966004 ,
       0.995907  , 0.9932265 , 0.9978552 , 0.986296  , 1.004608  ,
       0.9690738 , 0.9969182 , 0.9899134 , 0.98379177, 0.9960379 ,
       0.98343086, 1.0148426 , 0.98872817, 0.99989223, 0.9965612 ,
       0.999336  , 1.01773   , 1.0100908 , 1.0209026 , 0.98876417,
       1.007365  , 0.9905921 , 0.9929072 , 0.9898789 , 0.99685425,
       1.0064901 , 1.0027813 , 0.9899828 , 0.99781525, 1.0054702 ,
       1.0034132 , 0.99580175, 1.0052782 , 0.99309856, 0.991616  ,
       0.99610645, 1.0082271 , 0.9919551 , 0.9946438 , 0.985303  ,
       1.0013921 , 0.9891165 , 1.0003713 , 1.000647  , 0.97740006,
       0.98197967, 1.0031555 , 1.0092927 , 0.99349743, 1.0049434 ,
       1.0103996 , 0.99112874, 0.96884173, 0.98996085, 1.0083367 ,
       0.9958608 , 1.0107412 , 0.9999901 , 0.98449266, 1.0039603 ,
       1.0018408 , 0.99213225, 0.97882396, 0.9875377 , 0.9984396 ,
       1.004009  , 1.0036178 , 0.9959785 , 1.0022081 , 0.9986019 ,
       1.0106165 , 0.99741375, 1.0117874 , 1.0028225 , 1.0153832 ,
       1.005381  , 0.9927202 , 1.0150564 , 0.9882209 , 0.9910773 ,
       1.0079907 , 0.9749765 , 1.0151168 , 0.9872509 , 0.99706817,
       1.0014868 , 0.98768604, 0.99185884, 1.0028965 , 0.9974138 ,
       0.9820667 , 1.0139179 , 0.99034214, 1.0175594 , 1.0130482 ,
       0.9689012 , 0.99136883, 1.0041269 , 1.0202459 , 1.0003183 ,
       0.9858398 , 0.9985199 , 1.0003086 , 1.0192909 , 0.98162794,
       0.9716147 , 1.0099794 , 1.0209413 , 0.9964343 , 0.9996137 ,
       0.992645  , 0.99448127, 1.0015241 , 1.0036744 , 1.0042902 ,
       0.99366283, 1.0006505 , 1.0045049 , 1.0029318 , 0.9852194 ,
       1.0052804 , 1.0084491 , 0.99014384, 0.9870931 , 1.0085168 ,
       1.0051734 , 1.0056536 , 1.00384   , 1.0048912 , 0.9990991 ,
       0.9975125 , 1.0051657 , 0.9936059 , 0.989154  , 0.996883  ,
       1.0059627 , 1.0103265 , 1.0044874 , 0.9953363 , 1.0048492 ,
       1.0187933 , 0.9810088 , 0.9919876 , 0.98204374, 1.0002118 ,
       0.9840859 , 0.97438926, 1.0075725 , 0.9962071 , 1.0089096 ,
       1.0164586 , 0.98159957, 0.99006414, 1.0133518 , 0.9941676 ,
       1.0010376 , 0.9956103 , 1.0069735 , 1.0061135 , 0.9993851 ,
       1.0440669 , 0.98579496, 0.9824845 , 0.99127257, 0.9846169 ,
       0.9794572 , 0.98472315, 0.9752684 , 0.9848292 , 0.9971436 ,
       1.0051978 , 0.99485505, 0.9794744 , 1.0134754 , 1.0354308 ,
       0.96957535, 0.99866927, 0.99778706, 1.0009569 , 0.99017155,
       1.0172409 , 0.98780227, 0.98927027, 1.0165662 , 1.001967  ,
       1.0009844 , 0.9807918 , 0.9966146 , 0.9876978 , 0.9880553 ,
       1.0036898 , 0.9916643 , 0.9942061 , 1.0064014 , 0.99546415,
       0.9987047 , 1.0059183 , 0.9857919 , 0.9931264 , 0.99563235,
       0.98981714, 1.0192958 , 0.99592936, 1.016209  , 1.0092462 ,
       0.9931731 , 0.98401886, 1.0038269 , 0.99209607, 1.01222   ,
       1.0060872 , 1.0092576 , 1.0021693 , 1.0039359 , 0.98775476,
       0.96904206, 1.0027345 , 0.9984953 , 1.0097429 , 1.0030849 ,
       0.99593073, 0.99308664, 0.98874146, 0.98914754, 0.9811253 ,
       0.9840394 , 1.012609  , 1.010465  , 0.9939829 , 0.9922313 ,
       1.0041571 , 0.9915375 , 1.0092504 , 0.99915135, 1.0042989 ,
       1.0119517 , 0.9911827 , 1.0164092 , 1.0155836 , 0.9938424 ,
       1.0027049 , 0.9926401 , 0.975565  , 1.0061319 , 0.99275905,
       1.0361042 , 0.9931439 , 1.0246692 , 1.0170755 , 0.9745027 ,
       0.99853057, 0.9856834 , 0.9658686 , 0.98820573, 1.0043418 ,
       0.9838408 , 0.98189133, 1.0111465 , 0.9860249 , 1.0121183 ,
       0.9906513 , 0.989566  , 1.0130029 , 0.9803214 , 0.98608017,
       0.98888713, 1.0113869 , 0.9937511 , 0.99596506, 0.9879938 ,
       1.0092524 , 0.9996492 , 0.9806817 , 1.010504  , 0.9907757 ,
       1.0434772 , 1.0138851 , 0.98557514, 0.97683865, 1.0029532 ,
       1.0023555 , 0.9994611 , 1.0021906 , 0.99877274, 0.99365884,
       0.99829763, 0.98653215, 0.9975766 , 0.9965907 , 1.005318  ,
       1.0044037 , 1.008307  , 0.97194254, 1.0148928 , 0.9899066 ,
       1.0007424 , 1.0014637 , 1.0010393 , 0.9966812 , 0.9926096 ,
       1.0010886 , 0.9844405 , 0.9901296 , 0.99409103, 0.9936163 ,
       1.0053334 , 0.9790073 , 1.0035837 , 1.0061356 , 0.9854287 ,
       0.99011207, 0.9951888 , 0.9827165 , 0.9844763 , 0.9760764 ,
       0.9943578 , 1.0029377 , 1.0096928 , 0.99361616, 0.988054  ,
       0.9939055 , 0.98881626, 0.992167  , 0.9985288 , 0.99424404,
       0.99362236, 1.0287672 , 0.99532294, 1.0132171 , 0.99682254,
       0.96865594, 0.9806283 , 1.0083634 , 0.9880708 , 0.99424475,
       0.99970925, 0.99591565, 0.99385244, 0.9952179 , 0.99934125,
       0.9990075 , 0.9952182 , 1.0051874 , 1.0096848 , 0.9973424 ,
       1.0012746 , 0.99097085, 1.0126454 , 0.9875609 , 0.98837316,
       0.9986017 , 1.0096217 , 0.9988905 , 0.99559534, 0.9802229 ,
       0.984981  , 0.98204523, 0.99936295, 1.0098403 , 1.0034698 ,
       1.0019643 , 0.9905315 , 1.0087278 , 1.0115229 , 0.9865949 ,
       0.98795897, 1.0031472 , 1.003307  , 0.9989907 , 0.98741186,
       0.98967254, 0.99925256, 1.0112779 , 0.99881476, 0.99798524,
       0.9909028 , 0.9990262 , 1.0020341 , 1.0056826 , 0.99406815,
       1.0114974 , 1.0105397 , 1.00382   , 0.98061013, 0.9943635 ,
       0.97047734, 0.98090947, 1.0073076 , 0.9827215 , 0.99293375,
       0.99861056, 1.0140737 , 1.0072604 , 1.0116197 , 1.0259821 ,
       0.9891868 , 0.9954196 , 0.9901672 , 1.0023919 , 0.9980963 ,
       1.0089828 , 1.007058  , 1.0199368 , 0.9744251 , 1.0252854 ,
       1.0047972 , 0.99699247, 1.009226  , 0.98831344, 1.0161767 ,
       0.9758623 , 1.0022657 , 0.9801524 , 0.99476457, 1.0147476 ,
       1.0103378 , 0.9958922 , 1.0069891 , 1.0005192 , 0.9936437 ,
       0.9997005 , 0.9716076 , 0.9800369 , 1.0002444 , 0.9917992 ,
       1.0053079 , 0.99808276, 1.019313  , 1.001038  , 1.0132567 ,
       0.9922607 , 1.0103111 , 0.9840844 , 1.0095345 , 1.00735   ,
       0.99846673, 1.0011102 , 1.0297611 , 0.9935717 , 1.00893   ,
       0.99216765, 1.0074762 , 1.0271868 , 0.9928771 , 0.9957349 ,
       0.9776824 , 1.0004255 , 0.9992308 , 0.9997916 , 0.97932714,
       0.99585694, 0.99007475, 0.98948526, 0.9915832 , 1.0107218 ,
       0.9854944 , 0.9976874 , 1.0078135 , 1.0023957 , 0.98236513,
       1.0042232 , 1.0014207 , 1.0118517 , 1.0156416 , 1.0056227 ,
       0.99014175, 0.986132  , 0.99118334, 0.9931519 , 0.9995993 ,
       0.98410696, 1.0006522 , 1.0306699 , 0.9941522 , 1.0094736 ,
       0.9930315 , 1.0016705 , 1.0262384 , 0.99819875, 0.9985067 ,
       1.0074238 , 0.9897038 , 0.9865963 , 1.014427  , 1.0031282 ,
       0.9799708 , 1.0042735 , 0.9815283 , 0.9876524 , 0.9990628 ,
       0.9960753 , 0.99847984, 1.0013621 , 1.0033699 , 1.0041837 ,
       0.99019843, 0.990671  , 0.99345434, 0.999936  , 1.0023036 ,
       1.006369  , 0.99287814, 0.9906545 , 0.99284005, 0.9826661 ,
       1.0079435 , 1.0030718 , 1.0081689 , 1.0044454 , 1.0022764 ,
       1.0037137 , 1.0001819 , 0.9919478 , 1.0140599 , 1.006937  ,
       1.0172528 , 0.983651  , 0.992461  , 0.99406356, 0.99277866,
       0.9940138 , 0.9849625 , 1.0018185 , 1.012268  , 1.0232788 ,
       0.9936492 , 0.99955976, 1.0029805 , 1.0087043 , 1.0074384 ,
       1.0141554 , 0.99619573, 0.9953228 , 0.9832355 , 1.0010979 ,
       1.0039909 , 0.9913826 , 1.0069456 , 1.026571  , 1.0073032 ,
       1.0065335 , 0.9908923 , 0.9907825 , 1.0009793 , 1.013735  ,
       0.992806  , 0.96004254, 0.989615  , 0.99925023, 0.985332  ,
       0.99026847, 0.98366654, 1.0136646 , 0.99279153, 1.0241408 ,
       0.99855405, 0.99513716, 1.0038925 , 0.9943461 , 0.9963742 ,
       0.99931085, 1.0065844 , 1.0080795 , 1.0108805 , 0.9989953 ,
       1.0229387 , 1.0084012 , 0.9890869 , 0.97873795, 0.9956431 ,
       0.99160737, 1.0019306 , 1.0057777 ], dtype=float32), array([-9.44820512e-03,  2.56689207e-04, -1.47196315e-02, -2.03324342e-03,
        1.66728441e-02, -2.56034322e-02, -1.73664640e-03, -3.68471220e-02,
        2.24205628e-02, -3.98552790e-03,  1.19292652e-02,  1.57308802e-02,
        5.23368269e-03, -1.82033377e-03,  4.51816525e-03,  1.27535015e-02,
        4.30249609e-04,  1.07233953e-02, -3.36662903e-02, -4.37169634e-02,
       -2.18779277e-02, -2.25302912e-02, -1.14743011e-02, -1.05560739e-02,
       -1.69575177e-02,  2.94168256e-02,  1.15672126e-02,  9.07906331e-03,
        6.54260919e-04, -9.87709849e-04,  7.18796800e-04, -3.34750563e-02,
        6.84117386e-03, -1.90845709e-02,  1.49603002e-02, -1.30907726e-02,
       -7.13725947e-03, -1.17905410e-02,  6.08659466e-04,  9.90278437e-04,
        4.32339916e-03,  1.32206399e-02,  9.18007863e-04, -1.00101447e-02,
        1.75635517e-02, -4.21340801e-02, -1.35199744e-02, -6.78903563e-03,
       -3.09952162e-02,  8.05250183e-03, -8.39365926e-03,  1.05563262e-02,
       -3.14641744e-02,  1.03609811e-03,  1.44177960e-04,  1.99186546e-03,
       -8.15794617e-03, -5.71291940e-03, -5.84841613e-03, -4.87869885e-03,
        2.36992855e-02,  5.00920974e-03, -1.49268713e-02, -2.92302831e-03,
       -7.61062466e-03, -6.43909117e-03, -1.17559759e-02,  1.03016924e-02,
        3.30764637e-03,  8.17217492e-03,  1.05924923e-02,  4.75442084e-03,
        7.51908962e-03, -6.02421397e-03,  3.20815369e-02, -8.88404809e-03,
        1.86646134e-02, -1.18244356e-02, -6.07551634e-03,  2.79413187e-04,
       -2.59650201e-02, -3.33047094e-04, -1.47082023e-02,  6.05281384e-05,
        1.62014812e-02, -9.34048963e-04, -8.31136480e-03, -6.55822363e-03,
       -3.64679727e-03,  2.50954535e-02, -1.34233769e-03, -1.82868224e-02,
       -1.52543467e-02, -5.33849560e-03, -4.99345036e-03,  2.56715231e-02,
        1.20439362e-02, -6.32578600e-03,  1.22169349e-02,  1.95469689e-02,
       -4.94911475e-03,  8.45728815e-03, -4.09040309e-04, -1.32816229e-02,
       -7.61375017e-03, -1.23402979e-02, -2.43634172e-02, -2.86713485e-02,
        1.82215031e-03, -1.07459007e-02,  6.53273100e-03, -2.96548791e-02,
        2.05535386e-02, -6.79924991e-03,  7.36574177e-03, -2.12187860e-02,
        6.97265193e-03, -1.21708801e-02,  1.95756592e-02,  1.34171378e-02,
       -3.50925722e-03, -1.78118907e-02, -1.66194960e-02,  2.62313168e-02,
       -1.34537956e-02, -1.33008109e-02,  1.49227888e-03,  3.44713181e-02,
       -1.39866406e-02, -2.08941847e-03, -1.89499073e-02,  4.77759428e-02,
       -1.34048075e-03, -6.97741145e-03, -1.20786447e-02, -2.18212269e-02,
        3.43346484e-02, -2.60843504e-02, -3.91843030e-03, -2.13533379e-02,
        2.47641020e-02,  8.26854445e-03,  7.46645732e-03, -7.02377968e-03,
       -9.88814048e-03,  1.00192362e-02,  9.77276452e-03, -2.08805334e-02,
       -2.45945398e-02, -1.29015017e-02, -1.82079356e-02, -1.72053073e-02,
       -3.07456013e-02, -1.91036705e-02,  6.65165531e-03,  1.19319726e-02,
        4.93517960e-04,  1.74060080e-03, -7.16996379e-03, -1.27153588e-03,
       -6.41039992e-03, -6.37531886e-03, -1.44000985e-02, -1.67788435e-02,
       -3.38012143e-03, -3.08485553e-02, -1.39641226e-04, -3.62509256e-03,
        2.66558956e-03, -1.21907974e-02,  4.48344871e-02, -2.92656273e-02,
        1.63813122e-02, -2.15049461e-03, -1.84686631e-02, -8.69713258e-03,
       -8.31457414e-03,  1.62572898e-02, -7.13012880e-03, -7.90665299e-03,
       -6.48439163e-04, -5.36042824e-03, -1.26735400e-02, -2.71903537e-02,
       -2.81551927e-02, -1.10241696e-02,  2.38034944e-03,  5.51626040e-03,
       -1.81024037e-02,  4.39170143e-03, -6.73194882e-03,  1.71478409e-02,
       -1.00037009e-02,  1.43278809e-02,  1.63114443e-02, -9.78073291e-03,
       -5.70818596e-03, -2.03078985e-02, -2.41331365e-02, -1.81021988e-02,
        5.23021538e-03, -3.01235763e-04,  2.17836276e-02, -2.46890541e-02,
       -1.04051791e-02, -1.67441480e-02,  2.66582053e-02, -2.23443061e-02,
       -3.12132109e-03,  3.60874236e-02, -6.49650721e-03, -4.15410064e-02,
       -8.17368447e-04, -7.38515053e-03, -2.49241348e-02,  5.89468982e-03,
        6.39475835e-03, -5.86816855e-03,  1.39860883e-02, -1.48761300e-02,
       -8.68426356e-03,  3.82770528e-03,  3.88854300e-04,  3.17444373e-03,
        1.34666367e-02,  1.10790366e-02,  5.91662014e-03,  2.54542269e-02,
       -7.62216607e-03, -1.13607757e-02,  3.85523662e-02, -1.01101827e-02,
       -9.64188948e-03, -1.36940554e-02, -2.58191098e-02,  2.29323003e-03,
       -2.41613761e-02, -3.05494713e-03, -3.16094384e-02, -5.50647918e-03,
       -1.60967633e-02,  2.39249058e-02,  8.64280015e-03, -1.04202954e-02,
        8.19126982e-03, -1.62370652e-02, -5.30698337e-04,  4.60993405e-03,
       -6.35970011e-03, -1.01291891e-02, -4.97813569e-03,  4.35021147e-03,
       -1.02296202e-02,  1.35371638e-02,  1.22011956e-02, -4.02533039e-02,
       -6.80927234e-03,  2.65066773e-02,  2.20662099e-03,  2.14170921e-03,
       -2.30875444e-02, -1.36810923e-02,  1.70813203e-02, -3.37309279e-02,
        1.04030566e-02,  1.31990733e-02,  1.01967808e-02, -5.81927539e-04,
       -1.43677108e-02,  9.50365886e-03,  2.49382127e-02, -8.34978558e-03,
       -1.39467428e-02, -5.07621036e-04, -2.49475632e-02, -1.10892178e-02,
       -5.97415864e-03, -4.62445579e-02,  1.57238338e-02, -1.48387402e-02,
       -2.27100938e-03, -1.33822358e-03,  7.97844550e-04,  2.71226745e-03,
       -2.40279492e-02, -1.78193953e-02, -1.52346222e-02, -1.34196617e-02,
       -8.08026548e-03, -1.75365284e-02, -6.83892844e-03,  3.24759521e-02,
        6.17395341e-03, -1.89266056e-02, -2.85394234e-03, -1.01285032e-03,
       -2.13254243e-03,  8.48920085e-03, -8.71295575e-03, -9.42327734e-03,
       -1.84297282e-02,  2.02114205e-03, -8.36983963e-04, -2.99377367e-02,
       -7.13605667e-04, -2.08706111e-02, -3.23334336e-02,  4.33400273e-03,
        5.74619928e-03, -9.58150811e-03,  1.09903421e-02, -8.65473179e-04,
        6.93042530e-03,  1.33914603e-02,  2.70325392e-02, -1.15972823e-02,
       -1.02347583e-02, -2.16442235e-02,  1.31123466e-02, -8.96387547e-03,
       -1.03847217e-02,  1.59140173e-02, -2.44196150e-02, -1.87230241e-02,
        9.19888075e-03,  1.12461643e-02, -1.16249220e-02, -1.01896911e-03,
       -8.84990860e-03, -4.49694209e-02, -2.39120368e-02,  6.73749996e-03,
        9.59993573e-04,  2.65329536e-02,  2.38653994e-03,  5.77934505e-03,
       -6.72625657e-03, -1.80906076e-02, -1.06295329e-02, -3.18151130e-03,
        7.62110634e-04, -1.82729233e-02, -6.24819100e-03, -1.62944905e-02,
        2.73852260e-03,  1.88058000e-02,  8.61637667e-03, -4.09404188e-03,
        3.68200950e-02, -3.65975918e-03,  1.76731721e-02,  9.37452167e-03,
        1.80282369e-02,  2.79457159e-02, -7.81114958e-03, -2.34407894e-02,
        2.14958051e-03, -7.57698203e-03,  6.60292059e-03,  4.93698008e-03,
       -6.70011295e-03, -4.02645469e-02,  1.49713196e-02, -2.30107084e-02,
        9.82530788e-03, -8.24561995e-03, -2.67452449e-02, -1.09744230e-02,
       -3.05072148e-03,  5.37339877e-03, -1.80898383e-02, -1.37097761e-02,
       -7.70894019e-03, -3.63880694e-02,  6.25838246e-03,  4.92801797e-03,
        9.99629730e-04, -2.97876261e-02,  9.59108677e-03, -1.14772962e-02,
       -3.90203297e-02, -2.26703547e-02,  3.12674679e-02, -7.14544766e-03,
       -1.71374958e-02, -2.05283780e-02, -1.18197091e-02, -2.05170307e-02,
        8.49984493e-03, -1.24054011e-02, -1.48213040e-02,  1.77513424e-03,
       -9.55204386e-03,  8.96528270e-03, -1.08075915e-02, -2.25757584e-02,
        9.87487752e-03, -8.49298947e-03, -1.14994580e-02,  5.97060518e-03,
       -2.42731702e-02, -4.65509528e-03,  7.75820715e-03,  2.46559996e-02,
       -1.03885066e-02, -3.30067403e-03, -4.91922162e-03, -3.00694220e-02,
       -2.03499720e-02,  4.60145558e-04, -5.66432672e-03, -1.60735026e-02,
        8.77687335e-03, -3.26208957e-02,  2.40355753e-03, -1.89916473e-02,
       -4.12221253e-03, -1.34783909e-02,  3.88941285e-03, -4.51535620e-02,
       -3.07081034e-04, -1.81380883e-02, -1.20174503e-02, -1.28309745e-02,
       -5.06690890e-03, -5.51264547e-03, -3.47495675e-02,  5.58684627e-03,
       -9.71292611e-03,  3.41941370e-03, -1.57297514e-02,  2.76410338e-02,
       -6.19250769e-03, -4.14095670e-02,  4.43041604e-03, -2.19619926e-02,
        1.78760719e-02, -8.82630143e-03, -2.26090848e-02, -2.89514125e-03,
       -1.41706420e-02,  6.82070758e-03, -3.44927958e-03,  8.92210566e-03,
       -1.07135586e-02,  7.77609600e-03, -1.00226747e-02, -7.08037289e-03,
        1.34282587e-02, -1.67908650e-02, -3.16825658e-02, -1.63796078e-02,
       -1.41614408e-04, -9.47259087e-03,  1.94709096e-02, -1.23469289e-02,
       -6.31418778e-03,  1.14955939e-02,  2.01405529e-02,  6.74019800e-04,
       -7.66439969e-03,  2.45779566e-02,  2.18837820e-02, -2.85402942e-03,
       -1.78462360e-02, -1.04244901e-02, -4.44706110e-03, -9.34428442e-03,
       -4.81173443e-03,  4.76615038e-03, -1.00385454e-02, -2.24278290e-02,
        3.47967929e-04, -3.14270407e-02, -6.52504503e-04, -1.40545173e-02,
       -9.21538379e-03, -1.50633082e-02, -6.32857904e-03, -1.37174188e-03,
       -1.57078113e-02, -3.85161638e-02, -4.79725469e-03, -1.50692994e-02,
        1.82858407e-02, -2.50190105e-02, -2.89485976e-03,  2.10612989e-03,
        1.40851189e-04, -8.98519473e-04, -1.86159443e-02, -9.58949514e-03,
       -1.05396686e-02, -7.49708153e-03, -1.57274399e-02,  2.32201908e-02,
        7.14132795e-04, -2.28141546e-02,  1.02874066e-03, -3.18015851e-02,
       -1.22653702e-02,  2.46056728e-02,  1.12758884e-02,  6.64201623e-04,
       -8.60501453e-03, -2.15873756e-02, -4.68540937e-04,  3.14795785e-02,
       -6.94664707e-03, -4.62772232e-03,  4.40712413e-03, -1.12644779e-02,
        1.80578642e-02,  1.38600264e-02,  2.79334169e-02, -1.19770849e-02,
       -4.89610899e-03, -1.22522085e-03, -8.27618502e-03, -1.02996221e-02,
        2.96397787e-03, -1.47719420e-02, -1.99462450e-03,  1.15559297e-02,
        1.08410546e-04, -9.29052243e-04, -7.98899774e-03,  5.99807454e-03,
       -1.70387644e-02,  5.78402635e-03, -9.52677894e-03,  1.42086130e-02,
       -2.36659981e-02,  4.27978076e-02,  1.08372169e-02, -4.50736564e-03,
       -2.15988476e-02, -1.70963425e-02, -1.09306341e-02, -3.88268121e-02,
       -2.02301703e-02, -2.76772212e-02, -1.34897158e-02, -1.61932446e-02,
       -4.25449898e-03,  2.42439043e-02, -9.03965905e-03,  8.47078301e-03,
       -9.38154571e-03, -6.36232924e-03,  9.78656393e-03, -2.11298540e-02,
       -8.55188724e-03, -6.87122461e-04,  1.24319047e-02, -1.21504478e-02,
       -4.77542207e-02, -1.81409512e-02,  1.02296437e-03, -6.78439811e-03,
        1.28887715e-02, -1.57689746e-03,  4.17772215e-03,  1.54988794e-02,
        3.43325660e-02, -8.60540476e-03,  1.31929582e-02, -1.11455638e-02,
       -3.24438530e-04, -5.64194331e-03, -2.07734499e-02, -3.60969715e-02,
       -1.58047657e-02, -2.92739994e-03, -6.75755693e-03,  1.35785732e-02,
       -1.79518610e-02, -5.24358312e-03, -9.88211110e-03, -3.18365470e-02,
       -8.24700575e-03, -2.76083546e-03,  1.27961151e-02, -1.73200562e-03,
        3.33179943e-02, -1.25927804e-02, -1.66454613e-02,  1.21883899e-02,
       -7.97366444e-03, -7.79903401e-03,  1.68732703e-02, -8.45645554e-03,
        4.38246131e-03, -1.39956502e-02,  9.05318558e-03, -1.01297675e-03,
        1.56485550e-02,  3.43285594e-03,  1.09096309e-02,  1.73121542e-02,
       -2.40363274e-02, -6.76313788e-03, -1.38890492e-02, -1.86178405e-02,
       -1.07687293e-02, -8.05753004e-03,  8.08365736e-03, -4.17718152e-03,
        6.34730980e-03, -1.60371754e-02, -4.27799113e-03,  2.12127361e-02,
       -3.45611721e-02, -1.24235339e-02, -1.51150879e-02, -1.83387834e-03,
       -2.51181554e-02, -2.38837209e-02, -1.61037070e-03, -1.56672616e-02,
       -1.48968706e-02, -1.02154007e-02, -1.20624332e-02,  1.74065623e-02,
        7.16310553e-03, -3.03646326e-02, -2.91713215e-02,  1.10870376e-02,
        2.57691508e-03, -1.38750859e-02,  9.44472966e-04,  1.17725488e-02,
       -1.90250005e-03, -1.49749042e-02, -1.53688965e-02,  2.89059170e-02,
       -1.74798481e-02,  1.51524702e-02, -1.05213253e-02,  1.23581290e-02,
       -4.76224953e-03, -8.68065190e-03,  1.66213978e-02,  3.88874626e-03,
       -4.50644549e-03, -7.32128136e-03,  5.41201886e-03,  8.22176784e-03,
       -3.41445161e-03, -2.01320481e-02, -7.01692840e-03, -1.52970823e-02,
       -8.52476899e-03, -5.46716759e-03,  8.49455968e-03,  7.13128224e-03,
       -9.47589055e-03,  2.55946093e-03, -1.49557609e-02, -2.27848217e-02,
       -1.82210677e-03,  1.42197767e-02, -1.65293962e-02, -5.29154483e-03,
       -1.09178713e-02,  1.15969470e-02, -1.90982372e-02, -1.46645447e-02,
        2.34016441e-02, -1.00345491e-02, -1.96793098e-02, -5.10198530e-03,
        1.11546228e-02,  2.57911682e-02,  1.56876594e-02, -1.17086247e-02,
       -1.77887585e-02, -1.73583888e-02, -5.88682806e-03,  2.57147122e-02,
        3.46727087e-04, -1.36784296e-02, -7.25648971e-03, -5.83629822e-03,
       -1.23114791e-02,  2.19334848e-02, -7.14970287e-03,  3.74266552e-03,
        6.53125206e-03, -3.07287276e-02, -3.51977884e-03, -2.62029516e-03,
       -1.20441224e-02,  2.05750298e-03, -6.46354817e-03,  4.90052402e-02,
       -1.09600117e-02, -1.38900029e-02, -5.40889055e-03, -1.58848497e-03,
        4.52968845e-04, -1.72482319e-02, -2.45725410e-03, -5.59996755e-04,
        5.10302722e-04,  9.28111316e-04, -2.58074682e-02, -2.72927154e-03,
        2.93417349e-02, -1.17215943e-02,  7.71375000e-03, -4.14405577e-03,
        2.04739533e-02, -2.34786188e-03,  2.03667935e-02,  2.82064024e-02,
       -9.04503278e-03, -2.34373417e-02, -1.22809745e-02, -8.97103455e-03,
        7.48691848e-03, -3.86107080e-02, -3.78021039e-02, -2.05714852e-02,
        2.53935665e-04, -2.93823015e-02,  2.75828522e-02, -1.33909890e-02],
      dtype=float32), array([ 2.54357010e-02,  5.56645952e-02,  2.72544865e-02,  5.33686802e-02,
        1.48608210e-02,  4.93085571e-02, -1.45185636e-02,  4.70925868e-02,
       -2.49380004e-02,  4.20201384e-02, -5.49269952e-02, -3.73103954e-02,
        4.12543975e-02, -2.14031041e-02, -6.35764226e-02, -2.66898666e-02,
        7.68991187e-04,  3.56121212e-02,  8.80667567e-03,  5.08980043e-02,
       -1.05969850e-02,  1.88786127e-02, -9.72698443e-03,  1.53162442e-02,
        4.53704633e-02, -3.65064219e-02, -5.87222278e-02, -4.25916463e-02,
       -4.25054282e-02, -2.53544934e-02,  2.62464248e-02,  4.49656807e-02,
       -1.74382124e-02,  1.89500451e-02, -3.23320143e-02,  4.22229208e-02,
        2.75116656e-02,  1.17720198e-02,  4.84794565e-02, -8.66179820e-03,
        3.15892957e-02,  2.86860354e-02, -2.43483186e-02,  2.93630138e-02,
        3.83433886e-02,  4.64956872e-02,  4.18939292e-02,  3.38985175e-02,
        6.66069835e-02, -4.89022620e-02,  2.35867631e-02, -2.23737601e-02,
        9.58726257e-02,  2.32007243e-02, -1.10583156e-02,  4.64867949e-02,
        3.03746220e-02,  3.50889005e-02,  3.30483094e-02,  5.41904829e-02,
       -3.78539506e-03,  4.22620997e-02,  3.44296992e-02,  5.75687438e-02,
        6.69901306e-03,  8.43834504e-03,  4.37336788e-02,  8.99630692e-03,
       -1.03919506e-02,  1.98952071e-02, -1.37963491e-02,  2.33130846e-02,
       -1.12812512e-03,  4.26937304e-02, -3.83074768e-02,  7.75104249e-03,
       -3.35654654e-02,  6.06615506e-02,  9.52754077e-03, -3.27765904e-02,
        4.45245020e-02,  8.75245035e-03,  6.88278601e-02, -5.52845150e-02,
       -5.43691218e-02,  3.42501677e-03, -1.25893839e-02,  3.57176438e-02,
        3.91965806e-02,  6.62035123e-02,  4.60198894e-02,  2.79680658e-02,
        7.78121687e-03, -3.70323658e-02, -4.12058719e-02, -5.32195605e-02,
       -1.60231255e-02,  3.92482094e-02, -2.22635153e-03,  5.75533919e-02,
       -3.86791937e-02, -4.83520627e-02,  3.02384999e-02,  3.61612998e-02,
       -1.83514636e-02, -2.43798103e-02,  4.51471104e-04,  3.16240303e-02,
        2.63715386e-02,  2.76055578e-02, -3.93206887e-02,  1.60777979e-02,
       -3.40668261e-02,  1.66177545e-02,  1.15530228e-03,  6.37083054e-02,
        1.74316373e-02,  3.83489616e-02,  6.08859584e-03, -4.19577174e-02,
        1.56728756e-02,  4.15162705e-02, -4.70559066e-03, -5.74393198e-02,
        1.27717722e-02,  3.98070514e-02, -1.05017629e-02, -2.18516663e-02,
        6.24456666e-02,  6.82222843e-02,  2.58210208e-02,  2.40243450e-02,
       -5.83087420e-03, -2.35676356e-02, -1.40751190e-02,  6.50813505e-02,
       -4.86448742e-02,  2.94630155e-02,  3.67277339e-02,  2.72356495e-02,
        3.84451747e-02,  1.44022154e-02,  2.85402779e-02,  6.41815085e-03,
        5.78171536e-02,  2.03506052e-02,  1.60909053e-02,  4.56647128e-02,
        3.94849405e-02,  2.91829631e-02,  5.77292666e-02,  1.86549732e-03,
        5.21312952e-02,  5.25838993e-02, -4.50504236e-02, -5.81659898e-02,
       -5.07579707e-02,  5.29916063e-02,  3.62406820e-02, -2.55138129e-02,
        3.87486741e-02,  4.21896912e-02,  5.30352965e-02,  4.47138175e-02,
       -3.69374291e-03,  4.52482551e-02,  2.43653525e-02,  1.56137615e-03,
        2.27886345e-02,  4.30518575e-02, -4.00830843e-02, -3.67471240e-02,
       -3.36407125e-02, -1.86986756e-02, -3.70239727e-02,  1.11143058e-02,
        3.60511579e-02, -6.01476841e-02, -4.55790497e-02,  5.02121029e-03,
       -6.10730574e-02,  4.72493768e-02, -3.38435546e-02,  5.91750219e-02,
        5.26237451e-02,  2.75168456e-02,  4.79929615e-03, -1.21573061e-02,
        2.76113488e-02,  5.09981625e-02,  2.86272615e-02, -1.69614214e-03,
        5.15781045e-02, -3.99870127e-02,  1.64494235e-02, -1.49511388e-02,
        4.05209474e-02,  3.87995280e-02,  5.27651533e-02,  4.62600887e-02,
        5.90929352e-02, -1.63972285e-02, -4.72715199e-02, -2.42422055e-02,
        2.84517137e-03,  2.38767955e-02, -6.55338839e-02,  4.54088859e-02,
        1.29363686e-02,  2.02312227e-02, -5.72923105e-04,  4.53030914e-02,
       -1.96695384e-02, -3.22875641e-02,  2.92251054e-02,  4.81373034e-02,
        2.52213739e-02,  2.64130849e-02, -1.73104890e-02,  7.68192811e-03,
       -2.25296486e-02,  8.80978722e-03,  2.35354900e-02, -4.47143465e-02,
       -3.08554564e-02,  5.49926469e-03, -4.21440564e-02, -5.08642606e-02,
        3.88115495e-02, -2.81703714e-02, -3.63974944e-02,  3.31319682e-02,
        2.88535543e-02,  4.09427434e-02,  2.01726593e-02, -3.71645652e-02,
        1.26728900e-02,  1.76734962e-02,  4.06572782e-02, -2.00551115e-02,
        7.79943448e-03, -8.22550524e-03, -5.47438078e-02,  6.97746454e-03,
       -1.12648988e-02,  6.37147725e-02,  3.95190865e-02, -1.50262937e-02,
        5.24380058e-02,  5.84266940e-03, -4.00623633e-03, -2.44924854e-02,
        3.29778083e-02,  1.17259854e-02, -3.51890437e-02,  1.74808074e-02,
       -1.52353533e-02, -4.89270762e-02, -4.17030267e-02,  3.08089629e-02,
        2.47544311e-02, -3.03227566e-02,  1.70874149e-02,  2.31688302e-02,
        2.55005993e-02,  2.43067835e-03, -2.12317687e-02, -1.96790937e-02,
        1.95012130e-02,  3.15785557e-02, -3.80123854e-02,  3.46917249e-02,
        1.22281844e-02,  2.17064265e-02,  1.16928658e-02,  1.78005546e-02,
        4.55836542e-02,  4.77672853e-02, -3.87363210e-02,  2.94571556e-02,
       -1.42941298e-02, -4.26498950e-02, -1.57954376e-02,  4.99373209e-03,
        5.19628040e-02,  9.67597663e-02, -7.15516321e-03,  4.33727801e-02,
        4.17914130e-02,  5.67227565e-02, -3.51161994e-02, -1.99463572e-02,
        1.37415919e-02,  5.07306866e-02,  3.06903534e-02,  2.44934745e-02,
        1.35717746e-02, -3.86165120e-02,  3.42677683e-02, -7.73313940e-02,
        1.30712474e-02,  4.01240885e-02,  1.37260063e-02,  6.82230443e-02,
        2.11131424e-02, -2.81499065e-02,  4.02444787e-02, -2.63185240e-02,
       -2.07494572e-02, -3.29525582e-02, -1.68942027e-02, -2.70556230e-02,
       -2.03157663e-02, -5.43047413e-02, -1.97294764e-02,  3.93047705e-02,
        3.90975662e-02,  7.78030828e-02, -3.03786714e-02,  4.23128530e-02,
       -2.05212031e-02,  1.52298110e-02,  3.61767337e-02,  4.38448451e-02,
       -4.38417979e-02,  7.42415152e-03,  4.43766154e-02,  7.09759146e-02,
       -1.42359938e-02,  2.82721724e-02,  3.19953673e-02, -2.24639215e-02,
       -9.43449419e-03, -2.64272504e-02,  4.42655012e-02,  7.54365418e-03,
        4.60529849e-02,  2.61423439e-02,  2.79948432e-02,  6.94065616e-02,
        3.87216695e-02,  5.77716604e-02, -2.64246874e-02, -3.35845537e-02,
        4.58730981e-02, -5.44714334e-04, -2.67356960e-03,  2.64236499e-02,
       -5.90707324e-02,  3.52558978e-02, -4.48364243e-02, -4.34643887e-02,
        4.17475030e-02, -3.31756547e-02,  2.26092692e-02,  6.17935546e-02,
        1.78895835e-02, -1.34520708e-02, -4.94080922e-03,  2.68362705e-02,
        3.78362052e-02,  2.89487243e-02, -6.66873679e-02,  3.86708230e-02,
       -2.60828715e-02,  4.82766777e-02,  3.56892757e-02,  6.80749565e-02,
        2.33952031e-02, -4.23812494e-02,  4.09784056e-02, -1.81710627e-02,
       -2.70390660e-02, -4.13638838e-02,  2.72723753e-02,  2.63234656e-02,
       -3.76437493e-02,  5.98366447e-02,  3.58580872e-02,  3.79822142e-02,
        2.62750760e-02,  1.36874840e-02, -4.90405923e-03,  2.96216086e-02,
        6.37771562e-02,  4.82580550e-02,  4.21233028e-02,  2.70923991e-02,
       -3.85551490e-02,  3.85630727e-02,  1.98690221e-02,  2.39272267e-02,
       -6.50741719e-03,  3.45898420e-02,  2.05759332e-02, -2.27489620e-02,
        3.61050316e-03,  3.21490653e-02,  2.83601191e-02,  1.13730077e-02,
       -6.55763142e-04,  2.63043698e-02, -5.17618097e-03, -3.19040902e-02,
        9.69198346e-03,  8.03807937e-03,  2.13688798e-02,  5.19928560e-02,
       -4.80171889e-02,  2.45605875e-02,  4.39239405e-02,  4.05623689e-02,
       -3.16356011e-02,  6.09149784e-02,  5.62467091e-02,  3.98946814e-02,
        2.37233005e-02,  2.09911950e-02,  1.69561505e-02,  3.98073792e-02,
        1.52679142e-02, -5.77813014e-02,  3.68839614e-02,  1.22761214e-02,
        6.16228618e-02,  3.66957635e-02,  3.86823937e-02,  2.39377730e-02,
        3.39854918e-02,  3.16188596e-02,  3.72364856e-02,  2.88167130e-02,
       -6.97547123e-02,  5.82655780e-02, -2.89987028e-02, -3.37602422e-02,
        2.87380945e-02,  5.40637523e-02,  2.81410348e-02,  3.84168662e-02,
        2.26724055e-02,  7.43250772e-02,  5.37166186e-02,  2.65390482e-02,
       -7.20845610e-02,  1.74826640e-03, -3.09775607e-03,  5.46438135e-02,
        3.71084698e-02,  3.30177620e-02,  4.95227315e-02,  4.47326601e-02,
       -2.46210229e-02,  5.84975816e-02, -3.19994204e-02,  3.79996863e-03,
        1.35787604e-02, -3.49055752e-02, -2.65772287e-02,  5.89173008e-03,
        4.93982621e-02,  1.72632020e-02, -2.50194725e-02,  3.79536711e-02,
        4.82792743e-02, -4.03556302e-02, -2.00972520e-02,  4.48686108e-02,
        4.76308241e-02,  4.57756408e-02,  6.33450001e-02, -3.41188312e-02,
        7.03015039e-03,  5.99809326e-02, -2.87736077e-02, -2.18682401e-02,
        4.21871431e-02,  1.81324105e-03,  1.27087776e-02, -5.89295030e-02,
        1.82216074e-02,  3.31883170e-02, -2.59491876e-02,  3.40078138e-02,
       -2.89235637e-02,  4.97819521e-02,  3.31966914e-02,  8.48495029e-03,
        1.71268899e-02,  2.09904183e-02,  1.05214985e-02,  1.70123775e-03,
       -3.06329839e-02, -2.34615877e-02, -3.02126072e-02, -1.60448365e-02,
       -1.77737549e-02, -2.95475568e-03,  2.47984268e-02,  6.17831759e-02,
        1.52539583e-02, -1.59477778e-02, -4.33980078e-02,  2.70741060e-02,
        2.44814698e-02,  4.09100205e-04,  4.05548327e-02, -5.84672540e-02,
        3.57270129e-02,  5.06035015e-02,  3.16134356e-02,  3.91255058e-02,
       -2.25973856e-02, -1.40707265e-03, -6.40560091e-02,  7.21919350e-03,
        3.57870646e-02,  2.38383617e-02, -2.70246360e-02,  3.36168744e-02,
       -1.84172299e-02, -2.18030307e-02, -4.04781289e-03, -2.82073915e-02,
        4.57508601e-02,  5.75824901e-02,  4.63362671e-02, -5.14885373e-02,
       -7.19127618e-03, -4.37479056e-02,  2.28956807e-02, -3.85678671e-02,
        4.83665802e-02, -4.74730600e-03, -2.92492807e-02, -4.43723500e-02,
        2.99180001e-02,  2.38631852e-02,  1.31766926e-02,  5.53734880e-03,
        2.61147618e-02,  4.81929816e-02,  1.01935659e-02, -2.50707306e-02,
       -5.32714389e-02, -8.17698017e-02,  3.35224047e-02,  2.06235629e-02,
        3.41682173e-02,  4.18912135e-02,  4.60263640e-02,  7.53649548e-02,
        3.03167552e-02, -3.15692686e-02, -1.35675957e-02,  5.56226522e-02,
        8.09161067e-02,  3.20622250e-02,  3.22378874e-02,  4.82592210e-02,
       -2.27162093e-02, -4.61792126e-02, -2.51937844e-02, -7.03603327e-02,
       -4.88151722e-02,  5.99004105e-02, -6.16111383e-02, -2.90039741e-02,
       -3.91428210e-02, -1.89911500e-02,  2.56280843e-02, -2.42960751e-02,
        2.52937842e-02,  2.39548236e-02,  4.07096930e-02, -3.67626511e-02,
        3.84443551e-02,  3.04390825e-02, -6.44408390e-02,  6.42280579e-02,
        3.17634828e-02, -3.18979621e-02,  9.48757958e-03,  2.31746808e-02,
       -3.70041318e-02,  5.51459976e-02,  2.68488303e-02,  9.36761126e-03,
        1.99599583e-02,  6.30613789e-02, -2.17330176e-02, -4.19759899e-02,
        3.66850942e-02,  1.31166205e-02,  2.68392731e-02,  4.14452776e-02,
       -4.52863425e-02,  2.03951448e-02,  1.17431721e-02, -1.00069325e-02,
        4.12734114e-02, -3.14637460e-02,  4.32907343e-02,  6.67416537e-03,
        6.57915976e-03,  2.52267215e-02,  7.36002177e-02, -2.72911452e-02,
        2.67531760e-02,  5.02591394e-02,  4.65004258e-02, -3.51310708e-02,
        2.86300033e-02,  2.78326627e-02,  8.35344382e-03,  3.45346183e-02,
       -2.03697011e-02,  2.41004061e-02,  1.66079774e-03,  3.41168568e-02,
       -8.96607526e-03, -5.71529474e-03,  5.11898920e-02, -4.64312360e-02,
        2.17075665e-02,  5.24373651e-02,  4.79465090e-02,  3.59169915e-02,
        5.10681123e-02,  2.76199132e-02, -5.10251708e-02, -2.63503976e-02,
        1.37225352e-02, -4.10498492e-02, -6.57737330e-02, -2.72878837e-02,
        2.35014446e-02, -4.83537577e-02,  3.43395770e-02,  1.31782964e-02,
       -5.44453114e-02,  4.29144613e-02, -3.81380767e-02,  4.43945155e-02,
       -4.15361747e-02,  4.43706475e-02,  5.71040474e-02, -1.32214651e-02,
        3.59396897e-02,  6.41274378e-02,  5.42589501e-02,  3.39242294e-02,
       -1.44079141e-02,  2.10493393e-02, -4.20765057e-02,  4.26180325e-02,
        4.50137034e-02,  7.23832782e-05,  4.01843525e-02,  1.71894301e-02,
        4.36001457e-02, -4.93425205e-02,  1.64736565e-02, -2.22046413e-02,
        4.70733605e-02, -3.61919403e-02, -9.62485734e-04, -4.76399362e-02,
       -3.00746523e-02,  3.95710245e-02,  1.41589744e-02, -2.38332897e-02,
       -5.50407320e-02,  4.06021252e-02, -2.78150290e-02, -2.13062949e-02,
        2.55656242e-02,  2.98956372e-02, -6.44940604e-03,  3.04613579e-02,
       -3.18332501e-02,  7.26754358e-03,  1.62060130e-02, -4.13825028e-02,
        2.65178028e-02, -2.00812742e-02, -2.52825785e-02,  4.47280928e-02,
       -2.31040847e-02,  5.22089824e-02,  4.41305898e-02,  4.70929816e-02,
        5.53663224e-02,  4.19558166e-03,  4.78702690e-03, -2.06480771e-02,
        2.36231014e-02,  1.37384664e-02,  7.57203251e-02,  1.59351584e-02,
        3.32145691e-02,  4.70918678e-02,  1.92114152e-02,  3.83796245e-02,
        2.53037438e-02, -3.19957621e-02,  5.68474233e-02, -2.90061999e-02,
       -3.22890952e-02,  5.22337779e-02, -5.31120859e-02, -9.04654525e-03,
        1.14670470e-02,  3.50270681e-02,  2.00915243e-02, -1.58536322e-02,
        3.96453328e-02,  5.47103249e-02,  4.11815047e-02, -3.22091840e-02,
        4.44956049e-02, -3.29734273e-02,  3.23303677e-02,  3.79614867e-02,
        4.80021574e-02,  4.07428928e-02, -1.49940597e-02,  4.00331169e-02],
      dtype=float32), array([0.09318388, 0.0902775 , 0.08906242, 0.11638671, 0.08822112,
       0.10251739, 0.08955519, 0.10131657, 0.09000553, 0.11204981,
       0.09691703, 0.09576622, 0.08865643, 0.08846952, 0.10563718,
       0.09089334, 0.09218868, 0.09647025, 0.09300936, 0.1120379 ,
       0.09040388, 0.0896107 , 0.08506013, 0.09454042, 0.08994155,
       0.09105813, 0.10269889, 0.10824141, 0.1635476 , 0.09289095,
       0.09101689, 0.11265091, 0.08503842, 0.08594251, 0.08633325,
       0.09985536, 0.0903228 , 0.08709332, 0.08686909, 0.08892125,
       0.08761431, 0.09626754, 0.0879811 , 0.1064209 , 0.11784361,
       0.10398981, 0.08645553, 0.1069854 , 0.10822657, 0.09405258,
       0.08979055, 0.09140921, 0.11627217, 0.08509315, 0.08954828,
       0.09579024, 0.09279187, 0.09736063, 0.09532348, 0.10131688,
       0.08940365, 0.09504061, 0.08898752, 0.11398911, 0.08447812,
       0.08757722, 0.09907589, 0.08961669, 0.08817895, 0.08953147,
       0.08681463, 0.08863065, 0.08417611, 0.09201867, 0.08539742,
       0.08833199, 0.09658753, 0.11283557, 0.08737887, 0.09710158,
       0.09974006, 0.09028021, 0.09863481, 0.09844561, 0.10118896,
       0.0849456 , 0.0851694 , 0.09198254, 0.09089082, 0.12062435,
       0.09902201, 0.08996967, 0.09054163, 0.09233946, 0.09497472,
       0.10678639, 0.08839975, 0.11820368, 0.08612929, 0.11082384,
       0.09558823, 0.09334954, 0.09203002, 0.09362718, 0.08533598,
       0.0870264 , 0.08779246, 0.10394944, 0.09229238, 0.09835207,
       0.09201961, 0.09259231, 0.09401113, 0.09003858, 0.08614779,
       0.11110567, 0.0948755 , 0.09584649, 0.08611989, 0.1036198 ,
       0.09308907, 0.09192321, 0.08744093, 0.09523611, 0.09008404,
       0.09128375, 0.08764116, 0.08846965, 0.09502374, 0.12604667,
       0.09728207, 0.09063333, 0.08651987, 0.08751319, 0.08540424,
       0.11034028, 0.09236412, 0.09316579, 0.09673576, 0.09099825,
       0.09725536, 0.09025428, 0.09359596, 0.08634882, 0.10893761,
       0.09071048, 0.09556606, 0.10631856, 0.09987847, 0.08871046,
       0.0960307 , 0.09690307, 0.09701179, 0.11146112, 0.10301809,
       0.10355752, 0.10519629, 0.10395812, 0.11889853, 0.09597497,
       0.093236  , 0.0941651 , 0.09629354, 0.09318376, 0.08474302,
       0.09502525, 0.08952977, 0.09126787, 0.09302328, 0.09267633,
       0.11028075, 0.09487293, 0.08451724, 0.09181517, 0.0918149 ,
       0.08273464, 0.10023196, 0.11370531, 0.09791309, 0.08829692,
       0.10197822, 0.0993069 , 0.09790953, 0.11508857, 0.10696141,
       0.09041027, 0.08869538, 0.08793934, 0.10120339, 0.13242185,
       0.10065003, 0.08742657, 0.10578658, 0.09560695, 0.08633444,
       0.08986836, 0.09640647, 0.09257879, 0.11098472, 0.09532613,
       0.10308844, 0.08704068, 0.10264654, 0.08659732, 0.09222527,
       0.08904008, 0.1044504 , 0.09628117, 0.08283649, 0.10411606,
       0.08375283, 0.10374774, 0.08965424, 0.09299214, 0.08854674,
       0.09814709, 0.09047978, 0.09131137, 0.08691328, 0.09303165,
       0.08814647, 0.08459974, 0.09152228, 0.09586146, 0.08538754,
       0.08778926, 0.11010949, 0.10800005, 0.10910559, 0.08794483,
       0.09500015, 0.09276497, 0.09392875, 0.1006346 , 0.10018791,
       0.08824673, 0.09029847, 0.08944968, 0.10051662, 0.09145025,
       0.08641748, 0.08912271, 0.10426218, 0.08326006, 0.08583702,
       0.10373289, 0.09607722, 0.08469687, 0.1127531 , 0.09623741,
       0.09172428, 0.08454613, 0.13608207, 0.09199241, 0.09301912,
       0.09548856, 0.08857516, 0.09560837, 0.09777535, 0.08848883,
       0.08888106, 0.09286578, 0.09371918, 0.09979051, 0.1014017 ,
       0.08448228, 0.08960967, 0.0870325 , 0.09431387, 0.08910416,
       0.09260491, 0.09637531, 0.08948822, 0.08864442, 0.09233329,
       0.09416405, 0.10655509, 0.1254146 , 0.09375603, 0.09950487,
       0.09985477, 0.09457804, 0.08998271, 0.0860771 , 0.10071962,
       0.12133601, 0.08965713, 0.08887552, 0.09362834, 0.1022033 ,
       0.09201688, 0.09704353, 0.10340022, 0.11159185, 0.10482979,
       0.09552316, 0.08980761, 0.08934344, 0.08500593, 0.12658857,
       0.08976796, 0.09830607, 0.10035128, 0.11255103, 0.09762734,
       0.09162586, 0.09876352, 0.09835427, 0.09066948, 0.10623088,
       0.08431975, 0.08753734, 0.08311299, 0.10276933, 0.08838306,
       0.09650576, 0.09630393, 0.11779919, 0.09656542, 0.0928281 ,
       0.08566696, 0.0900397 , 0.09859324, 0.09415018, 0.10097599,
       0.09073599, 0.09804901, 0.13081625, 0.08797927, 0.10022956,
       0.10424191, 0.08797445, 0.09195017, 0.09104276, 0.09301339,
       0.09215399, 0.08509491, 0.0985904 , 0.09957409, 0.1067749 ,
       0.09150939, 0.11023117, 0.08809075, 0.08578731, 0.11391371,
       0.08338571, 0.09357695, 0.08887634, 0.10249823, 0.09908702,
       0.0980972 , 0.10378296, 0.10083658, 0.11208318, 0.08465271,
       0.11457571, 0.08723874, 0.08447537, 0.09059171, 0.10333683,
       0.09357648, 0.08557113, 0.09895004, 0.09099763, 0.08504221,
       0.10767092, 0.08936311, 0.11107821, 0.08633238, 0.09607378,
       0.10025146, 0.08889523, 0.09979536, 0.0902828 , 0.11317839,
       0.08934006, 0.08476936, 0.10154527, 0.10178353, 0.10330073,
       0.09886324, 0.0947208 , 0.08532945, 0.1017685 , 0.10509054,
       0.10182354, 0.10194727, 0.10655113, 0.0908614 , 0.09385782,
       0.10195312, 0.09371979, 0.0861602 , 0.09138559, 0.09128418,
       0.09983855, 0.08431647, 0.09926949, 0.09233814, 0.09502868,
       0.08900847, 0.09206037, 0.08897968, 0.09371018, 0.09287144,
       0.08539812, 0.10097422, 0.13299811, 0.09425507, 0.08661209,
       0.1065158 , 0.09391107, 0.08917699, 0.09962913, 0.10798166,
       0.09613533, 0.08294485, 0.0913167 , 0.08449379, 0.09975325,
       0.08486515, 0.10688934, 0.08851916, 0.10340231, 0.1075841 ,
       0.09446003, 0.10867468, 0.08865929, 0.09873757, 0.08813448,
       0.09105758, 0.09465323, 0.09994899, 0.11954158, 0.09138349,
       0.08572651, 0.10994187, 0.09748647, 0.09897976, 0.09011849,
       0.09286258, 0.14656785, 0.10534486, 0.09081177, 0.11457993,
       0.08488277, 0.08735112, 0.10466302, 0.08932248, 0.09548879,
       0.09859367, 0.08597185, 0.0943161 , 0.10609695, 0.09684402,
       0.09436616, 0.09138359, 0.10549979, 0.09198689, 0.08993808,
       0.0932581 , 0.09862076, 0.091176  , 0.0977822 , 0.10562554,
       0.09136277, 0.09184416, 0.10706614, 0.10654519, 0.09828033,
       0.12033549, 0.09025095, 0.09066571, 0.11267412, 0.08806125,
       0.0856946 , 0.09834091, 0.08729341, 0.08762578, 0.11486711,
       0.08650407, 0.09407489, 0.08949018, 0.08946359, 0.09338883,
       0.10545923, 0.09710417, 0.09079479, 0.08708107, 0.08827413,
       0.09161381, 0.08407504, 0.09194864, 0.08385929, 0.09757403,
       0.08945245, 0.10137151, 0.08828937, 0.09037695, 0.10308665,
       0.09616268, 0.09496401, 0.10551678, 0.08425091, 0.09267004,
       0.08692037, 0.10639699, 0.09348654, 0.09062252, 0.10912468,
       0.08254156, 0.09799318, 0.09342707, 0.0871854 , 0.12715057,
       0.09151576, 0.10104419, 0.09240083, 0.09766743, 0.10358569,
       0.08720391, 0.08698902, 0.08792429, 0.09216941, 0.09614433,
       0.09943575, 0.10532247, 0.08696892, 0.09033883, 0.11085135,
       0.09531886, 0.09161019, 0.10439965, 0.08783409, 0.08439778,
       0.09822151, 0.09697177, 0.09741408, 0.08873423, 0.08950559,
       0.09379295, 0.0934535 , 0.08680522, 0.09577395, 0.09935866,
       0.11991577, 0.09289324, 0.09587351, 0.10192423, 0.09827727,
       0.10862114, 0.1108681 , 0.08906044, 0.0947914 , 0.08928736,
       0.09977403, 0.11087918, 0.09702905, 0.09092198, 0.10079819,
       0.09178124, 0.09393841, 0.09298065, 0.12582499, 0.10020515,
       0.10040765, 0.10222662, 0.09133381, 0.09181537, 0.09649208,
       0.09469988, 0.09047302, 0.09031744, 0.10296696, 0.0999685 ,
       0.08965902, 0.10402609, 0.10374819, 0.1052737 , 0.11117913,
       0.08853315, 0.08638067, 0.08998926, 0.09213832, 0.09629313,
       0.1140306 , 0.09321787, 0.09174977, 0.08872399, 0.10437907,
       0.09173873, 0.09934144, 0.09576096, 0.08927727, 0.08494002,
       0.09638585, 0.09933367, 0.08819056, 0.08668578, 0.08433326,
       0.09683318, 0.09673812, 0.09603997, 0.08468015, 0.09167268,
       0.09057835, 0.10957128, 0.08742132, 0.10960788, 0.11399335,
       0.10933345, 0.09424783, 0.09961331, 0.09444565, 0.08834438,
       0.08876905, 0.09462269, 0.09798484, 0.08587936, 0.088069  ,
       0.08272407, 0.08297431, 0.10375173, 0.09479706, 0.08675585,
       0.1362789 , 0.10492854, 0.10779105, 0.10120503, 0.0920762 ,
       0.10237568, 0.09164146, 0.09198915, 0.09251221, 0.09125487,
       0.09041284, 0.08701762, 0.10215709, 0.10719202, 0.0863915 ,
       0.09991372, 0.11586875, 0.09827154, 0.09610525, 0.09151957,
       0.10443095, 0.10450127, 0.08478188, 0.09308279, 0.10159231,
       0.09006653, 0.10569438, 0.08809022, 0.08882648, 0.09380926,
       0.09678476, 0.10361056, 0.08715399, 0.09613977, 0.09246645,
       0.11158059, 0.09344514, 0.08600008, 0.08681162, 0.095156  ,
       0.09644125, 0.08309219, 0.09790196, 0.09576489, 0.1011812 ,
       0.094913  , 0.10256293, 0.09666689, 0.09982654, 0.08887469,
       0.08785883, 0.09995021, 0.09686308, 0.08494064, 0.11402313,
       0.09586276, 0.09286579, 0.08944898, 0.09230062, 0.09191172,
       0.08732818, 0.08756226, 0.10364515, 0.0916063 , 0.10352059,
       0.10253938, 0.10142986, 0.10514955, 0.08989041, 0.09099156,
       0.09720325, 0.08542223, 0.0939022 , 0.14147665, 0.09237859,
       0.09430104, 0.09876727, 0.08712032, 0.08909725, 0.08817901,
       0.10043353, 0.11183769, 0.08784256, 0.09477271, 0.0892226 ,
       0.09586816, 0.08257236, 0.09482281, 0.08758915, 0.08964796,
       0.08596233, 0.11318906, 0.09548841, 0.09321208, 0.08788761,
       0.09375089, 0.09771351, 0.10393623, 0.09536583, 0.09128749,
       0.09536209, 0.09648643, 0.11275198], dtype=float32), array([[[[-0.0324141 ],
         [ 0.03352994],
         [-0.0191069 ],
         ...,
         [ 0.00147527],
         [-0.02354529],
         [ 0.02900861]],

        [[-0.00864201],
         [ 0.0423145 ],
         [ 0.00106678],
         ...,
         [ 0.0063873 ],
         [-0.02655365],
         [ 0.03774066]],

        [[ 0.00650709],
         [-0.01635031],
         [ 0.00586856],
         ...,
         [ 0.01295718],
         [-0.00437561],
         [-0.01935106]]],


       [[[-0.02620599],
         [ 0.03713913],
         [ 0.00896772],
         ...,
         [-0.00994031],
         [-0.00155905],
         [ 0.01983021]],

        [[ 0.01354893],
         [-0.00478063],
         [ 0.02594092],
         ...,
         [ 0.00235448],
         [ 0.01189577],
         [ 0.00362295]],

        [[ 0.02361674],
         [ 0.00102432],
         [-0.01730915],
         ...,
         [ 0.02820601],
         [ 0.00139326],
         [ 0.0048205 ]]],


       [[[-0.01832935],
         [ 0.00835015],
         [ 0.00762406],
         ...,
         [-0.02126941],
         [ 0.00504168],
         [ 0.03336411]],

        [[ 0.00418711],
         [-0.00599014],
         [ 0.00648737],
         ...,
         [-0.02641674],
         [ 0.00398841],
         [-0.00042081]],

        [[ 0.01128568],
         [ 0.0238181 ],
         [ 0.01221545],
         ...,
         [ 0.00065189],
         [-0.03266658],
         [-0.01807884]]]], dtype=float32), array([[[[ 0.02358059,  0.05000296,  0.00684468, ...,  0.03633358,
          -0.00733569, -0.01540812],
         [-0.04537474,  0.02570686, -0.08409727, ...,  0.02863675,
           0.05194673, -0.02707922],
         [-0.04801051,  0.0072985 ,  0.01753902, ..., -0.02425634,
          -0.05165655,  0.05294678],
         ...,
         [-0.03135815, -0.02279795,  0.0278282 , ...,  0.01650609,
           0.04273248, -0.00754779],
         [ 0.04259082, -0.04016594,  0.05606977, ...,  0.00132007,
           0.03554107, -0.03483242],
         [-0.0628034 ,  0.00968635, -0.06568979, ..., -0.01254924,
          -0.05122786, -0.02206477]]]], dtype=float32), array([0.99514514, 1.0234069 , 1.0006641 , 1.0240533 , 0.98543465,
       1.000968  , 0.99138135, 0.9882306 , 0.99655986, 0.9930441 ,
       1.0008434 , 1.0090276 , 1.0014913 , 0.98675185, 1.008706  ,
       1.0012959 , 0.9906432 , 1.0005776 , 1.0099318 , 1.0286787 ,
       1.0126883 , 0.99961734, 0.98795915, 1.0086846 , 0.98389024,
       1.0106335 , 1.0167477 , 0.99076176, 1.02341   , 1.0165163 ,
       0.9925276 , 1.0301036 , 0.9878818 , 1.0004555 , 0.98896307,
       0.99278814, 0.9937678 , 0.99174106, 0.98187983, 0.99145937,
       0.9846902 , 0.9978454 , 0.9963538 , 0.9941829 , 0.9970824 ,
       1.0013688 , 0.9867485 , 1.0378659 , 1.0370771 , 1.0211903 ,
       0.9938952 , 1.0015    , 1.0258945 , 0.99418044, 0.992715  ,
       0.99900806, 0.99309725, 1.0189227 , 0.9890594 , 1.0064685 ,
       0.993567  , 1.0137305 , 0.99612427, 0.97976553, 0.98308694,
       0.99498796, 1.0110235 , 0.99927783, 0.9814211 , 0.9987409 ,
       1.0210757 , 0.9921483 , 1.0089885 , 0.99345344, 0.97188926,
       0.99480975, 0.9915849 , 0.9948977 , 0.99678916, 1.0050269 ,
       1.0077412 , 1.000845  , 1.0347809 , 0.9963173 , 0.99059814,
       0.98947453, 0.99430984, 1.0108632 , 0.98639345, 0.9901339 ,
       1.0062437 , 0.99902683, 0.992786  , 0.98289317, 1.0013783 ,
       1.0006772 , 0.9957059 , 1.0248312 , 0.99223393, 1.0264664 ,
       1.0025694 , 0.99074197, 0.98659563, 0.992723  , 0.9784005 ,
       0.9908949 , 0.99434334, 0.9863994 , 1.0047987 , 0.990055  ,
       0.9921981 , 0.99612695, 1.004772  , 0.9975311 , 1.0016458 ,
       1.0484011 , 0.99385524, 0.992537  , 0.99493295, 0.9944868 ,
       0.9937768 , 1.0007467 , 0.99188614, 0.99937224, 0.99433947,
       0.9886113 , 1.0068661 , 1.015294  , 0.99147797, 0.9959465 ,
       0.99874353, 0.9988761 , 1.0044961 , 1.0053059 , 1.0186671 ,
       1.0016059 , 0.9868243 , 0.99502736, 0.9961901 , 0.9804288 ,
       0.98529696, 1.0042591 , 0.9986265 , 1.0208135 , 1.0072869 ,
       0.98184365, 0.9980371 , 0.99150723, 1.0233296 , 0.9964936 ,
       0.99854666, 1.0203711 , 1.0024507 , 1.0052415 , 0.99585664,
       0.99981904, 0.9921953 , 1.0008858 , 0.9962565 , 0.98943377,
       1.0069908 , 1.0044016 , 0.9935344 , 0.9925516 , 0.9966517 ,
       0.9835997 , 0.9955035 , 0.99540555, 1.0020679 , 0.99739254,
       1.0032008 , 1.0066549 , 0.99095803, 0.98496634, 0.9955572 ,
       0.9907777 , 1.0006075 , 1.0028199 , 0.9940711 , 0.99735624,
       1.0172594 , 0.994469  , 1.0107492 , 1.0045967 , 1.0099002 ,
       0.9891702 , 0.9945363 , 1.0095506 , 0.99284106, 0.9880597 ,
       0.99359274, 1.0010058 , 0.99679136, 0.99843323, 0.9945281 ,
       0.98052025, 0.98560274, 0.9865593 , 1.0308527 , 0.99059117,
       1.0018197 , 0.99630374, 0.99661964, 1.0165169 , 1.0103345 ,
       0.9946877 , 0.9980614 , 0.9966096 , 1.0076079 , 0.9829125 ,
       0.99557054, 1.003206  , 1.0012211 , 1.000677  , 1.0229602 ,
       1.0153456 , 1.0072852 , 1.0074567 , 0.9993495 , 1.0120872 ,
       1.0156801 , 0.9954183 , 1.0038482 , 0.9956571 , 1.0078276 ,
       1.000429  , 0.9859247 , 0.9990097 , 0.9882656 , 0.99858683,
       0.9826022 , 1.0032011 , 0.9932322 , 1.0197634 , 0.9927888 ,
       0.9966679 , 1.0202701 , 0.9960633 , 0.9976675 , 0.9939644 ,
       0.990368  , 0.9890383 , 1.0090871 , 0.99641514, 0.98337144,
       1.0004021 , 1.0277627 , 0.994742  , 1.0106214 , 0.9896777 ,
       0.9942771 , 0.99312025, 1.0174495 , 1.0073882 , 1.0027586 ,
       1.0042069 , 0.9996468 , 0.98848885, 0.9974666 , 1.0007026 ,
       0.99714345, 0.99781066, 0.994328  , 0.98815084, 1.0018761 ,
       1.0213825 , 0.9994588 , 1.0130504 , 0.9884134 , 0.9931349 ,
       0.9988447 , 0.9967303 , 0.988326  , 0.99798363, 0.9925878 ,
       0.99708116, 1.0154933 , 1.0207859 , 1.0051912 , 0.9903559 ,
       0.9990213 , 1.0075256 , 0.9907838 , 0.99520814, 1.0024818 ,
       1.0047848 , 0.99629843, 1.011275  , 0.9911815 , 0.98575425,
       0.999403  , 0.995832  , 0.98902255, 0.99603236, 1.003392  ,
       0.9942676 , 0.9982991 , 0.9958533 , 0.9906541 , 0.99752444,
       0.9920828 , 0.9955671 , 1.0076252 , 0.99285525, 0.9916088 ,
       0.98912215, 1.0202793 , 0.99598926, 0.9836146 , 0.9902476 ,
       0.9846976 , 1.0061003 , 1.026861  , 1.004638  , 0.9820422 ,
       0.9910437 , 0.9929083 , 0.9951985 , 1.0106523 , 1.0037465 ,
       0.9831346 , 1.0082593 , 1.0030254 , 0.99518704, 0.99879515,
       0.9970227 , 0.9934144 , 0.9947984 , 0.9997553 , 1.0053505 ,
       1.0161824 , 0.99068934, 0.9853198 , 1.0245259 , 0.98133767,
       0.9929627 , 0.9938188 , 0.9848971 , 0.99692124, 1.026181  ,
       0.9996069 , 0.9981145 , 0.99234366, 0.99507207, 0.99521977,
       1.0003561 , 0.9972717 , 1.0377073 , 1.0042136 , 1.0015246 ,
       0.997991  , 0.9890123 , 0.9968761 , 1.0084698 , 1.0055252 ,
       1.0025669 , 1.0052786 , 0.99134606, 1.0021391 , 1.0062816 ,
       0.99533796, 1.0016131 , 1.0373176 , 1.0129155 , 1.0091206 ,
       0.99665916, 1.0160784 , 1.0159805 , 0.99892485, 0.99780273,
       1.014108  , 0.9983754 , 0.9863462 , 1.0034215 , 0.9916416 ,
       1.000569  , 0.9900312 , 0.9839267 , 0.99693984, 0.9966035 ,
       0.98765856, 0.9966775 , 1.0079262 , 0.99534875, 1.0077045 ,
       0.9974241 , 0.9862915 , 1.0013322 , 1.0092053 , 0.99306893,
       1.0103838 , 0.997285  , 1.0025133 , 0.9966894 , 1.0046388 ,
       0.992445  , 1.0002449 , 1.0209824 , 0.98569596, 1.0005096 ,
       1.0036733 , 1.0134183 , 0.9948907 , 0.9935888 , 0.99346215,
       1.0014832 , 0.99564123, 0.9976133 , 1.0102191 , 0.98499787,
       1.0007932 , 0.99215525, 0.99597514, 0.99094546, 1.0059977 ,
       0.9945025 , 0.99616545, 1.0452102 , 1.006288  , 0.9861385 ,
       0.9869404 , 1.0246092 , 0.9761477 , 1.002124  , 1.0136275 ,
       0.98950595, 1.0085807 , 0.99640256, 1.0051925 , 1.0070398 ,
       0.99611354, 1.0146911 , 1.003656  , 1.0193533 , 1.0073892 ,
       0.9932713 , 0.99386585, 1.0068644 , 1.0023274 , 0.9966594 ,
       0.9895034 , 1.0044941 , 1.0121213 , 0.9969574 , 0.9919566 ,
       0.99277705, 0.9917671 , 0.99882215, 1.0139577 , 0.99687105,
       0.99402165, 1.0492209 , 0.9947844 , 0.995234  , 1.0073404 ,
       1.0188713 , 0.9964605 , 0.98504454, 0.996688  , 0.99218726,
       0.9928682 , 0.993717  , 1.0006938 , 1.003831  , 1.0342172 ,
       1.0073489 , 1.0153397 , 0.9881849 , 0.9907854 , 0.9898837 ,
       0.9987223 , 0.99749255, 0.987143  , 1.0122808 , 0.9992978 ,
       1.0003768 , 0.99706227, 1.0081437 , 1.0026431 , 1.0104128 ,
       0.9938218 , 0.9988208 , 0.9890412 , 0.9877171 , 0.9892515 ,
       1.0239561 , 0.98608   , 0.9918612 , 0.9935971 , 1.0079755 ,
       0.98668474, 1.0223053 , 1.0046996 , 0.9879    , 0.9969006 ,
       0.9947592 , 1.002679  , 0.9924917 , 0.9963218 , 0.9977898 ,
       1.0058006 , 0.99323255, 1.0036093 , 1.0103034 , 0.99926966,
       1.002601  , 1.0010759 , 0.9956588 , 1.0102708 , 0.9828505 ,
       0.99165547, 0.98845863, 0.9914979 , 0.9939224 , 0.99615914,
       0.99300945, 0.9922329 , 1.0009023 , 0.99218345, 1.0111165 ,
       0.9979226 , 1.0005571 , 1.0022854 , 0.9989252 , 1.0081266 ,
       1.0155163 , 0.9802996 , 1.0206943 , 0.9953131 , 0.997931  ,
       0.99170893, 0.99559575, 0.99916285, 0.9939384 , 0.9890429 ,
       1.0117376 , 1.0095549 , 0.99480563, 0.9974582 , 0.9953247 ,
       1.0248613 , 1.0353471 , 1.0013381 , 1.0071404 , 1.0267788 ,
       0.99160045, 1.0205836 , 0.993561  , 1.0339311 , 0.9953157 ,
       0.99564594, 0.9978548 , 1.0000759 , 0.9872598 , 0.98938674,
       0.9992451 , 0.99141127, 0.9850071 , 0.9985078 , 1.007121  ,
       1.0082172 , 1.0249075 , 0.9956187 , 1.0069908 , 0.97537684,
       0.9952167 , 0.99983275, 1.0068593 , 0.9970171 , 1.037928  ,
       1.0094538 , 0.9964077 , 0.9884295 , 0.99732316, 1.0120422 ,
       1.0183071 , 0.9953566 , 0.9922675 , 1.0065812 , 0.9881371 ,
       0.99763834, 0.98671067, 0.99180037, 1.0176507 , 1.0067105 ,
       0.99655735, 0.99696034, 0.9923736 , 0.9976638 , 0.9825334 ,
       0.9928395 , 0.9904245 , 0.9878319 , 1.0009036 , 0.9859491 ,
       0.99764115, 1.0135562 , 0.99288416, 0.9998867 , 0.9859276 ,
       1.0210277 , 0.9791632 , 1.0045729 , 1.0130085 , 0.9901629 ,
       0.9970671 , 1.0009298 , 0.9947374 , 1.0068053 , 0.9926711 ,
       0.9970592 , 0.99066204, 0.9876153 , 1.0149145 , 0.9977302 ,
       0.9949106 , 0.9812147 , 0.99359155, 0.9978903 , 0.99688166,
       1.0169479 , 0.98673517, 0.99718845, 1.0066531 , 1.000576  ,
       0.99124086, 1.0028596 , 0.98952127, 1.0161271 , 0.99792117,
       1.0108536 , 0.98750925, 0.9990798 , 0.99141115, 0.9990823 ,
       1.0030982 , 0.99642265, 0.9939694 , 0.9803687 , 1.0000811 ,
       0.9902245 , 0.98779255, 0.9945705 , 1.016564  , 0.98930293,
       0.9831781 , 1.0232263 , 1.0057532 , 0.99962044, 1.0025194 ,
       1.009741  , 0.9929665 , 0.99638873, 0.9954152 , 0.9927533 ,
       0.9898181 , 1.0014058 , 0.99764097, 0.99151033, 0.9906907 ,
       1.021105  , 1.0019133 , 0.9899046 , 0.98974687, 1.0088708 ,
       0.9949217 , 0.9950285 , 1.0092393 , 1.0099766 , 0.99561   ,
       0.9885127 , 1.0045261 , 1.0017644 , 0.9929587 , 0.9961621 ,
       1.0025624 , 0.99732155, 0.9953417 , 1.0004766 , 1.0034904 ,
       0.9919635 , 0.9958792 , 0.9849082 , 0.99377257, 0.9871474 ,
       0.99393463, 0.9954864 , 0.9903551 , 1.0084344 , 0.9904488 ,
       0.9929932 , 0.9782303 , 0.99196434, 0.9967941 , 0.9958309 ,
       1.0081943 , 1.0175279 , 1.0067545 , 0.97770745, 0.9992678 ,
       1.0006887 , 0.9927179 , 0.99354184, 1.0012629 , 1.0048661 ,
       0.98086184, 1.0016755 , 1.0088173 , 1.0147305 , 1.010492  ,
       1.0005666 , 0.99883646, 0.98680115, 0.9918561 , 1.0139446 ,
       0.9897211 , 0.9973774 , 0.98418945, 0.9938299 , 1.0043933 ,
       0.99308485, 1.0311335 , 0.9783253 , 1.0124332 , 0.99952227,
       0.99485105, 1.0232393 , 0.9980003 ], dtype=float32), array([-1.42859097e-03,  1.04776425e-02, -2.29291860e-02, -2.90126284e-03,
       -7.98911229e-03, -1.24222990e-02, -2.79665971e-03, -8.38882569e-03,
       -1.77443717e-02, -2.51189969e-03,  3.88016482e-03, -1.03681134e-02,
        6.83441933e-04, -1.71381962e-02,  6.81625027e-03,  9.34762321e-03,
       -6.85990462e-03,  8.91569350e-03, -1.49559369e-02, -3.25704291e-02,
       -5.49753197e-04, -4.54957597e-03,  7.20304553e-04, -1.23102888e-02,
       -6.10256987e-03,  1.29339695e-02,  6.74635731e-03, -7.96836428e-03,
        2.42277049e-02, -4.15957766e-04, -7.46258255e-03,  1.22372489e-02,
       -2.47483533e-02,  9.86261480e-03, -1.97829697e-02,  3.35516431e-03,
       -1.61407713e-03, -4.89384308e-03, -1.82402239e-03, -1.68868862e-02,
       -1.64651144e-02,  4.81367949e-03,  7.85192288e-03,  9.19763348e-04,
       -9.50285792e-03, -4.22662869e-03, -6.84931222e-03,  2.74023004e-02,
        3.64528177e-03,  4.20490168e-02, -1.07181501e-02, -8.13157205e-03,
        2.73537962e-03,  2.44320882e-03, -1.01249376e-02, -1.46570662e-02,
        1.22063942e-02,  1.41395759e-02, -1.07463608e-02,  2.31291912e-02,
       -2.16237898e-03, -2.92317085e-02, -5.21646347e-04, -2.19610669e-02,
       -4.67192847e-03, -1.00113712e-02, -1.77668426e-02, -9.86559223e-03,
       -1.72576234e-02, -6.98919315e-03, -3.62018906e-02,  2.04843376e-03,
        2.84453128e-02, -1.79840194e-04, -2.35697590e-02, -1.96151948e-03,
       -1.20835006e-02,  4.66912473e-03, -5.72380563e-03,  1.27024688e-02,
       -3.92477289e-02,  3.85721284e-03,  1.86862405e-02, -1.06228413e-02,
       -2.26635784e-02, -1.01720821e-02, -4.47993213e-03, -1.77236833e-02,
       -1.77410021e-02, -7.44447764e-03,  2.27084607e-02, -1.44975726e-02,
        2.65228824e-04, -1.86442435e-02, -1.21434098e-02,  1.87676549e-02,
        2.02554371e-03,  1.09271947e-02, -3.07186274e-03,  2.11237185e-03,
        9.27891233e-04, -2.66490504e-02, -1.45874284e-02,  1.81208248e-03,
       -1.72288250e-02, -3.27778893e-04, -1.36037441e-02, -2.25972682e-02,
        9.73351672e-03, -2.96879951e-02, -3.69328866e-03, -7.52555963e-04,
        2.89446563e-02, -2.86252820e-03,  5.47771156e-03,  4.31094579e-02,
       -5.31580811e-03, -1.26634596e-03, -6.98103057e-03,  1.28770445e-03,
       -3.56270373e-03, -2.94835661e-02, -3.30396462e-04, -4.27586143e-04,
       -8.54851305e-03, -3.91998934e-03,  1.26562128e-02,  2.39833035e-02,
       -1.05164489e-02, -1.17690749e-02,  1.03654237e-02,  1.09038549e-04,
        8.00975016e-04,  4.73648403e-03, -2.13071629e-02, -5.98481670e-03,
       -8.79263505e-03, -4.67796950e-03,  5.95872814e-04, -1.27656953e-02,
       -1.58742666e-02, -5.39811281e-03,  6.08964125e-03, -9.80325695e-03,
        6.65999297e-03, -1.01544624e-02, -1.15265101e-02, -7.81467999e-04,
       -1.68291386e-02, -1.35705154e-02,  6.29371637e-03, -3.28556634e-02,
       -2.23623384e-02, -2.81403959e-02, -4.48901160e-03, -1.16406763e-02,
       -9.02097579e-03, -2.18080916e-03,  7.44171266e-05, -7.01038539e-03,
        2.60054842e-02,  2.40861960e-02, -1.89233962e-02, -2.40811314e-02,
       -5.27619803e-03, -1.07441191e-02,  4.71635954e-04,  2.73213838e-03,
        2.82165757e-03, -6.13418058e-04, -2.82019912e-03, -6.23067329e-03,
       -1.72883961e-02, -1.50943566e-02, -2.14087944e-02, -1.65426508e-02,
        1.09174950e-02, -5.03731845e-03, -1.79234408e-02,  3.40705761e-03,
       -1.01294527e-02, -1.84516199e-02,  1.64739415e-03,  2.32212921e-03,
       -1.38983747e-03, -7.24242674e-03,  4.87900106e-03, -3.57724447e-03,
       -8.21409281e-03,  3.13637918e-03,  7.84807466e-03, -4.96028084e-03,
        5.45702316e-03,  4.78121910e-06, -6.30378257e-03, -1.44232614e-02,
       -1.04986513e-02, -9.04225558e-03,  1.77114401e-02, -1.11737838e-02,
       -1.11619327e-02, -4.94913338e-03, -1.03451451e-02,  8.92830919e-03,
        6.96920184e-03, -6.43408019e-03,  9.01483581e-05, -9.47124418e-03,
       -3.99997048e-02, -1.93499774e-02, -9.30118607e-04, -5.10336608e-02,
       -1.50722507e-02, -1.82963721e-02,  1.35986432e-02,  3.96700352e-02,
       -4.90714889e-03,  1.53916338e-02,  1.48335809e-03, -1.48809580e-02,
       -2.42105150e-03, -8.52305070e-03,  9.54737607e-03, -2.58233747e-03,
       -9.64334002e-04, -2.72004250e-02, -1.90505385e-02, -6.16006926e-03,
       -6.36301842e-03, -5.42232487e-03, -1.96189377e-02,  1.02819176e-02,
       -6.54055085e-03, -5.64731099e-02,  7.05255382e-03, -9.85505711e-03,
       -1.57944243e-02, -6.08657300e-03, -4.65322658e-03, -2.66448595e-03,
        1.32354442e-03, -9.61350091e-03, -6.02767291e-03, -2.16396861e-02,
       -1.28045054e-02,  3.40767438e-03,  1.35489097e-02, -3.01327836e-02,
       -1.79346800e-02, -1.34690199e-02, -1.77768487e-02,  1.07241636e-02,
        1.41285220e-02, -2.83124810e-03, -1.40790781e-02,  2.78958760e-04,
        6.65077567e-03, -1.73668116e-02, -9.05816536e-03,  6.26682490e-03,
       -5.11847390e-03, -2.78367172e-03, -5.97658893e-03, -7.76789384e-03,
       -4.58359346e-03,  2.33203471e-02,  2.67328206e-03, -2.97900978e-02,
       -1.81039926e-02,  9.36237257e-03, -2.24221833e-02, -4.54453938e-03,
       -1.12475641e-02, -6.71316870e-03, -7.16233579e-03, -1.72130466e-02,
        1.30399950e-02,  1.83189306e-02, -1.35709234e-02, -1.31505225e-02,
       -6.11500628e-03, -2.05675084e-02, -4.01918218e-03, -4.74527432e-03,
       -8.08466692e-04,  4.31252737e-03, -3.68410419e-03,  1.45977857e-02,
       -4.09970665e-03, -1.35866916e-02, -1.11729270e-04, -7.53779663e-03,
       -5.72157744e-03, -1.90206207e-02, -8.97944346e-03, -3.74087738e-03,
       -5.98584348e-03, -1.82362311e-02, -2.73253191e-02,  6.43262547e-03,
       -2.59592314e-03, -6.44909311e-03,  1.76898241e-02, -1.08270440e-02,
       -8.74490291e-03, -1.15523729e-02, -1.49505155e-03,  2.34132679e-03,
       -8.48142151e-03, -8.73215590e-03, -1.59685016e-02, -3.49800289e-03,
       -3.03555429e-02,  2.37904880e-02, -1.82858296e-02, -1.34122763e-02,
       -9.31905117e-03,  2.58532516e-03,  2.35689688e-03,  1.77750108e-03,
        5.00722555e-04,  1.13218594e-02, -2.67127180e-03,  2.81617953e-03,
        4.01487434e-03, -1.49669470e-02,  3.87447397e-03, -9.22617130e-03,
       -1.23587763e-02,  4.41323547e-03, -1.33116078e-02, -2.64383806e-03,
        2.84104754e-05,  3.39001194e-02, -1.99180357e-02, -7.05364021e-03,
       -1.30581474e-02, -2.16600765e-02, -2.31484795e-04,  2.96647735e-02,
        6.34319207e-04,  1.67644620e-02, -1.95286272e-03, -1.38117839e-02,
       -9.64769814e-03,  7.34782033e-03, -4.81246226e-03,  1.13261426e-02,
        1.61079187e-02, -6.75181951e-03, -2.89519900e-03, -1.07496185e-02,
       -2.72569596e-03, -1.20516876e-02, -3.47013026e-02,  1.10013355e-02,
        1.54557722e-02, -8.53837375e-03, -4.37003141e-03, -1.12159699e-02,
       -5.56663051e-03,  3.11673060e-03,  3.45811732e-02, -1.45818889e-02,
        2.09596343e-02, -1.58577990e-02, -3.40143703e-02, -2.73145493e-02,
       -3.71590257e-03, -4.02178317e-02, -2.02338584e-02,  4.90166619e-03,
       -7.61673599e-03,  1.74938273e-02, -1.78871618e-03,  1.29550215e-04,
       -2.30856538e-02, -3.40924854e-03, -5.94827998e-03,  2.17886246e-03,
        3.59601853e-03,  1.51154166e-02, -1.18771140e-02, -1.32242488e-02,
        7.42908707e-03, -2.68070633e-03, -8.92770477e-03, -5.27707953e-03,
       -4.75193316e-04,  9.55616031e-03,  6.69607800e-03, -8.00853781e-03,
        1.34348019e-03,  1.41268913e-02,  8.42452515e-03, -1.05288289e-02,
       -9.48142988e-05,  1.03702093e-03, -8.53828620e-03, -2.07228586e-04,
       -2.29293015e-02, -5.76382875e-03, -5.05614281e-03, -3.68644409e-02,
       -2.39177630e-03,  1.87110826e-02,  9.88469576e-04, -9.05577186e-03,
       -6.83145551e-03, -1.60352904e-02,  1.17774094e-02, -6.11658813e-03,
       -1.42070989e-03, -5.50964801e-03,  7.42653850e-03, -4.72219614e-03,
       -5.92039851e-03,  2.90086549e-02,  3.57113779e-02,  1.18510537e-02,
       -6.96468214e-03,  2.89422143e-02, -2.27658041e-02, -1.26589369e-02,
       -2.97980104e-03, -9.98381618e-03,  4.57847025e-03,  2.05482263e-02,
       -8.14550743e-03, -2.36849929e-03, -1.23862475e-02,  1.86517984e-02,
       -1.99830886e-02,  6.26756926e-04,  4.51021537e-04, -1.59550167e-03,
       -1.08607272e-02,  2.15106271e-03, -5.11946976e-02, -2.35514343e-02,
       -7.67028751e-03,  8.30192398e-03,  1.03179514e-02, -5.50854951e-03,
       -1.68540999e-02, -2.27054488e-02, -7.38502573e-03, -2.94825472e-02,
       -2.53627952e-02, -3.57668218e-03, -1.68109965e-02, -3.95601727e-02,
       -1.91156159e-03, -1.86847895e-02, -6.24073250e-03, -2.95492671e-02,
       -2.11355481e-02, -2.28497945e-02, -1.50696281e-02,  2.23337300e-03,
        1.05342548e-02, -7.99185317e-03,  7.37195322e-03, -5.39544830e-03,
        1.61243752e-02, -3.23758624e-03, -6.96418434e-03, -1.09464303e-02,
        7.77812302e-03,  9.76689346e-03,  2.77482923e-02,  5.50975185e-03,
       -1.69683825e-02,  2.57030334e-02,  3.82127566e-03,  3.21359816e-03,
       -1.58081308e-03,  4.37843092e-02, -1.45110013e-02, -1.45284925e-02,
       -7.69618340e-03,  5.72148710e-04,  2.58446019e-03, -2.50522867e-02,
       -9.73879080e-03,  5.63354697e-03, -3.74433212e-02, -3.26657575e-03,
       -3.54753458e-04,  6.13667490e-03,  1.09918546e-02, -1.67181473e-02,
        9.65669937e-03, -9.23625426e-04, -2.77459323e-02,  3.79646989e-03,
        7.82248005e-03, -7.81228207e-03,  5.68733271e-03, -7.85344280e-03,
       -1.81187484e-02, -3.58468294e-03,  1.09493900e-02,  9.98763554e-03,
        4.56627831e-03,  2.06496622e-02, -1.39621831e-03, -2.85324350e-05,
        9.79404058e-03, -8.43185652e-03, -8.96529164e-05, -7.77174393e-03,
        5.40681975e-03, -5.60994446e-03,  3.64077813e-03, -8.85790307e-03,
       -4.84537508e-04,  1.33502698e-02,  5.21952193e-03,  1.47618474e-02,
       -1.21900057e-02,  5.37396083e-03, -2.03104503e-02,  3.72964982e-03,
       -7.47990049e-03, -2.37556919e-02,  1.35303685e-03, -2.35113371e-02,
       -8.04095529e-03, -4.11684578e-03, -1.21929739e-02,  1.81643050e-02,
        2.90250930e-04, -4.08289628e-03, -4.15431671e-02,  1.14356074e-02,
       -1.53113352e-02,  1.34942047e-02, -4.54828725e-04, -8.02768953e-03,
       -6.09910861e-03, -2.05268133e-02,  2.05876939e-02,  1.24129821e-02,
        7.77263939e-03, -1.24628739e-02,  2.08340865e-02, -2.03557350e-02,
        2.94672623e-02, -1.05406193e-03, -1.61738489e-02,  5.08397212e-03,
       -6.53794408e-03, -1.62672065e-02, -1.72497742e-02, -4.02978668e-03,
       -5.00020105e-03, -8.87997914e-03, -8.48468207e-03,  2.74488851e-02,
       -3.85195203e-02,  2.02830392e-03,  5.28099341e-03,  2.30700020e-02,
       -3.18021290e-02, -1.43671199e-03,  1.96774560e-03, -2.26902450e-03,
       -4.93021496e-02, -2.53661796e-02,  1.31571833e-02, -1.01711024e-02,
       -1.94363631e-02,  7.44722877e-03,  1.23333130e-02,  4.04970534e-03,
       -7.05995597e-03,  1.07082315e-02,  7.22035393e-03, -3.21546081e-03,
       -4.64656763e-03, -1.10316640e-02,  7.03059975e-03,  1.52493352e-02,
       -9.77090467e-03, -7.61586986e-03,  4.85306373e-03, -3.11252549e-02,
       -9.82543733e-03, -5.78970509e-03, -9.21452697e-03, -5.76242281e-04,
       -2.08843662e-03, -9.83958412e-03, -1.77254155e-02, -1.26416085e-03,
        3.50296940e-03, -1.07007874e-02, -7.24076701e-04, -8.40685517e-03,
        1.62281319e-02, -2.34559737e-02, -6.45097531e-03,  2.45470693e-03,
       -1.25786504e-02,  3.16189532e-03, -7.18490360e-03, -1.41401170e-02,
       -5.55800158e-04, -8.95285141e-03, -8.08525551e-03,  4.75386949e-03,
       -1.11998618e-02,  2.40373649e-02,  2.17766315e-02, -4.43541668e-02,
       -7.44238868e-03, -6.38853433e-03,  2.13119597e-03,  6.77283714e-03,
       -2.08451729e-02, -1.47452659e-03, -7.37888506e-03,  8.04654043e-03,
       -1.35776671e-02, -6.28980063e-03, -1.70397223e-04,  1.35587621e-02,
        4.67207516e-03, -3.68798487e-02,  1.12629365e-02, -2.41712574e-02,
       -1.60499674e-03, -6.00830326e-03,  5.25020342e-03,  1.85331032e-02,
       -8.53712205e-03, -2.71494361e-03, -2.65649930e-02, -2.61333603e-02,
        3.67089058e-03, -1.23610981e-02, -3.36021069e-03, -1.61683597e-02,
       -1.48174101e-02, -1.78579949e-02, -2.66285483e-02,  4.68783546e-03,
        1.17195267e-02, -1.10015320e-02, -1.16493674e-02,  2.69277696e-03,
       -2.21870653e-02,  3.51695955e-04,  3.65215493e-03, -1.49560431e-02,
       -2.44237971e-03, -2.55995225e-02, -1.12247691e-02, -2.80865151e-02,
       -4.54710722e-02,  9.56340041e-03, -3.30919810e-02,  2.33173231e-03,
        1.28186382e-02, -8.05272441e-03, -4.23599547e-03,  5.10806916e-03,
        4.24865773e-03, -3.78647144e-03, -9.58377682e-03,  8.33520386e-03,
        2.29685963e-03, -1.46920886e-02,  1.68490945e-03,  1.73958894e-02,
       -8.54938384e-03, -1.36285205e-04, -3.77347833e-03, -4.77024773e-03,
       -1.11512830e-02, -2.38414574e-02, -1.17066391e-02, -8.66191741e-03,
        4.47299331e-03,  7.76345097e-03, -3.43789370e-03, -5.45062416e-04,
       -7.31345033e-03, -3.18842530e-02, -6.00055885e-03, -2.79846303e-02,
       -5.03947102e-02, -1.09472510e-03, -3.24113630e-02,  1.71246547e-02,
        3.30198668e-02, -3.23901102e-02, -3.16967955e-03, -6.48421794e-03,
        1.47664817e-02, -7.16883969e-03,  1.33149968e-02,  6.32165233e-03,
       -2.86244927e-03, -7.37904198e-03,  1.70283648e-03,  1.33335339e-02,
       -2.56492924e-02,  2.36050133e-02,  2.23202212e-03,  5.44472307e-04,
       -1.50546096e-02,  1.67487236e-03, -7.49550387e-03, -2.45527606e-02,
        1.17054423e-02, -1.92983802e-02, -1.12956790e-02,  8.92393570e-03,
       -9.74080642e-04,  7.83019699e-04,  1.10039907e-03, -2.91391406e-02,
       -1.27734113e-02,  2.16858485e-03,  2.37729792e-02, -4.00713272e-03],
      dtype=float32), array([ 9.83460620e-02,  4.50787880e-03,  1.38332576e-01,  3.62564102e-02,
       -1.11700609e-01,  8.93423930e-02, -5.02679721e-02, -3.42237875e-02,
        2.04842389e-01, -4.57734987e-02, -4.01652642e-02,  2.10373461e-01,
       -2.68427879e-02,  4.27402146e-02, -5.30956276e-02,  4.32262849e-03,
        2.14291796e-01,  3.41622606e-02,  1.47745892e-01,  2.11628899e-01,
        1.46178380e-01, -2.86347289e-02, -2.84428056e-02, -2.81316298e-03,
       -4.81820852e-02,  7.92674795e-02,  1.81106720e-02,  6.04137890e-02,
        2.34451075e-03,  1.75715350e-02, -9.11202133e-02, -7.71518284e-03,
        9.71759036e-02, -1.16329238e-01,  1.26983404e-01, -5.92820300e-03,
       -8.03139061e-02, -4.73940372e-02,  1.92842335e-02,  1.80926487e-01,
       -5.99059835e-02, -3.11435703e-02, -1.40241504e-01,  8.14314485e-02,
       -3.41411047e-02,  1.61919639e-01,  1.50011554e-01, -4.05741408e-02,
        1.92702234e-01, -7.93777406e-02,  7.09820241e-02,  1.05816707e-01,
        7.23274946e-02, -3.63611355e-02,  6.87966347e-02,  1.46188259e-01,
        3.51494253e-02, -9.79250595e-02,  6.19086549e-02, -7.54942968e-02,
       -7.63812065e-02,  1.89920321e-01, -5.31244315e-02,  1.51403099e-01,
        7.09963664e-02,  1.38296217e-01,  4.68086712e-02, -1.08271666e-01,
       -1.11968788e-04,  9.62594077e-02,  2.25312218e-01, -1.12379842e-01,
        6.64655194e-02, -3.19149382e-02,  5.21516539e-02,  3.06235440e-02,
        1.42853826e-01, -3.24621312e-02,  6.01028837e-02, -5.13431355e-02,
        1.74114779e-01,  3.62475701e-02, -7.15838606e-03,  9.84522328e-02,
        1.17253527e-01, -7.19380826e-02, -4.58560660e-02,  9.41771939e-02,
        4.19613607e-02,  4.33484726e-02, -4.22067456e-02, -1.38814032e-01,
       -9.99295637e-02,  2.25967932e-02,  1.67195588e-01, -1.44787595e-01,
        3.92599478e-02,  7.71826208e-02,  8.61005634e-02,  4.58581932e-02,
       -4.75722412e-03,  8.70401934e-02, -6.30586222e-02, -1.11308992e-01,
        5.29378392e-02, -1.12624042e-01,  1.07811831e-01, -3.33027877e-02,
        9.09468010e-02,  1.28924236e-01, -8.42889324e-02, -9.63377580e-02,
        8.12403560e-02, -7.31023923e-02,  3.66042443e-02,  2.98374649e-02,
       -1.84344754e-01, -1.21671921e-02, -3.92929316e-02, -5.60299195e-02,
       -2.22558118e-02,  8.53477046e-02, -4.75994609e-02, -1.15903310e-01,
        1.13062419e-01,  7.00530335e-02, -1.18049726e-01, -2.45340858e-02,
       -7.00877234e-02,  9.78769138e-02, -1.43837467e-01,  6.39601350e-02,
        1.64534096e-02,  5.07407971e-02,  1.78336665e-01, -4.94653806e-02,
       -1.32807598e-01, -9.13471207e-02,  1.31348297e-02,  6.67786822e-02,
        1.65685520e-01,  1.43078595e-01, -1.54928699e-01,  3.63049470e-02,
       -1.84192419e-01,  8.71330053e-02, -6.68164492e-02,  1.19111780e-02,
        1.69201225e-01,  2.07377464e-01, -1.55743614e-01,  2.48231813e-01,
        1.74474508e-01,  1.10832192e-01, -9.39424708e-02, -7.54209161e-02,
        1.22788072e-01,  3.38978432e-02, -8.02185386e-02,  8.34921468e-03,
       -6.29946217e-02, -1.93069369e-01,  8.22131708e-02, -1.35305554e-01,
        9.66851860e-02,  9.66161937e-02,  6.20425818e-03, -7.46266916e-02,
        2.93266168e-03,  1.82098784e-02,  2.98628844e-02, -8.04974290e-04,
       -5.98340593e-02, -1.29398763e-01,  1.57031327e-01,  2.79656146e-02,
       -4.51501273e-02,  2.52879914e-02,  1.51561260e-01,  7.62178898e-02,
        1.47897005e-01,  1.09165639e-01, -2.08027035e-01, -6.55345246e-02,
        9.91936848e-02,  1.54651923e-03, -2.09919773e-02,  1.53719008e-01,
        5.95190302e-02,  1.29519194e-01, -1.84795290e-01, -8.05190299e-04,
       -2.15639267e-03, -1.11522041e-01, -1.03507511e-01, -5.84577471e-02,
        1.25477225e-01,  1.11640327e-01,  2.95776371e-02, -7.33346641e-02,
        1.23415075e-01, -1.88254588e-03,  3.72591540e-02,  1.09907500e-02,
       -1.83244068e-02, -7.31317997e-02, -1.03112936e-01,  6.31136075e-02,
        1.10778756e-01,  5.24811484e-02,  7.28174075e-02,  2.10396096e-01,
        1.49010882e-01,  2.02684894e-01, -1.27109541e-02, -2.43265092e-01,
        3.46839055e-02, -8.34641978e-02, -7.65227228e-02,  1.20328031e-01,
        5.59323020e-02,  1.25173002e-01,  3.86849269e-02,  2.27983985e-02,
        4.93711680e-02,  1.53029278e-01, -9.30112302e-02,  5.38328215e-02,
        1.21010460e-01, -2.07948498e-02, -7.85462931e-02, -3.54699939e-02,
       -6.02941439e-02,  2.77993441e-01,  5.75915389e-02,  5.38266301e-02,
        1.64789706e-01, -2.11022887e-02,  1.46662612e-02, -1.04518488e-01,
       -3.83894034e-02,  1.14184998e-01,  8.80203694e-02,  1.51651487e-01,
        7.73967728e-02, -2.01822475e-01,  1.78508580e-01,  2.46804819e-01,
        1.32275268e-01,  1.37210175e-01,  2.13616684e-01, -9.91994217e-02,
        1.65042579e-02,  9.23587382e-02,  6.63393140e-02, -1.86004400e-01,
       -1.99704334e-01,  8.18110406e-02,  7.18934536e-02, -6.40097111e-02,
       -5.65664247e-02,  6.46551549e-02, -1.12543710e-01, -8.71248171e-03,
        5.72072454e-02,  7.73142427e-02,  1.08754830e-02,  2.17918590e-01,
       -2.83093168e-03, -9.99090374e-02,  8.41365308e-02, -5.45648187e-02,
        1.99246388e-02, -1.29316121e-01,  5.08549474e-02,  1.93858370e-01,
        7.61734173e-02, -1.96890570e-02, -3.52205010e-03, -8.90088081e-02,
        2.63853762e-02,  7.29633346e-02,  4.30402346e-02,  3.05807292e-02,
       -4.39807549e-02,  5.84485829e-02, -1.05889663e-01,  7.66040459e-02,
        4.44455892e-02,  9.51816589e-02, -1.08693928e-01, -1.32999375e-01,
       -2.48546749e-02,  5.61261810e-02,  1.49221703e-01, -1.69506922e-01,
       -1.55283526e-01,  7.69402012e-02,  9.01862681e-02, -9.02298093e-02,
        1.34055287e-01, -9.03894380e-02, -1.13408804e-01,  1.09924853e-01,
        9.29807033e-03, -5.09315394e-02,  7.65454695e-02, -1.40642732e-01,
        3.04671880e-02, -1.35541931e-01, -1.60283819e-01,  1.77359730e-01,
        2.09171087e-01, -1.01951815e-01, -1.02347180e-01, -4.30654474e-02,
       -9.78191476e-03, -1.40308261e-01,  6.21047541e-02, -9.81505439e-02,
       -5.41218966e-02, -1.98033918e-02,  2.23466810e-02, -1.35234222e-01,
       -4.58216108e-02,  4.05515134e-02, -5.77373095e-02, -1.59769114e-02,
        7.03867674e-02,  1.28179953e-01,  1.50476381e-01,  6.56744838e-02,
       -4.59784605e-02,  1.52589930e-02,  9.50646028e-02,  3.47728282e-02,
        1.31617323e-01,  1.42704532e-01, -1.02324732e-01,  5.92076872e-03,
        1.71506405e-01, -7.89853409e-02,  6.34644926e-02,  3.04991882e-02,
       -6.92083240e-02, -1.65904343e-01,  8.28849897e-02,  4.14820127e-02,
        5.47761805e-02,  7.11657926e-02, -8.99788216e-02, -3.14093940e-02,
        5.40951602e-02,  1.90306325e-02,  1.67778149e-01,  1.28913810e-02,
       -4.81709652e-02, -9.88637507e-02,  2.68820524e-02,  5.04792780e-02,
       -5.38321249e-02,  1.33189917e-01, -6.71292320e-02,  1.45112023e-01,
       -1.49200186e-01,  1.29316226e-01,  7.64728412e-02,  7.55039975e-02,
        2.91709253e-03,  2.48959333e-01,  1.54086724e-01, -1.12974480e-01,
        5.92162535e-02, -5.58293834e-02,  1.34997427e-01, -1.38745820e-02,
        1.34635076e-01,  1.10109806e-01,  2.71451231e-02, -2.46657189e-02,
       -3.37189659e-02, -1.59869716e-01,  5.94400950e-02,  1.11677445e-01,
       -8.45585540e-02, -3.78811616e-03,  1.03720225e-01,  6.76352810e-03,
        1.45416185e-01, -7.40249734e-03,  4.55138274e-02,  2.52756216e-02,
        1.29670039e-01, -1.41815677e-01, -1.41825783e-03,  1.40912741e-01,
        8.73132274e-02,  1.88268558e-03,  4.83792312e-02,  1.14670187e-01,
        1.90406710e-01, -1.64009064e-01,  9.36709791e-02,  9.70295817e-02,
        6.89860526e-03, -1.38933202e-02,  6.56837448e-02,  8.00916106e-02,
        9.32945460e-02,  1.00289539e-01, -6.22527720e-03, -1.64752975e-01,
       -2.06722505e-02,  1.21421851e-02,  8.76940861e-02, -4.40272130e-02,
        8.00280720e-02,  3.86015768e-03,  1.56269938e-01, -6.81987852e-02,
        3.70662771e-02,  1.41199178e-03,  6.64614365e-02,  9.72817466e-02,
        1.37541413e-01, -3.62870842e-02,  1.30961224e-01, -2.02671545e-05,
        1.54573053e-01, -3.18533517e-02,  1.86675861e-01,  1.81682222e-02,
        5.72851375e-02,  6.72990233e-02,  1.50715634e-01, -8.93127024e-02,
       -3.91965918e-02,  4.70440127e-02,  2.08748966e-01,  8.48514885e-02,
        1.30514964e-01, -8.49739388e-02, -6.54537678e-02, -5.50272986e-02,
       -3.29445936e-02,  1.28120869e-01,  4.24966589e-03,  2.52800822e-01,
        2.09217981e-01,  9.08159092e-02,  7.34776631e-02,  2.51212656e-01,
        1.24089696e-01,  1.53693303e-01,  1.34641036e-01,  1.60291374e-01,
        1.34915397e-01, -1.68090090e-01,  2.42187545e-01, -2.95598712e-02,
        9.33281146e-03, -9.45106074e-02,  1.82053950e-02, -2.12074001e-03,
       -7.75562003e-02,  1.31348982e-01,  5.46284653e-02,  9.53172669e-02,
        1.83612518e-02, -9.26166028e-02, -8.67228806e-02, -5.57150729e-02,
       -3.83904688e-02, -1.66047588e-01,  1.37287199e-01,  8.92703701e-03,
       -1.40272990e-01,  2.82270815e-02, -5.14803268e-02, -5.54188937e-02,
        2.05853750e-04,  3.38878222e-02,  5.22031225e-02,  1.34044766e-01,
       -1.82492048e-01, -8.77631828e-02,  8.16838294e-02,  7.90706947e-02,
       -3.44027653e-02,  1.41674103e-02, -4.45380285e-02,  1.41113266e-01,
        6.25962317e-02, -1.29614234e-01,  1.06163427e-01, -8.90968591e-02,
       -4.66666184e-02,  6.43173531e-02, -1.07286319e-01, -6.67421743e-02,
       -3.45526682e-03,  1.03655867e-01,  9.03830305e-02,  6.46167435e-03,
       -1.20028540e-01, -1.03747927e-01,  1.27227247e-01,  1.81339383e-02,
       -1.27318045e-02,  1.14506677e-01, -8.22814927e-03, -7.30781555e-02,
        1.74730516e-03,  1.45790488e-01,  1.51464745e-01,  4.02522609e-02,
       -1.65039785e-02,  3.29155140e-02, -1.65464561e-02, -2.86034010e-02,
        7.70147964e-02, -8.19820464e-02,  1.24758780e-01,  1.05506033e-02,
       -2.94717271e-02,  1.55666411e-01,  6.42321855e-02,  2.42535561e-01,
        2.49902047e-02,  7.50318989e-02,  4.19706553e-02,  2.73797363e-02,
       -1.02854274e-01,  1.34671852e-01,  2.07866415e-01,  2.38972418e-02,
        1.40986547e-01, -2.52049156e-02, -3.11975870e-02,  2.09142081e-02,
        3.39084640e-02,  1.86898500e-01, -1.25352412e-01, -1.13981627e-01,
       -4.61809076e-02,  8.14320967e-02, -2.67338119e-02,  1.30042046e-01,
       -1.81642082e-02, -1.66368000e-02,  2.54562348e-02, -1.16997873e-02,
       -1.66533262e-01, -6.58519194e-02,  2.46117771e-01, -3.89964767e-02,
       -4.54928055e-02,  4.72687371e-02,  1.11000456e-01,  2.67582433e-03,
        1.88769162e-01,  4.11623605e-02, -9.32873860e-02, -7.58411288e-02,
        1.20933563e-01, -1.30498067e-01, -7.15470389e-02, -4.11363654e-02,
        1.80900127e-01,  1.23471946e-01, -6.91270689e-03,  2.13986356e-02,
        4.99757305e-02, -1.79919340e-02, -7.36486688e-02, -1.04475863e-01,
       -1.88047841e-01, -3.11043914e-02,  2.95546930e-03,  7.25279190e-03,
        6.17172793e-02,  2.86381189e-02,  1.57116707e-02, -5.90098575e-02,
        3.94861959e-02,  7.45372698e-02, -1.29293033e-03,  1.62631616e-01,
        1.48330748e-01, -5.38736396e-03,  2.71539972e-03, -3.06080119e-03,
       -3.63132823e-03,  1.19193956e-01, -1.00418806e-01, -3.80447470e-02,
        4.34816517e-02,  7.44273663e-02, -1.20052375e-01, -6.61576167e-02,
        4.26218957e-02,  1.33763552e-01, -7.49713778e-02,  1.69885889e-01,
       -1.29757032e-01,  8.14053193e-02,  1.16477415e-01,  8.18252414e-02,
        1.46011934e-01, -1.72392443e-01, -7.21694231e-02,  2.88953222e-02,
       -6.53973892e-02, -2.10658666e-02, -1.77012816e-01,  1.09074414e-01,
        2.85495277e-02,  7.74729103e-02,  2.29334943e-02,  7.98362121e-03,
        2.04214826e-01,  4.31712642e-02, -1.09208459e-02, -7.48009384e-02,
        1.88565627e-01, -9.25418064e-02,  5.44960462e-02, -6.53250888e-02,
        9.34234634e-02,  1.83827594e-01,  7.53535703e-02,  1.26685113e-01,
        9.93858948e-02, -8.17406923e-02, -3.49727180e-03, -1.73010856e-01,
       -1.60207331e-01, -4.66000699e-02, -6.05151057e-02,  2.43715663e-02,
        2.47937515e-02, -6.98901117e-02, -7.92846158e-02,  9.78992432e-02,
        1.63971394e-01,  6.95099756e-02,  1.48606256e-01, -1.05093047e-01,
        9.28660557e-02,  1.34295439e-02,  9.18546543e-02, -9.19463020e-03,
        1.63130865e-01,  1.43282926e-02, -2.61025429e-02, -1.48906514e-01,
       -5.44883162e-02,  1.55464366e-01,  1.02186859e-01,  1.55174389e-01,
        2.67857522e-01,  5.03070466e-02,  1.34628564e-01,  5.93848191e-02,
       -5.78521900e-02,  3.68618369e-02,  1.78718641e-01,  1.59761712e-01,
        7.63707906e-02, -7.89160356e-02, -2.49067396e-02, -7.74822012e-02,
       -1.62694365e-01,  3.32320966e-02,  9.82537940e-02, -1.74169578e-02,
        7.95784518e-02, -1.30414078e-02,  4.23383601e-02,  6.88259304e-02,
        4.66707051e-02,  1.29963443e-01,  3.43016125e-02, -5.74766211e-02,
       -1.38960570e-01,  1.20329462e-01,  1.02309830e-01,  4.60605845e-02,
        1.44924641e-01,  1.34969205e-01, -7.50429705e-02, -8.33172053e-02,
        1.89040869e-01, -1.11886621e-01,  1.68256283e-01,  2.02579945e-02,
       -1.75529987e-01,  2.26708502e-01,  2.30082050e-02,  4.44383509e-02,
       -3.42232399e-02, -3.84906046e-02,  1.50327757e-02, -2.70738825e-02,
       -2.83659459e-03,  2.84587573e-02, -8.54986385e-02, -9.98188853e-02,
        8.29854980e-02, -1.61922902e-01, -1.39850667e-02, -1.11651719e-01,
       -1.41218364e-01, -1.29366964e-01,  1.35358796e-01,  1.89910382e-01,
       -8.61292779e-02,  7.30777532e-02,  5.91474660e-02, -7.63144940e-02,
       -7.00583234e-02,  8.12042877e-02, -5.89894801e-02,  1.22796990e-01,
       -1.06033556e-01, -7.93009400e-02,  5.20921545e-03,  7.94658214e-02],
      dtype=float32), array([0.10798092, 0.12141123, 0.16447075, 0.18327504, 0.17874475,
       0.15848297, 0.1238741 , 0.11041074, 0.19075963, 0.10495529,
       0.11049213, 0.25750926, 0.09757812, 0.23224661, 0.1682272 ,
       0.10169432, 0.24107799, 0.13290262, 0.12022216, 0.2113223 ,
       0.15337591, 0.10781707, 0.12856369, 0.09717989, 0.12862681,
       0.22500765, 0.12748447, 0.2594349 , 0.18316957, 0.10214554,
       0.1410901 , 0.1003585 , 0.2109542 , 0.15306114, 0.12536284,
       0.10655992, 0.13319097, 0.13166311, 0.2889814 , 0.31483066,
       0.12013782, 0.15832235, 0.1874783 , 0.09042948, 0.09306307,
       0.13708606, 0.16824004, 0.12181143, 0.18916224, 0.11767414,
       0.16745718, 0.12968573, 0.15354933, 0.11245488, 0.14859146,
       0.14717962, 0.12409169, 0.16781817, 0.1660461 , 0.12723374,
       0.19270234, 0.18350333, 0.12632287, 0.19713089, 0.18906558,
       0.1485121 , 0.1354333 , 0.1838894 , 0.13052754, 0.11023919,
       0.20371573, 0.12930804, 0.15976493, 0.13588883, 0.10834008,
       0.11033013, 0.17071871, 0.1033563 , 0.13439989, 0.17594448,
       0.17835419, 0.1496153 , 0.13757637, 0.170519  , 0.15724684,
       0.11161465, 0.11208696, 0.10921334, 0.10385393, 0.11797077,
       0.16346559, 0.13511005, 0.15520166, 0.12912445, 0.21920443,
       0.24935772, 0.09376416, 0.17384799, 0.1668626 , 0.1266096 ,
       0.1387477 , 0.15959635, 0.09677555, 0.2004939 , 0.10082741,
       0.1457356 , 0.14369164, 0.12302575, 0.14688233, 0.21407911,
       0.09837402, 0.11203469, 0.11791883, 0.16905215, 0.09448398,
       0.15753838, 0.17231378, 0.10880493, 0.11534815, 0.11379326,
       0.09897181, 0.13174981, 0.10923213, 0.15052427, 0.12675244,
       0.11347347, 0.20279042, 0.09602214, 0.12710571, 0.20877966,
       0.18230543, 0.09539253, 0.14167666, 0.22137932, 0.1466707 ,
       0.16939701, 0.11883565, 0.13904157, 0.12707675, 0.13108517,
       0.14396198, 0.24978581, 0.14513347, 0.16597234, 0.1735312 ,
       0.13736579, 0.11313129, 0.10062893, 0.16187716, 0.23068282,
       0.23827462, 0.18703774, 0.19747356, 0.15691976, 0.22031133,
       0.19536965, 0.23226643, 0.09100702, 0.1651509 , 0.09192719,
       0.17757997, 0.16329905, 0.12893021, 0.11159119, 0.13649638,
       0.20740992, 0.1006996 , 0.14717115, 0.0933504 , 0.09520508,
       0.1318251 , 0.15949616, 0.10487903, 0.16310665, 0.21924458,
       0.14715478, 0.1334903 , 0.3141177 , 0.17025788, 0.12933367,
       0.13460499, 0.16604523, 0.12751405, 0.13049571, 0.1307963 ,
       0.10429996, 0.14420235, 0.12736915, 0.12323048, 0.12168892,
       0.28475124, 0.12072097, 0.2395853 , 0.09449966, 0.11530152,
       0.10601472, 0.17925437, 0.10541414, 0.13028903, 0.12349395,
       0.14801387, 0.10548963, 0.09367886, 0.22906207, 0.10326337,
       0.11938682, 0.1263601 , 0.1695979 , 0.1505319 , 0.09982003,
       0.15825917, 0.20654462, 0.15231517, 0.21027073, 0.12065823,
       0.3859084 , 0.12302688, 0.11277635, 0.12410464, 0.27967986,
       0.13088676, 0.31197762, 0.10517842, 0.09401381, 0.15998597,
       0.19042179, 0.12920745, 0.12415336, 0.20313121, 0.09619825,
       0.19051142, 0.13728105, 0.10605684, 0.17400193, 0.13084081,
       0.19635686, 0.15114883, 0.11369603, 0.11772686, 0.1165003 ,
       0.12374482, 0.18083966, 0.10930146, 0.14486316, 0.11011118,
       0.13702695, 0.17464693, 0.19829744, 0.20183627, 0.15126039,
       0.43241248, 0.1373943 , 0.09152011, 0.17438881, 0.1370005 ,
       0.1951671 , 0.19289231, 0.12723005, 0.08988139, 0.16495028,
       0.10959037, 0.10895903, 0.12822682, 0.10232645, 0.12174294,
       0.15720452, 0.09654387, 0.21959442, 0.09427501, 0.16472504,
       0.13152859, 0.12117862, 0.10800605, 0.1668927 , 0.08597001,
       0.26688328, 0.12068806, 0.14104949, 0.1237786 , 0.11382224,
       0.086082  , 0.14458747, 0.13452238, 0.12053167, 0.09688752,
       0.11666757, 0.14237115, 0.13621633, 0.10794056, 0.15071487,
       0.11585649, 0.1353686 , 0.10116883, 0.14167911, 0.17777309,
       0.177479  , 0.1805856 , 0.16010894, 0.1393509 , 0.14241537,
       0.18892981, 0.11309235, 0.15097487, 0.22170009, 0.10240848,
       0.12010011, 0.14636986, 0.23819815, 0.11511018, 0.14263216,
       0.1356827 , 0.16709597, 0.15138423, 0.14582428, 0.10693933,
       0.09369513, 0.09069709, 0.18470655, 0.11896214, 0.14806084,
       0.13295682, 0.10909567, 0.13166057, 0.15124846, 0.2812291 ,
       0.10841092, 0.13819519, 0.11227081, 0.13444695, 0.11546626,
       0.12582402, 0.10848679, 0.16126953, 0.23024273, 0.14613758,
       0.10441809, 0.12916462, 0.15955652, 0.11617956, 0.17755452,
       0.32851085, 0.1744822 , 0.14087111, 0.13123584, 0.12070846,
       0.12764145, 0.12598756, 0.20252562, 0.10066267, 0.1823441 ,
       0.11785514, 0.11578905, 0.1046812 , 0.28097934, 0.19452083,
       0.10641529, 0.15995999, 0.11933357, 0.09661929, 0.20394921,
       0.124116  , 0.19064417, 0.12397967, 0.12992778, 0.16531914,
       0.11800343, 0.2116572 , 0.1864475 , 0.09231234, 0.3231052 ,
       0.17614555, 0.15026483, 0.10982887, 0.16396393, 0.22109497,
       0.15598354, 0.1414209 , 0.1241243 , 0.12752417, 0.12532727,
       0.10597373, 0.21629673, 0.12719502, 0.18027319, 0.10873311,
       0.08831915, 0.18226247, 0.10856754, 0.15513779, 0.13375664,
       0.10544652, 0.09601724, 0.15121812, 0.27385002, 0.13288774,
       0.18836468, 0.167977  , 0.12553592, 0.11354866, 0.1151704 ,
       0.15435582, 0.14473616, 0.14258699, 0.17840324, 0.12102796,
       0.14611976, 0.10719606, 0.11697352, 0.13838518, 0.12760836,
       0.12674822, 0.25485435, 0.11588859, 0.10710038, 0.11352016,
       0.14200176, 0.22165786, 0.14112964, 0.20688596, 0.1190434 ,
       0.09481189, 0.1684546 , 0.1272741 , 0.1340699 , 0.13756636,
       0.12437309, 0.18222842, 0.13316374, 0.12965047, 0.10037666,
       0.30767435, 0.11119339, 0.11925593, 0.13180098, 0.13721801,
       0.1745662 , 0.09825554, 0.09544119, 0.19499649, 0.13139334,
       0.18902399, 0.22599766, 0.26584932, 0.10249076, 0.1109833 ,
       0.11125875, 0.12355657, 0.2080773 , 0.17320696, 0.14291134,
       0.10624021, 0.1876191 , 0.12542117, 0.21795726, 0.13763641,
       0.15940182, 0.25370964, 0.20822234, 0.31469977, 0.10539974,
       0.09791724, 0.14197461, 0.09279363, 0.12516265, 0.14016528,
       0.12047701, 0.12963817, 0.19204551, 0.11421248, 0.140418  ,
       0.16160242, 0.15183926, 0.13003862, 0.20804127, 0.12023342,
       0.20259069, 0.21966454, 0.17052497, 0.190037  , 0.10008797,
       0.13307095, 0.0907818 , 0.12593538, 0.18078434, 0.129458  ,
       0.13714434, 0.12894225, 0.11348619, 0.09480992, 0.1124968 ,
       0.12643969, 0.19048224, 0.11725754, 0.10676405, 0.18628752,
       0.10417859, 0.1166085 , 0.10003333, 0.09904379, 0.10669517,
       0.10634906, 0.1739076 , 0.25868756, 0.10806031, 0.11060578,
       0.19443078, 0.15073822, 0.11190898, 0.11881018, 0.17594787,
       0.09586807, 0.10300317, 0.08917571, 0.13696603, 0.13629435,
       0.11032876, 0.14381357, 0.15061703, 0.11590486, 0.11430472,
       0.11596443, 0.14088376, 0.13888067, 0.1091892 , 0.09346052,
       0.18849787, 0.12944275, 0.14528988, 0.08649257, 0.09399717,
       0.10972223, 0.12317546, 0.18940113, 0.12990318, 0.23636845,
       0.14002739, 0.1327954 , 0.09786244, 0.16116916, 0.1035239 ,
       0.1267161 , 0.17672135, 0.2277451 , 0.1892802 , 0.12149271,
       0.14336129, 0.10988242, 0.11741246, 0.14825076, 0.11440187,
       0.11276682, 0.14438222, 0.14819191, 0.14995384, 0.17329188,
       0.12983237, 0.14131282, 0.140216  , 0.11420639, 0.13434093,
       0.24480647, 0.24016698, 0.11785706, 0.20454296, 0.2077806 ,
       0.14511064, 0.12544239, 0.1276632 , 0.22618611, 0.12674081,
       0.14397497, 0.11196955, 0.1242623 , 0.14973877, 0.11159632,
       0.11770429, 0.29127553, 0.14869335, 0.09967764, 0.10970386,
       0.11900471, 0.11106241, 0.12626216, 0.20330806, 0.13464487,
       0.11123966, 0.14231409, 0.1473985 , 0.1993626 , 0.11768902,
       0.12134417, 0.13343827, 0.0962943 , 0.33217448, 0.09930071,
       0.09645262, 0.13538936, 0.11754942, 0.14471757, 0.11191597,
       0.14497407, 0.24397843, 0.11240291, 0.11743371, 0.15233535,
       0.10051048, 0.10434818, 0.1377682 , 0.19663307, 0.10761355,
       0.13715427, 0.10008288, 0.12188504, 0.17733875, 0.24092315,
       0.17437214, 0.32643336, 0.10646424, 0.10454   , 0.10877136,
       0.17717475, 0.09986957, 0.10862926, 0.17089207, 0.23577236,
       0.12900174, 0.1405477 , 0.13300802, 0.13196255, 0.27058285,
       0.11526007, 0.17039616, 0.10147624, 0.09571274, 0.11194321,
       0.21250677, 0.22211163, 0.1225386 , 0.21034491, 0.19873771,
       0.18479647, 0.15870923, 0.13225728, 0.10958284, 0.23540215,
       0.15503192, 0.16903414, 0.17262189, 0.15088229, 0.1059702 ,
       0.1456602 , 0.1544247 , 0.24368083, 0.10927567, 0.10461619,
       0.15562925, 0.14411418, 0.18789175, 0.11063723, 0.25285426,
       0.24456881, 0.12143493, 0.16636989, 0.19544801, 0.10392208,
       0.09295676, 0.20362066, 0.11553152, 0.1593384 , 0.13140069,
       0.1259677 , 0.14793691, 0.31140015, 0.09887134, 0.35722938,
       0.16849482, 0.09636272, 0.10937729, 0.11508168, 0.1044871 ,
       0.17073458, 0.19435291, 0.1043785 , 0.09943102, 0.21499921,
       0.28667173, 0.09892645, 0.12305766, 0.20108181, 0.16260909,
       0.12564789, 0.17269213, 0.22649603, 0.14159338, 0.24241391,
       0.13190755, 0.30682558, 0.2157231 , 0.11741024, 0.10952324,
       0.16798475, 0.12110186, 0.11146025, 0.10739646, 0.09954864,
       0.11682957, 0.10848261, 0.17307602, 0.12365908, 0.12875123,
       0.0941786 , 0.15197185, 0.16831078, 0.11697507, 0.19988728,
       0.15902145, 0.1514443 , 0.19510552, 0.12226637, 0.09971623,
       0.12966782, 0.18745317, 0.12422728, 0.18663003, 0.13165593,
       0.11763675, 0.11852755, 0.11732004], dtype=float32), array([[[[ 0.0170569 ],
         [-0.02170783],
         [ 0.03679874],
         ...,
         [-0.00756812],
         [-0.04939753],
         [-0.00294457]],

        [[ 0.02218243],
         [-0.02278281],
         [-0.0101566 ],
         ...,
         [-0.01186157],
         [ 0.00613014],
         [ 0.00801037]],

        [[-0.02702579],
         [-0.04209636],
         [ 0.0237291 ],
         ...,
         [ 0.00358186],
         [-0.0376061 ],
         [ 0.02083201]]],


       [[[-0.03261242],
         [-0.03275184],
         [ 0.02364233],
         ...,
         [ 0.00884202],
         [-0.04203078],
         [-0.00354385]],

        [[ 0.02688673],
         [ 0.00213109],
         [ 0.0173523 ],
         ...,
         [ 0.01431702],
         [-0.01203408],
         [ 0.01170628]],

        [[-0.00526641],
         [-0.01700527],
         [-0.02368306],
         ...,
         [ 0.03252085],
         [-0.04310842],
         [ 0.00519195]]],


       [[[-0.00068912],
         [-0.00773456],
         [ 0.01409106],
         ...,
         [-0.01986111],
         [-0.00987602],
         [ 0.02821395]],

        [[ 0.00604862],
         [-0.03624237],
         [-0.00147681],
         ...,
         [ 0.03363712],
         [-0.0141337 ],
         [-0.02234717]],

        [[ 0.02340944],
         [-0.00974778],
         [ 0.00790231],
         ...,
         [-0.00644402],
         [ 0.01455672],
         [ 0.00938431]]]], dtype=float32), array([[[[-0.03336829,  0.00340178,  0.02548257, ...,  0.04161889,
           0.01873313, -0.00151121],
         [-0.02563496,  0.06691448, -0.03728822, ..., -0.00889225,
           0.0507088 , -0.0002859 ],
         [ 0.03847977, -0.02786586, -0.02641323, ..., -0.02835157,
          -0.03744701, -0.05867559],
         ...,
         [ 0.06578047,  0.01333251,  0.05261229, ...,  0.02809777,
           0.05891429,  0.02486361],
         [ 0.04948007, -0.01005122,  0.04057302, ..., -0.01906008,
          -0.03858782, -0.03187496],
         [ 0.03072158, -0.02334987,  0.03714496, ..., -0.05574689,
           0.03256168, -0.05162215]]]], dtype=float32), array([0.99863   , 0.9947798 , 0.9888306 , 0.99354935, 0.99140555,
       1.0033418 , 1.0054969 , 1.0029864 , 0.9738164 , 0.98263216,
       0.9939393 , 1.0194763 , 0.99185973, 0.9952753 , 1.0042105 ,
       0.9906387 , 0.9966512 , 1.0080688 , 1.0066344 , 1.0310098 ,
       0.98919773, 0.9890113 , 0.99687135, 0.98085123, 1.0089036 ,
       0.9730924 , 1.005198  , 1.0114696 , 1.013198  , 1.0299937 ,
       0.9977294 , 1.0053413 , 0.997183  , 0.99500465, 1.0100352 ,
       0.9951317 , 1.0027272 , 0.9967172 , 1.0005101 , 0.9940404 ,
       0.9880265 , 0.9981455 , 1.0057359 , 0.98882174, 1.0031549 ,
       0.9978678 , 1.004108  , 0.9864527 , 1.0064881 , 1.0264927 ,
       0.99172884, 1.032089  , 1.0068622 , 0.98776114, 1.0116937 ,
       0.9953447 , 1.0150368 , 1.0086569 , 0.9750287 , 0.9920201 ,
       0.99603426, 0.9938019 , 0.9887212 , 0.9842064 , 0.9832624 ,
       1.0019462 , 1.031792  , 0.9944591 , 0.99571764, 1.0085799 ,
       1.0140604 , 0.98855746, 0.9981742 , 0.9997493 , 1.0238271 ,
       0.990421  , 0.99690086, 1.0013744 , 1.0036976 , 1.008251  ,
       0.9951626 , 0.99483836, 0.99975044, 1.001405  , 1.018221  ,
       1.0001706 , 0.98762846, 0.9902519 , 1.0333222 , 0.988047  ,
       0.99701107, 0.99675786, 1.0304139 , 0.9953672 , 1.015373  ,
       1.0328023 , 0.9838895 , 0.9803642 , 1.007411  , 0.9972453 ,
       0.9966731 , 0.9982696 , 1.0079161 , 0.9871411 , 1.0086852 ,
       1.0049208 , 0.9886234 , 0.999444  , 1.0007622 , 0.997962  ,
       0.9919044 , 1.0191389 , 0.98788285, 1.0134875 , 0.9974284 ,
       1.004485  , 1.0020756 , 0.9986776 , 0.99207145, 0.99456525,
       1.0242671 , 0.9919349 , 0.99558777, 1.0083408 , 1.0208043 ,
       1.0199816 , 0.99567646, 0.9941586 , 0.99895036, 0.9979851 ,
       1.0108014 , 0.9951619 , 1.0101559 , 0.9944214 , 1.0161769 ,
       0.99140614, 0.99169344, 0.98514247, 0.9922215 , 0.9940198 ,
       1.0024533 , 1.0031447 , 1.0135067 , 1.0107044 , 1.0014343 ,
       0.99146795, 1.0062914 , 0.9952734 , 0.99700385, 0.98719597,
       0.9909808 , 1.0062917 , 1.0073999 , 1.0057517 , 1.0077466 ,
       0.9964605 , 1.0026112 , 0.9942482 , 0.99548125, 0.9978827 ,
       1.001789  , 0.9860307 , 1.0176529 , 1.0088075 , 1.0042657 ,
       1.0088731 , 1.0094845 , 1.0017718 , 0.9915485 , 1.0060053 ,
       1.0051324 , 0.99822396, 1.014136  , 1.0077884 , 0.98878884,
       1.009689  , 1.0028297 , 0.9987108 , 1.0389801 , 1.000405  ,
       1.0088778 , 1.0057042 , 1.0026073 , 1.0512048 , 0.99096656,
       1.0038896 , 1.0150956 , 1.0190699 , 1.0043643 , 1.0181085 ,
       0.9999883 , 1.0111835 , 0.99697113, 1.0026301 , 0.9898142 ,
       1.019218  , 1.0286462 , 0.9832192 , 1.0085107 , 1.0286428 ,
       0.9942729 , 0.99505633, 0.99549854, 0.9999155 , 0.98834926,
       1.0197929 , 1.0042064 , 0.99933666, 0.9870085 , 0.99726194,
       0.9871976 , 1.0216926 , 0.9976048 , 0.9946639 , 0.9928973 ,
       1.024567  , 0.9838405 , 0.974664  , 0.9879147 , 1.0113518 ,
       0.9972    , 1.0127443 , 1.0221909 , 0.9954067 , 0.9931247 ,
       0.99003035, 1.0244989 , 1.0151902 , 1.0047102 , 1.0028156 ,
       1.0032634 , 1.0073476 , 0.9854756 , 1.002601  , 0.9971084 ,
       1.0058419 , 1.0035359 , 0.9800687 , 1.0014114 , 1.0008088 ,
       0.99607825, 0.9919323 , 0.97942144, 0.996524  , 0.9966013 ,
       0.99728245, 1.0044959 , 0.9931217 , 1.0188025 , 0.9942224 ,
       0.99099433, 0.9871407 , 0.99338984, 0.99570894, 1.002698  ,
       1.0085255 , 0.9941556 , 0.99920446, 0.99529076, 0.9993116 ,
       1.0110972 , 0.9792995 , 1.0025822 , 1.0117192 , 0.98632836,
       0.9800118 , 0.9886642 , 1.0029005 , 0.98717386, 0.9971193 ,
       0.99464405, 0.9909539 , 1.0013735 , 1.0020714 , 0.9949492 ,
       0.984883  , 1.0172799 , 0.9892479 , 0.9967859 , 1.0164167 ,
       0.99392354, 1.0056851 , 0.99538887, 0.9911335 , 1.0207465 ,
       1.0095059 , 1.0107015 , 1.0136929 , 1.0069722 , 0.99868023,
       0.99692255, 0.9938732 , 0.99624693, 0.99877554, 1.0045485 ,
       1.0492064 , 0.9941161 , 1.0136114 , 0.9893677 , 1.0070107 ,
       0.9993915 , 0.9842449 , 0.99111366, 0.997221  , 1.0054047 ,
       0.99236536, 0.9938442 , 0.99182516, 0.9990937 , 1.0042801 ,
       1.0034397 , 1.0016291 , 1.0087584 , 1.0023618 , 0.99354124,
       0.99684274, 0.9965005 , 1.0187345 , 1.0055101 , 0.9901907 ,
       0.9998727 , 1.0028179 , 0.99679554, 0.9905909 , 1.018758  ,
       1.020091  , 1.034631  , 0.9901405 , 0.991608  , 1.0027994 ,
       1.0072474 , 0.99342436, 0.99636227, 0.9837247 , 1.0052804 ,
       1.000802  , 0.9963888 , 1.0149909 , 1.0159633 , 0.99612784,
       1.0031675 , 1.0245131 , 0.98805964, 1.020698  , 0.9895808 ,
       0.9882643 , 1.000636  , 1.0030683 , 0.99603206, 0.9915906 ,
       1.0103785 , 0.98617023, 1.0040741 , 1.0141877 , 0.9929254 ,
       0.9930803 , 0.99127245, 1.0024823 , 1.0007726 , 1.0040504 ,
       0.99691063, 0.9937001 , 1.0010675 , 0.99050957, 0.9971714 ,
       1.0001863 , 0.9939062 , 0.97979563, 0.9931816 , 1.0071261 ,
       0.9901358 , 1.0065705 , 1.0098726 , 1.0040604 , 1.0139011 ,
       1.0119847 , 0.989341  , 0.98925334, 0.9932556 , 0.997914  ,
       0.9931038 , 0.993359  , 0.9802504 , 0.9926153 , 1.0002747 ,
       0.99865854, 1.0101343 , 0.99291456, 0.9957102 , 1.0020832 ,
       0.98724574, 1.0393709 , 0.9968148 , 0.9937002 , 1.0033671 ,
       1.0076692 , 0.98452973, 0.996153  , 1.0112542 , 0.9910286 ,
       0.9975152 , 1.0185997 , 0.99290526, 1.0120564 , 0.98894733,
       1.0028087 , 1.0050888 , 0.9951262 , 0.99478734, 0.98820895,
       0.9971134 , 0.97352535, 0.98880124, 0.9865413 , 1.0295821 ,
       1.0055854 , 0.9965858 , 0.97750026, 0.990886  , 1.0108677 ,
       1.0105538 , 0.9926972 , 0.9919378 , 0.9956977 , 0.99674904,
       0.9943524 , 0.99072504, 1.0134882 , 0.99632484, 1.0182382 ,
       0.9943859 , 1.027728  , 0.9986473 , 0.981463  , 1.012438  ,
       1.0032591 , 0.9980663 , 0.99560124, 1.0046326 , 1.0058424 ,
       1.0392365 , 1.0025394 , 1.0062715 , 0.9947649 , 0.9968459 ,
       1.0023856 , 1.0052404 , 1.0000081 , 0.99145436, 0.9990922 ,
       1.019254  , 0.9925112 , 1.0104642 , 1.0212603 , 0.9977794 ,
       1.0009781 , 0.98477983, 0.9965632 , 1.0013461 , 0.9892768 ,
       0.984816  , 0.99493855, 0.9974598 , 0.9914172 , 1.0273218 ,
       1.0087702 , 1.0009116 , 0.9940654 , 1.0095401 , 1.0161822 ,
       0.9937514 , 1.0074648 , 1.0075847 , 0.99530613, 0.99553245,
       1.0240489 , 0.99548   , 0.9844694 , 0.9968917 , 0.9967472 ,
       0.9955687 , 0.9963471 , 1.0164653 , 0.985737  , 0.9934607 ,
       0.99173373, 1.0050534 , 1.0186965 , 1.0072865 , 0.997799  ,
       0.9939436 , 1.0111157 , 0.992448  , 0.9963459 , 0.9932678 ,
       0.9984533 , 1.0051577 , 0.99464375, 0.97662455, 0.9773471 ,
       0.9820275 , 1.003835  , 1.0080252 , 1.0084584 , 0.98826903,
       1.0080425 , 1.0148667 , 1.019291  , 1.0079389 , 1.0230042 ,
       1.0083418 , 1.018862  , 0.99252456, 0.98888946, 1.0269065 ,
       1.0021428 , 1.0036458 , 1.0015494 , 0.9931413 , 0.99204946,
       0.9990148 , 0.9982243 , 1.0134996 , 0.9929332 , 0.98336816,
       0.9887273 , 0.99954945, 0.9952392 , 1.0355568 , 0.9998858 ,
       0.9910349 , 1.0034496 , 0.98686236, 0.9869672 , 0.9916342 ,
       0.99446654, 0.98569286, 0.9973689 , 1.0260706 , 0.9950162 ,
       0.99218845, 1.0227568 , 0.9901755 , 0.99156564, 0.98828083,
       1.0016102 , 0.99509495, 0.99275106, 1.0113468 , 0.9929639 ,
       0.99704766, 0.9809101 , 1.0135322 , 0.9889652 , 1.0193835 ,
       1.0105616 , 0.9963743 , 1.0047613 , 1.0082542 , 0.99658626,
       1.0442939 , 0.9980486 , 1.0055873 , 0.9897829 , 0.98548186,
       0.98979366, 1.0000528 , 0.99286693, 1.0382892 , 0.9970304 ,
       1.0203031 , 0.9960218 , 0.99025255, 0.98568445, 1.0046649 ,
       1.0052264 , 1.0027668 , 1.0311013 , 0.9934038 , 0.980997  ,
       1.0017352 , 0.9892754 , 1.0007917 , 1.0033505 , 0.98560643,
       0.9918766 , 0.9949842 , 0.99092174, 1.008263  , 1.0017402 ,
       0.9983133 , 1.0235729 , 1.0060987 , 1.0377907 , 1.0209599 ,
       1.0062294 , 0.99863863, 0.9919396 , 0.99987316, 0.999267  ,
       0.9947596 , 1.006429  , 0.99319655, 0.9856039 , 1.0050054 ,
       1.012865  , 1.0010493 , 0.9846651 , 0.99755955, 1.010736  ,
       0.9931238 , 1.007799  , 1.0033542 , 0.99375665, 0.99834245,
       1.0006361 , 0.9928197 , 0.9995694 , 0.9962994 , 1.0057087 ,
       1.0253469 , 0.9976839 , 0.99051636, 0.9954339 , 1.0253074 ,
       0.99170953, 0.99334985, 1.0005877 , 1.0066584 , 1.0038316 ,
       0.99287885, 1.0366518 , 0.99085414, 0.99011266, 1.0147704 ,
       0.9915439 , 0.9951987 , 0.9859854 , 1.020575  , 0.99756366,
       0.99620724, 0.9942445 , 1.0013328 , 0.968895  , 0.9926914 ,
       1.0040343 , 0.9912578 , 0.99643576, 1.007513  , 0.98355585,
       0.99668145, 0.98279166, 0.9896243 , 1.0081563 , 1.0184788 ,
       0.99773836, 0.99692774, 0.9917157 , 0.9967021 , 1.0011487 ,
       1.0004188 , 1.0123885 , 0.9901689 , 1.0153366 , 1.0052989 ,
       1.0016514 , 1.0178254 , 1.0022312 , 0.9796554 , 0.99758047,
       0.9952319 , 0.99599105, 0.9869224 , 1.0042847 , 0.9859174 ,
       1.0269451 , 0.99884933, 0.98166615, 0.99658346, 0.98032343,
       0.99174833, 0.9988142 , 0.9930044 , 0.99742603, 0.99470407,
       0.9948952 , 1.0005141 , 0.9925095 , 1.0139449 , 1.0118946 ,
       0.9997107 , 0.991483  , 0.9894996 , 0.99201214, 0.9909359 ,
       1.0010047 , 1.0235126 , 0.9965016 , 0.9915345 , 1.0113325 ,
       0.98985666, 1.0099689 , 0.9988727 , 1.0025576 , 0.99354905,
       1.0327203 , 1.0041908 , 0.99758667, 0.9852884 , 0.9998805 ,
       1.0271546 , 1.0058469 , 0.9988309 , 0.9937374 , 0.9956161 ,
       1.0118375 , 0.99327487, 1.0096465 , 0.99594   , 0.9955425 ,
       0.9901968 , 0.99421376, 1.0028795 , 0.9900583 , 0.9975522 ,
       1.0029625 , 1.0032101 , 1.0012723 ], dtype=float32), array([ 6.31854916e-03, -3.64716118e-03, -3.17497249e-03, -2.11396087e-02,
       -1.39661236e-02,  5.75579470e-03, -2.35884413e-02,  9.24920663e-03,
       -2.22815014e-02,  1.45677314e-03, -7.45331682e-03,  2.69997064e-02,
        1.70555548e-03, -2.91347839e-02,  1.01411976e-02, -1.81207787e-02,
        5.76596241e-03, -2.77654501e-03,  1.35288741e-02,  1.44695938e-02,
       -1.19113987e-02, -8.75118189e-03, -1.88105844e-03, -1.21818734e-02,
        9.53795330e-04, -3.21457759e-02,  1.14822825e-02,  4.68235835e-03,
        1.06287310e-02,  1.48300668e-02,  7.53206341e-03, -1.67370029e-02,
        4.12027026e-03, -1.22281734e-03,  8.77041277e-03, -4.65592649e-03,
        6.42870786e-03,  1.14771342e-02,  7.91413989e-03, -1.10790562e-02,
       -5.93613600e-03, -7.76233990e-03, -7.40436651e-03, -8.41451623e-03,
       -2.96491552e-02, -6.25128532e-03, -1.98234469e-04,  8.42195936e-04,
        2.91243801e-03, -4.85708192e-02,  7.36750849e-03, -4.58636321e-02,
       -3.77351465e-03, -1.19903423e-02, -3.21453577e-03, -1.97032769e-03,
        6.40149042e-03, -6.07801322e-03, -1.38593744e-02, -4.51674871e-03,
       -1.10687185e-02, -8.57110322e-03,  3.00610601e-03, -1.33996624e-02,
       -4.81788814e-03,  1.26737608e-02,  1.05155120e-02, -1.48836130e-04,
       -6.28276635e-03,  1.29165538e-02,  1.03960196e-02, -8.81792139e-03,
        4.92747873e-03,  4.88160597e-03, -2.40332372e-02, -9.03834961e-03,
       -9.61392187e-04, -2.39174138e-03, -5.10733249e-03,  5.72172413e-03,
       -4.17165039e-03, -3.64227109e-02,  1.26615828e-02, -6.47883303e-03,
       -1.47935404e-02,  9.84698907e-03, -3.15657817e-03, -4.34587291e-03,
        4.46350779e-03, -1.15346881e-02, -8.96504801e-03, -1.86482444e-03,
       -4.78136260e-03,  2.53078132e-03, -8.78220191e-04,  1.72497984e-02,
       -3.52158630e-03, -4.94552776e-03,  3.84512311e-03, -2.88392268e-02,
       -6.22821320e-03, -1.96967367e-02,  9.17916745e-03,  3.86483478e-03,
        9.69035178e-03,  2.18529534e-02,  1.13420661e-04,  6.55161589e-03,
        4.89932299e-03, -4.23641782e-03, -3.51552735e-03, -1.45175103e-02,
       -1.30910939e-02,  8.93966295e-03, -2.05186103e-03, -9.79935192e-03,
        6.44231355e-03, -2.74061970e-02, -2.19363850e-02, -4.21204511e-03,
       -3.18035707e-02,  5.77850384e-04, -2.51043821e-03, -9.21530463e-03,
       -1.04669547e-02,  2.73919217e-02,  1.21961551e-04, -3.66156385e-03,
       -1.14264172e-02,  5.69637027e-03,  2.42780298e-02, -7.94441160e-03,
       -3.62908244e-02, -1.79258888e-04, -3.54226977e-02, -3.34120798e-03,
       -5.76184317e-03, -7.35659245e-03, -8.32096208e-03,  5.02324756e-03,
       -1.06959254e-03,  1.11033274e-02,  6.23093359e-03,  3.92702129e-03,
       -1.92262754e-02, -1.83369163e-02, -1.11682583e-02, -3.68692982e-03,
        2.00846256e-03, -2.83600502e-02, -4.10707295e-03,  1.87892597e-02,
        8.08781572e-03, -9.68916807e-03, -1.73895527e-03, -9.99076385e-03,
       -6.61059225e-04, -9.77565814e-03, -7.68980756e-03, -8.75246804e-03,
       -6.83591934e-03, -2.16922965e-02, -2.72758976e-02,  8.71659536e-03,
        1.13454182e-02,  7.27432175e-03,  1.06312037e-02,  1.07206749e-02,
       -3.52918054e-03,  1.96335055e-02,  1.43568881e-03, -2.49970052e-03,
        1.36204818e-02, -5.80367818e-03, -4.55109915e-03,  1.44800777e-02,
       -1.59477089e-02,  3.83307226e-03, -5.69895655e-02, -2.05587409e-02,
       -3.19780149e-02,  3.32023343e-03,  5.59771853e-03,  4.29899283e-02,
        5.12757525e-03,  2.55612447e-03,  2.77929679e-02, -3.95981595e-02,
        2.91179516e-04,  4.13772557e-03, -4.59756982e-03, -4.54234099e-03,
       -4.95521165e-03,  1.34156819e-03, -2.97791585e-02,  5.33664413e-03,
        4.74800318e-02, -2.22367700e-02, -1.53588019e-02,  1.29988440e-03,
       -5.19671012e-03, -3.00028850e-03,  7.93397950e-04, -9.53419413e-03,
       -9.63056926e-03, -2.23709084e-02,  6.38648216e-03, -6.08689617e-03,
       -2.81117694e-03,  2.30783131e-03, -1.83100253e-02,  3.26326117e-02,
       -1.74025297e-02,  9.30022355e-03, -4.79947310e-03,  2.71653081e-03,
       -1.73692703e-02, -1.16612772e-02,  2.93781341e-04, -1.41169662e-02,
       -1.64085848e-03, -4.55999859e-02,  1.16221746e-03, -2.61086393e-02,
       -3.76906968e-03, -1.07514169e-02,  6.01598935e-04, -1.06629822e-02,
       -4.93326746e-02, -6.71553565e-03,  5.61942952e-03,  1.94689147e-02,
       -1.76938511e-02,  1.11819627e-02, -1.93231963e-02, -3.16279125e-03,
        1.08783403e-02, -6.39350573e-03, -8.60696286e-03, -6.23362046e-03,
        1.46714551e-02, -9.75628104e-03, -4.35294537e-03,  3.69260437e-03,
        9.52024292e-03, -1.66216902e-02, -1.06427527e-03, -9.24210623e-03,
        2.80377958e-02,  4.08286927e-03, -6.45490643e-03, -1.43034616e-02,
        5.16847707e-03,  8.64841859e-04, -5.94985718e-03,  3.61594325e-03,
       -1.29461931e-02, -1.09296234e-03, -3.35543707e-04, -9.12635121e-04,
       -2.18185410e-03,  1.14110298e-04,  9.02843196e-03, -1.41176619e-02,
       -1.00710578e-02, -9.38701816e-03,  9.27238818e-03, -2.88519030e-03,
       -3.01553006e-03, -5.98109001e-03,  1.05019752e-03, -6.10751519e-03,
        9.19895712e-03,  4.16174345e-03, -1.72212208e-03, -5.04822843e-03,
       -1.66861527e-02, -2.75757983e-02, -1.08512221e-02, -5.96940182e-02,
       -1.34103810e-02,  2.41423268e-02, -2.90650204e-02, -3.24263773e-03,
       -7.68330460e-03, -1.40166273e-02,  1.11913746e-02,  1.62254944e-02,
        6.68363413e-03,  1.22019567e-03, -3.94454738e-03, -1.51175130e-02,
       -7.14444183e-03,  2.85355817e-03,  1.05854310e-02, -1.09075885e-02,
       -6.73544127e-03,  1.04220547e-02, -2.73534376e-02, -2.20984276e-02,
        1.43517694e-03, -2.56787222e-02, -3.20774829e-03, -4.63653542e-03,
        8.56688898e-03, -6.00205269e-03,  4.14323789e-04, -1.42363654e-02,
       -3.36551899e-03, -3.81853618e-02, -9.12777055e-03,  1.67126488e-02,
       -8.80024955e-03,  8.16271547e-03, -3.84209468e-03, -1.19290445e-02,
       -3.63453571e-03,  1.14325052e-02,  6.35300623e-03, -7.60171749e-03,
        3.80756590e-03,  1.33329548e-03, -1.08916182e-02, -1.95060670e-02,
        1.31986383e-03,  1.97641775e-02,  3.04315258e-02, -7.13254837e-03,
       -7.16875726e-03,  1.34793902e-02,  2.36406680e-02, -4.59328221e-05,
       -1.87830476e-03, -1.91613194e-02,  1.33999828e-02,  1.55175393e-02,
       -4.98446811e-04, -2.36672978e-03, -1.19456621e-02,  3.81150842e-03,
       -9.48891882e-03,  8.26473639e-04, -9.00193583e-03, -2.23783986e-03,
       -5.14231797e-04, -6.91831764e-03, -1.85041055e-02,  1.06681148e-02,
        8.20686109e-03, -1.74676478e-02,  9.24852490e-03, -1.59289539e-02,
       -1.53220976e-02,  2.59313360e-03, -2.68086558e-03,  6.25094911e-03,
       -6.01368677e-03,  2.07801834e-02, -1.14311529e-02,  2.06469744e-02,
       -4.16465662e-03, -3.50978076e-02,  4.33890708e-03, -3.46999168e-02,
       -3.09485663e-03, -1.19458009e-02, -9.12318751e-03, -1.36008728e-02,
        5.00096474e-03,  5.21316379e-03, -2.27140244e-02, -6.06991583e-04,
        2.10169591e-02,  1.77271049e-02,  1.94103494e-02,  1.25047648e-02,
       -4.18771087e-05, -7.09878700e-03, -2.10905587e-03,  3.79752950e-03,
       -5.28590754e-03, -4.33653546e-03, -2.79721506e-02,  6.40181708e-04,
       -2.95036519e-03,  1.05148472e-03,  9.80769470e-03, -5.54496190e-04,
        8.91445161e-05, -5.89928357e-04, -1.15261376e-02, -3.77775282e-02,
       -8.95546470e-03, -2.11101286e-02, -7.42657669e-03, -3.35626565e-02,
       -1.01855174e-02, -8.76555033e-03,  1.30381854e-03, -7.61979725e-03,
        1.07504120e-02,  1.92700196e-02,  2.15708674e-03,  1.58603396e-02,
       -6.50483323e-03,  4.58870921e-03,  4.56167292e-03, -1.46870771e-02,
       -3.91766988e-03, -2.79965252e-02, -1.42122768e-02, -1.46183344e-02,
       -1.32756522e-02, -1.74803305e-02,  6.02578744e-03, -5.65681374e-03,
        5.05781686e-03, -1.16558280e-02, -6.45848364e-03,  2.11642147e-03,
       -1.33325513e-02, -1.63629483e-02, -1.42866503e-02, -1.91406300e-03,
       -3.43368296e-03,  1.73499715e-02,  7.36340554e-03, -2.50031147e-02,
        4.33415873e-03,  1.20108118e-02, -9.64221172e-03,  2.78009176e-02,
        2.02615769e-03, -6.34886418e-03, -1.45231895e-02,  1.04347290e-02,
        2.33737007e-03, -1.96416676e-02, -1.47280970e-03,  1.17749814e-02,
       -2.45698541e-02, -1.47344451e-02,  1.84208099e-02, -2.68633477e-02,
       -1.53761776e-02,  9.30308737e-03,  1.43232252e-02, -7.44429324e-03,
       -5.08145988e-03, -6.38427446e-03, -8.43548682e-03,  5.02603455e-03,
        8.93830508e-03, -1.34255420e-02,  7.02186837e-04, -6.29573688e-03,
       -2.62057176e-03,  6.95011253e-03,  1.04498388e-02, -2.47721802e-02,
       -1.38057541e-04, -1.36479577e-02, -7.89070781e-03,  1.03578493e-02,
       -3.36357057e-02,  2.80066375e-02,  1.26037560e-02,  3.65792005e-03,
       -2.14989157e-03, -3.27387191e-02, -4.40244796e-03,  2.63404492e-02,
       -8.73653218e-03, -4.82639764e-03, -8.05070158e-03, -2.71538794e-02,
       -8.04043282e-03, -6.59763580e-03,  3.65361478e-03,  4.88237420e-04,
       -7.66035542e-03, -4.23092349e-03,  1.18625043e-02, -1.55155454e-02,
       -3.09839356e-03,  1.19152130e-04,  1.63388439e-02, -3.03423237e-02,
       -8.82194377e-03,  3.19679710e-03, -2.12674821e-03, -3.66396969e-03,
       -4.71708970e-03, -1.68941766e-02, -7.17453985e-03, -4.49191174e-03,
        6.79347338e-03, -4.18417454e-02, -3.22489589e-02, -7.99159799e-03,
       -1.25171365e-02, -4.39461414e-03,  5.66718681e-03, -3.06221675e-02,
       -1.51629457e-02,  1.45610999e-02, -2.18710545e-02, -2.48656143e-02,
       -7.40272168e-04, -4.01903167e-02, -2.92130690e-02,  2.54595671e-02,
       -2.63128467e-02, -8.58143345e-03, -1.33274612e-03, -1.37179531e-02,
       -1.71639938e-02,  1.35618197e-02, -1.20334793e-04,  1.91125460e-02,
        2.40629801e-04,  4.25556395e-03,  1.90123934e-02, -7.38750817e-03,
       -1.41673321e-02, -3.14505713e-04, -4.86991182e-03,  4.34673065e-03,
        3.81770800e-03, -2.34060083e-02, -7.95706827e-03, -3.09722591e-03,
       -2.27160659e-03, -1.18680019e-02,  9.40496754e-03, -1.45569108e-02,
       -3.37706953e-02, -6.56957226e-03,  1.26206679e-02,  5.40465536e-03,
       -6.46114442e-03,  1.23124374e-02, -1.33879185e-02, -1.27414120e-02,
       -1.42983515e-02, -1.13221596e-03, -4.77689318e-04, -7.85292033e-03,
        2.53196415e-02,  5.15562657e-04, -9.35173593e-03, -9.53315292e-03,
       -3.35650370e-02, -1.22308321e-02,  1.10821519e-02,  2.15121675e-02,
       -9.89375543e-03, -1.58002563e-02,  1.62667092e-02,  1.42063787e-02,
       -1.86741594e-02, -1.64643535e-03, -8.47247057e-03, -7.35624926e-03,
       -2.86896527e-02, -9.03273560e-03,  3.55452159e-03, -9.00972541e-03,
        2.80711353e-02,  4.83548362e-03,  2.18296070e-02, -4.15015854e-02,
       -2.38553155e-02, -1.49611011e-02, -2.49357428e-02,  4.61810920e-03,
        1.27738072e-02,  2.43577268e-02, -1.41250226e-03, -1.40357614e-02,
       -1.14635210e-02,  3.36392899e-03, -1.07424206e-03, -1.65512320e-02,
       -3.14307436e-02, -8.71531107e-03, -1.42221642e-03, -3.31775867e-04,
        9.65145230e-03, -3.03470367e-03, -1.00310855e-02, -1.00307697e-02,
       -6.97570329e-04,  2.29687337e-02,  1.83401536e-02,  5.91319008e-03,
        5.70450677e-03, -1.13743730e-02,  7.86894292e-04, -1.00557851e-02,
       -3.66087363e-04, -2.59886459e-02, -4.57200315e-03,  7.22821715e-05,
       -2.35456582e-02,  5.08608297e-03,  1.38631826e-02, -2.81703216e-03,
       -5.15059044e-04,  8.17618333e-03, -3.21535999e-03, -1.25719011e-02,
        5.23250923e-03, -2.55408976e-02,  1.51176229e-02,  6.66390546e-03,
       -6.01537898e-03,  1.05586620e-02,  3.28986347e-03, -1.67748779e-02,
        1.03389034e-02,  1.09254988e-03, -6.75817952e-03,  1.13800832e-03,
        3.95473791e-03, -1.91209384e-03, -1.81413181e-02,  3.06118350e-03,
       -2.44848654e-02,  2.56754365e-03, -1.53494552e-02,  4.49817767e-03,
       -8.37771688e-03, -6.68929750e-03,  3.34292650e-02, -8.28621443e-03,
       -2.27418123e-03, -1.10531840e-02,  2.83685327e-03,  9.14934324e-04,
       -6.80951588e-03,  6.53940660e-04, -6.06950885e-03, -2.38330513e-02,
       -3.56119638e-03,  7.97990616e-03, -9.16847680e-03, -5.79357101e-03,
        2.31486559e-02, -3.76135148e-02, -1.22210588e-02, -5.44110360e-03,
       -3.87011154e-04,  5.90652879e-03, -2.53758673e-03, -2.81494402e-04,
       -1.12379622e-03, -1.86048611e-03,  1.60191557e-03,  1.45025097e-03,
        1.46376784e-03, -8.46402813e-03, -6.88573159e-03,  8.43785144e-03,
        5.63854445e-03, -4.01985226e-03,  4.26046923e-03,  9.36075766e-03,
        2.45318771e-03, -2.29009259e-02, -3.03990999e-03, -3.80586064e-03,
       -6.44602021e-03,  1.31052332e-02, -2.34151492e-03,  2.97498927e-02,
        1.18405875e-02, -1.39927482e-02, -1.42733129e-02, -2.92717130e-03,
       -8.39041919e-03, -2.96561942e-02, -7.60630332e-03,  7.08479946e-03,
       -1.68513996e-03, -2.44060066e-03,  1.38320141e-02, -1.10576749e-02,
       -4.26713526e-02, -6.29962934e-03,  3.04738153e-03,  8.01578909e-03,
       -1.24066127e-02, -7.35891424e-03, -9.71410703e-03,  1.45044690e-02,
       -1.28348023e-02, -1.10509899e-02, -3.63414665e-03,  1.14836115e-02,
       -1.80948265e-02, -5.37469797e-03, -1.57308634e-02,  1.45668667e-02,
       -3.14306444e-03, -1.98102947e-02, -6.35138247e-03, -7.88906403e-03,
       -4.61982377e-03, -1.00274524e-02, -5.15087182e-03, -3.35713290e-02,
        1.77887268e-03,  2.74553226e-04, -3.38718481e-03,  2.03121104e-03,
       -5.18860715e-03, -1.67987160e-02,  1.31344330e-02, -5.42837521e-03,
       -1.31445210e-02,  1.80366554e-03,  8.27263226e-04, -1.68964602e-02,
       -5.67492656e-03, -1.90527607e-02,  2.13063583e-02,  7.55028939e-03],
      dtype=float32), array([-6.05794378e-02, -2.02386566e-02, -1.84208620e-02,  2.66382508e-02,
        3.00467573e-02, -2.34712265e-03,  5.12860939e-02, -3.52159142e-02,
       -6.51374832e-02,  1.30570782e-02, -3.97748910e-02, -1.79058071e-02,
       -4.24707308e-02,  9.92092788e-02, -5.32900868e-03,  3.52906585e-02,
       -2.71598063e-02,  5.59581490e-03, -5.75302215e-03, -4.00167331e-02,
       -2.20764168e-02, -3.03109773e-02,  7.32743414e-03,  2.34515760e-02,
       -5.64120263e-02,  2.15111375e-02, -1.20703969e-02,  2.63934657e-02,
        2.37425882e-02,  3.38689871e-02,  1.85877215e-02,  1.92222446e-02,
        5.42624854e-03,  5.53374365e-02,  1.93184521e-02,  6.56266697e-03,
       -4.53445136e-05, -2.80137062e-02, -1.40808783e-02, -2.29148921e-02,
       -4.81348857e-02,  5.70762251e-03,  5.31723574e-02, -2.63183881e-02,
        2.74761338e-02,  2.82029733e-02, -9.24026128e-03, -1.01389950e-02,
        1.03873508e-02,  4.40188423e-02, -2.76288614e-02,  4.47435826e-02,
        3.47324423e-02, -4.30616848e-02,  1.28939366e-02, -2.94153392e-03,
        5.24858683e-02,  2.54559610e-02,  2.61535812e-02, -1.74501482e-02,
       -1.09816724e-02, -4.55355458e-02,  2.13150382e-02,  6.42330199e-02,
       -4.84360196e-02, -2.88213082e-02, -4.84423072e-04, -2.62841471e-02,
        5.11820018e-02,  6.97384262e-03,  3.17225754e-02, -5.91238476e-02,
       -3.47004421e-02,  5.76715730e-02,  4.08146046e-02, -2.80993637e-02,
       -4.75665443e-02, -1.32867396e-02, -2.48546451e-02,  8.26616120e-03,
        1.45459659e-02,  4.05880772e-02, -3.09555512e-03,  2.67986767e-02,
        3.14540928e-03, -5.77167161e-02,  8.13350896e-04, -9.76497866e-03,
        7.21961213e-03, -5.25226630e-02, -1.15851425e-02, -1.76688246e-02,
        8.09095055e-03, -3.78662199e-02,  2.73495577e-02,  5.11702616e-03,
       -5.51533774e-02,  4.37661540e-03,  3.37877646e-02,  3.91296074e-02,
        7.72277708e-04,  4.04623300e-02,  9.61318705e-03, -2.72434093e-02,
        4.59021665e-02,  2.87909582e-02, -1.78660192e-02, -2.06170194e-02,
        3.80277224e-02,  2.57976279e-02, -8.54847860e-03,  5.84827662e-02,
        2.61570476e-02,  1.40169803e-02, -2.57965438e-02,  5.72822392e-02,
       -5.60684577e-02,  9.11859423e-02,  5.22211492e-02, -2.85620689e-02,
        7.71132335e-02,  2.10285373e-02, -2.99000926e-02,  4.50290553e-02,
        1.71403680e-02, -3.63336727e-02, -1.68709364e-02,  2.86461916e-02,
       -2.21566260e-02, -1.22435223e-02, -1.72309335e-02,  4.58167400e-03,
        2.12172791e-02, -2.72943471e-02,  4.55442816e-02, -3.30997594e-02,
       -2.52465364e-02,  9.41298343e-03,  4.45683412e-02, -3.23863365e-02,
        7.88733177e-03, -1.22625558e-02, -5.62330410e-02,  5.39390696e-03,
        2.93136686e-02,  6.37490442e-03,  2.97936741e-02,  2.39144266e-02,
       -2.27108262e-02,  5.25198244e-02,  8.45177565e-03, -5.77552244e-02,
       -3.20136175e-02,  3.29867974e-02,  3.34402658e-02, -5.45750745e-02,
       -3.04516517e-02, -2.04385649e-02, -9.11355834e-04, -3.50018439e-04,
        1.00768460e-02,  2.44173054e-02,  6.87670708e-02, -3.73707712e-02,
       -5.24298586e-02,  3.23715247e-02,  8.82840902e-03, -6.40794216e-03,
       -3.60635780e-02, -1.09781278e-02,  2.23120023e-02,  1.54597703e-02,
       -2.80926488e-02,  6.52464554e-02,  3.80297378e-02, -4.67354432e-02,
        1.67514142e-02, -3.32907140e-02,  6.13175593e-02,  3.53645422e-02,
        3.86984535e-02,  1.74592510e-02, -3.39459851e-02, -3.12003717e-02,
        5.18509783e-02, -6.50054067e-02, -3.90579738e-02,  1.52682010e-02,
       -9.51596536e-03, -7.06318468e-02,  6.93406211e-03,  1.00887813e-01,
       -2.61264965e-02, -5.55428229e-02,  3.55164036e-02,  1.66645832e-02,
       -4.41959947e-02, -1.56115619e-02,  7.01997057e-02,  3.31460908e-02,
       -3.94866243e-02, -6.10531382e-02, -2.84690619e-03, -2.82560978e-02,
        2.61067282e-02,  3.30148824e-02, -4.80622388e-02,  5.50816720e-03,
        2.49507613e-02, -1.00747717e-03,  4.01139036e-02, -2.96296068e-02,
        3.13080624e-02, -3.34484838e-02,  3.93039808e-02, -1.44733917e-02,
        1.62782315e-02, -7.68220611e-03,  8.11796635e-03,  3.53048071e-02,
       -4.34356742e-02,  6.87955767e-02,  3.61490324e-02,  6.91335499e-02,
        4.57644202e-02, -5.39058410e-02, -2.12913449e-03,  1.68495048e-02,
        7.36424699e-02, -4.40055020e-02,  1.71917398e-02,  3.65964808e-02,
        3.24080251e-02, -2.99548618e-02,  6.89966604e-02, -9.43776872e-03,
       -6.69502765e-02, -1.85037032e-02,  2.88122762e-02,  5.66734299e-02,
       -8.23483244e-03,  1.20066544e-02,  3.37488167e-02, -1.30208358e-02,
       -1.63218305e-02, -1.71444863e-02, -2.56753266e-02,  3.17564979e-02,
       -3.70831303e-02, -3.81637737e-02, -4.26270328e-02,  4.20615599e-02,
        1.18452380e-03,  2.80534495e-02,  3.64393368e-02,  3.85231078e-02,
       -1.33491410e-02, -3.95839615e-03, -2.68883016e-02,  3.28560546e-02,
        3.18772569e-02, -3.94636467e-02,  2.95371581e-02, -1.93203171e-03,
        1.41438916e-02,  2.44511534e-02, -2.01360043e-02, -9.93666891e-03,
       -3.60412523e-02, -3.43094729e-02, -6.34518545e-03,  4.66421805e-03,
       -1.96617581e-02, -2.70038974e-02, -1.90783255e-02,  8.00953154e-03,
        5.78285158e-02,  4.61208634e-02,  2.80326940e-02,  5.80519438e-02,
        3.57821956e-02, -4.94153425e-02,  3.21670957e-02, -1.60774291e-02,
        1.30450437e-02,  3.12498286e-02,  2.66962405e-02, -7.49932509e-03,
       -5.20756692e-02, -2.02242658e-02,  6.20084070e-02,  4.67186198e-02,
       -5.71315810e-02,  7.61111174e-03, -1.75285395e-02,  2.74257362e-02,
        7.15611875e-03,  2.37486977e-02,  9.02723372e-02,  5.94143458e-02,
        4.26333165e-03,  4.73777726e-02, -3.23292017e-02, -1.16944360e-02,
       -1.71399415e-02, -1.56330522e-02, -4.83872695e-03,  2.34340392e-02,
       -2.89113814e-04,  6.46889508e-02,  1.91903766e-02, -1.52473981e-02,
        1.54664591e-02, -2.53748111e-02, -1.66243576e-02,  2.63403207e-02,
        2.32850891e-02,  2.47908030e-02,  1.30777834e-02,  8.46794713e-03,
        1.45235537e-02, -5.37561253e-02, -3.85809201e-03,  6.35965914e-02,
        1.51963113e-02, -4.37494814e-02, -4.76162843e-02, -2.44700219e-02,
       -2.00434774e-02,  1.61708798e-02, -6.13592677e-02,  3.19069363e-02,
       -1.97800528e-02, -9.58592165e-03, -1.62582714e-02, -2.14409474e-02,
       -9.99628101e-03,  5.03935255e-02,  5.00863492e-02,  4.49960539e-03,
        4.11354788e-02,  1.79442242e-02, -2.99773961e-02,  2.91089974e-02,
       -1.51805067e-03, -4.06844281e-02,  4.96576577e-02, -2.18987875e-02,
       -5.28988689e-02, -2.16376255e-04, -4.08592299e-02, -4.66659898e-03,
        4.06541303e-02,  3.73607944e-03, -2.66859718e-02, -2.45936159e-02,
       -1.08649908e-02,  5.69558842e-03, -7.57879689e-02, -4.02597599e-02,
        2.54257233e-03,  7.07402676e-02, -7.39474036e-03,  2.74138357e-02,
        4.01412845e-02, -3.90208419e-03,  3.11058480e-03,  2.53889058e-02,
       -7.65480101e-02,  2.31148489e-02,  1.54762194e-02,  3.05198412e-02,
        5.47123030e-02, -5.17687649e-02, -2.94118188e-02,  2.44807974e-02,
       -1.31764477e-02,  2.18616333e-02, -5.57196550e-02, -2.99420170e-02,
        1.21958988e-06, -4.60886136e-02,  2.42230669e-02, -1.02747511e-02,
        1.07006086e-02,  3.63534726e-02, -4.23764810e-02, -1.92366019e-02,
       -7.73541280e-04,  2.23135706e-02, -2.43545212e-02,  9.72233936e-02,
        3.38169187e-02,  4.47930098e-02,  1.00827906e-02,  6.54841512e-02,
       -4.04770337e-02,  2.33957786e-02,  2.19064187e-02, -2.69822893e-03,
       -2.37506907e-02, -1.67327188e-02, -2.21225657e-02, -2.71756146e-02,
       -5.42340577e-02,  5.14307134e-02,  1.88561936e-03, -2.87562795e-02,
       -4.48082201e-02,  4.46991548e-02,  4.93111424e-02, -2.47663353e-02,
        1.02908118e-02,  5.98161295e-03, -2.34476253e-02,  7.06509128e-02,
       -1.38018746e-02,  9.59475245e-03, -3.07131317e-02,  5.39436415e-02,
        1.98028572e-02,  7.17708394e-02, -2.22643279e-02, -1.72082074e-02,
       -8.36497173e-03,  1.67516731e-02, -1.06338169e-02,  3.51944305e-02,
       -1.53979287e-02,  1.74900275e-02, -2.19071992e-02, -3.37470025e-02,
       -3.18133421e-02,  6.66061416e-03,  3.52616906e-02, -4.60089222e-02,
       -2.16427501e-02,  2.67945062e-02,  2.39420380e-03, -3.15788314e-02,
        5.96595854e-02,  2.82549188e-02, -5.15689794e-03,  4.87186499e-02,
        5.60220443e-02, -3.22510153e-02,  3.72579806e-02, -2.06207708e-02,
       -2.26112567e-02,  2.05992833e-02,  3.62523017e-04,  2.53345743e-02,
       -2.61221360e-02,  4.55659814e-02, -1.27779916e-02, -1.81341136e-03,
        2.45620161e-02, -2.98355334e-02, -1.54471314e-02, -5.48647717e-02,
        4.22434229e-03,  3.98541577e-02,  1.22857401e-02, -2.27700360e-02,
        6.66887462e-02, -7.10844174e-02, -3.76481190e-02,  2.15374585e-02,
        1.61611810e-02,  4.53788601e-02, -2.38545798e-02, -3.07641719e-02,
       -2.28594802e-02, -2.01551430e-02,  4.46480922e-02,  6.68701455e-02,
       -3.26504186e-02, -3.39391641e-02, -2.51337350e-03,  2.40088180e-02,
        4.16454338e-02, -2.62098927e-02, -3.33471922e-04, -3.34621556e-02,
        2.73920074e-02,  2.77563855e-02,  6.34701326e-02,  4.99463491e-02,
       -7.25297118e-03,  2.45429222e-02,  2.34784279e-02,  1.75108407e-02,
        2.55771331e-03, -2.97404896e-03,  4.25461959e-03, -7.39370054e-03,
        6.49239123e-02,  4.77264300e-02,  3.50519679e-02, -2.06787623e-02,
        3.51667358e-03,  6.54855371e-03,  3.73569243e-02,  7.60694593e-02,
        2.93231122e-02, -1.72740649e-02,  6.67324290e-02,  5.46190701e-02,
        5.52739166e-02,  4.95889075e-02,  2.93667372e-02, -4.28288430e-02,
        4.34501767e-02, -1.24868117e-02,  6.05521947e-02,  4.08267006e-02,
        3.17350477e-02, -2.67623365e-02, -1.53136617e-02, -5.48190325e-02,
        2.01896485e-03, -2.65176538e-02, -1.84275545e-02,  3.18748914e-02,
        3.44778895e-02,  2.99104229e-02,  2.03353744e-02, -3.44939623e-03,
        3.98290530e-02,  2.78016888e-02, -2.24128775e-02,  3.43610905e-02,
       -5.40868379e-02, -1.78388674e-02, -1.82910322e-03,  3.78037207e-02,
        4.52417992e-02,  1.74794588e-02,  2.13824064e-02, -2.08602604e-02,
        1.21550765e-02,  6.32089749e-02,  3.75018567e-02, -1.02849118e-02,
       -3.72102112e-02, -1.23906741e-02, -2.01850440e-02, -8.56165681e-03,
       -4.12467979e-02, -2.24770140e-02,  1.86789222e-02,  2.01920010e-02,
        3.19329612e-02, -2.47534132e-03,  3.19030806e-02, -3.24786939e-02,
       -3.81051935e-02,  1.45651428e-02, -1.02598723e-02, -4.86478992e-02,
        1.04044676e-02, -2.90098917e-02,  2.39512622e-02,  1.49555644e-02,
        4.95205149e-02,  1.24664493e-02,  5.32538071e-02,  2.29427442e-02,
       -6.66328333e-03, -5.27123315e-03,  2.20311787e-02,  4.04869281e-02,
        5.52703626e-02, -3.91438827e-02,  5.84140383e-02,  3.67138647e-02,
       -2.72109043e-02, -2.24621943e-03, -2.04172656e-02,  2.91461721e-02,
        3.16250920e-02,  4.55861762e-02, -1.04018031e-02,  4.23276313e-02,
        5.22712842e-02, -1.92567590e-03, -2.07065120e-02,  2.96676811e-02,
        6.83427528e-02, -1.85464360e-02,  1.26655884e-02, -6.67802850e-03,
       -3.83518077e-02,  2.18621287e-02,  5.10619096e-02, -2.82032453e-02,
       -2.24109031e-02,  4.48956043e-02,  1.89213036e-03,  1.35143427e-03,
        3.74131538e-02,  7.00134486e-02, -2.43540015e-02, -5.14628403e-02,
        2.66087092e-02, -3.27317230e-02, -3.07096466e-02,  5.08775422e-03,
        1.46818534e-02,  2.76961979e-02, -2.62935106e-02,  3.88003839e-03,
       -1.73612237e-02, -3.69158424e-02, -1.73302069e-02, -4.75800969e-02,
        6.15708120e-02, -4.20079567e-02, -2.09907070e-02,  2.33116280e-02,
       -7.63017638e-03, -2.36392189e-02, -1.39710130e-02,  2.33092979e-02,
        3.54503170e-02, -4.87331636e-02, -1.67161748e-02, -4.17893054e-03,
        2.76954025e-02,  1.89014722e-03,  3.46635096e-02,  2.36204918e-02,
       -2.98972018e-02, -1.87987946e-02, -4.70871665e-02, -2.24551372e-02,
        4.91347909e-03, -2.76692156e-02, -5.98746585e-03, -3.69840972e-02,
        3.10956389e-02, -1.99456662e-02,  1.49782440e-02,  1.71610303e-02,
       -3.90651375e-02,  1.94731522e-02,  6.08896911e-02,  3.53138372e-02,
       -2.08127219e-02,  6.07081987e-02,  3.23572941e-02, -4.16362286e-02,
       -2.78531630e-02, -2.63850596e-02, -1.91647522e-02, -1.86070632e-02,
        2.77447235e-02,  4.74417433e-02, -1.06802294e-02,  2.24986533e-03,
       -3.94713283e-02,  4.68561128e-02, -8.77550221e-04,  2.66801566e-02,
       -3.27438489e-02, -9.16683394e-03,  3.17602381e-02, -2.64733583e-02,
       -3.82946134e-02,  5.54971993e-02,  1.16259260e-02, -1.10120268e-03,
        2.54802629e-02, -1.37526840e-02,  5.55853993e-02,  1.36541147e-02,
       -7.53648113e-03, -4.99492176e-02,  5.87663464e-02,  9.95644368e-03,
       -2.02912316e-02,  4.90383208e-02, -9.91336722e-03, -2.29042843e-02,
       -3.45736444e-02,  2.82679172e-03,  1.75722353e-02,  2.33052876e-02,
        3.35576199e-02,  4.09656297e-03,  1.81639753e-02, -5.94066083e-03,
       -1.82438772e-02, -1.37587767e-02,  5.42086959e-02,  1.48169592e-03,
        4.02861908e-02,  1.06434450e-02, -3.60639542e-02, -1.68879516e-02,
       -2.75987592e-02,  5.15436046e-02,  3.16387527e-02, -5.69712855e-02,
        5.10557257e-02,  4.87209298e-02,  1.55157577e-02,  2.16752253e-02,
        3.29305269e-02,  3.50572541e-02,  4.27773520e-02,  3.09814494e-02,
       -2.29843687e-02,  2.64466535e-02, -2.53278408e-02,  1.04137640e-02,
       -1.90524738e-02,  4.12496366e-02, -3.30950841e-02,  2.60204971e-02,
        4.13356088e-02, -3.60883400e-02,  5.20043150e-02, -1.96343288e-02,
       -3.15886885e-02,  5.94468564e-02, -5.11264652e-02,  4.34637032e-02],
      dtype=float32), array([0.10683759, 0.09033819, 0.0830493 , 0.09346855, 0.0920965 ,
       0.08895197, 0.10925558, 0.09344487, 0.10470255, 0.08960889,
       0.09214479, 0.0863266 , 0.09640095, 0.11146742, 0.08790702,
       0.0932282 , 0.09842914, 0.10157199, 0.08923357, 0.08458104,
       0.09011482, 0.09117019, 0.10598477, 0.08820534, 0.12487462,
       0.08838295, 0.10045656, 0.09174629, 0.09630344, 0.0893962 ,
       0.0901752 , 0.09171479, 0.08184756, 0.10216088, 0.09422937,
       0.08321945, 0.08573844, 0.09249952, 0.09038992, 0.0861987 ,
       0.10550129, 0.09666585, 0.09171513, 0.08680028, 0.09105045,
       0.08914264, 0.0867475 , 0.08649842, 0.08552644, 0.11160028,
       0.08649531, 0.10966295, 0.0925445 , 0.10643873, 0.09080671,
       0.0952743 , 0.09044592, 0.0930147 , 0.09002312, 0.08741648,
       0.08913193, 0.10488978, 0.08539145, 0.12245863, 0.08937103,
       0.09257118, 0.08767404, 0.09520269, 0.09719098, 0.09384517,
       0.08803707, 0.09785757, 0.08962532, 0.11586826, 0.09247617,
       0.09045283, 0.09247825, 0.08490564, 0.08448173, 0.09734525,
       0.08500593, 0.09181862, 0.0837436 , 0.09063794, 0.09022081,
       0.10283492, 0.09237185, 0.08329853, 0.12814908, 0.10082065,
       0.08506987, 0.08732078, 0.09795853, 0.08959003, 0.09208108,
       0.10042037, 0.09385994, 0.09769791, 0.09173465, 0.10744052,
       0.08338388, 0.09153695, 0.08430358, 0.08449117, 0.08984761,
       0.09420015, 0.08714308, 0.08944247, 0.08476222, 0.09071632,
       0.08655116, 0.10414489, 0.08970377, 0.09117818, 0.08700452,
       0.10216991, 0.09369714, 0.0991495 , 0.10703312, 0.08553659,
       0.10120933, 0.09089673, 0.08792149, 0.09906126, 0.09655321,
       0.09215637, 0.09036035, 0.09252533, 0.08923499, 0.08515993,
       0.08880821, 0.0870472 , 0.09410004, 0.08821544, 0.09742923,
       0.09644689, 0.08820782, 0.08436692, 0.09556682, 0.0876975 ,
       0.08604896, 0.09383632, 0.13385648, 0.09321048, 0.09952624,
       0.09945446, 0.09024861, 0.09646451, 0.09416503, 0.12930728,
       0.08369211, 0.11799589, 0.09702431, 0.09655441, 0.10880396,
       0.12118786, 0.08894956, 0.09231038, 0.08255692, 0.09444468,
       0.1228778 , 0.09338134, 0.09732522, 0.08633027, 0.0952561 ,
       0.08483259, 0.08526472, 0.08745953, 0.08838965, 0.08950906,
       0.08829306, 0.08360656, 0.09235942, 0.0994726 , 0.09163219,
       0.09469812, 0.09119353, 0.08495025, 0.11032388, 0.08752109,
       0.09641099, 0.0934293 , 0.09804703, 0.10175107, 0.11903057,
       0.09593721, 0.09951182, 0.10437296, 0.09111133, 0.10101891,
       0.08720243, 0.10800872, 0.08825765, 0.09369195, 0.08919825,
       0.0925693 , 0.09412795, 0.08587673, 0.09780982, 0.10394847,
       0.08913505, 0.08792916, 0.08662472, 0.09458036, 0.08884708,
       0.09602953, 0.09827061, 0.08425891, 0.08928823, 0.08377954,
       0.10066111, 0.0896325 , 0.08979538, 0.08883961, 0.08875104,
       0.09285068, 0.08533543, 0.08547099, 0.08209008, 0.09448268,
       0.09847519, 0.10922559, 0.09726891, 0.10407612, 0.08990376,
       0.109974  , 0.09266374, 0.0927692 , 0.10956554, 0.167102  ,
       0.08937964, 0.08830917, 0.09633423, 0.09547359, 0.10102051,
       0.08969047, 0.09875912, 0.08795045, 0.08305485, 0.10293996,
       0.0893179 , 0.08609271, 0.09065704, 0.08630854, 0.09030016,
       0.08238846, 0.09142838, 0.09580322, 0.08931378, 0.08844978,
       0.08490696, 0.09225747, 0.08245256, 0.09052914, 0.12393504,
       0.08992488, 0.08580054, 0.08734398, 0.09015764, 0.0848979 ,
       0.09021979, 0.10252269, 0.08719161, 0.09661304, 0.08994604,
       0.09588781, 0.08898693, 0.08821608, 0.0910046 , 0.10441457,
       0.08666801, 0.08757368, 0.08809949, 0.08446277, 0.08426412,
       0.09298702, 0.11546654, 0.10264452, 0.08980009, 0.12042522,
       0.0927598 , 0.09789447, 0.09716024, 0.08951569, 0.09365747,
       0.10222466, 0.10146066, 0.08847267, 0.09754474, 0.08660678,
       0.10148907, 0.11118511, 0.10432576, 0.10179497, 0.08824881,
       0.10696164, 0.08326793, 0.08685073, 0.11265453, 0.0966067 ,
       0.0838806 , 0.08862051, 0.08630221, 0.0844365 , 0.08876169,
       0.08370781, 0.0871023 , 0.10304378, 0.08442318, 0.11027113,
       0.08639368, 0.0876509 , 0.09014457, 0.08927128, 0.09382132,
       0.08597288, 0.08833237, 0.09707375, 0.08937173, 0.08194952,
       0.0899106 , 0.09393644, 0.08591495, 0.1018602 , 0.08952111,
       0.10874835, 0.09293275, 0.08581039, 0.08919192, 0.09333584,
       0.09595931, 0.08576877, 0.08487716, 0.09177946, 0.08657757,
       0.09244714, 0.08808801, 0.09463073, 0.0960304 , 0.08637366,
       0.0903313 , 0.09468301, 0.08703308, 0.09771619, 0.08691592,
       0.08678313, 0.10781799, 0.09633415, 0.09040416, 0.08707324,
       0.08832678, 0.08658734, 0.09471264, 0.09636196, 0.08324602,
       0.09450541, 0.08797225, 0.09202202, 0.10527309, 0.09615094,
       0.08779544, 0.1325875 , 0.08317707, 0.08782951, 0.0884812 ,
       0.08702283, 0.0857843 , 0.0936038 , 0.12707452, 0.09743416,
       0.09573656, 0.09138993, 0.11598773, 0.10259151, 0.09034856,
       0.10868035, 0.08697487, 0.11520287, 0.09310653, 0.09438019,
       0.08597993, 0.11296674, 0.08807906, 0.09426873, 0.08892377,
       0.08658534, 0.09209685, 0.08401224, 0.08785833, 0.08551937,
       0.09631906, 0.1190762 , 0.09738698, 0.09400702, 0.08930596,
       0.11043111, 0.08767374, 0.08336633, 0.09096036, 0.10442003,
       0.09268125, 0.09152551, 0.08760374, 0.11055258, 0.10174401,
       0.15180504, 0.0874959 , 0.08607583, 0.09781359, 0.09954841,
       0.11754129, 0.09265727, 0.08515483, 0.08616917, 0.09406326,
       0.10350443, 0.08450872, 0.08377291, 0.0953831 , 0.11954749,
       0.10117394, 0.12062711, 0.08448918, 0.08822506, 0.08868315,
       0.08899979, 0.09325621, 0.09841047, 0.09474431, 0.09454785,
       0.11075476, 0.08664631, 0.08942021, 0.08314691, 0.10865603,
       0.08586424, 0.08576963, 0.09035503, 0.083409  , 0.08810451,
       0.09806062, 0.08947976, 0.08596809, 0.10307795, 0.10771655,
       0.09600991, 0.09068711, 0.08662599, 0.08992349, 0.09169313,
       0.09555878, 0.10489469, 0.08526293, 0.09601741, 0.08386578,
       0.09403209, 0.09012639, 0.08962797, 0.08421096, 0.08599467,
       0.08837972, 0.10471252, 0.09034138, 0.09580516, 0.1047104 ,
       0.10434105, 0.10005939, 0.08628675, 0.0849155 , 0.0957084 ,
       0.08412876, 0.0979213 , 0.12161017, 0.08220274, 0.08577904,
       0.1151431 , 0.0848749 , 0.09631667, 0.08486075, 0.09312517,
       0.1091807 , 0.08285236, 0.09013103, 0.08712009, 0.08493361,
       0.09205356, 0.10244647, 0.10794623, 0.0844395 , 0.08545709,
       0.08563276, 0.09222596, 0.08544023, 0.08918298, 0.08486196,
       0.10602548, 0.19873768, 0.11237603, 0.1058711 , 0.09106657,
       0.08487059, 0.08795413, 0.12300934, 0.11492484, 0.09433162,
       0.08819325, 0.11033144, 0.11088093, 0.12834983, 0.10485715,
       0.09289991, 0.08701016, 0.09338383, 0.08530313, 0.10436603,
       0.09398137, 0.09528343, 0.09228057, 0.08605146, 0.10440548,
       0.08386508, 0.09018572, 0.09142123, 0.09171973, 0.11486389,
       0.09292333, 0.08527549, 0.08922182, 0.11466154, 0.09593192,
       0.09032893, 0.12072426, 0.08597482, 0.08270249, 0.08475898,
       0.10897396, 0.10202036, 0.09265123, 0.10607368, 0.08511864,
       0.08493433, 0.11965901, 0.0961326 , 0.09256041, 0.08523355,
       0.08277518, 0.08494294, 0.08196639, 0.0876615 , 0.0938492 ,
       0.08796389, 0.08296209, 0.10233992, 0.08257786, 0.09779751,
       0.1121537 , 0.08819939, 0.08711479, 0.10504018, 0.10028203,
       0.09270094, 0.09148135, 0.10052188, 0.08614199, 0.09118696,
       0.08409276, 0.10232135, 0.08959837, 0.09270558, 0.08368991,
       0.09226491, 0.09650643, 0.10031339, 0.09069292, 0.10604073,
       0.11655204, 0.0909307 , 0.10628549, 0.08737273, 0.09038668,
       0.09409228, 0.0885658 , 0.08249093, 0.09602937, 0.10074086,
       0.0871094 , 0.08475067, 0.08672538, 0.11077967, 0.09015366,
       0.08575749, 0.08485837, 0.09077049, 0.10032632, 0.1111903 ,
       0.09063248, 0.08444972, 0.09036795, 0.08530366, 0.08542083,
       0.08311865, 0.10648742, 0.09021275, 0.09737091, 0.09680929,
       0.08955357, 0.08875551, 0.08649132, 0.08393639, 0.087569  ,
       0.0878881 , 0.08828198, 0.08986579, 0.11680911, 0.09779657,
       0.10522512, 0.09271093, 0.10284029, 0.08489454, 0.09287444,
       0.09273185, 0.09278678, 0.08643188, 0.08524994, 0.0981518 ,
       0.09422653, 0.08550659, 0.08510324, 0.10109285, 0.09189969,
       0.10576359, 0.10205987, 0.08531574, 0.08821546, 0.11576448,
       0.08696428, 0.08583805, 0.08968141, 0.10010417, 0.09066584,
       0.09603608, 0.0915694 , 0.1020891 , 0.09632936, 0.08869974,
       0.12742488, 0.1055145 , 0.09007435, 0.08922493, 0.10209203,
       0.09731742, 0.0944377 , 0.09886616, 0.0965938 , 0.11848617,
       0.08522277, 0.09749379, 0.09672245, 0.08279488, 0.0819384 ,
       0.09680137, 0.08975714, 0.08801893, 0.08944804, 0.090943  ,
       0.08323685, 0.11100552, 0.09977211, 0.10053606, 0.15732235,
       0.08731423, 0.08206112, 0.08959144, 0.09081671, 0.10228902,
       0.09401783, 0.09157319, 0.095582  , 0.11157884, 0.08671628,
       0.08570239, 0.10413367, 0.08662347, 0.08836403, 0.09215647,
       0.08255303, 0.10435156, 0.08902755, 0.09112448, 0.08492243,
       0.08704272, 0.08648566, 0.08355515, 0.08440861, 0.1015793 ,
       0.08670097, 0.10148739, 0.08547456, 0.09210242, 0.08962517,
       0.09460027, 0.10463242, 0.09970605, 0.09825478, 0.09417675,
       0.1043093 , 0.08584859, 0.08471523, 0.09982182, 0.10154339,
       0.10126295, 0.10031071, 0.08847886, 0.09020355, 0.08923346,
       0.09137018, 0.0937288 , 0.11414897, 0.09653042, 0.08714422,
       0.09569757, 0.08600699, 0.09143346, 0.08919409, 0.09271016,
       0.10613318, 0.08923925, 0.09969074], dtype=float32), array([[[[-0.01321657],
         [ 0.00013096],
         [-0.01273497],
         ...,
         [ 0.00485986],
         [ 0.04165142],
         [ 0.0123849 ]],

        [[ 0.0039709 ],
         [-0.0213068 ],
         [-0.00012973],
         ...,
         [-0.00014061],
         [ 0.0051287 ],
         [ 0.00929016]],

        [[-0.0092436 ],
         [-0.01498758],
         [ 0.00784155],
         ...,
         [ 0.02216924],
         [ 0.0312943 ],
         [ 0.04001437]]],


       [[[ 0.02682398],
         [ 0.0116237 ],
         [ 0.0261938 ],
         ...,
         [-0.0065297 ],
         [-0.00489192],
         [ 0.01700401]],

        [[ 0.00760792],
         [-0.01683319],
         [-0.00594742],
         ...,
         [ 0.02303117],
         [-0.01111233],
         [ 0.03134385]],

        [[-0.02367865],
         [-0.00208822],
         [ 0.02806269],
         ...,
         [ 0.03864349],
         [ 0.03012658],
         [-0.00922584]]],


       [[[ 0.02315777],
         [ 0.00739213],
         [ 0.01054112],
         ...,
         [-0.01065613],
         [-0.00921653],
         [-0.00847054]],

        [[ 0.00364864],
         [-0.02688122],
         [ 0.00097018],
         ...,
         [ 0.01970304],
         [ 0.04086492],
         [-0.00850921]],

        [[ 0.02073125],
         [ 0.00773822],
         [ 0.02355542],
         ...,
         [ 0.01566958],
         [-0.00335857],
         [ 0.01804264]]]], dtype=float32), array([[[[ 0.04245162, -0.04981577,  0.0328497 , ...,  0.05818962,
           0.01127351,  0.04847978],
         [ 0.02721803, -0.04978388, -0.05790213, ...,  0.04377645,
          -0.05329389, -0.06583081],
         [ 0.02566413,  0.0202862 , -0.0531658 , ..., -0.06251833,
           0.0121752 , -0.00143358],
         ...,
         [-0.03122249, -0.00784633, -0.00325667, ...,  0.0475383 ,
          -0.00489588,  0.00879321],
         [ 0.01197025,  0.02478473,  0.01380979, ..., -0.01074303,
          -0.01017205, -0.01245897],
         [-0.00711461, -0.05958639,  0.06867065, ...,  0.00692829,
          -0.00763274,  0.027231  ]]]], dtype=float32), array([0.99935526, 1.0016676 , 1.0003037 , 0.99584603, 1.0122892 ,
       0.9899844 , 1.0041829 , 0.9980069 , 1.0142114 , 0.9956103 ,
       0.9801869 , 0.9975445 , 1.0065342 , 0.9941953 , 1.0122325 ,
       0.987421  , 0.99006766, 0.99948555, 1.0079226 , 1.0228865 ,
       0.99254996, 1.0229503 , 1.0132942 , 1.0033076 , 0.9997644 ,
       0.9800287 , 0.9991772 , 0.99892837, 1.0086309 , 1.0137627 ,
       0.98110676, 1.0056607 , 1.0002753 , 1.0113219 , 1.0226334 ,
       0.9938695 , 0.98822486, 1.0100656 , 0.99448824, 0.99969226,
       1.0012275 , 0.9903337 , 0.9862828 , 0.97764564, 1.0025555 ,
       1.0052248 , 0.9893892 , 1.0036588 , 0.9801043 , 1.0029513 ,
       1.0145808 , 1.0064237 , 1.0005598 , 1.0158147 , 0.97310674,
       0.97004175, 0.9988373 , 0.99497676, 0.9941785 , 1.0106084 ,
       1.0105623 , 0.99348426, 0.99555385, 0.98811066, 1.0027095 ,
       1.0123388 , 1.0150799 , 1.0075668 , 0.98952204, 0.99537253,
       1.0130433 , 1.0017309 , 0.9985636 , 0.99174255, 1.0017567 ,
       1.02084   , 0.99558973, 1.0102699 , 0.99830264, 0.98017114,
       0.98247814, 1.014901  , 1.0004036 , 1.011294  , 0.98659366,
       0.99608284, 0.9886601 , 0.97288334, 1.0014604 , 0.9939225 ,
       1.0098587 , 1.0027702 , 0.9965797 , 1.0058045 , 0.99389255,
       1.0013287 , 1.0105988 , 0.99696547, 1.0032738 , 0.99529606,
       0.9920992 , 0.9937937 , 1.0111238 , 1.0074464 , 1.0043876 ,
       0.96665573, 0.98159957, 0.9813552 , 0.9959752 , 1.0225875 ,
       1.001671  , 0.99818355, 0.99111545, 1.0019622 , 0.9696654 ,
       1.0086946 , 1.0016932 , 0.9916275 , 1.0053457 , 1.0032154 ,
       0.98751324, 0.9955805 , 1.0024408 , 1.0069015 , 0.97246456,
       1.0144955 , 0.9919604 , 1.0064805 , 1.0136938 , 1.0007899 ,
       1.0264783 , 1.0211765 , 0.99829817, 0.9820757 , 1.0044867 ,
       1.0137235 , 0.99060726, 0.9735539 , 0.99061894, 1.0047293 ,
       0.9956734 , 0.9977613 , 1.0055184 , 0.99279207, 1.0000088 ,
       1.0147451 , 0.99797046, 0.97804415, 0.9945652 , 0.9972557 ,
       0.9964098 , 1.0140607 , 0.9826423 , 0.9924778 , 1.0012381 ,
       1.0028111 , 1.0057188 , 1.042752  , 1.0050105 , 0.9982106 ,
       0.99120533, 0.9771931 , 0.9933351 , 0.98423195, 1.0150726 ,
       0.9803291 , 1.0029987 , 0.99228054, 1.0139945 , 0.9996923 ,
       0.9977409 , 0.966671  , 1.0016725 , 1.017323  , 1.0184633 ,
       0.9848521 , 0.99305916, 1.0055493 , 0.9859596 , 1.012     ,
       0.98004687, 1.0120608 , 0.99929667, 0.9971326 , 1.0317326 ,
       0.9967486 , 1.0040699 , 1.0147948 , 1.037961  , 1.0158118 ,
       0.99581254, 1.0312898 , 1.0132833 , 1.0074962 , 1.0164315 ,
       0.9880241 , 0.9960267 , 0.9963972 , 0.9981574 , 1.0252246 ,
       0.9983122 , 1.0044357 , 0.99974895, 0.97550553, 0.974388  ,
       1.0229888 , 1.0008868 , 0.99565923, 0.99712545, 1.0125084 ,
       0.9795515 , 1.0062631 , 0.9989381 , 0.995985  , 1.0025831 ,
       1.0025748 , 1.0108129 , 1.0240043 , 0.9918536 , 0.9916798 ,
       0.9976727 , 1.0022836 , 0.99231523, 0.9925262 , 1.0099249 ,
       0.99599093, 1.0000672 , 0.99645454, 1.0194199 , 1.0077096 ,
       1.017758  , 1.010467  , 1.0249649 , 0.99788165, 1.0022902 ,
       1.0058297 , 0.99644935, 0.9935803 , 0.99504346, 0.998927  ,
       0.99442446, 1.008007  , 1.000101  , 0.9818899 , 0.9760478 ,
       0.9941799 , 0.9715325 , 1.019851  , 0.9839842 , 1.0314522 ,
       0.99125665, 1.0036871 , 1.0129919 , 1.0204749 , 0.97408724,
       0.9904627 , 1.00681   , 1.0056549 , 0.97167295, 0.9961458 ,
       0.98338085, 0.9816416 , 1.010176  , 1.0037614 , 1.0033227 ,
       1.0045861 , 0.9985022 , 0.99660957, 0.9818092 , 1.000858  ,
       1.012078  , 1.0198562 , 0.99587154, 0.9931699 , 0.9915979 ,
       1.0018649 , 1.0053803 , 1.0084696 , 0.99230826, 1.0094522 ,
       0.99605346, 0.9801987 , 1.0112268 , 1.0037372 , 1.0091993 ,
       0.97654974, 1.0023112 , 1.00478   , 0.9961312 , 0.9998923 ,
       1.0009031 , 1.0070736 , 0.99206495, 1.0036719 , 1.0223086 ,
       1.0160068 , 0.9813526 , 0.99845546, 0.9687701 , 1.0007664 ,
       1.01704   , 0.99858034, 0.99028033, 1.0264639 , 1.0166919 ,
       0.9756423 , 1.0072725 , 1.0089278 , 0.99346393, 0.9953329 ,
       1.0010744 , 0.9978525 , 0.9943776 , 1.0112914 , 0.9988529 ,
       1.0267135 , 0.98693514, 1.0328873 , 1.0066925 , 0.98169565,
       0.9983233 , 1.0082626 , 1.0107806 , 1.0089338 , 1.0106622 ,
       0.99947673, 0.9928653 , 0.97798383, 0.98830104, 1.0115895 ,
       0.9916407 , 1.0002009 , 0.987601  , 0.99591464, 1.0044118 ,
       0.99316084, 1.0215214 , 0.99080616, 1.0159943 , 0.9974523 ,
       1.0125303 , 1.001969  , 0.9985701 , 1.0057651 , 0.99905556,
       1.0018957 , 1.0269492 , 1.0023721 , 1.0117513 , 0.9875395 ,
       1.0256155 , 1.0029657 , 1.0248111 , 1.0181981 , 0.99439245,
       0.9810076 , 1.0140263 , 0.989894  , 0.9858049 , 0.9997364 ,
       0.98861307, 1.0125605 , 1.0060594 , 0.993418  , 0.9904507 ,
       0.9781437 , 1.0156531 , 1.0222228 , 0.99353254, 1.009723  ,
       1.0390749 , 0.99385685, 0.98533833, 0.97141856, 1.0125175 ,
       1.005001  , 1.0117013 , 0.995407  , 1.0145147 , 1.0229238 ,
       1.017464  , 1.0099741 , 1.0052581 , 0.9954069 , 1.0059102 ,
       0.9784686 , 1.0006337 , 1.0263352 , 0.99575585, 1.005527  ,
       1.0184853 , 1.0055045 , 1.0066216 , 0.9939786 , 0.9812157 ,
       0.9965198 , 0.9958714 , 1.0095927 , 1.009551  , 1.0038596 ,
       0.99198633, 0.99405986, 1.0093113 , 1.0150633 , 0.97626424,
       1.0027549 , 0.9989641 , 0.99326485, 1.0041945 , 0.99926573,
       0.9794106 , 1.0025989 , 0.98862827, 0.9954147 , 0.9914508 ,
       1.0037826 , 1.0168241 , 0.9703407 , 1.0058813 , 0.9975016 ,
       0.9894724 , 0.9919272 , 0.98782825, 1.0022234 , 0.9959723 ,
       0.99121964, 1.0205522 , 1.0212953 , 1.0168312 , 1.001828  ,
       1.0432425 , 0.98589206, 1.009863  , 0.9796752 , 1.0010333 ,
       1.0056814 , 0.97582215, 0.99231267, 1.0007515 , 0.98673135,
       1.0090922 , 0.9859832 , 1.0118183 , 0.99747276, 1.004844  ,
       1.0110432 , 0.99640006, 1.0073739 , 1.022551  , 1.02759   ,
       1.0126187 , 0.9987344 , 0.9903892 , 1.0182531 , 1.0107665 ,
       1.0071012 , 0.99087465, 1.0284058 , 1.0037895 , 0.99399394,
       0.99207217, 1.0051862 , 1.0056602 , 1.0015622 , 0.9877941 ,
       0.9867612 , 1.005542  , 0.98554516, 1.0188706 , 0.9928403 ,
       0.99837524, 1.0051515 , 1.0116653 , 1.0047699 , 1.000242  ,
       0.9921793 , 0.99600893, 0.99883676, 0.99316937, 0.9932717 ,
       0.9863379 , 0.98901343, 0.99491864, 1.0070317 , 1.0109512 ,
       0.9739505 , 1.0167022 , 1.011283  , 1.0029768 , 1.007626  ,
       0.99159795, 0.9915326 , 1.005818  , 1.013203  , 0.9825973 ,
       0.9931957 , 1.0044695 , 1.012886  , 1.0098845 , 0.9951444 ,
       0.99804664, 0.9909939 , 1.0044478 , 0.9817322 , 1.0049945 ,
       1.0063784 , 1.0009766 , 0.99897516, 1.003669  , 1.0056314 ,
       0.99953115, 1.0146996 , 1.0061474 , 0.98627985, 1.0030314 ,
       1.0054216 , 1.0269427 , 1.0194069 , 1.008037  , 1.0135456 ,
       1.0084664 , 1.0037086 , 1.00881   , 0.998701  , 1.0060313 ,
       1.0081456 , 0.99336755, 0.9885772 , 1.001765  , 1.0060638 ,
       0.9900253 , 1.0108424 , 1.0133976 , 1.0253145 , 0.996348  ,
       0.9984709 , 0.9898035 , 0.99710006, 0.9970219 , 1.0147184 ,
       0.98420924, 1.0231209 , 0.9886439 , 0.9912286 , 0.99581164,
       1.0211799 , 1.0295163 , 0.99760956, 1.0163435 , 1.0074979 ,
       0.99649096, 0.99957955, 1.0007566 , 1.0027404 , 1.0127685 ,
       1.002264  , 1.0257587 , 1.0133013 , 1.0053126 , 1.0406532 ,
       1.0034755 , 1.0067184 , 0.98027253, 1.0025687 , 1.0334646 ,
       0.982659  , 1.0160264 , 0.9978964 , 1.0025033 , 0.98357093,
       1.0045382 , 0.9919474 , 1.0052056 , 1.0079801 , 0.98938847,
       0.98925406, 1.0131041 , 0.99369067, 0.99008435, 1.0094054 ,
       0.9901521 , 0.99540466, 1.0070196 , 0.99651784, 1.0168047 ,
       0.99847925, 1.0048434 , 1.012977  , 1.0002371 , 1.002101  ,
       1.0040017 , 1.0045745 , 1.0381038 , 1.0107096 , 0.99403334,
       0.97250193, 1.0042869 , 1.011146  , 0.98397726, 0.99718523,
       0.9907683 , 0.99970704, 1.0334284 , 0.9952403 , 0.9922248 ,
       0.99810356, 0.9939012 , 0.99675906, 0.9841746 , 1.0105504 ,
       1.0211769 , 1.0082264 , 0.9975925 , 0.98244524, 1.0155977 ,
       1.0066043 , 1.0058994 , 1.009801  , 0.97895163, 0.9989511 ,
       0.98751235, 1.0042218 , 1.0259581 , 0.99752635, 1.0015917 ,
       0.9834625 , 1.0233066 , 1.032889  , 0.9995845 , 0.99006015,
       0.9977918 , 1.0113329 , 1.0048252 , 0.99852103, 1.003623  ,
       0.99221325, 0.9858624 , 0.99098617, 1.0221972 , 0.98003566,
       1.0146319 , 1.0025746 , 0.99117106, 1.0034355 , 0.9982933 ,
       0.9904146 , 0.9861051 , 0.99972665, 1.0069244 , 0.9927518 ,
       0.99596655, 1.0304248 , 0.9947157 , 1.006051  , 1.0015551 ,
       1.0154159 , 0.9977562 , 0.9884493 , 0.9888063 , 1.002276  ,
       0.9940895 , 0.9957268 , 0.9959775 , 1.0070446 , 1.0108603 ,
       1.0019692 , 1.0034678 , 1.00331   , 0.99052894, 1.0102173 ,
       1.0061612 , 0.9948942 , 1.0111636 , 1.0064554 , 1.0033573 ,
       0.9911272 , 1.0146399 , 1.0069413 , 1.0026709 , 0.9930347 ,
       0.9731789 , 1.0229535 , 1.018546  , 0.99663925, 1.0161942 ,
       1.0177207 , 0.99304783, 0.99298173, 1.0110083 , 0.99847   ,
       1.0100503 , 0.9879406 , 1.0018349 , 0.97585297, 0.9820595 ,
       1.0062616 , 1.0034368 , 0.9955394 , 1.0100636 , 1.0182451 ,
       0.9967365 , 1.001009  , 0.9988071 , 0.99343854, 1.01074   ,
       0.99561185, 1.0196279 , 0.98388404, 1.001869  , 1.0233235 ,
       0.9898355 , 0.99789083, 1.0099353 , 0.9930129 , 1.0035119 ,
       1.0098195 , 1.0198613 , 0.99842364, 0.99079174, 0.98720115,
       1.002953  , 1.0207747 , 1.0225179 , 1.0070376 , 1.0072534 ,
       0.9870535 , 1.0092978 , 1.0087221 ], dtype=float32), array([-4.98082489e-03, -2.11759261e-03, -1.35250846e-02, -4.16513067e-03,
        1.33956950e-02, -2.60140635e-02, -7.42256816e-04, -4.14313599e-02,
        1.64446943e-02, -3.70707572e-03,  2.13783514e-02,  1.15404362e-02,
        5.53200487e-03, -4.13645618e-03,  4.90562757e-03,  1.49562126e-02,
       -5.88628277e-03,  2.31807260e-03, -1.47267049e-02, -2.27710698e-02,
       -1.85467843e-02, -2.08466072e-02, -1.29502267e-02, -1.41726136e-02,
       -8.78010411e-03,  2.74391677e-02,  1.53831337e-02,  2.06470639e-02,
        3.58064449e-03, -5.55387046e-03,  1.48219918e-03, -1.70829687e-02,
        9.27840266e-03, -1.59474537e-02,  1.95874982e-02, -1.03348177e-02,
       -6.23527914e-03, -1.17508490e-02, -2.94817798e-03, -7.49606034e-03,
        4.94578853e-04,  2.24356577e-02,  2.87123513e-03,  5.25002414e-03,
        1.24676777e-02, -4.63002883e-02, -1.15250489e-02, -5.21203177e-03,
       -3.68578210e-02,  1.03736129e-02, -8.93043075e-03,  1.37115596e-02,
       -3.13240848e-02,  6.22608233e-04, -1.79417594e-03,  1.55524472e-02,
       -6.98994519e-03, -6.05916744e-03, -5.30503457e-03, -5.16122067e-03,
        5.95042855e-03,  2.34501418e-02, -1.28525225e-02, -9.27171018e-03,
        3.22431140e-03, -6.12907950e-03, -1.40744084e-02,  1.29869608e-02,
        9.78509989e-03,  6.11692620e-03,  1.24755157e-02,  4.22811322e-03,
        1.01899542e-02, -6.50240481e-03,  2.99637411e-02, -7.28599308e-03,
        1.69646014e-02, -9.35514458e-03, -5.55011909e-03, -6.38170680e-03,
       -2.10252162e-02, -2.33269483e-03, -8.38657934e-03,  1.56810519e-03,
        1.80421211e-02,  1.11540454e-03, -2.16698460e-03,  7.81553914e-04,
        7.70407123e-03,  1.02507062e-02, -3.51367681e-03, -2.11640876e-02,
       -1.20335771e-02, -7.27601489e-03, -2.96133594e-03,  8.21530074e-03,
        1.93791222e-02, -9.57725476e-03,  1.17796371e-02,  1.72225423e-02,
        2.29360347e-04,  5.96484030e-03, -1.67916529e-03, -1.08897071e-02,
       -6.46007434e-03, -1.11968545e-02, -2.19473336e-02, -2.93136276e-02,
       -3.30479164e-03, -5.61030488e-03,  5.07700955e-03, -1.84075348e-02,
        2.30483711e-02, -3.55240004e-03,  1.83918758e-03, -9.50241089e-03,
        8.73821601e-03, -1.55837415e-02,  1.88968442e-02,  1.39896907e-02,
       -1.57239195e-02, -1.80805996e-02, -1.57514047e-02,  2.01559234e-02,
       -1.35891419e-02, -1.28702950e-02,  7.33008899e-04,  3.33620459e-02,
       -1.84484920e-03,  9.62942559e-03, -1.87760275e-02,  4.11547907e-02,
        3.53399292e-03, -3.05792270e-03, -1.14028538e-02, -1.80352461e-02,
        3.51860300e-02, -2.90537421e-02, -2.62337597e-03, -2.22120900e-02,
        2.64256559e-02,  1.16683291e-02,  1.04809329e-02, -7.93970656e-03,
       -1.10833384e-02,  1.20005393e-02,  5.45173837e-03, -2.92372834e-02,
       -2.38352008e-02, -8.90668854e-03, -1.21556818e-02, -1.96033046e-02,
       -2.53425576e-02, -1.85927171e-02,  1.18299127e-02,  1.09288283e-02,
        1.37063989e-03,  4.34792414e-03, -7.46527128e-03,  1.56673079e-03,
       -6.78445259e-03, -5.82086062e-03, -7.44887209e-03, -1.89260840e-02,
       -4.90750931e-03, -2.98164468e-02,  2.00704182e-03, -1.66147831e-03,
        5.27032139e-03, -7.97371473e-03,  2.97559313e-02, -3.20050083e-02,
        1.75887551e-02, -4.48057568e-03, -1.48806479e-02, -8.09459388e-03,
       -7.07503175e-03,  1.99091919e-02, -3.12430831e-03, -8.72582570e-03,
        8.85004830e-03, -7.24845147e-03, -8.93563591e-03, -1.80378612e-02,
       -2.85644308e-02, -1.12733152e-02,  4.69415158e-04,  7.21374806e-03,
       -1.54515374e-02,  4.83099464e-03, -6.10304065e-03,  1.89961679e-02,
       -8.51798989e-03, -3.57722375e-03,  1.30466260e-02, -8.99990555e-03,
       -1.87076337e-03, -1.75267588e-02, -1.63457058e-02, -2.30721943e-02,
        9.28982534e-03,  2.24833307e-03,  2.52504535e-02, -2.77348496e-02,
       -1.25127593e-02, -1.71771161e-02,  3.65041159e-02, -2.11658534e-02,
        6.29628601e-04,  2.05565225e-02, -3.77160171e-03, -1.53876133e-02,
       -3.39482562e-03, -1.18005900e-02, -2.22760197e-02, -5.68147283e-03,
        5.84129756e-03, -2.57918518e-03,  2.46568508e-02, -1.60668194e-02,
       -9.56812315e-03,  5.84803754e-03,  7.18441186e-03, -6.25513960e-03,
        1.66763496e-02,  5.12605393e-03,  1.27266785e-02,  2.88722906e-02,
        1.66990189e-03, -9.22532193e-03,  4.14168611e-02, -7.11436011e-03,
       -1.35885319e-02, -1.13900881e-02, -2.45941691e-02, -2.85905856e-03,
       -2.04937644e-02, -1.17143756e-03, -3.16175371e-02, -1.76024821e-03,
       -9.69634857e-03,  3.34081128e-02,  1.32112550e-02, -1.21130124e-02,
        8.08662083e-03, -2.22711526e-02,  2.12251283e-02,  1.30328350e-03,
       -1.16239926e-02, -1.01066595e-02, -7.74611253e-03,  5.29467920e-03,
       -1.33528272e-02,  1.26168840e-02, -9.33554675e-03, -2.00339202e-02,
       -2.78808014e-03,  2.87515596e-02,  5.77149168e-03, -8.51029821e-04,
       -2.42019054e-02, -1.08280415e-02, -1.58919655e-02, -2.91164964e-02,
        1.20566497e-02,  1.73716135e-02,  9.05933790e-03,  7.30512850e-03,
       -1.09895281e-02,  7.99758174e-03,  2.99066100e-02, -1.03979437e-02,
       -7.06121465e-03,  1.18634151e-03, -2.46215053e-02, -1.04273809e-02,
       -5.28238108e-03, -5.21905050e-02,  1.16144549e-02, -1.39579661e-02,
       -2.13675690e-03,  1.47991339e-02,  8.99303763e-04,  1.81638519e-03,
       -2.53044311e-02, -1.02573810e-02, -1.58710349e-02, -1.01314867e-02,
       -7.38658942e-03, -1.35333650e-02, -6.33414509e-03,  3.59743722e-02,
        1.44298677e-03, -2.43716631e-02, -1.11880191e-02,  1.50606944e-03,
       -3.20679275e-03,  1.73109863e-02, -8.35896004e-03,  2.56906438e-04,
       -2.09662206e-02,  4.74711647e-03, -6.54510502e-03, -2.43446548e-02,
        5.05836820e-03, -2.03691795e-02, -3.29864100e-02,  3.98267666e-03,
        1.29144043e-02, -6.18410669e-03,  9.52007342e-03,  4.31539584e-03,
        9.50508285e-03,  1.68857351e-02,  1.51168481e-02, -8.67154682e-04,
       -2.54406407e-02, -1.68703943e-02,  2.45406348e-02, -9.73581150e-03,
       -1.17440009e-02,  1.35502284e-02, -2.56739613e-02, -4.44555376e-03,
        2.65689082e-02,  1.94160547e-02,  1.81593895e-02,  7.54364301e-04,
       -7.51825282e-03, -2.39809621e-02, -2.32327450e-02,  8.11994541e-03,
       -1.19897246e-04,  2.73772459e-02, -5.27238846e-03, -2.93943402e-03,
       -5.18965884e-04, -1.98929030e-02, -7.40025984e-03,  1.93765957e-03,
        1.15327053e-02, -1.87602490e-02,  5.91082079e-03, -1.45333698e-02,
        4.72978369e-04,  3.68160871e-03,  9.14984383e-03, -5.02159214e-03,
        2.76299529e-02, -1.83785427e-03,  1.66821182e-02,  2.07445472e-02,
        2.69630067e-02,  3.55344974e-02, -7.04390695e-03, -2.55391989e-02,
        5.11302752e-03, -1.62446164e-02, -1.13017336e-02,  4.72333934e-03,
       -6.80400757e-03, -3.33909281e-02,  1.55326342e-02, -1.84160266e-02,
        1.31890588e-02,  1.64169190e-03, -1.99270137e-02, -8.69304780e-03,
        7.56336981e-03,  2.96448590e-03, -1.90541334e-02, -1.48985256e-02,
       -2.42910581e-03, -3.76383848e-02,  6.70862151e-03,  1.26105128e-03,
       -2.85195676e-03, -3.41552719e-02,  8.30010604e-03, -1.40201477e-02,
       -3.82276364e-02, -2.50616670e-02,  3.01907528e-02, -6.30699098e-03,
       -8.97488091e-03, -2.20603272e-02, -1.06637171e-02, -2.17397287e-02,
        1.19074313e-02, -2.27383021e-02, -1.55907199e-02, -2.29770038e-03,
       -4.40897606e-03,  9.61065572e-03, -3.29413428e-03, -2.20418312e-02,
        8.43952294e-04, -1.04773464e-02, -1.15461340e-02,  7.25148758e-03,
       -2.13990919e-02, -2.13123439e-03,  1.23471273e-02,  3.22452411e-02,
       -1.15511334e-02, -4.11584647e-03, -4.20540338e-03, -3.10536493e-02,
       -1.62009876e-02, -3.51052685e-03, -8.60004779e-03, -2.00520121e-02,
        8.61352030e-03, -2.73682233e-02,  8.54607858e-03, -2.00736355e-02,
       -5.66113275e-04, -1.87937133e-02,  2.58089323e-03, -3.10336202e-02,
       -8.17992026e-04, -2.80389618e-02, -1.27695100e-02, -2.38929223e-02,
       -4.53335745e-03, -4.53564525e-03, -5.81031293e-02,  8.38410854e-03,
       -4.46436694e-03,  3.58965923e-03, -1.37981530e-02,  2.18074098e-02,
       -2.51535536e-03, -3.80897559e-02,  4.61406307e-04, -1.75440144e-02,
        7.74963619e-03, -3.38284485e-03, -2.16986928e-02, -5.98623883e-03,
       -1.42287677e-02,  3.43391462e-03, -3.26586794e-03,  5.22425398e-03,
       -1.16672767e-02,  1.18986731e-02, -5.73814567e-03, -4.93598683e-03,
        1.39164412e-02, -1.76034421e-02, -2.06315890e-02, -1.22928526e-02,
        5.27799595e-03, -5.18996548e-03,  3.09795979e-02, -1.21888593e-02,
       -4.26191138e-03,  1.76920407e-02,  1.90334227e-02,  5.70564182e-04,
       -3.63960187e-03,  6.47431519e-03,  2.93175578e-02,  2.55393307e-03,
       -3.11225671e-02, -1.22785214e-02,  4.08848468e-03, -1.85214896e-02,
       -4.63867933e-03,  5.83791640e-03, -7.18743121e-03, -2.00956501e-02,
       -1.17883170e-02, -3.38069089e-02, -4.21589240e-04, -2.04592161e-02,
       -9.83005017e-03, -2.13917401e-02, -4.20923764e-03,  2.20730365e-03,
       -1.41389742e-02, -2.90346257e-02, -4.16152319e-03, -3.09345173e-03,
        1.87011641e-02, -2.80165002e-02, -2.34888680e-03, -4.55086306e-03,
        1.07191009e-02,  2.52003781e-03, -7.13929394e-03, -1.40118916e-02,
       -1.20665831e-02, -9.74453334e-03, -1.27010178e-02,  2.58982833e-02,
        4.24982328e-03, -2.27918178e-02,  1.27960450e-03, -3.45205329e-02,
       -1.50734857e-02,  1.97960287e-02,  2.39040852e-02, -1.32636953e-04,
       -1.29068568e-02, -8.45323410e-03, -8.84838123e-03,  3.02878041e-02,
       -5.49683068e-03, -2.36482918e-03,  7.33041088e-05, -1.15611199e-02,
        1.98729746e-02, -1.71596780e-02,  3.09433173e-02, -5.50063839e-03,
       -6.40311325e-03,  2.67467578e-04, -7.95627479e-03, -9.36316792e-03,
        5.04774228e-03, -1.45581122e-02, -1.83988689e-03,  1.90236829e-02,
        2.45333824e-04, -1.80549361e-03, -7.13231927e-03,  1.21200026e-03,
       -2.20849141e-02,  6.42336579e-03, -9.17793903e-03,  1.31883305e-02,
       -2.11659241e-02,  4.31215279e-02,  1.09916730e-02, -3.76933208e-03,
       -2.25838386e-02, -1.36394026e-02, -6.29371614e-04, -3.23212929e-02,
       -1.79727320e-02, -3.65260616e-02, -1.19956536e-02, -1.20819537e-02,
       -1.70424003e-02,  1.57676116e-02, -4.04150272e-03,  6.21714862e-03,
       -1.10691143e-02, -7.87136517e-03,  6.54275250e-03, -1.96872260e-02,
       -4.54057474e-03,  5.36383456e-03,  1.60390902e-02, -7.80849019e-03,
       -4.16929387e-02, -7.82954786e-03,  4.93949279e-03,  2.10054009e-03,
        1.45743107e-02,  8.80825520e-03,  1.02029657e-02,  1.45856487e-02,
        3.78580466e-02, -5.72722033e-03,  1.87212694e-02, -1.06632710e-02,
        3.09626665e-03, -4.26560268e-03, -1.76231228e-02, -1.33172525e-02,
       -5.67335747e-02, -3.45878745e-03, -4.49918257e-03, -5.74523769e-03,
       -2.07457244e-02, -2.37878202e-03, -9.81384702e-03, -4.06042114e-02,
       -1.08926534e-03, -1.97510250e-04,  6.62613707e-03, -1.83398428e-03,
        3.84072401e-02, -8.30435008e-03, -1.48534579e-02,  1.38988709e-02,
       -2.94428528e-03, -7.94061576e-04,  1.81522332e-02, -6.21374277e-03,
        7.06255995e-03, -4.01473744e-03,  2.06525510e-04, -2.05002655e-03,
        1.75752677e-02,  1.61531512e-02,  6.45845011e-03,  1.49255143e-02,
       -1.87715180e-02, -3.19419987e-03, -1.03352284e-02, -8.85498710e-03,
       -1.22472011e-02, -3.14105814e-03,  9.35339078e-04, -7.58285867e-03,
        6.86861633e-04, -1.17121413e-02, -5.69039630e-03,  2.33731922e-02,
       -2.58258879e-02, -1.17722647e-02, -1.45597477e-02,  1.57544203e-03,
       -2.64618676e-02, -1.60380211e-02,  1.75910885e-04, -1.38348211e-02,
       -1.37884263e-02, -1.48398522e-02, -1.07556703e-02,  1.77106708e-02,
        5.41982660e-03, -2.60665640e-02, -2.27910988e-02,  1.21742403e-02,
       -4.76688519e-03, -8.54807813e-03,  9.45667364e-03,  1.91573594e-02,
        6.08599838e-03, -1.66409649e-02, -1.41875818e-02,  3.33587117e-02,
       -1.90732535e-02,  1.67901013e-02, -1.40570188e-02,  1.90671775e-02,
       -3.23727890e-03, -7.34549947e-03,  2.02644542e-02,  5.44358860e-04,
        1.79390539e-04, -1.07822604e-02,  6.11597206e-03,  8.26099329e-03,
       -3.22007877e-03, -2.02611368e-02, -5.33162849e-03, -1.10146124e-02,
       -2.50229798e-03, -6.34520175e-03,  1.39016248e-02,  5.50160464e-03,
       -9.88068432e-03,  2.80918996e-03, -1.63613316e-02, -2.64670458e-02,
        2.59094592e-03,  2.54317857e-02, -1.61295626e-02, -7.14198640e-03,
       -1.07779978e-02,  1.98623277e-02, -1.67419128e-02, -1.58147439e-02,
        2.96088327e-02, -1.18696941e-02, -1.92481074e-02, -3.65094584e-03,
        1.37118287e-02,  2.77559496e-02,  1.72390994e-02, -8.29683803e-03,
       -1.20939706e-02, -1.78590883e-02, -1.62662379e-02, -2.36403407e-03,
        7.56790768e-03, -1.06470268e-02, -1.39958662e-04, -1.00777587e-02,
       -1.36894491e-02,  1.99466348e-02, -2.57626106e-03,  4.79388330e-03,
        7.26611167e-03, -2.69340053e-02, -2.98006157e-03,  1.77130904e-02,
       -7.79561186e-03,  1.50311855e-03, -9.83622391e-04,  3.12011670e-02,
       -1.26257660e-02, -1.35683762e-02, -7.89424405e-03,  9.44097701e-04,
        6.33613439e-03, -1.91995688e-02, -4.10945946e-03, -6.77931169e-03,
        1.72304874e-03,  6.01955317e-03, -1.37362303e-02, -5.98139071e-04,
        2.44333278e-02,  4.41126700e-04,  1.74396522e-02, -1.83222175e-03,
        1.83017943e-02, -1.92876451e-03,  2.38219555e-02,  2.91551501e-02,
       -5.50547149e-03, -9.16649681e-03, -5.23832301e-03, -1.94054609e-03,
        7.93969631e-03, -2.70455666e-02, -3.67567316e-02, -1.73028391e-02,
       -1.02251070e-02, -2.92602554e-02,  2.13932507e-02, -8.34294781e-03],
      dtype=float32), array([ 0.04477057,  0.04543735,  0.03397752, -0.03008767,  0.00033523,
        0.01616487,  0.01054419,  0.04202588,  0.01975264,  0.0072916 ,
       -0.01500878,  0.04514401,  0.00031153,  0.06982095, -0.00910997,
       -0.01132686,  0.04244003, -0.04088146,  0.0035889 ,  0.03889583,
        0.02210415,  0.04734813,  0.04346043,  0.03349932, -0.02444595,
       -0.02867733, -0.04233506, -0.02771752, -0.02477388, -0.03868599,
        0.0118555 ,  0.05802342, -0.02745724,  0.04488547, -0.02841317,
        0.03820683,  0.02865222,  0.05145779,  0.04396753, -0.0177488 ,
       -0.04872321,  0.03951413, -0.02575476,  0.00157991, -0.02314643,
        0.02073923, -0.03293701,  0.06712787,  0.04919176, -0.04925213,
        0.03183182, -0.00723332,  0.00072873,  0.0200355 ,  0.04571733,
       -0.0277881 ,  0.07423183,  0.041764  , -0.00047741,  0.0261812 ,
        0.01900613,  0.02426188,  0.04363211,  0.0166994 , -0.03458562,
        0.03655951,  0.03595384, -0.05943602, -0.03938   , -0.03850209,
       -0.01457838, -0.02380319, -0.02283507, -0.0159151 ,  0.030613  ,
        0.03014496, -0.03045953,  0.02657054,  0.0342657 ,  0.01325152,
        0.04329867,  0.03940428,  0.02977575,  0.03601162, -0.02082618,
        0.03317819,  0.00061619, -0.03134837, -0.02786928, -0.0068348 ,
        0.04173287,  0.03205639,  0.06175315, -0.03237088,  0.0243421 ,
       -0.04764562,  0.02082757, -0.05958166, -0.04761288, -0.02129795,
       -0.05111723, -0.00638484,  0.01512194,  0.03766435, -0.01953191,
        0.00887845,  0.05083913,  0.06778231,  0.01648709,  0.03033416,
       -0.03147421,  0.05660463,  0.0043951 ,  0.03121168,  0.05379671,
        0.02140216,  0.0298463 ,  0.08539002, -0.03328011, -0.01892191,
        0.02472134,  0.04855996,  0.00912285, -0.0477944 ,  0.04527791,
        0.01571256, -0.04949411, -0.04075995,  0.01677983,  0.04256605,
        0.03004346, -0.02142565, -0.01862217, -0.01736162, -0.00712222,
       -0.02579567, -0.02623975,  0.0662603 ,  0.01656589,  0.04281577,
        0.02152899,  0.04967647, -0.01682898, -0.01775124,  0.036043  ,
       -0.00210072,  0.01035516, -0.03733645,  0.04787535,  0.03209551,
        0.01909696,  0.02996704,  0.03965622,  0.05023488, -0.00673551,
       -0.03313056, -0.00406617,  0.0107345 ,  0.03582933, -0.02966695,
        0.01230859,  0.02031911,  0.04561423, -0.01519397,  0.0222957 ,
        0.0362732 ,  0.0099248 , -0.00252065,  0.04726012,  0.03490824,
       -0.01159094,  0.03221396, -0.02772763,  0.04510559,  0.0369654 ,
       -0.03307036, -0.03100665, -0.06833614,  0.02412938,  0.01207575,
        0.00728283,  0.06948774,  0.01646537,  0.02908447,  0.08952708,
       -0.05943243,  0.00708076, -0.0154724 ,  0.04042615,  0.0616967 ,
        0.04666427,  0.00588423, -0.0127178 , -0.00075428, -0.03287064,
        0.03287872, -0.02082509,  0.02993464,  0.04599518,  0.05281324,
        0.02128789, -0.01045925, -0.01183882,  0.04798534,  0.05013474,
        0.00265305, -0.01869884,  0.03529458, -0.05076844, -0.03716766,
        0.0027357 , -0.00237337, -0.02420245,  0.03241595, -0.00908586,
        0.03381555,  0.04498257,  0.03209829, -0.01842153,  0.04482721,
        0.02375384, -0.05060393,  0.03044532,  0.01641367, -0.02060642,
       -0.03485512,  0.00436002, -0.03236547,  0.02798647, -0.02980783,
       -0.04368439,  0.03539279,  0.02134705,  0.06305692,  0.04596046,
        0.01075836, -0.00042207, -0.02139611,  0.05240395, -0.02087076,
        0.01246817, -0.05850575,  0.01595462,  0.03415494, -0.02109463,
        0.0382039 , -0.01317968,  0.02497568,  0.00861232,  0.04922234,
        0.01857428, -0.02139258,  0.04547167,  0.01331914,  0.00495828,
        0.03857081, -0.04836946, -0.06450424,  0.0342266 , -0.00473749,
        0.01735345,  0.0327928 , -0.0464493 ,  0.0128834 ,  0.04475879,
       -0.0542409 , -0.03246974,  0.04229497,  0.0067774 ,  0.00924034,
       -0.04122334,  0.02039913, -0.03823657,  0.01899158,  0.0086196 ,
        0.03136287,  0.04827141,  0.07776503,  0.05375387,  0.02295761,
       -0.01522686,  0.00398324, -0.02271937,  0.02859001,  0.03919832,
        0.02168668, -0.01418302, -0.03425618, -0.01114606,  0.01783527,
        0.05522634, -0.04102424,  0.0328525 ,  0.05624127,  0.00363432,
        0.02664244,  0.03263253, -0.02724197,  0.03115527, -0.05154806,
        0.03439504,  0.00306495, -0.01972445,  0.05588481,  0.06032466,
        0.03009921, -0.03485747,  0.04107805, -0.00779655,  0.01741778,
       -0.06805853,  0.01312527, -0.03865477, -0.05304172, -0.04258256,
        0.02366904,  0.04364193,  0.03679122, -0.06000576,  0.02552894,
       -0.02356797, -0.04311163, -0.01959327,  0.00934269,  0.01085098,
       -0.00283395, -0.04635292,  0.07082886, -0.00725204,  0.01854464,
        0.06245814, -0.06292735,  0.02208059, -0.04617355,  0.04076704,
        0.01137702,  0.01629744,  0.03042113,  0.07003736,  0.05723492,
        0.02046116,  0.04898928, -0.01802775,  0.03119575, -0.03932321,
       -0.01353173,  0.03194936,  0.04264887, -0.05697681,  0.01273671,
        0.01457771, -0.04439972, -0.02294388, -0.03637076,  0.03854721,
        0.0637103 ,  0.00912266, -0.0032888 ,  0.0529386 , -0.05683322,
        0.03464281,  0.04945743, -0.00816763,  0.04944587, -0.02648515,
       -0.04803627,  0.03996877,  0.0634675 , -0.02229639, -0.02391395,
        0.01195989,  0.06259404, -0.04496877,  0.02866677,  0.04199655,
       -0.02053547, -0.023883  ,  0.06178275,  0.02709778,  0.03612475,
        0.02450956,  0.0246409 , -0.02381533,  0.01909133,  0.04695626,
       -0.02102814,  0.04981601,  0.06771346,  0.00298432,  0.03499087,
        0.03153311,  0.02120082,  0.03751935,  0.03700319, -0.01905641,
        0.04729401,  0.0288842 ,  0.01288365,  0.02492656, -0.02026877,
       -0.01370996,  0.01075882, -0.01279656, -0.03280416, -0.0051564 ,
       -0.0135377 , -0.02602837,  0.06084221,  0.003928  , -0.01073788,
        0.04922433,  0.03126196,  0.01480153,  0.04441328, -0.02121927,
       -0.01638522,  0.06479424,  0.0548113 , -0.01916124,  0.02607747,
       -0.0198802 ,  0.04866802,  0.04930789,  0.02861139,  0.02781707,
        0.0134211 ,  0.03984327,  0.02104215,  0.04353834,  0.03091091,
        0.0440635 ,  0.01031439, -0.01886985,  0.06973433, -0.03400692,
        0.04053621,  0.03397199, -0.01037098,  0.02800696,  0.01260859,
        0.00011528,  0.03615224,  0.05812291,  0.03433536,  0.00733627,
        0.01527037, -0.01467362,  0.01849165,  0.02733571,  0.05182887,
        0.01801471, -0.02002704,  0.00968192,  0.05387049, -0.0306339 ,
        0.05459566,  0.01689739,  0.01559529, -0.01598649, -0.01595986,
        0.02504905, -0.02398831, -0.02105215,  0.02679469,  0.05040675,
       -0.028663  , -0.03067839,  0.0497092 ,  0.05151713,  0.03403418,
        0.03241583,  0.03674586, -0.01499069,  0.05491867, -0.02648053,
       -0.02854053,  0.03679954, -0.03957352,  0.01618474, -0.04312776,
        0.01573225,  0.04230859,  0.00910477, -0.01747891, -0.03630806,
        0.03021912,  0.0157717 ,  0.02168884, -0.04009805, -0.00146037,
       -0.04247171,  0.02429418, -0.03799885, -0.01321857, -0.0343811 ,
        0.00920494, -0.02476298,  0.00113665,  0.01322831,  0.05997814,
        0.03179245, -0.01814831, -0.05349893,  0.04763032,  0.0156503 ,
       -0.03165693, -0.03954142, -0.0012341 ,  0.01291172,  0.02384124,
        0.00280265,  0.04700299, -0.02879533,  0.02315402, -0.03846698,
        0.01460618,  0.01900952,  0.03647707,  0.01924105,  0.02659691,
       -0.01884276,  0.02221809,  0.03093178, -0.02151294,  0.00485909,
        0.04660083,  0.02936805,  0.00748559,  0.02486481, -0.03660379,
       -0.02192806, -0.04555885,  0.06240225, -0.061428  , -0.00098013,
        0.01510403, -0.00176497,  0.03431933,  0.03534259,  0.01844211,
        0.02056187,  0.02326498, -0.0377497 , -0.01447221,  0.01806999,
       -0.00383903,  0.04084176, -0.02207977,  0.05102435, -0.05625336,
       -0.05661692,  0.04368731, -0.0345204 , -0.02624292, -0.02020932,
        0.03595017,  0.08181284,  0.02966332, -0.03384722,  0.03586688,
       -0.03254905, -0.05851036,  0.01974017, -0.04389706, -0.03464273,
        0.04704709, -0.04613633, -0.01862326, -0.02736201, -0.00260496,
       -0.01204446, -0.03667651,  0.03497088,  0.02963609,  0.02863861,
        0.03391166,  0.04718207,  0.02900173,  0.03028989,  0.03178922,
       -0.01801052, -0.03268456, -0.01909376, -0.021399  , -0.03288396,
        0.0321358 ,  0.03020522, -0.01366222,  0.00469847,  0.0628395 ,
       -0.02537343, -0.03006885,  0.04915788,  0.05217377, -0.0094354 ,
        0.00385747, -0.01317861,  0.01047436, -0.01468515, -0.00896883,
       -0.02223147, -0.00409007,  0.01443107, -0.01757748,  0.02505451,
        0.02813579,  0.07240871,  0.00451981,  0.03899877,  0.00356373,
        0.02594943, -0.0332078 ,  0.07071097, -0.04954049,  0.03724095,
        0.02866493,  0.02580957,  0.01117413, -0.02268609, -0.02405235,
       -0.03005924, -0.026759  ,  0.03273033, -0.01134166, -0.0088661 ,
        0.0067141 ,  0.05098802,  0.03085402,  0.02860864, -0.01871695,
       -0.04955133, -0.01483357,  0.04234729,  0.03139301, -0.01521744,
       -0.03094743,  0.00507288,  0.03434039,  0.0216798 , -0.01666313,
        0.00665177,  0.01934553, -0.04363534,  0.02937483, -0.01523717,
        0.02845988, -0.03998084, -0.01768502, -0.00965041, -0.04224487,
        0.02466082,  0.01760767, -0.03242408, -0.04630933,  0.00385027,
        0.03593478,  0.04996426, -0.00838958,  0.06273767,  0.03458373,
        0.02603144, -0.01857787, -0.00594231, -0.02516571,  0.04088908,
       -0.06489482, -0.01754089, -0.03068959, -0.06350986,  0.05275252,
       -0.04409685, -0.02477918,  0.02142874, -0.03329217,  0.00731691,
        0.01695061,  0.01924685,  0.05141667,  0.01615963, -0.03756796,
       -0.01197469,  0.01743677,  0.0401067 ,  0.00890699,  0.04219204,
        0.01314318, -0.01768453,  0.04502401,  0.02276614,  0.05445084,
        0.03136827, -0.05003676, -0.02443263, -0.06446794,  0.04153053,
       -0.01834078,  0.03397535,  0.00807334,  0.03941742,  0.05636854,
       -0.01120715,  0.03430736, -0.02992223, -0.03703947, -0.01997957,
       -0.02252461,  0.01407954,  0.00059821, -0.04508621,  0.02009685,
       -0.0409334 , -0.07076472,  0.04163576,  0.01913557,  0.02403211,
       -0.03259818,  0.05200399,  0.02137134,  0.03395838,  0.02238788,
       -0.00413668,  0.02446369,  0.07200955,  0.04191853,  0.02768726,
        0.08088867,  0.02488666,  0.0350469 ], dtype=float32), array([0.09533255, 0.10302339, 0.08634281, 0.08770201, 0.09041479,
       0.08897807, 0.08556262, 0.11143314, 0.08636024, 0.08936711,
       0.09118218, 0.0911108 , 0.0892264 , 0.12342077, 0.08778637,
       0.08520261, 0.12439508, 0.09139387, 0.09868108, 0.09707036,
       0.08454438, 0.09688419, 0.10348637, 0.09122378, 0.08732671,
       0.09936156, 0.09629268, 0.09468675, 0.14117198, 0.09811924,
       0.08496363, 0.10178666, 0.0953898 , 0.09298882, 0.09147093,
       0.0926052 , 0.09279629, 0.10613196, 0.09224524, 0.09176349,
       0.09161697, 0.09485447, 0.08970813, 0.08581984, 0.09289269,
       0.09395749, 0.09041523, 0.11148182, 0.09615771, 0.10238324,
       0.08634351, 0.08378691, 0.11392259, 0.0937785 , 0.09629905,
       0.08777954, 0.11989706, 0.09812505, 0.086346  , 0.08896644,
       0.09426871, 0.08688764, 0.09614994, 0.08601414, 0.08923126,
       0.10364182, 0.09435135, 0.09969072, 0.09731534, 0.08894922,
       0.08449713, 0.08382283, 0.08831376, 0.08934504, 0.10724933,
       0.09662871, 0.09072794, 0.09719053, 0.09888884, 0.08947738,
       0.11296093, 0.09448396, 0.09545682, 0.1209227 , 0.09222415,
       0.08617137, 0.08281564, 0.08825292, 0.0889746 , 0.08711159,
       0.09886032, 0.09187206, 0.10854228, 0.08983602, 0.09125961,
       0.10407108, 0.08424724, 0.09074729, 0.10029049, 0.08979596,
       0.09280328, 0.08571265, 0.08419783, 0.09515961, 0.0907155 ,
       0.086713  , 0.10459063, 0.10157747, 0.09319492, 0.09110488,
       0.08934886, 0.10809988, 0.08332151, 0.09317452, 0.09594344,
       0.08917269, 0.0947974 , 0.13592985, 0.10134839, 0.08556167,
       0.08826008, 0.09855662, 0.09272388, 0.09120579, 0.10101699,
       0.08819673, 0.1018393 , 0.08697139, 0.09062607, 0.09737635,
       0.09728003, 0.08712796, 0.08928091, 0.08692113, 0.08340688,
       0.08763281, 0.09484838, 0.11203326, 0.09114029, 0.09194507,
       0.09386482, 0.09120122, 0.09148815, 0.09101586, 0.09525034,
       0.10119735, 0.09290434, 0.09375061, 0.09545046, 0.08902317,
       0.08470281, 0.09162858, 0.09207018, 0.10926515, 0.08726575,
       0.0870863 , 0.09511365, 0.08812965, 0.11436614, 0.08850925,
       0.08938751, 0.08601268, 0.09229386, 0.08665623, 0.08864866,
       0.10509055, 0.09163872, 0.08451346, 0.10791519, 0.09350251,
       0.08840833, 0.10215718, 0.08553945, 0.11310773, 0.09742645,
       0.10130723, 0.08964781, 0.11408936, 0.08274487, 0.08770497,
       0.09392013, 0.10547251, 0.08832558, 0.09546403, 0.10379203,
       0.11779872, 0.0879857 , 0.09332652, 0.08829239, 0.1142421 ,
       0.09811792, 0.09511626, 0.08693403, 0.08290128, 0.09010051,
       0.08881531, 0.087559  , 0.09189517, 0.10549752, 0.10038683,
       0.08722182, 0.09004353, 0.0862345 , 0.09656539, 0.10491159,
       0.09943005, 0.09081888, 0.09643745, 0.10410155, 0.09503083,
       0.08325073, 0.08975312, 0.08508498, 0.09538092, 0.09140545,
       0.09264254, 0.09176445, 0.08951262, 0.09213762, 0.10065818,
       0.09154983, 0.09328533, 0.08930346, 0.08634358, 0.089023  ,
       0.08970334, 0.09080358, 0.10627072, 0.08898662, 0.08908699,
       0.09654592, 0.09400902, 0.09121533, 0.09494334, 0.09454896,
       0.09379383, 0.09191641, 0.08725102, 0.10546407, 0.0867158 ,
       0.09025913, 0.11185022, 0.0878334 , 0.08493146, 0.08825675,
       0.09688114, 0.08873495, 0.0916556 , 0.09104858, 0.09321598,
       0.09347187, 0.08342658, 0.10006444, 0.08640902, 0.08538417,
       0.09278381, 0.09762957, 0.1070307 , 0.09375266, 0.0876522 ,
       0.10023821, 0.09409405, 0.09815358, 0.09030476, 0.08987315,
       0.1019276 , 0.09105934, 0.09696624, 0.08429956, 0.09062754,
       0.09494594, 0.09812432, 0.08896384, 0.08454324, 0.09049641,
       0.08870748, 0.10343199, 0.13281305, 0.12355898, 0.09450223,
       0.09010561, 0.08438496, 0.08858669, 0.09287196, 0.09444806,
       0.09217303, 0.09091353, 0.09124248, 0.09201255, 0.09893057,
       0.08864599, 0.09120373, 0.09529808, 0.09701798, 0.09201449,
       0.09086759, 0.10297297, 0.0996856 , 0.08818338, 0.10518823,
       0.09459498, 0.08713782, 0.08877629, 0.09858835, 0.10408041,
       0.09339272, 0.12282968, 0.11686401, 0.0885439 , 0.08653077,
       0.13458188, 0.08371338, 0.0910515 , 0.09796447, 0.10108491,
       0.0884404 , 0.09457164, 0.08952238, 0.09480894, 0.09093118,
       0.08795745, 0.09103004, 0.0879931 , 0.0921457 , 0.09136254,
       0.09217768, 0.0985261 , 0.10942021, 0.09552509, 0.09108686,
       0.11012969, 0.0960585 , 0.08746835, 0.10654171, 0.10230859,
       0.08941955, 0.092297  , 0.09298723, 0.10112442, 0.10158606,
       0.08723148, 0.09719983, 0.08669171, 0.09528188, 0.09165759,
       0.08967529, 0.09462495, 0.09418789, 0.10269815, 0.09282903,
       0.08632596, 0.09433006, 0.09597971, 0.09056892, 0.08947421,
       0.1062936 , 0.09967808, 0.08213206, 0.10884271, 0.09376589,
       0.08819031, 0.10102609, 0.0876586 , 0.09804989, 0.08974822,
       0.09244616, 0.10062174, 0.10890049, 0.08926231, 0.09722878,
       0.09734521, 0.11896268, 0.09520387, 0.10526188, 0.0917604 ,
       0.09032573, 0.09113769, 0.09989143, 0.09102789, 0.0951812 ,
       0.09628228, 0.09354217, 0.0887505 , 0.08621153, 0.10950032,
       0.08943055, 0.10106821, 0.10742588, 0.08737817, 0.09548607,
       0.093229  , 0.08754724, 0.10914136, 0.11285794, 0.08739465,
       0.09443975, 0.08812404, 0.0904633 , 0.09525522, 0.10641257,
       0.08794517, 0.08673008, 0.0860955 , 0.0911644 , 0.09152886,
       0.08817588, 0.089265  , 0.1021003 , 0.08431369, 0.08656953,
       0.10410101, 0.08808951, 0.08804673, 0.09871539, 0.08600909,
       0.08917626, 0.1011279 , 0.09875333, 0.08877616, 0.09727063,
       0.08612827, 0.09656113, 0.09203105, 0.09419751, 0.10151827,
       0.0858758 , 0.09701368, 0.09235363, 0.09848528, 0.09555823,
       0.09443009, 0.08680498, 0.08744727, 0.11989748, 0.09185411,
       0.10576753, 0.0946226 , 0.0877746 , 0.09418347, 0.09014239,
       0.08500942, 0.10454423, 0.10273499, 0.09099396, 0.08712501,
       0.08355612, 0.08814418, 0.09566546, 0.09789816, 0.10345179,
       0.0961369 , 0.08447087, 0.08366299, 0.09788682, 0.10161126,
       0.0983768 , 0.0889983 , 0.09187423, 0.08804908, 0.08614986,
       0.10209938, 0.08646289, 0.09224807, 0.09734005, 0.1032918 ,
       0.08843333, 0.0853133 , 0.09983798, 0.1066241 , 0.09007622,
       0.08898576, 0.09190035, 0.08916599, 0.12038513, 0.09147779,
       0.09128685, 0.09215832, 0.09375901, 0.08765703, 0.09450353,
       0.08792865, 0.09845668, 0.08724698, 0.0864711 , 0.09262936,
       0.09666193, 0.08663762, 0.09397112, 0.10339417, 0.08922408,
       0.09572175, 0.08753288, 0.09887608, 0.08963899, 0.09088678,
       0.08624242, 0.09100213, 0.08855586, 0.09139009, 0.09672039,
       0.09746594, 0.08467647, 0.11060175, 0.10649382, 0.08978293,
       0.09304087, 0.08810184, 0.09797893, 0.08473133, 0.09578611,
       0.08507322, 0.09422176, 0.08844693, 0.08838052, 0.08957783,
       0.08881257, 0.09322467, 0.1019739 , 0.09062584, 0.09035473,
       0.09424974, 0.08680974, 0.09605848, 0.08999844, 0.09528487,
       0.09837919, 0.09388877, 0.08454757, 0.09578604, 0.09635177,
       0.08631454, 0.09399854, 0.10116328, 0.10414571, 0.08375759,
       0.09903569, 0.09218767, 0.09263222, 0.08758842, 0.09629429,
       0.08718456, 0.09645045, 0.08956696, 0.08587235, 0.09144413,
       0.09201673, 0.09173206, 0.09029158, 0.10309008, 0.12426554,
       0.11568084, 0.09777652, 0.09693334, 0.096577  , 0.08871894,
       0.10033085, 0.11442757, 0.09119703, 0.09548572, 0.09941399,
       0.08695179, 0.10289523, 0.08653765, 0.11430288, 0.09786987,
       0.10004313, 0.09408349, 0.08859031, 0.09038364, 0.09955392,
       0.08606636, 0.09094482, 0.0900037 , 0.08444973, 0.09194368,
       0.08885186, 0.10887328, 0.09026396, 0.10166147, 0.0949106 ,
       0.08469636, 0.09243228, 0.08966922, 0.0937531 , 0.10092857,
       0.09941167, 0.09674893, 0.08835753, 0.08870814, 0.10570672,
       0.08820067, 0.09368508, 0.1008928 , 0.09842976, 0.08691875,
       0.08884733, 0.09049102, 0.08817396, 0.09916805, 0.09304468,
       0.09383781, 0.08296423, 0.08906475, 0.08688808, 0.09333313,
       0.08584613, 0.11168188, 0.08252729, 0.09466708, 0.08977763,
       0.09137306, 0.09017125, 0.10666034, 0.09840846, 0.09399445,
       0.09911202, 0.08819281, 0.08784347, 0.09827808, 0.08785407,
       0.08730961, 0.08777461, 0.09837766, 0.08658662, 0.08665707,
       0.08725595, 0.09387749, 0.10434182, 0.08714797, 0.08815303,
       0.0962029 , 0.08914614, 0.08999366, 0.09162268, 0.08525107,
       0.09463471, 0.08399122, 0.09525006, 0.09152119, 0.08880778,
       0.09324484, 0.08801525, 0.10113329, 0.099462  , 0.09086205,
       0.10023815, 0.08751568, 0.08371061, 0.08463457, 0.08742155,
       0.08625877, 0.09674633, 0.08653799, 0.09577697, 0.09192597,
       0.09500206, 0.1000472 , 0.08542417, 0.0991831 , 0.0892342 ,
       0.09398793, 0.08899812, 0.08875687, 0.09161684, 0.09579973,
       0.10696465, 0.08771335, 0.08916849, 0.10597145, 0.09984527,
       0.10131526, 0.09070285, 0.10138903, 0.09452467, 0.08990395,
       0.08284012, 0.09780477, 0.09549839, 0.09651268, 0.08970848,
       0.08672243, 0.09260547, 0.09812947, 0.08562518, 0.09449986,
       0.08639729, 0.08745681, 0.08973953, 0.09848583, 0.1069276 ,
       0.10320313, 0.10182122, 0.09198786, 0.12516017, 0.09949511,
       0.08716187, 0.0971485 , 0.0850236 , 0.10207776, 0.09312529,
       0.08725841, 0.09422133, 0.08439895, 0.09151646, 0.09369533,
       0.09819558, 0.08685995, 0.08896514, 0.10065952, 0.09494314,
       0.0936877 , 0.09694751, 0.09918062, 0.08862457, 0.0867462 ,
       0.10213739, 0.10156391, 0.08279079, 0.09580651, 0.09308079,
       0.09022186, 0.09031279, 0.1094158 , 0.09224394, 0.0916565 ,
       0.13819483, 0.09564874, 0.09479985], dtype=float32), array([[[[ 0.03166637],
         [-0.04581026],
         [-0.02765445],
         ...,
         [ 0.01934763],
         [-0.0368128 ],
         [-0.05435834]],

        [[ 0.03345153],
         [-0.0474159 ],
         [ 0.00607955],
         ...,
         [-0.03171824],
         [-0.01924982],
         [-0.01761045]],

        [[-0.00660827],
         [-0.012747  ],
         [ 0.02112241],
         ...,
         [ 0.01537092],
         [-0.03290514],
         [ 0.00368679]]],


       [[[-0.00252879],
         [-0.01335622],
         [-0.03005792],
         ...,
         [-0.00121688],
         [-0.02348427],
         [-0.02252837]],

        [[-0.00900501],
         [-0.00052147],
         [-0.0217234 ],
         ...,
         [ 0.00831412],
         [-0.00757555],
         [-0.02159837]],

        [[ 0.03036412],
         [ 0.02755252],
         [ 0.02110644],
         ...,
         [ 0.01325648],
         [-0.02827829],
         [ 0.0004661 ]]],


       [[[ 0.00154104],
         [ 0.02068323],
         [ 0.01209219],
         ...,
         [ 0.014013  ],
         [-0.00950924],
         [-0.05430992]],

        [[ 0.01875138],
         [ 0.01338347],
         [ 0.01133932],
         ...,
         [ 0.02128829],
         [-0.05187207],
         [-0.02596445]],

        [[-0.01858327],
         [ 0.02224064],
         [-0.00547292],
         ...,
         [ 0.02252353],
         [-0.01078983],
         [ 0.00753233]]]], dtype=float32), array([[[[ 0.05650001,  0.00587859,  0.00380549, ...,  0.04548355,
          -0.03047789,  0.01878246],
         [-0.04107784,  0.04006289,  0.02284072, ...,  0.05685983,
          -0.00646681, -0.032273  ],
         [-0.03894119,  0.04403323, -0.01422957, ...,  0.0171308 ,
          -0.02714962,  0.01392329],
         ...,
         [ 0.0132509 ,  0.02221416, -0.07048153, ...,  0.01711523,
           0.0446225 ,  0.03568068],
         [-0.04939914,  0.02209122, -0.04387527, ..., -0.027705  ,
           0.04456541,  0.03616543],
         [ 0.05742537,  0.06671996, -0.03780635, ...,  0.06106774,
          -0.01712362,  0.0263823 ]]]], dtype=float32), array([0.993083  , 0.9935378 , 0.9859124 , 0.98846537, 0.9877911 ,
       0.99673104, 1.0110722 , 1.0071865 , 0.9964024 , 1.0109893 ,
       1.0139447 , 0.99186724, 0.98791414, 1.0206515 , 1.0090774 ,
       0.9912934 , 0.99007636, 0.9885161 , 1.0097133 , 1.0102901 ,
       1.0075843 , 0.9891799 , 0.9966528 , 0.98897445, 1.0114878 ,
       1.0274714 , 0.9899106 , 1.0037805 , 0.99678403, 0.9889621 ,
       0.99859977, 1.0045929 , 1.0006644 , 1.0041032 , 0.98812693,
       0.9848384 , 1.0077218 , 1.0091784 , 0.9915428 , 1.0151473 ,
       1.0068758 , 1.008515  , 0.9969506 , 0.99763334, 0.99731255,
       1.0223775 , 0.9881172 , 1.004043  , 1.0115653 , 0.9970563 ,
       1.0053092 , 0.9905097 , 0.98904204, 1.011429  , 0.9975919 ,
       0.98580956, 0.9891587 , 0.98533815, 0.99995446, 0.9938081 ,
       1.0134223 , 1.0184636 , 0.9917007 , 0.9946919 , 0.99372584,
       0.982953  , 0.98490703, 0.98577386, 0.9813645 , 0.9956156 ,
       1.0136073 , 1.0115637 , 1.0088882 , 0.9963084 , 0.98844486,
       1.0111134 , 1.0057669 , 1.0153769 , 1.0186297 , 1.0103201 ,
       0.9989441 , 0.9953546 , 1.00402   , 1.0183611 , 0.9889389 ,
       1.003889  , 1.0242367 , 0.9958858 , 1.0213202 , 0.9900599 ,
       0.99567467, 1.0116587 , 0.99265695, 1.0029445 , 0.99815047,
       1.0227451 , 0.9957302 , 0.99700475, 1.0032326 , 0.9904487 ,
       0.9966152 , 0.996314  , 1.026991  , 0.98723507, 0.9915243 ,
       0.99987227, 1.00611   , 1.0311818 , 0.98930466, 0.9908655 ,
       0.99965316, 1.006911  , 0.99070066, 0.9878842 , 1.005562  ,
       0.99568033, 0.9979393 , 1.0144438 , 1.0238434 , 1.0130935 ,
       1.01296   , 0.9970181 , 0.9948663 , 1.0025338 , 1.0058222 ,
       1.001274  , 0.99559397, 1.0026507 , 0.99470663, 1.0090649 ,
       0.9893477 , 0.9920277 , 0.99623185, 0.9932739 , 0.99702436,
       0.9944158 , 1.0136642 , 0.9916212 , 1.0270296 , 1.0067118 ,
       0.9948985 , 1.0100343 , 1.0061013 , 1.0052743 , 1.0103903 ,
       0.98787516, 1.0185374 , 0.98771995, 1.0043404 , 0.99549174,
       0.9954738 , 0.98288125, 1.001325  , 1.003102  , 1.0107185 ,
       1.0130069 , 0.99905664, 1.0056491 , 0.98806673, 0.99730474,
       0.99656504, 0.9861213 , 0.9891261 , 1.0292293 , 1.0176951 ,
       1.0025811 , 1.0179534 , 0.99798405, 1.0148177 , 0.9962735 ,
       1.0315337 , 0.9923382 , 0.9937365 , 0.9962052 , 1.0083528 ,
       0.9924885 , 1.007344  , 1.0212187 , 0.9966663 , 1.00682   ,
       0.9928417 , 1.0048022 , 1.0096681 , 0.9970673 , 1.0178955 ,
       0.99358195, 0.99962634, 1.0032218 , 0.99972385, 0.98087615,
       0.9905375 , 0.99701893, 0.99254745, 0.99085283, 1.0006164 ,
       0.98832655, 1.005224  , 0.9882751 , 0.9843862 , 0.9963834 ,
       0.99295944, 0.99670243, 1.0012479 , 0.9844034 , 1.0060904 ,
       1.0081888 , 1.0098196 , 1.0047168 , 0.9955594 , 1.0030409 ,
       0.99102163, 0.99078184, 0.9956913 , 1.0013456 , 1.0015916 ,
       1.0081793 , 1.0299149 , 0.98849404, 0.999517  , 0.99647754,
       0.99885607, 0.990787  , 0.98063123, 1.0259557 , 0.9875443 ,
       0.9919554 , 0.9825798 , 1.010648  , 1.0021058 , 1.003678  ,
       0.98650944, 0.9954196 , 0.9922007 , 1.0157254 , 1.0015364 ,
       1.0004195 , 0.99097794, 1.0049323 , 0.99125654, 0.9908009 ,
       0.99727684, 0.99798304, 0.99270934, 0.98221093, 0.9974964 ,
       0.994662  , 0.9995513 , 1.0224345 , 0.9823118 , 1.0137868 ,
       1.0004481 , 1.0133446 , 0.99245644, 0.98656297, 1.0060079 ,
       1.007511  , 1.0101547 , 1.02881   , 1.0088805 , 1.01481   ,
       0.99369663, 0.99377394, 0.98614097, 1.0083106 , 0.99905187,
       1.0012997 , 1.0106317 , 0.99710953, 1.0289553 , 0.9890032 ,
       1.0173948 , 0.9920115 , 1.0152079 , 0.9875014 , 0.99788904,
       0.9965105 , 0.97865874, 1.0161778 , 1.0043694 , 1.0250033 ,
       0.9976925 , 0.99147946, 0.9737539 , 1.0037096 , 1.0110275 ,
       0.9951775 , 0.99901086, 1.0047753 , 1.0073916 , 0.9903021 ,
       1.0081807 , 1.0146152 , 0.99731165, 0.9982661 , 1.0112782 ,
       0.9872636 , 0.99617743, 1.0041426 , 0.9987132 , 0.9990966 ,
       0.97880024, 1.0114641 , 0.9961992 , 0.9986737 , 1.0075935 ,
       0.9920151 , 1.0017171 , 0.992688  , 1.0106847 , 1.010196  ,
       0.99273664, 1.0132608 , 0.98117626, 1.0146549 , 1.0041784 ,
       1.0029832 , 0.9942645 , 1.0033674 , 0.992968  , 1.0159949 ,
       0.9930649 , 1.0195924 , 0.9860965 , 0.9902798 , 0.99269146,
       1.0039485 , 1.0031015 , 0.99983174, 1.0003763 , 0.99230754,
       0.98221356, 0.995704  , 1.0050026 , 1.0133489 , 1.0060706 ,
       0.99709284, 1.0140793 , 1.0153183 , 0.99597716, 1.0107884 ,
       0.9678081 , 1.0170835 , 0.9735298 , 1.0039393 , 1.0111554 ,
       0.99673235, 0.9994844 , 1.0020373 , 0.99686235, 1.0049446 ,
       1.0148194 , 1.0018961 , 1.0001858 , 1.0057248 , 0.98895514,
       0.98629004, 1.0092977 , 1.0127636 , 1.0436949 , 0.9968775 ,
       1.0014871 , 0.99308574, 0.99623   , 1.0009508 , 1.0106791 ,
       1.0102835 , 1.0097623 , 1.008985  , 0.98141795, 0.9948804 ,
       1.0131537 , 1.0108987 , 1.015755  , 0.9983424 , 0.9999672 ,
       1.001256  , 0.99157786, 0.99586594, 1.007153  , 0.98562735,
       1.0054632 , 0.98970026, 1.014623  , 1.019463  , 1.0053562 ,
       1.026259  , 0.9932137 , 0.9905765 , 0.99632293, 0.9913699 ,
       0.99575406, 1.0035405 , 1.0190034 , 0.9996607 , 1.0130765 ,
       1.0116495 , 1.0050714 , 1.0003471 , 0.9938767 , 0.9933883 ,
       0.99774575, 1.0021892 , 1.0025244 , 1.0168806 , 0.98787373,
       0.9963971 , 1.0066547 , 0.9993194 , 1.0124173 , 0.99170494,
       0.9908326 , 1.0055797 , 1.0052403 , 0.9876038 , 0.9942583 ,
       0.9950574 , 0.9924225 , 0.98768306, 1.0289813 , 1.0229194 ,
       0.9987283 , 1.0018011 , 1.020315  , 0.9944515 , 1.0140302 ,
       1.0023215 , 0.99999964, 1.0076106 , 1.0039437 , 0.9974858 ,
       0.98910385, 1.0000216 , 1.0094525 , 0.9926163 , 1.0090911 ,
       1.0146443 , 1.0142047 , 1.0276942 , 0.9859997 , 0.9876161 ,
       0.98786867, 0.99458295, 1.0089492 , 1.0086435 , 0.9884893 ,
       0.99206424, 0.99808806, 0.99180007, 1.0059563 , 1.0050275 ,
       0.9990481 , 1.0068005 , 1.0069968 , 0.99601364, 1.0060323 ,
       0.9904363 , 0.9942326 , 0.9938628 , 0.986052  , 1.0112958 ,
       1.007115  , 0.9941065 , 0.990669  , 0.9994415 , 0.9949089 ,
       1.0459417 , 1.0009834 , 1.0008057 , 0.9942871 , 1.0029063 ,
       0.99827117, 1.0068809 , 0.9844249 , 0.997415  , 1.0033292 ,
       0.9973485 , 1.0137484 , 0.9980166 , 1.0108159 , 0.9969582 ,
       1.0096463 , 1.0033675 , 0.9927109 , 1.0139928 , 0.9849314 ,
       1.0036284 , 1.0125686 , 0.989443  , 0.9844208 , 1.0003688 ,
       0.99508387, 0.9820622 , 1.0125437 , 1.001185  , 0.99388325,
       1.0018365 , 0.99314773, 0.99216646, 0.99546295, 1.0026313 ,
       0.99242485, 0.9980484 , 0.9948733 , 0.99694526, 1.0045322 ,
       0.99996674, 0.9918037 , 1.0133668 , 1.0199583 , 0.9849252 ,
       0.99688965, 1.0055408 , 0.99128133, 0.98389655, 1.0094621 ,
       0.9923433 , 0.9986064 , 1.0096458 , 0.99585056, 0.99794877,
       1.0000808 , 0.9930372 , 0.98239076, 0.99111074, 0.99770266,
       0.98508316, 0.99871016, 0.99466467, 0.9997637 , 1.018889  ,
       0.9995212 , 0.993505  , 0.99867713, 0.9938675 , 1.0008541 ,
       1.0280778 , 1.0128183 , 1.0039078 , 1.0039961 , 1.0107017 ,
       0.9825416 , 0.98965985, 1.0064461 , 1.0008041 , 1.0046793 ,
       0.9993083 , 1.0106591 , 0.9972624 , 0.98364216, 0.9891746 ,
       0.98375   , 0.9917597 , 0.9880839 , 0.9815242 , 1.000019  ,
       0.9985877 , 0.9927918 , 0.98163515, 1.0374104 , 0.9961792 ,
       1.0050509 , 1.017722  , 1.0107943 , 1.010353  , 0.9871476 ,
       0.98986703, 0.9997065 , 1.0157027 , 0.9894788 , 0.98792547,
       0.989068  , 0.997367  , 0.9966457 , 1.0021626 , 0.99887305,
       1.0286512 , 1.0077461 , 1.0062826 , 1.0111543 , 0.9979219 ,
       1.0038074 , 0.9954277 , 0.99537367, 0.98846716, 1.0049791 ,
       0.9922835 , 1.0152416 , 1.0141437 , 0.9879399 , 0.9989171 ,
       0.99279296, 1.0109022 , 0.9827157 , 1.0134064 , 0.9911768 ,
       0.99311304, 0.99611527, 1.0129551 , 0.9985538 , 1.001467  ,
       0.99092376, 1.0155677 , 0.9969773 , 0.97500455, 1.0093697 ,
       1.0111274 , 1.0097731 , 1.0036405 , 0.9891292 , 0.99826133,
       0.99842876, 0.9991462 , 0.9961039 , 1.0133275 , 1.0169122 ,
       0.9963391 , 1.0073179 , 1.0067269 , 0.9983996 , 1.0081211 ,
       1.0179894 , 1.0000232 , 0.98741436, 1.0137075 , 1.0043315 ,
       0.999031  , 0.9936783 , 0.99407613, 1.0028971 , 0.9963528 ,
       1.0056391 , 0.99876803, 1.0026938 , 1.0212053 , 0.99840415,
       0.989739  , 0.9872455 , 0.993798  , 0.9908517 , 1.003803  ,
       0.9991279 , 1.0015805 , 1.0031127 , 0.99907815, 1.0014518 ,
       0.9922502 , 0.99657017, 1.0136702 , 0.99814177, 1.0057992 ,
       1.0123647 , 1.0085945 , 0.99499154, 0.9981508 , 0.98859125,
       1.0055012 , 1.0149981 , 0.98570585, 1.0002309 , 0.98979944,
       1.0075989 , 1.0198586 , 0.9982109 , 0.9937489 , 1.0026495 ,
       1.0262706 , 0.98126173, 0.99093497, 0.99971473, 0.995923  ,
       0.9908119 , 0.99235916, 0.9897161 , 0.9873798 , 0.9952416 ,
       0.99701834, 1.006643  , 0.988818  , 1.0150334 , 0.9979024 ,
       0.98378414, 0.99345005, 0.9843551 , 0.98989403, 1.0080458 ,
       0.9809281 , 0.9855068 , 0.99219966, 0.9917006 , 0.9867191 ,
       0.98858625, 1.0114801 , 1.0033832 , 0.9817457 , 1.0086101 ,
       1.0090407 , 0.9945133 , 0.987829  , 0.99713063, 0.9937861 ,
       0.9855146 , 0.9933254 , 1.0165172 , 1.0030509 , 1.0079895 ,
       1.0126415 , 0.9951151 , 1.0150888 , 1.0060402 , 1.0070335 ,
       1.0000261 , 0.99004906, 1.0032808 , 0.99325174, 0.99282384,
       0.99725413, 0.9833538 , 1.0122352 , 1.0063823 , 0.9981969 ,
       0.98780376, 1.0016158 , 1.0041891 , 0.99878323, 0.9913527 ,
       0.99786925, 0.9920162 , 0.99412656], dtype=float32), array([-2.24866509e-03, -3.63799781e-02, -1.97987072e-03, -1.41345179e-02,
       -5.62095735e-03,  2.91584223e-03,  3.25414985e-02,  3.39089632e-02,
       -2.02016570e-02, -2.00071000e-03,  2.84211375e-02, -4.38488796e-02,
       -1.06396694e-02, -3.64125916e-03,  1.17658181e-02, -2.09290255e-03,
        1.06747588e-02, -2.67163701e-02,  1.44044086e-02,  6.83668361e-04,
        1.35379387e-02, -2.40724385e-02, -1.57979876e-02, -1.33008566e-02,
       -2.31761411e-02,  3.69612686e-02, -8.47922731e-03,  1.38047698e-03,
        2.54817051e-03, -1.44592030e-02, -8.61057732e-03,  1.36317322e-02,
        1.46862091e-02,  9.40789375e-03, -2.50969008e-02, -1.52694080e-02,
        1.03318635e-02, -1.85705873e-03, -1.50499353e-02,  2.52143070e-02,
        2.08121049e-03, -2.84477565e-02, -8.68058763e-03, -1.27596501e-03,
       -1.52408620e-02,  4.76445183e-02, -9.49895289e-03,  2.08529178e-02,
        3.41152539e-03,  6.56379736e-04,  6.48851693e-03, -4.98614460e-03,
       -9.55851865e-04,  2.38073580e-02, -4.10039630e-03, -9.10249911e-03,
       -5.80573501e-03,  9.12561431e-04,  3.54089728e-03, -1.13303168e-02,
       -1.83352549e-02, -1.34182833e-02,  2.52348254e-04, -3.23589891e-03,
       -1.14072552e-02, -1.18649295e-02, -1.73585825e-02, -2.00227201e-02,
       -9.54018440e-03,  2.64709834e-02,  2.73724291e-02, -3.48084047e-02,
       -1.10322656e-02, -2.89183110e-03, -1.59979588e-03,  1.11890454e-02,
       -1.23623926e-02,  1.63569171e-02, -6.48476463e-03,  2.79390160e-03,
        1.31067075e-02, -2.33464539e-02, -4.51567173e-02,  1.71567630e-02,
       -1.43084805e-02,  4.89055784e-03,  4.56863921e-03, -1.18969241e-02,
        3.77361923e-02, -9.31662414e-03,  3.61178565e-04, -9.71548376e-04,
        2.85985065e-03,  1.12105347e-02,  8.87443137e-04,  1.76638421e-02,
        1.57830864e-02, -3.53906234e-03, -6.50808262e-03, -2.71599423e-02,
       -2.18841434e-02, -3.70531366e-03,  4.27386463e-02, -6.73723267e-03,
       -1.24449525e-02,  3.53914290e-03,  8.52359366e-03, -4.91443500e-02,
       -1.73315722e-02, -4.72772913e-03, -1.70382559e-02, -2.33491734e-02,
       -3.29549611e-03, -7.66932499e-03, -4.47880514e-02,  8.64511169e-03,
       -2.82876194e-03,  3.44034024e-02,  2.72557866e-02, -2.51927376e-02,
        4.25049625e-02,  1.84129197e-02, -4.03689267e-03, -1.79956518e-02,
        2.02848786e-03, -3.55277304e-03, -1.95100135e-03, -2.00580014e-03,
        6.09133951e-03,  2.17935760e-02, -2.15635858e-02,  1.04176821e-02,
       -5.32985292e-03, -8.60552862e-03, -1.36417374e-02, -1.46656428e-02,
        2.87805665e-02, -4.51875851e-02,  2.45978255e-02, -1.72998698e-05,
       -1.66696496e-03,  2.96685006e-02,  1.37255713e-02,  1.62056945e-02,
       -3.61343240e-03, -8.64477537e-04,  2.78583691e-02, -8.43177736e-03,
        1.09434677e-02,  4.72115993e-04, -6.85388595e-03, -3.33411363e-03,
       -1.09969340e-02, -1.04538454e-02,  4.01261728e-04,  2.19863635e-02,
       -2.02626716e-02, -2.21097954e-02, -7.74235604e-03, -2.21948634e-04,
       -4.03015083e-03, -1.13813104e-02, -8.78397841e-03,  5.00736423e-02,
        2.77196225e-02,  8.83986987e-03, -2.75821276e-02, -2.82048900e-02,
       -2.35753693e-02, -2.85655912e-02,  2.79160347e-02,  2.20398717e-02,
        4.89373552e-03,  1.44740078e-03, -3.07663046e-02, -2.72887945e-02,
       -6.12214394e-03,  1.08122351e-02,  4.32282407e-03,  9.39262100e-03,
        6.04176428e-04,  1.34409275e-02, -2.45482624e-02, -4.93335770e-04,
        3.39275599e-02, -1.47255668e-02,  1.25832446e-02, -1.46429392e-03,
       -2.77226209e-04, -1.13391597e-02, -7.76481768e-03, -3.69233638e-03,
        6.79887366e-03, -6.72955113e-03, -6.66440278e-03,  7.61457346e-03,
        2.23214389e-03, -1.21263331e-02, -1.40330363e-02, -5.67568373e-03,
       -7.95697048e-03,  3.03739845e-03,  3.73951066e-03,  2.70359684e-03,
       -9.40608699e-03,  5.58586908e-04, -3.40321735e-02, -3.55513506e-02,
       -2.73912819e-03, -3.00796865e-03, -1.90207697e-02, -9.93227307e-03,
       -4.31791833e-03,  1.17951613e-02, -8.71843565e-03,  3.16644683e-02,
        4.18553203e-02, -1.14739100e-02,  1.33950263e-02, -6.67696539e-03,
       -2.29591671e-02, -1.31884497e-02, -8.29301216e-03, -3.14611606e-02,
       -1.29304044e-02, -7.54277082e-03, -4.30757320e-03, -2.94218231e-02,
       -1.93452872e-02, -1.06920500e-03, -1.50453867e-02,  2.13985122e-03,
       -2.79650316e-02, -3.47202420e-02,  1.03416611e-02, -3.17111947e-02,
       -4.85314056e-03, -2.10129679e-03, -3.72556760e-03, -1.18392473e-02,
       -3.49404551e-02, -1.18973600e-02,  1.30689074e-03, -2.08702218e-03,
        2.70049251e-03, -2.94852573e-02,  4.42112191e-03,  3.74641158e-02,
       -6.03949931e-03, -1.35211814e-02, -4.30684686e-02,  1.46142850e-02,
       -4.70234128e-03, -1.84255820e-02,  1.02896523e-03,  8.90923850e-03,
       -2.43999865e-02,  3.15562189e-02,  4.00856696e-03,  5.94689744e-03,
       -2.18951376e-03, -7.92424940e-03, -7.05742044e-03, -1.08057735e-02,
       -2.81622410e-02,  1.91232818e-03, -1.56179015e-02, -3.57668428e-03,
        2.84294281e-02,  2.66902777e-03,  3.21344957e-02, -3.49046942e-03,
       -2.92210467e-03,  2.94932892e-04, -1.98451318e-02, -1.29095756e-03,
       -8.90655722e-03,  3.00458707e-02,  4.00662608e-03,  1.70227922e-02,
        5.13377273e-03,  9.65064671e-03, -1.06031122e-02,  1.44185219e-02,
        2.75665108e-04, -5.46510611e-03, -4.01838869e-02, -2.67237239e-02,
       -8.68969783e-03, -2.54750829e-02, -3.79750468e-02, -2.81665660e-03,
       -7.10736902e-04, -7.07785599e-03,  1.09798340e-02, -2.44365074e-02,
        6.76051481e-04, -3.07017956e-02,  3.79818212e-03,  5.05298423e-03,
       -2.31424253e-02,  1.43192727e-02,  2.45126337e-03, -1.23767788e-02,
        1.10431099e-02, -1.04702897e-02, -2.65240837e-02,  1.13863102e-03,
        1.34339035e-02,  9.73409601e-03, -1.94102840e-03,  3.62726673e-03,
       -3.68318148e-02, -2.37123109e-03,  4.46893321e-03, -6.00180812e-02,
       -1.42424311e-02,  7.55163562e-03,  1.39895976e-02, -1.14835496e-03,
       -2.24075885e-03,  3.96446623e-02, -2.24997420e-02, -3.97964055e-03,
       -6.50240155e-03,  5.12021128e-03,  2.61258557e-02, -8.34029727e-03,
        1.98088330e-03, -3.81984469e-03, -1.63034629e-02, -5.34595456e-03,
        4.38490696e-03, -1.93241145e-02,  3.06690875e-02, -2.75883963e-03,
        3.99557762e-02,  1.41285397e-02, -3.40412813e-03,  1.15854871e-02,
       -1.77176278e-02, -7.52881961e-03, -2.70412285e-02,  2.45126672e-02,
        1.63570605e-02,  1.11739356e-02, -2.57779676e-02, -3.93784866e-02,
        2.31295312e-03, -6.32677302e-02, -4.08090465e-02, -8.61708634e-03,
        4.04655817e-04,  6.80832239e-03, -1.90290175e-02, -5.70970308e-03,
        1.62346102e-02,  2.15614270e-02,  4.84326333e-02, -9.59561858e-03,
        1.97414169e-03, -4.82865516e-03,  8.90862569e-03, -5.54234302e-03,
        1.27848368e-02,  1.62590714e-03,  3.25654298e-02,  1.23716500e-02,
       -2.23869141e-02, -5.78558166e-03,  1.48978857e-02,  2.30663065e-02,
        3.45453806e-02, -2.79839411e-02,  9.49593913e-03, -6.69593317e-03,
       -1.09989578e-02,  7.74434581e-03,  2.04000026e-02, -7.23505300e-03,
        1.16310278e-02, -8.62931460e-02, -3.38143557e-02,  2.22354829e-02,
        5.56730619e-03,  3.49077955e-02, -1.12001775e-02,  1.41186276e-02,
       -6.01023342e-03,  1.16650434e-02, -1.66317192e-03, -3.60745797e-03,
        5.31228899e-04, -1.66123244e-03,  1.19876321e-02,  2.73542665e-02,
       -1.07135018e-02, -1.31544909e-02, -2.98215402e-03, -1.81919318e-02,
        4.71508224e-03,  6.24663755e-03,  1.05238613e-02, -3.90961990e-02,
       -4.16745283e-02, -3.26205348e-03,  1.95677355e-02, -1.81460520e-03,
        2.77747139e-02, -1.25686722e-02,  6.08299207e-03,  5.19637438e-03,
        1.56453438e-02, -1.21330833e-02, -1.26912072e-02, -2.91041359e-02,
       -1.70322368e-03, -1.65770911e-02,  5.54863736e-02,  3.38864736e-02,
        2.90319528e-02,  1.86629184e-02,  3.50880958e-02, -3.52576445e-03,
        3.45661715e-02,  1.27559965e-02,  9.17398278e-03,  1.36624733e-02,
       -3.00042704e-02, -9.59123368e-04, -1.80604961e-02, -2.09745541e-02,
        3.49871777e-02, -2.05277056e-02, -2.72749886e-02,  3.81313562e-02,
        1.26663446e-02,  4.43134904e-02, -4.44648176e-04, -8.17017723e-03,
       -2.52938177e-02,  1.73126056e-04,  1.49072418e-02,  1.41655756e-02,
       -9.73680429e-03, -1.41909684e-03,  7.22746889e-04, -1.92532204e-02,
       -2.73363218e-02, -7.44310906e-04, -5.92341879e-03,  5.52894222e-03,
        1.03701204e-02, -5.78250503e-03,  9.54612345e-03, -7.71305477e-03,
       -3.57590010e-03, -3.06281517e-03, -2.17921846e-02, -7.17424648e-03,
        1.62018221e-02, -2.38356763e-03, -1.86929330e-02, -1.35593889e-02,
       -3.68179101e-03,  7.05443546e-02, -4.18797415e-03,  3.11949378e-04,
        9.05003492e-03,  1.80313792e-02, -2.67774495e-03,  2.26641111e-02,
       -4.03689966e-02, -9.54994559e-03,  1.43649355e-02,  5.03619434e-03,
       -3.04642273e-03, -9.58775356e-03,  2.27731671e-02,  1.73838018e-03,
        2.64893798e-03, -2.61973329e-02, -1.06317131e-02, -8.83422419e-03,
       -2.13530120e-02, -1.71651077e-02,  4.55393782e-03,  4.61588195e-03,
       -1.75197665e-02,  3.97684332e-03, -1.57259346e-04, -4.48363693e-03,
        8.72609485e-03,  4.09994368e-03, -1.30767552e-02, -2.16038749e-02,
       -8.87458562e-04, -1.13290912e-02,  8.39795358e-03, -5.48819778e-03,
       -8.21053796e-03,  1.52678657e-02, -6.10923115e-03, -6.54828623e-02,
        1.09962691e-02,  1.79412030e-03, -8.71214084e-03,  9.41290613e-03,
        3.45354006e-02, -8.91518686e-03, -1.27480766e-02,  6.16500759e-03,
       -4.22116835e-03, -6.73982408e-03,  1.49134807e-02,  1.34588778e-02,
        2.16677226e-02,  1.88375395e-02, -2.00688113e-02, -8.84852652e-03,
       -6.47975598e-03,  2.10119877e-02, -2.58153938e-02, -6.92578265e-03,
       -2.46753567e-03, -3.98355573e-02, -2.11090464e-02,  1.37659698e-03,
       -1.45824812e-02,  3.92118888e-03, -1.56170968e-03, -2.03384440e-02,
       -1.73032749e-02, -2.86588594e-02, -1.07281469e-03,  1.13900127e-02,
        2.47197859e-02,  2.12899363e-03, -3.02649802e-03,  2.36018691e-02,
       -9.39772930e-03, -6.68124622e-03, -4.31834683e-02,  4.50501917e-03,
       -1.35473432e-02, -4.24491093e-02,  5.88142453e-03, -1.56054478e-02,
       -1.15356194e-02, -2.20051818e-02, -2.01751832e-02, -5.27810364e-04,
        1.44272791e-02, -8.78833700e-03,  1.88858889e-03, -2.69780438e-02,
        9.48150083e-03, -3.54215801e-02,  4.61835377e-02,  9.20211431e-03,
        1.02004390e-02,  1.33195240e-02,  2.58001368e-02, -4.37111640e-03,
       -1.20340455e-02, -1.08726425e-02, -8.22100090e-04,  9.60853696e-03,
       -4.55344701e-03, -1.41749894e-02,  5.15962718e-03, -9.94666852e-03,
       -5.86106889e-02, -9.42542509e-04,  4.41716006e-03,  3.32164429e-02,
        2.41392888e-02,  1.45618329e-02,  3.08076125e-02, -3.54506485e-02,
       -1.48023535e-02, -2.52053863e-03, -4.73529845e-03, -9.26499814e-03,
       -1.99187733e-02, -8.61537270e-03,  6.89782156e-03, -6.25359938e-02,
        9.16159060e-03, -2.46648807e-02, -7.87407998e-03,  2.66444776e-02,
       -1.58573203e-02,  2.04211958e-02, -4.90923002e-02, -6.06871583e-03,
        1.79439653e-02,  1.21223321e-02,  7.24988943e-03, -1.53855968e-03,
       -6.02724450e-03, -1.45471608e-02,  3.51227680e-03, -1.01174973e-02,
        1.05922371e-02, -5.57620898e-02,  1.58081446e-02, -5.32249222e-03,
       -8.22665170e-03, -9.90605727e-03, -2.82008201e-02, -1.27013270e-02,
        1.60132244e-04,  5.79600339e-04,  2.08889898e-02,  1.49494242e-02,
       -1.94880762e-04, -7.92047754e-03,  9.68559366e-03, -3.94820143e-03,
       -1.68495644e-02,  2.75330123e-04, -2.40406673e-02, -2.34512798e-03,
        6.95566274e-03, -2.90982635e-03,  1.22983158e-02, -1.19827837e-02,
       -2.05352088e-03, -1.14080543e-02,  2.90025752e-02, -1.53992968e-02,
       -3.69387642e-02,  3.59539017e-02,  2.41392595e-03, -2.79503246e-03,
       -8.72276537e-03,  4.73548518e-03, -1.02765672e-02, -6.15343032e-03,
        2.82183941e-03,  8.20736215e-03,  1.26298601e-02, -3.04215346e-02,
       -1.34451641e-02, -8.35301913e-03, -1.49206370e-02,  3.44619807e-03,
        1.90187208e-02,  4.59608994e-03,  3.85783752e-03,  2.37647146e-02,
       -2.30664313e-02,  5.80016989e-04, -3.70319970e-02,  6.32163743e-03,
       -5.48112579e-03, -1.64205208e-02,  7.30021438e-03, -3.41518386e-03,
        6.54549943e-03,  2.40284000e-02, -1.29543887e-02, -4.94756037e-03,
        7.31247431e-03,  3.30251008e-02, -3.36545077e-03,  2.15081242e-03,
       -1.64041054e-02, -6.21672533e-03, -1.10586837e-03, -5.91601897e-03,
       -5.57208322e-02, -5.99556752e-02, -5.74771920e-03,  6.87821489e-03,
        1.89023744e-02, -1.05817234e-02, -1.70919336e-02, -9.65815783e-03,
        1.38376793e-02, -2.07051937e-03, -1.22002224e-02, -1.55503843e-02,
        1.84492562e-02, -9.01876669e-03, -7.23250723e-03, -2.28777174e-02,
       -9.77340713e-03,  2.60345032e-03, -4.55321558e-03,  6.12707902e-03,
       -2.81594433e-02, -6.36881776e-03,  1.36373714e-02,  1.54720945e-02,
       -3.86645622e-03, -1.28752179e-03,  2.05961913e-02,  3.38595593e-03,
       -2.21376847e-02, -1.19496370e-04, -3.47347446e-02,  1.29946033e-02,
        1.39949890e-02,  1.86160188e-02, -6.23748871e-03, -3.38938856e-03,
        5.68167353e-03,  1.70793477e-02, -6.49395771e-03, -3.08407727e-03,
       -1.97568405e-02, -7.04057002e-03,  1.42885838e-02, -2.08026599e-02,
       -9.42113809e-03,  1.29944552e-02,  1.87118743e-02, -2.26587411e-02,
       -3.09903305e-02,  4.58387018e-04, -1.20247062e-02, -2.63226032e-03,
       -8.52757506e-03,  2.87171663e-03, -6.58187876e-03, -6.74154330e-03],
      dtype=float32), array([-0.03132548,  0.08587264, -0.03293821,  0.10460596,  0.02304856,
       -0.08910032, -0.00368783, -0.1571446 ,  0.13412648,  0.17820363,
       -0.06980145,  0.15269515, -0.04083091,  0.02659072, -0.13278128,
        0.0615842 , -0.11944529,  0.13309966, -0.088903  ,  0.05808201,
       -0.14273006, -0.0896119 ,  0.0851685 ,  0.00695174,  0.15005115,
       -0.07913421, -0.02185488,  0.12863183,  0.04011513,  0.08095469,
        0.11504013, -0.09751999, -0.06384307, -0.10979478, -0.00230573,
        0.09144507, -0.08431933,  0.10566532,  0.14182587, -0.04825641,
       -0.256171  ,  0.2281276 ,  0.08208746, -0.13133028,  0.13922971,
        0.0246458 , -0.06008168, -0.12931648, -0.01886113,  0.07154707,
       -0.02932147, -0.04181702, -0.03243979, -0.04086448,  0.11755097,
       -0.00280876,  0.09559503, -0.03890819, -0.07172826,  0.15496136,
        0.21308964,  0.21969803, -0.04498527, -0.11069428,  0.1595216 ,
       -0.04609026,  0.18738882, -0.14281894,  0.10295789,  0.00671039,
       -0.15209983,  0.14236943, -0.03367763, -0.02838968, -0.04858645,
       -0.02449721,  0.29100105,  0.15403654,  0.13491556, -0.01321804,
       -0.03012029, -0.00388871,  0.12782815, -0.04879303,  0.09187698,
       -0.03931844,  0.10124559, -0.05059048, -0.09182303,  0.07855158,
       -0.09300078, -0.00379703,  0.0614447 , -0.10267451, -0.13840161,
       -0.11088944,  0.03114218,  0.02336966,  0.13618569,  0.1783421 ,
        0.20371418,  0.02948155, -0.14141072, -0.00071583, -0.11355847,
        0.0620282 , -0.09366037,  0.13498734, -0.04352445,  0.0959625 ,
        0.22974348,  0.20755814, -0.11131974, -0.24794166,  0.23872884,
        0.04649265, -0.03388647, -0.16530664, -0.01111341,  0.13116376,
       -0.14973356, -0.06232594,  0.08936252,  0.08075537, -0.06416338,
        0.10835076,  0.02255335,  0.17757876,  0.01645131, -0.07850141,
        0.18444121, -0.0004295 ,  0.12079905, -0.06807903,  0.25970975,
        0.20586099, -0.15204753,  0.19654877,  0.08583508,  0.0946267 ,
       -0.06852459, -0.06150137, -0.1087474 , -0.14431162,  0.02370205,
       -0.0938361 , -0.22679137, -0.12192985, -0.03314611, -0.21928404,
       -0.002073  ,  0.08024782,  0.16242486,  0.13908452,  0.07736031,
        0.00604329,  0.06376731,  0.14276862,  0.106798  ,  0.07319396,
        0.0180023 ,  0.03741195, -0.18135601, -0.05564193, -0.05577506,
       -0.05500137,  0.24837796,  0.3002116 ,  0.17602707,  0.24019226,
       -0.02052801, -0.08537172, -0.0471439 , -0.07013289,  0.17212793,
        0.19418861,  0.17188086,  0.15839493, -0.07929385,  0.00253583,
        0.02351078, -0.04259333,  0.30422914, -0.00558946, -0.12063099,
        0.15809473, -0.07980878,  0.05872745,  0.03839136,  0.0620862 ,
       -0.02739092,  0.15624438, -0.11386961,  0.13925928,  0.11957239,
        0.05039505, -0.04278135,  0.1926526 , -0.11564855, -0.12374791,
       -0.00391572, -0.03365692,  0.06845533,  0.00841193,  0.07533154,
        0.2252016 ,  0.10426518,  0.27719247, -0.01257977,  0.09721314,
        0.14542343,  0.11140347, -0.02209159, -0.07719066,  0.06966576,
       -0.12414017, -0.06899559, -0.0878824 , -0.11861226,  0.02308623,
        0.1656008 , -0.19424382, -0.11996498,  0.23656002, -0.02264445,
       -0.07767185, -0.01323912,  0.09673715,  0.11114594,  0.01351814,
        0.0755413 , -0.16199765,  0.13963641,  0.16653185, -0.08335415,
        0.26696023, -0.099604  ,  0.04327463,  0.15467036,  0.10933045,
        0.2717728 , -0.15455227, -0.09338683, -0.11019523, -0.1675772 ,
        0.11821335, -0.07248455, -0.19547796,  0.05536756,  0.10938912,
        0.23494461,  0.03553149, -0.17489989,  0.05376876,  0.07235   ,
       -0.01344436,  0.12914295, -0.07386679,  0.11335574, -0.16202807,
       -0.10000009, -0.05880458,  0.04839967, -0.01395319,  0.23993002,
       -0.07678808,  0.11476275, -0.1295552 , -0.02504613, -0.05558332,
       -0.08479249, -0.03827914, -0.06685722,  0.09313128, -0.21064772,
        0.0704376 , -0.00424218, -0.14916731,  0.13614938,  0.1171967 ,
       -0.12122086, -0.08928367,  0.11339691, -0.0580716 ,  0.05857057,
       -0.05828507, -0.27350256,  0.14936401,  0.25902113,  0.02198659,
        0.22095582,  0.01401952,  0.0405164 , -0.11736117, -0.01267726,
        0.04596217, -0.23599124,  0.28358185, -0.13918601, -0.20096233,
        0.1221276 ,  0.13269663, -0.04336584, -0.08406619, -0.08698442,
       -0.09935719,  0.22760168, -0.02984082,  0.05641596, -0.08704948,
        0.05787363,  0.04692913,  0.10856602, -0.09360312, -0.1045618 ,
        0.24784519, -0.01992801, -0.00112425, -0.20682818,  0.21909234,
       -0.13804588, -0.09797771,  0.24523084, -0.03644304, -0.02478795,
       -0.14030655, -0.14693809, -0.06629296, -0.01584398,  0.07342196,
        0.13485251, -0.02192907,  0.01147502,  0.18772735, -0.11070722,
       -0.08191568, -0.13368052,  0.04669933, -0.15210083, -0.04507751,
        0.08277667,  0.04123706,  0.20940986, -0.10716006, -0.11210854,
       -0.05695396,  0.26429096,  0.18172982, -0.06108414,  0.1845451 ,
        0.24130565,  0.05047404,  0.00930226, -0.08769355,  0.0727395 ,
       -0.03658229, -0.11433036, -0.1767754 , -0.13437721,  0.16825628,
       -0.04869984, -0.1405301 , -0.06270318,  0.04735702, -0.05059496,
        0.08448759, -0.10002407,  0.04481852,  0.11963601, -0.12567331,
       -0.06053047, -0.11773448, -0.07088273,  0.20044456, -0.08985846,
        0.09351579,  0.08901209,  0.0613178 , -0.09792074,  0.02903988,
       -0.10008492,  0.32919767,  0.310199  , -0.11195002,  0.03587955,
       -0.12336572,  0.02980771, -0.16259609, -0.13394359, -0.10088482,
        0.02207059,  0.02442753,  0.1107682 , -0.10508928, -0.08360586,
       -0.04650126,  0.2403228 ,  0.14971992, -0.09203578,  0.15743501,
        0.0902674 ,  0.09031858,  0.07029768,  0.19238782,  0.21593173,
       -0.16340338,  0.05561821,  0.12733671, -0.11666552,  0.07535787,
        0.11603649,  0.06923199,  0.00201147,  0.08771949, -0.06316923,
        0.278403  , -0.15681288, -0.15822195, -0.05608404, -0.15643027,
       -0.06468841, -0.07067616, -0.06529938,  0.07110469, -0.0045412 ,
        0.00243909, -0.0961919 , -0.08779962,  0.20426667, -0.10022981,
        0.04743871,  0.16342287, -0.04909258,  0.18061626,  0.11977052,
       -0.10139271, -0.00409068, -0.00936301,  0.06760256,  0.02816476,
        0.16562581, -0.04495291, -0.06499876, -0.00854224, -0.1065318 ,
       -0.11961747, -0.17808847,  0.22563803,  0.19007403,  0.14325327,
        0.1356575 , -0.11155184, -0.158389  , -0.05165086, -0.0978042 ,
       -0.1578331 , -0.12150244, -0.14632316,  0.08902575,  0.13684162,
        0.01531055, -0.08560449,  0.08053557,  0.09709577,  0.04577592,
       -0.10768081,  0.06790128,  0.05877886, -0.00612349, -0.01981956,
       -0.0357354 , -0.1044292 ,  0.11289591,  0.11274987,  0.02443172,
       -0.01530295, -0.03901016,  0.09681134, -0.19615832, -0.08013523,
        0.09903041,  0.22691642, -0.08368477,  0.08526348,  0.05417557,
        0.08553219,  0.1039054 , -0.04644967,  0.14308923, -0.00398926,
       -0.05709468,  0.03228877, -0.03025881, -0.00496151,  0.13488056,
       -0.02354511,  0.03837585, -0.10841887, -0.08380346, -0.01728763,
        0.12429654, -0.04179843, -0.05454901,  0.20750715, -0.10246563,
       -0.04902626, -0.15595146,  0.04301175, -0.08736105, -0.03148252,
        0.13694263,  0.08449034,  0.05841099,  0.10112412, -0.18718508,
       -0.15035747, -0.09460863, -0.0494416 ,  0.1139146 ,  0.03451144,
        0.1438584 , -0.00524285, -0.04659426, -0.15061074, -0.05895857,
        0.11762815, -0.07524151,  0.11070232,  0.14832866,  0.15669535,
       -0.11489321,  0.15509264, -0.0560026 ,  0.11711168,  0.08139881,
       -0.02888132,  0.11504711, -0.01928354, -0.08431243, -0.03212973,
        0.02619925, -0.08803488,  0.22443171,  0.0784437 ,  0.10731063,
        0.15056507, -0.19978015,  0.01678226, -0.047276  , -0.28827274,
        0.03416967, -0.04555258, -0.15347002,  0.02387262,  0.00133291,
       -0.20133436, -0.0769041 ,  0.22162117, -0.1372068 , -0.14236768,
       -0.12794317, -0.01252222, -0.13366792, -0.2533822 , -0.05014184,
       -0.0365815 , -0.21253683,  0.09232111, -0.11572883, -0.14316809,
       -0.16522089, -0.24140622,  0.28401554, -0.13305223, -0.0443135 ,
       -0.13162884, -0.03575695, -0.07907242, -0.12303767,  0.30021554,
        0.09129679, -0.01848176, -0.04850522,  0.08205752,  0.2365788 ,
       -0.07448486,  0.17528135,  0.12588878, -0.0667906 ,  0.21196875,
        0.08380637, -0.17921978,  0.08318941, -0.02711681,  0.1543107 ,
        0.1283092 , -0.14224319,  0.11648016, -0.08721871, -0.11202125,
        0.05662439,  0.12596013,  0.10223821,  0.05434442, -0.07635359,
        0.227074  , -0.08088508,  0.06892107, -0.02599742,  0.13443148,
        0.16075398,  0.05321019,  0.1699184 , -0.26431826, -0.14527422,
       -0.16973849, -0.07013404, -0.08691252,  0.00630036,  0.13391532,
        0.1306164 ,  0.06283969,  0.13332316, -0.25846097, -0.15715759,
        0.12173187, -0.0431006 ,  0.0248344 ,  0.13043045,  0.0177046 ,
       -0.12024502,  0.17527333,  0.14412789, -0.06516102,  0.01003711,
       -0.10674038,  0.10547595, -0.07069512,  0.05626857, -0.079183  ,
       -0.09134065, -0.01575729,  0.10305744,  0.14328088,  0.07051742,
       -0.16202728,  0.06435967,  0.06690986, -0.06270558, -0.06191589,
        0.11009807, -0.08359654,  0.13668029, -0.13638076,  0.1813917 ,
        0.095667  ,  0.09870555,  0.03765801, -0.16550212, -0.11763682,
       -0.12293114,  0.02955374, -0.19991477,  0.11271793, -0.16067562,
       -0.10928214, -0.03808727, -0.05355569,  0.08360422,  0.12045229,
        0.02513802, -0.14507817,  0.21581084,  0.14266208,  0.12125825,
       -0.14865752,  0.05601051, -0.11130933, -0.17829219, -0.09596231,
        0.01957098, -0.04301665, -0.07450293,  0.11293398,  0.08074261,
        0.04133282,  0.11285046, -0.01463445,  0.13220441,  0.01736695,
       -0.15261467,  0.10905004,  0.12678906,  0.05580352, -0.05500413,
       -0.1439113 , -0.10396423,  0.0133972 , -0.07819366, -0.16452862,
        0.15601651, -0.12424903,  0.18900606, -0.03268247, -0.14303316,
        0.07144739,  0.0807045 ,  0.12580927,  0.02491954, -0.00226309,
       -0.08000545,  0.09009643,  0.10213315, -0.01953996, -0.2158061 ,
       -0.05764446,  0.07402922, -0.11623682,  0.12048779,  0.1358365 ,
        0.15856856,  0.07943879, -0.24742585, -0.04058542, -0.16479869,
       -0.01287093, -0.12775123, -0.03372733], dtype=float32), array([0.10450471, 0.1823047 , 0.13447618, 0.3420516 , 0.15563543,
       0.12360461, 0.15719703, 0.31190717, 0.21009246, 0.20521769,
       0.18932486, 0.23779322, 0.10341351, 0.13865365, 0.22747564,
       0.1665677 , 0.24263735, 0.18278594, 0.12434138, 0.15024206,
       0.19554497, 0.10748578, 0.17538533, 0.14394265, 0.18828933,
       0.15554804, 0.12825827, 0.2700284 , 0.11567292, 0.11854669,
       0.2018792 , 0.14718351, 0.13720836, 0.17108922, 0.14502314,
       0.204902  , 0.30051282, 0.11802558, 0.17081988, 0.23061566,
       0.55102646, 0.3968365 , 0.12911591, 0.14846055, 0.19473694,
       0.10045113, 0.11479649, 0.16176228, 0.13097255, 0.22664808,
       0.11963253, 0.12078468, 0.20015818, 0.14847744, 0.15667062,
       0.09664934, 0.17290236, 0.10612773, 0.10157289, 0.21120673,
       0.26601207, 0.31118304, 0.10516178, 0.33383155, 0.29345775,
       0.09941164, 0.26291156, 0.22890349, 0.11134879, 0.15194888,
       0.28296116, 0.21486549, 0.26470473, 0.1808999 , 0.14394459,
       0.12289685, 0.7480974 , 0.20537049, 0.415     , 0.11377431,
       0.18494092, 0.12096462, 0.28997824, 0.3256465 , 0.16174941,
       0.11398038, 0.1959043 , 0.29970488, 0.33516446, 0.12449291,
       0.11837187, 0.15573731, 0.23511153, 0.11715598, 0.17678007,
       0.1708986 , 0.12658337, 0.24972627, 0.4810884 , 0.25189582,
       0.21159227, 0.12454535, 0.23817988, 0.4843422 , 0.22329065,
       0.2100257 , 0.13557108, 0.22941433, 0.11598132, 0.16445455,
       0.27824757, 0.33194315, 0.20694038, 0.6100048 , 0.4747283 ,
       0.10007707, 0.13122502, 0.2705576 , 0.1581537 , 0.15316887,
       0.1638425 , 0.14419258, 0.12282618, 0.14857908, 0.18786456,
       0.28394827, 0.09103954, 0.8102    , 0.09935718, 0.14078382,
       0.20323117, 0.12649362, 0.18701747, 0.13074346, 0.31668136,
       0.35783696, 0.21966746, 0.33337256, 0.18913767, 0.19875896,
       0.11936192, 0.15342036, 0.14314222, 0.298861  , 0.33819848,
       0.15745221, 0.18577711, 0.24694346, 0.1250068 , 0.27637875,
       0.09804644, 0.10093804, 0.24258418, 0.18391109, 0.14778572,
       0.14746325, 0.1765934 , 0.17807856, 0.48224613, 0.14437462,
       0.15706028, 0.1447863 , 0.2515921 , 0.15385191, 0.15658301,
       0.16434643, 0.36653405, 0.39109254, 0.22272645, 0.2557948 ,
       0.14482115, 0.14773658, 0.17623118, 0.168109  , 0.23398253,
       0.18039398, 0.20700304, 0.2945763 , 0.12406413, 0.13850799,
       0.18357478, 0.2142578 , 0.53426105, 0.11535957, 0.15507138,
       0.24026279, 0.16033155, 0.13985485, 0.20682448, 0.23094906,
       0.1116681 , 0.16756913, 0.11010013, 0.3035437 , 0.22281004,
       0.18431723, 0.18080804, 0.22491097, 0.23089674, 0.1549675 ,
       0.09178468, 0.13149379, 0.13038303, 0.09535918, 0.13394946,
       0.3342794 , 0.21184908, 0.34886137, 0.16945967, 0.25566694,
       0.25423303, 0.12569237, 0.2740007 , 0.18696395, 0.23947002,
       0.2797581 , 0.17113046, 0.12916118, 0.23907135, 0.10803045,
       0.22309272, 0.54372823, 0.11175147, 0.26517478, 0.09501009,
       0.13434142, 0.15253213, 0.24654531, 0.2802771 , 0.33048436,
       0.19313177, 0.28200346, 0.24107838, 0.20808414, 0.14317739,
       0.29154414, 0.11685436, 0.1367463 , 0.14586577, 0.14092126,
       0.46901667, 0.23747133, 0.21070139, 0.18893164, 0.20129141,
       0.22326092, 0.12220591, 0.27622736, 0.16449162, 0.20002253,
       0.29328793, 0.14834261, 0.12459362, 0.13912271, 0.26194057,
       0.14015366, 0.22571331, 0.14309432, 0.23981486, 0.37938428,
       0.2076192 , 0.1203946 , 0.10574231, 0.1115258 , 0.2281411 ,
       0.12365045, 0.25226796, 0.22579654, 0.14658159, 0.21968602,
       0.17761649, 0.09424096, 0.13689397, 0.12045178, 0.19509044,
       0.11926714, 0.11061762, 0.27894744, 0.20647413, 0.5481714 ,
       0.19212227, 0.194764  , 0.20251334, 0.26704514, 0.21223903,
       0.13951173, 0.2696729 , 0.19852968, 0.44661772, 0.3149558 ,
       0.29899064, 0.16340694, 0.09418895, 0.1346612 , 0.15874201,
       0.1833673 , 0.37459287, 0.29868722, 0.14183688, 0.17170659,
       0.1737219 , 0.1698219 , 0.12858261, 0.16593891, 0.12001683,
       0.14088011, 0.34513554, 0.13037941, 0.18213421, 0.13424915,
       0.2413595 , 0.16135013, 0.12036267, 0.10541218, 0.17532803,
       0.32316652, 0.09951223, 0.14518496, 0.35859424, 0.33433706,
       0.15586957, 0.17728586, 0.31873974, 0.12059635, 0.09919044,
       0.1951414 , 0.4693198 , 0.11428007, 0.13532187, 0.16141425,
       0.14034395, 0.1051532 , 0.11910273, 0.18320325, 0.14088431,
       0.11446168, 0.3013591 , 0.13343596, 0.14889345, 0.15194574,
       0.24540506, 0.14515698, 0.3021072 , 0.18298087, 0.1966843 ,
       0.185289  , 0.6102959 , 0.25549638, 0.15155956, 0.2311078 ,
       0.29748052, 0.14870861, 0.1563337 , 0.12635128, 0.1499846 ,
       0.15128466, 0.22386497, 0.21266241, 0.28559858, 0.28818277,
       0.35829833, 0.24062958, 0.1278614 , 0.13321589, 0.12859675,
       0.42429566, 0.33585203, 0.13822903, 0.21670745, 0.1475062 ,
       0.13586214, 0.24939977, 0.21721889, 0.27889347, 0.21064214,
       0.18053055, 0.11160333, 0.1515442 , 0.14028321, 0.25820452,
       0.20014171, 0.42442882, 0.26182947, 0.19322817, 0.19240378,
       0.12710173, 0.12293977, 0.35321668, 0.19229673, 0.10412218,
       0.10264447, 0.19531567, 0.22120346, 0.17365128, 0.12672526,
       0.1309519 , 0.54449666, 0.24587645, 0.13219237, 0.21241935,
       0.12809779, 0.10602661, 0.21401532, 0.19932416, 0.17375658,
       0.2749339 , 0.14818533, 0.15524994, 0.2593886 , 0.14715944,
       0.17226754, 0.26650175, 0.1494737 , 0.18164879, 0.09506867,
       0.47499037, 0.18567665, 0.2502716 , 0.3257361 , 0.37407294,
       0.31637895, 0.18825431, 0.18621135, 0.13670032, 0.14923877,
       0.14273933, 0.1236963 , 0.16406944, 0.22248529, 0.1924757 ,
       0.15194592, 0.25601494, 0.13975866, 0.32873997, 0.16159731,
       0.22331265, 0.14258204, 0.15890436, 0.15410696, 0.1834885 ,
       0.17899376, 0.12788391, 0.18999147, 0.14618291, 0.18879229,
       0.14823432, 0.20381992, 0.3625825 , 0.31061226, 0.5143326 ,
       0.12622643, 0.14773907, 0.16080937, 0.10877634, 0.12625392,
       0.23665006, 0.12104974, 0.17587039, 0.19666079, 0.21299647,
       0.13146752, 0.12430278, 0.18510571, 0.22454627, 0.10444784,
       0.23447412, 0.10926158, 0.1533452 , 0.10298094, 0.1419762 ,
       0.10987064, 0.18477812, 0.36622694, 0.19858535, 0.09695493,
       0.17098951, 0.13011804, 0.1813396 , 0.28627723, 0.11926754,
       0.18135543, 0.55032253, 0.11352579, 0.19113751, 0.10836305,
       0.14553404, 0.13986763, 0.2652114 , 0.19681938, 0.1011972 ,
       0.16762109, 0.1413079 , 0.11539543, 0.10261102, 0.19373903,
       0.148571  , 0.12753034, 0.50704026, 0.22262709, 0.10932678,
       0.265337  , 0.18054487, 0.10512417, 0.35807464, 0.1742991 ,
       0.20887569, 0.31339225, 0.20283793, 0.12030281, 0.16494891,
       0.17616561, 0.18701601, 0.16581158, 0.15619443, 0.29401925,
       0.24079542, 0.14515866, 0.15534031, 0.28712776, 0.09596487,
       0.22430067, 0.12557703, 0.2138567 , 0.21826747, 0.11372209,
       0.2330574 , 0.11832894, 0.16053942, 0.24084254, 0.25395417,
       0.15880191, 0.15771036, 0.11686197, 0.15084884, 0.1748459 ,
       0.22724126, 0.16386211, 0.11900992, 0.1975549 , 0.13561954,
       0.09105195, 0.23188317, 0.29583436, 0.1629837 , 0.14137816,
       0.36088324, 0.29706514, 0.12772463, 0.11181353, 0.58363825,
       0.1522038 , 0.09983511, 0.32490355, 0.09807593, 0.15481094,
       0.3416566 , 0.1789854 , 0.2287363 , 0.26069137, 0.21185772,
       0.16839433, 0.11779416, 0.24260247, 0.5311841 , 0.09331057,
       0.16252048, 0.3979036 , 0.15023884, 0.14864896, 0.22185369,
       0.4191921 , 0.6082473 , 0.3957738 , 0.11872978, 0.11459619,
       0.20346734, 0.15163283, 0.10216793, 0.3049165 , 0.301731  ,
       0.1242541 , 0.14199471, 0.11671548, 0.09392802, 0.24871182,
       0.1307183 , 0.43073258, 0.22854812, 0.13007836, 0.3468739 ,
       0.10772398, 0.29076752, 0.1032405 , 0.1855517 , 0.14548267,
       0.09921373, 0.24867938, 0.3133776 , 0.12686902, 0.20547277,
       0.1103479 , 0.2270149 , 0.14877875, 0.14825356, 0.11877979,
       0.40942362, 0.12940954, 0.22155227, 0.12970486, 0.14512552,
       0.22392377, 0.143202  , 0.2445411 , 0.49630427, 0.15116696,
       0.24514157, 0.12695153, 0.11274564, 0.1295609 , 0.20456654,
       0.20064197, 0.12263302, 0.18184757, 0.3454074 , 0.20115653,
       0.14053644, 0.17728372, 0.11449531, 0.16663592, 0.10811498,
       0.19510983, 0.25567228, 0.27546722, 0.1328508 , 0.11709347,
       0.38407487, 0.15166998, 0.15791409, 0.11579917, 0.10441623,
       0.11786573, 0.14101675, 0.21023346, 0.1638347 , 0.24291475,
       0.17739156, 0.11649659, 0.1377556 , 0.19039066, 0.13850825,
       0.17486955, 0.13556564, 0.25858167, 0.28244296, 0.31172955,
       0.20872153, 0.18350023, 0.11071819, 0.21443963, 0.1971787 ,
       0.17282827, 0.1422278 , 0.37115324, 0.22894086, 0.24543785,
       0.15751927, 0.138455  , 0.14613968, 0.14878596, 0.21291895,
       0.11016687, 0.34677377, 0.2845817 , 0.22090834, 0.19266014,
       0.15448721, 0.09498972, 0.14095873, 0.35364777, 0.21724533,
       0.11730789, 0.10736536, 0.12729372, 0.16199002, 0.20463985,
       0.1476934 , 0.20369053, 0.14851497, 0.27073917, 0.1780679 ,
       0.2562556 , 0.19009653, 0.20904143, 0.4137066 , 0.13784206,
       0.23059893, 0.0962659 , 0.288002  , 0.23307182, 0.29294235,
       0.23304507, 0.13285586, 0.23439124, 0.19813928, 0.25576955,
       0.1077021 , 0.16806045, 0.24171303, 0.13248286, 0.12827606,
       0.15463482, 0.14740181, 0.16325623, 0.11922164, 0.214796  ,
       0.15071742, 0.16172333, 0.14912376, 0.17859595, 0.26255468,
       0.23558272, 0.1641778 , 0.25566846, 0.10764382, 0.1065305 ,
       0.09719898, 0.18787956, 0.1079995 ], dtype=float32), array([[[[-0.01109655],
         [-0.00499911],
         [-0.02184995],
         ...,
         [ 0.02531974],
         [-0.00941467],
         [-0.00201603]],

        [[ 0.00829096],
         [ 0.00785158],
         [-0.02770749],
         ...,
         [-0.0181853 ],
         [ 0.02605537],
         [ 0.02294135]],

        [[-0.00976793],
         [ 0.00160278],
         [-0.02201717],
         ...,
         [ 0.01614284],
         [-0.00239229],
         [-0.02530279]]],


       [[[-0.00885746],
         [-0.00215502],
         [ 0.01693843],
         ...,
         [-0.02044592],
         [-0.00453716],
         [ 0.02092339]],

        [[-0.01414406],
         [-0.02959681],
         [-0.0337197 ],
         ...,
         [-0.00587937],
         [-0.00955825],
         [ 0.00555128]],

        [[ 0.01206828],
         [-0.00224682],
         [ 0.02082428],
         ...,
         [-0.02526954],
         [ 0.0012186 ],
         [-0.00638871]]],


       [[[ 0.03414107],
         [-0.04029673],
         [ 0.00270924],
         ...,
         [-0.02246479],
         [ 0.02663877],
         [-0.01348979]],

        [[ 0.01331741],
         [ 0.01900242],
         [ 0.00239008],
         ...,
         [ 0.0015793 ],
         [-0.01869345],
         [-0.02353801]],

        [[-0.01342364],
         [ 0.01548781],
         [ 0.01583213],
         ...,
         [-0.01320115],
         [ 0.00643989],
         [-0.0133649 ]]]], dtype=float32), array([[[[ 0.03074592, -0.01360419, -0.00543577, ...,  0.00895068,
           0.04917318, -0.01577337],
         [ 0.02880027,  0.06237768,  0.03354767, ...,  0.02500248,
          -0.01925252, -0.0158123 ],
         [ 0.02224107,  0.0605334 ,  0.04085428, ...,  0.04796083,
          -0.02653893,  0.01642997],
         ...,
         [ 0.04859306, -0.01195147,  0.05354726, ..., -0.02348122,
          -0.05332124,  0.04881145],
         [ 0.02391647,  0.00742309, -0.00616307, ..., -0.06736498,
          -0.01664354, -0.02845121],
         [-0.05105055,  0.01824995, -0.00866832, ..., -0.0207158 ,
           0.06783943,  0.05438932]]]], dtype=float32), array([0.99803513, 1.0046088 , 0.9909473 , 0.998925  , 1.009385  ,
       1.0102648 , 0.98682344, 1.0043676 , 0.99249053, 0.9875424 ,
       1.0137045 , 0.9978348 , 1.0289787 , 0.9885228 , 0.9862596 ,
       0.98506165, 0.9964507 , 0.99223745, 0.98453563, 1.0087757 ,
       0.9952657 , 1.0134813 , 0.98180574, 0.983137  , 0.98363453,
       1.028472  , 0.99120706, 0.9978226 , 0.99608475, 1.0055279 ,
       0.9965834 , 0.9909497 , 1.0088195 , 0.9869361 , 0.9871276 ,
       1.0101018 , 0.9951565 , 1.0013592 , 0.991991  , 0.99566454,
       0.99965966, 1.009058  , 1.0144224 , 0.9934407 , 0.9886827 ,
       1.0095977 , 0.9937109 , 1.0028099 , 0.9880714 , 0.99179965,
       0.99530286, 1.0012437 , 0.9943108 , 1.0204488 , 0.99881077,
       0.99373007, 0.9878978 , 0.9962814 , 1.0012109 , 0.990365  ,
       0.99226886, 1.0282114 , 0.9969717 , 0.9903098 , 1.000336  ,
       1.0306643 , 0.99839455, 0.9876054 , 0.9999619 , 0.99637496,
       1.0107069 , 1.0004262 , 0.99552906, 1.0101556 , 1.0077564 ,
       0.99519104, 1.0485154 , 1.0034434 , 0.98869485, 0.99631745,
       1.0186913 , 0.9984681 , 1.0164804 , 1.0186532 , 0.981034  ,
       0.9908985 , 0.98441607, 0.9978066 , 1.0029902 , 1.0121826 ,
       1.0066577 , 0.98545796, 1.0060967 , 1.0149214 , 1.0247982 ,
       1.004649  , 0.99494153, 0.98274714, 0.9992755 , 0.992986  ,
       0.9940198 , 0.9996449 , 0.9928516 , 0.9987387 , 0.9964083 ,
       0.9976152 , 0.9932132 , 1.0148445 , 1.0200297 , 1.0012342 ,
       1.0014148 , 1.00554   , 0.99170697, 1.0083278 , 0.9880546 ,
       0.99300206, 1.0140091 , 0.9901396 , 0.9921137 , 1.001117  ,
       1.0027852 , 0.9954374 , 0.9911879 , 1.0140386 , 0.9870319 ,
       1.0036606 , 0.99858767, 0.9952204 , 0.9996857 , 1.0013453 ,
       1.0184261 , 0.9834129 , 0.9930039 , 1.0013175 , 0.9919818 ,
       0.999328  , 1.0175048 , 1.0157317 , 0.99982584, 1.0095348 ,
       1.0154545 , 1.0001463 , 0.9856472 , 0.98534214, 1.0040792 ,
       1.007201  , 0.98751014, 0.997181  , 0.9919595 , 0.9822713 ,
       0.99827754, 0.9880614 , 0.9923642 , 1.0021844 , 1.0012395 ,
       1.0000186 , 0.99890643, 1.0418522 , 0.98625445, 0.9994709 ,
       1.0196625 , 1.003318  , 1.0112756 , 0.99970746, 0.9927138 ,
       0.99240863, 1.01221   , 0.9974342 , 1.0000583 , 0.9939982 ,
       1.0098492 , 1.0052904 , 0.99654025, 0.9868637 , 0.99398726,
       0.9960083 , 0.9987761 , 1.0052245 , 0.99647254, 0.9895953 ,
       1.0006697 , 1.0377278 , 1.0004892 , 0.9937094 , 1.0062596 ,
       0.98809   , 1.0010458 , 0.99408364, 0.99538654, 1.0103773 ,
       0.9812282 , 1.0325006 , 1.0090463 , 0.99053043, 0.9915313 ,
       1.009817  , 1.0130328 , 0.9951111 , 1.0041921 , 0.99951357,
       0.99544066, 1.0177225 , 0.9920638 , 1.0157822 , 0.99520326,
       1.0172827 , 0.98961174, 0.98628753, 0.9916352 , 1.0074002 ,
       1.0168159 , 0.9934917 , 0.988325  , 1.007515  , 1.010527  ,
       1.0062574 , 1.0240341 , 0.97554773, 0.99648726, 0.99623597,
       1.0049473 , 1.001142  , 1.0190561 , 0.99811554, 0.9903545 ,
       1.024149  , 0.99670416, 0.9915205 , 1.0305558 , 1.0038401 ,
       1.0062487 , 0.9965081 , 0.9901354 , 0.99091583, 1.0194002 ,
       1.0012163 , 0.9878287 , 1.0047727 , 0.9958263 , 1.0079724 ,
       1.0088613 , 0.99974567, 0.9938919 , 0.98859984, 0.9823225 ,
       0.99936116, 1.0017405 , 0.99341565, 1.0079964 , 0.99383503,
       0.9880807 , 0.9984338 , 1.0094824 , 1.0151185 , 0.9984495 ,
       0.99544066, 1.0129155 , 0.9804648 , 0.9985739 , 0.9998461 ,
       1.0197995 , 0.98319054, 1.001893  , 1.0069065 , 0.99213946,
       1.006089  , 1.0309583 , 0.98926765, 1.0043627 , 0.9992017 ,
       0.993411  , 0.9972312 , 0.99234873, 1.015442  , 0.9936574 ,
       0.9948315 , 1.0054574 , 1.003481  , 1.043779  , 0.99472517,
       0.9957667 , 1.000054  , 0.9869266 , 0.9974767 , 1.0018605 ,
       0.99786747, 0.99713975, 1.0057555 , 0.9926236 , 0.9977677 ,
       0.99058783, 0.9927715 , 0.9931272 , 0.9905573 , 1.004585  ,
       1.005621  , 1.0026755 , 0.9891249 , 1.0226712 , 0.98901856,
       0.9953288 , 0.98984605, 0.98725605, 0.9985844 , 1.014867  ,
       0.98927516, 1.0066432 , 1.002196  , 0.99140894, 0.9931884 ,
       0.993842  , 1.0215297 , 1.0214546 , 0.988273  , 1.0209677 ,
       1.0115051 , 0.9938527 , 0.9980289 , 1.0042611 , 1.0082889 ,
       1.0023791 , 0.98722464, 1.0063626 , 0.99199736, 1.0021403 ,
       1.0083863 , 1.0183932 , 1.0256283 , 1.0105191 , 0.99382395,
       0.9869267 , 1.008749  , 1.0002164 , 1.0052485 , 1.0014423 ,
       0.99900866, 1.0061818 , 0.9878381 , 0.9957725 , 1.0022713 ,
       1.0066756 , 1.0158383 , 1.0114095 , 0.9973379 , 0.99385124,
       1.0176897 , 0.99447143, 0.9998303 , 1.0067035 , 0.9994608 ,
       0.995967  , 0.9958306 , 1.0008334 , 0.9950678 , 0.9892162 ,
       1.0117532 , 1.0327158 , 1.0046059 , 0.99673575, 0.9885719 ,
       1.0079015 , 1.0082867 , 0.9874066 , 0.9983873 , 0.98816997,
       1.0072086 , 0.997435  , 1.0060999 , 0.9993266 , 0.9864672 ,
       0.9885896 , 0.9849375 , 1.0173274 , 0.99522144, 1.0175164 ,
       0.9877676 , 0.9877703 , 0.9892942 , 0.99404866, 1.0039055 ,
       0.99599916, 0.99575335, 1.0006595 , 1.0004133 , 1.0225079 ,
       0.9942754 , 1.0086787 , 1.0013796 , 0.9993706 , 0.98919004,
       1.0293288 , 0.99643576, 0.9837467 , 0.99587965, 1.0073632 ,
       0.99268615, 1.0302743 , 0.9926942 , 1.0185642 , 0.98680675,
       1.0115668 , 0.9928226 , 1.0032051 , 1.0014657 , 0.9930486 ,
       1.0101643 , 1.0196879 , 1.0042347 , 0.993276  , 0.9887286 ,
       1.0015192 , 0.98956096, 1.0059657 , 0.9972682 , 0.9902836 ,
       0.98600423, 0.9865028 , 1.007779  , 1.0060056 , 0.98965746,
       0.98300934, 1.0342555 , 1.0046397 , 0.99719673, 1.0030268 ,
       0.99262977, 1.0161709 , 0.9981437 , 0.99137574, 1.0017489 ,
       1.0019064 , 0.9957879 , 0.99232423, 0.98719954, 1.0096757 ,
       1.010834  , 0.9906347 , 0.9928788 , 0.9977781 , 0.989033  ,
       1.0224869 , 0.99598026, 0.99396104, 0.9971374 , 0.98680466,
       0.9811599 , 1.0013192 , 1.013384  , 0.99716574, 0.986813  ,
       1.0075214 , 1.0181713 , 1.0111092 , 0.9856523 , 1.0070513 ,
       0.9691542 , 1.005313  , 0.9949839 , 0.9990843 , 0.99199873,
       1.0015045 , 0.9983535 , 1.0186249 , 0.99446446, 0.9959473 ,
       0.9937197 , 0.9980316 , 1.0061476 , 0.9948271 , 0.9944741 ,
       0.99460304, 0.9777593 , 0.9946675 , 1.0127769 , 1.0080823 ,
       0.99424964, 0.99391925, 0.9950032 , 1.0086    , 0.99212825,
       0.99992436, 0.99607223, 1.0035319 , 1.006459  , 0.9926915 ,
       1.0398524 , 1.0156983 , 1.0214136 , 1.009317  , 0.9959626 ,
       1.0004815 , 0.99577206, 0.98992676, 0.99185115, 1.022246  ,
       0.99640286, 1.0014925 , 1.0114356 , 0.99550927, 1.00272   ,
       0.9943429 , 1.0031172 , 1.0027003 , 1.0018579 , 1.0133992 ,
       0.9927457 , 0.98442864, 0.9957374 , 0.98842007, 0.98410696,
       1.029312  , 0.9955521 , 0.9898015 , 0.99619406, 0.9931395 ,
       1.0422809 , 1.0069181 , 0.99340516, 1.0000409 , 1.0006436 ,
       0.9947522 , 0.9919491 , 1.0040216 , 1.0057606 , 1.0218539 ,
       1.0181743 , 0.99638206, 0.9914845 , 0.9718627 , 0.99853915,
       1.018046  , 0.99776644, 1.0053236 , 1.018097  , 0.9955709 ,
       0.9951374 , 0.9958206 , 0.9962587 , 0.9953194 , 0.98563975,
       1.0078423 , 0.9995385 , 1.0190278 , 1.0248058 , 1.0001557 ,
       1.0057833 , 1.0034009 , 1.0087639 , 0.9934431 , 0.99590266,
       1.0041012 , 0.9900673 , 1.0047488 , 0.98311013, 0.9951223 ,
       1.0023195 , 0.9985366 , 0.9867064 , 1.0002661 , 0.99026483,
       1.0093789 , 1.0077208 , 1.0087757 , 0.98118514, 1.000489  ,
       1.0013487 , 0.9855511 , 1.0122896 , 0.9910768 , 0.98866177,
       0.98819625, 1.0102615 , 0.991609  , 0.98525333, 0.9968628 ,
       0.9923757 , 0.97426337, 1.0305341 , 1.0047703 , 1.0019412 ,
       1.0091972 , 0.9980736 , 0.99790704, 0.99414706, 1.001737  ,
       1.0219157 , 0.9947672 , 0.980337  , 1.0055302 , 1.0121098 ,
       1.0131079 , 1.0235794 , 0.99475497, 0.9925748 , 0.99164957,
       0.99558216, 0.988154  , 1.0163186 , 1.0179226 , 0.994634  ,
       1.0148402 , 0.99892116, 0.9946312 , 1.00718   , 1.0041635 ,
       1.0061647 , 0.9964905 , 1.0039179 , 1.0049657 , 0.9975595 ,
       1.0058956 , 0.9900121 , 1.0020231 , 0.9945207 , 1.0009946 ,
       1.0035043 , 0.99117297, 1.0037435 , 1.0172479 , 1.0112714 ,
       1.0095125 , 1.0044063 , 0.9917616 , 1.0093039 , 0.99234957,
       0.99036676, 1.0014395 , 0.99895614, 0.98915386, 1.018013  ,
       1.0826793 , 1.002249  , 0.9949663 , 0.994025  , 1.0055335 ,
       1.0023445 , 0.9950953 , 0.99698204, 1.005372  , 0.9910113 ,
       1.004797  , 1.0014999 , 1.0015053 , 0.9940917 , 0.97892916,
       0.9863857 , 0.99314994, 0.99522895, 0.9906886 , 0.9890308 ,
       1.0032655 , 0.9959997 , 1.0072027 , 0.98863953, 0.98819196,
       1.0015963 , 0.99701333, 0.9936252 , 0.9936668 , 0.98979765,
       1.0026261 , 1.0143763 , 0.9956536 , 0.9868175 , 0.9897843 ,
       0.99542063, 0.99586946, 1.0017776 , 0.98953116, 1.0150199 ,
       1.0022373 , 1.0099868 , 1.0019861 , 1.0007315 , 0.9851922 ,
       0.9950824 , 1.0032494 , 0.9950377 , 1.0046442 , 0.9883077 ,
       0.9899673 , 1.0190846 , 1.039749  , 0.9872366 , 0.99518573,
       0.99627626, 0.9986251 , 0.9982621 , 0.99684376, 1.0077032 ,
       0.994926  , 1.0023943 , 0.9851191 , 1.0020064 , 0.9919964 ,
       0.9950804 , 0.98745   , 0.99175876, 0.9948109 , 0.990164  ,
       0.9942118 , 0.9883982 , 0.9977924 , 1.0088472 , 0.9953379 ,
       1.0050701 , 0.9948609 , 1.0058376 , 1.0004557 , 1.0004815 ,
       1.0096074 , 1.0005541 , 0.99845034, 0.9985597 , 0.998716  ,
       0.9907627 , 0.9988475 , 1.0133845 , 0.9956692 , 1.0045805 ,
       0.9989116 , 0.9880696 , 1.0018474 , 1.0014168 , 0.99538517,
       0.9893475 , 1.0072405 , 0.9909867 ], dtype=float32), array([-7.03317346e-03, -2.29411833e-02, -5.44195669e-03, -6.96935924e-04,
        2.09476762e-02,  4.33186442e-03, -1.49872275e-02, -1.59498665e-03,
       -6.87138364e-03, -1.04388921e-02, -1.51381949e-02,  2.34820833e-03,
        3.66777517e-02, -3.51224355e-02, -3.62447537e-02, -1.94226038e-02,
       -1.86291020e-02, -7.39784027e-03, -9.03759245e-03, -4.75766463e-03,
       -4.95457696e-03, -4.93979566e-02, -1.36040887e-02, -1.29920701e-02,
       -1.03560891e-02,  2.48680077e-02, -4.93810838e-03, -2.49229837e-02,
       -1.78191159e-02, -1.08836684e-06, -3.87947261e-02, -1.86104339e-03,
       -8.90398677e-03, -3.16453911e-02, -8.92386027e-03,  7.91619346e-03,
        1.03714680e-02,  5.10057248e-02,  2.42377110e-02, -8.73444695e-03,
        9.63333435e-03,  3.90992239e-02,  6.46498566e-03, -4.76449542e-03,
       -1.37369884e-02, -3.20112612e-03, -6.75796065e-04,  1.04647584e-03,
       -8.32646526e-03, -9.43248998e-03, -1.10370824e-02, -4.14562076e-02,
       -1.07899811e-02,  1.78338066e-02,  2.62626354e-03, -2.65640579e-02,
       -3.02145444e-02, -3.65181733e-03,  1.34356767e-02, -3.88712343e-03,
        1.75102800e-02, -3.73278707e-02, -1.48379849e-03, -1.34444050e-02,
       -8.55593244e-04,  2.99712699e-02, -1.48658659e-02, -7.32867979e-03,
       -2.56605260e-03, -4.52779001e-03, -4.53562401e-02,  7.27071520e-03,
       -2.97350285e-04,  4.57874276e-02,  5.16017899e-03, -2.81712809e-03,
       -3.32036056e-02,  7.98873976e-03, -2.26282608e-02,  1.89155131e-03,
       -5.22982422e-03,  5.13615739e-03, -3.09462901e-02,  4.35256772e-02,
       -8.48150719e-03,  1.35588450e-02, -8.29265825e-03,  2.26171548e-03,
       -5.18633351e-02, -7.47111044e-04, -1.83872376e-02, -1.95335019e-02,
       -1.20885763e-02, -1.23359868e-02,  2.31613219e-02,  1.30208367e-02,
       -5.53022046e-03, -8.67833942e-03,  3.99862928e-03, -2.62478981e-02,
       -3.41350585e-03,  1.51459640e-02, -5.04704425e-04,  4.33266489e-03,
       -1.93074998e-02, -3.18029970e-02,  3.55322351e-04,  1.88737120e-02,
        4.58742492e-02,  7.04544317e-03, -2.95563489e-02,  4.99919662e-03,
       -4.60429229e-02,  2.15174370e-02, -1.35257710e-02, -2.44930740e-02,
        4.61138450e-02,  5.79208601e-03, -4.61120298e-03, -1.58259962e-02,
        2.64406484e-03, -4.19569481e-03, -1.09329587e-02,  6.85792603e-03,
       -1.19957048e-02,  6.28345879e-03, -2.38769706e-02, -2.33169068e-02,
        1.22204693e-02, -5.46715502e-03,  3.25173549e-02, -1.79166067e-02,
       -9.92895104e-03, -1.32634751e-02,  5.47173060e-03,  9.92344460e-04,
        1.59551725e-02,  7.25560542e-03,  5.92895318e-04, -1.77796111e-02,
       -1.11812446e-03,  2.92653148e-03,  2.86395289e-03, -1.05992639e-02,
        1.07918438e-02,  9.05544497e-04, -2.95819361e-02, -5.51099936e-03,
       -1.97745990e-02,  1.38329007e-02,  1.88722368e-03, -1.54963892e-03,
       -2.23442297e-02, -3.39759979e-04, -1.16876476e-02, -2.80001271e-03,
        1.30049968e-02, -4.72290330e-02, -1.20488610e-02, -2.62599601e-03,
        1.76618677e-02,  3.38065140e-02,  2.52805129e-02, -2.87373108e-03,
       -1.21707167e-03, -2.38973871e-02, -5.08931745e-03,  2.77073719e-02,
        3.30208801e-03, -2.81605637e-03, -5.25081605e-02,  1.34190479e-02,
       -1.75080996e-03,  6.09500986e-03, -5.27853519e-03, -4.04285965e-03,
        9.24731977e-03, -1.38188917e-02,  3.00747552e-03, -2.97161681e-03,
       -2.26099696e-02, -5.93509749e-02, -2.71591991e-02, -9.90729220e-03,
        1.88033711e-02, -4.55055013e-02, -1.29196867e-02,  5.98838506e-03,
       -1.67103279e-02,  7.09144305e-03, -1.34884426e-02,  3.89556251e-02,
       -7.42227677e-03,  6.78129820e-03,  3.41820996e-03,  4.28284705e-03,
        1.53234638e-02,  3.45755066e-03, -1.25628738e-02, -5.03096264e-03,
       -1.02706812e-02, -6.85388967e-03, -1.53641803e-02,  8.73282459e-03,
       -4.75806091e-03, -4.16601636e-03, -8.00850801e-03, -2.74627935e-02,
       -1.14790658e-02,  4.22574440e-03, -1.43301329e-02, -9.60185379e-03,
       -2.69640088e-02, -8.14422686e-03, -3.75892106e-03, -8.80838663e-04,
       -5.21293394e-02, -3.66074070e-02,  7.09624449e-03, -3.22484225e-03,
        1.48485822e-03, -1.03235524e-02,  2.55589150e-02, -2.40052206e-04,
       -6.81382883e-03,  4.93507273e-02, -1.31089985e-02, -1.25059357e-03,
        6.35100342e-03, -6.52999384e-03,  8.11121333e-03, -3.19368998e-03,
       -1.67572014e-02, -1.77083127e-02,  1.17935380e-02, -5.11597889e-03,
       -7.31022004e-03, -2.72912759e-04, -1.04133254e-02,  8.02467670e-03,
        2.24917494e-02,  7.98576977e-03, -4.80131898e-03, -2.68301107e-02,
       -9.79895145e-03, -2.59101333e-04,  5.26612811e-03, -5.06169209e-03,
        5.07057272e-03, -1.60043016e-02, -3.29059437e-02, -4.04120074e-04,
       -5.09201065e-02, -2.85261478e-02, -1.00017237e-02,  1.73944398e-03,
        2.17747129e-02, -1.69599578e-02, -5.88082382e-03, -4.94607724e-04,
        3.88767198e-02,  2.31867074e-03,  1.38037726e-02,  1.40047837e-02,
       -1.67202111e-02,  1.25311529e-02,  2.59351637e-02, -8.51616636e-03,
        4.59887227e-03, -4.96522523e-04, -1.19093824e-02, -6.59427326e-03,
       -1.29666710e-02, -3.35124545e-02,  5.64745162e-03, -1.40867271e-02,
       -3.35472226e-02,  1.55912200e-03,  3.89476717e-02, -7.82278739e-03,
       -3.92625816e-02, -1.75626483e-02,  8.87541380e-03,  7.46518420e-03,
       -1.56973558e-03, -4.00204817e-03,  6.47295266e-03, -1.61489192e-03,
       -3.13423644e-03, -1.01700868e-03, -6.09035697e-03, -1.31416284e-02,
       -5.66017488e-03, -1.21654039e-02,  4.10383008e-03,  4.73734550e-03,
       -2.99219992e-02, -3.94335575e-03,  3.48834656e-02, -3.08491606e-02,
        2.42601195e-03,  5.29098557e-03, -3.02769593e-03,  3.88932717e-03,
        1.64650511e-02, -2.51963045e-02,  5.42055769e-03,  1.76565293e-02,
       -5.59606310e-03,  3.60642839e-03, -5.67210745e-03,  2.09718607e-02,
       -3.93121690e-03, -1.15308398e-02,  4.97651026e-02,  1.17463972e-02,
       -2.10270309e-03, -1.20585412e-02,  1.01727517e-02, -3.04673798e-02,
       -5.72999520e-03, -2.52039190e-02,  1.43883061e-02, -1.00901928e-02,
       -3.97229753e-02,  2.64903810e-02,  2.03959178e-02,  2.00706255e-02,
        1.07088909e-02, -1.08423196e-02, -7.63331354e-03, -1.38499476e-02,
        7.65088340e-03, -1.04954010e-02,  9.74668597e-04,  5.96691901e-03,
        9.59731638e-03, -3.13161546e-03,  3.29356384e-03, -5.01571186e-02,
        4.37588105e-03,  1.56824477e-02, -2.53072102e-02,  2.71460880e-03,
       -1.19155562e-02,  1.37982527e-02, -4.78467159e-03, -7.94616062e-03,
       -1.83444005e-02,  2.02656537e-03,  9.45623592e-03,  9.59522382e-04,
       -2.28300001e-02, -1.17467120e-02, -1.74756590e-02, -1.56557150e-02,
        2.73147859e-02,  5.39464236e-04, -8.02575424e-03, -1.40111130e-02,
        1.52435964e-02, -1.02010695e-02, -1.93682127e-02, -8.35762068e-04,
       -1.09578883e-02,  6.28842926e-03,  7.14359945e-03,  1.60937733e-03,
       -2.94044218e-03, -4.22200700e-03, -1.34689258e-02, -2.91629061e-02,
       -3.06294672e-02, -3.25239683e-03,  2.55230125e-02, -1.71081871e-02,
       -1.02889938e-02, -6.45610038e-03,  1.72064494e-04,  2.78552482e-03,
       -2.81290822e-02, -1.73819959e-02,  6.36619423e-03,  1.70569886e-02,
       -4.56511229e-03, -5.97099913e-03, -8.65457952e-03, -1.29628256e-02,
       -1.21917697e-02, -1.14556309e-02,  2.36416608e-02,  4.67703096e-04,
       -2.40594223e-02, -5.28370496e-03,  8.97252373e-03, -1.53336013e-02,
        1.72204729e-02, -2.44437158e-03,  2.20671669e-02, -2.96472814e-02,
       -1.39727462e-02, -5.38984966e-03,  1.18788350e-02,  1.13473525e-02,
       -6.06830698e-03, -1.83898327e-03,  2.55532134e-02, -1.19015248e-02,
       -1.05600702e-02, -7.10313348e-03,  1.93518482e-03, -1.21683860e-02,
        4.40583471e-03, -1.00458534e-02, -5.38600981e-03, -3.43467551e-03,
       -1.47375064e-02, -2.17776783e-02,  1.36846881e-02, -1.11285187e-02,
       -6.78573083e-03,  3.43888365e-02,  1.75863374e-02,  2.96679698e-03,
        1.39717781e-03, -2.67989351e-03,  3.92111763e-02, -1.17682023e-02,
       -7.29025109e-03,  5.42730931e-03,  8.43538530e-03, -5.34466887e-03,
       -8.58367048e-03,  6.92500616e-04, -1.88456140e-02, -2.51781661e-02,
       -4.44194349e-03,  4.44474397e-03, -1.31878653e-03, -9.83495452e-03,
        8.97482596e-03,  2.17223018e-02, -5.94429066e-03, -7.36474060e-03,
       -2.52653821e-03, -1.33806178e-02, -1.36342086e-02,  3.61869205e-03,
        1.36412994e-03, -1.10982573e-02,  2.53646309e-03,  2.87840292e-02,
       -3.32239941e-02, -1.82031933e-02,  9.46783740e-03, -4.22047032e-03,
       -1.84896979e-02,  1.24306427e-02,  2.99033406e-03, -2.32945364e-02,
        2.97322776e-03,  6.65099453e-03,  2.04934124e-02, -4.14934522e-03,
       -6.83127670e-03, -5.55816339e-03, -1.09321382e-02,  1.41049987e-02,
       -2.32123677e-03, -1.15788002e-02, -1.04206176e-02, -3.17304465e-03,
       -1.20588415e-03,  3.12460680e-02,  1.14926416e-02,  6.45690737e-03,
       -3.73083055e-02, -1.07792830e-02,  1.26193147e-02,  2.68242881e-03,
        1.50237987e-02,  1.05549330e-02, -2.33411212e-02, -1.71423447e-03,
        4.32149181e-03,  4.40531317e-03,  2.54573417e-03,  3.41890678e-02,
        9.25765280e-03,  3.54259345e-03, -1.28285233e-02, -2.41458267e-02,
       -2.41521536e-03, -1.82353128e-02,  2.34848391e-02, -2.37120525e-03,
        2.86724605e-03,  1.07810441e-02, -1.48919318e-03, -7.35098356e-03,
       -1.20971240e-02, -1.51050137e-03, -9.37751494e-03,  1.68888979e-02,
       -3.78046706e-02, -5.58769098e-03, -6.60078228e-03, -1.69155386e-03,
       -7.80249853e-03, -6.18769694e-03,  2.63766404e-02, -5.19805076e-03,
        1.06539847e-02, -8.62804800e-03, -1.13688316e-02, -3.25565808e-03,
        3.15839462e-02, -2.24702023e-02, -1.97135527e-02,  1.27591733e-02,
       -2.66378629e-05, -6.61121542e-03,  1.12222666e-02,  1.68463569e-02,
       -1.39311058e-02,  9.21725295e-03,  3.20665329e-03, -9.58270859e-03,
       -1.14224050e-02, -2.85270275e-03,  4.03071521e-03,  8.67366884e-03,
        1.47697178e-03,  1.35297766e-02,  5.04633831e-03, -1.26714734e-02,
        3.28396377e-03, -4.67681186e-03, -8.29053950e-03, -4.60801367e-03,
       -3.03264009e-03,  5.43127675e-03,  3.35887168e-03,  1.51683968e-02,
       -3.09086852e-02,  2.76692491e-03, -3.18488069e-02,  2.00865213e-02,
       -5.45281544e-03,  1.82247926e-02, -1.14639038e-02, -4.14283061e-03,
       -1.91182503e-03, -1.28743285e-02, -1.14312572e-02,  1.93180740e-02,
        1.77228329e-04,  1.09608434e-02, -1.62873641e-02,  1.77413586e-03,
        2.62344535e-03,  2.57757362e-02,  2.61190138e-03, -3.54225002e-03,
       -1.49889560e-02,  5.12663159e-04, -2.18681712e-02, -6.85344590e-03,
       -1.23840552e-02, -7.61466473e-03, -2.41255504e-03,  1.98540334e-02,
       -1.13645447e-02, -2.47092210e-02, -1.28765786e-02, -1.39314858e-02,
       -1.79712195e-02,  2.07157750e-02,  1.91861913e-02,  2.04899088e-02,
       -3.38361152e-02, -2.31585708e-02, -4.86137299e-03, -1.20241172e-03,
        6.95183128e-03,  2.04485618e-02, -1.37711847e-02, -5.71592525e-03,
        1.40961772e-02,  6.84411870e-03,  2.72136442e-02,  3.20564620e-02,
        1.20854685e-02, -3.78863961e-02, -3.81628703e-03, -1.68270175e-03,
       -1.63664687e-02,  2.00765319e-02,  1.46291461e-02,  7.27534061e-03,
        2.45248768e-02, -1.18698813e-02,  4.30455897e-03, -5.40291937e-03,
        3.48087749e-03,  2.14258432e-02, -2.20235833e-03, -5.90678258e-03,
        8.92950781e-03,  6.36993069e-03,  5.95331949e-04, -2.92329257e-03,
        5.36869792e-03, -1.01586767e-02,  1.70757028e-03, -1.02128880e-03,
       -2.12735534e-02,  7.08584161e-03,  9.53498855e-03,  2.60386057e-02,
        3.32808960e-03, -9.31823160e-03, -7.01929815e-03,  1.75773557e-02,
        5.71087142e-03, -6.50056079e-03, -1.89255886e-02, -4.34216112e-04,
       -3.17271822e-03,  1.64949372e-02, -4.89991643e-02, -2.27374933e-03,
        1.07960533e-02,  6.28796872e-03, -1.23092942e-02,  1.29951723e-03,
        1.28172536e-03, -2.66937143e-03,  7.12193316e-03, -1.11679239e-02,
       -1.64992232e-02,  6.65168650e-03, -2.72286916e-03,  4.23366856e-03,
       -1.38179092e-02, -1.47811426e-02,  1.66630221e-03, -1.76559086e-03,
        3.94603657e-03, -1.15255946e-02,  3.26090306e-03,  1.04576982e-04,
        2.19476391e-02, -1.80274304e-02, -2.53618229e-04,  1.43458415e-02,
       -8.81904550e-03,  8.88633914e-03, -2.02468038e-02, -9.22731683e-03,
        1.81986690e-02,  5.48353232e-03,  7.80384289e-03, -2.52188332e-02,
       -1.42482324e-02, -1.98457707e-02, -6.92811562e-04, -2.86485883e-03,
       -9.21809021e-03,  1.66297672e-04,  1.69638009e-03,  1.55658470e-02,
       -1.88598817e-04, -1.04554622e-02, -3.97395566e-02, -1.39354530e-03,
       -1.94678735e-02, -3.61885433e-03,  9.49651003e-03, -6.50848774e-03,
       -3.44535299e-02,  4.21981104e-02,  3.97276282e-02, -1.65467337e-02,
       -6.31610071e-03,  6.92706730e-04, -4.14959592e-04, -3.96935875e-03,
       -5.22781461e-02, -2.37397645e-02, -7.61522725e-03,  2.29372829e-03,
       -2.68845074e-02, -1.54466005e-02, -3.77075304e-03, -8.38522054e-03,
        6.05356367e-03,  9.57495766e-04, -3.28320893e-03, -6.51610363e-03,
       -1.04430756e-02, -1.60425331e-03, -5.27885044e-03,  1.52220121e-02,
        5.54300845e-03,  1.20766449e-03, -1.71304233e-02,  7.02078082e-03,
        1.21973632e-02, -1.16877854e-02,  1.98151879e-02, -2.32008509e-02,
       -9.44808591e-03, -5.51890768e-03,  5.16262045e-03, -1.64648835e-02,
        1.25089996e-02,  2.51085795e-02,  2.19054963e-03,  1.02635324e-02,
        2.69653101e-04, -3.37629404e-04, -1.33329183e-02,  1.13988211e-02,
       -1.57713983e-02, -3.08742374e-03,  2.25166753e-02,  4.05871822e-03],
      dtype=float32), array([-0.0090157 ,  0.05503695, -0.03020125,  0.04477397, -0.03026336,
        0.02970232,  0.01686738,  0.02141745, -0.00978705,  0.01764141,
        0.05054281, -0.05149249,  0.00347442, -0.02478287,  0.05954482,
        0.04026798,  0.05169852, -0.04509443,  0.03018245, -0.03400048,
        0.00094497,  0.06588267,  0.0247011 ,  0.03697996, -0.04776319,
        0.01161759, -0.04744434,  0.04206308,  0.0348651 ,  0.00087113,
        0.04659025, -0.02013838,  0.03239818,  0.04336635,  0.00518252,
       -0.0246985 , -0.01986756, -0.02473741, -0.02327631,  0.03804672,
       -0.014893  , -0.05290977,  0.01274265, -0.01308869, -0.02231622,
        0.02101273, -0.03587127, -0.04108633, -0.00226738,  0.01996815,
       -0.04230636,  0.0530506 , -0.02397271, -0.01784035, -0.0153184 ,
        0.05417005, -0.05576451, -0.01956847, -0.02739343, -0.04120431,
       -0.01931702,  0.01677325, -0.02070537,  0.05695418,  0.01681766,
        0.02148046,  0.01637363, -0.01668561,  0.01965113,  0.04751732,
        0.0435079 ,  0.00809599, -0.01770121, -0.04504895,  0.05389102,
       -0.00927422,  0.05758119, -0.0256212 ,  0.04125138, -0.00938681,
        0.047908  ,  0.01188621,  0.0534093 , -0.04892847,  0.03001671,
       -0.03360046,  0.00030455, -0.030841  ,  0.06409051,  0.0319135 ,
        0.02109317, -0.04570718,  0.01647928,  0.05492634, -0.00578273,
        0.00820144,  0.02242273,  0.05501926, -0.01396061,  0.02988661,
        0.0124732 , -0.00554531, -0.00043683, -0.00029137, -0.01189718,
        0.02647391, -0.03574929, -0.03022837, -0.01698103, -0.01686698,
       -0.00543748,  0.03866175,  0.07108206, -0.04118555,  0.03270527,
        0.0851602 , -0.05565398, -0.04645037,  0.00274983,  0.04942061,
       -0.04177647,  0.0218205 , -0.01587774, -0.0147432 , -0.00336062,
       -0.04468625,  0.02597796,  0.0562099 , -0.03645486,  0.02467832,
       -0.0201606 ,  0.00908785,  0.03021267, -0.00701544, -0.03771108,
       -0.01527292, -0.01510189, -0.00450706,  0.01068051,  0.00334916,
        0.03030344, -0.00422864, -0.02587876, -0.00252746, -0.03091172,
        0.01323534,  0.07402109, -0.04686119,  0.01930284,  0.00272873,
        0.00460294,  0.04529129,  0.03176536,  0.0430992 ,  0.03642844,
        0.02433618, -0.02507276,  0.07325766, -0.00112873,  0.01307378,
        0.02164791, -0.05111181, -0.03131268, -0.03267285, -0.02660193,
        0.02480136,  0.02990165, -0.03438174, -0.03748132, -0.0045572 ,
        0.07842065, -0.02709628,  0.05299919, -0.03580816, -0.01538092,
       -0.04102127, -0.02084821,  0.03627232, -0.0041312 , -0.04321426,
        0.02767912,  0.0582778 ,  0.07864432, -0.02079044,  0.02810722,
        0.05854445,  0.03105322, -0.03150611, -0.00400594,  0.04097413,
       -0.00175642, -0.05599879,  0.02479995, -0.02257731, -0.03436977,
        0.0415534 , -0.04403899, -0.02059334,  0.02103908, -0.01781303,
        0.02334914,  0.02650774,  0.05430871,  0.02406726, -0.0269604 ,
        0.02862675,  0.01671514,  0.05100312,  0.00901963,  0.02209092,
        0.04312101,  0.02204133,  0.02492413,  0.03799196,  0.04218867,
       -0.00882095,  0.0760208 ,  0.04878745, -0.02967305, -0.0385118 ,
        0.0104545 ,  0.06352363, -0.01136409,  0.0523672 , -0.05289989,
       -0.03577854, -0.02063714, -0.0332559 , -0.01694133,  0.03188485,
       -0.01575845, -0.03648779,  0.05352588, -0.02276413,  0.02192233,
       -0.02743291,  0.03150035,  0.01223688,  0.0287011 , -0.0669899 ,
       -0.04214354, -0.01715261, -0.03542618,  0.04346569,  0.04428127,
        0.00772886,  0.00822695,  0.03140134, -0.01656203,  0.0358116 ,
        0.07358836, -0.06367897,  0.06869698,  0.02302746,  0.02959856,
       -0.01189621, -0.04981142,  0.04264077, -0.03865994, -0.00820794,
       -0.00997163,  0.0261232 , -0.01587637, -0.01692882,  0.06341784,
        0.01491147,  0.00620821, -0.02320585, -0.03323169, -0.02939169,
       -0.03091845, -0.00609196, -0.03032542,  0.08507738,  0.03799534,
        0.03689773,  0.0556693 ,  0.07151663,  0.0098685 , -0.02977058,
        0.05576241,  0.03779143,  0.01000551, -0.05040359,  0.01032478,
       -0.02066872, -0.01209178,  0.01381753,  0.0006532 , -0.02291953,
        0.01251709, -0.0255853 ,  0.01937592,  0.00892137, -0.03840221,
       -0.03298301,  0.01761452, -0.02790164,  0.02260549,  0.03472298,
       -0.03020425, -0.02224007,  0.00476856, -0.05592487,  0.06331642,
       -0.01103737,  0.03970248, -0.04526187, -0.05985297, -0.04575069,
        0.03371497, -0.02229514,  0.02636617, -0.02179122, -0.03138366,
        0.01575035,  0.05286589,  0.04961259, -0.06349911,  0.03728918,
       -0.02196939,  0.04533969, -0.04235416, -0.03301515,  0.09529947,
       -0.01952006, -0.01669183, -0.00467036, -0.00147153,  0.05178406,
        0.00278585,  0.01905676, -0.01025957,  0.0261274 ,  0.00055765,
       -0.0073722 , -0.00758882, -0.01595522,  0.00279287,  0.06363302,
       -0.01929902,  0.03937278,  0.0452107 , -0.03182985,  0.03866871,
        0.00290502,  0.02296465,  0.05125471,  0.04983223,  0.00998042,
       -0.04006133,  0.01339598, -0.01639999,  0.0305229 ,  0.02934549,
        0.00469191,  0.0357712 , -0.01628601,  0.03195356, -0.01111967,
       -0.0284207 ,  0.04227883, -0.01828756, -0.04355079,  0.03886162,
       -0.01486335,  0.01005927,  0.02055071, -0.0294247 , -0.04670265,
       -0.05185932, -0.02621767,  0.03842786, -0.03880164, -0.00622385,
        0.04408482, -0.03861218,  0.02666706,  0.01592565,  0.02635842,
        0.05132012,  0.02113942,  0.04104156,  0.01332005,  0.01820928,
        0.00076636,  0.04672726,  0.02739313,  0.02407168, -0.02451979,
        0.01343991,  0.00424508,  0.02107357,  0.03504683, -0.00944394,
        0.03150368,  0.03702512,  0.01567633,  0.0020111 ,  0.00543889,
        0.03744543, -0.01630215,  0.00718599, -0.00549311, -0.02188413,
        0.03475474, -0.0039833 ,  0.06074193,  0.01226174, -0.02851762,
       -0.02632578, -0.03673747, -0.01385083,  0.00988263,  0.05605574,
       -0.00243151, -0.00117878,  0.0709455 , -0.03187098, -0.00303077,
        0.01221975, -0.03079325, -0.03023211, -0.02694054, -0.02465004,
       -0.0051103 , -0.04419747,  0.02086116, -0.02713837, -0.01212266,
       -0.01329865, -0.03534536,  0.0301128 , -0.03325251,  0.03845875,
        0.02797552, -0.07047262,  0.02839726,  0.0444243 ,  0.04583193,
        0.04841932, -0.03726278, -0.03597845,  0.01873187, -0.03696861,
        0.03384317,  0.0070666 ,  0.01832028, -0.03253052, -0.02311776,
        0.02002541,  0.00417871,  0.07439801,  0.03665957,  0.00486689,
        0.00994741,  0.0650297 , -0.04396908, -0.0050563 ,  0.03430279,
       -0.01773036, -0.04457371, -0.04731116, -0.00680822, -0.01245853,
       -0.01361591, -0.01968691,  0.04857485, -0.00037277,  0.00120617,
       -0.00707582, -0.01390456, -0.01589744, -0.00448208, -0.054364  ,
       -0.03250636,  0.04483885,  0.01853351, -0.02635305, -0.0398335 ,
       -0.0275786 , -0.01703646,  0.07582956,  0.04109364, -0.02727973,
        0.03096845, -0.08853962, -0.00689874, -0.03420401, -0.02662061,
       -0.03039395,  0.0643277 , -0.01596089,  0.00051691,  0.00572175,
       -0.00924341, -0.04492371, -0.04659996,  0.00974401,  0.03665187,
        0.03367854,  0.01312037,  0.03891407, -0.0229514 ,  0.03086163,
       -0.01558727,  0.03847262, -0.03770311, -0.01970975, -0.01008996,
        0.01581706, -0.01824815, -0.01513102, -0.03109959, -0.03385504,
        0.02793009, -0.03396301,  0.04793246,  0.02085681, -0.01510109,
       -0.03578309,  0.0065392 , -0.00177708, -0.03692922,  0.0420435 ,
        0.03597612, -0.02663167, -0.03387278,  0.03038049,  0.01548386,
        0.0010928 , -0.02688771,  0.00528403,  0.00219718, -0.02267957,
        0.02719788, -0.0345186 ,  0.03588405, -0.02824883,  0.03004869,
        0.02663187, -0.0006192 ,  0.02961728,  0.01633298,  0.04441172,
        0.02391795,  0.02103884, -0.03719849,  0.01170345, -0.04611024,
        0.02927271,  0.03865021, -0.03707897, -0.01122001,  0.05202225,
       -0.03915253,  0.00099397, -0.03075507,  0.04350863, -0.04156988,
        0.00320518, -0.04032665,  0.01929499, -0.00494905, -0.07821912,
       -0.05210787, -0.01787708, -0.00088025,  0.04333324, -0.01960095,
       -0.04404792, -0.03258129, -0.05320182, -0.06077345,  0.03399527,
       -0.00839438,  0.0210271 ,  0.00549427, -0.03844321, -0.02060392,
        0.02536198,  0.01090612, -0.04889292, -0.03005246, -0.01678579,
        0.02309854,  0.0215475 ,  0.01111923, -0.00605412, -0.0282658 ,
       -0.03174864,  0.02342889, -0.06207477,  0.05457979, -0.0043709 ,
       -0.01047071,  0.01538052, -0.03686693,  0.05270834, -0.04018753,
       -0.02753766, -0.01492672, -0.02621834,  0.05336481, -0.02657634,
       -0.02570511,  0.02821766,  0.02832292,  0.03202274, -0.02668017,
       -0.0157028 , -0.02894877, -0.0324241 ,  0.03078969,  0.00614445,
       -0.01139892,  0.04248066, -0.03163555,  0.0233827 , -0.0436483 ,
        0.06317442, -0.03256746,  0.01301721,  0.00898023, -0.0451507 ,
       -0.00675644,  0.02638439,  0.00749458,  0.03267926, -0.0029641 ,
        0.0845296 , -0.00075814, -0.05029478, -0.01455654,  0.02605338,
       -0.05613563, -0.00256971,  0.00084679,  0.01045884, -0.02822725,
       -0.02011274, -0.01588789,  0.00084925, -0.02386577,  0.03330537,
        0.04899214,  0.02060895, -0.02708508, -0.01331859, -0.00831208,
        0.02925447, -0.02348747,  0.03246895,  0.06174299,  0.00976439,
       -0.01480553, -0.02265949, -0.06010521,  0.04309331,  0.01880559,
       -0.02803393, -0.09791899, -0.00347561,  0.01920924,  0.02366805,
        0.01296481, -0.02329239,  0.03697743, -0.01806642,  0.03171097,
        0.00444246, -0.02245674, -0.01147544, -0.01526046,  0.05322305,
       -0.02910846,  0.02252333, -0.04347208, -0.02119892, -0.04731107,
        0.02161047, -0.07287844,  0.00140028, -0.01908054,  0.03063889,
       -0.02242031, -0.02555577, -0.0193809 ,  0.08106775,  0.00696676,
        0.01929027,  0.04674359,  0.04480667,  0.01545568,  0.03390386,
        0.01088948, -0.03312582,  0.02853115,  0.02233442, -0.02201655,
       -0.00457424, -0.0015834 , -0.01589504, -0.00872367, -0.03471246,
       -0.01796809,  0.05579356,  0.03195031, -0.01010695,  0.04255552,
        0.03893337,  0.03524324,  0.00391347,  0.04891617, -0.03158732,
       -0.00026373,  0.01765593, -0.00558781,  0.03569712, -0.01580524,
       -0.03292927, -0.04053852,  0.06495595, -0.00899708,  0.04256001,
        0.05394513, -0.04887843, -0.0094007 ], dtype=float32), array([0.08416275, 0.10772365, 0.08894511, 0.09424046, 0.09409668,
       0.0862325 , 0.08799849, 0.08932336, 0.08674134, 0.090847  ,
       0.09824258, 0.08922824, 0.08740088, 0.12326544, 0.11779696,
       0.09179221, 0.10437887, 0.10060673, 0.09723914, 0.08792703,
       0.08883008, 0.13025185, 0.09961528, 0.10225333, 0.08356396,
       0.09671108, 0.09130323, 0.10578407, 0.09608404, 0.08838379,
       0.09673854, 0.10157624, 0.09305276, 0.10863088, 0.08292858,
       0.08786326, 0.08291942, 0.10354663, 0.09427298, 0.10182741,
       0.0930976 , 0.09759992, 0.09687567, 0.08352995, 0.08536315,
       0.09046972, 0.08967366, 0.08763862, 0.08618136, 0.08875941,
       0.09786936, 0.12732916, 0.08426714, 0.09691725, 0.08469794,
       0.10351614, 0.1280624 , 0.08592381, 0.11761334, 0.09419979,
       0.08730395, 0.11153945, 0.09919982, 0.09825005, 0.08794335,
       0.09867565, 0.10517882, 0.0909164 , 0.0984013 , 0.10121395,
       0.11577106, 0.09597432, 0.08698917, 0.09506541, 0.09376325,
       0.08433561, 0.10994788, 0.09201998, 0.08792803, 0.08564807,
       0.09195545, 0.08441856, 0.10195518, 0.09889165, 0.09754568,
       0.09001855, 0.09066615, 0.08762912, 0.1321649 , 0.09496749,
       0.0944591 , 0.1161274 , 0.0896375 , 0.11234508, 0.08729678,
       0.08937415, 0.10816283, 0.09863044, 0.08826661, 0.09947503,
       0.08281291, 0.09218755, 0.08783143, 0.08545301, 0.13581316,
       0.09096351, 0.10870284, 0.12133623, 0.09417694, 0.08568556,
       0.09752084, 0.1007036 , 0.1081529 , 0.09809233, 0.08787508,
       0.10110677, 0.11233436, 0.08712443, 0.08285958, 0.10094635,
       0.09338943, 0.08710732, 0.08186083, 0.09242974, 0.09957048,
       0.09315169, 0.10920183, 0.11380595, 0.09556686, 0.09012929,
       0.08621333, 0.0992825 , 0.09413844, 0.12605414, 0.09470908,
       0.08589026, 0.08740377, 0.09224981, 0.08550314, 0.08901752,
       0.09562965, 0.10481428, 0.09068494, 0.08366352, 0.10095481,
       0.08391003, 0.0944844 , 0.08434445, 0.09075423, 0.08556651,
       0.08600766, 0.08624534, 0.0878227 , 0.09199518, 0.09594331,
       0.08763436, 0.08496241, 0.12507595, 0.08439665, 0.0841355 ,
       0.09624071, 0.11180502, 0.08758596, 0.08988196, 0.09514988,
       0.09891351, 0.08389117, 0.08877122, 0.08835357, 0.09227617,
       0.13197379, 0.09412591, 0.108031  , 0.09407732, 0.08970337,
       0.09416655, 0.08817834, 0.11015286, 0.08834623, 0.0979837 ,
       0.09930009, 0.09844515, 0.16820139, 0.0878721 , 0.09433603,
       0.10204308, 0.08654065, 0.09453338, 0.0893307 , 0.10481378,
       0.0829121 , 0.11689251, 0.10070537, 0.09031203, 0.09327599,
       0.09944201, 0.08560716, 0.08529815, 0.09298002, 0.08431762,
       0.08540285, 0.09539682, 0.08884303, 0.09520304, 0.08308906,
       0.10815139, 0.09060981, 0.10643639, 0.08671179, 0.09107916,
       0.09581356, 0.08514829, 0.09617239, 0.09467871, 0.09409022,
       0.08565234, 0.14356923, 0.09210176, 0.10111369, 0.08816136,
       0.08634117, 0.097227  , 0.08815124, 0.10780921, 0.0883102 ,
       0.09979065, 0.09959389, 0.09502699, 0.10159969, 0.08987346,
       0.08258396, 0.0853126 , 0.10069609, 0.08318732, 0.09595481,
       0.08395249, 0.08566271, 0.08582991, 0.08492827, 0.09870337,
       0.10558888, 0.09804195, 0.08629692, 0.08792377, 0.09409641,
       0.0965524 , 0.09201537, 0.09017354, 0.08517812, 0.10614208,
       0.10949022, 0.10890812, 0.116085  , 0.08979122, 0.08498234,
       0.08518066, 0.11551856, 0.08924589, 0.09663926, 0.08974039,
       0.09120496, 0.09965484, 0.0895981 , 0.08557204, 0.15247777,
       0.08638103, 0.09289803, 0.0856923 , 0.08739171, 0.10692965,
       0.0898229 , 0.08602034, 0.08904187, 0.17029858, 0.11399407,
       0.09485342, 0.1173243 , 0.11413718, 0.09116788, 0.10390704,
       0.11159703, 0.11027931, 0.08931254, 0.09567504, 0.08524782,
       0.0866768 , 0.08593263, 0.08999266, 0.08705074, 0.09032302,
       0.08889551, 0.08587001, 0.0844667 , 0.08530224, 0.10244025,
       0.08764806, 0.09071577, 0.08715041, 0.11721551, 0.09603038,
       0.0935882 , 0.08511273, 0.08847648, 0.10465646, 0.12658042,
       0.09583373, 0.09223343, 0.09871443, 0.10366283, 0.10441982,
       0.09794613, 0.10983381, 0.0970533 , 0.08297797, 0.09596624,
       0.09295566, 0.09456934, 0.11594604, 0.10740886, 0.08961355,
       0.09089845, 0.10501081, 0.09893666, 0.08812273, 0.14859086,
       0.09511656, 0.08552099, 0.08711471, 0.09064844, 0.10508033,
       0.08812111, 0.09981394, 0.08490326, 0.09587103, 0.08857518,
       0.08686972, 0.09231689, 0.08444563, 0.08856685, 0.11874165,
       0.09097129, 0.09015104, 0.09762502, 0.12038489, 0.0910591 ,
       0.09423117, 0.08878663, 0.09502054, 0.10761411, 0.08652917,
       0.10981143, 0.08179873, 0.09894296, 0.10197154, 0.09796553,
       0.09221158, 0.10733018, 0.08553217, 0.08754041, 0.08778602,
       0.10333336, 0.08838718, 0.08663953, 0.09474468, 0.10375362,
       0.0906758 , 0.08766532, 0.08761816, 0.08377898, 0.09678942,
       0.097836  , 0.08666278, 0.10200717, 0.09324199, 0.10090233,
       0.1017529 , 0.08917169, 0.08858629, 0.08539326, 0.08612882,
       0.09744715, 0.0990942 , 0.09126996, 0.09685928, 0.09560689,
       0.08756164, 0.10520206, 0.08333704, 0.08846829, 0.08672637,
       0.09825027, 0.083713  , 0.0873225 , 0.09762233, 0.10129829,
       0.09733103, 0.14601189, 0.08203006, 0.10211372, 0.08795574,
       0.10369394, 0.08576839, 0.08935437, 0.08928766, 0.09577956,
       0.10374468, 0.09480984, 0.13358307, 0.0819848 , 0.10136709,
       0.08825335, 0.08629535, 0.08766277, 0.09291139, 0.10241207,
       0.08793309, 0.08383058, 0.1135063 , 0.08761156, 0.09227116,
       0.08298172, 0.09669221, 0.10084681, 0.08452725, 0.10567924,
       0.08569607, 0.10407948, 0.08689786, 0.09166501, 0.08407049,
       0.09393519, 0.08716779, 0.08650238, 0.0848289 , 0.0901581 ,
       0.09518435, 0.11257806, 0.08836339, 0.09905513, 0.09537169,
       0.10973962, 0.09543555, 0.09872593, 0.08906735, 0.09415682,
       0.09036687, 0.08551923, 0.09128366, 0.09392922, 0.08716495,
       0.08860468, 0.0856792 , 0.14684233, 0.08976856, 0.086298  ,
       0.08306839, 0.09563652, 0.10699263, 0.08757938, 0.09412781,
       0.08813192, 0.08892946, 0.08838407, 0.08267239, 0.08316682,
       0.08996415, 0.08671001, 0.08760332, 0.08653414, 0.08254981,
       0.0821164 , 0.08775885, 0.09109192, 0.09612931, 0.09326083,
       0.09224399, 0.10355717, 0.09323543, 0.10481448, 0.09034984,
       0.11244925, 0.08405292, 0.11260922, 0.08601573, 0.08445219,
       0.0965936 , 0.13013   , 0.08842107, 0.09485807, 0.08434591,
       0.10079142, 0.09679739, 0.0897586 , 0.08714321, 0.09779996,
       0.0825807 , 0.09481356, 0.09372607, 0.08271526, 0.08837161,
       0.09217075, 0.08479828, 0.09424281, 0.0923437 , 0.0917813 ,
       0.08332943, 0.08883072, 0.10046849, 0.09122612, 0.08807215,
       0.09422113, 0.09202193, 0.097432  , 0.08896325, 0.0838374 ,
       0.09888405, 0.10201387, 0.0861521 , 0.08597767, 0.0866725 ,
       0.09793817, 0.08516629, 0.08484836, 0.10007308, 0.09580407,
       0.09129283, 0.08817286, 0.08577691, 0.08948063, 0.08468611,
       0.09786852, 0.09436627, 0.08989247, 0.09683105, 0.08933271,
       0.09203785, 0.09184406, 0.08432511, 0.08198151, 0.08787119,
       0.09506319, 0.08379403, 0.09054187, 0.09934162, 0.10063334,
       0.0863378 , 0.09453395, 0.09727605, 0.08248419, 0.09316418,
       0.08833155, 0.09484609, 0.09045338, 0.08750154, 0.10440787,
       0.09265728, 0.08704121, 0.10015226, 0.11122778, 0.09674046,
       0.10141937, 0.09888168, 0.09880304, 0.08679357, 0.10388085,
       0.10392918, 0.08199343, 0.08284171, 0.09036373, 0.08668127,
       0.09266373, 0.10408677, 0.11224273, 0.11275686, 0.08702743,
       0.08545114, 0.08904555, 0.09230566, 0.09802902, 0.09895813,
       0.09730124, 0.09619658, 0.09978787, 0.0945616 , 0.09117723,
       0.09089261, 0.10140306, 0.08574242, 0.09827656, 0.08870188,
       0.10009611, 0.11177728, 0.09389117, 0.10147858, 0.08640232,
       0.08281162, 0.08640646, 0.09134442, 0.0887004 , 0.10591177,
       0.09612231, 0.08656096, 0.09175474, 0.09783381, 0.09083664,
       0.09193772, 0.08652548, 0.09039894, 0.09533203, 0.09021951,
       0.08953452, 0.08711444, 0.08345182, 0.09484525, 0.08193994,
       0.08661228, 0.14420262, 0.08522703, 0.08439022, 0.09481986,
       0.09039953, 0.09783079, 0.08702267, 0.10612389, 0.09766892,
       0.09177216, 0.09824134, 0.09199843, 0.10209736, 0.08973104,
       0.1041189 , 0.08939437, 0.08891971, 0.08375449, 0.08758058,
       0.10079031, 0.08663367, 0.08473153, 0.0856203 , 0.08721489,
       0.11850815, 0.08258575, 0.09291039, 0.10065471, 0.11317901,
       0.0933092 , 0.09310548, 0.09648205, 0.08755611, 0.08470602,
       0.09414575, 0.08464463, 0.10286026, 0.10111769, 0.08839726,
       0.09955379, 0.08449363, 0.11549129, 0.10118043, 0.092306  ,
       0.10508373, 0.12150732, 0.08494943, 0.09449346, 0.08367785,
       0.08906748, 0.08315898, 0.10478459, 0.08373617, 0.11771409,
       0.08372477, 0.08667787, 0.09262895, 0.08355087, 0.1011193 ,
       0.08676881, 0.08988906, 0.09167092, 0.08479425, 0.08478484,
       0.10040143, 0.1203822 , 0.0930837 , 0.08810925, 0.11113153,
       0.09419473, 0.08844614, 0.09611123, 0.1121271 , 0.08967022,
       0.08554661, 0.09275147, 0.0864642 , 0.08937641, 0.08643094,
       0.08520234, 0.09424023, 0.08798848, 0.0900327 , 0.09799682,
       0.0910655 , 0.09713829, 0.08715006, 0.08581974, 0.10279629,
       0.09582274, 0.10567503, 0.09376324, 0.08796468, 0.09496208,
       0.09480907, 0.10113465, 0.0938752 , 0.09794909, 0.09916293,
       0.08562542, 0.08577747, 0.08789621, 0.10070733, 0.08689395,
       0.09092326, 0.09552852, 0.10527719, 0.0907345 , 0.09294468,
       0.09311322, 0.09232195, 0.08367592], dtype=float32), array([[[[ 0.02651967],
         [-0.01443607],
         [ 0.0037062 ],
         ...,
         [ 0.00849015],
         [-0.00847118],
         [ 0.01316258]],

        [[-0.0095624 ],
         [-0.0435543 ],
         [-0.02083576],
         ...,
         [-0.00106121],
         [-0.00328788],
         [-0.00516389]],

        [[-0.01303748],
         [-0.00227476],
         [-0.01256971],
         ...,
         [ 0.01326814],
         [-0.0071309 ],
         [-0.00492634]]],


       [[[ 0.02196932],
         [-0.04434758],
         [-0.00237142],
         ...,
         [ 0.01623981],
         [ 0.04422484],
         [-0.01245989]],

        [[ 0.02005913],
         [-0.00628811],
         [-0.00152609],
         ...,
         [-0.03663065],
         [ 0.00413829],
         [-0.0037166 ]],

        [[-0.0268073 ],
         [-0.03232037],
         [-0.02288394],
         ...,
         [ 0.00820018],
         [ 0.02535353],
         [ 0.02380873]]],


       [[[ 0.02424633],
         [-0.01387674],
         [-0.0125266 ],
         ...,
         [-0.01723096],
         [ 0.03598867],
         [ 0.0100385 ]],

        [[-0.03210822],
         [-0.00398432],
         [ 0.02415124],
         ...,
         [-0.01575413],
         [-0.00753597],
         [ 0.00043616]],

        [[ 0.00042632],
         [-0.01098749],
         [ 0.0154689 ],
         ...,
         [-0.02738606],
         [ 0.00842641],
         [ 0.00371785]]]], dtype=float32), array([[[[ 0.03455798,  0.03711104, -0.05294606, ..., -0.04899184,
           0.06737494,  0.03032672],
         [ 0.07322004,  0.04414291, -0.01728762, ...,  0.01750918,
           0.0647491 ,  0.03398049],
         [ 0.04905171, -0.03523773, -0.03832442, ..., -0.04244888,
          -0.04091631,  0.02396264],
         ...,
         [ 0.01430583, -0.0446572 , -0.05251606, ...,  0.01286927,
          -0.05024354,  0.04529048],
         [-0.06075773,  0.01044513,  0.04382623, ..., -0.01042114,
          -0.01274935,  0.02354065],
         [ 0.02082643, -0.03455442,  0.03429671, ..., -0.00284031,
          -0.03414168, -0.05315625]]]], dtype=float32), array([0.9867752 , 1.0051266 , 0.9976025 , 0.9948937 , 0.9907363 ,
       1.0054249 , 0.99197716, 0.9974266 , 0.9916972 , 0.9986244 ,
       1.009216  , 0.9937281 , 0.99291253, 1.0004776 , 1.0274335 ,
       1.0106415 , 0.99232614, 0.9948568 , 1.0368282 , 1.0201    ,
       0.98771924, 1.0074781 , 0.99170977, 0.98558784, 0.9972251 ,
       0.99862015, 0.97797775, 0.99695826, 1.0199754 , 0.9853746 ,
       1.0079173 , 1.0069578 , 1.0005649 , 0.9803692 , 0.9981175 ,
       1.0054494 , 0.9847323 , 0.98663104, 1.0181307 , 1.0034723 ,
       1.0068748 , 1.009383  , 1.0087925 , 1.0034993 , 0.99181753,
       0.9838958 , 0.9922033 , 0.9971229 , 1.0200835 , 1.0004942 ,
       1.0086178 , 1.0064683 , 1.0060223 , 1.0266216 , 1.0256131 ,
       0.99487036, 1.0004538 , 1.0168777 , 1.0118358 , 0.98834133,
       0.9957196 , 0.99674916, 1.0041771 , 0.99764174, 0.99303734,
       1.0097945 , 1.020429  , 1.005738  , 1.0076839 , 0.9965205 ,
       0.9947949 , 0.99232894, 1.0106494 , 1.0031058 , 0.99696875,
       1.0033654 , 1.0086638 , 0.99856406, 0.9923539 , 0.98477775,
       1.0060534 , 0.9999783 , 1.0109072 , 0.9913308 , 1.0196522 ,
       0.99534386, 0.9954738 , 0.97294474, 1.0022241 , 1.0042344 ,
       1.000904  , 1.0029482 , 0.98423815, 1.009396  , 1.0028762 ,
       1.0010982 , 1.0068843 , 1.0138075 , 1.0039102 , 0.9879842 ,
       0.99366313, 1.005598  , 1.0129386 , 0.9983125 , 0.9882886 ,
       1.0003484 , 0.99789184, 0.99859935, 0.98309416, 1.0267764 ,
       1.0079669 , 0.9949343 , 0.9987796 , 1.0033784 , 1.0139598 ,
       1.0027754 , 0.99722093, 1.0026733 , 1.015184  , 1.000935  ,
       0.9966937 , 0.97870165, 1.0175413 , 1.0100138 , 1.0015525 ,
       0.98072475, 1.0035238 , 1.0147702 , 1.0032573 , 1.0089648 ,
       1.0309236 , 1.0070369 , 0.99261636, 0.9914308 , 0.98914135,
       0.983753  , 1.0070332 , 1.0049565 , 0.9895723 , 0.9772481 ,
       1.0190561 , 0.98301685, 1.0201336 , 0.9828603 , 0.9991121 ,
       1.0014266 , 1.0019822 , 1.0122955 , 1.0053036 , 0.99058706,
       0.9973012 , 0.9976882 , 1.0219146 , 0.99834806, 0.99641013,
       0.99692583, 1.0030373 , 1.0386517 , 1.004965  , 0.9942293 ,
       0.97865546, 0.99724466, 1.0145786 , 0.98494905, 0.9977705 ,
       0.9958022 , 0.9855178 , 1.0004808 , 1.0194402 , 1.0071528 ,
       1.0081825 , 0.9787333 , 0.9870381 , 0.997296  , 0.9986512 ,
       0.99587905, 0.9879376 , 1.0092305 , 0.99255174, 0.9823991 ,
       0.9893204 , 1.0244962 , 1.017734  , 0.9979217 , 1.0337442 ,
       0.9871351 , 1.0253268 , 1.0057935 , 1.0222667 , 1.0309972 ,
       0.9807942 , 1.0092036 , 0.97720516, 0.99338466, 1.0071973 ,
       0.99745476, 0.97856325, 0.99267185, 1.0164518 , 0.98784727,
       0.9897306 , 1.0062934 , 1.0253745 , 0.980345  , 1.0224369 ,
       1.0079796 , 0.99775326, 0.97577053, 0.9935538 , 0.9913841 ,
       0.9818896 , 0.9976996 , 0.99380726, 1.0145265 , 1.0223742 ,
       1.0032407 , 0.99930346, 0.9907698 , 1.0016435 , 0.99252355,
       0.9867934 , 1.0036784 , 0.9861951 , 1.0008482 , 1.0069486 ,
       0.9986125 , 0.99817455, 1.0226989 , 0.9986952 , 0.9834961 ,
       0.9996846 , 1.0065695 , 0.97981983, 1.0467306 , 0.9944039 ,
       1.0142058 , 0.9951817 , 0.98571044, 1.0145673 , 0.993712  ,
       1.0034769 , 1.0075454 , 1.0064696 , 0.9866627 , 0.99959034,
       0.99524224, 0.99310637, 1.0145056 , 0.9926516 , 1.0126498 ,
       1.0258552 , 1.0012153 , 1.03472   , 0.9746586 , 0.9911207 ,
       0.9957937 , 1.001421  , 0.9989989 , 1.0112852 , 1.0016925 ,
       0.9896697 , 0.99567676, 0.99604464, 0.99151397, 1.0019569 ,
       0.9954586 , 1.0009195 , 1.0041126 , 1.0071473 , 0.98051465,
       1.0044652 , 0.99704516, 0.988561  , 1.0042058 , 1.0061504 ,
       1.0132319 , 0.99730766, 0.99688363, 1.0092708 , 1.0234573 ,
       0.9955144 , 0.9986149 , 0.9915956 , 0.98359543, 0.99952024,
       0.9989048 , 1.0096762 , 0.9891159 , 0.9948596 , 1.0078872 ,
       0.98613286, 1.0139829 , 0.9937147 , 1.0105765 , 0.98662025,
       0.9932789 , 1.0258961 , 1.0020019 , 1.0048046 , 1.0066562 ,
       1.0083026 , 1.002749  , 1.0070175 , 0.998288  , 1.0246593 ,
       0.98855054, 0.97047573, 1.0017031 , 1.0091723 , 0.986817  ,
       0.9782102 , 1.0064167 , 1.0040888 , 1.009269  , 1.0062857 ,
       1.0159721 , 0.99728364, 1.0408174 , 0.99518436, 0.98627096,
       1.006462  , 1.0199369 , 0.9973272 , 1.0018797 , 0.9804794 ,
       0.9932692 , 1.002621  , 1.017399  , 0.98614454, 0.99599534,
       1.0064843 , 0.9834042 , 0.9997422 , 1.0080295 , 1.0030793 ,
       1.0036242 , 1.0050384 , 1.0037334 , 1.0416076 , 0.99985456,
       1.0082116 , 1.0030956 , 0.9903179 , 1.004471  , 1.011146  ,
       0.9986887 , 1.0246925 , 1.0090925 , 0.9971311 , 0.9895055 ,
       1.0111195 , 1.0033966 , 1.0163977 , 1.0011283 , 0.9967315 ,
       0.97739553, 0.99652046, 0.9928944 , 0.9864318 , 1.010701  ,
       1.0141292 , 0.99761546, 1.0007312 , 1.0179689 , 1.0195428 ,
       0.9888345 , 1.0017012 , 1.0145875 , 0.9850579 , 1.0013614 ,
       1.014754  , 0.99051344, 1.0050493 , 0.998379  , 0.9999394 ,
       1.0099894 , 0.9947008 , 1.0300534 , 0.9916259 , 0.99673533,
       1.0134758 , 0.98926824, 0.98778653, 0.9995773 , 1.0004405 ,
       0.9906687 , 0.99983436, 1.0070512 , 1.0040715 , 1.0066448 ,
       1.000737  , 0.9871227 , 0.99836797, 1.0130825 , 0.9840342 ,
       1.0380079 , 0.9682494 , 0.99599653, 0.99544424, 0.9885334 ,
       0.97841877, 0.9947491 , 0.9693992 , 0.99584574, 0.9993344 ,
       1.001575  , 1.0149916 , 0.9932627 , 1.0006467 , 0.9847915 ,
       0.9962921 , 1.0141438 , 1.0008012 , 1.0196854 , 0.983835  ,
       0.99407107, 1.0141262 , 1.0020252 , 0.9973708 , 1.0159132 ,
       1.003114  , 1.0365022 , 0.97760665, 1.0263091 , 0.99291986,
       1.0033276 , 1.009672  , 1.0062729 , 1.0197816 , 1.0103995 ,
       0.9792773 , 1.0297304 , 1.0009454 , 1.0240408 , 0.9969717 ,
       0.9929031 , 1.0038359 , 1.0265734 , 1.0098168 , 0.9984089 ,
       1.014786  , 1.0022827 , 0.9975681 , 1.0091934 , 1.0044495 ,
       1.0050367 , 0.9863025 , 1.0207939 , 1.0115966 , 0.9999838 ,
       1.0196136 , 0.9983473 , 0.9969389 , 0.9946922 , 1.006349  ,
       1.010722  , 0.9957827 , 0.9963445 , 0.9969164 , 0.99010336,
       1.0157548 , 0.99734527, 0.99867797, 1.013517  , 1.0120623 ,
       1.0008519 , 0.9924722 , 1.0028617 , 0.993765  , 0.98893535,
       0.9987171 , 1.0013249 , 1.0037644 , 1.0518132 , 1.0002277 ,
       1.0180877 , 0.9994599 , 0.99033827, 0.99903446, 0.98339206,
       1.0057031 , 1.0382739 , 0.99962765, 1.0022328 , 0.9952183 ,
       1.0203204 , 1.0155991 , 0.99708986, 1.0085006 , 0.98591363,
       1.0152458 , 1.007184  , 0.98253196, 0.99756396, 0.9984175 ,
       1.0082164 , 0.9816588 , 1.0005118 , 1.009008  , 1.0263804 ,
       0.990951  , 1.0064487 , 0.99515367, 0.99194247, 0.9922107 ,
       0.988577  , 0.9996426 , 1.025071  , 0.99461526, 0.98068696,
       0.99768096, 0.9826201 , 0.98121756, 1.0051862 , 1.0062387 ,
       0.97935784, 1.0093685 , 0.9957514 , 1.00949   , 1.0169559 ,
       0.99456316, 1.000238  , 1.0218383 , 0.99150234, 0.9938202 ,
       1.0098375 , 0.9904964 , 1.0157443 , 1.0171311 , 0.9796469 ,
       0.9897702 , 1.01682   , 0.9969997 , 1.0048617 , 0.99071944,
       0.9979303 , 1.0170264 , 0.999453  , 0.9971468 , 1.0027176 ,
       0.9954378 , 0.9954509 , 1.0036064 , 1.002061  , 1.012353  ,
       1.0090429 , 1.0208749 , 0.99787295, 0.99479485, 0.996484  ,
       1.0045018 , 1.0307821 , 1.0035204 , 1.006117  , 1.0015734 ,
       1.0017173 , 1.0026097 , 1.0087487 , 0.99223745, 1.0068077 ,
       1.0008507 , 1.0054005 , 0.99866116, 0.99466616, 1.0122435 ,
       1.0109013 , 1.0133463 , 0.98665714, 1.0081885 , 0.9862664 ,
       1.0060501 , 1.000037  , 0.9998419 , 1.0023596 , 1.0006424 ,
       0.9987655 , 1.013747  , 1.0264297 , 0.9917437 , 1.033431  ,
       1.0067438 , 0.99428076, 1.0094101 , 1.0064815 , 1.0110993 ,
       0.9951239 , 0.9861234 , 0.9833829 , 1.0112649 , 0.98494375,
       1.0020353 , 0.9902362 , 1.0370166 , 1.0223845 , 0.9846637 ,
       0.990057  , 0.99364734, 0.99575365, 1.0054003 , 1.0010053 ,
       1.0165895 , 0.9985685 , 1.0163084 , 0.9948863 , 0.99903136,
       1.0080119 , 1.0280098 , 0.9932788 , 0.9855753 , 1.0063286 ,
       1.0155684 , 1.0189549 , 1.0267549 , 0.98044443, 0.9911662 ,
       0.97907037, 0.99977463, 0.99391955, 0.9862297 , 0.9958472 ,
       0.99080616, 1.0075675 , 1.0017221 , 1.0074904 , 1.0007933 ,
       0.9951081 , 1.0122647 , 1.0132223 , 0.9914349 , 1.0036101 ,
       0.9965312 , 0.9883154 , 1.0337138 , 1.0047684 , 0.98553973,
       1.0077375 , 0.98980546, 1.0109435 , 1.0206306 , 1.0008796 ,
       1.0166192 , 1.0069324 , 1.0116    , 0.97954524, 1.0061443 ,
       1.0062108 , 1.0045733 , 0.9936893 , 1.0170307 , 1.0042062 ,
       0.98574585, 1.0057198 , 0.9977585 , 0.9846611 , 1.008693  ,
       0.9781165 , 1.003786  , 0.98620737, 0.9868508 , 0.9928642 ,
       0.98435444, 0.9935215 , 0.9991225 , 1.0076402 , 0.9940156 ,
       0.9903048 , 0.98583406, 0.9923905 , 1.0030946 , 0.9935062 ,
       0.99583566, 0.99760675, 0.99534434, 0.9954699 , 1.0027037 ,
       1.00932   , 1.0083083 , 1.0111659 , 0.9741511 , 0.9925895 ,
       0.98337096, 1.0023965 , 1.0301865 , 1.004558  , 0.99145955,
       1.0176055 , 1.0011177 , 1.0112857 , 1.0102624 , 1.0088837 ,
       1.0071801 , 0.982713  , 1.0088876 , 1.0090027 , 1.0009776 ,
       0.98569435, 1.016709  , 0.990527  , 1.004794  , 1.0120014 ,
       0.9980022 , 1.0307802 , 0.9893032 , 0.992207  , 0.99416983,
       0.99391055, 0.9830607 , 1.01101   , 1.0110998 , 1.0293308 ,
       1.0079677 , 0.99852586, 1.0013213 , 1.0036931 , 0.9996326 ,
       0.99193   , 0.9911018 , 0.9961762 , 1.0105913 , 1.0075628 ,
       0.9741968 , 1.005188  , 1.0146497 , 0.987003  , 1.0009508 ,
       1.0022552 , 1.0041369 , 0.98277587], dtype=float32), array([-9.44124331e-05,  8.52257758e-03, -1.18513443e-02, -5.64121176e-03,
        1.29794301e-02, -2.24759541e-02,  2.30615726e-04, -3.52299996e-02,
        6.96881767e-03, -4.25959798e-03,  2.30217874e-02,  6.86817430e-03,
        8.31700803e-04, -2.37752427e-03,  7.58564053e-03,  2.15152334e-02,
       -1.43321659e-02,  9.28622857e-03, -1.26208495e-02, -1.89815909e-02,
       -1.54253412e-02, -1.54019343e-02, -1.29903257e-02, -1.44104743e-02,
       -8.86216760e-03,  2.09985022e-02,  1.10959541e-02,  1.80230848e-02,
        6.21248502e-03, -5.80753293e-03,  2.26242305e-03, -2.15473417e-02,
        1.36502339e-02, -2.14547571e-02,  2.30327547e-02, -6.53757155e-03,
       -1.24162398e-02, -1.03450418e-02, -4.86055017e-03, -3.74947907e-03,
       -5.48757752e-03,  2.52936557e-02,  3.24805523e-03,  7.05535058e-03,
        2.07279180e-03, -4.38745432e-02, -1.09419450e-02, -1.37715712e-02,
       -4.40102331e-02,  1.85565511e-03, -1.09046958e-02,  1.30598228e-02,
       -2.76585575e-02,  1.04907509e-02, -5.83930081e-03,  1.20055508e-02,
       -6.94097346e-03, -4.85388469e-03, -3.58091854e-03, -2.59379926e-03,
        4.48336452e-03,  1.20906364e-02, -1.41667873e-02, -1.17118582e-02,
       -5.76049715e-05, -5.28348656e-03, -1.20382644e-02,  1.53883342e-02,
        9.91454907e-03,  6.04829891e-03,  6.18222449e-03, -4.62239841e-03,
       -7.69262947e-03, -5.05628111e-03,  1.79659948e-02, -6.01475360e-03,
        1.27836820e-02,  3.63063090e-03,  3.61857237e-04, -2.11247001e-02,
       -2.54865680e-02,  2.76886672e-03,  8.33396916e-05, -4.47823480e-03,
        1.16337193e-02,  3.16982483e-03, -2.89934501e-03,  9.04732291e-03,
        9.63029638e-03,  9.96014662e-03, -1.79157927e-04, -1.76783111e-02,
       -8.35993886e-03, -6.84066396e-03, -5.16336272e-03,  7.88162556e-03,
        1.11931032e-02, -8.92417878e-03,  1.18589830e-02,  1.91591401e-02,
        1.99258374e-03,  2.05254601e-03, -1.64527260e-03, -8.13410059e-03,
       -4.44260845e-03, -8.36934894e-03, -2.46806219e-02, -2.14405768e-02,
       -1.22736450e-02,  2.51726573e-03,  3.59817315e-03, -2.02145670e-02,
        1.41968913e-02,  4.12734691e-03,  4.56286175e-03, -1.01432409e-02,
        9.95517988e-03, -1.71540733e-02,  7.55804963e-03,  1.20120309e-02,
       -9.64259729e-03, -1.71466954e-02, -1.69559401e-02,  3.09038535e-02,
       -1.57723296e-02, -1.41350245e-02,  3.27358721e-03,  2.57462952e-02,
        3.01097473e-03, -1.83700467e-05, -2.17389110e-02,  2.59105563e-02,
        3.39424564e-03,  3.34379124e-03, -9.67991352e-03, -1.94774512e-02,
        3.45075652e-02, -2.60480437e-02, -1.26667293e-02, -2.28804797e-02,
        2.55112797e-02,  9.34524182e-03,  5.87247871e-03, -1.21829780e-02,
       -1.26399100e-02,  1.27974367e-02,  2.28098640e-03, -1.89609900e-02,
       -2.53136009e-02, -8.36416148e-03, -1.41646974e-02, -2.01536771e-02,
       -1.70127600e-02, -1.85186211e-02,  6.80258963e-03,  1.89353507e-02,
        2.84438115e-03, -5.23306616e-03, -1.15214884e-02,  5.51761827e-04,
       -2.65257829e-03, -8.10580235e-03, -1.69698112e-02, -1.67693961e-02,
       -4.89012664e-03, -2.94849798e-02,  5.99859050e-03, -8.91163363e-05,
        7.08372006e-03, -1.57626439e-02,  3.54762785e-02, -2.29068939e-02,
        1.54741174e-02, -2.32543214e-03, -2.06384640e-02, -1.41741084e-02,
       -2.38133245e-03,  2.03532930e-02,  1.71696395e-03, -5.89456130e-03,
        9.62699670e-03, -1.41564002e-02, -4.76384535e-03, -1.57071408e-02,
       -1.83649939e-02, -9.99830384e-03, -8.59064050e-03,  1.20838853e-02,
       -6.91917911e-03, -1.04595879e-02, -7.84044247e-03,  2.27270871e-02,
       -1.14488285e-02, -6.93279924e-03,  1.45752467e-02, -5.03305299e-03,
       -2.04872194e-04, -4.68050223e-03, -2.01636199e-02, -1.39464810e-02,
        1.23102237e-02,  2.11706734e-03,  2.80711111e-02, -2.86843330e-02,
       -1.32493312e-02, -1.02187237e-02,  3.85048874e-02, -2.35029049e-02,
        6.38442929e-04,  1.32280653e-02, -2.01236885e-02, -9.98690259e-03,
       -1.20396120e-02, -9.59509239e-03, -2.58789901e-02, -1.64365098e-02,
        3.49218631e-03, -3.40343989e-03,  2.50176922e-03, -1.79315228e-02,
       -1.63423102e-02,  1.68394968e-02, -3.38995690e-03, -6.79040328e-03,
        2.41726097e-02,  8.37155059e-03,  6.71288790e-03,  3.52834314e-02,
       -1.65012404e-02, -1.29358638e-02,  3.36022712e-02, -2.41061579e-03,
       -5.95575199e-03, -1.38302632e-02, -2.48501077e-02, -1.34760505e-02,
       -1.84567925e-02, -1.47431763e-03, -2.93882620e-02,  6.44006254e-03,
       -8.01726151e-03,  3.26104797e-02,  1.54096959e-02, -1.07351784e-02,
        6.43105945e-03, -2.01234221e-02,  2.05544923e-02,  1.12537760e-03,
       -1.25650736e-02, -5.44374902e-03, -1.12147462e-02, -5.59560210e-03,
       -1.54450489e-02,  7.55302282e-03, -7.02426536e-03, -2.09896229e-02,
        1.22737326e-03,  5.68244746e-03,  1.03207724e-02,  1.89442793e-03,
       -1.54011874e-02, -1.01685924e-02, -1.70872435e-02, -1.90872885e-02,
        8.42445903e-03,  1.99155435e-02, -3.50026507e-03,  6.37510279e-03,
       -7.10264081e-03,  2.37125810e-03,  1.11230090e-02, -4.40474506e-03,
       -8.42340849e-03, -9.26252548e-03, -3.64573039e-02, -5.97042125e-03,
       -9.53569077e-03, -4.47179265e-02,  6.87622931e-03, -4.41452041e-02,
       -1.97804766e-03, -9.21560568e-04,  1.68701843e-03, -1.46654965e-02,
       -3.32379565e-02, -5.87811274e-03, -1.59611609e-02, -6.18481170e-03,
       -5.65255200e-03, -1.69422496e-02, -7.17845140e-03,  3.03293653e-02,
        2.24657427e-03, -1.19321607e-02, -7.31245382e-03, -3.93791124e-03,
        1.35231623e-03,  1.68551579e-02, -8.52916203e-03,  4.52066539e-03,
       -1.71224084e-02, -6.47540623e-03, -4.85932641e-03, -3.04281134e-02,
        3.88933253e-03, -2.04696283e-02, -2.49505360e-02,  1.45798817e-03,
        1.17266458e-02, -7.04024266e-03,  6.70919986e-03,  2.35164817e-03,
        6.97945664e-03,  6.95629371e-03,  4.71045030e-03, -8.25544633e-03,
       -1.92750748e-02, -1.49899861e-02,  1.97861791e-02, -1.45587353e-02,
       -8.99790507e-03,  1.10443877e-02, -2.81943828e-02, -1.17096305e-02,
        2.42253840e-02,  1.92715526e-02,  5.19850990e-03,  1.05602806e-03,
       -8.51209927e-03, -2.25821584e-02, -1.90548263e-02, -3.22444225e-03,
       -1.84251956e-04,  2.40760855e-02, -7.67535064e-03, -5.29395463e-03,
        1.46895042e-03, -1.88019611e-02, -4.51916736e-03, -8.09097663e-03,
        2.42503770e-02, -2.32770536e-02,  1.54201202e-02, -1.24493316e-02,
        8.31643399e-03,  2.56662071e-03,  5.20473439e-03, -1.40377376e-02,
        3.29187512e-02, -6.37168624e-03,  1.21872583e-02,  2.43422408e-02,
        1.70138776e-02,  3.26833278e-02, -1.23325428e-02, -1.61515977e-02,
       -6.95045223e-04, -1.11509999e-02, -1.00609111e-02,  6.33476768e-03,
       -7.41354655e-03, -1.38666630e-02,  1.54323950e-02, -1.36575187e-02,
        1.75598562e-02,  5.28241415e-03, -1.51969641e-02, -1.20509248e-02,
        8.58854875e-03,  1.33421440e-02, -2.60084961e-02, -1.10090226e-02,
       -6.55517960e-03, -3.35533544e-02, -5.76363504e-03,  3.27399024e-03,
       -3.02446121e-03, -3.30069512e-02,  6.39242586e-03, -1.14105009e-02,
       -3.64533514e-02, -2.20785495e-02,  2.69633811e-02, -7.39396643e-03,
        4.22108918e-03, -2.74040047e-02, -5.08516654e-03, -1.38090402e-02,
        1.92733929e-02, -1.99851487e-02, -1.93751473e-02, -4.66046110e-03,
       -7.37325056e-03,  1.17658861e-02, -4.49212873e-03, -2.10696403e-02,
        2.72447220e-03, -1.74194630e-02, -2.05754465e-03,  6.65424066e-03,
       -2.39380971e-02, -2.17180466e-03,  1.42726395e-02,  3.84481251e-02,
       -1.05006350e-02, -9.40387975e-03, -1.13499945e-03, -2.28830334e-02,
       -1.16506824e-02, -1.13935554e-02, -1.05387354e-02, -1.95317250e-02,
        8.98000039e-03, -3.35183144e-02,  4.92347172e-03, -2.32309531e-02,
        3.36524472e-03, -1.87248178e-02,  5.78244729e-03, -4.14923541e-02,
       -3.54272197e-03, -3.17577049e-02, -1.87729336e-02, -1.68089774e-02,
        6.52810419e-03, -8.85981694e-03, -5.56290597e-02, -1.25906337e-02,
       -8.13185645e-04,  1.97206922e-02, -1.78081691e-02,  2.25124918e-02,
       -3.20330425e-03, -4.55169082e-02, -9.14808479e-04, -1.79897137e-02,
        1.09358383e-02, -6.31406321e-04, -1.99359003e-02, -5.32078044e-03,
       -1.49298161e-02,  2.50329915e-03, -1.00743799e-02,  6.93290029e-03,
       -1.20901996e-02,  9.12519544e-03, -9.60550085e-03, -3.21806781e-03,
        1.65773388e-02, -7.66833918e-03, -1.65524893e-02, -1.15576219e-02,
        5.54861408e-03, -3.04649528e-02,  2.92264801e-02, -4.14808141e-03,
       -6.61669718e-03,  2.37071179e-02,  1.13502378e-02, -1.78147200e-03,
       -2.51915958e-03,  5.08288946e-03,  2.58143395e-02,  4.80297767e-03,
       -2.91736107e-02, -1.19684963e-02, -1.34665158e-03, -2.03543510e-02,
       -2.02918821e-03,  6.12418808e-04, -6.09785272e-03, -1.81979463e-02,
       -8.63381289e-03, -3.50706652e-02,  1.26115733e-03, -1.67737976e-02,
       -1.51015036e-02, -2.13658474e-02, -9.50971060e-03,  5.99540304e-03,
       -1.29661774e-02, -2.63355076e-02, -4.29865578e-03, -3.91825149e-03,
        2.25519482e-02, -3.07442024e-02, -3.37952189e-03, -8.72932747e-03,
        1.35297747e-02, -1.88164681e-03, -5.91066573e-03, -1.25867259e-02,
       -1.38212889e-02, -2.67238654e-02, -5.61193703e-03,  4.45933528e-02,
       -9.74366348e-03, -1.77669972e-02,  8.83959420e-03, -3.75276320e-02,
       -1.26186106e-02,  1.23780854e-02,  2.16558948e-02, -9.39730089e-04,
       -1.61086060e-02, -1.19247325e-02, -6.66177180e-03,  2.26788390e-02,
       -4.37275320e-03, -1.59323029e-03,  7.20689120e-03, -8.55469890e-03,
        1.70864929e-02, -1.21769346e-02,  3.90187018e-02, -3.06170341e-03,
       -3.35366582e-03, -4.31296322e-03, -1.19831301e-02, -1.18828919e-02,
        4.76463791e-03, -1.33749684e-02, -1.91686174e-03,  1.40528362e-02,
        1.12459157e-03, -2.76720850e-03, -1.51308915e-02,  4.74736607e-03,
       -2.70598941e-02, -6.67463895e-03, -1.88422035e-02,  7.71951023e-03,
       -1.86755061e-02,  4.27710526e-02,  1.39050242e-02,  4.01992351e-04,
       -2.14552917e-02, -1.21168224e-02, -3.20594013e-03, -3.42905745e-02,
       -1.22475317e-02, -2.19987184e-02, -1.58732235e-02, -3.79297649e-03,
       -1.48593923e-02,  1.57931428e-02, -3.67814465e-03,  2.39734328e-03,
       -7.66467070e-03, -1.28794450e-03,  7.65390834e-03, -1.39745064e-02,
       -9.98250674e-03,  5.87866642e-03,  1.45953204e-02, -6.88663404e-03,
       -4.08630706e-02, -6.10468956e-03,  7.93415308e-03,  1.53402602e-02,
        1.23034334e-02,  6.58284780e-03,  1.59709267e-02,  1.94481481e-02,
        3.72533090e-02, -1.44440541e-02,  1.65335163e-02, -1.24576911e-02,
        3.03288433e-03, -9.61033336e-04, -1.76122990e-02, -7.45303975e-03,
       -4.41081710e-02, -3.48165003e-03, -6.56535057e-03, -2.62779999e-03,
       -2.47612800e-02, -2.07115384e-03, -8.95548239e-03, -4.01425436e-02,
        1.19338831e-04,  1.07909087e-04,  1.11963460e-02, -1.60530058e-03,
        3.44990008e-02, -9.17258393e-03, -1.04680359e-02, -3.76402773e-03,
       -2.13400903e-03,  1.65306609e-02,  2.01702192e-02, -2.19796086e-03,
        1.08758956e-02, -7.30166631e-03,  7.29896873e-03, -4.45642509e-03,
        3.52023775e-03,  4.20462247e-03, -5.18367393e-03,  1.05429869e-02,
       -2.02745553e-02,  1.45654089e-03, -9.80544137e-04, -3.85677977e-03,
       -1.28537761e-02,  9.30339750e-03,  1.91518886e-03, -6.29294990e-03,
       -3.62005550e-03, -1.55169852e-02, -9.73775052e-03,  1.82021521e-02,
       -3.29679400e-02, -1.09574730e-02, -9.68975201e-03, -6.94130547e-04,
       -2.75250822e-02, -2.29518563e-02,  4.10141423e-04, -1.37812532e-02,
       -8.95152707e-03, -1.76227950e-02, -1.19169513e-02,  1.69301871e-02,
        8.90703779e-03, -1.90382954e-02, -8.76691006e-03,  1.33817764e-02,
       -4.80215065e-03, -8.23688973e-03,  8.27071536e-03,  1.25581827e-02,
        4.32875520e-03, -1.32177975e-02, -9.86177474e-03,  3.13689746e-02,
       -1.70584805e-02,  3.03978696e-02, -1.66553184e-02,  1.59472302e-02,
       -6.45056181e-03, -5.64408395e-03,  2.74889246e-02, -1.84825808e-03,
        2.70220247e-04, -1.18431617e-02, -3.41509352e-03,  9.91673861e-03,
        1.22557650e-03, -2.35341750e-02, -3.45577695e-03, -1.65156946e-02,
       -5.83559275e-03, -2.07163603e-03,  1.22960545e-02, -1.67247001e-03,
       -1.25271957e-02, -2.47027812e-04, -1.28461868e-02, -2.53844447e-02,
        5.07745938e-03,  2.32674107e-02, -1.64007228e-02, -8.39120615e-03,
       -1.20966276e-02,  1.61447152e-02, -1.38616432e-02, -8.33627116e-03,
        2.61624865e-02, -1.02726072e-02, -2.70616710e-02,  4.38601058e-03,
        9.70716868e-03,  2.96421852e-02, -1.21998172e-02, -1.11361342e-02,
       -1.14802178e-02, -3.88769135e-02, -1.20895291e-02, -1.21980775e-02,
        4.44141310e-03,  8.10620561e-03,  1.18335336e-03, -3.86749930e-03,
       -1.22931134e-02,  2.26443857e-02, -2.33554398e-03,  2.88201962e-03,
        5.85817173e-03, -3.15497257e-02, -3.25335260e-03,  1.15974052e-02,
       -4.50418098e-03,  3.00896214e-03, -1.92844914e-03,  2.35580634e-02,
       -1.22277848e-02, -1.22897103e-02, -1.33758103e-02,  5.38086798e-03,
        6.81437203e-04, -1.79415531e-02, -1.15028368e-02, -2.71268375e-03,
        4.89975931e-03,  7.83726852e-03, -1.41404225e-02,  1.96088711e-03,
        8.29954259e-03, -3.52640892e-03,  1.66924726e-02, -8.23379867e-03,
        1.46409748e-02, -2.38320511e-03,  3.08542904e-02,  2.97579803e-02,
        2.09268602e-03, -1.46042453e-02, -4.50161099e-03, -1.02516264e-03,
        6.77410141e-03, -2.61997860e-02, -3.14545371e-02, -1.56998858e-02,
       -1.60249062e-02, -2.61091813e-02,  1.83900483e-02, -1.23768738e-02],
      dtype=float32), array([-0.02289619, -0.02683974,  0.01671984,  0.02736067, -0.04368705,
        0.04861157, -0.02531791, -0.03546869, -0.02285626,  0.04044374,
       -0.02531784,  0.02225057, -0.01434097,  0.03581635,  0.00377554,
       -0.00540664, -0.00423612, -0.02965992,  0.0308008 ,  0.0588294 ,
        0.01847226,  0.07483034,  0.0105113 ,  0.01375797, -0.02996026,
       -0.05522482, -0.03688163,  0.01175884,  0.09922799,  0.02352441,
        0.00653463, -0.01868698, -0.02813933,  0.03231008, -0.03484157,
        0.01673974,  0.00940126, -0.02294567,  0.05470404, -0.00407986,
       -0.03918758,  0.01375534, -0.04107135,  0.02721986, -0.03344116,
        0.06955046, -0.0383522 ,  0.03569282,  0.05931164,  0.00735325,
        0.03931314, -0.01871883,  0.01426407,  0.00811926,  0.01376382,
        0.0254054 ,  0.04028351,  0.04824225,  0.04697283, -0.00199889,
       -0.04079486,  0.01061543,  0.06253867,  0.02883735,  0.00764685,
        0.02870792,  0.03122992, -0.03805687, -0.03843439, -0.03138087,
       -0.02612518,  0.03723305, -0.02018984,  0.03135929, -0.00788717,
        0.0626312 , -0.03897117,  0.00587809, -0.03665663,  0.03582384,
        0.04650654,  0.00314839,  0.01326849, -0.02518306, -0.00522379,
       -0.02040818, -0.01596696, -0.00366422,  0.01935038, -0.02280759,
        0.03015191,  0.05000192, -0.00394203, -0.02654431, -0.00197698,
        0.03722806, -0.04701782, -0.00800591, -0.04238601, -0.04824225,
       -0.02356198,  0.00169615,  0.01670365, -0.0032264 ,  0.02133086,
       -0.00849998,  0.02510603,  0.03378193,  0.05201672,  0.05448092,
       -0.03561903,  0.02661719, -0.01965742,  0.01961778,  0.01450301,
        0.04072182,  0.02457824,  0.02730412, -0.02569272, -0.03541544,
       -0.04064803,  0.04582574,  0.03684285, -0.02834328,  0.01504141,
        0.01385584, -0.02478697, -0.03040607, -0.00228297,  0.05594734,
        0.02528865, -0.0272895 , -0.02112567, -0.01005137, -0.01327117,
        0.04357946, -0.03840563,  0.06313311, -0.01936092,  0.04447342,
       -0.02500429, -0.01602256, -0.01293409,  0.03283275,  0.04180861,
       -0.00832925, -0.00413499,  0.02663258,  0.00826582,  0.02002761,
        0.04293301,  0.0390706 ,  0.03624729, -0.03083016, -0.01284731,
       -0.03219825,  0.00063665,  0.05129379,  0.05783209,  0.0475739 ,
        0.02348562, -0.02558125,  0.01441338, -0.02870107,  0.03369908,
        0.02475974,  0.06598873, -0.02909433,  0.03925646,  0.02335086,
       -0.01739762, -0.0037902 , -0.01251736, -0.0198291 , -0.02141674,
        0.01620645,  0.00693381,  0.00888601, -0.02892693,  0.03133829,
        0.0106432 ,  0.03514999,  0.00502039, -0.04330939,  0.02280961,
       -0.04595032,  0.01216129, -0.01393127,  0.03514898,  0.05585082,
        0.04989457,  0.01928672,  0.04461744,  0.00178547, -0.00985717,
       -0.01491723, -0.00317293, -0.00909501,  0.0678691 ,  0.02848424,
        0.02049595,  0.00917137, -0.02920568,  0.03280567,  0.03695603,
        0.0419355 , -0.04599314,  0.03128592, -0.00344467,  0.0328511 ,
        0.03444195,  0.04251899,  0.01574267,  0.01891394,  0.02486677,
        0.03335261,  0.04416376, -0.02719542, -0.00573677,  0.06086358,
        0.02740938, -0.03072759,  0.03883949, -0.0303365 , -0.02355554,
        0.03174197, -0.03242943, -0.05295942,  0.03712492,  0.0358427 ,
       -0.03574777, -0.01277647,  0.01720114,  0.03630397,  0.03144111,
       -0.02812001, -0.02592153, -0.02183866, -0.00335141, -0.025786  ,
        0.02417943, -0.0245634 , -0.03410985,  0.01371655,  0.00623826,
        0.02728956,  0.01856296,  0.00089139,  0.01018181,  0.01799971,
        0.02388948, -0.0481209 ,  0.02695544, -0.04803783,  0.02759532,
        0.03571514,  0.03918252,  0.02229266,  0.0018366 ,  0.04824248,
        0.00833275,  0.03643944,  0.01026518,  0.0470131 ,  0.02740913,
       -0.02283888, -0.02970771, -0.00674752,  0.01394011, -0.03609684,
       -0.04659865,  0.01086794, -0.01576332,  0.0063551 ,  0.03653258,
        0.03043473,  0.03838354,  0.0258494 , -0.02611318,  0.03506596,
        0.0175378 , -0.03126886,  0.00342541, -0.04715032,  0.0698823 ,
       -0.02115589,  0.0260937 , -0.0118182 ,  0.02462044,  0.03154021,
        0.02141258, -0.0240077 , -0.04106304,  0.02477222,  0.01462381,
        0.04494511,  0.03063777, -0.04961748,  0.03941168, -0.0093587 ,
        0.01777611,  0.03132569, -0.03442933, -0.01145048,  0.05654481,
        0.04580744,  0.04311367,  0.04044954, -0.02289715, -0.02470687,
        0.0541103 , -0.04661343, -0.02838633, -0.03205664, -0.01254173,
        0.02884435, -0.02037516,  0.04467883, -0.01379798,  0.03587314,
       -0.03457959, -0.02300812,  0.02781985,  0.01080914, -0.00194438,
       -0.02839359, -0.03028265, -0.00763236, -0.00186798,  0.05073592,
        0.04142406,  0.03938495,  0.03148133, -0.04371325,  0.04220859,
        0.04356065,  0.05434372,  0.05305437,  0.05082679,  0.04923553,
        0.01636672,  0.07544752, -0.04003667,  0.02730395, -0.0240675 ,
       -0.01285948,  0.03906022,  0.04759313, -0.0371974 ,  0.03908674,
        0.00854256, -0.03707471, -0.01365569, -0.01885496,  0.04465117,
        0.0397538 ,  0.01011925, -0.01697307, -0.01313354,  0.0354882 ,
        0.01266809,  0.02816787, -0.0571379 ,  0.00216677, -0.05074263,
       -0.00377811, -0.01200839,  0.05413774, -0.02170707, -0.03242008,
        0.07165719,  0.0122634 , -0.02799158,  0.04515254,  0.04080011,
       -0.02324448,  0.0032067 ,  0.0486742 ,  0.02450041, -0.02172871,
        0.02145292,  0.01582583, -0.00855116,  0.00255184,  0.02284655,
       -0.01900345, -0.01916549,  0.01113454, -0.02015087,  0.03704922,
        0.04433654,  0.01113913,  0.0440811 ,  0.02055433, -0.02523855,
        0.00724476,  0.02229164,  0.04940423,  0.02584909,  0.02455354,
       -0.00536061,  0.06093556,  0.03516302,  0.00912571,  0.01582215,
        0.02106912,  0.01268828,  0.02111556,  0.03245621, -0.02500832,
        0.0110335 ,  0.03585297, -0.04418701, -0.00417556,  0.00369091,
        0.03446621,  0.03599665,  0.02843292, -0.01492858,  0.03395313,
       -0.0504631 ,  0.05878915,  0.08077832,  0.04390289,  0.01298906,
        0.03566332,  0.05649639,  0.04590665,  0.00521989, -0.02030201,
        0.00677051,  0.00443248, -0.03907181,  0.01115287, -0.01117288,
       -0.02503243, -0.03367778,  0.02487328,  0.04329837,  0.04153289,
        0.05486692, -0.0119004 ,  0.04732603,  0.01722205,  0.01688588,
       -0.00897012, -0.05620045,  0.03634049,  0.046409  ,  0.02553729,
        0.0162713 , -0.01766476, -0.01837719,  0.05552018, -0.00486411,
        0.01771911,  0.01655239, -0.01010011, -0.04698748,  0.02935485,
        0.05923752, -0.02488514, -0.02688334,  0.02148991, -0.01656133,
       -0.01685048, -0.02822386, -0.0354687 ,  0.0005302 ,  0.0233058 ,
        0.00705501, -0.02657293, -0.00071113,  0.04842527, -0.04571965,
        0.02526075,  0.00395371,  0.00782106, -0.00897991, -0.01694462,
        0.05508405,  0.06511047, -0.02514713, -0.0348058 , -0.01363133,
       -0.00333658,  0.02793742,  0.07309997, -0.05007337, -0.01024882,
       -0.02394303,  0.0419155 , -0.01322445,  0.08032976, -0.04109702,
       -0.03529502, -0.01325222,  0.06613235,  0.0142266 ,  0.02361948,
        0.04872814, -0.02265682,  0.06897131, -0.00239437,  0.02558843,
        0.04544698, -0.04221835,  0.0158812 , -0.00816082,  0.02245665,
       -0.03672587,  0.02727912, -0.04325899,  0.03335324, -0.05066137,
       -0.03320069,  0.00528028,  0.04030948, -0.02554578,  0.02127253,
        0.01777241, -0.01326332,  0.0434988 , -0.01979531,  0.06945505,
        0.03940016,  0.02768212,  0.02750761,  0.01946458,  0.00579074,
        0.04268698, -0.03424594,  0.03459991, -0.07914907, -0.03564966,
       -0.01725983,  0.02349816,  0.05643617,  0.03123143,  0.04349054,
        0.03461098,  0.04843663, -0.00111898, -0.0033076 , -0.02064892,
       -0.07843701,  0.03395006,  0.01456803,  0.04989763,  0.01963606,
       -0.08516935,  0.03573845,  0.03658113, -0.01150016, -0.04083919,
        0.00992097,  0.05331875,  0.04168659, -0.03541939,  0.03652706,
       -0.00040427,  0.01503248,  0.0004734 , -0.00926852, -0.04584495,
        0.0387407 , -0.01219401,  0.00898092,  0.03152629, -0.00236719,
        0.0302541 , -0.01565488,  0.06285841,  0.04059723,  0.01884263,
       -0.03300627,  0.01633256,  0.04346706,  0.04180554,  0.00858692,
        0.03811187, -0.02814679, -0.01461813,  0.03166023,  0.00841814,
        0.0210038 , -0.05336886,  0.0224942 , -0.01459242, -0.01423465,
       -0.03509352, -0.02054481,  0.01598816,  0.03221665, -0.03921098,
       -0.00753206, -0.02020678, -0.03234971, -0.00724371, -0.02314726,
        0.00850184, -0.01137344,  0.01992048, -0.00311122,  0.01409987,
        0.06169995,  0.00726916, -0.04004717,  0.0648519 ,  0.04161039,
       -0.03891453, -0.01793795,  0.02540006, -0.02436168, -0.02851228,
       -0.05247134,  0.00553487, -0.01848394, -0.01703182,  0.01567195,
       -0.05034507,  0.00106849,  0.05890434, -0.03679333, -0.0193128 ,
        0.05164286,  0.0369675 , -0.00713674,  0.02673157,  0.00592155,
       -0.03189163,  0.00222561,  0.00447373, -0.02842626, -0.03280194,
       -0.02116732,  0.00768385, -0.02961396,  0.04217665, -0.05170424,
       -0.01076524,  0.02217826, -0.04323936, -0.04302406, -0.0126469 ,
       -0.02967028, -0.05954419, -0.01150464, -0.01527973,  0.0070052 ,
       -0.01560121,  0.03645447, -0.01504443, -0.02037303, -0.02855441,
        0.01904139, -0.01407835,  0.01271213,  0.01750738,  0.02413699,
       -0.04000544, -0.03878981, -0.02945291, -0.02790253,  0.04077819,
        0.00240612,  0.04403849,  0.03382857, -0.04700575,  0.00646946,
       -0.01980136, -0.0358686 , -0.01569386, -0.05384672, -0.02175484,
       -0.01576131,  0.06581575, -0.01280084,  0.03406417,  0.04386207,
        0.00899538, -0.01697104,  0.0274158 , -0.03299418,  0.03582902,
       -0.04148336, -0.02237431, -0.00816278,  0.01227264, -0.01644501,
        0.03636578, -0.02186422, -0.02915399,  0.00409836, -0.04097011,
       -0.0131837 ,  0.0390957 ,  0.02766975,  0.04276761,  0.03754843,
        0.02031676,  0.0027302 ,  0.0158552 , -0.04091004, -0.01867507,
       -0.02764648,  0.03699525, -0.05786959,  0.00795896,  0.04239849,
       -0.02686311, -0.02552545,  0.01415526, -0.03662293,  0.0150042 ,
       -0.05792632,  0.00201573, -0.02056208,  0.05309883,  0.00010669,
       -0.01984856,  0.0728321 ,  0.05267823,  0.02006401,  0.02729097,
       -0.02026785,  0.0374139 , -0.05580291], dtype=float32), array([0.08923078, 0.103531  , 0.08696622, 0.08735144, 0.09927578,
       0.09481844, 0.09412281, 0.10557707, 0.09634709, 0.10346712,
       0.09438972, 0.09238928, 0.09865256, 0.11522648, 0.09656632,
       0.09456822, 0.08866816, 0.09148376, 0.09920017, 0.10361163,
       0.09566501, 0.12455579, 0.097578  , 0.08711649, 0.08747435,
       0.10457531, 0.0882944 , 0.08390205, 0.11834846, 0.08828121,
       0.08842982, 0.08473416, 0.0914448 , 0.09473749, 0.089076  ,
       0.09120221, 0.08916674, 0.08881656, 0.10192769, 0.08441223,
       0.09174131, 0.08759488, 0.09825391, 0.09429524, 0.08751518,
       0.13659593, 0.09844305, 0.10983387, 0.10656308, 0.0892661 ,
       0.08749345, 0.09027896, 0.09962343, 0.09246529, 0.08946838,
       0.08950444, 0.09926992, 0.11606292, 0.09412146, 0.0855766 ,
       0.09372757, 0.08648692, 0.1046854 , 0.08928923, 0.08627744,
       0.09545269, 0.10276294, 0.08648483, 0.10209003, 0.0910266 ,
       0.09902368, 0.09098465, 0.08506998, 0.08855783, 0.08565149,
       0.11795751, 0.09552839, 0.09070647, 0.09544328, 0.09640875,
       0.10251124, 0.08730753, 0.09139718, 0.0887939 , 0.09170737,
       0.08493845, 0.09153704, 0.09237257, 0.08708247, 0.09340286,
       0.08646725, 0.10938381, 0.09002779, 0.08920407, 0.08589704,
       0.09056292, 0.11214664, 0.0840467 , 0.09351005, 0.12515305,
       0.08768691, 0.08646993, 0.08451016, 0.08988231, 0.09432098,
       0.084575  , 0.09634236, 0.10786921, 0.10113665, 0.09542546,
       0.10607368, 0.1148966 , 0.08564937, 0.08849508, 0.08666665,
       0.09732559, 0.08662535, 0.11044287, 0.09410161, 0.09445168,
       0.09013131, 0.10033529, 0.09944868, 0.09368683, 0.10659134,
       0.09490333, 0.08482808, 0.08693898, 0.08664617, 0.09525786,
       0.10379341, 0.08542237, 0.08587415, 0.08359212, 0.08341829,
       0.09793638, 0.09419265, 0.11874097, 0.08709489, 0.09337279,
       0.10910398, 0.08859943, 0.09261438, 0.11662345, 0.10400137,
       0.09682351, 0.08694001, 0.09833352, 0.09229293, 0.08812776,
       0.09501906, 0.09863293, 0.10222396, 0.09409126, 0.08716233,
       0.09367722, 0.08984945, 0.09137694, 0.12022843, 0.10239659,
       0.08743891, 0.09685239, 0.09358503, 0.08665828, 0.08817471,
       0.10023117, 0.09490071, 0.09726138, 0.08649418, 0.09340384,
       0.08629418, 0.09062761, 0.08609368, 0.08874501, 0.09747937,
       0.09801546, 0.08394685, 0.08765309, 0.08635398, 0.09957284,
       0.0934168 , 0.09261726, 0.08701877, 0.10896403, 0.09446765,
       0.10711796, 0.09147132, 0.09413148, 0.08822076, 0.10589368,
       0.0929926 , 0.10003243, 0.10037071, 0.08497304, 0.09495033,
       0.09350802, 0.08534845, 0.09043593, 0.10789779, 0.11823753,
       0.09206846, 0.08703855, 0.09850038, 0.08743662, 0.10426149,
       0.09072232, 0.10691784, 0.10107113, 0.09076292, 0.10684396,
       0.09008352, 0.10265781, 0.08526082, 0.0849039 , 0.09017386,
       0.08949038, 0.10704741, 0.08599022, 0.09003405, 0.11225493,
       0.09146318, 0.0965626 , 0.09959871, 0.08948892, 0.09390875,
       0.08660983, 0.10334861, 0.10337348, 0.09132212, 0.09363897,
       0.10451506, 0.08832533, 0.09728817, 0.09498631, 0.09443594,
       0.09365077, 0.08705425, 0.0995996 , 0.10244209, 0.09284942,
       0.08570334, 0.11559508, 0.09298523, 0.08442114, 0.08709676,
       0.10591353, 0.09556944, 0.08592805, 0.09187113, 0.09907542,
       0.0973502 , 0.09493814, 0.09563316, 0.11046007, 0.10485797,
       0.09321909, 0.09699103, 0.08786849, 0.08906882, 0.11332429,
       0.09154259, 0.09037284, 0.08505551, 0.10428408, 0.09233563,
       0.09772587, 0.09775216, 0.0916989 , 0.09029467, 0.09323812,
       0.108343  , 0.08349065, 0.09184823, 0.09052473, 0.09856789,
       0.10048711, 0.09257769, 0.11782089, 0.08893946, 0.10768867,
       0.09010229, 0.10968438, 0.09353595, 0.10418794, 0.10860673,
       0.08906907, 0.08486863, 0.08473703, 0.09355652, 0.08712836,
       0.09148495, 0.08907224, 0.10342991, 0.09237003, 0.08744185,
       0.09637151, 0.09325591, 0.09799494, 0.10098851, 0.0872114 ,
       0.09568858, 0.10432917, 0.10164683, 0.09275377, 0.10478821,
       0.09451256, 0.09732362, 0.10497209, 0.08787841, 0.08741955,
       0.09805225, 0.09237143, 0.09319717, 0.09672459, 0.08800312,
       0.09102765, 0.08712788, 0.09353075, 0.08902771, 0.10462511,
       0.08893765, 0.08882394, 0.09794159, 0.08894116, 0.08629871,
       0.08755293, 0.09894428, 0.09567491, 0.08744369, 0.08902328,
       0.11346303, 0.098765  , 0.09809689, 0.10211774, 0.10675377,
       0.09659062, 0.09342691, 0.09598571, 0.09470195, 0.09094408,
       0.10974307, 0.10855326, 0.09287267, 0.09598635, 0.09713785,
       0.08666918, 0.10485974, 0.09296993, 0.0907287 , 0.11287611,
       0.09302595, 0.09400743, 0.09549919, 0.08808874, 0.10763804,
       0.10389509, 0.08775084, 0.0817927 , 0.09108168, 0.09317422,
       0.09106514, 0.11036719, 0.11696117, 0.09843582, 0.09344683,
       0.0843731 , 0.0867538 , 0.10766471, 0.08851709, 0.0853788 ,
       0.12212326, 0.08952462, 0.0943747 , 0.11472594, 0.09164616,
       0.08705346, 0.08367998, 0.10851323, 0.09088431, 0.08606055,
       0.09396443, 0.11416341, 0.08876038, 0.08485574, 0.0889006 ,
       0.08620342, 0.09529813, 0.08721245, 0.09813591, 0.09841643,
       0.11531407, 0.08812916, 0.10927699, 0.09154168, 0.09444567,
       0.10014644, 0.09389986, 0.10549627, 0.09332754, 0.09066863,
       0.08737157, 0.10460288, 0.09377507, 0.08429407, 0.11658439,
       0.09411456, 0.0955488 , 0.10323033, 0.10405944, 0.08913162,
       0.10710101, 0.09369572, 0.1032691 , 0.10801804, 0.0908417 ,
       0.0937694 , 0.09619895, 0.09264095, 0.08992231, 0.10452483,
       0.0963116 , 0.10784116, 0.11949313, 0.09972744, 0.08855584,
       0.0922082 , 0.13104987, 0.10378775, 0.09153166, 0.08902239,
       0.09960499, 0.08997914, 0.09993157, 0.09296147, 0.08645622,
       0.09474501, 0.09566827, 0.0964002 , 0.09849275, 0.10187611,
       0.10570074, 0.08913893, 0.11611632, 0.09754173, 0.08550221,
       0.0870605 , 0.09435876, 0.09497481, 0.10281688, 0.09828761,
       0.09070908, 0.08863062, 0.09254416, 0.09716304, 0.08847935,
       0.09375439, 0.08704671, 0.08822469, 0.09194182, 0.09394981,
       0.10947354, 0.08929556, 0.09713728, 0.09618792, 0.09805642,
       0.08656062, 0.08319621, 0.09561151, 0.08673348, 0.09450419,
       0.08709437, 0.09223631, 0.0857848 , 0.11926702, 0.09496208,
       0.09169859, 0.08353624, 0.084275  , 0.08334869, 0.09050927,
       0.11687733, 0.12298395, 0.09584064, 0.08754003, 0.09339245,
       0.09411025, 0.10781287, 0.11112437, 0.1194161 , 0.08885349,
       0.08552669, 0.10709406, 0.08371782, 0.11543244, 0.09658962,
       0.09578116, 0.08296061, 0.12032154, 0.0903391 , 0.10808195,
       0.10280668, 0.09792516, 0.11431267, 0.08822789, 0.09767883,
       0.0906846 , 0.0939954 , 0.09308039, 0.08690803, 0.10026432,
       0.08633061, 0.09093451, 0.10433253, 0.09341866, 0.0974865 ,
       0.10224073, 0.08956213, 0.09633137, 0.09128472, 0.09152885,
       0.08666944, 0.08951797, 0.10129826, 0.08974794, 0.12992387,
       0.11173639, 0.09764732, 0.09071713, 0.09548372, 0.08623657,
       0.10661744, 0.09219254, 0.09460106, 0.12959076, 0.09676594,
       0.09297345, 0.08807018, 0.09729345, 0.09691087, 0.10053777,
       0.09565815, 0.09671556, 0.09027689, 0.08613559, 0.09380159,
       0.10936595, 0.09758496, 0.08437506, 0.12607013, 0.10134204,
       0.11255281, 0.09503302, 0.09283259, 0.08902054, 0.10162438,
       0.09216247, 0.10298155, 0.10178038, 0.10050876, 0.098215  ,
       0.0933144 , 0.0879968 , 0.09114184, 0.09535731, 0.10278762,
       0.09277004, 0.09277261, 0.08610269, 0.09108733, 0.0953214 ,
       0.08691863, 0.08407738, 0.11040009, 0.08922113, 0.08990602,
       0.08922154, 0.1011192 , 0.10244597, 0.09327333, 0.10026117,
       0.09450859, 0.09166523, 0.08806503, 0.09002723, 0.08621163,
       0.09997213, 0.10416454, 0.09298819, 0.09222514, 0.08981693,
       0.09912888, 0.08695139, 0.09557715, 0.08697636, 0.10156441,
       0.09295434, 0.08508538, 0.09826852, 0.08939229, 0.10717317,
       0.09219147, 0.08799047, 0.09054297, 0.09326368, 0.09032299,
       0.08480508, 0.09226939, 0.09320627, 0.10538326, 0.10101141,
       0.09061132, 0.09128006, 0.09853547, 0.09701753, 0.09622975,
       0.10204127, 0.09813816, 0.0887509 , 0.09009174, 0.09046271,
       0.09852912, 0.0884704 , 0.10321704, 0.09385405, 0.08879434,
       0.10595376, 0.10043623, 0.09094378, 0.08849201, 0.08431212,
       0.09874409, 0.08887804, 0.08948625, 0.08465596, 0.08812615,
       0.10814926, 0.0845332 , 0.09790318, 0.09810248, 0.10314558,
       0.08984936, 0.0969579 , 0.10541639, 0.09104646, 0.08621032,
       0.09512255, 0.12156334, 0.08769313, 0.08924879, 0.08698369,
       0.08524677, 0.09670101, 0.08424097, 0.09079286, 0.09448298,
       0.08512603, 0.09056611, 0.08805319, 0.0884965 , 0.10998663,
       0.09738357, 0.09438625, 0.09977956, 0.0968041 , 0.0969414 ,
       0.08500701, 0.09578001, 0.11940181, 0.10851178, 0.09247287,
       0.10026037, 0.09850243, 0.09594517, 0.09407476, 0.08880065,
       0.09208937, 0.09905677, 0.10207238, 0.09826745, 0.09356487,
       0.08728912, 0.09129485, 0.09387907, 0.10119554, 0.08761083,
       0.10066888, 0.09278463, 0.09820923, 0.08863306, 0.10383409,
       0.10349447, 0.09143747, 0.09080195, 0.08526404, 0.09897894,
       0.08588345, 0.11382656, 0.11142248, 0.10881857, 0.10624219,
       0.09199869, 0.10543707, 0.092508  , 0.08689245, 0.09250703,
       0.09221461, 0.09470779, 0.104043  , 0.09312632, 0.09424107,
       0.10032904, 0.09042446, 0.08758932, 0.0947362 , 0.08596543,
       0.11815752, 0.08630546, 0.08913935, 0.09805715, 0.08410569,
       0.08879625, 0.1371724 , 0.09493952, 0.10110183, 0.08939742,
       0.0934982 , 0.09164474, 0.10907912], dtype=float32), array([[[[ 0.02314423],
         [-0.0110593 ],
         [ 0.04074595],
         ...,
         [ 0.04204059],
         [-0.02065073],
         [-0.03582728]],

        [[-0.01632047],
         [-0.00921185],
         [-0.00955794],
         ...,
         [ 0.00677087],
         [ 0.0242034 ],
         [-0.0170837 ]],

        [[ 0.02572548],
         [ 0.006856  ],
         [ 0.01095809],
         ...,
         [ 0.00132765],
         [ 0.00309142],
         [-0.0271124 ]]],


       [[[-0.02081565],
         [-0.00378538],
         [ 0.01626529],
         ...,
         [ 0.03132929],
         [ 0.01843154],
         [-0.00681204]],

        [[-0.01261414],
         [ 0.00405984],
         [-0.01435826],
         ...,
         [ 0.01781143],
         [ 0.01507195],
         [-0.04292136]],

        [[ 0.01206654],
         [-0.00019205],
         [ 0.03401479],
         ...,
         [-0.0053208 ],
         [ 0.01638001],
         [-0.00708178]]],


       [[[ 0.01188016],
         [-0.00891858],
         [-0.01953166],
         ...,
         [ 0.02921136],
         [ 0.03920283],
         [-0.00644446]],

        [[ 0.01392565],
         [-0.00406549],
         [-0.01127977],
         ...,
         [ 0.01179112],
         [ 0.0161449 ],
         [-0.01558429]],

        [[-0.00195996],
         [-0.01272025],
         [-0.01017661],
         ...,
         [-0.00721636],
         [ 0.04274351],
         [-0.03365464]]]], dtype=float32), array([[[[ 0.03273485, -0.07592708,  0.06318184, ..., -0.00231523,
          -0.06598663,  0.04558264],
         [ 0.01672589,  0.02186388, -0.06236666, ..., -0.00494088,
          -0.02516308, -0.0663128 ],
         [ 0.05209775, -0.02961709,  0.00832746, ..., -0.02313028,
          -0.07964794,  0.03788793],
         ...,
         [-0.0143106 , -0.0204417 , -0.02012263, ..., -0.0654503 ,
          -0.01679734, -0.0026114 ],
         [-0.00529484, -0.05636431, -0.03801979, ...,  0.03796537,
          -0.00223674, -0.06042922],
         [ 0.0322354 ,  0.02055028,  0.00779841, ...,  0.01711058,
           0.03529198, -0.04252421]]]], dtype=float32), array([1.0104192 , 1.0101817 , 0.9918724 , 1.0017045 , 0.99317944,
       1.0024767 , 0.9991924 , 1.0125442 , 1.0050254 , 1.0193524 ,
       0.98323524, 1.0307894 , 1.0205888 , 0.9999442 , 1.0150905 ,
       0.9958267 , 0.99503577, 1.0045307 , 0.9924846 , 0.9867592 ,
       1.0136931 , 0.993237  , 0.9912938 , 0.989139  , 0.99336433,
       1.0103077 , 0.9939915 , 0.9976182 , 1.0196692 , 0.9985667 ,
       0.9907697 , 0.99456215, 1.0200208 , 1.0059458 , 0.99478984,
       1.0047436 , 1.0008719 , 0.99434084, 1.0263485 , 1.0033344 ,
       1.0089768 , 1.0195025 , 0.99047464, 0.99287736, 0.9994096 ,
       0.99382794, 1.0037582 , 1.00159   , 0.9865673 , 0.9945714 ,
       1.006357  , 1.001747  , 0.9801324 , 0.990502  , 0.9936661 ,
       0.99907434, 0.9820331 , 0.98998356, 1.0054594 , 0.9924277 ,
       0.9983488 , 0.9979193 , 0.9998912 , 1.0055588 , 1.0061233 ,
       1.0004387 , 0.9971731 , 0.9892269 , 1.0031534 , 1.0208946 ,
       1.0177368 , 0.9941996 , 0.98487943, 0.98805404, 0.993426  ,
       1.0095073 , 0.99035025, 0.9994127 , 1.0313485 , 0.99647754,
       0.99813634, 0.9971496 , 0.9950901 , 1.0202248 , 0.99159074,
       0.97591776, 1.0098705 , 0.9982867 , 1.0230362 , 0.9950711 ,
       1.0078025 , 1.0044113 , 0.9941989 , 1.0014112 , 1.0200796 ,
       0.99591   , 0.996299  , 1.0097995 , 0.99757594, 0.9968618 ,
       1.0011473 , 0.98841935, 0.9872928 , 0.97783715, 1.0043507 ,
       0.9954758 , 0.98681265, 0.999848  , 0.9972209 , 0.9882608 ,
       1.0151396 , 1.0123811 , 0.99326915, 1.0006478 , 0.98835534,
       0.9962931 , 0.9864893 , 1.0156258 , 0.99036604, 0.9939821 ,
       0.99727815, 1.0130088 , 1.0039643 , 1.0033034 , 0.97956526,
       0.9986588 , 0.9955843 , 0.9960192 , 1.0041264 , 1.0058503 ,
       0.9997419 , 0.9893618 , 1.0109978 , 0.9810514 , 0.9870736 ,
       1.0081717 , 0.9920597 , 0.9853334 , 1.0258315 , 1.043103  ,
       0.99687624, 1.0345083 , 0.996006  , 1.0098773 , 1.0207254 ,
       0.98100096, 1.0108378 , 0.99679637, 1.0181147 , 0.98266274,
       1.0104699 , 1.0143358 , 0.9968258 , 1.0036757 , 0.9883289 ,
       0.98840994, 0.99791086, 0.9957405 , 1.0050213 , 1.0042415 ,
       1.0094974 , 1.0111024 , 0.9976265 , 0.99584883, 1.0059187 ,
       0.9958859 , 1.0070254 , 1.011661  , 0.9879381 , 0.99337035,
       0.99870425, 0.9925709 , 0.99317497, 1.0056257 , 1.0060819 ,
       1.0085828 , 1.0039479 , 0.99826175, 1.0059264 , 1.0052199 ,
       0.98648363, 0.99750435, 0.9809165 , 1.0166805 , 1.0049284 ,
       0.9900634 , 1.0118996 , 0.9991747 , 1.0127536 , 0.99874943,
       0.9968346 , 1.005911  , 0.9982798 , 0.99175704, 0.99174756,
       0.99998534, 0.9981001 , 0.9916809 , 1.010518  , 0.9927864 ,
       0.99149346, 1.0178276 , 1.0138409 , 1.0027196 , 1.0058261 ,
       0.99689007, 0.99333787, 1.0152278 , 0.99111646, 0.9939852 ,
       1.0001884 , 1.0018026 , 1.0188944 , 0.98297036, 1.0278456 ,
       0.99108446, 1.0103072 , 1.0343318 , 1.0055157 , 1.0046587 ,
       1.0077456 , 0.9928353 , 1.0131133 , 0.9987637 , 1.0001345 ,
       1.0010313 , 1.0105903 , 0.99214727, 1.0079806 , 0.99433315,
       0.99046683, 0.98454267, 0.98657966, 1.013735  , 0.99739563,
       1.0014954 , 0.99644834, 1.0040905 , 0.9971557 , 0.99809855,
       0.9959974 , 1.0048106 , 1.0067748 , 0.9993537 , 0.98854375,
       0.99407214, 0.9943615 , 0.99300516, 1.0049714 , 0.98669   ,
       1.0030421 , 1.0040872 , 1.0180514 , 1.011316  , 0.99744207,
       0.9869631 , 0.9888035 , 1.0140089 , 1.0324309 , 0.99747604,
       0.9972082 , 1.0234586 , 1.0118937 , 0.99283725, 0.99329937,
       1.0030745 , 1.0058223 , 0.98669004, 1.0033708 , 1.0036254 ,
       0.9874208 , 0.99826545, 0.99281114, 1.0261538 , 1.0083451 ,
       0.98761874, 0.9909044 , 0.9969397 , 1.0059589 , 0.99604887,
       1.002729  , 1.0021772 , 0.9834857 , 1.0041147 , 1.0321121 ,
       1.0074804 , 1.0173947 , 0.9946613 , 1.0045481 , 1.010936  ,
       0.9970633 , 1.0009379 , 0.99527764, 0.99775106, 1.0053937 ,
       0.9947478 , 0.9980869 , 1.0081466 , 1.0046186 , 0.98719954,
       1.0146905 , 1.0105964 , 0.99606663, 0.99181134, 0.99319965,
       0.99545807, 1.0058181 , 0.9966889 , 0.9987386 , 0.9935531 ,
       1.0109088 , 0.99636364, 0.9999042 , 1.0087519 , 1.004866  ,
       1.0064625 , 1.0181967 , 1.01692   , 0.9828988 , 0.9939399 ,
       1.0132829 , 1.0008094 , 1.0059928 , 0.9971904 , 0.9961613 ,
       0.9897614 , 1.0121198 , 1.0099642 , 0.99701256, 0.9935877 ,
       1.013133  , 0.9866656 , 1.0199773 , 0.99662393, 0.99841803,
       1.0040016 , 0.9943841 , 1.007077  , 0.9961253 , 1.0019505 ,
       0.9997547 , 0.99948937, 0.9843723 , 1.0046299 , 0.99775565,
       0.99049574, 0.98589927, 0.98913527, 0.99469125, 0.9925344 ,
       0.9906097 , 1.0111054 , 1.0012437 , 0.99402624, 0.9902774 ,
       1.0014957 , 0.98885226, 1.0094934 , 1.0047808 , 0.9961421 ,
       0.9862129 , 1.007801  , 1.0210727 , 1.0001773 , 0.9968594 ,
       1.0072944 , 0.988584  , 1.0126759 , 0.99383587, 0.9969552 ,
       0.9928399 , 0.99342805, 0.99901783, 0.99398166, 0.99258745,
       0.9992773 , 0.9875482 , 0.99119127, 1.0153549 , 1.0020608 ,
       1.0251204 , 0.9816947 , 0.9940251 , 1.004519  , 1.0032356 ,
       0.99468726, 1.0001113 , 1.0086273 , 0.9926043 , 1.0157465 ,
       0.97421604, 0.9875054 , 0.9999394 , 1.013375  , 0.9975412 ,
       1.0164114 , 0.9959765 , 1.0002081 , 0.9896625 , 1.0135604 ,
       1.0069932 , 1.0073007 , 0.98417383, 1.0009567 , 0.98968774,
       0.98940206, 1.0057467 , 1.0072372 , 0.99284357, 0.99629223,
       1.0107809 , 0.9923598 , 0.99629104, 1.0072826 , 0.99363345,
       1.0113165 , 1.0038191 , 0.99895734, 0.98774195, 1.0066636 ,
       1.0005016 , 0.99696225, 1.0045661 , 1.0048044 , 1.0281352 ,
       1.01366   , 0.9904643 , 0.9961031 , 1.0059503 , 0.9884555 ,
       0.99803215, 1.0314339 , 1.0002557 , 0.99634916, 1.0082034 ,
       1.0005674 , 0.9912018 , 1.0079156 , 0.9967389 , 0.99100804,
       0.99008155, 1.0197383 , 0.994747  , 0.98784715, 0.9888832 ,
       0.99414736, 0.9968001 , 0.9951463 , 0.9996955 , 1.0044725 ,
       1.0116892 , 0.99057066, 1.028487  , 1.0383941 , 1.0047143 ,
       1.0482944 , 0.97990805, 1.0103774 , 0.9848866 , 1.0056648 ,
       0.9869617 , 1.0235962 , 1.005123  , 0.9918656 , 1.0115124 ,
       0.99362063, 0.9895684 , 0.9980494 , 1.0268233 , 0.994432  ,
       1.0006526 , 0.9969846 , 0.99605054, 0.99967796, 0.99867225,
       0.99394125, 1.0141765 , 0.99270415, 1.018163  , 0.9912903 ,
       1.0232788 , 1.0059808 , 0.99723375, 1.0076993 , 0.9899433 ,
       0.995036  , 0.992536  , 1.0008894 , 0.99409556, 1.0155356 ,
       1.0049618 , 0.9972186 , 1.0016018 , 1.0023328 , 0.9928994 ,
       1.0003467 , 0.9956305 , 0.99795294, 0.99140203, 1.0024366 ,
       1.0106943 , 0.9896405 , 0.9938927 , 1.0070058 , 0.9985017 ,
       1.0100187 , 1.0064822 , 0.9975888 , 1.0005668 , 0.99241585,
       1.0116696 , 0.9968051 , 0.9916418 , 0.9943137 , 0.99674046,
       1.0309432 , 1.0031446 , 1.0024873 , 1.005632  , 1.016194  ,
       1.0132921 , 1.0053439 , 1.0073245 , 0.99201876, 0.99237114,
       1.0140363 , 0.9962712 , 0.9939689 , 0.99823076, 0.9881338 ,
       1.0079834 , 1.017317  , 0.99809074, 1.0061274 , 1.0142432 ,
       1.0029483 , 1.0028123 , 1.0141578 , 0.9986016 , 0.99268   ,
       1.0300242 , 1.0137773 , 0.9843671 , 1.001074  , 1.0199146 ,
       0.9887649 , 0.9971661 , 0.99363697, 0.98742753, 0.9933962 ,
       0.99603355, 0.99180144, 0.9930331 , 0.9906639 , 1.0011258 ,
       1.0008676 , 1.00681   , 1.0093508 , 0.9957    , 1.004352  ,
       0.990979  , 0.9962429 , 0.99791515, 0.9880589 , 0.9898588 ,
       0.993796  , 1.0123096 , 0.99248874, 0.9968898 , 0.98828137,
       1.0104703 , 0.9937742 , 0.9937298 , 0.98960364, 1.026191  ,
       0.9958836 , 1.0117661 , 0.9994553 , 0.99132305, 0.9855689 ,
       1.0124404 , 0.99547243, 1.0007604 , 1.0040231 , 0.9818383 ,
       0.99287355, 0.9863671 , 0.994518  , 1.0057915 , 0.9938676 ,
       0.9914601 , 1.0014774 , 1.0124038 , 0.9878074 , 0.98935777,
       1.0103881 , 0.99503154, 0.995767  , 1.0116968 , 0.989755  ,
       1.026034  , 0.9916396 , 0.99500483, 0.9992636 , 0.9929944 ,
       1.0042945 , 0.9908349 , 1.0039234 , 0.9935183 , 0.99623847,
       0.9937007 , 0.9945111 , 0.9897874 , 1.0044723 , 0.9986622 ,
       0.99729407, 0.99764085, 0.98853886, 0.98604167, 1.0064111 ,
       0.99249667, 1.0002198 , 0.97962964, 0.99865735, 0.99780184,
       1.0057268 , 0.9958903 , 0.990046  , 0.991257  , 0.9876933 ,
       1.0171295 , 1.0018407 , 1.0100133 , 0.9988986 , 1.0054387 ,
       0.9947036 , 1.001955  , 0.9937791 , 0.9857268 , 1.017359  ,
       1.0097268 , 1.0011137 , 0.98754025, 1.0093572 , 0.9933902 ,
       1.0253134 , 0.99217063, 1.0135098 , 1.034957  , 1.0005132 ,
       0.9988029 , 0.97937894, 1.0085166 , 0.99920434, 0.9969993 ,
       0.9936005 , 0.9940328 , 1.0065154 , 1.0033953 , 0.99083483,
       0.993844  , 0.99439615, 0.9932833 , 0.9889478 , 0.9975429 ,
       0.9932787 , 1.0114776 , 0.99640167, 0.9942836 , 0.99688613,
       1.0120723 , 0.9997746 , 0.99579275, 0.9948308 , 1.0170866 ,
       1.0004551 , 0.99644494, 1.0060649 , 0.9920725 , 1.0084268 ,
       0.99212426, 1.0002085 , 1.0024589 , 1.0061479 , 0.9957476 ,
       1.0011117 , 0.9928468 , 1.0012624 , 0.9929706 , 0.9985003 ,
       0.9962359 , 1.0009637 , 1.0061647 , 0.99599504, 0.9914938 ,
       0.9813507 , 0.99520415, 0.9971061 , 1.0128887 , 0.9963379 ,
       0.99493015, 1.0044177 , 0.9991756 , 0.99129605, 1.0082483 ,
       1.0107113 , 0.9983039 , 1.0007252 , 0.98991275, 1.0354866 ,
       0.99739164, 0.993229  , 1.0104462 , 0.9922909 , 1.0069573 ,
       1.0038637 , 1.0064838 , 1.0016004 , 1.0181621 , 0.97691214,
       1.0055177 , 0.99689376, 1.0064865 , 0.9865234 , 0.9959096 ,
       1.0095739 , 1.012501  , 0.98978996], dtype=float32), array([-4.21699509e-03, -1.45883849e-02, -6.82053249e-03, -1.03226798e-02,
       -7.33456155e-03, -1.88202155e-03,  1.14935404e-02,  2.78021358e-02,
       -5.49903652e-03, -2.57107988e-02, -1.90352406e-02,  2.40904652e-02,
        6.21347222e-03, -1.51029034e-02,  4.32681292e-03, -7.93358590e-03,
        2.81933346e-03,  8.35353602e-03, -3.20987590e-02, -8.29359703e-03,
        1.89266615e-02,  2.76380265e-03, -1.53438998e-02, -1.70233548e-02,
       -6.75099064e-03,  3.43099609e-02, -8.37198831e-03, -5.15353307e-03,
        8.29953142e-03, -5.31358225e-03, -1.15918992e-02,  8.91010556e-03,
        3.23453136e-02, -1.23594643e-03, -7.93069974e-03,  8.18410248e-04,
       -2.22204011e-02, -8.26274976e-03, -4.22900394e-02,  1.14294682e-02,
       -7.39244628e-04, -3.97680216e-02, -9.29747056e-03, -3.51021672e-03,
       -2.00096378e-03, -1.05996672e-02,  1.24461146e-03,  1.13667734e-02,
       -7.55333062e-03, -8.70642997e-03, -1.04007423e-02,  6.94943883e-04,
       -2.23204978e-02, -8.39676335e-03, -4.40081814e-03,  3.04759084e-03,
       -1.38698779e-02, -2.13784296e-02,  8.17778753e-04, -1.03430599e-02,
       -2.01970199e-03, -6.16678270e-03, -1.45236505e-02,  6.26389123e-03,
       -7.28506595e-03, -3.70804295e-02, -1.60174295e-02, -2.05762014e-02,
        1.12573821e-02,  3.19895856e-02, -1.05975736e-02,  1.14996638e-02,
        4.56283009e-03, -8.64459900e-04, -7.16431392e-03, -7.68393558e-03,
       -3.24397199e-02, -1.78013351e-02,  3.45540233e-02, -1.23453774e-02,
        3.64583218e-03,  6.38817437e-04, -2.41955975e-03,  3.28942984e-02,
       -3.22228260e-02, -2.20297128e-02,  2.38336436e-02, -5.59047423e-03,
        4.23353128e-02, -2.03657139e-04,  1.04704536e-02, -5.89229316e-02,
       -7.03954883e-03,  1.24519821e-02,  2.41004135e-02, -7.78877118e-04,
       -2.37533636e-02,  9.92418919e-03, -3.22104292e-03, -5.93520608e-03,
        1.98330600e-02, -3.63049377e-03, -1.08666462e-03, -4.08141362e-03,
       -1.17717125e-02, -4.51991288e-03,  1.39113702e-03,  5.06180758e-03,
       -7.02432683e-03, -2.49583926e-02,  3.92203685e-03,  4.06415761e-03,
        1.68857386e-03, -9.49355890e-04, -3.39191011e-03,  3.11982725e-03,
       -3.60985175e-02,  3.66626913e-03,  5.74171543e-04, -3.46507765e-02,
       -7.74684409e-03, -3.57641615e-02, -3.50616314e-02, -1.38331880e-03,
       -3.06168068e-02,  2.44454574e-03,  3.56551539e-03,  4.93686739e-03,
        1.35128126e-02, -5.97329624e-03, -2.28631310e-02, -3.81177776e-02,
       -1.55924773e-02, -1.47836627e-02, -1.31900171e-02,  5.54760732e-03,
        1.06557272e-02, -1.58932135e-02,  2.84073390e-02, -8.58348329e-03,
       -1.34208621e-02,  3.23929102e-03,  1.88934477e-03, -3.19486782e-02,
       -1.19900052e-02, -2.40574889e-02,  8.74749199e-03, -3.27571072e-02,
        2.27958485e-02, -1.90560725e-02,  6.36269944e-03,  8.09556246e-03,
       -1.98794063e-03,  2.69145537e-02, -2.30093542e-02, -1.98398018e-03,
       -8.43353104e-03,  2.39080028e-03, -8.70405138e-03,  4.26623132e-03,
        1.96336824e-02, -2.65215747e-02, -1.18707810e-02,  1.14019989e-04,
        1.02971541e-02,  1.36177968e-02,  1.27127403e-02,  1.77421533e-02,
        3.14127002e-03, -6.64574374e-03, -8.01445916e-04, -6.04773453e-03,
        1.53274760e-02,  1.63764115e-02, -4.19076358e-04,  1.24819987e-02,
        1.42744603e-02, -1.65066067e-02,  9.06723738e-03, -1.85186472e-02,
       -8.78518261e-03, -3.08624119e-03, -2.23170146e-02,  5.02966419e-02,
        2.81781261e-03, -3.78752686e-03, -2.46405005e-02, -2.98538315e-03,
        5.64429117e-03, -4.20159427e-03, -9.10032075e-03, -3.00125778e-02,
       -8.88275728e-03, -4.58582211e-03, -5.98195242e-03, -2.52281519e-04,
       -3.60012637e-04,  3.81578066e-05,  2.39965469e-02, -2.10921606e-03,
       -5.96648920e-03,  2.79840101e-02,  2.79312972e-02,  9.47328471e-03,
       -2.49502454e-02,  4.62906249e-03, -1.63436029e-02, -2.86501404e-02,
        1.10662379e-03,  7.24553084e-03,  3.33659910e-03,  1.22352811e-02,
        1.06115602e-02,  4.48678527e-03,  1.38495378e-02, -2.33432767e-03,
        2.58044433e-03, -1.43469274e-02,  8.45950563e-04, -6.53552497e-03,
        9.81945917e-03, -1.36426585e-02,  4.68337070e-03,  2.00975337e-03,
       -1.95987727e-02,  1.35029871e-02,  2.65536569e-02, -8.32134392e-03,
        6.98858127e-03, -8.74430407e-03, -1.10749947e-02, -1.44108068e-02,
       -7.75905000e-03,  1.26127489e-02, -2.31068190e-02, -4.31133583e-02,
        1.80481989e-02,  4.22903989e-03, -4.43693483e-03, -1.99242868e-02,
       -1.09433886e-02,  2.56531481e-02,  3.78329158e-02, -5.20448247e-03,
       -5.90949086e-03,  6.45233272e-03,  1.34015878e-04, -3.66836041e-02,
       -6.57717604e-03,  3.95672349e-03,  8.06516968e-03,  5.28781815e-03,
        1.97064169e-02,  8.14405212e-04,  4.64888522e-03, -3.91129125e-03,
       -7.08514638e-03, -2.55127214e-02,  4.19472083e-02, -7.89673161e-03,
       -9.60576115e-04, -4.53486945e-03,  1.82610992e-02, -3.37255211e-03,
       -6.94229919e-03,  1.43827740e-02, -1.63909439e-02, -1.12584718e-02,
        1.76406559e-02,  1.03079490e-02, -1.76328234e-02, -2.36213841e-02,
       -1.43675311e-02, -6.42351294e-03, -1.58000998e-02, -3.82530084e-03,
       -3.28507135e-03, -2.67035402e-02, -5.74107841e-03,  4.53505607e-04,
        9.36059630e-04,  1.14817163e-02, -8.22324655e-04, -2.15479676e-02,
        7.99602456e-03,  1.64183211e-02, -2.21553929e-02,  7.52583891e-03,
        8.41304718e-05,  1.88201549e-03,  8.64590518e-03, -3.77029926e-03,
       -1.19090537e-02, -1.88144166e-02, -3.55758052e-03, -2.68446580e-02,
       -6.29850104e-03,  8.30356032e-03, -2.43323054e-02, -1.72081608e-02,
        1.69956274e-02, -1.98978409e-02,  1.21340167e-03, -2.92188749e-02,
        1.47210155e-02,  2.06730468e-03, -1.88697707e-02, -1.08983638e-02,
       -3.35431402e-03, -3.94348800e-03, -9.60965455e-03, -2.61403527e-03,
        4.29970864e-03, -4.44802940e-02,  7.45118270e-03,  8.98484793e-03,
       -1.56250764e-02, -2.02166121e-02, -1.99251063e-02, -1.17420098e-02,
        2.86006015e-02, -1.96389444e-02,  7.60296360e-03, -6.14800397e-03,
        9.45651345e-03, -3.05258017e-02,  7.03017577e-04, -1.92970373e-02,
       -1.54514099e-02, -9.36047081e-03, -2.13771816e-02,  6.57659722e-03,
        3.83094363e-02, -1.08408593e-02, -1.32928863e-02, -4.50740522e-03,
       -1.09110409e-02,  1.62903816e-02, -9.28850193e-03,  4.23282059e-03,
        6.15633186e-03,  1.21046668e-02, -8.02062452e-03,  8.47768132e-03,
       -6.95162889e-05, -4.47309017e-03, -1.81026626e-02, -7.38098240e-03,
        2.32482515e-02, -4.07086918e-03, -6.38145162e-03,  1.25678685e-02,
       -2.50224303e-03, -1.02398032e-02, -8.20127130e-03,  2.68378621e-03,
       -9.32122301e-03,  4.52671712e-03,  8.80266260e-03, -6.01167371e-03,
        1.35537377e-02,  7.38557614e-03,  4.23913561e-02,  9.00277961e-03,
        1.03015061e-02,  2.13268232e-02, -6.45587221e-03,  1.47313336e-02,
       -8.25117156e-03, -7.56540801e-03, -2.53870059e-02, -1.32591976e-02,
       -8.61602928e-03, -2.24355678e-03,  2.11593183e-03, -2.00521230e-04,
       -1.32847428e-02, -9.98965744e-03,  3.67998742e-02,  1.29629867e-02,
        2.48022284e-02, -2.92789247e-02, -1.59468804e-03, -2.69441772e-03,
       -2.18531825e-02, -5.95153309e-03,  1.87813712e-04, -7.02545941e-02,
       -2.15507559e-02, -5.06239496e-02, -1.27872247e-02, -1.27308331e-02,
        6.78768009e-03,  7.42260367e-03, -6.57728733e-03,  3.74005362e-02,
       -9.57443379e-03, -3.26278154e-03, -9.97617282e-03,  1.21931988e-03,
        8.39089626e-04,  5.52752847e-03, -6.48509664e-03, -3.14659160e-03,
       -3.54462233e-03, -3.05230403e-03, -1.73340400e-03,  1.20701157e-02,
       -1.05882380e-02, -5.74443431e-04,  6.18122099e-03, -6.72982121e-03,
        1.62211456e-03,  1.63085405e-02, -1.98378898e-02,  1.40859289e-02,
       -2.24692281e-02,  5.77425864e-03, -7.25342985e-03, -7.41116644e-04,
        1.23928636e-02, -7.43159559e-03,  2.92399758e-03, -5.60986772e-02,
        3.27794105e-02,  2.13954337e-02, -1.30016385e-02, -7.61859026e-03,
       -4.22479436e-02, -2.65662596e-02,  8.08528811e-03, -6.02872595e-02,
       -3.24593335e-02, -1.01347510e-02, -5.87550644e-03,  1.31998565e-02,
       -5.88954752e-03,  4.30879463e-03, -6.43071672e-03, -7.69165112e-03,
       -5.08387014e-03, -4.47581609e-04,  2.23488722e-04,  8.55720043e-03,
       -2.38273162e-02, -3.22082676e-02,  2.69088312e-03,  6.35222951e-03,
       -1.05567276e-02,  1.46760941e-02, -3.08074970e-02, -1.40702259e-02,
       -3.91295329e-02,  3.93118942e-03,  3.50651890e-03,  4.38866243e-02,
       -8.70078709e-03,  2.18254402e-02, -1.17038507e-02, -3.53148277e-03,
       -1.87218618e-02, -3.75686050e-03,  9.98702645e-03, -1.96331705e-04,
        3.16027179e-03, -5.76497195e-03,  6.76831417e-03, -3.81295546e-03,
       -4.51516844e-02,  1.34447101e-03,  5.44344541e-04,  1.30394259e-02,
       -2.50779674e-03, -8.30545370e-03,  1.75693501e-02, -8.61542393e-03,
        2.37976704e-02, -1.25510804e-02,  8.55992176e-03, -1.36703458e-02,
        2.58418880e-02, -3.93139850e-03, -2.00116658e-03, -2.13077366e-02,
       -1.13806862e-03,  1.02666114e-03, -1.08436840e-02,  1.46060213e-02,
       -7.15088239e-03,  7.17032515e-03,  1.23661468e-02,  2.01257821e-02,
        3.33720422e-03, -7.03430222e-03, -7.31352344e-03, -1.40335469e-04,
       -4.06759828e-02,  9.81960073e-03, -2.64369859e-03, -4.48708422e-03,
        1.29271876e-02, -6.28002500e-03, -6.14949549e-03,  1.88858733e-02,
        3.85698164e-03,  5.15080243e-03, -3.34436074e-02, -1.73239373e-02,
        2.56293803e-03, -1.14692431e-02, -7.33937789e-03, -7.29920017e-03,
       -1.23712402e-02, -1.15073603e-02, -9.69408487e-04,  2.04257034e-02,
        1.89144406e-02, -1.16205181e-03,  1.14598954e-02,  2.64871512e-02,
        1.87224373e-02,  2.10022721e-02,  1.41371554e-02, -1.35738552e-02,
       -9.64866485e-03,  2.86168437e-02, -1.40172569e-03, -5.14623895e-03,
        4.33158036e-03, -1.38936145e-02,  9.33855120e-03, -3.16957198e-02,
        2.40932754e-03, -1.02293410e-03,  2.44148672e-02,  1.39931040e-02,
       -2.37223841e-02,  1.70470066e-02, -2.11808644e-03, -2.89488002e-04,
        1.91047862e-02,  1.24870492e-02, -2.03002095e-02, -1.54554071e-02,
        1.22089535e-02, -1.78690087e-02,  3.29947961e-03, -8.23934097e-03,
       -1.70140027e-03, -2.43293680e-02, -1.00510791e-02, -3.08125634e-02,
       -4.69888449e-02,  5.04508894e-03, -1.18183857e-02,  9.67769045e-03,
       -1.50239002e-02,  1.31631112e-02, -4.84362384e-03,  1.03355506e-02,
       -6.60075480e-03,  1.43845249e-02,  5.07286517e-03, -1.25896120e-02,
       -1.49840573e-02, -2.44809268e-03,  2.73139551e-02, -7.22735934e-03,
        1.89516563e-02,  1.24908052e-03,  1.42933540e-02, -4.69063409e-03,
       -1.35001646e-05, -7.19844224e-03,  1.82738025e-02,  3.18329409e-03,
        9.07519087e-03,  3.11069214e-03, -1.28423283e-02, -3.20693059e-03,
        1.09235290e-03,  2.04588077e-03,  2.96474691e-03,  2.10948139e-02,
       -7.05714896e-03, -3.00716376e-03, -1.20264208e-02, -5.64947817e-03,
       -1.94304753e-02,  1.13924714e-02, -2.79156901e-02,  1.08361272e-02,
       -3.08388900e-02,  2.83976062e-03, -1.62643772e-02,  1.35208834e-02,
        4.42593649e-04, -1.13197053e-02,  1.84102058e-02, -2.78005395e-02,
       -4.97670332e-03, -3.51663632e-03, -1.70795247e-02, -4.47982475e-02,
       -1.97953472e-04,  1.70681644e-02, -8.68530478e-03,  1.33516500e-04,
        3.19807418e-03,  1.26038576e-02,  4.54846566e-04,  8.84933118e-03,
       -2.13793833e-02,  2.42399890e-03, -1.45812295e-02,  5.01193339e-03,
        2.72306474e-03, -1.51312761e-02, -2.39878669e-02,  1.85177382e-03,
       -1.73061062e-02, -1.90362695e-03, -2.61783018e-03, -7.59396236e-04,
        1.66289147e-03,  1.44044422e-02, -1.60030462e-02, -3.65914474e-03,
       -1.44099630e-03, -1.19510759e-02, -1.77613776e-02,  9.43539478e-03,
        1.83838848e-02,  1.30276335e-02,  9.91452392e-03,  4.60315822e-03,
        8.05754866e-03, -1.35503104e-02, -3.98787623e-03,  2.09572930e-02,
        3.45275141e-02, -4.07826947e-03, -2.07407214e-02,  6.90813269e-03,
       -3.90712451e-03,  1.22060152e-02,  3.65713402e-03, -5.17525524e-03,
        1.96788814e-02,  1.39340863e-03, -1.32126873e-03, -5.19964425e-03,
       -1.94666665e-02, -2.08240226e-02,  2.03252840e-03,  5.87314600e-03,
        8.58012645e-04, -2.23380495e-02,  1.07503729e-02,  2.83943396e-03,
       -6.49634423e-03, -2.62450194e-03, -3.40258842e-03, -4.84660314e-03,
       -4.65661287e-02, -8.30744766e-03, -5.16648463e-04,  1.79363778e-04,
       -2.99007702e-03, -8.85582156e-03,  1.42203458e-02, -4.62740399e-02,
        4.15719440e-03, -1.29901674e-02,  1.78581029e-02, -2.08548759e-03,
       -1.75259414e-03,  1.46468468e-02, -3.89529280e-02,  4.77256067e-03,
       -2.75775101e-02,  7.77910044e-03,  2.06854548e-02,  5.77012077e-03,
       -2.15362608e-02, -2.26465352e-02, -4.79961466e-03,  1.10522029e-03,
       -1.03977472e-02, -1.11604738e-03,  5.75056486e-03,  1.70449968e-02,
       -1.10044261e-03,  1.52548216e-02, -1.13625694e-02, -2.03287173e-02,
       -2.35703494e-02, -8.11004080e-04,  1.66701693e-02, -1.99966095e-02,
       -8.46842304e-03,  1.96910817e-02, -5.81095868e-04,  3.05740302e-03,
        8.21909867e-03,  1.82579819e-03, -7.49750994e-03,  2.19400357e-02,
       -1.50201228e-02,  3.02180368e-02,  9.58686695e-04, -1.74180008e-02,
        1.56529564e-02, -1.19251031e-02,  2.01290026e-02, -1.26829389e-02,
        2.09902618e-02,  1.15535734e-02,  1.35390377e-02, -5.70406625e-03,
        2.36446988e-02,  8.40735622e-04, -2.13522986e-02, -1.43755069e-02,
        7.19645899e-03, -2.03978829e-02,  1.38952984e-02, -7.61243468e-03],
      dtype=float32), array([ 1.17355287e-01,  4.73289676e-02,  6.44716108e-03,  1.44614443e-01,
        7.08802119e-02,  1.85114756e-01, -1.35207444e-01, -3.90770882e-02,
        9.42595303e-02,  2.23843291e-01,  8.98267999e-02,  1.63751513e-01,
        4.75919470e-02,  2.30897307e-01, -7.76657537e-02,  1.04228348e-01,
        1.86397769e-02, -4.36506532e-02,  2.42896870e-01, -9.11445022e-02,
       -2.57446855e-01, -8.68812352e-02,  7.04414174e-02,  1.36876389e-01,
        1.21381402e-01, -1.84871599e-01,  4.92167659e-02, -3.64314159e-03,
        1.00403642e-02, -7.37470984e-02,  1.48983702e-01,  1.08507998e-01,
       -1.31777838e-01, -2.10732386e-01, -4.54468057e-02,  6.95669129e-02,
        8.05254281e-02,  1.20257825e-01,  1.82656199e-01, -8.08970816e-03,
        3.91369425e-02,  2.06966013e-01, -1.02779515e-01, -8.88248086e-02,
       -5.18191271e-02, -7.61562437e-02,  9.98056307e-02, -1.39548406e-01,
       -2.45787445e-02,  5.58111072e-02,  2.06044272e-01, -5.38974665e-02,
        1.32849351e-01,  1.25696510e-01, -1.38805136e-01, -1.77181035e-01,
       -8.31989571e-02,  2.61923730e-01, -1.81330219e-01, -5.02997302e-02,
        8.59706402e-02, -3.00759841e-02,  4.12668437e-02, -1.04671210e-01,
        1.05286404e-01,  1.89425424e-01,  6.25191703e-02,  1.93849981e-01,
       -5.20763546e-02, -1.80023938e-01,  8.53931308e-02, -7.39604607e-02,
       -1.06378958e-01, -9.22631770e-02, -6.96484093e-03,  2.47448713e-01,
        2.67516315e-01,  1.17430612e-01, -1.36584088e-01, -4.53073084e-02,
        1.70672163e-01, -7.41372705e-02,  1.45140603e-01, -1.28608346e-01,
        3.25051576e-01,  6.39479086e-02, -1.54105619e-01,  7.03389496e-02,
        2.56097503e-02, -1.52570277e-01, -1.91242099e-01,  2.52917200e-01,
       -1.11791812e-01,  1.65600181e-01,  3.50128375e-02,  1.00617722e-01,
        2.37943873e-01, -1.48359155e-02, -3.16390507e-02, -1.04157321e-01,
        7.27779046e-02, -1.25514761e-01, -1.55880466e-01, -9.68053043e-02,
       -1.40133843e-01,  8.46004635e-02, -1.45856112e-01, -1.28979832e-01,
       -5.21824919e-02, -2.33339325e-01,  1.32835150e-01, -5.62671907e-02,
       -9.35893804e-02, -1.20713376e-01,  2.73399018e-02,  4.76426966e-02,
        5.32835238e-02, -3.08780093e-02, -9.88074169e-02,  1.63234666e-01,
       -1.08915262e-01,  1.49657845e-01,  2.76591748e-01,  2.69558132e-01,
        6.01469688e-02, -1.46698341e-01, -9.80760530e-02,  7.76879787e-02,
       -3.05473283e-02,  9.12413299e-02, -2.83707142e-01,  1.08406827e-01,
        3.11545208e-02,  1.29365399e-01, -6.51295334e-02, -2.13045463e-01,
       -2.00742349e-01,  8.13819319e-02,  4.53852490e-02, -6.19234666e-02,
       -1.48776859e-01,  2.99714948e-03, -1.11193039e-01,  2.93831646e-01,
        8.85249525e-02, -7.10644349e-02,  1.22767957e-02,  2.12119460e-01,
        3.05772498e-02, -6.27942905e-02, -1.61280975e-01, -1.45121723e-01,
       -7.59135187e-02, -1.38091937e-01, -3.08598131e-01, -1.06242105e-01,
       -3.31615023e-02,  5.21124825e-02,  9.46986526e-02, -2.48100106e-02,
       -8.25419948e-02,  2.09944785e-01, -1.84815768e-02, -6.64599985e-02,
       -1.35216862e-01, -1.32811651e-01, -1.04408041e-01, -1.05948932e-01,
       -1.30108207e-01, -5.25780469e-02, -7.83080012e-02,  5.03881164e-02,
       -6.89522773e-02, -5.86852543e-02,  1.74398702e-02, -1.91515192e-01,
        1.16445906e-01,  3.84312272e-02, -2.94360090e-02,  1.19770661e-01,
        1.70908526e-01,  8.23947042e-02,  1.43985823e-01, -2.18100026e-01,
        1.82470664e-01, -9.77697298e-02,  4.27703261e-02, -1.55869469e-01,
        1.19594961e-01, -9.26921517e-03,  1.69947550e-01,  1.57972887e-01,
        9.45955515e-02, -3.99646424e-02, -2.03347988e-02,  7.58663490e-02,
       -7.05626756e-02,  7.32086077e-02, -1.40420690e-01, -7.97077343e-02,
        8.17337036e-02, -3.59540507e-02, -2.28757709e-01, -2.08208680e-01,
       -3.40233713e-01, -5.73844984e-02,  6.60101622e-02,  1.07936762e-01,
        1.79137215e-01, -1.07663218e-02, -1.70574382e-01, -6.54688850e-02,
       -9.35806334e-02,  1.05274402e-01,  6.81705447e-03,  1.11908436e-01,
       -5.14764749e-02,  1.73520252e-01, -1.12399943e-01,  4.63730320e-02,
        2.04360798e-01, -1.23551711e-01,  3.49278972e-02,  9.61485505e-02,
       -1.27418011e-01, -2.66476929e-01, -1.41549319e-01, -1.18599303e-01,
       -5.78647032e-02, -4.78930362e-02,  3.11807711e-02,  5.92268668e-02,
       -1.30395386e-02, -2.56553385e-02,  2.51106888e-01,  1.61039442e-01,
        5.66480123e-02, -9.63107422e-02,  1.29024401e-01,  1.44636080e-01,
        1.39110252e-01, -2.22245395e-01, -1.48277223e-01,  9.76427943e-02,
        1.44244447e-01,  7.06716441e-03,  3.05048265e-02,  1.44295827e-01,
        2.19461218e-01, -1.56018359e-04, -2.40285601e-02,  2.54174508e-02,
       -5.83803840e-02, -5.86259179e-02, -3.92517745e-02, -1.35941878e-01,
        6.67919293e-02,  2.47695357e-01, -4.96192239e-02,  1.55224890e-01,
       -1.29960433e-01,  9.18802395e-02, -1.13660634e-01, -1.44274965e-01,
        1.25378877e-01, -1.75026298e-01,  1.09708905e-01,  1.41133979e-01,
        5.91914020e-02, -6.70210421e-02, -1.97678939e-01,  1.48003399e-01,
        1.54309213e-01, -8.70751441e-02,  7.48139322e-02,  7.64789507e-02,
        1.04559787e-01,  1.51085824e-01,  7.13320673e-02, -1.72341093e-01,
        3.43307815e-02,  9.61157382e-02,  3.33800563e-03,  1.06843397e-01,
        9.86789390e-02, -7.42093995e-02,  2.22647935e-01, -1.68114588e-01,
       -2.05350459e-01, -1.28901765e-01, -1.34971187e-01,  9.99546051e-02,
        3.51194665e-02,  1.56005755e-01,  1.41039684e-01,  2.09664822e-01,
       -3.64628918e-02,  6.02320991e-02,  1.09457180e-01, -2.13375926e-01,
       -4.03884910e-02,  2.41498590e-01, -8.68119523e-02,  2.59124219e-01,
       -1.97208837e-01, -1.52034434e-02,  1.19846903e-01, -1.93613134e-02,
        4.66931574e-02, -1.97554380e-01,  1.78764001e-01, -1.20905124e-01,
       -3.67609151e-02,  1.89116806e-01, -2.67102242e-01, -8.28949660e-02,
        1.15835711e-01,  1.44492343e-01,  1.17354169e-01, -2.10938361e-02,
       -7.40567148e-02,  1.01254337e-01, -6.42758235e-02,  1.70920342e-01,
       -2.14312360e-01,  2.05680430e-01,  5.65278195e-02,  1.20865114e-01,
        7.19439164e-02,  5.19281216e-02,  1.90453112e-01, -2.12014019e-02,
       -1.19328961e-01,  1.59471437e-01,  1.37000158e-01, -2.69294620e-01,
        5.65085672e-02,  1.25626966e-01,  1.12482920e-01, -1.84437856e-01,
       -7.47887790e-02, -1.13655671e-01,  2.57505327e-01, -2.17402965e-01,
        1.03477404e-01, -1.81318566e-01,  1.50351599e-01, -1.09243784e-02,
       -1.61212549e-01, -1.78350016e-01,  1.27779230e-01,  6.01918437e-02,
       -1.04346953e-01,  3.15836892e-02, -1.06359452e-01,  9.84169766e-02,
        1.67014837e-01, -2.45361067e-02,  1.55972481e-01, -8.92602876e-02,
       -8.33087564e-02, -2.48044487e-02, -1.24909416e-01, -7.25239096e-03,
       -1.41568393e-01,  5.02332635e-02, -5.63333854e-02,  1.98736146e-01,
       -7.74365067e-02,  1.12577617e-01,  1.13005877e-01,  5.82370237e-02,
       -1.59939468e-01,  1.74375787e-01, -2.24300086e-01, -3.21731456e-02,
        1.04251325e-01,  6.27267882e-02, -1.79907501e-01, -1.55009747e-01,
       -3.20550650e-02,  2.05474660e-01, -1.22317038e-01,  1.13638915e-01,
        9.97467488e-02,  7.23220855e-02, -1.46506041e-01,  3.87311995e-01,
        2.19618246e-01,  4.60403830e-01,  1.22805022e-01, -9.21365693e-02,
       -1.51934579e-01, -1.32508073e-02,  1.51993200e-01,  1.61579296e-01,
        9.68622491e-02,  2.42348120e-01,  1.98900998e-01,  1.07934758e-01,
        8.03397894e-02,  5.86882606e-02,  2.09188238e-02,  7.76240900e-02,
        1.80793658e-01,  6.57529235e-02,  9.27902311e-02, -1.40246227e-01,
        1.77549362e-01, -1.18747830e-01,  3.59907970e-02, -2.20853925e-01,
       -8.66544694e-02, -6.18068278e-02,  1.77173853e-01, -1.43517449e-01,
        1.65259078e-01, -1.86949417e-01,  9.73878205e-02,  5.63703701e-02,
       -9.18708965e-02,  2.24483773e-01,  1.74524963e-01,  2.75955170e-01,
       -1.78730741e-01, -1.76650316e-01, -6.82129264e-02,  1.36275381e-01,
        3.06213319e-01,  1.58997655e-01, -6.31555319e-02,  4.03959095e-01,
        1.20785624e-01,  7.54337385e-02,  1.31370202e-01, -1.51385948e-01,
       -1.76196694e-01,  5.42819314e-02,  4.90742922e-02,  1.43416971e-01,
       -2.57301461e-02, -4.15439785e-01,  4.10358906e-02, -7.20814988e-03,
        1.63521037e-01,  1.93082124e-01, -1.25410005e-01, -1.27896830e-01,
        1.06660523e-01, -1.04354002e-01,  1.59757331e-01,  2.95646153e-02,
        2.76088536e-01,  9.47817415e-02, -9.00872424e-02, -5.87907173e-02,
       -1.06130816e-01, -1.03700690e-01, -3.66337784e-02, -1.54914349e-01,
        1.01538248e-01,  1.22669764e-01, -6.91280663e-02,  4.33679819e-02,
       -3.22803296e-02, -1.13846235e-01, -6.67274445e-02,  1.96164176e-01,
        1.28877684e-01, -2.16850668e-01, -1.12848960e-01, -3.02584320e-01,
       -1.92163177e-02,  2.61765540e-01, -8.42222795e-02, -4.15501408e-02,
       -1.17942028e-01, -8.84113554e-03,  1.45007316e-02, -7.73522854e-02,
       -1.40270114e-01,  2.33696312e-01, -8.26570988e-02,  1.73314974e-01,
       -3.35114151e-02, -1.16267018e-01,  2.07739733e-02, -7.00054020e-02,
       -1.37650684e-01,  1.41503021e-01,  8.54927897e-02, -5.75045086e-02,
       -8.26237127e-02, -1.68129712e-01,  1.14723749e-01,  3.13218799e-03,
        1.76128387e-01,  2.44744569e-02, -2.70485524e-02, -1.82652310e-01,
        3.89243774e-02, -4.14119214e-02,  9.16563720e-02,  1.41022250e-01,
        8.72401297e-02,  1.12645641e-01,  2.18441799e-01,  1.17574498e-01,
       -7.08659887e-02, -1.16190135e-01,  9.33680832e-02, -7.37884045e-02,
       -5.99814095e-02,  1.31518841e-01, -4.51958776e-02,  8.76417309e-02,
       -5.97127117e-02, -2.37580366e-03,  1.04367256e-03, -5.60133904e-02,
       -2.62709539e-02, -1.23963602e-01, -1.23204328e-01, -8.85691959e-04,
        3.51654738e-02, -1.00778691e-01,  1.08617216e-01, -5.27693257e-02,
       -1.47360787e-01, -1.50760099e-01, -1.53883472e-01,  4.49842215e-02,
        5.55681922e-02,  6.02918975e-02, -2.08834752e-01,  1.62156280e-02,
        1.50345266e-01, -9.16422307e-02,  7.04954118e-02,  1.18672550e-01,
        2.05101669e-01, -1.17321223e-01,  5.52137382e-02,  1.11175999e-01,
        2.11626180e-02,  1.24084607e-01, -1.54064924e-01,  1.42317623e-01,
       -5.58320284e-02,  7.66518787e-02, -6.65154159e-02,  1.40389562e-01,
        1.82437137e-01,  2.47011278e-02, -1.19644023e-01, -5.02001643e-02,
        1.92552030e-01, -2.30591055e-02,  7.50026628e-02, -9.68662426e-02,
        2.15683103e-01, -1.10872194e-01, -1.22014932e-01, -1.26581654e-01,
        9.44195539e-02,  1.50827020e-01, -1.05650961e-01,  1.94235563e-01,
       -1.61883578e-01, -1.35191247e-01, -1.40295312e-01, -1.11937195e-01,
       -7.34400600e-02,  3.80886719e-02,  4.85919998e-04, -1.61819950e-01,
       -6.10255003e-02, -1.22918256e-01, -1.18574724e-01, -5.40497415e-02,
        1.28228679e-01,  4.52709720e-02,  2.44528819e-02,  1.13281280e-01,
        3.38574909e-02, -1.70176014e-01, -4.85609705e-03,  9.65742022e-02,
       -1.27252162e-01, -2.26884976e-01,  1.51844367e-01, -1.20439380e-01,
        1.06120124e-01, -6.96383789e-02, -1.01563856e-01,  7.44043291e-02,
       -1.21742375e-02, -9.08250287e-02, -1.84016466e-01, -8.45104009e-02,
       -7.37705603e-02,  1.46074682e-01,  1.39614165e-01,  1.66983068e-01,
        7.76031986e-02, -1.29570380e-01,  7.91209713e-02, -7.55253015e-03,
       -2.61131246e-02,  7.78214410e-02, -1.30076453e-01, -4.10173461e-02,
        1.95890278e-01,  1.49132058e-01,  6.80271387e-02,  6.35895059e-02,
        8.35925341e-03, -1.36921123e-01,  1.15865678e-01, -9.51671451e-02,
        1.48987710e-01, -8.56818631e-02, -6.34988248e-02,  8.43139812e-02,
       -6.29796972e-03, -6.30630776e-02,  1.38450250e-01,  2.08120927e-01,
       -9.94495526e-02,  1.86610281e-01,  3.00251603e-01, -1.74106807e-01,
       -1.05293587e-01,  8.75736549e-02, -4.84337807e-02, -5.46262413e-02,
       -9.15495604e-02, -2.28520885e-01, -8.25001597e-02, -6.44671693e-02,
       -2.61509478e-01,  7.62433484e-02, -4.71668458e-03,  6.68756058e-03,
        3.17277163e-02,  1.44970685e-01,  1.24084711e-01,  6.36928082e-02,
       -6.45011663e-02, -1.30450502e-01, -5.52973971e-02,  1.10044563e-02,
       -1.59617197e-02,  1.89595371e-01, -3.76242474e-02, -1.44771129e-01,
       -1.30368531e-01,  1.45515636e-01, -4.42661904e-02, -4.85094376e-02,
       -1.28919825e-01,  9.12359543e-03, -6.56639636e-02, -6.50611073e-02,
        1.65271744e-01, -1.25478720e-02,  3.98426466e-02,  6.57445267e-02,
       -1.33572131e-01,  1.30062491e-01,  1.73285171e-01,  1.11104727e-01,
       -1.28179073e-01,  1.07962877e-01,  1.05713792e-02, -1.28271446e-01,
       -4.42716181e-02, -2.67487735e-01,  1.71863660e-01,  9.26143900e-02,
        1.18305579e-01,  2.48168018e-02, -1.92408115e-01,  6.91168830e-02,
        2.10277289e-01,  2.25897238e-01, -1.25052184e-01, -5.67378523e-03,
       -1.21161394e-01, -1.38509989e-01, -1.25860229e-01, -4.97100912e-02,
       -2.16629043e-01,  5.73275946e-02,  1.57687724e-01,  1.73158556e-01,
       -3.05625349e-01, -1.47672340e-01,  5.66136986e-02,  2.84464862e-02,
        8.55888203e-02, -1.17722154e-01, -1.66365728e-01,  6.62057102e-02,
       -1.32507399e-01,  1.00613259e-01,  1.59175709e-01, -1.51295066e-01,
        1.97176024e-01, -7.55951181e-02, -1.49915874e-01,  9.00185779e-02,
       -3.56477350e-02, -1.35421738e-01, -4.77248542e-02,  1.06328353e-01,
       -1.42639369e-01, -4.20142971e-02, -2.76734792e-02, -8.91448855e-02,
       -2.01743972e-02, -1.18518375e-01,  1.39099270e-01,  1.17116481e-01,
       -5.62594235e-02,  1.96563303e-01,  3.31695452e-02, -1.03581809e-01],
      dtype=float32), array([0.40031615, 0.5266902 , 0.11720859, 0.21842739, 0.26713747,
       0.156272  , 0.22365901, 0.14445157, 0.61360836, 0.47024977,
       0.32810122, 0.22188966, 0.23084794, 0.41945553, 0.26631248,
       0.15783589, 0.22217423, 0.12524894, 0.387468  , 0.19990163,
       0.4992642 , 0.34968278, 0.18929605, 0.23259033, 0.17154281,
       0.35393637, 0.12879345, 0.26947922, 0.4757948 , 0.12275117,
       0.25012916, 0.38755736, 0.2785783 , 0.2850752 , 0.16788058,
       0.24281865, 0.14400567, 0.15554795, 0.31444716, 0.17145082,
       0.26923066, 0.35668135, 0.133565  , 0.13820814, 0.17026915,
       0.152189  , 0.13601874, 0.2806186 , 0.12559298, 0.16120002,
       0.34080017, 0.17016688, 0.2602555 , 0.23243186, 0.19871019,
       0.29594457, 0.1499694 , 0.33206636, 0.1689469 , 0.11123509,
       0.25228384, 0.14226402, 0.1667572 , 0.2467557 , 0.20949873,
       0.2668715 , 0.21067433, 0.3637233 , 0.15342048, 0.2658292 ,
       0.18440759, 0.18774159, 0.18114729, 0.15651134, 0.17817134,
       0.3967619 , 0.2911383 , 0.26005706, 0.2355613 , 0.27721044,
       0.18112557, 0.17222477, 0.3295873 , 0.1620421 , 0.35512918,
       0.11253721, 0.35865143, 0.17231196, 0.14482571, 0.2306272 ,
       0.12244926, 0.37780824, 0.14572391, 0.28094897, 0.23032847,
       0.18855362, 0.32740116, 0.24142425, 0.3381396 , 0.4436814 ,
       0.21374297, 0.24310066, 0.44663683, 0.11744761, 0.11672822,
       0.2240018 , 0.28446075, 0.12476818, 0.19093147, 0.22324878,
       0.6730512 , 0.42690048, 0.40179822, 0.15069406, 0.168527  ,
       0.19282834, 0.22983778, 0.7426736 , 0.18866384, 0.33206776,
       0.25996858, 0.22125237, 0.5207294 , 0.9624136 , 0.17505404,
       0.82609576, 0.16955788, 0.20268759, 0.16749077, 0.29593635,
       0.8444637 , 0.2628809 , 0.4277969 , 0.17386654, 0.15138705,
       0.30932045, 0.40008807, 0.29240292, 0.21497504, 0.9350202 ,
       0.3369366 , 0.91497225, 0.14495605, 0.3592177 , 0.29132858,
       0.6713886 , 0.11492582, 0.32972455, 0.24962217, 0.13203312,
       0.14384934, 0.39409128, 0.1958006 , 0.22468385, 0.9702646 ,
       0.2627286 , 0.1564314 , 0.14589576, 0.19434433, 0.13504732,
       0.20558347, 0.3097108 , 0.16581757, 0.22762026, 0.3480137 ,
       0.15322876, 0.25532058, 0.30045345, 0.2817582 , 0.18860947,
       0.23714437, 0.14718525, 0.2193573 , 0.29845506, 0.1709573 ,
       0.35077137, 0.2267435 , 0.15783691, 0.24123192, 0.31236017,
       0.29435533, 0.16387507, 0.2364288 , 0.38012877, 0.25257587,
       0.14226057, 0.44681054, 0.2984194 , 0.5600801 , 0.12186186,
       0.22773497, 0.32373482, 0.27075088, 0.13282655, 0.1690663 ,
       0.09726615, 0.1788111 , 0.3757555 , 0.4554369 , 0.24831884,
       0.2164761 , 0.22300927, 0.5023461 , 0.4546577 , 0.7207392 ,
       0.18375012, 0.18671568, 0.3459496 , 0.5056975 , 0.12636256,
       0.318354  , 0.16057456, 0.29443282, 0.28311655, 0.19722676,
       0.23799829, 0.11139458, 0.26621112, 0.13046715, 0.17352372,
       0.19221514, 0.09618592, 0.48159665, 0.14305703, 0.23389426,
       0.32519966, 0.37167427, 0.2992818 , 0.13374253, 0.18152541,
       0.11475474, 0.16167516, 0.12586786, 0.19375783, 0.5392653 ,
       0.3954567 , 0.23070252, 0.10718174, 0.37849015, 0.29276547,
       0.15098491, 0.37001646, 0.20109972, 0.14844224, 0.21291824,
       0.15929879, 0.11009236, 0.28099507, 0.37914735, 0.11042752,
       0.18149407, 0.15256524, 0.14053345, 0.19544758, 0.14743313,
       0.16243461, 0.15212256, 0.31182185, 0.18490735, 0.2025791 ,
       0.23611023, 0.23976184, 0.18738148, 0.40902692, 0.24316786,
       0.1704713 , 0.2616591 , 0.17660145, 0.15678939, 0.23200434,
       0.30706   , 0.32919678, 0.29898563, 0.9137209 , 0.20957139,
       0.13724491, 0.2501438 , 0.3855957 , 0.14933492, 0.32071084,
       0.15828039, 0.30461532, 0.21637323, 0.20738786, 0.15252383,
       0.20197459, 0.343082  , 0.2656934 , 0.31959403, 0.5462874 ,
       0.1433029 , 0.277473  , 0.12183499, 0.27875778, 0.21556938,
       0.28020296, 0.13052979, 0.20305748, 0.25918877, 0.5561775 ,
       0.2225725 , 0.3160827 , 0.15150654, 0.72088915, 0.40404156,
       0.18553488, 0.3570487 , 0.13797969, 0.11747981, 0.32715023,
       0.25699592, 0.40455988, 0.17308794, 0.31267768, 0.6821516 ,
       0.23747233, 0.23026386, 0.24632308, 0.17481965, 0.18905835,
       0.13814889, 0.1672843 , 0.1983095 , 0.45708227, 0.25197703,
       0.39252532, 0.15816204, 0.21238719, 0.16689683, 0.1509555 ,
       0.28303558, 0.16181682, 0.27953762, 0.45078835, 0.23502453,
       0.8567731 , 0.20149791, 0.5231766 , 0.42999646, 0.20201865,
       0.16763566, 0.21686935, 0.6828586 , 0.39840838, 0.26589856,
       0.1689085 , 0.45298833, 0.11082334, 0.21777406, 0.22041424,
       0.31740063, 0.18806368, 0.2076719 , 0.10333984, 0.28973514,
       0.19807604, 0.3752953 , 0.50292623, 0.24749051, 0.12653032,
       0.27792323, 0.17242469, 0.29825044, 0.11595307, 0.20954777,
       0.3588718 , 0.11468671, 0.30947357, 0.23173979, 0.21515651,
       0.18409716, 0.24869043, 0.3271812 , 0.2664249 , 0.31042916,
       0.75236964, 0.15994525, 0.1124537 , 0.44294327, 0.28521588,
       0.22327457, 0.5176005 , 0.17682733, 0.20753732, 0.26382136,
       0.2190222 , 0.30810586, 0.6963063 , 0.18757501, 2.060502  ,
       0.35518166, 0.26964954, 0.17967626, 0.60155314, 0.51403975,
       0.5604658 , 0.1682775 , 0.39900532, 0.2938971 , 0.29635924,
       0.18846537, 0.17442846, 0.12052709, 0.17952818, 0.1917786 ,
       0.10118629, 0.16136909, 0.17882381, 0.3303879 , 0.36527646,
       0.13421215, 0.3180254 , 0.2308378 , 0.27609015, 0.29316407,
       0.2460079 , 0.4404985 , 0.24184671, 0.16306046, 0.17778416,
       0.34503958, 0.2437442 , 0.3665282 , 0.6160181 , 0.66675496,
       0.28758568, 0.2228773 , 0.22489113, 0.41971368, 0.1927141 ,
       0.24668023, 0.7753378 , 0.20793419, 0.31442118, 0.2320199 ,
       0.15368709, 0.38450742, 0.20293242, 0.25327042, 0.6089431 ,
       0.10976658, 1.3402871 , 0.21006787, 0.11247683, 0.28898224,
       0.44679093, 0.24557944, 0.29693758, 0.14843573, 0.32861593,
       0.22337128, 0.14499992, 0.2837145 , 0.4086618 , 0.19995992,
       0.26463446, 0.30209243, 0.25276   , 0.14660506, 0.22453527,
       0.20910949, 0.28591886, 0.24600416, 0.12372717, 0.14864686,
       0.1761465 , 0.25197023, 0.30517748, 0.23618442, 0.5687866 ,
       0.13524629, 0.79102105, 0.14885995, 0.5818637 , 0.13065733,
       0.10049319, 0.21129774, 0.1157181 , 0.77723974, 0.11128438,
       0.37333047, 0.9023108 , 0.14158957, 0.24816032, 0.11951375,
       0.31459773, 0.20729046, 0.17168875, 0.17637628, 0.3247693 ,
       0.196272  , 0.13211429, 0.1316132 , 0.21323673, 0.2143018 ,
       0.13716683, 0.3556295 , 0.18685587, 0.11715874, 0.28599003,
       0.27627462, 0.11397927, 0.4551144 , 0.5464559 , 0.17639914,
       0.20631495, 0.38839042, 0.4086444 , 0.10538419, 0.15949614,
       0.19762565, 0.18502548, 0.25629446, 0.33972764, 0.12204175,
       0.27643114, 0.16480578, 0.14195672, 0.20787618, 0.2041422 ,
       0.4694369 , 0.23814686, 0.22140124, 0.11194422, 0.12616104,
       0.20952411, 0.13113277, 0.15776584, 0.24786343, 0.21550766,
       0.14590421, 0.25192612, 0.16773398, 0.15749209, 0.36005726,
       0.15348029, 0.2644569 , 0.15518197, 0.13409393, 0.1254489 ,
       0.77458227, 0.15182555, 0.22644049, 0.21972592, 0.31508797,
       0.30261916, 0.2788941 , 0.2810625 , 0.16217121, 0.17960553,
       0.3012663 , 0.3540469 , 0.25917467, 0.1889856 , 0.24464282,
       0.18796542, 0.21496774, 0.18860595, 0.16030307, 0.18913922,
       0.3136527 , 0.23439912, 0.23043439, 0.16826285, 0.22782788,
       0.25483537, 0.17367671, 0.40374798, 0.24139048, 0.23530796,
       0.19675365, 0.21555272, 0.11735798, 0.1543568 , 0.25836837,
       0.32481363, 0.11875125, 0.25433803, 0.24749316, 0.14120845,
       0.18791431, 0.15503284, 0.14861776, 0.16267647, 0.11716868,
       0.22972253, 0.09736977, 0.2194126 , 0.24064632, 0.2740075 ,
       0.26392534, 0.12252356, 0.20013858, 0.14957917, 0.16604003,
       0.2055686 , 0.12164641, 0.15901522, 0.39972654, 0.17285694,
       0.41259474, 0.33852172, 0.26324695, 0.3686449 , 0.21992937,
       0.27453604, 0.20167412, 0.12429603, 0.11779588, 0.20707898,
       0.16870154, 0.17511404, 0.23948434, 0.12054588, 0.17750604,
       0.11646342, 0.09974965, 0.13279223, 0.22842436, 0.49074233,
       0.14826797, 0.14717983, 0.12540807, 0.0986656 , 0.19839641,
       0.19126359, 0.29245764, 0.28870612, 0.22761397, 0.30732015,
       0.82185173, 0.27840987, 0.15330233, 0.12448399, 0.29189697,
       0.17222689, 0.12873338, 0.5322121 , 0.2886289 , 0.15946186,
       0.43285784, 0.23209435, 0.1417686 , 0.11213816, 0.12942539,
       0.2156302 , 0.16432838, 0.22383514, 1.2829959 , 0.18781994,
       0.26475647, 0.19341812, 0.1305603 , 0.3356614 , 0.22238678,
       0.24059068, 0.16920097, 0.24003592, 0.10110243, 0.17931046,
       0.1348939 , 0.1331262 , 0.12636988, 0.16390105, 0.31260577,
       0.1307198 , 0.24656686, 0.12007843, 0.162217  , 0.23005213,
       0.2612041 , 0.30433732, 0.2248322 , 0.13821334, 0.1959291 ,
       0.1514497 , 0.13893798, 0.36055523, 0.30875337, 0.130973  ,
       0.18866213, 0.23360369, 0.41340086, 0.21764311, 0.1639779 ,
       0.25226986, 0.15496492, 0.19374883, 0.17608577, 0.31033877,
       0.32753485, 0.16761737, 0.3179661 , 0.21528059, 0.19065185,
       0.23680912, 0.57522976, 0.23330499, 0.27096125, 0.24922715,
       0.1210864 , 0.27852044, 0.4732284 , 0.32199866, 0.18490748,
       0.24744852, 0.2659914 , 0.18472415, 0.26974195, 0.24988052,
       0.14772964, 0.30902797, 0.11610431, 0.1636655 , 0.15152429,
       0.32617292, 0.39213973, 0.13533048, 0.23024838, 0.18585378,
       0.1892696 , 0.23032705, 0.24606165, 0.18590835, 0.33685338,
       0.3528711 , 0.20613277, 0.17820129], dtype=float32), array([[[[ 0.0111366 ],
         [ 0.03838347],
         [ 0.01616587],
         ...,
         [ 0.00900299],
         [-0.02196249],
         [-0.01720833]],

        [[ 0.03332642],
         [ 0.0401312 ],
         [ 0.00467557],
         ...,
         [ 0.00121682],
         [ 0.00120455],
         [ 0.02779203]],

        [[-0.00993327],
         [ 0.01864854],
         [-0.00742318],
         ...,
         [-0.02360444],
         [-0.01507814],
         [ 0.00061101]]],


       [[[ 0.03788783],
         [ 0.03758668],
         [-0.03426774],
         ...,
         [-0.00171001],
         [-0.00942833],
         [ 0.03128758]],

        [[ 0.0405085 ],
         [ 0.03147294],
         [-0.00592546],
         ...,
         [-0.02441894],
         [-0.04485694],
         [ 0.01327621]],

        [[ 0.02528212],
         [-0.01239177],
         [-0.02376172],
         ...,
         [-0.02492879],
         [-0.00496176],
         [-0.01480746]]],


       [[[-0.01676744],
         [ 0.00954012],
         [ 0.01348726],
         ...,
         [-0.01395062],
         [-0.01925545],
         [-0.01309363]],

        [[ 0.00338886],
         [-0.02209509],
         [ 0.01466737],
         ...,
         [-0.03257444],
         [ 0.00405868],
         [-0.02234106]],

        [[ 0.03837614],
         [ 0.01782196],
         [-0.0071682 ],
         ...,
         [-0.02167212],
         [-0.03174229],
         [-0.00981705]]]], dtype=float32), array([[[[ 0.02775362,  0.00773414,  0.00567376, ..., -0.06537552,
          -0.01155859,  0.01286201],
         [ 0.00998164, -0.07061949, -0.01930688, ..., -0.04962027,
          -0.0017413 , -0.0662874 ],
         [-0.06390233, -0.04241076, -0.05995347, ...,  0.00769164,
           0.04853296, -0.06704603],
         ...,
         [ 0.03113432,  0.00843162,  0.00717623, ..., -0.04261214,
           0.05483409,  0.05021834],
         [ 0.03609136, -0.01688368, -0.05974529, ...,  0.08256361,
           0.02844711,  0.01751815],
         [-0.03748089, -0.06810273, -0.00026345, ...,  0.00495707,
           0.02874438,  0.05071216]]]], dtype=float32), array([0.99254096, 0.9955565 , 0.99601203, 1.0039122 , 1.0378151 ,
       1.0298587 , 0.9960434 , 1.003657  , 1.0008355 , 0.99167603,
       1.0200633 , 1.0065937 , 1.0004524 , 0.9890332 , 0.9952972 ,
       0.9917064 , 1.0051745 , 1.0023007 , 0.9855773 , 0.9984754 ,
       1.0241327 , 0.9855976 , 1.0078511 , 0.9991787 , 0.9993587 ,
       1.0166079 , 0.9976262 , 1.0014173 , 0.9907805 , 0.9869322 ,
       0.9875089 , 0.99410814, 1.0099487 , 1.0094349 , 0.9907508 ,
       0.99009925, 0.9968005 , 0.98407847, 0.99837655, 0.99025834,
       0.9876834 , 0.98982537, 0.9940572 , 1.0101874 , 0.992024  ,
       1.0055939 , 1.0107597 , 1.000524  , 0.9953808 , 0.98788995,
       0.99762243, 1.0067152 , 0.9999687 , 0.9985791 , 0.99190485,
       0.99809855, 1.0067803 , 1.0378778 , 0.9939511 , 1.0094903 ,
       0.9864404 , 0.9915931 , 0.99259114, 0.9915891 , 0.99450105,
       1.0376412 , 1.0127133 , 1.0087526 , 0.98811436, 0.9992408 ,
       1.0010705 , 1.018752  , 0.99983627, 1.0023926 , 0.99930465,
       0.9944279 , 0.9882629 , 0.9937871 , 0.99141544, 1.0026864 ,
       0.9944765 , 0.9915842 , 0.995959  , 0.99336034, 1.0091833 ,
       1.0031615 , 1.001422  , 0.99159354, 0.9958159 , 1.0061247 ,
       0.99964666, 1.0295283 , 0.98363835, 1.0284709 , 1.0171037 ,
       0.9944426 , 0.9934368 , 1.0090029 , 1.0049884 , 1.0051752 ,
       0.99376714, 1.0044309 , 1.0017993 , 1.0283055 , 0.9971846 ,
       0.9993611 , 0.9956758 , 1.0203357 , 1.0157965 , 1.0001287 ,
       0.99782926, 0.99569046, 1.0014838 , 1.001658  , 0.994456  ,
       1.0029947 , 0.99686027, 1.0013754 , 0.99265665, 0.99236286,
       0.9930548 , 1.0042205 , 0.991756  , 1.0011681 , 0.9971726 ,
       0.98862475, 1.0101472 , 1.0035983 , 0.9874656 , 0.9877266 ,
       1.0072799 , 0.9932177 , 0.99939716, 1.0053039 , 0.9933694 ,
       1.0035648 , 0.9953086 , 0.9898472 , 1.0164369 , 1.0023494 ,
       1.0090915 , 0.9826791 , 0.9946874 , 0.98218066, 0.9870545 ,
       0.9887414 , 0.99954474, 0.98774767, 0.9929856 , 0.9910135 ,
       0.9902095 , 1.0002602 , 0.9918198 , 1.0012982 , 0.9976775 ,
       1.0011277 , 0.99410003, 0.99583375, 0.9954182 , 1.0048579 ,
       1.0042284 , 0.995108  , 1.0332664 , 0.99750286, 0.9940706 ,
       1.0012066 , 0.98683035, 1.0146674 , 0.99198204, 0.99670416,
       1.0029442 , 0.993015  , 0.9967726 , 0.9998908 , 0.9931535 ,
       0.99751943, 0.98235095, 1.0018574 , 0.98782   , 0.9921485 ,
       0.99657464, 1.0070176 , 0.99536127, 1.0153224 , 1.02292   ,
       0.98919314, 0.99212265, 1.0049285 , 0.99903667, 1.0024515 ,
       1.0178351 , 0.9895853 , 0.9969058 , 0.9885012 , 1.006556  ,
       1.0111704 , 0.9860324 , 0.9878496 , 1.0152498 , 0.9971545 ,
       1.0106077 , 1.0165899 , 0.99804896, 0.9888144 , 1.0038162 ,
       1.0062476 , 0.9832851 , 1.0178031 , 0.99663174, 0.9919914 ,
       1.0061052 , 0.99836975, 0.99947685, 0.9982007 , 0.98831254,
       0.99290705, 0.9870777 , 0.99385625, 1.0104643 , 0.995475  ,
       1.0131929 , 0.99636227, 1.032808  , 1.0068947 , 0.9931482 ,
       0.99841166, 1.0307338 , 0.9950119 , 0.9933328 , 0.995306  ,
       0.993228  , 0.9975206 , 1.0163339 , 1.0140365 , 0.9769194 ,
       0.9832741 , 0.9943273 , 1.0011551 , 1.0204588 , 0.9970082 ,
       1.0267154 , 0.9825835 , 1.0089284 , 0.9935088 , 1.0033622 ,
       0.99602276, 0.9971268 , 0.99465394, 0.99029183, 0.9937364 ,
       0.9890924 , 1.0142407 , 0.9905893 , 0.9989893 , 0.99682796,
       1.0139406 , 0.99403787, 1.0135005 , 0.99217767, 0.98271376,
       0.9948824 , 1.0072478 , 1.0006006 , 1.0067711 , 0.9842197 ,
       1.0033892 , 0.9993698 , 1.0094539 , 0.99702024, 1.0315356 ,
       0.9876866 , 0.9965281 , 0.9992916 , 0.9877418 , 0.9911429 ,
       1.005351  , 0.9971319 , 0.9937538 , 1.006194  , 0.9931196 ,
       1.0126559 , 0.99308664, 0.9926299 , 1.016213  , 0.99725956,
       0.9919359 , 1.0050709 , 1.0081376 , 0.9955172 , 1.0160905 ,
       0.9965705 , 0.9896267 , 1.0017958 , 0.9963468 , 0.98768365,
       0.9936653 , 0.9973454 , 1.0006866 , 0.99768156, 1.0072184 ,
       0.9975402 , 0.9908751 , 1.0029228 , 0.99426025, 1.0150001 ,
       0.9907795 , 1.0075021 , 1.00698   , 0.9912655 , 1.0048784 ,
       1.0001384 , 0.9934069 , 0.9964448 , 1.0329468 , 0.9986133 ,
       1.0031087 , 1.0178206 , 0.9972296 , 0.9884877 , 0.9820764 ,
       0.99620074, 0.9844336 , 0.9883548 , 1.003741  , 1.0177218 ,
       0.9887052 , 0.98905   , 0.99565804, 0.9912191 , 0.9951172 ,
       1.029539  , 1.0067481 , 0.99362874, 0.99823195, 0.9929072 ,
       0.9952274 , 0.98602504, 1.0017155 , 1.0001909 , 0.9989871 ,
       0.99671924, 1.0098115 , 1.0168755 , 1.020906  , 1.0140638 ,
       0.9958754 , 0.97915727, 1.0055768 , 0.9933682 , 0.99643207,
       0.985525  , 1.0061283 , 1.0002725 , 1.0033125 , 1.025642  ,
       1.0084348 , 0.9945817 , 0.9987763 , 1.0148053 , 1.0042685 ,
       1.0018461 , 0.9898299 , 1.0004839 , 1.0024471 , 0.99068236,
       1.0061299 , 1.0124232 , 0.991626  , 1.0109128 , 1.0050395 ,
       1.0053291 , 1.0020586 , 1.0010538 , 1.0097884 , 0.99535424,
       0.97841436, 1.0035442 , 0.99734044, 0.9941187 , 0.9977076 ,
       0.97412735, 0.9852012 , 0.99418306, 1.0057901 , 1.0010064 ,
       0.9863252 , 0.99624807, 0.99986684, 1.0091326 , 0.99673283,
       1.0187926 , 0.99759173, 1.0060881 , 1.0080221 , 0.99518466,
       0.9942234 , 1.0023378 , 0.9958495 , 1.0136065 , 0.9883404 ,
       1.0024393 , 0.9953241 , 0.9923046 , 0.9970513 , 0.9938322 ,
       1.0063521 , 0.9984419 , 0.9900094 , 0.9858679 , 0.9999634 ,
       0.98928386, 0.9976111 , 1.0020574 , 0.99744457, 0.99462587,
       1.025215  , 0.9890632 , 1.0070043 , 0.99640447, 1.0150713 ,
       1.0260653 , 0.996432  , 0.9914965 , 1.0138096 , 0.9949221 ,
       0.9976858 , 0.9764156 , 0.9929602 , 0.9942079 , 0.9955699 ,
       1.0016928 , 0.9838631 , 0.9909846 , 1.0245036 , 0.9877549 ,
       0.99528104, 0.9953438 , 1.0030605 , 0.9855047 , 0.9978213 ,
       1.0200069 , 1.0048686 , 1.0078343 , 1.0053068 , 0.98092526,
       1.0030717 , 0.9960376 , 1.0008358 , 0.9986424 , 0.9978557 ,
       0.993293  , 0.99320126, 0.99563324, 0.99697846, 0.98993576,
       1.0169495 , 1.0093436 , 1.0204004 , 1.0030826 , 1.0043658 ,
       1.0075749 , 0.9949744 , 0.9894576 , 0.99727935, 0.9928384 ,
       1.0056187 , 0.99597657, 0.98523736, 1.0069215 , 0.99769515,
       0.9931774 , 0.99465704, 1.0005898 , 0.998471  , 0.9835692 ,
       1.0060351 , 0.992951  , 1.0237544 , 0.99643344, 0.99932206,
       0.9908883 , 0.9936507 , 1.0033104 , 0.9937358 , 1.0094156 ,
       0.98326504, 1.006346  , 0.99792075, 1.0121368 , 0.99402165,
       1.0057913 , 1.001603  , 0.99174607, 0.9904127 , 0.98990816,
       1.0180986 , 0.99462926, 1.0014168 , 0.99421835, 1.0004511 ,
       1.0104799 , 1.0046062 , 0.9969579 , 1.0050635 , 0.99145514,
       0.99257654, 0.9924213 , 1.0381882 , 1.0026767 , 1.0240008 ,
       0.9869792 , 1.006845  , 1.0033586 , 1.0004439 , 1.0417997 ,
       0.99723256, 0.9994114 , 0.9895329 , 1.0042689 , 0.99038535,
       1.0216024 , 1.0053558 , 0.99447834, 0.99576455, 0.98451453,
       0.9899199 , 1.0027883 , 1.0092932 , 0.9994774 , 1.0071485 ,
       1.0037605 , 0.99943835, 0.99490714, 0.994579  , 0.9926972 ,
       1.0027803 , 0.9987632 , 0.9927806 , 0.99593353, 1.0103648 ,
       0.9991232 , 0.997905  , 1.0065712 , 1.0085012 , 0.99845284,
       1.0256522 , 0.9958057 , 1.0085378 , 1.0002601 , 1.0045019 ,
       1.0059712 , 1.0144241 , 0.9912525 , 1.0164013 , 0.9885569 ,
       0.99236953, 1.0017715 , 1.0016439 , 0.9866213 , 1.0208273 ,
       1.0015979 , 0.9953797 , 0.9993096 , 0.9910188 , 0.9834148 ,
       1.0191208 , 0.9949806 , 1.0010134 , 0.9840616 , 1.0396997 ,
       1.0063076 , 0.9963028 , 0.9905419 , 0.9743137 , 1.0046765 ,
       0.9953996 , 1.0025225 , 1.0199476 , 1.0049798 , 1.010135  ,
       0.9937505 , 0.98976797, 0.9949304 , 1.0083733 , 0.99904937,
       0.99196553, 1.0081526 , 1.0295334 , 0.99311674, 0.9872001 ,
       0.99771994, 0.9900291 , 0.99513036, 0.999718  , 1.0136523 ,
       1.0073488 , 1.0001745 , 0.99642664, 1.0170372 , 1.0030015 ,
       1.0022799 , 1.0012395 , 1.0237908 , 1.0255588 , 0.98885316,
       1.0174577 , 0.99485075, 1.0021809 , 0.99628776, 1.0061843 ,
       0.9983961 , 1.0063152 , 0.99132407, 1.0185697 , 0.99896824,
       0.9926873 , 1.0118449 , 1.0138766 , 1.0158318 , 0.9906324 ,
       0.99464834, 0.99559367, 1.0023602 , 0.9959421 , 1.0172553 ,
       1.0064607 , 0.99317884, 0.9970402 , 0.9914906 , 0.99018997,
       0.9993568 , 1.0072395 , 0.9913932 , 0.9986025 , 0.99816424,
       0.99336606, 0.9958375 , 0.9995239 , 0.9973302 , 1.0013981 ,
       0.9989007 , 1.013005  , 0.9782237 , 0.9974277 , 1.0030595 ,
       0.9937658 , 1.0090374 , 0.9893935 , 0.9917325 , 0.9974359 ,
       0.9989637 , 1.0160578 , 1.0247078 , 0.9902057 , 0.98795533,
       1.0079343 , 0.9893735 , 1.0264903 , 1.0238374 , 1.0026633 ,
       0.99744165, 0.9959494 , 0.9980769 , 0.9848106 , 1.0057474 ,
       0.9888549 , 0.98877203, 0.9997296 , 1.0083302 , 1.016397  ,
       0.995753  , 0.9988589 , 1.000917  , 0.9923195 , 0.99655885,
       0.9925183 , 0.9975171 , 0.992535  , 0.996929  , 0.9978736 ,
       0.9871708 , 1.0059425 , 1.0138943 , 0.9964562 , 1.0266327 ,
       0.9906972 , 0.99984336, 0.99691063, 0.9898457 , 0.98570067,
       1.0043236 , 1.0025219 , 0.9891314 , 1.0117674 , 0.995515  ,
       0.98867315, 1.0045959 , 1.000833  , 0.99051166, 0.9947685 ,
       1.0006257 , 0.9953928 , 1.0128767 , 0.9980501 , 0.9866889 ,
       0.9986974 , 0.9977936 , 1.0101352 , 0.99853987, 1.0015224 ,
       0.9950469 , 0.9929475 , 1.0032699 , 1.030352  , 1.0034971 ,
       0.99241704, 1.0122445 , 1.0093693 , 0.993667  , 0.9959501 ,
       0.99210215, 0.99388516, 1.0026411 , 0.99288774, 0.9943532 ,
       0.9875341 , 1.0082262 , 0.99583477], dtype=float32), array([ 1.22400606e-03, -9.83066112e-03, -1.03780413e-02, -1.64054567e-03,
       -6.31540455e-03, -3.78978848e-02,  1.70151424e-02,  3.07595730e-02,
        3.57632991e-03, -7.48465885e-04, -7.40969228e-03,  1.48949893e-02,
       -7.12464191e-03, -7.99795799e-03, -1.56926773e-02,  3.23915132e-03,
        9.27034859e-03,  5.87100396e-04, -1.02110617e-02,  2.17155856e-03,
        2.49767434e-02, -1.08015863e-02,  1.86558831e-02,  4.20998037e-03,
        3.92260402e-03,  2.18477715e-02, -1.15031088e-02, -2.71469355e-03,
       -9.48574394e-03, -4.41987161e-03, -1.82721019e-02, -8.67325813e-03,
        5.32108452e-03,  1.53371776e-02, -4.94125579e-03, -3.85063607e-03,
       -4.89969132e-03,  2.94374162e-03, -1.96942268e-03, -7.31971674e-03,
       -1.06460508e-02, -9.58837662e-03, -6.41791662e-03, -1.81907043e-02,
       -5.26355859e-03, -8.89082346e-03,  1.25558546e-03, -3.03028822e-02,
       -4.17340640e-03, -1.53038613e-02, -1.86984171e-03, -2.29804573e-04,
        1.32193719e-03, -3.15216323e-03, -1.00381030e-02, -1.87374791e-03,
        6.15792908e-03, -3.37287635e-02, -1.06173046e-02, -5.07582277e-02,
       -8.58811755e-03, -6.12716423e-03, -1.20626613e-02,  1.24156103e-02,
       -7.98076112e-03, -3.05913836e-02,  1.17234448e-02,  6.61469623e-03,
       -1.46959806e-02, -3.80396545e-02, -8.61664477e-04, -7.95846153e-03,
       -1.31251132e-02, -4.95098438e-03, -2.36307122e-02, -8.78360309e-03,
       -7.42490171e-03,  1.28850387e-03, -2.06768718e-02, -3.61239463e-02,
        8.59572925e-03, -2.86084926e-03,  1.70205021e-03,  3.24033573e-03,
        8.64655711e-03,  3.96414427e-04,  1.59442006e-03, -2.14695092e-03,
        8.29479599e-04,  1.43495090e-02,  1.79892741e-05, -3.77831683e-02,
       -2.17677969e-02, -2.15706229e-03, -3.59587930e-02,  2.31941021e-03,
       -6.18500961e-03,  1.17970062e-02, -1.37559436e-02,  1.45142956e-03,
       -1.77397835e-03, -6.91676838e-03, -2.88373791e-02,  7.02092610e-03,
       -1.34366862e-02, -2.17343662e-02, -8.39108694e-03, -1.94373727e-02,
        3.71427787e-03, -7.03021465e-03, -2.08447985e-02, -1.58269226e-03,
       -5.31048561e-03, -3.80841666e-05,  7.59584538e-04,  2.08170712e-02,
        1.05718719e-02,  1.05690444e-03,  3.21243191e-03, -4.20581922e-03,
       -1.50912274e-02, -1.03631942e-02, -1.32411178e-02, -3.52872126e-02,
        4.22449736e-03, -1.43149924e-02,  1.82977561e-02,  1.40263163e-03,
       -5.13966335e-03,  9.85252578e-03,  1.60058774e-02,  4.39869706e-03,
       -2.56157247e-04,  1.88372878e-03,  2.82258540e-03,  1.05603272e-03,
       -3.43522825e-03, -1.74854938e-02,  1.28664216e-02,  1.02943985e-03,
        6.15314534e-03, -1.46196354e-02, -1.01966625e-02, -1.49516501e-02,
        1.24457888e-02, -2.21496001e-02, -5.39503247e-03, -1.44650396e-02,
       -1.35554932e-02, -6.52065175e-03, -1.69416498e-02, -8.44952185e-03,
       -1.15031218e-02, -6.10593241e-03,  2.84885187e-02,  2.06827233e-03,
       -4.33790265e-03,  6.18455670e-05, -1.39255198e-02,  1.08399540e-02,
        6.19818550e-03,  2.34487397e-03, -3.97338383e-02, -1.32880593e-02,
       -3.91114037e-03, -7.46199768e-03, -1.49496002e-02,  8.55201948e-03,
       -2.33474094e-03,  1.39780641e-02,  1.82210226e-02,  6.25465903e-03,
       -9.24092159e-03, -1.31926071e-02,  1.02179376e-02,  3.89708928e-03,
       -1.47378817e-02,  3.37034184e-03, -7.49614742e-03, -2.84646023e-02,
       -1.73212979e-02,  1.01647442e-02, -2.38377857e-03, -5.51468413e-03,
        4.28128429e-02, -2.01366376e-02, -9.38933995e-03, -5.68457355e-04,
        1.80988386e-03,  3.25709768e-03, -3.91165912e-02,  6.41286653e-03,
       -5.14721638e-03, -1.93910766e-03, -3.86969484e-02, -2.15757801e-03,
       -6.15127198e-03,  4.87182243e-03,  5.53315831e-03, -8.99910275e-03,
       -2.62729321e-02, -3.29398960e-02, -1.71495434e-02, -1.35030067e-02,
       -1.94892325e-02,  1.70411430e-02, -1.09395832e-02,  1.72767043e-02,
       -1.01562142e-02, -1.41776893e-02,  8.55418015e-03,  6.52689813e-03,
        6.70107128e-03, -3.04670888e-03, -6.69906382e-03, -6.31705218e-04,
       -3.72653967e-03, -4.16896977e-02, -1.47655606e-02, -3.17593734e-03,
       -2.02385969e-02, -1.07952412e-02,  3.82903381e-03,  4.84497694e-04,
        6.10970194e-03,  5.67058707e-03, -1.90914627e-02, -1.46589596e-02,
        3.42486019e-05, -9.88331903e-03, -8.32766015e-03, -1.05618006e-02,
        2.68396921e-02,  2.49449367e-05, -2.32117847e-02, -1.31267169e-02,
       -4.78789676e-03, -2.60519627e-02, -2.24427804e-02,  2.91246199e-03,
       -1.81168262e-02, -9.81335994e-04,  2.86503113e-03,  9.06009972e-03,
        6.22976746e-04, -8.59126169e-03,  3.92265851e-03, -5.22647472e-03,
        3.66961001e-03, -2.66314019e-04, -1.20742386e-02,  1.15547981e-02,
       -2.83010621e-02, -9.19260271e-03,  1.91064784e-03, -1.14582032e-02,
       -6.05431851e-03,  2.73800641e-02, -3.60020879e-03, -3.65255773e-02,
       -2.51018209e-03, -1.42208138e-03,  3.44184297e-03, -1.10187074e-02,
       -1.31044863e-02,  1.60220582e-02,  5.87938726e-03,  5.60315326e-03,
       -1.84167176e-02,  3.39116342e-02, -1.25026572e-02,  1.20599139e-02,
        7.38943089e-03, -6.71658479e-03,  6.96182018e-03,  4.74428106e-03,
       -6.31307531e-03, -4.10004286e-03, -2.76140105e-02,  7.14110024e-03,
        1.81016512e-02, -9.10694152e-03, -5.65915089e-03, -2.75868922e-02,
       -3.34753538e-03, -7.06334738e-03, -2.18656287e-02,  1.12628955e-02,
       -2.26437021e-03,  1.36933653e-02,  1.14140613e-02, -4.34659747e-03,
       -3.56144756e-02, -3.70694399e-02, -2.73511233e-03, -1.52055419e-03,
       -1.70805771e-03,  1.05111590e-02, -1.00222472e-02,  4.62495675e-03,
       -2.21620803e-03, -1.05681028e-02,  7.63280690e-03, -8.33942089e-03,
        9.42512695e-03, -1.33470343e-02,  2.60508507e-02, -4.54246113e-03,
        8.17683525e-03,  9.31449584e-04, -4.40898445e-03,  6.14368590e-03,
       -2.97994446e-03,  3.77433896e-02, -8.20239715e-04, -3.47303250e-03,
        1.11595755e-02, -3.63845797e-03, -1.73584260e-02, -5.90150198e-03,
        2.61958176e-03, -5.09775896e-03, -5.27385343e-03,  1.82577297e-02,
       -2.70135663e-02, -1.21088903e-02, -1.75272636e-02, -5.68532944e-03,
        4.25731821e-04, -2.83429259e-03,  1.99026298e-02,  6.58039143e-03,
        1.74685083e-02,  1.88586698e-03, -1.16132759e-02, -5.88320778e-04,
       -6.33241516e-03,  2.65158061e-03, -3.90559877e-03, -9.08610597e-03,
        3.75600741e-03, -4.66025025e-02,  1.97661631e-02, -5.53832273e-04,
        1.07666012e-02,  5.29664056e-03, -1.08011514e-02,  3.09054181e-02,
       -2.67166570e-02,  4.53174143e-04, -6.69708315e-05,  9.44475923e-03,
       -1.51926484e-02,  7.65777333e-03,  4.12487276e-02, -1.98006518e-02,
       -1.47119267e-02, -6.70922128e-03,  1.56152621e-02, -1.13956761e-02,
       -4.48565278e-03,  9.27769486e-03, -2.09192093e-02, -9.41845588e-03,
       -8.55792314e-03, -1.65973585e-02, -5.00159860e-02, -1.34768179e-02,
        2.62407609e-03,  1.08742686e-02, -3.59871518e-03,  1.38966320e-03,
       -7.14061363e-03,  1.67064182e-02,  1.12042185e-02, -1.84612535e-02,
       -1.21469162e-02, -1.17591508e-02,  3.45668686e-03, -5.01291314e-03,
       -1.54718012e-02, -8.37711152e-03, -9.37408581e-03, -1.97277013e-02,
       -1.34894764e-03, -1.67545769e-02, -1.80051895e-03, -9.50115174e-03,
       -1.30288452e-02,  8.54900852e-03,  2.47685276e-02,  2.75283819e-03,
       -3.20094265e-02, -4.55273269e-03, -6.16970472e-03,  5.51070366e-03,
        1.29968161e-02, -1.21476175e-02,  4.75350115e-03, -1.21772308e-02,
        1.02961436e-02, -5.60803898e-03, -1.22053213e-02,  9.25687980e-03,
       -4.70167631e-03,  1.15015684e-02, -4.56968090e-03, -1.66251287e-02,
       -2.01471429e-02, -1.91265959e-02, -7.02348957e-03, -3.09844799e-02,
       -1.32578705e-02, -2.93696206e-03, -6.47105975e-03, -1.23889092e-02,
       -7.21445726e-03, -2.78051570e-02, -2.23462656e-02, -1.44377630e-02,
       -6.67851791e-03,  5.35347452e-03, -8.55701882e-03, -9.21349227e-03,
       -1.23923717e-04, -3.67197441e-03,  4.25488036e-03, -5.09264087e-03,
       -1.01822671e-02, -1.47781812e-03,  6.53438363e-03, -4.71014204e-03,
       -9.75871831e-03,  8.35624523e-03, -8.21509957e-03, -7.97117874e-03,
        2.71301717e-03,  1.82868596e-02, -8.93007871e-03,  7.23147416e-04,
       -1.97690949e-02,  1.75468496e-03, -2.01842226e-02,  1.64045952e-02,
       -1.08491164e-02, -7.29298359e-03,  6.27727993e-03,  4.87439744e-02,
        9.09168273e-03, -3.85554228e-03, -1.00178150e-02, -1.10604400e-02,
       -6.75833039e-03, -1.28127672e-02, -1.20564625e-02,  6.81494921e-03,
       -1.56102958e-03,  9.63783078e-03,  1.56311151e-02, -1.34765962e-02,
        1.49110286e-02, -1.06026400e-02, -2.28289887e-02, -4.68656374e-03,
       -9.62909835e-04,  3.21831089e-03, -1.32357492e-03, -2.01991089e-02,
        3.81744374e-03, -1.57237996e-03,  4.20390861e-04, -1.47743234e-02,
        9.69367009e-03, -8.14709580e-04, -1.30030550e-02, -6.05144445e-03,
        1.18953793e-03, -1.43644353e-02, -2.71733422e-02, -1.07130772e-02,
       -1.00783845e-02, -6.78924331e-03, -1.74144916e-02, -2.39957757e-02,
        2.02706875e-03, -2.72086225e-02, -4.44633104e-02, -2.99612829e-03,
       -8.78709718e-04, -4.24193870e-03,  3.15036718e-03, -1.28599408e-04,
       -3.24123132e-04, -2.74529797e-03, -1.86126977e-02,  2.66821813e-02,
       -6.69827219e-03, -1.04196207e-03, -4.30215616e-03, -1.70491694e-04,
        1.12289824e-02,  2.28555454e-03, -4.66009136e-03, -2.46757432e-03,
        7.67439511e-03, -4.24175477e-03, -2.02028211e-02, -1.31479613e-02,
        8.37921072e-03, -3.21638286e-02, -3.34537053e-03, -2.35861633e-02,
        2.70872074e-03,  1.62548665e-02, -4.55329008e-02, -7.11634662e-03,
       -1.68508221e-03,  7.75882415e-03, -3.00768390e-02, -5.66444220e-03,
       -2.84558758e-02, -5.86973643e-03, -5.23141213e-03, -1.07538821e-02,
       -9.76736657e-03,  7.72941019e-03,  1.00173813e-03,  2.47343127e-02,
        3.75477411e-03,  2.24569477e-02,  5.19093685e-03, -2.28689378e-03,
       -1.04313567e-02, -2.95201782e-03,  2.30710953e-03,  1.28296297e-03,
       -7.33738206e-03, -9.46989842e-03,  4.61124303e-03,  2.38596927e-02,
        3.20303440e-03,  3.66960000e-03, -1.81472069e-03,  1.61665678e-02,
       -1.92363877e-02, -1.28290020e-02, -5.86185465e-03,  6.51275925e-03,
        1.26210181e-02, -1.08274100e-02,  2.70770695e-02, -9.75034758e-03,
       -2.24539265e-02,  7.53774354e-03, -1.08991330e-02, -4.79267118e-03,
        5.89381391e-03, -2.56513972e-02, -1.56345442e-02, -3.52030843e-02,
        1.54285110e-03, -3.18560153e-02,  9.74512717e-04,  1.87568169e-03,
       -2.06261426e-02,  6.39983360e-03,  8.11821129e-03,  1.21050570e-02,
       -5.72912162e-03, -8.20998847e-03,  8.37324373e-03, -6.20247703e-03,
       -1.29999053e-02, -1.53671829e-02,  7.79949734e-03, -3.33790551e-03,
        3.06453812e-03, -1.65923722e-02,  2.84942775e-03, -1.76428296e-02,
       -1.12544866e-02, -1.98676977e-02,  1.10263359e-02,  9.78606753e-03,
       -1.27609493e-02,  5.80241554e-04,  8.73518363e-03,  1.04939211e-02,
       -1.68109243e-03, -1.50462985e-02, -3.25130182e-03, -5.58621716e-03,
       -8.72742664e-03, -1.81436036e-02,  2.23106854e-02, -1.40986014e-02,
       -7.31430529e-03, -6.92543713e-03, -5.37570193e-02,  5.67709375e-03,
        6.91061700e-03,  5.27261011e-03,  1.32652000e-02, -6.64062798e-03,
       -1.17895948e-02, -4.44803201e-02, -3.20748799e-03,  1.26162246e-02,
       -1.11196153e-02, -1.41893132e-02,  1.54254725e-02,  1.74505580e-02,
        5.42386761e-03,  1.23359216e-02,  5.24031883e-03,  2.28491356e-03,
        1.96121987e-02,  1.17979310e-02, -4.17629629e-03, -1.13713723e-02,
       -6.01621205e-03,  1.07371043e-02, -4.76196641e-03, -7.05393916e-03,
        1.17702121e-02, -6.50637271e-03, -1.28396302e-02,  3.97801306e-03,
       -4.98037692e-03, -1.04263499e-02,  4.26460290e-03, -2.89482903e-02,
       -9.04255174e-03, -6.60177227e-03, -5.22910058e-03, -8.56246706e-03,
       -4.52126842e-03,  1.18922228e-02, -1.09582033e-03, -1.61577929e-02,
       -2.15897001e-02,  7.52357673e-03, -1.82263982e-02,  1.20162657e-02,
        4.17742366e-03, -3.02117374e-02,  5.95798623e-03, -1.17628444e-02,
       -7.39151053e-03, -1.34554487e-02, -8.12256418e-04, -3.08927018e-02,
       -4.73359376e-02, -1.84227794e-03, -1.14222169e-02, -1.62702035e-02,
       -1.11968108e-02, -1.90775795e-03,  9.98144690e-03,  7.91456364e-03,
       -3.00382245e-02, -3.27197975e-03, -4.25872114e-03, -1.13632688e-02,
        2.13098545e-02, -7.35842576e-03, -5.93303330e-03,  4.30115080e-03,
        7.03954138e-03,  2.92076394e-02, -5.15980646e-04,  1.36850961e-03,
       -1.47636479e-03, -9.15421173e-03,  1.07979216e-02,  5.86380600e-04,
       -9.38833971e-03,  1.59554440e-03, -2.43404061e-02,  1.09053391e-03,
       -1.19590946e-02,  7.06608221e-03, -1.28976535e-06, -1.27204810e-04,
        2.41186488e-02, -1.10806869e-02,  1.27861397e-02, -3.51832015e-03,
       -1.89936080e-04, -1.21820532e-02,  6.65855641e-03, -2.13300693e-04,
       -1.47662377e-02,  1.09049361e-02,  2.67408346e-03, -1.32555682e-02,
       -2.74132052e-03, -2.79932041e-02, -2.00708173e-02, -2.55159549e-02,
        1.13427835e-02, -7.27490894e-03, -5.05075715e-02,  8.29094648e-03,
       -1.53026516e-02,  1.01637077e-02, -3.17893177e-03, -2.28277724e-02,
       -1.25978524e-02, -1.83256567e-02, -5.32092666e-03, -1.54611804e-02,
        7.15043116e-03, -2.46051583e-03,  1.62455870e-03, -4.86219162e-03,
       -3.21768806e-03,  7.63267465e-03, -2.12385505e-02, -2.83507514e-04,
       -4.02526697e-03, -5.25157619e-03,  2.01541092e-02, -3.49799870e-03,
       -5.92903839e-03, -8.24319385e-03,  2.59618852e-02,  1.43221894e-03],
      dtype=float32), array([-0.03478388,  0.03891828, -0.02142139, -0.01660002, -0.0096509 ,
        0.06468214, -0.01574652, -0.03948111, -0.01971505, -0.04135519,
        0.05131129, -0.04007397,  0.0153808 , -0.01356358,  0.00798468,
       -0.01446387, -0.0343178 ,  0.027404  ,  0.01423287, -0.07990194,
        0.02110836, -0.00657183, -0.0257389 , -0.04513418, -0.03278926,
       -0.01268775, -0.02705285, -0.02564191, -0.05293634,  0.00374563,
        0.05221115, -0.04237606, -0.04569647,  0.02007042, -0.02015531,
       -0.00853657,  0.00191036, -0.03733969, -0.01455485, -0.03714091,
        0.00916066, -0.02875266, -0.03982881,  0.03442377, -0.02488241,
       -0.00608708, -0.02207626,  0.02146234, -0.02556597, -0.00739311,
       -0.03678714,  0.03292105, -0.02471709,  0.0198247 , -0.02892473,
       -0.02856186, -0.02012423,  0.02822584,  0.04843681,  0.06197025,
        0.01786886,  0.0108338 ,  0.03847497, -0.04226705, -0.07474447,
        0.05884344,  0.04964082, -0.01174908,  0.03940971,  0.07005637,
       -0.02791666,  0.00204769,  0.04928799,  0.01737917, -0.06915429,
        0.01415372, -0.00212662, -0.03368841, -0.01600244,  0.04646955,
       -0.0263366 , -0.03557294, -0.05209808, -0.03056587, -0.01338578,
        0.0213913 ,  0.02113534,  0.03127551, -0.02069276, -0.05505785,
       -0.01056616,  0.1013377 ,  0.0622652 ,  0.05795062,  0.06413244,
        0.0282372 ,  0.03232478, -0.05687005, -0.00398684, -0.01434552,
        0.02978241,  0.02172933,  0.02942567,  0.01508724,  0.01674989,
        0.05399601,  0.05260819,  0.02859869,  0.03119306,  0.04243638,
       -0.00114216, -0.03795088,  0.03465962,  0.01173291,  0.0145114 ,
       -0.04678639, -0.03481552, -0.01666607, -0.0265533 ,  0.03258191,
       -0.02964939, -0.03073226, -0.03835735,  0.06964597, -0.05346686,
        0.04649382, -0.01079036, -0.036831  ,  0.00261093, -0.06900121,
       -0.0065989 , -0.00306866, -0.04866647, -0.01250111, -0.04420608,
       -0.051941  , -0.04525348,  0.03394385, -0.03769089,  0.00655961,
        0.01784665, -0.05039904, -0.01103286, -0.02120095, -0.06746617,
        0.0128634 , -0.02890205,  0.05983387, -0.02179447, -0.01785632,
        0.0415553 , -0.00989311, -0.00391646,  0.04806479, -0.05728076,
       -0.02718457, -0.0158134 , -0.00576755,  0.06157364,  0.03161239,
       -0.02135906, -0.01491119,  0.03496864,  0.0550218 , -0.01645418,
       -0.04345049,  0.01492302,  0.04909418, -0.02442372,  0.02682258,
       -0.0243942 , -0.00687903, -0.0289406 ,  0.03186861, -0.02629683,
       -0.02184824, -0.01380266, -0.04179464,  0.01220995,  0.04323398,
        0.04684121, -0.0237508 ,  0.00113637,  0.04621538, -0.04899707,
        0.00093671, -0.02928502,  0.05625295,  0.00204145,  0.02981611,
        0.07088215, -0.00987529, -0.03129632, -0.02871151,  0.09244391,
        0.0001335 ,  0.03841922, -0.06569714,  0.01684927,  0.02910745,
        0.04925226,  0.02088839, -0.0021546 , -0.06850596, -0.00435091,
       -0.05664925,  0.01701797,  0.00651801,  0.03667078, -0.01430262,
        0.01625531, -0.01156169, -0.04999101, -0.04066526, -0.02700238,
       -0.04438518,  0.03987622,  0.0448948 ,  0.02856771, -0.02195397,
       -0.01771201,  0.05887011,  0.02408684, -0.01705266, -0.05914281,
       -0.00902194,  0.06918168,  0.03678862, -0.0096664 , -0.00981927,
       -0.03959867,  0.01342039, -0.02076369,  0.02626386,  0.04038503,
       -0.04214811, -0.01373217,  0.03506495,  0.06980212, -0.05190068,
        0.06417644, -0.01155772, -0.04190093, -0.04238499, -0.00503939,
        0.00770447, -0.02232338, -0.01351544, -0.0256277 , -0.01076808,
        0.02140947, -0.0132566 ,  0.0479966 , -0.00383287, -0.00120074,
        0.06680483, -0.01493522, -0.04435921, -0.03948326,  0.05762948,
       -0.0353604 ,  0.0394269 ,  0.06111812,  0.04297678,  0.04880593,
       -0.04723832, -0.02500356,  0.02264545,  0.02596368,  0.00607636,
       -0.02870274, -0.05714068, -0.06323432,  0.02665591, -0.00055636,
       -0.03297986,  0.04750181, -0.04539142,  0.06775621, -0.03914044,
        0.04379047,  0.01048314, -0.05144309,  0.04873568, -0.01778483,
       -0.01532022,  0.016779  , -0.03406392, -0.05130772,  0.03202177,
       -0.05055008,  0.00641005,  0.04912883,  0.04336033, -0.02659798,
        0.01329927, -0.02814179,  0.05231212,  0.02759473, -0.0224738 ,
       -0.02844118, -0.03744995, -0.00055653, -0.0017867 ,  0.03618789,
       -0.02033905, -0.03297909,  0.06177193, -0.0055286 , -0.05410127,
        0.04806979,  0.03971838, -0.00242066,  0.01008598, -0.04249469,
        0.0548502 ,  0.01793178, -0.01438201,  0.0234793 , -0.05377644,
       -0.05892683, -0.02157382, -0.02381654, -0.03594001,  0.11881344,
        0.03586587,  0.03586982, -0.00750179, -0.03431324,  0.0145709 ,
        0.00802227,  0.01599316, -0.01433668, -0.03017126,  0.04619908,
       -0.02764608,  0.0083395 , -0.02675809, -0.0244457 ,  0.03108486,
       -0.04464322,  0.08447102, -0.04608512,  0.06989526,  0.00448191,
       -0.04579196,  0.01736549, -0.04206531,  0.07086337, -0.02369263,
       -0.04053888,  0.02752433,  0.0545716 , -0.06358367, -0.04825765,
        0.04869553,  0.03719322, -0.03563164,  0.01482034,  0.00059154,
        0.04584174,  0.0181595 ,  0.06538564,  0.0203751 ,  0.00654727,
       -0.00739162,  0.05020529,  0.04347729,  0.01517846, -0.03736563,
       -0.03119345, -0.01251171, -0.0290098 , -0.05421172, -0.02752204,
        0.02310537,  0.0475624 , -0.03883898, -0.01869638, -0.0327392 ,
        0.0151066 , -0.0260958 , -0.03017761,  0.02901374,  0.02287175,
       -0.04457473,  0.0283191 ,  0.05145072,  0.04839909,  0.01170627,
       -0.03842307, -0.05203165,  0.10402238,  0.0032461 ,  0.03686251,
       -0.0370165 , -0.02001581, -0.01521881,  0.02940675, -0.03529732,
       -0.01986449, -0.06585054,  0.06090144, -0.03461204, -0.02831375,
       -0.00583613, -0.03946855, -0.02473573,  0.01799998,  0.05667394,
        0.00368618,  0.06165877,  0.06673872,  0.00416063, -0.01248819,
       -0.0175835 ,  0.00794614,  0.03981928,  0.02902693,  0.07598267,
        0.07142601, -0.05193689, -0.04005032, -0.0623297 , -0.02360018,
        0.05549715,  0.02777072, -0.0062972 ,  0.0504351 ,  0.01577904,
       -0.02400545, -0.04512947,  0.01768086,  0.01732128,  0.05291258,
        0.03234912, -0.02268472, -0.02709287,  0.04501248, -0.06336066,
        0.03969644,  0.02985099,  0.03027985, -0.04839123, -0.01232365,
        0.03833075, -0.02320448, -0.03506951, -0.01104566, -0.05274273,
        0.04917587,  0.01933334,  0.016007  ,  0.07403916,  0.05853711,
       -0.01919048, -0.06203121,  0.02535104, -0.02768653, -0.00634473,
       -0.03351714,  0.00603115,  0.05193752,  0.01213622, -0.02302457,
        0.04166705, -0.00360719,  0.06547072,  0.01784092, -0.00099901,
        0.00889811,  0.05735411, -0.03572218, -0.01736675, -0.02183084,
        0.02257107,  0.03644164,  0.054837  ,  0.02935767,  0.02034083,
        0.03621014, -0.03715613,  0.04317744,  0.05783464, -0.01587106,
        0.04800417,  0.0662221 ,  0.03563752, -0.02816487, -0.0249352 ,
       -0.03268623, -0.02977114, -0.02372965, -0.00256435,  0.04761853,
        0.00370646,  0.00676418, -0.06353956,  0.00567098, -0.06333893,
        0.01756594, -0.0058267 , -0.02412214,  0.02530253, -0.02465518,
        0.01281242,  0.04716346,  0.05347438, -0.02294345,  0.06075604,
       -0.06204337,  0.04021167,  0.04949277, -0.01509344,  0.06510662,
        0.03415453,  0.00204297, -0.08070953,  0.06281018, -0.02957296,
        0.07497799,  0.03795697,  0.00059142, -0.00803777, -0.02116907,
       -0.05396372, -0.03535094, -0.05021672, -0.03721783, -0.04608347,
        0.0102648 ,  0.05755519,  0.0024121 ,  0.02585019,  0.00750846,
       -0.03722083, -0.03400737, -0.03321967, -0.02239469, -0.03929521,
       -0.02519024, -0.01365083, -0.00781786, -0.03313825,  0.06313305,
        0.00276962,  0.00844953,  0.03988571, -0.00695698,  0.00981072,
        0.00169276,  0.05405335,  0.03105113,  0.02973042,  0.01915156,
        0.02620519, -0.02205976,  0.04111593,  0.04235539,  0.07725354,
        0.05883314,  0.06472202,  0.03367789, -0.02513632, -0.05004916,
        0.00986308, -0.02950468, -0.0465745 ,  0.05187548,  0.06378512,
       -0.03285201,  0.04379529, -0.03266279,  0.03392592, -0.02538381,
       -0.01039819,  0.00783261,  0.06038478,  0.00044983,  0.07904547,
       -0.0136535 ,  0.07397391, -0.04540603, -0.0387563 , -0.02686981,
       -0.00661774,  0.02473298,  0.02363113, -0.03938591, -0.02918967,
       -0.03589984,  0.0133403 ,  0.03434142,  0.03816281, -0.03742503,
        0.05271655,  0.01368355, -0.00322322,  0.06017436, -0.0140702 ,
       -0.03012303,  0.01906336,  0.04387574,  0.00780772, -0.0005499 ,
        0.05184021, -0.04494621, -0.03143357,  0.04879121,  0.02017507,
       -0.0157048 , -0.01384801,  0.00345429,  0.02739131, -0.01731206,
        0.0354994 , -0.04844412,  0.02315247,  0.02564879,  0.04263895,
        0.03649592, -0.01762304, -0.01583199,  0.03334156,  0.02012712,
        0.03813662,  0.02707428, -0.05311039, -0.0168419 , -0.00108723,
       -0.00363693,  0.08671383, -0.02894937, -0.00898939, -0.02731498,
       -0.00170022, -0.0281585 ,  0.03463896, -0.02313094,  0.02188124,
       -0.0449071 ,  0.02956211,  0.03584869, -0.0678485 , -0.01695305,
        0.01888293,  0.06217003,  0.01558195, -0.01454817,  0.01148985,
       -0.02794764,  0.0667515 ,  0.05455612,  0.01366959,  0.00398362,
        0.0637639 , -0.03031402,  0.01392822,  0.02134824, -0.01448888,
       -0.02067644, -0.03681679,  0.02446178, -0.0188055 , -0.03192842,
       -0.01647156, -0.00818934,  0.03390878,  0.02632515,  0.02418454,
        0.0134954 , -0.01814434, -0.00095152,  0.02688702, -0.00892656,
        0.00228707,  0.02348773, -0.03273381,  0.067054  , -0.03164864,
       -0.00980152,  0.04226429,  0.03222047, -0.01745199,  0.01145211,
       -0.00505854,  0.0068446 , -0.02216111, -0.02873816, -0.03631118,
       -0.03509768, -0.01776411,  0.04259306, -0.01716873, -0.03404485,
       -0.02993427,  0.03777216,  0.04181659,  0.05430995,  0.05801726,
       -0.05270186, -0.01461648,  0.07000636,  0.0034715 ,  0.01502654,
       -0.05588938, -0.02456483,  0.02780104, -0.00423619,  0.05775251,
       -0.02817493,  0.02890342,  0.02975849,  0.03293675, -0.05469901,
       -0.04324451, -0.00734451, -0.03149553,  0.03677493, -0.01615833,
        0.03405508, -0.03385615, -0.07325182, -0.01202562, -0.02037271,
       -0.03601215, -0.03798296, -0.04117531], dtype=float32), array([0.09318811, 0.10077559, 0.08783451, 0.0847643 , 0.11663136,
       0.11641219, 0.09247172, 0.10554818, 0.0865861 , 0.09204174,
       0.09766335, 0.10194185, 0.09171139, 0.09402598, 0.09145781,
       0.08200171, 0.09832266, 0.0840075 , 0.10225698, 0.13519518,
       0.09880948, 0.08793212, 0.08765338, 0.09576848, 0.08356109,
       0.08964942, 0.09540791, 0.08878792, 0.09006754, 0.08754279,
       0.11359609, 0.09525072, 0.08603173, 0.09598733, 0.08420991,
       0.08608915, 0.0839413 , 0.1073886 , 0.08357809, 0.09235135,
       0.08589058, 0.08760273, 0.09184343, 0.08783662, 0.08416119,
       0.08875823, 0.09059497, 0.09791088, 0.08507609, 0.09801963,
       0.08937052, 0.08798809, 0.0911326 , 0.08532767, 0.0867537 ,
       0.08870605, 0.10168742, 0.11060353, 0.09166604, 0.12197489,
       0.08727442, 0.08364557, 0.09060033, 0.09996577, 0.10137589,
       0.11865819, 0.09367283, 0.09088203, 0.10753218, 0.1087474 ,
       0.08737318, 0.09000017, 0.09560637, 0.09761663, 0.11159369,
       0.08765794, 0.08323027, 0.08988009, 0.0850282 , 0.09067173,
       0.0923842 , 0.09052564, 0.11696818, 0.0887399 , 0.08657266,
       0.08629579, 0.08681946, 0.09367067, 0.08449668, 0.09661438,
       0.08576988, 0.14445737, 0.11870538, 0.0946096 , 0.1084195 ,
       0.11056416, 0.09309833, 0.09290945, 0.08851028, 0.08732294,
       0.09452097, 0.09625538, 0.09675845, 0.09237381, 0.09001993,
       0.11570819, 0.08814321, 0.10056639, 0.0947116 , 0.09497573,
       0.08952901, 0.10395847, 0.09576523, 0.08664254, 0.0841449 ,
       0.09693527, 0.08557202, 0.08380367, 0.0853183 , 0.09443033,
       0.08559095, 0.08432817, 0.09027661, 0.11333821, 0.09906673,
       0.09241078, 0.09012842, 0.08804704, 0.08377261, 0.11021423,
       0.09179848, 0.08312078, 0.09711009, 0.08714571, 0.09527099,
       0.08894807, 0.09006298, 0.08406739, 0.09217464, 0.09188332,
       0.09134925, 0.0929442 , 0.08317257, 0.08470678, 0.11191831,
       0.08584922, 0.09618121, 0.09152554, 0.09582562, 0.08493901,
       0.1033943 , 0.0869223 , 0.08770098, 0.10092662, 0.1066938 ,
       0.09000763, 0.08571965, 0.08494285, 0.10099452, 0.09057708,
       0.08591332, 0.08928215, 0.10385091, 0.09862286, 0.08511749,
       0.10193056, 0.0878085 , 0.09401669, 0.09872639, 0.08494904,
       0.09213058, 0.08374148, 0.08357011, 0.09121218, 0.09042817,
       0.09102865, 0.09613663, 0.09477077, 0.08210816, 0.10421071,
       0.09713586, 0.08730885, 0.08478916, 0.10167868, 0.10379829,
       0.08539736, 0.08439232, 0.10533544, 0.0839911 , 0.09091086,
       0.12365704, 0.0825512 , 0.08361767, 0.08841995, 0.12716264,
       0.1024701 , 0.09345902, 0.10171206, 0.09057265, 0.09024651,
       0.12115551, 0.10126733, 0.09241428, 0.09887732, 0.09454334,
       0.10076007, 0.08509892, 0.09142958, 0.09057799, 0.08320513,
       0.08571069, 0.08276811, 0.10046218, 0.09490167, 0.09301574,
       0.09429986, 0.09013925, 0.095022  , 0.09242555, 0.08517702,
       0.08915482, 0.1044042 , 0.08812941, 0.09001317, 0.11250475,
       0.08407589, 0.11559883, 0.09283447, 0.0831788 , 0.08689249,
       0.09057605, 0.09573761, 0.09916109, 0.09337659, 0.0899955 ,
       0.09309509, 0.08546206, 0.08956259, 0.1130304 , 0.09649847,
       0.10870284, 0.09017642, 0.10076634, 0.09057808, 0.08393551,
       0.08479727, 0.09127993, 0.0884032 , 0.08942089, 0.08644991,
       0.08732367, 0.08541553, 0.121568  , 0.08335821, 0.08622836,
       0.12037521, 0.08415127, 0.10144813, 0.0917799 , 0.09460171,
       0.08763708, 0.09439245, 0.10100471, 0.09770743, 0.09789106,
       0.10158829, 0.10336825, 0.09096351, 0.10417479, 0.10720225,
       0.08494046, 0.10217279, 0.10816372, 0.10970861, 0.08516941,
       0.0924904 , 0.09813726, 0.08639403, 0.10781417, 0.08374076,
       0.09709653, 0.0822282 , 0.09426887, 0.10900024, 0.08813333,
       0.08498614, 0.08886789, 0.09470464, 0.09014372, 0.10374881,
       0.10536175, 0.08500201, 0.10784882, 0.10314494, 0.08519791,
       0.08231153, 0.0876306 , 0.09018558, 0.09257687, 0.08620715,
       0.09459224, 0.09129121, 0.08466599, 0.08460323, 0.09206416,
       0.09049004, 0.09053259, 0.09824972, 0.08695758, 0.08941966,
       0.09805613, 0.10635181, 0.08314294, 0.10343181, 0.09800763,
       0.09830014, 0.08605453, 0.08706483, 0.09089454, 0.110273  ,
       0.1006877 , 0.08710513, 0.08676402, 0.09067323, 0.2012118 ,
       0.09451722, 0.09224518, 0.08450168, 0.08584869, 0.08492773,
       0.08660965, 0.08363254, 0.08740465, 0.09061736, 0.09012099,
       0.08854645, 0.08503983, 0.08780268, 0.08991665, 0.09106639,
       0.09277547, 0.14740919, 0.08985548, 0.12064261, 0.08906133,
       0.10296586, 0.08473855, 0.08988207, 0.11862585, 0.08842942,
       0.09196582, 0.09733161, 0.1028865 , 0.10419038, 0.0960641 ,
       0.11379831, 0.08937369, 0.08322002, 0.09090349, 0.08824047,
       0.10467824, 0.09194744, 0.10076988, 0.0936608 , 0.08625235,
       0.09557345, 0.12830545, 0.0959743 , 0.08670709, 0.09751508,
       0.10291253, 0.09008457, 0.11002226, 0.0893804 , 0.09286224,
       0.08549663, 0.09270147, 0.10204013, 0.08593623, 0.09020109,
       0.09371986, 0.09309265, 0.09169786, 0.10475829, 0.08835819,
       0.0946205 , 0.09132774, 0.10391854, 0.10255556, 0.08315965,
       0.08795431, 0.10463654, 0.15004788, 0.0900993 , 0.09681046,
       0.10499687, 0.08662695, 0.08401884, 0.08771028, 0.08619972,
       0.09190957, 0.12909436, 0.1083323 , 0.09453958, 0.09163447,
       0.09345222, 0.08985407, 0.10363708, 0.08783793, 0.10509727,
       0.08254942, 0.1269828 , 0.10944408, 0.08457294, 0.08659866,
       0.11328135, 0.08472567, 0.10716658, 0.09244933, 0.12295041,
       0.12148051, 0.09936952, 0.09456555, 0.11398106, 0.08947468,
       0.09452526, 0.08735133, 0.08359161, 0.09924452, 0.08622269,
       0.09235948, 0.08985495, 0.08586194, 0.08908301, 0.10662275,
       0.09392533, 0.08616681, 0.100244  , 0.10656668, 0.10225891,
       0.09691911, 0.08736882, 0.10187875, 0.09248658, 0.08511402,
       0.09862307, 0.08914938, 0.09197666, 0.08749371, 0.08526912,
       0.08513058, 0.08991829, 0.08825426, 0.11382119, 0.09844513,
       0.08445419, 0.09049916, 0.10361015, 0.10541159, 0.09204022,
       0.10100547, 0.08454765, 0.10238999, 0.08832064, 0.08630802,
       0.09308368, 0.084348  , 0.12506427, 0.08971832, 0.08757412,
       0.08637264, 0.09862209, 0.09164952, 0.08736568, 0.08371061,
       0.09099308, 0.09623127, 0.10341802, 0.11460853, 0.08728997,
       0.09318711, 0.10266402, 0.09566499, 0.10645884, 0.08277314,
       0.09686966, 0.14596571, 0.09836581, 0.11237474, 0.08749332,
       0.10004847, 0.09209016, 0.09045903, 0.0830977 , 0.10253283,
       0.08957884, 0.08198254, 0.11423516, 0.08458342, 0.09357626,
       0.09938943, 0.08749627, 0.110521  , 0.09151241, 0.09399761,
       0.08412421, 0.10143247, 0.10729639, 0.09056601, 0.11573394,
       0.10299717, 0.09985829, 0.08978737, 0.08708402, 0.12310368,
       0.09325753, 0.08702608, 0.10899924, 0.11304559, 0.09409432,
       0.12899384, 0.08993576, 0.08325105, 0.08399945, 0.08841627,
       0.09764929, 0.09041332, 0.09924321, 0.09791717, 0.10146678,
       0.09259396, 0.09074986, 0.08646422, 0.08604554, 0.08608446,
       0.08771189, 0.09035437, 0.08835617, 0.08912537, 0.09521846,
       0.09123144, 0.08492773, 0.08308291, 0.10117702, 0.10063819,
       0.08975608, 0.08462468, 0.09820672, 0.08991719, 0.09133724,
       0.09248312, 0.09631368, 0.09017698, 0.09564004, 0.08676435,
       0.08486598, 0.09110437, 0.09380084, 0.09899914, 0.11482862,
       0.11092051, 0.10933895, 0.09239754, 0.09203174, 0.09236965,
       0.08897935, 0.09211978, 0.08743577, 0.08991768, 0.11877542,
       0.09015939, 0.09120102, 0.10359728, 0.09012447, 0.09310331,
       0.08574253, 0.09616913, 0.09221795, 0.08576109, 0.10827636,
       0.08667438, 0.11618008, 0.09374653, 0.09319247, 0.09257156,
       0.08205011, 0.08941998, 0.09453069, 0.08647536, 0.08670904,
       0.08676853, 0.08253229, 0.09386424, 0.10460391, 0.10019775,
       0.11760528, 0.08368649, 0.0834127 , 0.11431691, 0.08863255,
       0.09026286, 0.1021628 , 0.10942513, 0.09389479, 0.08355732,
       0.13903987, 0.10052833, 0.10753317, 0.09846866, 0.09670313,
       0.08593526, 0.0866484 , 0.08566026, 0.09750783, 0.0862462 ,
       0.09339286, 0.11075091, 0.09237689, 0.08493605, 0.08779916,
       0.09295741, 0.08721962, 0.08326014, 0.08614096, 0.10051108,
       0.09082834, 0.09503221, 0.08947024, 0.08643809, 0.08328857,
       0.08942502, 0.12880822, 0.08682512, 0.08218943, 0.08921098,
       0.09826462, 0.09974114, 0.08815937, 0.08612453, 0.08690979,
       0.09199898, 0.10736635, 0.09554924, 0.1103548 , 0.0839964 ,
       0.09369201, 0.12877722, 0.08378407, 0.08546139, 0.09014496,
       0.08494636, 0.11545071, 0.11485205, 0.08534082, 0.0852146 ,
       0.1365347 , 0.08490051, 0.09665811, 0.09912863, 0.08933215,
       0.11907648, 0.08701974, 0.08875829, 0.0869246 , 0.09252183,
       0.08559888, 0.08188263, 0.09745678, 0.09294941, 0.10275899,
       0.0834374 , 0.09112698, 0.08809066, 0.08644494, 0.08721075,
       0.08427861, 0.08576107, 0.09631522, 0.1164548 , 0.09326511,
       0.0879534 , 0.09282085, 0.09742542, 0.08948115, 0.10270829,
       0.08282315, 0.08958255, 0.08499917, 0.09350661, 0.09466004,
       0.08406515, 0.08405249, 0.09197577, 0.08717398, 0.08650544,
       0.0829566 , 0.10121377, 0.10116562, 0.09725351, 0.10302398,
       0.09694425, 0.09048209, 0.10773294, 0.08548689, 0.10387593,
       0.09851757, 0.08436777, 0.10677732, 0.08346704, 0.09963001,
       0.09225409, 0.08684971, 0.08877518, 0.08918823, 0.09319792,
       0.09315301, 0.08682492, 0.08921637, 0.09297112, 0.08790173,
       0.09161893, 0.08650678, 0.10473701, 0.08292691, 0.09233563,
       0.08772083, 0.09199648, 0.08943833], dtype=float32), array([[[[ 0.00582002],
         [ 0.01478895],
         [ 0.00703976],
         ...,
         [ 0.02117654],
         [-0.01015156],
         [ 0.03606746]],

        [[-0.01233193],
         [ 0.04279868],
         [-0.01382647],
         ...,
         [ 0.00960084],
         [ 0.00988438],
         [ 0.01756179]],

        [[ 0.02017011],
         [ 0.00600121],
         [ 0.00721608],
         ...,
         [-0.01750104],
         [-0.0123879 ],
         [ 0.02288493]]],


       [[[-0.01113654],
         [-0.015055  ],
         [ 0.01851451],
         ...,
         [-0.00361165],
         [ 0.04327583],
         [-0.00880454]],

        [[ 0.01646689],
         [-0.00650725],
         [ 0.01309269],
         ...,
         [ 0.0336828 ],
         [ 0.01207929],
         [-0.01491064]],

        [[-0.00935906],
         [ 0.01898217],
         [-0.0265207 ],
         ...,
         [-0.01141486],
         [-0.01207888],
         [-0.01783566]]],


       [[[ 0.01807587],
         [ 0.02426292],
         [ 0.01532341],
         ...,
         [-0.00298739],
         [ 0.02227137],
         [-0.01258134]],

        [[-0.0078413 ],
         [-0.00152026],
         [ 0.02722903],
         ...,
         [-0.0074449 ],
         [ 0.03248908],
         [ 0.00705089]],

        [[ 0.0197638 ],
         [-0.00631755],
         [ 0.01852665],
         ...,
         [-0.00404941],
         [ 0.01616549],
         [ 0.00937503]]]], dtype=float32), array([[[[ 0.0232019 ,  0.03851517, -0.01375855, ...,  0.01199793,
          -0.02056498, -0.01072506],
         [-0.05436028, -0.02325137, -0.03881736, ..., -0.03635558,
           0.03276021,  0.05424371],
         [-0.05536885, -0.05767803, -0.00622033, ..., -0.02101743,
           0.01629937, -0.04795737],
         ...,
         [-0.00592339, -0.00130431, -0.04551167, ...,  0.02923208,
           0.02440488, -0.02945252],
         [-0.02618047,  0.01878309,  0.04473126, ..., -0.03634514,
          -0.02630754,  0.04879129],
         [-0.00358659, -0.0171846 , -0.03184023, ..., -0.03554366,
           0.05136623,  0.04382347]]]], dtype=float32), array([1.0137253 , 1.0138625 , 0.9910225 , 1.0085545 , 1.0010799 ,
       1.0049403 , 0.9901193 , 1.0191388 , 1.0001085 , 1.0177027 ,
       1.0096613 , 1.0067185 , 1.0006635 , 1.0095226 , 1.0038879 ,
       1.0081029 , 0.9980927 , 0.9933643 , 1.0044806 , 1.0064119 ,
       0.9986713 , 1.0051827 , 1.026201  , 0.99741936, 1.004256  ,
       0.9984316 , 1.0063604 , 1.0146488 , 0.97948045, 0.9978933 ,
       0.99659795, 1.0165662 , 1.0057387 , 0.99176043, 0.9929544 ,
       1.0198338 , 0.9807197 , 0.9997513 , 1.0104058 , 0.99669075,
       0.99807954, 0.9969302 , 0.9989579 , 1.0108314 , 1.0104883 ,
       1.0337617 , 0.9910113 , 1.005035  , 1.0299196 , 1.016216  ,
       1.0058694 , 1.000765  , 1.006602  , 1.0085663 , 0.99668175,
       0.9849805 , 0.99135035, 1.0082836 , 1.0134141 , 0.989191  ,
       1.0057703 , 1.0048356 , 0.99838775, 1.0070543 , 0.9951151 ,
       1.0159217 , 1.011793  , 0.989485  , 1.0017962 , 0.99309534,
       0.99688345, 0.9975254 , 0.9912481 , 0.99735534, 1.0131161 ,
       1.0009707 , 1.0043119 , 0.9855673 , 0.99788564, 1.0048271 ,
       1.0102613 , 1.0187657 , 0.9997653 , 1.003001  , 1.024167  ,
       1.0044855 , 0.99245036, 0.9954678 , 1.0093585 , 0.99696505,
       1.0044436 , 0.994188  , 0.99092144, 1.0063103 , 1.0131432 ,
       0.9800833 , 1.0240189 , 1.0067258 , 1.0039066 , 0.99998796,
       0.99001276, 1.0062665 , 1.021759  , 1.0006609 , 1.003301  ,
       0.9952931 , 0.9922884 , 1.0084647 , 0.9909693 , 1.0116464 ,
       1.0035294 , 1.015553  , 1.0002776 , 0.9962286 , 1.016493  ,
       0.9914135 , 1.013331  , 1.020433  , 1.0081756 , 0.9972067 ,
       0.9968984 , 1.0003979 , 0.9991375 , 1.0065377 , 0.9967334 ,
       0.9989846 , 1.0025802 , 1.0164948 , 0.99252206, 1.004291  ,
       1.0142052 , 1.0120775 , 0.99517167, 1.0003005 , 0.99806035,
       1.0069749 , 1.0287607 , 1.0006542 , 0.9884127 , 1.0249768 ,
       0.9890291 , 1.0018244 , 1.0038537 , 0.995124  , 1.026813  ,
       0.98279285, 0.99969405, 1.0112773 , 0.99512   , 0.9803305 ,
       1.0034398 , 1.014533  , 0.9887662 , 0.986323  , 1.0043522 ,
       1.0015825 , 1.0032713 , 1.0023103 , 1.0010861 , 0.99363387,
       1.002556  , 1.0005006 , 1.0236439 , 1.0007654 , 0.9891189 ,
       0.9983228 , 0.9907316 , 0.98961127, 1.0058466 , 1.0023396 ,
       1.0045795 , 0.993951  , 1.0052308 , 1.0137134 , 1.0159527 ,
       1.00289   , 0.9991902 , 1.0072198 , 1.005026  , 0.9887354 ,
       1.0120285 , 1.0166445 , 0.9780074 , 0.9997969 , 0.9767248 ,
       1.0100719 , 1.0308491 , 1.0078149 , 0.9891064 , 0.98830277,
       0.99594593, 0.9731069 , 0.9982837 , 0.9891367 , 1.0074792 ,
       1.0120977 , 1.0060507 , 1.0102443 , 1.0105684 , 1.006268  ,
       1.0166233 , 0.9915327 , 1.0241944 , 1.0144128 , 1.0187823 ,
       0.99467963, 1.0101308 , 1.0028455 , 0.99690753, 1.0112402 ,
       0.9887373 , 1.0150908 , 0.9858805 , 0.9986788 , 0.98109484,
       0.99411476, 1.0152332 , 0.9893856 , 0.99639136, 0.9896902 ,
       1.0105387 , 1.0091779 , 0.9959149 , 1.0154214 , 1.0146695 ,
       0.9969274 , 0.98887295, 1.0231202 , 0.9945113 , 0.99738294,
       0.99751043, 1.0168877 , 0.99639106, 1.0121464 , 0.9985845 ,
       1.0120796 , 0.998921  , 1.0023465 , 1.006092  , 0.9959245 ,
       0.99104714, 1.0198014 , 0.99876404, 0.98397994, 1.0002991 ,
       1.0016087 , 0.9928845 , 1.0118942 , 0.9995848 , 1.0105786 ,
       0.9872143 , 1.0005004 , 0.98739284, 1.0094514 , 1.007616  ,
       0.9997803 , 0.99724245, 1.0010307 , 1.0004823 , 1.0035912 ,
       0.99370533, 0.9840328 , 0.99942744, 1.0106003 , 0.989752  ,
       1.0155627 , 0.98644733, 1.0064597 , 1.0045557 , 0.98830515,
       0.9919287 , 0.9894159 , 1.0021937 , 1.0122062 , 1.013689  ,
       1.0043737 , 0.9910882 , 1.0237924 , 0.99074847, 1.0043138 ,
       1.0125713 , 0.99920857, 1.0042487 , 0.9973092 , 1.0086987 ,
       0.9889251 , 0.9919094 , 1.0053576 , 1.0230665 , 1.0010077 ,
       0.9985998 , 1.0040393 , 0.996346  , 0.9926001 , 1.003616  ,
       0.99066305, 1.0048054 , 1.0198894 , 0.99845797, 1.0147078 ,
       0.9966502 , 1.0055369 , 0.98714536, 1.0061367 , 1.0066366 ,
       1.0019778 , 0.99724424, 0.9870064 , 1.0036137 , 1.0187888 ,
       0.98978865, 1.0095309 , 1.0039039 , 1.0012574 , 0.99913645,
       0.99354565, 1.0016125 , 1.0095544 , 1.0203757 , 0.9918705 ,
       0.9885559 , 0.98553807, 0.99114406, 1.0143609 , 1.0108327 ,
       0.9901377 , 1.011212  , 1.0016191 , 0.98994994, 0.9881548 ,
       1.0337249 , 0.999206  , 0.9976846 , 0.9960797 , 0.9996552 ,
       1.0096399 , 1.0262088 , 1.0125252 , 0.9907371 , 0.99726254,
       1.0118554 , 0.9994408 , 0.9938602 , 0.997259  , 0.9986886 ,
       1.0053344 , 1.0021335 , 1.0197784 , 0.99092436, 0.9966688 ,
       1.0055932 , 1.0006407 , 0.9920904 , 1.0084696 , 0.9968275 ,
       0.9928058 , 0.9917994 , 0.9919377 , 1.0077899 , 1.0082453 ,
       1.0154866 , 0.9966918 , 0.9971919 , 1.0191516 , 1.0101422 ,
       0.9974427 , 0.9871817 , 1.0140564 , 0.98337483, 0.9792915 ,
       1.0263739 , 1.0082959 , 0.99201787, 1.0060686 , 0.9935372 ,
       1.0086018 , 0.99199784, 1.0042685 , 0.9872614 , 1.0111371 ,
       0.99682415, 1.0151157 , 0.99930334, 1.0030427 , 1.0082737 ,
       1.0020509 , 0.9899631 , 0.99881685, 1.0016029 , 0.98834884,
       1.0190215 , 1.008307  , 1.0022782 , 1.0013608 , 1.0049412 ,
       1.0090029 , 0.9847126 , 1.0192746 , 0.9894625 , 0.9950476 ,
       1.0011188 , 0.9936222 , 1.0120479 , 1.0021366 , 1.0353309 ,
       1.006356  , 0.98618424, 1.0138565 , 0.992494  , 0.99581575,
       1.0220485 , 1.0105133 , 0.99084675, 1.0003842 , 0.99638724,
       1.0038351 , 0.97334576, 0.97886455, 1.0113897 , 1.007402  ,
       0.9869487 , 1.0164778 , 0.99758685, 1.0080434 , 1.0216316 ,
       0.9700046 , 1.0088582 , 0.9932296 , 1.007238  , 1.0024884 ,
       1.0154858 , 1.0181688 , 1.0057268 , 1.0371099 , 0.97736496,
       0.99924916, 0.995328  , 1.0234363 , 1.0198619 , 1.0037196 ,
       0.99349684, 1.0031682 , 0.9994813 , 1.0017105 , 0.99273396,
       0.98590475, 1.0008157 , 1.0059189 , 0.9891573 , 0.9911402 ,
       1.0126742 , 0.99165934, 0.99704117, 1.0199035 , 0.99906874,
       0.99928355, 1.0006192 , 0.9756557 , 0.9991112 , 0.97373545,
       1.0066938 , 0.9904316 , 1.0042669 , 1.012949  , 1.0070736 ,
       1.0027348 , 1.0079519 , 0.99478745, 1.0194222 , 1.0037525 ,
       1.0048873 , 0.99309915, 0.9794623 , 1.055244  , 1.0033253 ,
       1.0185305 , 1.0151572 , 0.99193066, 0.9903596 , 0.99864495,
       1.0033165 , 1.0228547 , 0.9970909 , 0.9997679 , 1.0099087 ,
       1.012578  , 1.0051444 , 0.98908895, 1.01474   , 1.0136367 ,
       0.99533373, 0.9887708 , 0.9816694 , 0.9986072 , 0.99364513,
       1.0181026 , 0.9934065 , 0.9882302 , 1.0028743 , 1.0202426 ,
       0.99062294, 1.0072511 , 1.0010117 , 0.9924939 , 0.9913125 ,
       0.98968107, 1.0110849 , 1.0275923 , 0.9983943 , 0.99260134,
       1.011693  , 0.9948086 , 1.003219  , 0.973053  , 1.0111516 ,
       1.011919  , 0.99657637, 0.9941998 , 0.9975404 , 1.0091214 ,
       0.99810946, 0.99555296, 1.0112851 , 1.008616  , 0.99544203,
       1.0275534 , 0.9965266 , 0.99139446, 1.0378847 , 0.9990321 ,
       1.0155804 , 1.0013381 , 1.0074728 , 1.0133698 , 1.002256  ,
       1.0080011 , 0.98267806, 1.0128543 , 0.98518825, 1.028026  ,
       1.0006757 , 0.99437565, 0.99179864, 1.0125135 , 1.0125344 ,
       0.99484587, 1.0263944 , 0.98779553, 1.0078841 , 0.9813867 ,
       1.028987  , 1.0208788 , 0.9953174 , 1.0003809 , 1.0022435 ,
       1.0115101 , 0.9997093 , 1.011348  , 0.97811204, 1.0056342 ,
       1.0057248 , 1.0106534 , 0.9790024 , 0.99936575, 1.0097475 ,
       1.0031408 , 1.0111412 , 0.99800605, 0.9983315 , 0.9826217 ,
       0.99613637, 1.0010083 , 1.0240902 , 0.9964677 , 0.9962549 ,
       0.9951734 , 1.013341  , 0.9853661 , 1.0182351 , 1.0234622 ,
       1.012188  , 0.99262995, 0.9969504 , 0.98289007, 1.023104  ,
       1.0152928 , 0.9925364 , 0.9960574 , 1.0070846 , 0.99000144,
       1.0020248 , 1.0126994 , 0.9985837 , 1.0115644 , 1.0048723 ,
       1.0073603 , 1.0021158 , 1.0019152 , 0.9954567 , 0.9966377 ,
       0.99546933, 1.0041084 , 1.0025405 , 0.9994986 , 1.0014626 ,
       0.99678534, 1.0258884 , 0.9940172 , 1.0078434 , 0.97006047,
       1.001086  , 1.0209489 , 1.042523  , 0.98531955, 1.0033655 ,
       0.99076986, 1.0170053 , 1.0066601 , 0.9905493 , 0.9985124 ,
       0.9981843 , 0.98589945, 0.9959655 , 1.0049155 , 1.0126245 ,
       0.98853606, 1.0357732 , 0.9799816 , 1.0096114 , 0.992979  ,
       1.0135026 , 1.0004569 , 1.0115469 , 0.9893114 , 1.0002534 ,
       0.9967625 , 0.9999436 , 1.0307972 , 1.0163115 , 1.0062383 ,
       0.99591076, 1.0091653 , 1.0108492 , 1.0124586 , 0.98625636,
       0.9913579 , 0.9898778 , 0.9929321 , 1.0131594 , 0.9842852 ,
       1.0121201 , 1.0143162 , 1.0029038 , 0.9974143 , 1.0131373 ,
       0.99353904, 1.0091802 , 0.99387175, 1.0059555 , 0.98525   ,
       1.0112513 , 1.0032654 , 0.99896365, 1.0003829 , 0.98696196,
       0.99912757, 0.98999053, 1.010931  , 0.9968943 , 1.0048671 ,
       1.0043331 , 0.99531734, 1.0130923 , 1.0079972 , 1.0019131 ,
       0.99576664, 0.98400366, 1.0087832 , 0.9973625 , 0.987802  ,
       0.98626256, 0.996419  , 1.0254309 , 0.99731576, 0.9998287 ,
       0.9998226 , 1.009349  , 0.9990951 , 1.0092427 , 1.0081713 ,
       1.0066501 , 1.0066937 , 0.9860021 , 0.978965  , 1.0021824 ,
       1.0089244 , 0.995156  , 1.0074489 , 1.0031935 , 0.99377114,
       0.99795556, 1.00106   , 0.99864155, 0.9952156 , 1.0110092 ,
       1.0004421 , 1.0022998 , 0.9924043 , 1.0110469 , 0.9978184 ,
       1.0013028 , 1.0114254 , 0.9787833 , 0.98731285, 0.99999636,
       1.0154161 , 1.0150727 , 0.99896795, 1.0176808 , 1.0088264 ,
       0.99108076, 1.0137323 , 1.010867  , 0.98793995, 0.9906115 ,
       0.9986241 , 1.0035394 , 0.9892226 ], dtype=float32), array([ 1.16391247e-03,  1.06681604e-02, -1.09812375e-02, -5.33214444e-03,
        1.17680123e-02, -1.84291508e-02, -2.76114442e-03, -3.46623175e-02,
        2.09790710e-02, -5.95949963e-03,  1.48436660e-02, -3.03147081e-03,
        2.10838020e-03, -4.26890189e-03,  7.38350581e-03,  2.07745917e-02,
       -1.50817120e-02,  5.03205974e-03, -1.83256976e-02, -4.47352510e-03,
       -1.62491594e-02, -1.57391708e-02, -9.59106162e-03, -1.71796270e-02,
       -6.10965490e-03,  2.20666863e-02,  6.74104644e-03,  1.43917492e-02,
        5.20658121e-03, -4.75622667e-03,  1.90328388e-03, -1.83850415e-02,
        6.82943733e-03, -1.96802821e-02,  5.15215239e-03, -5.91011625e-03,
       -9.42885783e-03, -8.45428091e-03, -1.24135353e-02, -1.14935162e-02,
       -1.46468752e-03,  1.56578571e-02,  4.98161232e-03, -1.76206715e-02,
        2.04945775e-03, -4.39318828e-02, -7.56718172e-03, -6.14055991e-03,
       -4.56198379e-02,  4.34993627e-03, -1.21532008e-02,  2.06198711e-02,
       -2.12843381e-02,  1.54289948e-02, -5.02188457e-03,  3.35891149e-03,
       -4.21934482e-03, -1.89664476e-02, -1.64692551e-02, -1.63436728e-03,
        1.20900543e-02, -2.11454788e-03, -1.12291966e-02, -1.66957006e-02,
       -2.05471925e-03, -3.17289005e-03, -7.46957446e-03,  1.54275857e-02,
        1.24442456e-02, -9.05697700e-03,  1.20565365e-03, -5.49730519e-03,
       -7.46631296e-03, -3.52115044e-03,  1.42562343e-02, -2.03791801e-02,
        8.52341857e-03,  4.86014225e-03,  3.14305420e-03, -2.38915626e-02,
       -1.96325481e-02,  1.93754071e-03, -2.02342984e-03, -5.21529885e-03,
        9.71471891e-03,  4.77353670e-03, -6.57870062e-03,  4.02302574e-03,
        1.43154413e-02,  6.03568181e-03, -1.44773833e-02, -2.08129678e-02,
       -1.09476028e-02, -9.53296758e-03, -9.42535419e-03, -3.38539691e-03,
        7.67086865e-03, -1.07571417e-02, -7.50103427e-05,  2.04085428e-02,
        7.94527587e-03,  4.79233451e-03,  4.40770248e-03, -1.18213007e-02,
       -8.65940563e-03, -1.45596359e-02, -2.20963117e-02, -2.13335063e-02,
       -5.77334920e-03, -2.53647119e-02,  1.98670756e-03, -2.62456108e-02,
        5.30936290e-03,  3.98757693e-04,  6.46995008e-03,  5.93846850e-03,
        8.34319368e-03, -1.62789896e-02,  1.20653212e-03,  3.37995298e-04,
       -7.44802551e-03, -2.23756824e-02, -1.01078451e-02,  2.73912735e-02,
       -1.52150076e-02, -1.32748988e-02,  5.75995771e-03,  2.70527899e-02,
        3.44679644e-03, -7.02719809e-03, -1.42768854e-02,  1.94350388e-02,
        3.00786528e-03,  6.36470853e-04, -9.17878002e-03, -1.97675731e-02,
        3.81061286e-02, -2.65123378e-02, -8.22822843e-03, -2.13333741e-02,
        2.30173543e-02,  2.62733083e-03,  8.83753691e-03, -9.51257162e-03,
       -1.29672298e-02,  1.46158151e-02,  1.99771975e-03, -1.95358172e-02,
       -2.56981812e-02, -8.23857076e-03, -1.26571627e-02, -1.53418565e-02,
        2.49018543e-03, -1.83366109e-02,  2.13933107e-03,  1.56032126e-02,
        4.39854898e-03, -4.91410028e-03, -1.14159845e-02,  7.77359179e-04,
       -2.17686477e-03, -1.53331207e-02, -1.70873292e-02, -1.67691316e-02,
       -5.19358611e-04, -3.50772589e-02,  1.02612078e-02,  3.22037085e-05,
        1.67866182e-02, -1.87963732e-02,  2.47769356e-02, -2.32935138e-02,
        1.25090554e-02, -4.01938660e-03, -2.06240807e-02, -1.28437346e-02,
       -2.75508105e-03,  8.96053668e-03, -4.63855406e-03, -4.28685872e-03,
        8.82268511e-03, -1.42221395e-02, -6.25492912e-03, -1.62477978e-02,
       -1.02721555e-02, -7.27138203e-03,  3.75008117e-03,  3.16529651e-03,
        2.58098077e-03, -7.30789383e-04, -7.10203033e-03,  1.59386229e-02,
       -1.38681969e-02, -9.73910373e-03,  1.11891944e-02,  2.05890671e-03,
        2.83883372e-03, -8.64043739e-03, -3.64357186e-03, -6.40656846e-03,
        1.23193488e-02,  2.19848286e-03,  2.31689010e-02, -3.14432010e-02,
        9.84400744e-04, -9.01197549e-03,  1.76478573e-03, -2.13883277e-02,
        4.47764900e-03,  9.28295963e-03, -2.02248003e-02, -7.45942397e-03,
       -9.02098697e-03, -1.03931893e-02, -2.32133288e-02, -1.19168609e-02,
        4.86541353e-03,  3.05615552e-03,  3.66904680e-03, -1.20784696e-02,
       -1.03211021e-02,  1.84176750e-02, -2.29404145e-03, -6.07299153e-03,
        3.39079574e-02,  1.70433410e-02,  1.89836801e-03,  4.86843996e-02,
       -1.97791271e-02, -8.41594394e-03,  1.56486277e-02, -3.26676667e-03,
       -9.72985290e-03, -1.22583462e-02, -2.56235059e-02, -7.81884231e-03,
       -1.56795979e-02, -8.74613412e-03, -2.51187962e-02,  2.22983188e-03,
       -7.01825228e-03,  1.74022019e-02,  7.07490183e-03, -1.38199162e-02,
       -7.19495956e-03, -2.37885732e-02,  6.69326633e-03,  1.73505349e-03,
       -1.03058685e-02,  3.40407365e-04, -9.56913922e-03, -6.73883595e-03,
       -1.27791436e-02,  5.05673420e-03, -8.58661532e-03, -1.44758150e-02,
        3.66820581e-03,  3.06054205e-03,  2.27175886e-03, -3.84932687e-03,
       -1.25701744e-02, -9.38724447e-03, -1.32197291e-02, -2.52061188e-02,
        1.00677181e-02,  1.73646975e-02,  6.09601056e-03,  6.59711892e-03,
       -7.29485415e-03,  1.73236325e-03,  1.16033601e-02, -1.71335193e-03,
       -7.54293893e-03, -8.26290995e-03, -2.68431529e-02, -1.41076138e-02,
       -1.27045726e-02, -4.07798514e-02,  7.01620569e-03, -4.27934565e-02,
        1.75198028e-03, -3.86261335e-03,  4.91320482e-03, -1.48598151e-02,
       -3.61569971e-02, -4.25649062e-03, -1.49454763e-02, -5.41690271e-03,
       -6.42671669e-03, -1.25188464e-02, -1.70466374e-03,  2.00738627e-02,
        5.95245324e-03, -1.80233195e-02, -1.08339544e-02, -9.24735703e-03,
       -2.78980378e-03,  1.85872912e-02, -1.16482815e-02, -1.70592195e-03,
       -2.15693489e-02, -7.47541524e-03, -1.64222065e-02, -3.08410488e-02,
        7.94968009e-03, -2.13948358e-02, -2.81802434e-02, -1.78008026e-03,
        7.68512348e-03, -7.01991448e-05,  8.10247567e-03,  3.04674054e-03,
        5.59691852e-03,  2.08351505e-03,  1.43744587e-03, -1.27954809e-02,
       -1.63397435e-02, -3.44797131e-03,  2.05681473e-02, -1.62798129e-02,
       -6.11945568e-03,  1.23814093e-02, -2.94365212e-02, -1.04478393e-02,
        2.13414766e-02, -2.59309541e-04,  9.42126475e-03, -1.81058072e-03,
       -8.66505038e-03, -1.77624375e-02, -1.24656446e-02, -2.08952464e-03,
       -1.89836603e-03,  1.16730882e-02, -2.90137541e-05, -5.37825143e-03,
        5.01684519e-03, -2.64166426e-02,  4.05684300e-03, -9.71032120e-03,
        2.55429111e-02, -1.97515935e-02,  3.83230252e-03, -1.09164929e-02,
       -1.60077482e-03,  1.19476309e-02,  7.51913013e-03, -1.28843263e-02,
        1.84393227e-02, -2.23933696e-03, -1.63129019e-03,  3.56397964e-02,
        1.49005465e-02,  1.86765566e-02, -1.44163612e-02, -1.51102599e-02,
       -1.16304914e-03, -8.26231029e-04, -8.96079931e-03,  6.41272822e-03,
       -5.06489212e-03, -4.95203491e-03,  1.60660949e-02, -9.32504237e-03,
        1.76173002e-02,  1.65383762e-03, -1.06862215e-02, -1.05440253e-02,
        3.32124857e-03,  3.37542570e-03, -2.48810276e-02, -9.56436433e-03,
       -9.42797586e-03, -2.11245157e-02, -6.33690320e-03,  5.14428597e-03,
       -2.26254785e-03, -2.77201384e-02,  9.09702759e-03, -1.26653370e-02,
       -3.15021537e-02, -1.48075484e-02,  1.08852349e-02, -6.50869822e-03,
       -3.01133725e-03, -3.08771636e-02, -9.40571539e-03, -1.33640813e-02,
        6.00874471e-03, -1.91054530e-02, -1.89645011e-02,  5.29834142e-05,
       -1.15817599e-02, -1.23759490e-02, -8.29396187e-04, -2.64444984e-02,
        1.87496538e-03, -7.00444123e-03,  1.23228412e-03,  7.20766885e-03,
       -1.34536745e-02, -2.62503023e-03,  9.81829502e-03, -2.12418684e-03,
       -8.94738827e-03, -1.27180871e-02, -1.78468254e-04, -2.16254238e-02,
       -8.69662128e-03, -5.34093985e-03, -1.10094175e-02, -1.54979536e-02,
        1.43256569e-02, -3.38410512e-02,  4.49075596e-03, -2.07325537e-02,
        7.63540948e-03, -1.85391251e-02,  6.71990868e-03, -3.46266329e-02,
        1.17089576e-03, -2.20011622e-02, -1.21062053e-02, -5.18825045e-03,
        6.55492488e-03, -5.62540349e-03, -4.44116965e-02, -7.29587395e-03,
        3.45424237e-03,  1.22549413e-02, -2.12085694e-02,  1.84655469e-02,
        3.16967635e-05, -4.47144844e-02, -1.23617677e-02, -1.76464841e-02,
        1.52003178e-02,  2.07910780e-04, -1.80320311e-02, -1.85233948e-03,
       -2.20808424e-02,  3.24216159e-03, -8.78258795e-03,  5.61861880e-03,
       -1.16731953e-02,  1.02756256e-02, -1.00034354e-02, -3.69099993e-03,
        1.74725484e-02, -3.65457824e-03, -1.76448133e-02, -9.44996625e-03,
       -2.28174336e-04, -3.41070965e-02,  9.33813304e-03, -5.78381633e-03,
       -5.61857130e-03,  1.18589159e-02,  5.53925149e-03, -4.98571433e-03,
       -3.20593663e-03,  5.16557181e-03,  2.16859840e-02, -2.01504771e-03,
       -6.42816862e-03, -1.47626186e-02, -1.49929675e-03, -1.88948996e-02,
        2.14796071e-03, -5.08999173e-03, -6.60118368e-03, -1.97745878e-02,
       -1.35267843e-02, -2.49926690e-02,  2.54838332e-03, -1.02526583e-02,
       -1.39911221e-02, -2.21232120e-02, -6.17785659e-03,  6.85926573e-03,
       -1.17389197e-02, -2.44546328e-02, -2.63276882e-03, -6.50429120e-03,
        2.20446028e-02, -4.07768898e-02, -9.12390277e-03, -5.31886704e-03,
        1.05546378e-02, -5.46503812e-03, -2.26452784e-03, -1.14558255e-02,
       -1.36331059e-02, -2.29816269e-02, -3.07007320e-03,  3.75826322e-02,
       -9.09419265e-03, -2.05686409e-03,  1.22731319e-02, -1.93692110e-02,
       -1.42238708e-02,  4.38419264e-03,  2.20573507e-02, -3.85068823e-03,
       -8.32630042e-03, -1.83256287e-02, -1.23436749e-02, -3.71342350e-04,
       -6.86979620e-03,  1.08687335e-03,  1.36704780e-02, -1.14453388e-02,
        1.76513083e-02, -1.16793150e-02,  2.83780489e-02, -5.67886000e-03,
       -2.00850656e-03, -4.94237151e-03, -1.66885145e-02, -2.17561442e-02,
       -1.08331591e-02, -1.51922917e-02, -3.33465496e-03,  1.25900321e-02,
        2.91112834e-03, -1.17289163e-02, -1.58574190e-02,  1.11096411e-03,
       -2.79756859e-02, -1.01746041e-02, -1.37392739e-02,  9.05762799e-03,
       -2.12281104e-02,  1.77625865e-02,  4.51070536e-03,  1.95100496e-03,
       -2.10662875e-02, -1.43357320e-02, -1.90912152e-03, -1.62825957e-02,
       -8.54034908e-03, -1.76877379e-02, -1.78197436e-02, -6.00936916e-03,
       -1.48981782e-02,  1.59513764e-02, -1.00498954e-02,  7.12781912e-03,
       -1.67021696e-02,  8.18292238e-03,  8.95612966e-03, -1.77569576e-02,
       -9.97374300e-03,  7.03397254e-03,  6.72960654e-03, -8.05408414e-03,
       -4.18283716e-02, -2.51509668e-03,  1.16065098e-02,  8.41646083e-03,
        8.06392543e-03,  8.43840744e-03,  1.39695518e-02,  1.33875534e-02,
        2.79837567e-02, -2.91106217e-02,  7.88009726e-03, -2.02357583e-02,
        6.49435818e-03, -4.43830155e-03, -2.00915914e-02, -7.39574013e-03,
       -3.74090336e-02, -1.60330394e-03, -1.38875516e-02, -1.52739312e-03,
       -2.37823259e-02,  8.14657751e-03, -1.81153901e-02, -2.87358575e-02,
       -6.76152203e-03,  1.63400534e-03,  8.81012157e-03, -3.97364656e-03,
        2.21341830e-02, -9.66002699e-03, -1.41840940e-02, -5.02943993e-03,
       -1.59432995e-03,  1.91885959e-02,  1.60272121e-02, -2.25046021e-03,
        1.15986634e-02, -7.48889055e-04,  2.09056921e-02, -1.03372242e-03,
        2.70400615e-03, -1.28675923e-02, -9.72328987e-03,  1.50214359e-02,
       -1.17200501e-02, -1.09886786e-03,  1.61767442e-04, -2.93547264e-03,
       -7.36115081e-03,  1.42320655e-02,  8.38960987e-03, -8.33734404e-04,
       -4.71197488e-03, -1.81017034e-02, -4.50563757e-03,  8.73292517e-03,
       -2.96678562e-02, -1.17777344e-02, -1.24233300e-02, -1.05340965e-02,
       -2.39543132e-02, -2.20775306e-02,  5.55992685e-03, -1.54787255e-02,
       -1.01080760e-02, -1.27241919e-02, -3.56973009e-03,  1.37958108e-02,
        4.80926409e-03, -1.55784711e-02, -1.85648501e-02, -1.34484039e-03,
       -6.99742977e-03, -4.56202077e-03,  8.00766938e-05,  1.09782545e-02,
        4.91978275e-03, -1.54479826e-02, -1.24364942e-02,  3.34307775e-02,
       -1.47503754e-02,  3.03618368e-02, -2.40969658e-02, -2.04416644e-03,
       -7.29645975e-03, -5.83951967e-03,  2.59427913e-02, -5.21215983e-03,
        5.33403223e-03, -8.33892636e-03, -4.97217430e-03,  1.79859716e-03,
        1.95609475e-03, -1.57573838e-02, -6.00551860e-03, -4.85841511e-03,
       -4.89917211e-03, -2.16481765e-03,  7.71978078e-03, -1.10191070e-02,
       -9.25557222e-03,  6.13814779e-03, -1.03255268e-02, -2.14647129e-02,
        8.01895629e-04,  2.26386040e-02, -2.28026398e-02, -5.24180569e-03,
       -1.25642484e-02,  7.67430849e-03, -1.14000710e-02, -7.28369411e-03,
        2.05181297e-02, -2.07294188e-02, -2.05605030e-02,  6.08023955e-03,
        3.44484765e-03,  2.33554263e-02, -1.12941405e-02, -1.20842364e-02,
       -8.11358634e-03, -3.59062888e-02, -1.51080815e-02, -4.83902358e-03,
        5.58389956e-03,  5.91652794e-03, -1.86722726e-02, -3.32538271e-03,
       -1.27930520e-02,  2.00451147e-02, -3.11029935e-03,  8.97486112e-04,
        9.72319976e-04, -3.96963358e-02, -1.30491634e-03,  4.30691615e-03,
       -4.86710249e-03,  8.76142364e-03,  4.85565513e-04,  7.53022963e-04,
        1.36744545e-03, -1.16137378e-02, -1.12824496e-02,  4.42782836e-03,
       -1.26774667e-03, -1.04644075e-02, -5.50448103e-03, -5.28378470e-04,
        6.84463978e-03,  6.58319099e-03, -1.16606569e-02, -8.67512543e-03,
        7.07900804e-03,  1.37514090e-02,  9.51533765e-03, -8.32245569e-04,
        5.86690661e-03, -4.26488556e-03,  2.43575182e-02,  3.11381146e-02,
       -2.19168048e-03, -1.31654609e-02, -9.48757678e-03, -4.42650542e-03,
       -5.41519606e-03, -2.71934327e-02, -2.06399187e-02, -1.35547612e-02,
       -2.08789352e-02, -3.14374864e-02,  1.80910267e-02, -2.07256898e-02],
      dtype=float32), array([ 1.22413039e-02, -4.84564230e-02,  1.01871975e-02,  4.13600244e-02,
       -3.92589979e-02,  5.05071394e-02, -1.00989004e-04,  6.85032224e-03,
       -5.52812964e-02, -1.92310642e-02, -5.23515232e-02,  3.86500731e-02,
       -9.62070655e-03,  7.15998784e-02,  4.64519486e-03, -1.60254147e-02,
        3.68008502e-02, -2.08814610e-02,  2.30436921e-02,  5.28765656e-02,
        1.86444111e-02,  2.29918025e-02,  1.83623005e-02,  2.48922443e-04,
       -7.27599999e-03, -8.28748289e-03,  3.74303386e-03, -4.62845825e-02,
       -2.81864684e-02, -1.55253438e-02,  2.61833109e-02,  5.28761074e-02,
       -2.88461149e-02,  8.03621113e-03, -2.89734844e-02,  1.60603151e-02,
        5.49314208e-02, -1.21193975e-02, -3.08328308e-02, -1.80086941e-02,
        1.30861867e-02, -3.84277329e-02, -4.08847257e-02,  5.94324619e-02,
       -2.19539143e-02,  1.39632905e-02, -2.05032565e-02,  3.94236706e-02,
        6.62815496e-02, -2.22050752e-02, -1.93411636e-03, -2.72591915e-02,
        2.01336406e-02, -3.39981951e-02,  3.73814851e-02, -1.64725855e-02,
       -3.36823091e-02,  4.88476120e-02,  3.07544973e-02,  3.13741006e-02,
       -4.32923511e-02,  3.14631090e-02,  5.03054559e-02, -4.15323488e-02,
        3.93634737e-02,  3.84036489e-02,  1.29666403e-02, -2.79406384e-02,
       -3.76212001e-02, -3.90987322e-02, -6.52551949e-02,  9.82984155e-03,
       -1.40837338e-02, -1.95861124e-02, -5.78711648e-03,  2.47600004e-02,
        1.64807718e-02, -2.92647015e-02, -1.02943489e-02, -2.82650944e-02,
        4.92402613e-02, -2.77714920e-04,  3.13993059e-02, -3.18319686e-02,
       -3.48798418e-03, -2.80029196e-02, -4.38731426e-04,  2.47373600e-02,
       -1.98374651e-02,  2.04480570e-02,  2.46578287e-02,  3.32859941e-02,
        5.97802661e-02, -8.41855630e-03, -9.26656369e-03, -2.59188674e-02,
       -3.97034138e-02,  3.25396843e-02,  4.46400866e-02, -6.24965914e-02,
       -3.30905728e-02, -3.15743079e-03,  1.65513717e-02,  5.12103401e-02,
        1.53749259e-02,  3.54213268e-02,  6.30316213e-02, -7.62412976e-03,
        1.63153801e-02,  5.26679270e-02, -5.66791482e-02,  5.22712655e-02,
       -1.94831900e-02, -1.95397474e-02,  4.02352437e-02,  2.78605018e-02,
        3.99123179e-03,  4.96630780e-02, -1.24977194e-02, -6.55231299e-03,
        1.01696486e-02,  1.43532576e-02,  4.09651957e-02, -2.40711235e-02,
       -2.40211766e-02,  1.32474573e-02, -4.61914018e-02, -3.21962275e-02,
        1.70316901e-02,  4.12086491e-03,  5.01865298e-02, -2.24633273e-02,
       -2.19675470e-02, -2.03260817e-02, -1.05360067e-02,  3.79069615e-03,
       -2.93581840e-02,  3.68911512e-02, -2.03704536e-02,  1.15451375e-02,
        4.08387519e-02,  1.41278817e-03, -4.22964990e-02,  1.75543223e-02,
        5.09363785e-02,  1.41250519e-02, -4.36529256e-02,  2.02418938e-02,
        4.71320003e-02, -2.95983665e-02,  3.36309373e-02,  2.74034608e-02,
        4.34146114e-02,  5.51758185e-02, -4.46124654e-03, -1.95441358e-02,
       -5.36959507e-02,  3.24479640e-02,  6.13450333e-02, -1.67218037e-02,
        4.25453112e-02,  2.44841594e-02,  7.42131472e-03,  1.12423971e-02,
       -4.43645231e-02,  5.84155843e-02,  1.08071249e-02,  3.63999791e-02,
       -1.54174874e-02, -2.91695516e-03, -6.90823421e-03,  3.64400186e-02,
        9.96943843e-03,  4.44712229e-02,  3.77941541e-02, -1.91387087e-02,
       -5.75111294e-03, -2.26176251e-02, -5.48507273e-02, -1.87613163e-02,
        2.87476853e-02,  3.19048800e-02, -2.20742412e-02,  5.82300685e-02,
       -3.44959944e-02,  4.41920310e-02,  9.65967681e-03, -2.14144476e-02,
       -2.81357148e-04,  1.96456499e-02,  4.48157080e-02, -5.17981313e-03,
        2.13101692e-02,  2.61394903e-02, -6.04841672e-02, -1.36502944e-02,
        5.78264892e-03,  3.65763940e-02,  4.68709171e-02,  2.45246496e-02,
        5.00627309e-02,  1.84502651e-03, -2.99725812e-02, -2.52389833e-02,
        2.06708908e-02,  3.19621228e-02, -2.88842302e-02,  3.09385564e-02,
        6.78929733e-03, -1.23123601e-02,  3.63832824e-02,  4.15284447e-02,
        6.93410635e-03,  7.58079067e-03, -2.18135472e-02,  2.54629739e-02,
        4.61410172e-02, -1.87600888e-02, -2.49193851e-02,  4.71742302e-02,
        2.19494831e-02, -2.95161176e-02, -2.38504168e-02, -3.45814526e-02,
       -3.77693363e-02,  2.17880346e-02,  2.30080131e-02, -7.30296820e-02,
        4.33299690e-02,  2.75935959e-02, -4.79575507e-02,  2.63284799e-02,
        4.54118997e-02,  4.18032221e-02,  4.96290401e-02, -3.54650915e-02,
       -3.40045318e-02,  2.70435903e-02,  6.68027773e-02,  2.46928469e-03,
        3.21088135e-02, -4.42594253e-02, -1.00602750e-02,  3.61760408e-02,
       -9.25269816e-03,  6.39777035e-02,  1.82528887e-02,  1.57297067e-02,
        5.03931269e-02,  1.32081062e-02,  3.59727703e-02, -2.77135987e-02,
       -2.33574044e-02,  5.04738651e-03,  6.49480820e-02,  2.60603987e-02,
        3.13081257e-02, -5.13936207e-02,  1.66564640e-02,  2.78934613e-02,
        3.68406326e-02, -1.90919473e-05, -2.30187029e-02,  4.41346765e-02,
       -3.15012261e-02, -5.57311326e-02, -3.01982854e-02,  1.30572142e-02,
        2.37517729e-02, -2.50066947e-02, -4.70447838e-02,  3.62700373e-02,
       -1.81684531e-02, -3.91803915e-04,  6.64598495e-02,  3.49469706e-02,
       -1.58878751e-02,  5.73222488e-02,  2.32226104e-02,  5.22800162e-02,
        2.19439785e-03, -1.63327958e-02, -3.41762304e-02, -1.47080999e-02,
        6.86744452e-02, -1.30032226e-02, -5.35154017e-03, -1.68534890e-02,
       -2.42390647e-03,  2.78381445e-02,  3.65519635e-02,  1.37484409e-02,
       -2.78474130e-02,  3.18500288e-02,  3.00118998e-02,  4.28727120e-02,
        4.16457728e-02, -4.50597368e-02,  3.95664051e-02, -7.95597676e-03,
        5.30625135e-02,  2.35231058e-03,  1.12121189e-02,  5.98495267e-02,
        3.31055485e-02,  3.07975858e-02,  4.69646044e-02, -1.19663049e-02,
       -2.64549274e-02, -3.19206938e-02, -4.26679775e-02, -5.41321859e-02,
       -2.53212936e-02, -6.86501488e-02, -4.33278605e-02,  3.75311002e-02,
        1.64044481e-02,  2.19935607e-02, -2.70369612e-02,  4.33486216e-02,
       -1.49487481e-02,  2.66776886e-02,  3.36190760e-02,  4.15574610e-02,
       -2.29877494e-02, -2.97881328e-02, -3.00347824e-02,  2.33712513e-02,
       -3.49074486e-03, -8.67655594e-03,  8.03757682e-02, -4.40468866e-04,
        4.83751744e-02, -3.20982672e-02,  3.12177911e-02,  4.20158580e-02,
        4.15341333e-02,  3.29976454e-02,  2.73400191e-02, -4.13768896e-04,
        1.56608894e-02,  7.00157955e-02, -1.91195402e-02,  8.69624037e-03,
       -3.35019194e-02,  6.49661794e-02,  1.13430135e-02,  1.86691824e-02,
       -1.87451039e-02,  5.09889089e-02,  2.29144748e-02, -5.42054437e-02,
       -1.96948815e-02, -2.36063898e-02,  7.98070729e-02,  4.56058644e-02,
        2.31577475e-02, -2.35982258e-02,  2.30080653e-02, -8.03202614e-02,
        9.97285126e-04, -6.65400550e-03, -2.87822783e-02,  1.78539641e-02,
       -2.89576109e-02, -2.56050862e-02,  3.90824775e-04,  5.65152988e-02,
        5.46662742e-03,  2.29682121e-02,  3.51438224e-02,  1.98433921e-02,
        2.75137406e-02,  2.37043202e-02,  4.14568856e-02, -1.73979551e-02,
        4.06871829e-03,  5.20997867e-03, -3.42460871e-02,  3.16608213e-02,
       -2.26306133e-02, -2.89935023e-02, -2.27849148e-02,  1.87160855e-03,
        2.87814755e-02,  4.39134315e-02,  3.74909975e-02,  3.55831161e-02,
       -3.94454524e-02,  3.51477228e-02,  2.11305227e-02,  1.64214484e-02,
        4.84740324e-02,  2.52719186e-02, -2.33719889e-02,  9.86355823e-03,
        4.22299504e-02,  3.29768956e-02,  3.06408815e-02, -3.52583751e-02,
       -2.15385165e-02,  5.07042967e-02, -1.26725147e-02, -2.09003836e-02,
        4.45808321e-02,  4.75084037e-02,  2.72907075e-02,  2.01747306e-02,
        4.97038998e-02,  2.17168704e-02,  7.13555142e-03,  4.86511402e-02,
       -1.85347032e-02,  4.53950055e-02, -3.92335095e-02,  4.53118868e-02,
       -3.51409614e-02,  1.98827498e-02, -1.48974666e-02,  5.34560271e-02,
       -2.32359041e-02,  6.09936155e-02,  2.40231939e-02,  4.59006652e-02,
        7.57672191e-02, -1.67689640e-02,  6.49636909e-02,  2.31686011e-02,
       -1.05305174e-02, -3.21086645e-02,  2.12750454e-02,  2.47630011e-02,
       -5.40398434e-02,  3.07340994e-02,  4.37574042e-03, -2.17266027e-02,
       -5.24351150e-02,  3.68848303e-03,  4.59752865e-02,  4.02333662e-02,
        5.52303046e-02,  2.07353216e-02,  3.23000029e-02, -6.94410701e-04,
        1.42197013e-02,  1.35179982e-02, -3.32889147e-02,  4.21722792e-02,
        1.74343418e-02, -1.76430214e-02,  3.33689637e-02, -4.72358195e-03,
       -4.60178917e-03,  2.90338658e-02, -5.26201315e-02,  4.14922237e-02,
       -1.88457198e-03, -3.35514396e-02, -2.00907886e-02, -2.21099015e-02,
        2.79576741e-02,  4.37943600e-02, -4.74295467e-02,  5.10209799e-02,
        2.48373399e-04, -2.67018601e-02, -1.64339729e-02,  5.53916506e-02,
        4.91425246e-02, -1.80365369e-02,  3.32631990e-02, -3.33450958e-02,
        1.36831393e-02,  7.14124516e-02, -9.02233180e-03,  5.33993617e-02,
        3.66592817e-02,  7.39542767e-03,  2.46636923e-02, -5.17980047e-02,
       -1.56297488e-03,  7.73181617e-02, -1.98952332e-02, -2.31529940e-02,
       -2.39138026e-02,  3.49038430e-02,  3.23062129e-02,  4.15783515e-03,
       -3.69534232e-02,  5.03785834e-02, -2.65201032e-02,  2.11864468e-02,
        3.82232033e-02, -5.35896793e-03, -3.93395014e-02, -3.97861004e-02,
        1.93833709e-02,  7.98817538e-03,  3.54563892e-02,  4.88994420e-02,
        4.62304465e-02, -2.93868780e-02, -5.68394735e-02, -2.26183180e-02,
       -5.07204235e-02,  4.20149267e-02, -1.11434255e-02, -3.39000896e-02,
       -2.47793309e-02,  4.03729528e-02, -3.33105363e-02,  3.62776034e-02,
       -1.29863545e-02, -7.26098660e-03, -5.47600500e-02,  3.96640087e-03,
        3.44755985e-02, -4.78445031e-02,  3.12873833e-02,  3.28597985e-02,
       -2.44330596e-02,  7.90816775e-05,  5.47073074e-02,  3.50688118e-03,
        4.25015613e-02,  1.04861856e-02,  5.81426993e-02,  3.46815283e-03,
        1.94075983e-02, -6.35116221e-03,  2.37139352e-02, -2.11268496e-02,
        6.46343604e-02, -1.62116326e-02,  3.58852670e-02, -4.84964103e-02,
       -9.28606559e-03,  4.56305966e-02, -4.32465523e-02,  8.35379865e-03,
        3.06612458e-02,  4.36902754e-02, -5.53400703e-02,  6.94475137e-03,
       -4.09599543e-02, -5.72331995e-02,  3.64803039e-02,  9.98585857e-03,
        4.80290055e-02, -1.79075338e-02, -5.34465127e-02,  5.88619001e-02,
        1.88250765e-02, -4.26942967e-02, -2.44184746e-03,  6.00092448e-02,
        2.11396422e-02,  4.73835729e-02,  3.06045543e-02,  7.60486722e-03,
        1.90714898e-03, -4.80194055e-02,  2.55337320e-02, -5.14770299e-02,
       -5.59371561e-02,  4.63188067e-02, -4.24485020e-02, -1.85773652e-02,
       -4.49982435e-02,  1.30774155e-02, -1.37765417e-02,  3.44054513e-02,
        5.62109500e-02,  4.56546694e-02,  4.66135927e-02, -1.90031342e-02,
        4.62135300e-02,  9.44762491e-03,  4.57343347e-02,  2.56223548e-02,
        4.12470847e-02, -3.51499468e-02, -2.39649396e-02, -8.96367524e-03,
       -4.12999839e-02,  4.01515104e-02, -4.69251834e-02, -2.68487185e-02,
       -1.30376341e-02, -4.42451201e-02, -4.05054539e-02, -3.45576406e-02,
       -4.38642018e-02,  5.39848842e-02, -4.35598083e-02, -1.50690172e-02,
        4.15924424e-03, -5.45319468e-02, -5.43850325e-02,  1.37402108e-02,
        2.03987770e-02, -4.67690499e-03,  2.10152995e-02,  2.03183219e-02,
        2.80296281e-02,  2.54750028e-02,  3.39320898e-02, -1.64112411e-02,
        4.06297445e-02, -2.59730741e-02, -5.84054850e-02, -2.14891005e-02,
        4.79961932e-02, -2.02278718e-02,  4.11979631e-02, -1.13595845e-02,
        2.90552583e-02, -1.05639240e-02, -2.91499570e-02,  3.06165833e-02,
       -2.57861484e-02,  2.80439612e-02,  1.84503309e-02, -3.22472118e-02,
       -1.70831918e-05,  3.15528177e-02,  4.91700768e-02, -1.56264044e-02,
        4.36295867e-02,  2.18434185e-02, -4.09840047e-02,  9.44086991e-04,
        5.18564768e-02, -4.10848334e-02, -2.70066392e-02, -1.87690966e-02,
        4.91717681e-02, -4.07874919e-02,  3.86990532e-02, -3.80233191e-02,
       -2.60792356e-02, -2.04369053e-02, -4.85997461e-02,  1.33029213e-02,
       -8.02796427e-03, -3.82917002e-02,  8.30625743e-03,  2.50451872e-03,
       -1.09948376e-02,  4.25444767e-02, -2.22246605e-03,  2.59024836e-02,
       -2.22824030e-02,  3.99398105e-03, -2.67567299e-02,  2.15848573e-02,
       -1.38302678e-02,  2.25358289e-02,  2.88635325e-02,  1.95663683e-02,
        4.34932560e-02, -5.47244400e-02,  9.54360794e-03, -2.91340295e-02,
       -1.22706061e-02,  7.07876077e-03, -2.28606258e-02,  1.11216884e-02,
       -4.10145670e-02,  1.91081825e-04, -1.91752594e-02,  4.84614670e-02,
       -5.38287982e-02, -2.67137010e-02, -1.77223925e-02,  2.10406501e-02,
        3.72223812e-03,  5.57862334e-02,  2.44426187e-02, -1.38610145e-02,
        3.24355923e-02, -1.43354926e-02, -3.72256301e-02, -1.24673955e-02,
        2.78063212e-02, -3.43886577e-02, -2.09878926e-04, -1.44131212e-02,
        3.76713206e-03,  5.58125153e-02,  5.44761047e-02,  1.83955655e-02,
       -2.26917472e-02, -4.28063720e-02,  2.72566900e-02, -1.34959593e-02,
        3.00290659e-02,  3.61547805e-02,  4.86016087e-02,  3.94022465e-02,
        1.45194195e-02,  4.05887030e-02,  2.24681124e-02,  1.71802379e-02,
       -5.04124947e-02, -5.63901775e-02,  4.24163043e-02, -2.95281820e-02,
       -2.88948063e-02,  3.37908417e-03, -1.23983482e-02, -7.76004745e-03,
       -3.30773648e-03,  1.99127328e-02, -4.07133251e-02, -4.11043167e-02,
        3.79458778e-02,  6.70302473e-03,  4.81613278e-02, -2.61024013e-02,
       -2.54348163e-02,  6.11733459e-02,  7.86897391e-02,  2.80650239e-02,
       -9.80989821e-03,  3.94243188e-02, -2.61931680e-02,  1.33450022e-02],
      dtype=float32), array([0.09138738, 0.09929401, 0.08360751, 0.08913325, 0.1002204 ,
       0.09430119, 0.08856364, 0.09057169, 0.10500538, 0.09469437,
       0.10154194, 0.1115135 , 0.09233796, 0.14410008, 0.08607427,
       0.0893527 , 0.09215654, 0.08625204, 0.10316119, 0.11108921,
       0.09181761, 0.095711  , 0.10798097, 0.09181968, 0.084152  ,
       0.08650728, 0.08730625, 0.10221607, 0.09922012, 0.0883406 ,
       0.08463974, 0.10286796, 0.10447399, 0.086488  , 0.10109917,
       0.10092459, 0.11818048, 0.09293306, 0.09195774, 0.08744211,
       0.08654451, 0.09762654, 0.09314536, 0.1141718 , 0.10127618,
       0.10864724, 0.09291482, 0.09514663, 0.13042016, 0.09603965,
       0.08486099, 0.09711956, 0.0942358 , 0.11085331, 0.10762863,
       0.09386142, 0.09873463, 0.12383173, 0.1027124 , 0.10146597,
       0.09138497, 0.0908636 , 0.11979108, 0.10169608, 0.08872172,
       0.09878377, 0.09106245, 0.09907296, 0.09397817, 0.10045534,
       0.10203519, 0.08341721, 0.08410373, 0.0878282 , 0.08636841,
       0.11265594, 0.08709741, 0.09255096, 0.08416438, 0.09001817,
       0.10101849, 0.08904596, 0.09825869, 0.10288759, 0.08660637,
       0.09691495, 0.08411114, 0.09534562, 0.09681769, 0.08965682,
       0.08672346, 0.09563786, 0.10643707, 0.08931535, 0.09834309,
       0.08712346, 0.0888203 , 0.09520028, 0.09850376, 0.10071   ,
       0.09732921, 0.08591515, 0.09095713, 0.11864245, 0.09570643,
       0.09988645, 0.1130252 , 0.09388914, 0.0895181 , 0.10635161,
       0.10268388, 0.12210327, 0.08730928, 0.08480398, 0.11602707,
       0.08693951, 0.0922383 , 0.12932868, 0.09404388, 0.08700293,
       0.08772683, 0.09183747, 0.08630433, 0.09963675, 0.09346369,
       0.08780052, 0.09272468, 0.09853478, 0.09031803, 0.09270898,
       0.10956935, 0.09426271, 0.0893197 , 0.08838751, 0.08858684,
       0.0923311 , 0.09471613, 0.10894052, 0.09097793, 0.09255058,
       0.11054204, 0.08493943, 0.10853437, 0.08966795, 0.1193532 ,
       0.08861854, 0.08542837, 0.09482776, 0.11989541, 0.09447531,
       0.08861751, 0.09124846, 0.09176234, 0.12340869, 0.08285447,
       0.08863517, 0.1016226 , 0.10286321, 0.11675965, 0.08917136,
       0.10838173, 0.09700714, 0.09422792, 0.09148872, 0.10232966,
       0.13809083, 0.08931678, 0.10605145, 0.08578678, 0.08864915,
       0.08386376, 0.09564716, 0.08649205, 0.10916188, 0.09959581,
       0.09006934, 0.08788171, 0.09982672, 0.10951194, 0.09586076,
       0.08990471, 0.09652813, 0.09683217, 0.09750515, 0.08808404,
       0.1036741 , 0.08982517, 0.09131156, 0.09415086, 0.09540148,
       0.11749877, 0.08733716, 0.08698989, 0.08656155, 0.11256171,
       0.08795252, 0.08912408, 0.08999324, 0.1047525 , 0.09838303,
       0.09329041, 0.08958311, 0.10169914, 0.11470778, 0.09730567,
       0.09159882, 0.11276115, 0.09228335, 0.09088908, 0.09207905,
       0.0999331 , 0.09760686, 0.08431383, 0.08366793, 0.09740913,
       0.08600006, 0.09508003, 0.0875145 , 0.09706987, 0.10814115,
       0.09756497, 0.09907294, 0.09064911, 0.09079135, 0.10879391,
       0.09117602, 0.08558346, 0.12437317, 0.0956203 , 0.11007301,
       0.10548618, 0.09701525, 0.09525293, 0.11448421, 0.10128976,
       0.09400847, 0.08671731, 0.09504662, 0.12007981, 0.08535182,
       0.1041491 , 0.10583971, 0.09183531, 0.08909782, 0.09465155,
       0.11767215, 0.08564022, 0.09836537, 0.10251114, 0.10764895,
       0.1030552 , 0.09296605, 0.08506852, 0.08590627, 0.1223615 ,
       0.10608415, 0.10052062, 0.1008273 , 0.08958554, 0.09252887,
       0.08947662, 0.09009771, 0.09170414, 0.12086912, 0.09568223,
       0.10413722, 0.09298511, 0.09314375, 0.096474  , 0.09375224,
       0.11025301, 0.09322106, 0.08632176, 0.08934351, 0.14771804,
       0.09334694, 0.09042022, 0.12831517, 0.0990297 , 0.11007952,
       0.08677583, 0.08524545, 0.10311341, 0.08882792, 0.1240017 ,
       0.08665867, 0.08957271, 0.09112756, 0.09084651, 0.09220444,
       0.10202452, 0.08470456, 0.08523755, 0.0944168 , 0.09567516,
       0.09602945, 0.09899276, 0.09678806, 0.09952475, 0.09349783,
       0.10546917, 0.08674569, 0.08921981, 0.12040338, 0.08938225,
       0.10154311, 0.11581929, 0.08763904, 0.09530649, 0.10255888,
       0.11056656, 0.1079668 , 0.08978461, 0.12526664, 0.09272365,
       0.10991779, 0.08904147, 0.09282171, 0.10129889, 0.09626285,
       0.08377849, 0.091334  , 0.11161909, 0.09218193, 0.09791642,
       0.09412412, 0.10643004, 0.09865508, 0.08631713, 0.09940743,
       0.15021078, 0.08630601, 0.11442738, 0.09987491, 0.09846055,
       0.10680763, 0.0982761 , 0.10285199, 0.09562605, 0.09492049,
       0.09215944, 0.12976494, 0.08655294, 0.08957537, 0.10058542,
       0.10519568, 0.09346127, 0.09008432, 0.09254245, 0.10008927,
       0.0877426 , 0.11353846, 0.09429092, 0.10002053, 0.11402924,
       0.10598016, 0.09298644, 0.08490571, 0.10323559, 0.16359991,
       0.09902468, 0.09199   , 0.09755884, 0.09056306, 0.0906399 ,
       0.09457864, 0.08841594, 0.12972386, 0.09411443, 0.09628087,
       0.11365534, 0.1023368 , 0.08793306, 0.10724777, 0.09382317,
       0.09018763, 0.09069508, 0.09482606, 0.10017306, 0.09009999,
       0.09397385, 0.09205913, 0.08965465, 0.0838068 , 0.09474611,
       0.11555199, 0.09752838, 0.09921688, 0.09007175, 0.11313336,
       0.09594611, 0.09490921, 0.10836682, 0.08604025, 0.09035379,
       0.0950124 , 0.10754728, 0.12013883, 0.09125632, 0.1038622 ,
       0.10151387, 0.0972805 , 0.0850566 , 0.08509886, 0.11571634,
       0.09271838, 0.09491124, 0.09677611, 0.10706311, 0.09517721,
       0.09680569, 0.11041592, 0.09246058, 0.10450003, 0.1026177 ,
       0.1188077 , 0.09558367, 0.09147161, 0.08756937, 0.11448796,
       0.08898987, 0.11489677, 0.09033561, 0.11067274, 0.14458351,
       0.08850292, 0.11213501, 0.08699569, 0.09205782, 0.08939601,
       0.09592954, 0.08959715, 0.10863444, 0.10698076, 0.08714209,
       0.08558427, 0.11503107, 0.09072383, 0.11444106, 0.10073395,
       0.08942547, 0.08411285, 0.10978211, 0.09648757, 0.0854321 ,
       0.08739837, 0.09181369, 0.10296006, 0.08938874, 0.09243219,
       0.10482584, 0.08291566, 0.08410662, 0.09189668, 0.11052683,
       0.10719768, 0.0896172 , 0.08992066, 0.09292901, 0.08475493,
       0.10010351, 0.10772304, 0.0930265 , 0.09717516, 0.09170698,
       0.09610286, 0.0843051 , 0.0949971 , 0.0961108 , 0.08883549,
       0.10041028, 0.09372237, 0.08804295, 0.13925813, 0.08542512,
       0.12996446, 0.09312073, 0.09691075, 0.08720171, 0.09752801,
       0.08891573, 0.13084844, 0.08671388, 0.10443001, 0.09718724,
       0.12393831, 0.09453776, 0.08504509, 0.1034777 , 0.09334461,
       0.08734652, 0.09586325, 0.09437812, 0.09065899, 0.09727731,
       0.10287975, 0.08701105, 0.09598902, 0.08664045, 0.10370076,
       0.10348694, 0.09829263, 0.10049489, 0.0905574 , 0.12165397,
       0.09603777, 0.086762  , 0.10166393, 0.0924981 , 0.11455089,
       0.08604328, 0.08773491, 0.09360904, 0.08717965, 0.1241215 ,
       0.08833546, 0.09255195, 0.11317087, 0.1049467 , 0.10246029,
       0.08859146, 0.08425408, 0.10585192, 0.08722833, 0.09778014,
       0.0995617 , 0.09922382, 0.0864203 , 0.09368564, 0.08761398,
       0.10550629, 0.09618843, 0.11634441, 0.09212567, 0.08935782,
       0.10208879, 0.08643855, 0.11529975, 0.10696169, 0.09029569,
       0.09929895, 0.10066932, 0.10577287, 0.0873284 , 0.09561656,
       0.1307607 , 0.09492909, 0.08660052, 0.10689331, 0.10017043,
       0.09860782, 0.12138526, 0.08961134, 0.1156993 , 0.08380176,
       0.10221127, 0.09569696, 0.11192632, 0.0913287 , 0.08497132,
       0.08568833, 0.10735942, 0.09697462, 0.12424847, 0.09886876,
       0.11946392, 0.10709817, 0.09529006, 0.09680291, 0.09102764,
       0.09074711, 0.09577204, 0.11536675, 0.08883138, 0.10662799,
       0.09025297, 0.11895484, 0.08668692, 0.11606461, 0.10527223,
       0.08926156, 0.09970254, 0.09176163, 0.08565813, 0.10920674,
       0.10480347, 0.11363589, 0.09158842, 0.10295282, 0.10967592,
       0.10286794, 0.08663113, 0.09963217, 0.11530026, 0.11177529,
       0.08671258, 0.08662426, 0.1157642 , 0.10599004, 0.08785474,
       0.09302775, 0.08557597, 0.0963833 , 0.08897384, 0.08688947,
       0.08937927, 0.09706011, 0.09015442, 0.09988753, 0.10074548,
       0.09890255, 0.09026984, 0.10854007, 0.09476508, 0.10259834,
       0.08606529, 0.09768339, 0.08956754, 0.0878701 , 0.10615268,
       0.10423993, 0.09863052, 0.08958158, 0.0955086 , 0.0858332 ,
       0.0973272 , 0.1179444 , 0.10175331, 0.09568916, 0.09885225,
       0.09172837, 0.08808949, 0.11097128, 0.09206735, 0.08592025,
       0.09866268, 0.10891596, 0.09827866, 0.09177505, 0.10584208,
       0.1034949 , 0.09248124, 0.10709704, 0.08474936, 0.08752039,
       0.09255249, 0.0876689 , 0.08322112, 0.09360527, 0.10036965,
       0.08556166, 0.09658173, 0.09127628, 0.08353645, 0.09846873,
       0.08637853, 0.09061047, 0.08574974, 0.09274483, 0.0938865 ,
       0.10548063, 0.09964556, 0.08946866, 0.09977333, 0.0916567 ,
       0.08538558, 0.08733431, 0.08940858, 0.09095195, 0.09434501,
       0.09379011, 0.09453494, 0.11321984, 0.08945768, 0.08562523,
       0.08768602, 0.08394927, 0.1156712 , 0.11698075, 0.08562862,
       0.09263496, 0.08803917, 0.12014318, 0.08560352, 0.09085181,
       0.09098947, 0.0853818 , 0.09144552, 0.08948569, 0.12232829,
       0.11509642, 0.0878829 , 0.09214478, 0.10850562, 0.10195081,
       0.08610654, 0.09338798, 0.09617809, 0.11652147, 0.10640088,
       0.0909427 , 0.10063276, 0.08579775, 0.08987338, 0.10837914,
       0.11877289, 0.11545854, 0.09444349, 0.09171259, 0.10473568,
       0.10057982, 0.10235931, 0.08979621, 0.09215049, 0.09434738,
       0.10911952, 0.09374778, 0.08725893, 0.09813213, 0.09264883,
       0.08914953, 0.11276497, 0.14356866, 0.09584942, 0.08637101,
       0.11346295, 0.08700898, 0.09195689], dtype=float32), array([[[[ 6.87771535e-05],
         [ 1.53266778e-02],
         [ 2.49297433e-02],
         ...,
         [ 3.13387401e-02],
         [ 1.12442654e-02],
         [-4.98962868e-03]],

        [[-3.62522453e-02],
         [ 1.98104475e-02],
         [-1.48679996e-02],
         ...,
         [-1.84025038e-02],
         [-1.77455638e-02],
         [-2.59394404e-02]],

        [[-1.10489986e-04],
         [-3.04682255e-02],
         [-2.13944837e-02],
         ...,
         [ 9.24938079e-03],
         [ 7.04356795e-03],
         [ 1.44042717e-02]]],


       [[[ 1.73813291e-02],
         [ 2.05032378e-02],
         [ 1.28057525e-02],
         ...,
         [-2.67219339e-02],
         [ 1.43208727e-02],
         [ 2.60537304e-02]],

        [[-2.41676066e-02],
         [-8.38311296e-03],
         [ 1.40269762e-02],
         ...,
         [-2.84332484e-02],
         [ 8.35399609e-03],
         [ 3.17667495e-03]],

        [[ 1.53653724e-02],
         [ 4.64392267e-03],
         [-2.01328360e-02],
         ...,
         [ 4.18445887e-03],
         [-1.07561480e-02],
         [ 2.04419978e-02]]],


       [[[ 1.80630274e-02],
         [-9.38964915e-03],
         [ 1.54947471e-02],
         ...,
         [-1.06450543e-02],
         [-7.00411107e-03],
         [-5.05175628e-03]],

        [[ 1.18549764e-02],
         [ 2.07970031e-02],
         [-3.30033377e-02],
         ...,
         [ 2.22870670e-02],
         [ 2.22940315e-02],
         [-1.04184393e-02]],

        [[ 1.41686946e-03],
         [-2.42725965e-02],
         [ 1.77708343e-02],
         ...,
         [-4.98915464e-03],
         [ 3.52961123e-02],
         [ 1.57618131e-02]]]], dtype=float32), array([[[[ 0.03989338,  0.02375351, -0.04129132, ..., -0.06198701,
          -0.02435362,  0.04365093],
         [ 0.00056872,  0.01015735,  0.03885921, ...,  0.04127887,
          -0.00691492, -0.04705112],
         [ 0.03463927,  0.03919052,  0.00588224, ...,  0.0144265 ,
          -0.05397649, -0.03171355],
         ...,
         [ 0.04429782, -0.06934536, -0.06755318, ..., -0.00900748,
          -0.0404293 , -0.04681276],
         [ 0.04786333,  0.01957773, -0.04549645, ..., -0.06466053,
           0.03876861,  0.03505962],
         [-0.00900539,  0.04559304, -0.00177216, ..., -0.01923165,
           0.03248353,  0.01425946]]]], dtype=float32), array([0.9844848 , 1.0195116 , 1.0247512 , 0.9847362 , 1.0014466 ,
       0.9979418 , 0.9963308 , 1.0006831 , 1.0153297 , 0.99411345,
       1.0194105 , 1.0004545 , 0.98753214, 0.99378973, 0.99515563,
       0.9988888 , 0.9869342 , 0.998196  , 0.9963402 , 0.9894176 ,
       1.0017622 , 1.0088425 , 1.0126666 , 1.0028197 , 0.99866706,
       1.0034318 , 1.0007805 , 1.0011384 , 1.0017971 , 0.98897946,
       0.9997249 , 1.0221888 , 0.9857623 , 1.0006107 , 0.9904258 ,
       0.9948091 , 0.9960444 , 0.9969313 , 1.0192544 , 1.0021168 ,
       1.0251085 , 0.98967004, 0.98642355, 1.019414  , 0.97085786,
       1.0133879 , 0.9897789 , 1.0344673 , 0.9887539 , 0.98336387,
       0.99295443, 0.99631286, 0.99737847, 1.021718  , 0.99454707,
       1.0157428 , 1.0105679 , 1.0150193 , 0.99849117, 1.0198941 ,
       1.007643  , 0.99135447, 1.0194073 , 0.9881012 , 0.9917544 ,
       0.98970914, 1.0009961 , 0.9956762 , 0.9951032 , 1.0039594 ,
       1.000634  , 0.99791145, 0.99502397, 1.003541  , 1.0160627 ,
       0.9983155 , 0.9998627 , 0.9912918 , 0.98126847, 0.99683446,
       0.9886245 , 1.012394  , 0.99576765, 1.0089346 , 1.0099133 ,
       1.0128175 , 1.0000557 , 0.99264985, 0.996865  , 0.9845334 ,
       1.0008749 , 0.9978123 , 0.98745865, 1.0077654 , 1.0012729 ,
       1.0160328 , 0.9983166 , 0.99666303, 0.9885849 , 0.9923216 ,
       0.9920577 , 1.0043105 , 1.0334809 , 1.0062852 , 0.9941655 ,
       0.9969528 , 1.0033224 , 1.0091394 , 1.0004652 , 1.0034903 ,
       1.0135462 , 0.99687   , 0.9850461 , 0.9901947 , 0.99086493,
       1.0068067 , 0.9954214 , 0.9953417 , 0.9952493 , 0.9980108 ,
       0.98188   , 0.99498713, 1.0514404 , 0.99036425, 1.003679  ,
       0.99599713, 0.99545354, 0.9969539 , 0.99661   , 0.993463  ,
       0.9957396 , 0.99311185, 1.0090731 , 1.0055687 , 1.0083072 ,
       0.9892026 , 1.0003313 , 0.99368155, 1.0293992 , 0.9844852 ,
       0.99100965, 0.9912878 , 1.0187212 , 1.004918  , 0.98921704,
       1.0034634 , 0.9798514 , 0.9907371 , 1.0048801 , 0.9945166 ,
       1.008368  , 0.99305516, 0.99801695, 1.0466418 , 1.0001104 ,
       1.001315  , 1.0111767 , 0.99390554, 0.99178326, 1.0129232 ,
       0.9978368 , 1.0050316 , 0.97172284, 0.99945045, 0.98480076,
       0.99472153, 1.0144116 , 0.9894925 , 0.98429257, 1.002221  ,
       0.9884758 , 0.9928203 , 1.0146348 , 0.9862929 , 0.9958651 ,
       0.9993884 , 0.9712561 , 0.99424714, 0.9947601 , 0.9968997 ,
       1.0253278 , 0.9947441 , 1.0059111 , 1.0224065 , 1.038735  ,
       0.98187375, 0.9895016 , 1.000731  , 0.99850416, 0.98337054,
       1.0054185 , 0.990137  , 1.0101608 , 1.0003806 , 1.0073007 ,
       1.0150775 , 1.007049  , 1.0259025 , 1.0025389 , 0.98184973,
       0.9931561 , 1.0077704 , 0.99339783, 0.9909777 , 1.0100721 ,
       1.0015224 , 1.0024691 , 1.0253358 , 0.9870702 , 1.0042405 ,
       0.9864438 , 0.99093145, 1.0070416 , 1.0092182 , 0.99480444,
       0.9892193 , 0.99361897, 0.9938318 , 1.021062  , 1.0061446 ,
       1.0070567 , 0.99971354, 0.992416  , 0.99564207, 1.0039704 ,
       0.99359363, 0.9950762 , 1.0049628 , 1.0224404 , 0.99651897,
       0.9898641 , 1.009956  , 0.9904346 , 0.9899792 , 1.0298816 ,
       0.9885714 , 0.9951824 , 0.98814607, 0.9922868 , 1.0065851 ,
       1.0213405 , 1.0026426 , 1.0009202 , 0.9884138 , 1.0072247 ,
       0.9957391 , 0.9912629 , 1.0035591 , 1.0138097 , 0.99948156,
       1.0204651 , 0.99757046, 0.9940069 , 1.0036553 , 0.9877476 ,
       0.9948085 , 0.9935222 , 0.99287575, 1.0040208 , 1.02305   ,
       0.99391043, 1.01964   , 0.9951668 , 0.977511  , 1.029138  ,
       0.9948233 , 0.99396676, 1.0071446 , 1.0007846 , 0.9977678 ,
       1.0233903 , 0.990253  , 0.99708563, 0.99644375, 0.9903829 ,
       1.0170603 , 1.023114  , 0.994486  , 0.99231386, 1.0034584 ,
       0.9986176 , 1.0403094 , 1.008081  , 1.0162466 , 0.9842642 ,
       1.019781  , 1.0057938 , 1.0003489 , 0.99543786, 0.99298376,
       1.0005633 , 0.9946516 , 1.0354095 , 1.0063784 , 1.000043  ,
       0.99830323, 0.9969436 , 1.0103694 , 0.9951373 , 0.9973525 ,
       1.0001038 , 0.99401736, 0.9933686 , 0.9911081 , 1.0049149 ,
       1.0053334 , 1.0096523 , 0.9967814 , 0.9834223 , 0.99602485,
       1.0001948 , 0.9998744 , 0.9980123 , 0.9995826 , 1.0193213 ,
       0.9976959 , 0.99110043, 1.0186226 , 0.9959967 , 1.0012981 ,
       0.9927768 , 1.0008196 , 0.9958876 , 0.99663705, 0.9977419 ,
       0.99667794, 0.9973926 , 0.9975258 , 0.99464434, 0.98781794,
       0.9960945 , 0.9977206 , 0.9867605 , 1.0172234 , 0.99503404,
       0.9998915 , 1.0415969 , 1.018466  , 1.0027477 , 0.9835786 ,
       1.0053712 , 0.98466563, 1.0016637 , 1.0210754 , 1.0090091 ,
       0.9891427 , 0.9992458 , 1.005231  , 1.0155584 , 1.0286885 ,
       0.9879484 , 1.0169823 , 0.9896924 , 1.0108097 , 0.9966235 ,
       1.0023425 , 0.9956086 , 0.9889996 , 1.0220165 , 0.9976092 ,
       0.9971954 , 1.0063349 , 1.0006644 , 0.99595207, 0.98378384,
       0.998772  , 0.9953516 , 0.9952482 , 0.98419446, 0.9953783 ,
       0.993309  , 0.98783815, 0.9938027 , 1.0322709 , 0.99106044,
       1.0159134 , 1.0209796 , 0.98656297, 1.0344566 , 1.0078079 ,
       0.9852542 , 0.99466133, 0.99061745, 1.0008487 , 1.0234993 ,
       0.98794407, 0.9940908 , 0.99830896, 1.037382  , 0.9966206 ,
       1.0080165 , 1.003997  , 0.9966403 , 0.9956429 , 0.9927036 ,
       0.9980529 , 0.9945567 , 0.98914397, 0.992831  , 1.0129191 ,
       1.0036299 , 1.0098962 , 1.0033069 , 0.99087036, 1.0031377 ,
       1.0189953 , 0.99981815, 0.9910484 , 0.9892219 , 0.9991263 ,
       0.99295324, 0.99881536, 0.9842001 , 0.99226534, 1.0139779 ,
       1.0008103 , 0.9986985 , 0.9970273 , 1.0002471 , 1.0122522 ,
       0.9910507 , 0.9946048 , 0.99350595, 1.0118613 , 0.99812675,
       0.9971316 , 0.9822528 , 0.99487615, 1.0041653 , 1.0177604 ,
       1.0090252 , 0.9923541 , 0.9837185 , 0.9964426 , 0.9956442 ,
       1.0023144 , 0.9999237 , 0.99365395, 1.0042822 , 0.9939866 ,
       0.99267626, 1.0277466 , 1.0099181 , 0.9895496 , 1.0000421 ,
       0.9964635 , 0.99293023, 0.9999427 , 0.9984832 , 0.9886845 ,
       0.9934962 , 0.987091  , 0.98924416, 1.0022796 , 1.0131391 ,
       1.0050418 , 1.0056248 , 0.9933313 , 0.99108136, 0.9885802 ,
       0.99414176, 0.9934379 , 1.0189179 , 0.99240553, 0.9913575 ,
       0.9899577 , 1.0001146 , 0.9957525 , 1.0103999 , 1.0003961 ,
       0.9980716 , 1.0143596 , 1.0016106 , 1.0167857 , 0.98966265,
       1.0074959 , 0.9894832 , 1.0013195 , 0.99658126, 1.0160868 ,
       1.0300537 , 1.0128994 , 0.9996838 , 1.0100733 , 1.0074699 ,
       0.9965622 , 0.9881406 , 0.99738497, 0.9955161 , 1.0011498 ,
       0.9933699 , 0.997135  , 0.9992522 , 0.9872056 , 1.0175563 ,
       1.0054394 , 0.9941045 , 0.9948059 , 0.9918914 , 1.0006979 ,
       0.9902435 , 1.0093914 , 1.0005817 , 1.0123787 , 0.98541325,
       1.0077808 , 0.9891516 , 1.0045619 , 1.0151179 , 1.0033509 ,
       0.99591714, 0.9999501 , 0.99532515, 0.99269533, 0.9972457 ,
       0.99431574, 0.9962603 , 0.9967581 , 1.0114444 , 1.043089  ,
       0.9922537 , 1.0034992 , 1.0066162 , 0.9970208 , 0.99934894,
       1.0097154 , 0.9881144 , 1.0029469 , 0.9907923 , 0.986054  ,
       0.9979869 , 0.9917062 , 0.9979376 , 1.0192741 , 0.98678255,
       0.99740756, 1.0127394 , 0.99773353, 0.9853425 , 0.99081063,
       0.98149973, 1.006054  , 0.98187464, 0.9953754 , 1.0018305 ,
       1.0090759 , 0.9881405 , 1.0170268 , 0.9998968 , 0.99120486,
       1.0038732 , 0.99374473, 1.0044103 , 1.0114541 , 0.99330205,
       1.0008048 , 1.0204672 , 1.0178351 , 0.9959692 , 0.99461955,
       0.9966696 , 0.99422   , 1.0015656 , 1.0169959 , 0.9953534 ,
       1.0077736 , 0.9924099 , 0.99511486, 0.9913665 , 1.0068697 ,
       1.0040785 , 1.0256677 , 0.98967654, 1.0036131 , 0.9955034 ,
       1.0026549 , 1.0156482 , 1.0016743 , 0.99667925, 1.0068213 ,
       0.9979723 , 1.0068089 , 0.9882195 , 1.0114412 , 0.9954405 ,
       0.9881298 , 1.0108184 , 0.997662  , 1.002427  , 0.98597544,
       1.0166364 , 0.99729717, 1.0045396 , 1.0021095 , 1.0181066 ,
       0.99636555, 1.0000881 , 1.0286857 , 1.02379   , 0.9993318 ,
       0.9917432 , 1.0114652 , 1.0142895 , 0.9826288 , 1.0013018 ,
       0.9917322 , 1.012705  , 0.9953839 , 1.0087079 , 1.0008595 ,
       0.99537194, 1.0141178 , 1.0040957 , 0.99767697, 0.9922639 ,
       0.9985121 , 0.9887119 , 0.99262905, 0.99794847, 1.0112212 ,
       1.0029893 , 1.0064167 , 0.9915925 , 1.030507  , 0.989771  ,
       0.99539864, 0.9970439 , 0.99256694, 0.9975196 , 1.0027064 ,
       1.0115532 , 1.0042436 , 1.0012975 , 0.99087036, 1.0051926 ,
       0.99261093, 0.99277395, 0.98908556, 0.99810475, 1.0060948 ,
       1.0002164 , 0.99205846, 0.9931832 , 0.98832643, 1.0085235 ,
       0.98690027, 0.99292755, 1.0088127 , 1.0032911 , 1.0049314 ,
       0.999109  , 0.9904066 , 1.0107782 , 0.9958981 , 0.99538654,
       0.9888882 , 1.0193106 , 0.9942938 , 1.0174088 , 0.99426323,
       1.0089933 , 0.9983858 , 0.99210095, 1.0017586 , 1.0325615 ,
       1.0091338 , 0.97289324, 0.98938173, 0.9925874 , 0.98388064,
       0.99188054, 0.9987175 , 1.0019734 , 0.98949254, 1.0197724 ,
       0.9945449 , 0.9912268 , 1.019795  , 0.99239224, 1.0034901 ,
       0.9919692 , 1.0327561 , 0.99820524, 0.99748087, 0.993339  ,
       1.0168753 , 0.99797267, 0.9959503 , 0.9932942 , 0.99514073,
       0.9978459 , 1.0020761 , 0.98736066, 0.9936721 , 1.0014364 ,
       0.9984424 , 1.0051898 , 1.0011038 , 0.99636036, 1.0455008 ,
       0.9994561 , 0.99725837, 1.0526478 , 0.9955246 , 0.99874264,
       0.99924004, 1.0052929 , 0.9950064 , 0.9937355 , 0.994729  ,
       0.9956342 , 0.9974693 , 0.99737453, 0.986167  , 0.99066955,
       1.0072893 , 1.000063  , 0.9963398 , 0.99995583, 0.99988514,
       1.018097  , 1.0100048 , 0.9973251 , 1.0079    , 1.0218256 ,
       1.0177187 , 0.9893095 , 0.995541  ], dtype=float32), array([-7.37160351e-03,  2.98213884e-02,  1.83080938e-02, -5.20934463e-02,
        1.53794615e-02,  4.26940154e-03, -1.49361428e-03,  2.72527151e-02,
        9.84891225e-03, -8.65142420e-03,  1.39892129e-02, -8.50933511e-03,
       -1.52990753e-02, -4.80290689e-03, -5.84056508e-03,  1.47788727e-04,
       -9.87306423e-03, -1.45472120e-02, -4.39045159e-03, -2.65876465e-02,
        1.11393081e-02,  5.16375480e-03,  4.66169370e-03,  6.83392491e-03,
       -1.79238394e-02, -5.62759489e-03, -2.63974797e-02, -8.13852903e-03,
        1.12942560e-02, -4.53506969e-03, -1.78436982e-03, -5.74783571e-02,
       -2.55316086e-02,  5.62631665e-03, -1.12335514e-02,  1.98825495e-03,
       -2.59306878e-02, -9.11547244e-03, -5.28789125e-02,  1.15957409e-02,
       -3.12537104e-02,  1.28762494e-03,  7.52215215e-04,  4.79566352e-03,
       -2.75740307e-02,  1.83727760e-02, -8.92717764e-03,  2.80986521e-02,
       -4.29834891e-03, -1.79399420e-02, -3.09770498e-02, -2.76229461e-03,
       -5.86628914e-04,  3.73737141e-03, -2.42816992e-02,  8.35855305e-03,
       -2.23185541e-03,  2.53932700e-02,  1.15421396e-02,  2.87776347e-02,
        4.85251984e-03, -1.15174754e-03,  2.06543151e-02, -1.21200783e-02,
       -1.85334254e-02, -1.46796629e-02, -2.00537741e-02, -9.49180510e-04,
        7.39223906e-04, -1.56850042e-03,  6.02232665e-03, -8.47350154e-03,
       -1.96607783e-02, -9.09480150e-06,  2.45552510e-02, -2.19688378e-02,
        7.82732293e-03, -2.10035089e-02, -2.58021615e-02,  3.25423200e-03,
       -2.77957413e-02,  1.23325689e-02, -2.73300707e-02,  3.53709375e-03,
       -2.54091918e-02,  1.81699861e-02,  5.82803087e-03, -2.80070007e-02,
       -2.71012653e-02, -6.60067657e-03,  2.22245906e-03, -4.46681213e-03,
       -5.26722521e-03, -1.70585662e-02,  8.44101794e-03,  1.98023599e-02,
       -3.69178364e-04, -2.61454377e-03, -1.55078834e-02, -5.32658817e-03,
       -2.68680695e-03,  1.58377811e-02,  5.19408435e-02,  2.78314319e-03,
       -8.13600700e-03, -2.83580329e-02,  8.31334759e-03, -6.60250476e-03,
       -7.33572990e-03, -2.81107123e-03,  1.66069772e-02,  1.10725197e-03,
       -7.79023580e-03, -1.82968397e-02, -9.36003309e-03,  9.71181411e-03,
       -3.97798512e-03, -5.80358645e-03,  1.57710107e-03, -3.68694142e-02,
       -1.11461366e-02,  5.83608029e-03,  5.08138724e-02, -8.14339425e-03,
        6.31750189e-03,  2.28374940e-03, -1.66703947e-02, -5.57364291e-03,
       -1.77781396e-02, -9.06916801e-03, -1.92631800e-02, -7.98470620e-03,
        1.45504344e-02, -1.20984213e-02,  3.85268927e-02, -8.01019184e-03,
        6.55256398e-03, -7.95340259e-03,  2.30165478e-02, -1.88983660e-02,
        8.45909864e-03, -2.62985908e-04,  2.13778112e-02, -1.60148200e-02,
       -9.24767181e-03, -2.78076343e-03, -3.66001539e-02, -1.58293322e-02,
        1.09834317e-02, -7.58677861e-03,  2.11946666e-02, -1.03281401e-02,
       -5.32961916e-03,  3.96010987e-02,  7.07902387e-03, -1.22389081e-03,
        4.63960087e-03, -2.81266589e-02, -1.08526452e-02,  1.02271251e-02,
        3.30557791e-03, -1.36099374e-02, -1.65830757e-02,  4.66918200e-03,
       -1.29775675e-02,  2.97692092e-03,  4.73064817e-02, -8.50290898e-03,
       -2.81843413e-02,  7.03646074e-05, -3.31349741e-03, -7.46237230e-04,
        2.14900710e-02, -6.57438813e-03,  4.86577163e-03,  6.76148618e-03,
       -2.68770978e-02, -3.88219440e-03,  1.07646901e-02, -1.47862954e-03,
        2.43289154e-02,  1.49219222e-02,  1.35875512e-02,  3.31331678e-02,
        2.67003719e-02, -4.21802886e-02, -2.79560052e-02,  2.34214049e-02,
        8.60720593e-03, -5.03589446e-03,  5.32045588e-03, -1.21932486e-02,
        2.73955483e-02, -1.16286883e-02,  3.31139639e-02,  4.01145928e-02,
       -1.51770655e-03, -6.18268503e-03, -4.17081714e-02, -9.23321396e-03,
       -5.98745793e-03, -1.02151595e-02, -4.65452904e-03, -3.54456082e-02,
        2.17424091e-02,  6.58872596e-04, -5.93531244e-02,  2.14264020e-02,
       -4.97708023e-02,  2.31830264e-03, -1.86080839e-02, -2.05799639e-02,
       -2.03803508e-03, -1.40677448e-02, -2.70271674e-02, -4.30381810e-03,
       -3.39632039e-03, -1.76087860e-02,  4.45187390e-02, -3.07079544e-03,
        2.13237442e-02,  2.54783174e-03, -2.32054945e-02, -7.10334675e-03,
       -9.81417671e-03, -2.50880281e-03, -4.31205099e-03,  8.02669302e-03,
        6.78069610e-03, -5.58121735e-03, -5.77846402e-03,  1.46194175e-02,
       -8.86951759e-03, -2.63002422e-03, -2.12784167e-02, -3.38927954e-02,
       -1.02288928e-02, -2.38275416e-02, -1.28968582e-02, -3.31922970e-03,
        1.53404279e-02,  5.70780551e-03, -5.16530313e-03, -1.37015078e-02,
        8.72150995e-05, -2.73174886e-03,  1.74165377e-03, -4.43203822e-02,
        2.51552928e-02, -1.51377507e-02,  2.40301955e-02, -2.36346964e-02,
       -8.33143201e-03, -6.68187579e-03, -1.14784380e-02, -9.93933715e-03,
       -1.21143702e-02, -6.93335803e-03,  6.96791941e-03,  1.28222564e-02,
       -1.43015916e-02,  2.81679276e-02, -7.87915941e-03, -2.36172657e-02,
        1.28169879e-02,  2.18576118e-02, -6.06599404e-03,  2.11516041e-02,
       -1.43928640e-02, -2.94032926e-03,  4.53479700e-02, -3.26459459e-03,
        1.05714984e-03, -4.76713199e-03, -3.26301903e-03, -1.54400561e-02,
        3.92864794e-02, -4.79570311e-03, -6.85415324e-03,  1.87896602e-02,
       -7.55885430e-03,  1.22807138e-02,  1.91779877e-03,  3.17167863e-02,
       -2.37103701e-02,  1.17720310e-02, -5.52486803e-04, -6.89731305e-03,
       -2.16498491e-04, -2.75884997e-02, -1.50459297e-02, -1.64408889e-03,
       -3.28770690e-02,  1.82308368e-02,  1.18634466e-03,  2.15635262e-02,
        1.41899183e-03,  1.35375587e-02, -1.96762709e-03,  3.83484885e-02,
       -6.44755224e-03, -1.75956916e-02, -1.93374185e-03, -5.06976666e-03,
       -1.45763811e-03,  1.89903211e-02,  1.20960325e-02,  2.90593089e-05,
       -3.81492376e-02, -8.00988544e-03,  5.31271659e-03,  2.74302554e-03,
        3.60216293e-03,  1.22132981e-02, -2.62163067e-03, -8.33243597e-03,
       -2.46069976e-03,  3.36553454e-02, -7.24682468e-04,  1.88278488e-03,
       -1.46639615e-03, -4.28903699e-02, -1.07999165e-02, -2.12434921e-02,
       -3.08388309e-03, -2.99599650e-03, -5.68563351e-03, -3.32636340e-03,
       -7.60020548e-03, -7.79124955e-03, -1.28857279e-02, -3.48874852e-02,
       -2.74873599e-02,  1.68591943e-02, -3.92693793e-03,  1.81156155e-02,
        2.30763368e-02,  1.63483638e-02,  4.20608744e-03,  5.84499561e-04,
        1.66395158e-02, -2.65900418e-02, -1.30536919e-03,  2.02415995e-02,
        1.36837969e-02, -1.08626690e-02, -1.97286177e-02,  2.26006117e-02,
        3.40862869e-04,  2.34982353e-02,  7.91477039e-03, -3.41013889e-03,
       -4.72024502e-03, -2.44913697e-02,  4.10155952e-03,  1.28409844e-02,
       -1.55329015e-02, -9.84993018e-03,  1.72902960e-02, -2.79203220e-03,
       -1.36796273e-02, -9.04371496e-03,  9.63509642e-03, -6.99121691e-03,
       -2.48106886e-02, -2.85789510e-03, -5.52954199e-03, -4.75022290e-03,
        5.88667113e-03,  3.52111808e-03, -7.61179207e-03, -1.60255712e-02,
       -1.74130127e-03, -3.12243681e-02, -1.27719631e-02,  1.23856543e-02,
       -2.33761482e-02, -1.09465728e-02,  4.85806577e-02,  2.40114722e-02,
       -1.54370358e-02, -1.35096237e-02, -7.20222853e-03,  1.67775415e-02,
        3.47538441e-02, -1.28349159e-02, -1.35977212e-02, -2.85738410e-04,
       -2.93640941e-02,  4.10394976e-03,  1.22073609e-02,  9.32694692e-03,
        4.02199570e-04,  1.20420102e-02, -1.86066870e-02, -2.91325636e-02,
        1.84824807e-03, -5.66973211e-03, -5.93829621e-03,  3.90132032e-02,
        5.92689915e-03,  4.96599749e-02, -4.07706801e-04, -5.36146481e-03,
        1.18682971e-02, -5.70610678e-03, -3.39760911e-03, -3.45111964e-03,
       -1.66403931e-02,  6.05258532e-03, -1.98406843e-03,  3.23787681e-03,
       -4.02069837e-03, -8.45220126e-03,  1.88834090e-02, -8.76496267e-03,
        2.06665107e-04,  1.37420725e-02,  1.08679673e-02, -2.72138081e-02,
       -1.91336451e-03, -5.60299819e-03, -1.04769664e-02, -6.85855001e-02,
        6.17954368e-03,  2.45783795e-02, -1.83310211e-02, -1.57931056e-02,
       -4.58177663e-02, -3.62367742e-02,  1.78684462e-02, -2.99841091e-02,
       -7.40897469e-03, -1.01240147e-02,  1.27504962e-02, -2.20308863e-02,
       -1.01684760e-02,  9.36368480e-03, -6.26602676e-03,  3.84291960e-03,
       -4.28850064e-03,  5.43890372e-02,  1.77585706e-02, -3.66845094e-02,
        9.62812081e-03, -7.10836984e-03,  6.35693641e-03, -2.95650610e-03,
       -2.95746457e-02, -3.29047511e-03,  1.26323970e-02, -1.68348085e-02,
        8.98796075e-04,  1.26846251e-03,  3.34281623e-02, -3.64689752e-02,
       -1.29406722e-02,  1.79884955e-03, -1.03700710e-02,  1.14485985e-04,
       -4.73010121e-03, -3.11454982e-02,  4.79266383e-02, -6.52641756e-03,
       -7.62523012e-03, -8.81629344e-03, -1.78255197e-02,  1.54995341e-02,
        1.06700705e-02,  1.63660327e-03, -5.32291923e-03,  2.88181342e-02,
       -2.30671819e-02,  1.26146590e-02, -1.89878419e-02, -7.16781244e-03,
        1.71242151e-02, -1.70749724e-02, -1.01987030e-02,  2.83047874e-02,
        1.13181928e-02,  2.33288165e-02,  7.31855631e-03, -8.35893676e-03,
        3.21133574e-03,  5.94539428e-03, -9.36866552e-03, -3.30366306e-02,
       -1.43732987e-02, -5.15294727e-04, -1.15359873e-02,  3.21510551e-03,
       -1.01404898e-02, -1.92041192e-02,  3.28551754e-02,  1.82165811e-03,
       -8.74816533e-03, -5.84191037e-03, -9.31457896e-03, -1.71725582e-02,
       -2.82592466e-03,  7.27206795e-03, -7.75284192e-04, -1.00077754e-02,
       -1.63959973e-02,  5.72734000e-03, -1.91001147e-02,  3.59333642e-02,
        9.91113484e-03,  1.34087661e-02, -1.02361497e-02, -1.68794524e-02,
       -2.07994655e-02,  3.46422149e-03,  1.25383455e-02, -1.05719632e-02,
       -9.63689294e-03, -1.16826058e-03, -1.17185367e-02,  2.21632747e-03,
       -1.33846300e-02, -1.21565918e-02,  6.99418131e-03, -1.66613683e-02,
        7.65566539e-04,  2.11664345e-02,  6.49099238e-04, -1.08033707e-02,
       -1.31618744e-02, -8.90152529e-03, -1.20045776e-02, -7.80012691e-03,
        3.58064333e-03,  1.42411375e-02, -5.91306947e-03,  2.47126026e-03,
        1.20550375e-02, -5.74715808e-03, -1.41559979e-02, -2.51303092e-02,
       -1.26978448e-02, -3.09792720e-02, -1.40535282e-02, -7.95120187e-03,
       -1.01294229e-02, -1.07148373e-02, -1.86195504e-02,  1.34463806e-03,
        7.57196872e-03, -4.10453137e-03, -2.63994057e-02, -5.05819102e-04,
       -1.90889323e-03,  1.60018746e-02, -1.39657385e-03,  1.06504029e-02,
        2.15722043e-02,  3.17839943e-02, -7.71510997e-04, -1.47974619e-03,
        1.02422852e-02, -2.38615237e-02,  9.42010258e-04,  3.42179760e-02,
        4.10817983e-03,  4.81095491e-03, -8.05593748e-03, -6.55243034e-03,
       -1.38744032e-02,  1.80722249e-03,  5.50208148e-03, -7.33801583e-03,
       -1.49657708e-02, -3.41102830e-03, -4.90064500e-03, -3.84853827e-03,
        2.17452496e-02, -3.76141928e-02, -1.60347088e-03,  5.24454657e-03,
       -8.68459931e-04, -1.84980687e-02, -2.62160189e-02,  2.12477185e-02,
       -3.38570215e-02, -2.05083229e-02,  2.89984141e-02,  8.56026635e-03,
       -1.20561244e-03, -2.33260375e-02,  3.41732949e-02, -1.66858209e-03,
        5.26404474e-03,  5.23183821e-03,  4.13083434e-02,  5.04204957e-03,
       -3.63464765e-02,  1.01196794e-02,  3.85405943e-02, -1.18257124e-02,
        9.08265729e-03, -4.53866348e-02, -5.24702296e-02, -1.91226751e-02,
       -6.67954888e-03, -5.46649471e-03,  1.23091135e-02,  2.22516302e-02,
        3.02686784e-02, -6.89030066e-03, -5.50814625e-03,  5.47298044e-03,
        8.92082974e-03, -2.50662398e-03, -9.34167206e-03,  1.58534609e-02,
       -1.35734389e-02, -5.06406464e-03, -2.33171694e-03,  1.16919577e-02,
        2.42376365e-02,  9.56047513e-03, -1.90078653e-02, -6.17990829e-03,
       -4.52357437e-03,  4.51393425e-03, -1.05871375e-04, -5.71706519e-03,
       -1.12306559e-03,  1.33471228e-02,  3.82415913e-02,  9.35113896e-03,
        1.61684130e-03, -5.49978111e-03,  5.36903390e-04, -3.49934027e-03,
       -8.09035450e-03, -9.05725057e-04, -1.85344238e-02,  6.31013140e-03,
        5.06654615e-03, -9.44411103e-03, -2.94069815e-02, -1.01040835e-02,
        7.74586620e-03, -1.36335324e-02, -2.44675530e-03,  1.08396234e-02,
        2.51021795e-02,  8.52325279e-03, -4.11087880e-03, -1.34640662e-02,
        1.99907217e-02,  4.92338557e-03,  9.32238717e-03,  9.14217997e-03,
        2.23739725e-02, -2.66178022e-03,  9.86611098e-03, -1.68416407e-02,
       -1.96387786e-02,  2.22866330e-03, -5.46901599e-02, -6.00342639e-03,
        2.72084344e-02,  1.27455257e-02, -1.92496236e-02, -9.01285466e-03,
       -1.00394264e-02, -3.14841047e-02, -1.79100987e-02, -6.46773772e-03,
       -9.57042631e-03, -1.42981531e-02,  2.32443046e-02,  7.63511984e-03,
       -1.87017780e-03,  3.76473106e-02, -8.19466729e-03,  3.56208417e-03,
       -5.49997017e-03,  5.60879670e-02,  7.63797341e-03,  8.60795286e-03,
       -1.74006261e-02,  2.26901006e-02, -8.17712303e-03,  1.59407035e-03,
       -3.01888329e-03, -3.30945849e-02, -2.02612509e-03,  6.23593712e-03,
       -4.04605046e-02, -1.83811989e-02, -1.69206839e-02, -2.18094196e-02,
        8.12742673e-03,  7.87269883e-03, -6.17578113e-03,  5.05433418e-02,
       -7.31849903e-03, -1.68642402e-02, -3.31203043e-02, -1.84698589e-02,
        7.06847664e-03, -3.40157412e-02,  9.33741126e-03, -4.06595599e-03,
       -2.11536326e-03,  4.27762046e-03,  7.62195373e-03, -1.42770391e-02,
       -1.53037179e-02, -1.72808859e-02, -5.52813476e-03,  1.34699512e-02,
       -1.35000306e-03, -3.02744447e-03, -1.52297923e-02, -3.20294918e-03,
       -2.12399522e-03,  1.47295883e-02, -3.48787010e-03,  7.25081097e-03,
        2.84899455e-02,  2.03966051e-02, -5.21325367e-03, -3.57897170e-02],
      dtype=float32), array([-0.10521041, -0.08502826,  0.02825186,  0.2743024 , -0.04306722,
        0.07402588, -0.1907825 , -0.15808213,  0.04153876,  0.0870051 ,
       -0.14331613,  0.23538443, -0.08951584,  0.07327434,  0.04052454,
       -0.23698883, -0.05234552, -0.14451532, -0.07081171,  0.2271847 ,
        0.03486878, -0.1507362 ,  0.03297225,  0.04319065,  0.2021378 ,
        0.16592462,  0.1299203 ,  0.24468905, -0.16681994,  0.1400252 ,
        0.00841223,  0.3697934 , -0.2374101 ,  0.13899066,  0.12463359,
       -0.06412897,  0.24018091, -0.04372834,  0.3644599 , -0.02371788,
        0.12301715, -0.05746653,  0.07554708, -0.02687716,  0.10197742,
       -0.08102304,  0.02235727,  0.07995002,  0.06402942, -0.10848107,
        0.23093641, -0.03059061,  0.07331306,  0.20627956,  0.2828403 ,
       -0.18331182, -0.00949446, -0.35615763, -0.13911857, -0.10427587,
        0.00356504, -0.13018228, -0.08605052, -0.04159689,  0.22514404,
        0.16325435,  0.1390027 , -0.05642289, -0.0239875 ,  0.15109453,
       -0.02316588, -0.14271091,  0.16306104, -0.19763917, -0.17587508,
       -0.21632297, -0.02699016,  0.12337624,  0.05107437, -0.1291916 ,
        0.1747161 ,  0.03520058,  0.31255803, -0.07123505, -0.05624975,
       -0.02310346,  0.11385614, -0.14253938,  0.25224692,  0.13455208,
       -0.1740736 ,  0.12682672,  0.12147926,  0.23355226, -0.03814248,
       -0.12338521, -0.05345533, -0.10596564, -0.09634558,  0.15445055,
       -0.09279305, -0.14685309, -0.09913231, -0.0206169 ,  0.10939633,
        0.19386002, -0.09611745,  0.07530566, -0.11332981, -0.11336653,
       -0.03473804, -0.11063343, -0.17947651,  0.21058461,  0.08913308,
        0.12270709, -0.03846313,  0.03917957, -0.12656431,  0.27594632,
        0.14711682,  0.10743223,  0.09570922, -0.16721629,  0.07513459,
       -0.1328741 ,  0.03051654,  0.1198466 ,  0.17017859,  0.08155526,
        0.22833091, -0.00219074, -0.01094666,  0.14447801, -0.09695574,
       -0.05031608, -0.05484226,  0.12772585, -0.08546539,  0.1642186 ,
        0.01221736, -0.07216926,  0.05805999, -0.16119263,  0.07556774,
       -0.05907365,  0.10135394,  0.08924145, -0.22868665,  0.04546675,
       -0.06565376,  0.10695837,  0.00471594, -0.04547954,  0.09153964,
       -0.112759  , -0.08052299,  0.23008251,  0.07822005, -0.22823802,
       -0.1638597 ,  0.10081733,  0.11612385, -0.13459063,  0.02292044,
        0.30901238, -0.14030673, -0.05246993,  0.16204685, -0.2629657 ,
       -0.08439275, -0.08828931, -0.1404264 ,  0.12266856, -0.12635003,
       -0.13237607,  0.11982029,  0.20597194, -0.05600206,  0.11184116,
       -0.13061264, -0.07223181, -0.03381981, -0.12838085,  0.06337869,
        0.21164398,  0.20343368, -0.05611466, -0.08228733,  0.05124295,
       -0.09889713,  0.15026662, -0.0903063 ,  0.15512595, -0.2128658 ,
       -0.16973746,  0.19264273,  0.11489048,  0.34272915,  0.03528472,
       -0.20200089,  0.0773649 , -0.136469  ,  0.26870742,  0.07996014,
       -0.05541673,  0.14215755, -0.28341144,  0.18466955,  0.04657512,
       -0.20668696,  0.09735788,  0.00224326, -0.02006856,  0.07299291,
        0.14270216, -0.0281091 ,  0.14599814, -0.17807876,  0.18201467,
       -0.09554647, -0.07324196,  0.21982859, -0.06707887, -0.16548693,
       -0.03990991,  0.08985867, -0.0960511 ,  0.08508397, -0.06597921,
        0.08594418,  0.09179796,  0.05137616,  0.02244405,  0.21965997,
        0.30718118,  0.00436587,  0.16149046,  0.18247   ,  0.08006769,
        0.02511488, -0.20910122, -0.12682733, -0.19755775,  0.09087892,
       -0.09274574,  0.18763563,  0.2582399 , -0.08484162,  0.17331979,
        0.01929115,  0.17976525,  0.12723301,  0.16189852,  0.0056818 ,
        0.0188209 , -0.00093582, -0.08675263,  0.10685391, -0.07093199,
       -0.01214815, -0.11654423,  0.17326306,  0.21659784, -0.15277284,
       -0.18493249,  0.19341058, -0.22397074,  0.09915192, -0.14536092,
       -0.15267777,  0.1949181 , -0.11033407, -0.11133979,  0.12592337,
        0.03334825, -0.1243587 , -0.078091  , -0.09991461,  0.11711521,
       -0.13763082,  0.08168964,  0.12628601, -0.10801815,  0.11848492,
        0.02283278,  0.07725345,  0.1170871 , -0.1339581 ,  0.15630546,
        0.14792296,  0.10268526,  0.24043089, -0.10580856,  0.01311238,
       -0.14706746, -0.13484561,  0.0097311 , -0.24391274, -0.11587601,
       -0.152569  , -0.05014298,  0.07147027, -0.08540887,  0.03404128,
       -0.09803344, -0.0652219 , -0.05467742,  0.13780515, -0.14022507,
       -0.1353042 , -0.1238677 ,  0.00478489, -0.11969942,  0.02074346,
       -0.01741744, -0.02194817, -0.04135032,  0.06294379,  0.07204324,
       -0.06798337,  0.17033598,  0.02663257,  0.04458297, -0.08549234,
       -0.07954314,  0.14379045, -0.07241798,  0.06460045,  0.11421917,
        0.03277434,  0.19882205,  0.18001385, -0.01890165, -0.09520908,
       -0.14012468,  0.09128377, -0.10751809, -0.05919798,  0.04108559,
       -0.14018208,  0.11185691, -0.11823082, -0.02281265, -0.17526427,
        0.17728299, -0.22929226, -0.147556  ,  0.08100372, -0.08148985,
       -0.08144657, -0.08673033, -0.03849306,  0.1513393 , -0.21245016,
       -0.15172292, -0.00234357,  0.10487308, -0.2569326 , -0.07461889,
        0.14021985,  0.20252332,  0.10874903,  0.03308825,  0.10118973,
        0.09112061,  0.14677073, -0.04288338, -0.05135849, -0.00878424,
        0.13963124,  0.03736443,  0.07617549,  0.20169432, -0.03134578,
       -0.12219485,  0.20625089,  0.1254237 , -0.1709557 , -0.12392344,
       -0.0759026 ,  0.04669182,  0.11113498, -0.03692926, -0.071675  ,
       -0.03774333, -0.10156067, -0.13457212,  0.22498736, -0.00806982,
       -0.23027055, -0.18970169, -0.14403878, -0.14411244, -0.19183256,
        0.20558216, -0.03471034, -0.05865826,  0.13402705, -0.1398214 ,
       -0.02355917, -0.19718271,  0.16192156, -0.15975319, -0.10983623,
        0.17611265,  0.02050519, -0.00528063,  0.20022632, -0.10966258,
       -0.03713847,  0.02585461, -0.0365558 , -0.04010437, -0.15065761,
       -0.00848555, -0.11687613, -0.08027486, -0.19555286,  0.12944137,
       -0.01766534, -0.07173894,  0.11986428,  0.29257938, -0.1546573 ,
        0.01923968,  0.0968461 ,  0.07912931,  0.23709457,  0.21771474,
       -0.1828644 ,  0.10013345,  0.05137506,  0.097992  ,  0.09977508,
        0.13068278,  0.11445769,  0.1462275 , -0.04873822, -0.06975932,
       -0.06916413, -0.25770298,  0.10947268,  0.24667801, -0.1590631 ,
        0.06937934, -0.13217522,  0.10690004,  0.20769109,  0.03408242,
       -0.0886001 ,  0.14305937, -0.06699636, -0.07176641, -0.11142584,
        0.12619145,  0.07599945, -0.01166561,  0.10426526, -0.07800692,
       -0.08832454,  0.16832726, -0.17676662, -0.14273383, -0.04620172,
        0.09661409,  0.23389359, -0.14553972,  0.08256801,  0.1760714 ,
       -0.00983788, -0.08517106,  0.17647204, -0.11986557,  0.40801764,
        0.2123526 ,  0.06817275,  0.18514748,  0.04380406, -0.02976923,
        0.02509734, -0.05407317, -0.18514374,  0.14756986, -0.12733972,
       -0.00131326, -0.08886624,  0.17535391, -0.01352267, -0.09444856,
       -0.09869821, -0.03842495,  0.10872091,  0.10298536, -0.11070146,
       -0.10944107,  0.16041857,  0.07068627,  0.12473974,  0.13869064,
       -0.13252781,  0.02835432, -0.0896126 ,  0.02957989,  0.00095754,
       -0.08198165,  0.11688246, -0.20320079, -0.06127831, -0.10448375,
       -0.12958333,  0.05582079,  0.08431824,  0.08182585,  0.11632232,
       -0.0611129 ,  0.07414689, -0.07923663,  0.10085452,  0.22332585,
        0.1315488 , -0.10610851,  0.03517853,  0.1250761 ,  0.06058605,
       -0.19534321, -0.15772128, -0.11828577, -0.10380485, -0.10412833,
        0.12519142, -0.05409706,  0.01174195,  0.07622112,  0.05378228,
        0.04476688, -0.03340299, -0.01048822,  0.02563638,  0.217546  ,
        0.11166928,  0.16538256,  0.12831365,  0.07072766, -0.23168781,
       -0.02576294, -0.0064318 ,  0.12457652,  0.00193227, -0.06317897,
        0.12817027, -0.07644356, -0.03677424, -0.24866961,  0.04698956,
       -0.03720485, -0.37424567,  0.00968026, -0.11495874,  0.14330359,
        0.01102049, -0.04094357, -0.2925409 , -0.10344894, -0.08780241,
       -0.06484231,  0.08439621, -0.1534176 ,  0.24567045,  0.09012395,
       -0.02644939,  0.17532492,  0.08671868, -0.17255357, -0.11261102,
       -0.07681083, -0.14346638,  0.2500156 ,  0.09314118,  0.20694715,
        0.22059959,  0.06940052,  0.15038094, -0.15222608,  0.27025628,
        0.11668032, -0.13840227, -0.15536591, -0.0842089 ,  0.20470767,
       -0.03775926, -0.08342352,  0.03423464, -0.05083321, -0.08677589,
       -0.03014961,  0.26968783,  0.13751683, -0.20848872,  0.01727914,
       -0.15720892,  0.30262867,  0.37504473,  0.12274145, -0.17870347,
       -0.13640185, -0.05433318, -0.12208888, -0.05432708,  0.13001344,
        0.03367953, -0.11251335, -0.02537056, -0.10553826, -0.03492256,
       -0.12421685, -0.12047785,  0.10118562,  0.06497408, -0.04345512,
       -0.14709574, -0.13553962,  0.142115  ,  0.1015992 , -0.1791815 ,
       -0.14640662, -0.15434577, -0.0115664 ,  0.05606479, -0.20994078,
       -0.2691923 , -0.23249857,  0.07792527,  0.12361829,  0.10035931,
       -0.10714392, -0.03123213, -0.05722391,  0.2736631 ,  0.07389221,
       -0.09202067,  0.12610392,  0.1542043 ,  0.15392356,  0.09784276,
        0.09602164, -0.16630314, -0.07999698, -0.1109568 , -0.11978415,
        0.03936462,  0.20620918, -0.02408412, -0.13575946, -0.1902085 ,
        0.1277532 , -0.03721783, -0.08503854,  0.06970253, -0.04888187,
       -0.1348847 ,  0.11831548,  0.27226803, -0.1312934 ,  0.06954537,
       -0.03622449,  0.10801692,  0.03295203, -0.18633187,  0.11054011,
        0.20452225, -0.05623191,  0.14026256, -0.01349215, -0.13389055,
       -0.00910366,  0.16374862, -0.14408873, -0.08358751, -0.18685059,
        0.0724908 , -0.03324163, -0.07993689, -0.27542576,  0.04764869,
        0.14478186, -0.09317152, -0.09376025, -0.15357949,  0.42491242,
       -0.11783779, -0.16854826,  0.26019445,  0.1793287 , -0.161666  ,
        0.09062464, -0.11699854, -0.13848536, -0.15328729,  0.00292055,
       -0.05365914,  0.16281833,  0.2576245 ,  0.12507415, -0.01838016,
        0.12807862, -0.01571363, -0.11206891, -0.06130559, -0.14307114,
        0.15570903,  0.09978738,  0.11212996,  0.27575207, -0.03498232,
       -0.20242755, -0.19978853,  0.11355063, -0.00748935,  0.14352658,
        0.09210862, -0.027168  ,  0.04721899,  0.10137413, -0.04328105,
       -0.03680621, -0.107268  ,  0.23470928], dtype=float32), array([0.158222  , 0.2040389 , 0.15912569, 0.41914582, 0.1982414 ,
       0.18350662, 0.61871445, 0.3938313 , 0.17467625, 0.22228639,
       0.2129374 , 0.7956213 , 0.1752047 , 0.1582526 , 0.12375589,
       0.31694221, 0.17515561, 0.22936445, 0.1486895 , 0.6166803 ,
       0.18702377, 0.22026436, 0.17358933, 0.26178536, 0.3171563 ,
       0.29085717, 0.3273245 , 0.2755678 , 0.45644218, 0.2333666 ,
       0.16704562, 0.52594066, 0.46140194, 0.33188245, 0.1588568 ,
       0.17992543, 0.21595638, 0.15336746, 0.8721217 , 0.16996062,
       0.553846  , 0.16187425, 0.22180127, 0.11692591, 0.2097815 ,
       0.3956696 , 0.31727266, 0.25947145, 0.18933702, 0.25601497,
       0.476289  , 0.49965775, 0.20138729, 0.4479548 , 0.48307762,
       0.3721851 , 0.4594693 , 0.761758  , 0.22489387, 0.21490973,
       0.5021997 , 0.3645687 , 0.22986756, 0.13222551, 0.5297741 ,
       0.23939635, 0.21050657, 0.14594898, 0.1512152 , 0.6837166 ,
       0.11092097, 0.18863831, 0.40512046, 0.42900392, 0.36711264,
       0.21674785, 0.11713409, 0.34168723, 0.2784287 , 0.33855432,
       0.29216686, 0.28842875, 0.5180436 , 0.22490121, 0.34459496,
       0.138979  , 0.27847126, 0.2424017 , 0.61003065, 0.30284712,
       0.41429555, 0.19246404, 0.32799578, 0.5361469 , 0.14354824,
       0.1494036 , 0.29885885, 0.1832002 , 0.19161281, 0.1576705 ,
       0.20509902, 0.39408407, 0.48264402, 0.21524976, 0.22741012,
       0.2801558 , 0.37701645, 0.23983455, 0.1686174 , 0.28609657,
       0.1645184 , 0.32599455, 0.4325785 , 0.31219926, 0.2579033 ,
       0.11952535, 0.16787258, 0.17303309, 0.2744439 , 0.55843323,
       0.21350579, 0.1925748 , 0.46634638, 0.26418507, 0.27257025,
       0.2984882 , 0.13940164, 0.17894575, 0.47545916, 0.34300476,
       0.43594044, 0.15101714, 0.13617317, 0.25363892, 0.3527952 ,
       0.14643542, 0.17472601, 0.24382977, 0.4778641 , 0.2652454 ,
       0.19606711, 0.12193125, 0.19731463, 0.5847804 , 0.10984242,
       0.12646814, 0.24619569, 0.20129566, 0.25257212, 0.14233164,
       0.18522349, 0.22768973, 0.16522448, 0.22475344, 0.18166809,
       0.19998178, 0.20435338, 0.2674952 , 0.11508762, 0.6569546 ,
       0.3375383 , 0.2406117 , 0.33127823, 0.19279051, 0.12987652,
       0.9920621 , 0.5100264 , 0.13582544, 0.34859288, 0.2869394 ,
       0.15299284, 0.20804456, 0.25722194, 0.19902329, 0.195648  ,
       0.32753035, 0.36835638, 0.27860594, 0.26531002, 0.21802695,
       0.25969964, 0.19939174, 0.17287908, 0.26248246, 0.2167447 ,
       0.31387717, 0.26679546, 0.17099775, 0.24451014, 0.15552989,
       0.13391659, 0.25309318, 0.3027612 , 0.3238974 , 0.38645583,
       0.5266845 , 0.31491536, 0.204963  , 1.0434564 , 0.16490978,
       0.3282859 , 0.32996368, 0.17529997, 0.63337725, 0.30130625,
       0.1977617 , 0.27329698, 0.37837994, 0.52846235, 0.16984591,
       0.4764526 , 0.29117304, 0.37667325, 0.51787096, 0.26568347,
       0.25220177, 0.11387261, 0.31166452, 0.55651075, 0.28675142,
       0.20334831, 0.32708827, 0.43762502, 0.1668796 , 0.30540243,
       0.1576743 , 0.1856302 , 0.14041649, 0.29657778, 0.30809575,
       0.24330208, 0.24472523, 0.16511416, 0.13010156, 0.32871705,
       0.40759385, 0.23141292, 0.2703712 , 0.6574455 , 0.30190098,
       0.2928263 , 0.2699482 , 0.19016148, 0.33144122, 0.20566244,
       0.12987432, 0.74194485, 0.4115894 , 0.14832477, 0.22032642,
       0.19966055, 0.40409857, 0.26866868, 0.49721593, 0.09779017,
       0.16331562, 0.12744978, 0.16286856, 0.26699507, 0.19312571,
       0.1239199 , 0.24802937, 0.35834223, 0.4412545 , 0.3292445 ,
       0.4841044 , 0.29726622, 0.51342326, 0.27125412, 0.1765007 ,
       0.3031764 , 0.2949185 , 0.15072197, 0.28204677, 0.19416745,
       0.43826136, 0.39386743, 0.10483894, 0.20412414, 0.288678  ,
       0.15428708, 0.22863778, 0.40861046, 0.36297572, 0.40666306,
       0.3180101 , 0.1693549 , 0.23551533, 0.17907   , 0.49494535,
       0.33725762, 0.32756427, 0.36779928, 0.3063673 , 0.13479644,
       0.30498317, 0.20354147, 0.19031768, 0.39319184, 0.22391887,
       0.21350661, 0.27946544, 0.14402361, 0.21180132, 0.13226478,
       0.30920127, 0.13857017, 0.12114736, 0.20112728, 0.13986325,
       0.24093287, 0.29205802, 0.21061468, 0.4015134 , 0.25528255,
       0.16928385, 0.19536138, 0.1919796 , 0.23590045, 0.13540001,
       0.25143787, 0.23190445, 0.1469594 , 0.13495447, 0.26035324,
       0.2160059 , 0.31227803, 0.19199301, 0.15125196, 0.1313343 ,
       0.18932547, 0.48013037, 0.2643711 , 0.23579323, 0.41976672,
       0.24741833, 0.6307118 , 0.21226078, 0.12582664, 0.15609835,
       0.21899648, 0.23454472, 0.18820782, 0.18396139, 0.22602308,
       0.426193  , 0.44047087, 0.37953106, 0.2565737 , 0.4371103 ,
       0.23249392, 0.22693677, 0.12937108, 0.3646516 , 0.42240155,
       0.45620096, 0.20198569, 0.13013378, 0.25809842, 0.21847695,
       0.23846805, 0.51237124, 0.23640223, 0.10764558, 0.21751405,
       0.16680053, 0.3102083 , 0.1162494 , 0.23075467, 0.09093373,
       0.33733276, 0.15329468, 0.16036081, 0.31381685, 0.25143856,
       0.19052595, 0.3597273 , 0.30020076, 0.32541838, 0.59224945,
       0.20758772, 0.13117969, 0.27236986, 0.17171602, 0.16900231,
       0.12285271, 0.8399193 , 0.46202788, 0.55849427, 0.11215287,
       0.3447369 , 0.37091693, 0.2752352 , 0.21153146, 0.37730968,
       0.51145554, 0.35587153, 0.22232309, 0.3604375 , 0.5280113 ,
       0.14238271, 0.35410014, 0.24587871, 0.3976774 , 0.13081045,
       0.20463748, 0.13304581, 0.13171747, 0.25143906, 0.27343923,
       0.10514037, 0.18338941, 0.1197328 , 0.27829075, 0.28897446,
       0.10169787, 0.27174968, 0.34036815, 0.5768156 , 0.28841636,
       0.18133469, 0.1429977 , 0.15901104, 0.4890005 , 0.31790337,
       0.21377274, 0.17035304, 0.31235677, 0.38091245, 0.22539783,
       0.40468052, 0.3512497 , 0.17427787, 0.23494174, 0.3247389 ,
       0.3230113 , 0.31958875, 0.68660897, 0.20614491, 0.12864587,
       0.17541261, 0.46560943, 0.1969616 , 0.5619669 , 0.21029294,
       0.23031506, 0.19383466, 0.28996363, 0.27339295, 0.12654682,
       0.14856522, 0.4793813 , 0.25097552, 0.14663346, 0.33788162,
       0.36853173, 0.22926123, 0.13865049, 0.17458937, 0.22550929,
       0.14101109, 0.28257588, 0.557103  , 0.25407782, 0.19299339,
       0.28176975, 0.5423198 , 0.33207634, 0.146326  , 0.31873265,
       0.11286546, 0.23751107, 0.23472737, 0.28376696, 1.5968031 ,
       0.3598623 , 0.13660933, 0.3825328 , 0.17781998, 0.1650783 ,
       0.3854228 , 0.35126185, 0.20951699, 0.35881224, 0.22971101,
       0.36428067, 0.22970209, 0.20688409, 0.15795362, 0.29689065,
       0.24196936, 0.34401667, 0.19925405, 0.22926356, 0.46387318,
       0.10752717, 0.3101858 , 0.18065391, 0.16319644, 0.270694  ,
       0.29419702, 0.16703403, 0.3174457 , 0.62953156, 0.23419349,
       0.20588087, 0.19035369, 0.5395955 , 0.27152133, 0.2552084 ,
       0.20714946, 0.22273476, 0.17721176, 0.13035013, 0.17866428,
       0.19170024, 0.12742159, 0.12568532, 0.18821599, 0.3067346 ,
       0.2365367 , 0.3708848 , 0.24434233, 0.4566577 , 0.23944685,
       0.3841181 , 0.13836937, 0.25195283, 0.1479856 , 0.22022344,
       0.37444052, 0.12937614, 0.2647801 , 0.23966908, 0.1685018 ,
       0.24510317, 0.48626697, 0.22155905, 0.16398813, 0.3200977 ,
       0.22315209, 0.25963038, 0.38098818, 0.19360521, 0.76287633,
       0.9506443 , 0.17320538, 0.32388368, 0.15045898, 0.20500667,
       0.19747987, 0.2525529 , 0.19495812, 0.415757  , 0.19282268,
       0.2063601 , 1.3998202 , 0.10739302, 0.31676948, 0.34037274,
       0.16841188, 0.6864367 , 0.52752274, 0.18426898, 0.2919494 ,
       0.18975289, 0.15917046, 0.2889033 , 0.51367736, 0.23201528,
       0.20899104, 0.2695912 , 0.21506543, 0.28446802, 0.2029044 ,
       0.13866696, 0.23369493, 0.5337126 , 0.27047822, 0.5894192 ,
       0.31609446, 0.21776868, 0.3623926 , 0.50050986, 0.43078423,
       0.16527116, 0.45327908, 0.33685645, 0.40496317, 0.31441945,
       0.17057744, 0.3070658 , 0.18055427, 0.24525091, 0.2806236 ,
       0.12719649, 0.5151807 , 0.19851519, 0.37573564, 0.18669885,
       0.42031154, 0.82340205, 0.7984312 , 0.41478875, 0.21137942,
       0.23694561, 0.36979643, 0.21806237, 0.16419429, 0.2450925 ,
       0.14655282, 0.24091859, 0.1471008 , 0.15532853, 0.165999  ,
       0.27008292, 0.1720934 , 0.40801197, 0.16059214, 0.16983457,
       0.2889001 , 0.2587744 , 0.33736935, 0.29719332, 0.19921789,
       0.23671998, 0.3474087 , 0.16093512, 0.1164218 , 0.33983845,
       0.72996515, 0.25689143, 0.16942142, 0.2909144 , 0.27990764,
       0.14381662, 0.27731326, 0.11692319, 0.4245556 , 0.22120658,
       0.19980367, 0.3245268 , 0.39087006, 0.2424871 , 0.46251115,
       0.18354101, 0.15745418, 0.12308699, 0.3054619 , 0.1170264 ,
       0.13824277, 0.4818335 , 0.2776644 , 0.20211829, 0.39240542,
       0.11658745, 0.17061923, 0.20586899, 0.40994364, 0.13956967,
       0.23552164, 0.52945316, 0.3973451 , 0.215628  , 0.22828084,
       0.43372232, 0.1456647 , 0.11488569, 0.40055448, 0.39374024,
       0.41316995, 0.3380704 , 0.3832591 , 0.16713622, 0.2783175 ,
       0.17472683, 0.35369697, 0.17047511, 0.18417326, 0.39546993,
       0.22066595, 0.26001537, 0.15252842, 0.4811667 , 0.1830211 ,
       0.36699912, 0.1011003 , 0.28352347, 0.3014218 , 0.9905002 ,
       0.2475616 , 0.19919094, 0.4711692 , 0.262509  , 0.32200617,
       0.19632855, 0.32911405, 0.19500099, 0.23251434, 0.30075905,
       1.0425568 , 0.3416683 , 0.2912244 , 0.33415064, 0.16726936,
       0.4151589 , 0.27982208, 0.23781504, 0.16290434, 0.30593604,
       0.18418807, 0.18208091, 0.30904698, 0.9812191 , 0.15312426,
       0.4688866 , 0.3121231 , 0.297227  , 0.11761772, 0.21752228,
       0.5002187 , 0.21842854, 0.20766701, 0.2286831 , 0.1505595 ,
       0.23801832, 0.10520659, 0.56697965], dtype=float32), array([[[[-0.02128519],
         [-0.03686731],
         [-0.00660458],
         ...,
         [ 0.03272638],
         [-0.00437751],
         [-0.0076242 ]],

        [[-0.01150029],
         [-0.01634564],
         [ 0.01998456],
         ...,
         [ 0.02836754],
         [ 0.0188684 ],
         [-0.00196758]],

        [[ 0.0155095 ],
         [ 0.02003486],
         [-0.00633668],
         ...,
         [ 0.02368422],
         [ 0.0041005 ],
         [-0.01524591]]],


       [[[ 0.00240576],
         [-0.04152275],
         [ 0.0038816 ],
         ...,
         [-0.00500924],
         [-0.00771989],
         [-0.02539606]],

        [[ 0.0191659 ],
         [-0.04108683],
         [ 0.02095761],
         ...,
         [ 0.02155929],
         [-0.00625918],
         [-0.02244912]],

        [[-0.01616385],
         [-0.01487663],
         [ 0.04395294],
         ...,
         [ 0.01245823],
         [-0.01613875],
         [ 0.01051433]]],


       [[[-0.02496998],
         [-0.01710182],
         [ 0.04286888],
         ...,
         [ 0.04013282],
         [ 0.01889142],
         [ 0.00557645]],

        [[ 0.01154161],
         [-0.0239232 ],
         [ 0.02598443],
         ...,
         [ 0.00684655],
         [ 0.02126503],
         [ 0.00210374]],

        [[ 0.00353188],
         [-0.03840176],
         [ 0.01980092],
         ...,
         [-0.00910064],
         [-0.03570672],
         [-0.02741233]]]], dtype=float32), array([[[[-0.01450151, -0.00455657, -0.03540117, ..., -0.01155916,
           0.03325097,  0.04499133],
         [-0.01541857, -0.04792677,  0.02331698, ..., -0.03825199,
          -0.02282058,  0.01628052],
         [ 0.02766009,  0.03767964, -0.03698616, ..., -0.00338468,
           0.01523225,  0.01779917],
         ...,
         [-0.05533648,  0.00316054,  0.05648314, ...,  0.03477605,
           0.01405461, -0.00640838],
         [ 0.03161813, -0.0470271 , -0.06416192, ..., -0.02220522,
          -0.04876662,  0.05024942],
         [-0.03807226, -0.04478439, -0.03408203, ..., -0.04230258,
           0.03552895,  0.03475967]]]], dtype=float32), array([0.9926812 , 0.9949119 , 0.99946165, 1.0090439 , 1.0041982 ,
       1.0030981 , 1.0173159 , 0.9935758 , 1.0301455 , 0.98131806,
       0.9991136 , 0.9950457 , 0.99300885, 0.993457  , 0.99905944,
       1.0019482 , 1.0007199 , 0.9860573 , 1.0098264 , 1.0100355 ,
       0.99822587, 1.0085949 , 1.0180262 , 0.9966411 , 0.9949874 ,
       1.0069319 , 0.9922814 , 0.97834927, 1.0116557 , 1.0045898 ,
       0.9907912 , 0.9996137 , 0.99270856, 1.0031592 , 0.9825532 ,
       0.99876314, 0.99710965, 0.9917915 , 1.0079535 , 0.9863191 ,
       0.99134105, 0.9894979 , 0.9926036 , 0.9969753 , 0.99949527,
       0.9987873 , 0.985787  , 1.0063992 , 0.9966625 , 1.0032581 ,
       0.99547005, 0.98909694, 1.0045654 , 0.9938479 , 0.99486643,
       0.9984265 , 0.9957199 , 0.98644555, 1.0036511 , 1.0194672 ,
       0.99188566, 0.98676556, 1.0018485 , 1.0038545 , 1.0048332 ,
       0.9978595 , 1.0105846 , 1.0008218 , 0.9930071 , 1.0031439 ,
       0.9856123 , 1.0066072 , 1.0167552 , 1.0157439 , 0.9895193 ,
       1.0016633 , 0.99342716, 1.0123008 , 1.002294  , 0.9922812 ,
       1.0076828 , 1.0048463 , 0.9956673 , 1.0010128 , 1.0023023 ,
       1.012588  , 1.0056391 , 1.0214055 , 0.9955447 , 0.9851188 ,
       0.99868315, 0.9869285 , 0.9894227 , 1.0127484 , 1.0022624 ,
       0.98821205, 0.9927529 , 0.99301934, 1.0043709 , 1.0264615 ,
       0.99822325, 0.98868567, 1.0069674 , 0.98894566, 0.98839605,
       0.99845165, 1.0162181 , 0.99745756, 0.99370164, 0.9943819 ,
       1.0033075 , 0.9921688 , 0.99809057, 1.0111603 , 0.991608  ,
       0.987808  , 0.995344  , 0.99452263, 1.0014204 , 1.0071783 ,
       1.000166  , 0.9901261 , 0.9930569 , 0.99387157, 0.98914194,
       0.9856584 , 0.99277306, 0.9925912 , 0.9918164 , 0.9908993 ,
       0.98348075, 0.99430794, 1.0012606 , 1.0034096 , 0.99579746,
       1.0249758 , 1.0008557 , 0.99950945, 0.995974  , 0.9970289 ,
       0.98808646, 1.0120193 , 0.9919107 , 0.9954746 , 0.99286926,
       1.0098575 , 0.9977581 , 0.9893341 , 0.99668026, 0.99136865,
       1.0050743 , 0.9968617 , 0.99805534, 0.9981112 , 0.9967103 ,
       1.0012016 , 0.9918705 , 1.01768   , 1.0008861 , 1.0013856 ,
       0.9965537 , 0.9973441 , 1.0061513 , 0.9951663 , 1.0010481 ,
       1.0007508 , 0.98747224, 0.9950806 , 0.9923272 , 1.0127248 ,
       1.0002667 , 0.9873464 , 1.0238632 , 1.0031122 , 0.999012  ,
       1.0280113 , 0.99360913, 1.0092736 , 0.9816235 , 0.9956893 ,
       0.98697585, 0.9942377 , 0.99528456, 1.0060138 , 0.9914394 ,
       0.98945874, 0.98912513, 1.0007445 , 0.99586326, 0.9923967 ,
       0.9906222 , 1.0018948 , 1.0043672 , 0.99795246, 0.9912076 ,
       0.9971562 , 1.0073941 , 1.00207   , 1.0095447 , 1.0180894 ,
       0.99510443, 0.99309593, 0.9936866 , 0.99252397, 0.99712825,
       0.9874211 , 0.9969107 , 1.0177401 , 0.9942802 , 0.9983339 ,
       0.9952378 , 0.98137295, 0.9842976 , 1.0011708 , 1.0182558 ,
       0.9963317 , 1.002147  , 1.0066888 , 1.0033375 , 1.0106692 ,
       0.9967675 , 0.9943156 , 0.9845429 , 0.9843382 , 0.9932287 ,
       0.99660456, 1.0010458 , 0.99088883, 0.995065  , 0.9935299 ,
       1.0013342 , 0.9806523 , 0.9937964 , 0.9910789 , 0.98617756,
       1.0205427 , 1.0003463 , 1.0009694 , 1.0034494 , 0.9951954 ,
       1.0020773 , 0.9821875 , 1.0064838 , 1.0037304 , 0.9907505 ,
       1.0227103 , 0.98930174, 0.99091494, 0.98625743, 1.0127952 ,
       0.9930422 , 0.98809814, 1.0250827 , 0.99183077, 0.9976178 ,
       0.99828994, 0.9912614 , 1.0230228 , 0.996594  , 1.0016552 ,
       0.9914758 , 1.0017713 , 0.99072033, 0.99800307, 0.99192697,
       1.0037402 , 1.0060419 , 0.9959184 , 1.0371156 , 0.99815863,
       0.9994982 , 0.9901659 , 0.9856601 , 0.9922453 , 1.0165204 ,
       0.99589634, 1.0053086 , 0.9974806 , 0.97301763, 0.9985206 ,
       0.9947009 , 0.9903294 , 0.9917783 , 0.989363  , 1.0013974 ,
       0.9830324 , 0.9810227 , 0.99996525, 0.9984791 , 1.0001862 ,
       1.0105877 , 0.9959213 , 1.000791  , 1.0071111 , 0.99413204,
       0.9713699 , 0.98655784, 1.0186613 , 1.00028   , 0.98631835,
       0.99341106, 0.9991382 , 1.0112348 , 0.9867506 , 1.022474  ,
       0.9972437 , 0.9972967 , 1.0288678 , 0.9999025 , 0.99646306,
       0.99861026, 1.032824  , 0.9940499 , 0.9917955 , 0.9863431 ,
       0.9904725 , 0.9973413 , 0.99992883, 0.9950376 , 1.0106527 ,
       0.9916961 , 1.0020666 , 0.9997522 , 0.9874676 , 0.996749  ,
       0.9919172 , 1.0170442 , 0.99309975, 1.0072333 , 0.98697305,
       1.0154933 , 0.9921038 , 1.0012558 , 0.99857324, 1.0161024 ,
       1.0182652 , 0.9970225 , 0.9916209 , 0.9961332 , 1.0149342 ,
       1.006486  , 1.0055834 , 0.99660367, 1.0035874 , 0.99709857,
       1.000028  , 0.9960926 , 0.9967515 , 0.99559003, 1.0169666 ,
       0.9940581 , 1.0449777 , 1.0009456 , 0.9855456 , 0.9962676 ,
       1.0027491 , 0.99392414, 0.9961993 , 1.0026562 , 0.99633986,
       0.9989039 , 1.0057915 , 1.0051    , 0.9919749 , 0.99834746,
       1.0001711 , 0.9942791 , 0.99529517, 0.993382  , 0.98788   ,
       0.99398196, 1.0015898 , 1.0083336 , 0.99959177, 0.9914639 ,
       0.99223095, 0.9840971 , 1.0456136 , 0.9859615 , 1.0131385 ,
       0.99065685, 0.9876313 , 1.0054971 , 0.98915505, 0.99914914,
       0.9896413 , 0.9950819 , 0.9958346 , 1.0021557 , 0.9932242 ,
       0.99330014, 1.0008467 , 1.0037632 , 0.9888615 , 0.9957861 ,
       0.9910477 , 0.98995304, 0.99347705, 0.9874217 , 0.9935648 ,
       0.99438906, 0.9948499 , 0.9910874 , 0.99335104, 0.9932284 ,
       1.005604  , 1.0018045 , 0.9906749 , 0.99033767, 0.9913251 ,
       0.9963874 , 1.0059385 , 0.99610275, 0.9985819 , 0.9886541 ,
       0.99549264, 1.0069236 , 0.9901046 , 1.0121967 , 0.9967688 ,
       0.9961925 , 0.9948101 , 1.0177879 , 1.0140295 , 0.9887538 ,
       0.9992084 , 1.0066333 , 0.9978766 , 1.0372105 , 0.9944872 ,
       0.9978498 , 0.9958207 , 0.998067  , 0.991446  , 1.0046113 ,
       0.9933392 , 1.0136038 , 0.9939075 , 0.9915876 , 0.9940926 ,
       0.9945766 , 1.0324467 , 1.004495  , 0.99902797, 0.9986415 ,
       1.006124  , 1.0033596 , 0.9989658 , 1.0012568 , 0.9983429 ,
       0.99032056, 0.9966489 , 1.0012763 , 1.0074255 , 1.0084437 ,
       1.0115786 , 0.9937757 , 0.9883503 , 0.9978682 , 0.9954415 ,
       1.0189747 , 0.979006  , 1.0022906 , 1.0201422 , 1.0020161 ,
       0.9879466 , 0.99708337, 0.9753449 , 0.9960412 , 1.0085231 ,
       1.0247077 , 0.99532455, 0.9887078 , 1.0146176 , 1.0060669 ,
       1.0028639 , 1.0008227 , 0.9981209 , 0.9908864 , 1.0036995 ,
       1.006479  , 0.99463457, 0.9905142 , 0.996569  , 0.99025744,
       1.016772  , 0.9995385 , 0.9936443 , 0.98323524, 0.99350214,
       0.9956701 , 0.9977073 , 1.0040073 , 0.9995016 , 1.0018648 ,
       0.99567723, 0.9969476 , 0.9899805 , 1.0058608 , 1.0327784 ,
       1.0000373 , 0.99050844, 0.9888455 , 1.026099  , 0.9908876 ,
       0.9935692 , 1.0277379 , 0.98398846, 0.9889421 , 0.9962473 ,
       0.99255294, 0.9887651 , 0.99678785, 0.9941238 , 0.99696255,
       0.998738  , 0.9941656 , 0.99721944, 1.0114022 , 0.9949634 ,
       0.99719536, 0.9951645 , 0.9881749 , 0.99418944, 0.9960211 ,
       1.0163109 , 1.0057425 , 0.9924416 , 1.039098  , 0.9936086 ,
       1.0093082 , 0.99050856, 0.99366945, 0.9990488 , 0.9969886 ,
       0.99419737, 0.99313164, 1.0040447 , 1.0471085 , 1.0035226 ,
       0.9904408 , 0.98765224, 0.98571163, 1.0138065 , 0.99164075,
       0.9920183 , 0.99270064, 0.9970122 , 0.99317104, 0.9986763 ,
       0.9889588 , 0.9929389 , 0.99549496, 0.9968496 , 1.0070008 ,
       0.9984805 , 1.0050963 , 1.0014894 , 0.99162626, 0.9922694 ,
       0.9832745 , 0.99631417, 0.9957268 , 0.9981723 , 0.99563843,
       0.9932823 , 1.0007056 , 0.9951073 , 0.9945736 , 0.98848903,
       0.9860465 , 0.9945965 , 1.0051773 , 0.9923983 , 0.98677003,
       1.0056803 , 1.0004057 , 0.9805854 , 1.0174878 , 0.9887051 ,
       0.97618216, 0.9938138 , 1.0064703 , 0.9864515 , 0.99626243,
       0.9973953 , 0.9935987 , 0.9956704 , 1.0148593 , 1.0093806 ,
       0.9908288 , 1.0164906 , 0.99604857, 0.98845446, 0.9939903 ,
       0.9926561 , 0.99889785, 1.0185893 , 1.0047795 , 1.0038174 ,
       0.9880647 , 1.0057834 , 1.0242854 , 1.0005395 , 0.99345434,
       0.9921167 , 0.9872991 , 0.99726266, 1.0045463 , 1.0043999 ,
       0.98712003, 1.0167873 , 0.98846275, 0.9902891 , 0.98868257,
       0.9972145 , 1.01395   , 0.9882931 , 1.0187868 , 0.9875435 ,
       0.995497  , 1.0061462 , 1.0053222 , 1.0061705 , 1.019588  ,
       1.0017997 , 0.9998438 , 1.0049468 , 1.0181056 , 1.0153586 ,
       0.9899653 , 0.99772   , 0.98816556, 0.9935226 , 0.9963454 ,
       0.99791986, 1.007447  , 0.98780024, 0.98398393, 1.0066205 ,
       0.9968214 , 1.0029768 , 0.99655455, 1.0019302 , 0.9897213 ,
       1.0201758 , 1.0234311 , 1.0529606 , 0.9977823 , 0.99223566,
       0.99180657, 1.0195525 , 1.0075011 , 0.9973973 , 0.99722445,
       0.9996194 , 0.9889347 , 0.99834734, 0.99046886, 1.000444  ,
       0.9904141 , 0.9963309 , 0.99443597, 0.9922378 , 0.99660575,
       0.9957559 , 0.9935325 , 0.99045813, 0.9808649 , 0.9911917 ,
       1.0013123 , 1.0214486 , 0.9925803 , 1.0057837 , 1.0104204 ,
       1.0056093 , 0.9885906 , 0.9990854 , 1.007451  , 0.99495906,
       0.996088  , 1.0147092 , 0.9985214 , 0.9942055 , 1.0002716 ,
       1.0149661 , 0.99388593, 1.0046712 , 0.9956263 , 1.017956  ,
       1.0070269 , 1.0224897 , 0.9999046 , 0.9953703 , 1.0033745 ,
       1.0123774 , 1.0049976 , 0.9986661 , 0.9886394 , 0.99466467,
       1.0106978 , 1.0080997 , 0.9951544 , 1.002781  , 0.99274886,
       0.9950712 , 1.0447723 , 1.034336  , 0.9947221 , 1.0028883 ,
       1.0114089 , 1.0135262 , 0.99811256, 1.0017834 , 1.0252837 ,
       0.99561775, 0.9992516 , 1.0094436 , 0.9924633 , 1.0074337 ,
       0.9833533 , 1.0019042 , 0.9962753 , 0.98801684, 1.0314465 ,
       0.9961917 , 0.9954936 , 1.0167465 ], dtype=float32), array([-8.32601171e-03,  3.87718144e-04, -4.00062557e-03, -8.06578062e-03,
       -6.09999662e-03, -2.24504229e-02, -1.81608815e-02, -9.16517153e-03,
       -5.53183593e-02, -9.56776086e-03, -9.22748726e-03, -2.15812996e-02,
       -5.36799338e-03, -5.64972544e-03, -8.43615178e-03,  4.83120966e-04,
       -2.03297827e-02, -1.11336643e-02,  9.42523591e-03, -1.51701961e-02,
        1.66851971e-02,  2.00561900e-02,  2.85729524e-02,  2.41064909e-03,
       -8.97660665e-03, -9.34040919e-03, -1.76154615e-04, -1.13712996e-02,
        4.22865711e-03, -8.79882253e-04, -1.16453385e-02, -2.48100306e-03,
        7.49034050e-04, -1.23730125e-02, -4.00934648e-03, -8.27440235e-04,
       -8.26187339e-03, -2.39179693e-02,  2.09263712e-02, -3.49353440e-03,
       -6.95666764e-03, -1.63584724e-02, -4.93914867e-03, -4.69651120e-03,
        1.00758849e-02, -4.18734085e-03, -6.46119891e-03, -9.37719364e-03,
       -2.10611969e-02,  2.63756467e-03, -7.68813863e-03, -1.23061948e-02,
        3.19891796e-03, -1.55777261e-02,  1.46264536e-03,  8.12212995e-04,
       -2.28476524e-03, -9.09952540e-03, -3.53365508e-03, -4.63766567e-02,
       -1.67872086e-02, -1.62682384e-02,  1.23382118e-02, -6.86844904e-03,
        8.15824047e-03, -8.40377621e-03, -2.16057226e-02,  1.01654408e-02,
       -5.97180845e-03,  2.12130491e-02, -4.04228689e-03,  1.63320284e-02,
        1.04377521e-02,  2.25751400e-02, -3.22227888e-02, -5.10717556e-03,
       -8.67335591e-03,  3.17415595e-03, -4.63220105e-03, -6.27655163e-03,
       -5.35264388e-02, -1.48055358e-02,  7.03059090e-03,  6.21768471e-04,
       -1.30685112e-02,  5.02792699e-03, -2.28474718e-02, -1.18646007e-02,
       -7.10786646e-03, -1.42569337e-02, -1.11676264e-03, -5.02727553e-03,
       -8.21987516e-04,  2.32953373e-02, -3.63199017e-03, -1.04937106e-02,
       -1.50580779e-02, -1.07935062e-02,  6.15798449e-03,  7.08581461e-03,
       -3.79827544e-02, -1.80198066e-02,  6.87164953e-03, -9.73515399e-03,
       -7.54310470e-03, -1.47080263e-02,  4.82050149e-04,  1.55666461e-02,
       -5.24801156e-03, -2.04043277e-02, -2.87694559e-02, -9.41919256e-03,
        2.14240141e-02,  3.13435099e-03, -1.95583887e-03, -2.16961093e-02,
        1.65115821e-03, -1.84107330e-02, -1.54487547e-02,  9.76122392e-04,
       -9.81710292e-03, -6.51522726e-03,  3.22249066e-03, -6.02104748e-03,
       -8.30820017e-03, -1.07166292e-02,  1.28495885e-05, -7.02126371e-03,
       -9.07132216e-03, -7.22114416e-03, -5.89651382e-03,  1.98459509e-03,
        6.59473380e-03,  1.55591061e-02, -4.07116080e-04, -1.36081297e-02,
       -1.07616708e-02,  1.97933102e-03, -4.72091977e-03, -2.94222985e-03,
       -9.25075915e-03, -8.50183330e-03, -4.68023829e-02, -5.78606082e-03,
       -6.66904449e-03, -8.47283285e-03,  9.17642005e-03, -6.30789623e-03,
       -8.34738370e-03, -3.43794725e-03,  7.47821468e-04, -4.57568886e-03,
       -1.24319028e-02,  8.94954335e-03, -4.67845099e-03,  5.76330628e-03,
       -9.95096285e-03, -4.01729047e-02, -1.52404583e-03,  1.28656924e-02,
       -5.42020053e-03, -1.58677883e-02,  1.28786126e-02, -1.23693957e-03,
       -1.40603194e-02, -1.29124697e-03, -5.68462210e-03,  5.75041585e-03,
       -8.71630292e-03,  8.78995750e-03,  3.35155707e-03, -1.49220787e-02,
        7.12614600e-03,  6.40936149e-03,  9.10412869e-04,  4.07858826e-02,
       -1.42705739e-02,  1.08958697e-02, -1.19422963e-02, -2.33422797e-02,
       -4.80275694e-03, -3.89089342e-03, -8.10840819e-03,  2.41470945e-04,
       -5.27427765e-03, -9.01093241e-03, -7.34714791e-03, -1.76163334e-02,
       -2.21082737e-04, -1.01547902e-02, -7.15078134e-03,  9.37337987e-03,
        2.07024552e-02,  4.88006556e-03, -6.24992559e-03, -5.08617684e-02,
       -4.37103258e-03, -1.68947987e-02, -3.33127985e-03, -1.71401557e-02,
       -1.71406083e-02, -2.22937129e-02, -8.76149256e-03, -2.93549825e-03,
       -2.12021489e-02, -1.54001443e-02, -1.23710954e-03, -4.09129588e-03,
       -8.99399631e-03, -2.95714964e-03, -2.48137908e-03, -1.90203413e-02,
       -1.10501861e-02,  4.59832978e-03,  1.90786049e-02, -5.90589736e-03,
       -1.37311947e-02, -8.47113132e-03,  8.06398410e-03, -1.37628401e-02,
       -6.38701255e-04, -2.09382712e-03, -1.21006314e-02, -1.26444437e-02,
       -7.94377830e-03,  2.53223232e-03,  8.74618161e-03, -6.18677307e-03,
       -1.53113378e-03, -5.42509891e-02,  5.64526953e-03, -2.44418415e-03,
       -2.26698201e-02,  9.03629325e-03, -2.17264891e-02, -2.44399179e-02,
       -7.41151394e-03,  1.06487153e-02, -1.83259929e-03, -4.48346866e-04,
        1.11376401e-02,  6.63641095e-03, -3.13665122e-02,  4.90944181e-03,
       -1.39481742e-02,  1.02559617e-03, -1.33804455e-02, -6.98295934e-03,
       -8.57559871e-03, -3.94639187e-03, -1.25974650e-03,  2.23685801e-03,
        3.55812325e-03, -1.19374590e-02, -9.86711867e-03,  8.79059173e-03,
       -1.11348825e-02,  1.19035412e-02, -1.09301123e-04,  3.74970899e-04,
       -2.64323670e-02,  8.89201928e-03, -2.12978460e-02,  1.78521890e-02,
       -4.44320403e-03,  2.27176026e-03,  5.59108704e-03, -5.35890972e-03,
       -3.75812594e-03, -6.51925988e-03, -3.27178137e-03, -1.00519992e-02,
       -1.03872074e-02, -7.79136224e-03, -2.16588955e-02,  1.07215892e-03,
        8.33093747e-03,  5.17034251e-03,  1.01924753e-02, -5.87290945e-03,
       -3.65171046e-03,  4.32154723e-03, -9.36183333e-03, -1.86064690e-02,
        3.63100879e-03, -1.16664765e-03, -7.32113281e-03, -2.02527065e-02,
       -3.40508006e-04, -7.01012975e-03, -2.43838434e-03, -5.51688904e-03,
        8.98362487e-04, -4.68826853e-03,  7.35122012e-03, -1.60713550e-02,
        8.91591702e-03, -6.03931956e-03,  7.01567903e-03, -1.32090962e-02,
       -3.21404496e-03, -8.78694560e-03,  3.01142246e-03, -2.47976487e-03,
       -1.39895706e-02,  4.54783021e-03,  7.05617853e-03, -4.70773540e-02,
        2.32953532e-03, -5.46958297e-03, -4.54205908e-02,  2.69432180e-02,
        1.26294531e-02, -1.56857595e-02,  2.00968282e-03, -6.40894705e-03,
       -8.40870477e-03, -2.15315688e-02, -3.49316094e-03, -3.06395907e-03,
       -2.11331528e-02, -7.97903258e-03, -4.53378120e-03, -2.57383212e-02,
        2.33273677e-05, -7.48975016e-03, -2.47505009e-02,  6.77786244e-04,
       -6.92586647e-04, -1.15893548e-02, -1.73006821e-02, -1.57553740e-02,
       -1.19329942e-02,  1.05162268e-03, -2.76342724e-02, -3.59333009e-02,
        7.28139654e-03, -6.30576443e-03,  6.17109708e-06, -1.74956757e-03,
       -1.42911135e-03,  6.41336804e-03,  1.16803870e-02, -2.65420359e-02,
       -1.33896591e-02, -2.51361225e-02,  7.01553829e-04,  4.37369710e-03,
        1.54883266e-04, -3.54110338e-02, -2.19679549e-02, -4.86113355e-02,
       -9.33985226e-03, -8.24579503e-03, -5.01000369e-03, -1.93566382e-02,
       -1.70719884e-02, -7.94172287e-03,  4.73248959e-03,  4.73158172e-04,
       -3.86173814e-03, -3.73088159e-02, -1.43283214e-02, -1.92048326e-02,
       -1.37620978e-02,  6.50231028e-03,  3.25676333e-03, -3.41578270e-03,
       -1.47690140e-02, -9.60485637e-03,  6.91700901e-04,  6.01806073e-03,
       -9.70996043e-04, -4.46537398e-02, -2.03808490e-02, -8.11170507e-03,
       -2.75879633e-03, -3.01120151e-02, -1.34505806e-02, -1.56157948e-02,
        3.16573819e-03, -1.16182612e-02,  5.04042581e-03, -8.55049863e-03,
        1.12850023e-02, -7.73819955e-03, -1.90384965e-02,  1.28803384e-02,
       -2.08145753e-03, -9.18409880e-03, -5.24291396e-03, -3.09075462e-03,
       -2.88355481e-02,  7.21051730e-03,  1.89852761e-03,  1.42345706e-03,
       -1.82947912e-03, -6.07602205e-03, -1.73145793e-02, -5.19127073e-03,
        9.84044746e-03, -3.86606343e-03,  1.44201750e-03, -4.12474060e-03,
       -7.38860061e-03, -1.34585565e-02,  1.76120817e-03, -1.86373666e-02,
       -1.07015586e-02, -7.76710361e-03, -3.75979883e-03, -2.99399160e-03,
       -1.38632298e-04,  1.95681769e-03, -1.89959109e-02,  2.05024355e-03,
        8.12131912e-03, -7.78773241e-03, -3.57200243e-02,  2.83619761e-03,
       -7.29328487e-04, -8.97616986e-03, -2.22808961e-02,  1.01404646e-02,
       -1.47455093e-02,  1.16274273e-03,  1.40982512e-02, -5.73270908e-03,
       -8.50350596e-03, -3.95518504e-02, -9.85232927e-03, -2.46678852e-03,
        8.25421070e-04,  7.26398721e-05,  3.59739969e-03, -9.12754331e-03,
        7.02214986e-03, -5.77189354e-03, -8.54811259e-03, -1.69017946e-03,
       -1.80061744e-03,  1.97016913e-03,  1.19361840e-02,  1.81341893e-03,
        1.46970376e-02,  1.53026013e-02, -3.74487415e-03, -3.71948304e-03,
        3.88737838e-03, -8.10504705e-03, -1.18030030e-02, -1.34814791e-02,
       -1.64388902e-02, -3.70861106e-02,  1.33261681e-02,  1.62034836e-02,
       -3.98107339e-04, -5.07368473e-03,  1.12257414e-02, -9.84325353e-03,
        1.09451136e-03, -1.65170003e-02, -1.04709473e-02, -3.03302743e-02,
       -1.28623346e-04, -4.09780722e-03, -1.12938806e-02, -1.78517308e-02,
       -2.50593876e-03, -6.19694404e-03, -3.14023197e-02, -7.19709601e-03,
       -1.49881244e-02,  1.82814915e-02,  9.44722164e-03, -2.09526662e-02,
        1.62237172e-03, -2.19019083e-03, -2.48769484e-03,  1.33900263e-03,
       -1.98060218e-02, -1.06929615e-03, -9.39488411e-03,  1.00782458e-02,
       -1.50149018e-02, -3.98680083e-02, -2.54059285e-02, -5.61876362e-03,
        4.31093620e-03, -6.63087703e-03, -4.23468091e-03,  6.03879627e-04,
       -2.12091021e-02, -1.60777271e-02,  2.39370344e-03,  2.15643947e-03,
       -7.62185268e-03, -2.83225793e-02,  1.11165857e-02,  1.29584149e-02,
       -1.64292823e-03, -1.41389379e-02, -6.82643801e-03, -9.01894830e-03,
       -1.02094607e-02, -5.75747620e-03, -1.37701416e-02, -2.61901356e-02,
       -1.30383484e-02, -5.75846992e-02, -1.36175670e-03, -1.09833106e-02,
       -6.05670176e-03,  1.54664833e-03, -1.41346492e-02,  1.91873382e-03,
       -1.19192316e-03, -8.21058732e-03,  6.88490178e-03, -1.00909802e-03,
       -2.12581945e-03, -2.11274880e-03, -8.21861904e-03, -1.25785694e-02,
        9.09605529e-04,  1.33327767e-02, -1.23067410e-03, -1.79173925e-03,
       -9.16413963e-04, -1.71140805e-02, -2.16516890e-02,  8.98024155e-05,
       -4.91134636e-03, -5.83687564e-04, -1.86036490e-02, -1.06955087e-03,
       -1.58441458e-02,  1.45055111e-02,  1.30987400e-02, -1.79740228e-02,
       -2.65164636e-02, -7.47535191e-03, -5.11264615e-03, -2.30406458e-03,
       -4.78851702e-03, -1.07576726e-02, -9.60796233e-03, -2.45621707e-03,
       -8.80352221e-04, -5.58391679e-03, -6.24329690e-03, -4.55438113e-03,
       -7.30293151e-03, -1.46581894e-02,  2.33583935e-02, -4.85557914e-02,
       -1.02796396e-02,  8.70361808e-04, -7.49053713e-03, -9.52917058e-03,
       -1.77143198e-02,  4.30697389e-03, -2.61730375e-03,  7.04716193e-03,
       -1.18936393e-02, -1.11899350e-03,  3.03147361e-03, -1.22102425e-02,
        1.62383250e-03, -1.13800904e-02,  1.47823291e-02, -5.12466440e-03,
       -9.85677913e-03, -1.99863091e-02, -8.90226290e-03, -7.62720546e-03,
        3.00296512e-03, -2.30544172e-02,  2.47014943e-03, -9.67703015e-03,
       -1.22886309e-02, -2.84817419e-03,  9.84726846e-03,  3.52259749e-03,
        3.91605916e-03, -3.94618977e-03, -4.05753031e-03,  1.61182845e-03,
        2.65123951e-03, -1.68778952e-02, -2.97616725e-03,  5.55405533e-03,
        4.11565043e-03,  3.55681567e-03,  7.68136466e-03, -1.17990347e-02,
       -7.97855388e-03, -1.21562621e-02,  3.28080170e-03, -1.41084157e-02,
       -2.16538869e-02, -1.75163429e-02,  3.47757828e-03, -2.30785497e-02,
       -2.73516588e-02,  1.30912075e-02, -6.89363526e-03,  5.96732134e-04,
        1.48416813e-02,  6.85232971e-03,  9.12534073e-03, -1.34906452e-02,
       -1.17473891e-02, -8.76908004e-03, -1.65559836e-02, -7.13039935e-03,
        1.70833729e-02, -1.31153502e-04, -3.16060585e-04, -1.09849861e-06,
        1.44840619e-02, -1.07870772e-02, -4.69578132e-02, -3.09520047e-02,
        2.07681488e-03,  1.49746006e-03, -9.24083870e-03,  1.57689359e-02,
       -2.72901729e-03, -7.72872753e-03, -9.50749777e-03, -2.11014482e-03,
       -8.36810749e-03,  1.97509362e-05, -9.64670500e-04, -4.58107679e-05,
       -1.04325851e-02, -8.78320355e-03, -1.18554514e-02, -9.27199889e-03,
       -9.17091034e-03,  8.56134202e-03, -7.06570037e-03,  2.33014650e-03,
       -1.20689366e-02, -5.47047937e-03, -2.35689301e-02, -2.38706581e-02,
        8.89561139e-03, -4.74717049e-03, -9.45052877e-03,  8.35719146e-03,
        1.50825102e-02, -1.28241889e-02, -9.59659088e-03, -3.54878567e-02,
       -9.68047697e-03, -3.83746042e-03,  4.73073887e-04, -6.65599341e-03,
       -2.88264896e-03,  8.47588934e-04, -1.46935331e-02, -1.26280328e-02,
        5.68237575e-03,  6.23699185e-03,  2.30088306e-04,  5.35290176e-03,
       -1.61956847e-02, -1.42310606e-02,  3.94932507e-03, -4.96351272e-02,
       -2.26871367e-03,  1.01845078e-02, -5.54295431e-04, -1.29543047e-03,
       -2.48691533e-02, -2.24372814e-03,  2.21131109e-02, -3.62249557e-03,
        5.45679219e-03, -1.05776638e-02, -9.34797898e-03, -1.30387591e-02,
       -1.11507922e-02, -4.36345413e-02, -3.02638812e-03,  2.04464309e-02,
       -8.87523871e-03,  3.08075361e-02,  3.05083431e-02,  7.47039774e-03,
        2.39470247e-02, -9.80899762e-03,  1.45127792e-02,  3.77863017e-03,
       -1.58506557e-02,  2.83896254e-04, -1.27484584e-02, -1.12911323e-02,
        7.37431971e-03, -7.01082917e-03, -6.04904536e-03,  1.55884493e-02,
       -7.54793128e-03, -6.64552301e-03, -1.12840841e-02, -7.01512210e-03,
        3.34653049e-03, -3.46167083e-03, -3.27465720e-02,  1.14149489e-02,
        5.73355798e-03,  5.97111369e-03,  1.08495331e-03, -1.28833605e-02,
        4.01190424e-04, -1.84314027e-02,  3.01350025e-03, -2.08432358e-02,
       -8.64773337e-03, -1.94138510e-03, -8.99257045e-03, -1.78349335e-02,
        2.55900994e-02,  5.59209567e-03, -5.47923893e-03,  1.70524884e-02],
      dtype=float32), array([-5.94911538e-03, -2.35291142e-02, -2.51540393e-02,  2.22339686e-02,
       -9.60953254e-03,  3.57605629e-02,  4.59442139e-02,  1.76733676e-02,
        9.56308618e-02, -7.17408210e-03,  4.47033867e-02,  3.40536609e-02,
        5.03481785e-03,  1.54256972e-03,  1.95947066e-02,  4.73661013e-02,
        4.24269140e-02,  1.00298785e-02, -1.06754042e-02,  7.52242878e-02,
       -4.38349620e-02, -1.26790919e-03, -5.59860766e-02, -7.35988421e-03,
        7.49809155e-03,  3.87453437e-02, -6.82392297e-03,  2.67635239e-03,
        3.45166437e-02, -4.17283699e-02, -3.65404040e-02, -1.39033943e-02,
       -2.74540670e-02,  4.38002758e-02,  8.15250352e-03, -3.32927890e-02,
        6.17704354e-02, -5.12344874e-02, -5.24460599e-02,  9.39485058e-03,
        2.02683434e-02, -4.86321300e-02, -1.81491561e-02,  1.76347401e-02,
       -8.20737705e-03, -6.96882047e-03,  1.85478870e-02,  4.31796676e-03,
        6.44130632e-02,  1.09215511e-03,  1.38865001e-02, -5.62220300e-03,
       -3.28919329e-02,  2.82119643e-02, -6.70533068e-03, -4.79305275e-02,
       -1.22986641e-02, -7.68726645e-03,  3.93247791e-02,  6.99924529e-02,
       -4.62085456e-02, -9.68451705e-03,  4.52845581e-02, -9.32637695e-03,
       -2.35892162e-02, -1.05547095e-02,  3.98669839e-02, -1.19140828e-02,
       -3.51439342e-02, -4.77931499e-02,  3.53757525e-03, -8.75109248e-03,
        4.38448302e-02, -2.85825338e-02,  3.38477604e-02,  4.06775437e-02,
        5.04554100e-02,  1.36029832e-02,  2.11615637e-02, -3.15317791e-03,
        9.62627679e-02,  3.79454382e-02, -3.52475457e-02, -2.63275821e-02,
       -1.40236225e-02,  1.30194649e-02,  5.84504753e-02,  5.13698161e-02,
        1.11984788e-02,  9.19751637e-03,  4.74965498e-02,  1.42963175e-02,
       -3.37261930e-02, -2.57951748e-02, -3.59403007e-02,  5.66048082e-03,
       -1.05976062e-02,  4.95800339e-02, -4.11893465e-02, -1.25480130e-01,
        5.64161725e-02,  3.97011153e-02,  3.19480188e-02,  3.16075683e-02,
        3.89241576e-02,  3.93678993e-02, -4.47397754e-02, -4.84670959e-02,
       -1.18977558e-02,  2.74977274e-03,  8.67967606e-02, -8.45165644e-03,
        1.59070678e-02, -5.96285276e-02,  8.52140877e-03,  2.17471924e-02,
       -3.35943587e-02, -7.48337852e-03,  5.36713526e-02, -2.21331026e-02,
        3.93910706e-02,  9.03181080e-03, -4.04017046e-03,  3.06433402e-02,
       -2.43174043e-02, -3.63722630e-02, -1.69390738e-02, -9.31523927e-03,
       -1.14589510e-02,  1.63071640e-02, -4.84536914e-03, -1.48895634e-02,
       -8.58022366e-03, -2.80176755e-02, -2.75793485e-02,  5.33273518e-02,
        4.78949174e-02, -3.37242447e-02, -2.37356108e-02, -1.73111353e-02,
        1.76756065e-02, -3.60740013e-02,  6.17492162e-02, -2.55155582e-02,
        2.45433650e-03,  1.89710651e-02, -3.54702808e-02, -1.00070080e-02,
        2.90395669e-03,  2.28896402e-02,  8.74795765e-03, -3.66533138e-02,
        4.69045667e-03, -2.35818792e-02, -2.98866518e-02, -6.32663164e-03,
        8.80687591e-03,  5.82385138e-02, -2.00259872e-02,  8.59253481e-03,
       -5.42230755e-02,  2.63491441e-02, -7.72018451e-03, -4.13518324e-02,
        1.00749284e-02, -8.00545514e-03, -1.38143431e-02, -3.36134322e-02,
       -3.08155324e-02,  9.92103387e-03,  1.61092151e-02, -4.10558805e-02,
        3.20662782e-02,  9.86566860e-03,  5.74541185e-03, -2.54478008e-02,
       -2.04032492e-02,  2.75323223e-02,  6.39126962e-03,  6.14911690e-02,
       -2.47378983e-02, -2.44131088e-02, -1.04919225e-02,  2.63970066e-02,
        4.67203557e-03, -2.56792502e-03,  1.37832556e-02,  4.89752777e-02,
       -1.47212967e-02,  2.04168800e-02,  1.04271751e-02, -5.90803698e-02,
       -4.23477851e-02, -3.27395201e-02,  1.74928010e-02,  6.42419979e-02,
        4.14691940e-02,  3.30164582e-02,  1.95691213e-02,  7.32254684e-02,
        3.23813111e-02,  1.25465356e-02, -2.97799744e-02, -9.30724666e-03,
       -3.22809666e-02,  4.57717218e-02,  3.17312567e-03, -7.09892437e-02,
        1.20196287e-02,  1.99010856e-02, -4.31360304e-02,  3.12842126e-03,
       -2.33702511e-02, -2.40900386e-02, -1.52661689e-02, -1.84001718e-02,
        1.82693545e-02,  3.58048454e-02, -1.30368648e-02,  2.30447128e-02,
       -5.76009713e-02, -2.90663838e-02,  3.14040179e-03, -2.55192947e-02,
        2.78044865e-02, -1.00565897e-02, -1.29857818e-02, -2.67557404e-03,
       -4.76206094e-02,  6.72895014e-02, -1.37398485e-02, -3.62463817e-02,
        6.30776137e-02,  2.59098466e-02, -3.51041853e-02,  5.23001850e-02,
        1.54011762e-02, -3.43918055e-02, -3.15206572e-02,  2.46759653e-02,
       -4.35313508e-02,  3.01909689e-02,  3.15125175e-02,  7.90039450e-03,
        6.22406565e-02, -5.04571497e-02, -4.07605544e-02,  3.19990329e-03,
        2.60129403e-02, -2.23982036e-02, -6.42456673e-03, -4.21843044e-02,
       -2.55215187e-02,  2.29824372e-02,  4.23310250e-02, -3.96122076e-02,
        7.51910906e-04, -3.00219171e-02,  5.14895543e-02, -4.83597629e-02,
       -5.71857579e-02, -2.75600012e-02,  3.25257424e-03, -1.46152489e-02,
        4.64442708e-02, -3.34671512e-02, -4.05488759e-02, -1.19620319e-02,
        4.00065444e-02,  3.87977362e-02, -1.12922220e-02,  5.84011315e-04,
       -2.59726718e-02,  5.80241764e-03,  3.00585125e-02, -3.08102798e-02,
        6.27055531e-04, -4.09812070e-02,  3.07858866e-02,  2.47078147e-02,
       -3.19188237e-02, -5.73329031e-02,  3.51121537e-02,  3.33460234e-02,
       -5.36652952e-02, -3.89270857e-02,  6.48958310e-02,  2.38481052e-02,
        2.59452276e-02,  8.36465228e-03, -6.68639317e-03,  1.30136805e-02,
        3.28525156e-02,  6.02351055e-02, -1.55738154e-02,  5.31261526e-02,
        2.52944324e-02,  1.70288198e-02, -2.75547691e-02, -1.75504517e-02,
       -2.31132726e-04,  3.04643400e-02, -1.82917751e-02, -4.28290032e-02,
        6.12494834e-02,  1.90734304e-02, -2.45136749e-02,  5.48616834e-02,
       -4.10931706e-02,  9.49982496e-04,  4.63697389e-02,  5.04577421e-02,
       -4.94085848e-02,  2.57298257e-02,  2.56850608e-02, -4.06609476e-02,
       -2.02798340e-02,  4.98880036e-02,  5.22302650e-03,  1.85950398e-02,
        6.86744750e-02,  4.68894728e-02,  3.47097553e-02,  2.46555880e-02,
        1.55507298e-02, -5.00122793e-02,  6.95806816e-02, -3.86479311e-02,
       -3.22739370e-02,  4.14074287e-02, -8.70640762e-03, -2.87777446e-02,
        3.32039371e-02, -3.41005661e-02,  7.33175203e-02,  8.16564411e-02,
       -8.18997249e-03, -2.89746076e-02, -1.30099393e-02,  1.59269397e-03,
        1.80979762e-02, -1.89619008e-02, -3.75686064e-02,  3.23888138e-02,
        1.24630444e-02,  1.49125687e-03, -4.92963716e-02, -1.62391458e-02,
       -5.45621738e-02,  1.78090427e-02,  4.55404557e-02,  6.18376508e-02,
        3.81967612e-02, -8.47150479e-03,  1.15003455e-02,  3.09449024e-02,
       -1.84258018e-02,  1.55504439e-02, -2.19961125e-02, -1.44617129e-02,
        2.46811565e-02,  6.25412464e-02, -3.59934010e-02,  4.29085344e-02,
        5.52476533e-02, -4.68027964e-02,  3.52526344e-02, -4.26532365e-02,
       -2.02325918e-02,  2.31544543e-02, -1.31770298e-02, -2.61491146e-02,
        2.16158591e-02,  7.46532977e-02, -4.58838344e-02, -2.20915545e-02,
        9.59750207e-04,  7.86254853e-02, -3.05641051e-02, -4.50866334e-02,
       -2.82631516e-02,  2.53564976e-02,  1.77832227e-02,  7.43693393e-03,
       -4.21261638e-02, -1.70412790e-02,  3.01572140e-02, -2.56046373e-03,
       -9.16677713e-03,  3.58061790e-02,  1.05275568e-02,  4.89504449e-02,
       -3.31683680e-02, -2.59135365e-02, -3.02374437e-02, -3.57721262e-02,
       -3.97705883e-02,  9.73431952e-03,  4.76753386e-03,  4.70157806e-03,
       -5.38417175e-02, -1.24975266e-02, -3.49296555e-02,  1.76112726e-02,
        9.31095053e-03, -2.85709780e-02, -4.49700765e-02,  6.00393862e-02,
        3.40718478e-02,  2.30268613e-02, -1.83160265e-03,  4.06391360e-02,
        1.73586924e-02, -5.84546365e-02,  7.29075372e-02, -2.92190872e-02,
       -4.43300866e-02, -3.18620615e-02,  5.59645034e-02, -8.29918683e-03,
       -6.75666332e-02,  1.97021030e-02,  3.86318080e-02,  4.02606577e-02,
       -3.83816510e-02, -2.02056803e-02, -1.94275118e-02,  2.02407558e-02,
        6.18955791e-02,  4.38537784e-02,  5.65267988e-02, -3.29852812e-02,
       -3.01756896e-02, -1.26564912e-02, -3.59543934e-02, -1.25931464e-02,
       -1.48962876e-02,  2.90992986e-02, -2.32045278e-02,  1.42065985e-02,
       -1.76781067e-03,  4.37275041e-03, -1.12866750e-02, -3.65050919e-02,
       -1.28928917e-02, -1.66794993e-02, -2.12109834e-02, -3.87066975e-02,
        1.90575607e-02, -5.55410562e-03, -5.95898144e-02, -4.33400758e-02,
        4.01296541e-02,  5.40721528e-02, -1.16369473e-02, -5.09139933e-02,
        2.13201437e-02,  1.57285929e-02,  6.58073975e-03, -8.69860779e-03,
        2.59617474e-02,  2.75822543e-02,  1.29440613e-02,  5.72751276e-02,
        6.75283046e-03,  1.66536197e-02,  4.01193090e-02,  3.32832076e-02,
       -7.23978784e-03, -3.86809148e-02,  3.98245826e-02,  2.16460265e-02,
        1.44921141e-02, -2.63879895e-02, -3.91140133e-02, -5.37713356e-02,
       -1.17443502e-03,  2.19619018e-03,  7.63246696e-03, -1.22484064e-03,
        4.54638414e-02,  4.55816044e-03,  1.58342218e-03, -4.44715470e-02,
       -2.64901891e-02,  8.44858363e-02,  4.87743318e-02, -1.85761154e-02,
       -1.19961835e-02, -9.25826316e-05,  1.14996964e-02, -3.09729874e-02,
        1.47798052e-02,  2.46682968e-02, -2.26740260e-02, -6.18309155e-02,
        3.25589105e-02,  3.27373855e-02, -2.05027703e-02,  2.25474071e-02,
       -9.75624286e-03,  3.01085580e-02, -2.08222717e-02,  6.03209510e-02,
       -1.68382823e-02, -1.66375898e-02,  3.84786129e-02, -2.60340888e-02,
        1.34093233e-03,  8.17323700e-02,  7.89511763e-03, -2.35444549e-02,
       -6.58550207e-03,  2.73114163e-02,  3.28592062e-02,  1.08835585e-02,
       -4.16134521e-02,  2.15384215e-02,  1.51924761e-02, -9.35661793e-03,
       -8.54535401e-03, -1.69120282e-02,  4.62437272e-02,  2.51250006e-02,
       -1.52120171e-02, -5.87687492e-02, -2.34770663e-02,  2.33635176e-02,
        3.69770899e-02,  2.18070485e-02, -1.76093765e-02,  5.96548244e-03,
       -2.45469040e-03, -2.99322437e-02,  1.39412880e-02, -3.09321191e-02,
        1.28801484e-02, -3.02381255e-02,  4.20149975e-02,  1.36961425e-02,
       -3.42844874e-02,  1.69254038e-02, -4.67379056e-02,  1.83486268e-02,
       -1.68817695e-02,  1.58119388e-02,  7.15218065e-03, -5.49660213e-02,
        1.36127360e-02, -3.55324559e-02, -1.53656714e-02,  4.92127892e-03,
       -1.62231158e-02, -2.53414661e-02, -3.40518765e-02,  6.54945672e-02,
       -1.21031497e-02,  2.47679581e-03, -1.94164813e-02,  7.26024294e-03,
        2.01335233e-02, -5.23780212e-02, -6.34336798e-03, -4.21842076e-02,
       -1.94547474e-02, -3.27234901e-02, -4.54607569e-02, -4.94649541e-03,
       -3.01083759e-03, -3.47596779e-02, -2.75746491e-02, -1.15958611e-02,
        3.08225546e-02,  6.10961132e-02,  6.97542727e-03,  2.16429904e-02,
       -2.09168755e-02,  4.00262661e-02,  3.65114072e-03,  1.08434279e-02,
       -2.49256119e-02,  2.11437116e-03,  1.06498683e-02, -8.52132495e-03,
       -8.18204880e-03,  1.22494046e-02,  1.77040175e-02, -3.09594031e-02,
        2.15833522e-02,  1.45288324e-02,  4.65954607e-03, -9.81975440e-03,
       -2.80953199e-02, -3.95255312e-02, -7.02750459e-02, -2.41629612e-02,
        3.85700203e-02,  3.90017852e-02,  1.85548223e-03,  5.12785167e-02,
        1.72967054e-02,  5.47273122e-02, -2.94585824e-02, -6.67887434e-05,
        2.01968774e-02,  3.39147111e-04,  2.85335793e-03, -2.04054974e-02,
       -5.33184260e-02, -2.17382726e-03,  2.28983797e-02,  4.80294563e-02,
       -8.03631847e-04,  4.05550785e-02, -1.11725461e-02, -2.02701632e-02,
        3.60739566e-02,  1.96461789e-02, -6.87014358e-03, -2.79179960e-02,
       -6.04163706e-02,  1.53717240e-02,  6.13387376e-02,  7.04891533e-02,
        1.95915643e-02, -6.47615716e-02, -3.71274576e-02, -5.77192940e-02,
        3.11979037e-02,  2.68079340e-02, -3.29215899e-02, -2.81100720e-02,
        4.27230857e-02,  1.85199082e-02,  1.42549742e-02, -2.65012421e-02,
       -2.86732987e-02, -9.66777653e-03, -1.21179130e-02,  6.93371333e-03,
        6.83797821e-02, -2.04301178e-02,  3.46653499e-02, -4.39284258e-02,
       -2.08118837e-02, -1.76896732e-02,  3.92110720e-02,  6.28656000e-02,
       -2.13896427e-02, -4.75385264e-02,  4.13870402e-02,  2.89862212e-02,
       -1.36683965e-02,  3.49718109e-02,  4.15624566e-02,  4.09418531e-02,
        1.64968949e-02,  1.60359126e-02, -3.62891704e-02,  1.80818606e-02,
       -4.87321243e-03,  1.94004290e-02,  2.28595342e-02, -1.86506063e-02,
       -2.38150563e-02, -6.30259216e-02, -5.04018180e-02, -5.53197749e-02,
        4.02024873e-02, -3.08117252e-02, -4.92146648e-02,  3.54741924e-02,
       -1.99477002e-02, -7.76899513e-03, -1.02062859e-01, -8.77284352e-03,
        4.85206135e-02, -2.45384313e-03, -2.97564138e-02, -1.50609678e-02,
       -2.49125529e-02,  7.10313693e-02,  4.30315062e-02, -5.16405702e-03,
       -8.37174989e-03,  6.03487603e-02, -5.22970147e-02,  3.45935002e-02,
        7.87251722e-03, -1.18396692e-02, -3.07662878e-02,  2.87249722e-02,
       -2.12287661e-02,  4.14451025e-02, -1.70344189e-02, -3.34826298e-02,
        3.32883969e-02, -1.74571760e-02,  3.88314612e-02,  1.45669179e-02,
       -3.85063887e-02,  7.33796414e-03,  3.12748961e-02, -4.16036882e-02,
        4.03768308e-02,  1.04706688e-03, -5.32419840e-03, -8.15232377e-03,
        3.84470001e-02,  2.00075097e-02,  7.49173388e-02,  7.52385380e-03,
       -2.38451120e-02, -3.87101956e-02, -5.98266833e-02,  3.86596918e-02,
       -3.85725908e-02, -5.07624960e-03, -3.39525864e-02, -7.59845832e-03,
        3.88694054e-04,  2.61364300e-02,  7.61561329e-03,  2.35898402e-02,
        3.45288552e-02,  3.14484956e-03,  9.25253332e-03,  3.05130947e-02],
      dtype=float32), array([0.09725315, 0.09264137, 0.09063121, 0.08736832, 0.09309395,
       0.10001809, 0.09325016, 0.08583203, 0.10903405, 0.08766841,
       0.0944627 , 0.10307705, 0.08269528, 0.08511785, 0.09018461,
       0.11439949, 0.11368374, 0.08717685, 0.08666804, 0.09449846,
       0.08909005, 0.08534467, 0.09210219, 0.08468889, 0.08578502,
       0.08743022, 0.08366027, 0.08369306, 0.10297052, 0.09422143,
       0.10343345, 0.08859274, 0.09363474, 0.08870766, 0.08553061,
       0.10391858, 0.11239761, 0.10583349, 0.10900317, 0.08586272,
       0.08737422, 0.08896566, 0.11052118, 0.09224151, 0.08401932,
       0.09284052, 0.08362056, 0.08428853, 0.10084753, 0.08408701,
       0.089449  , 0.08619858, 0.08917367, 0.09298418, 0.08310321,
       0.09545761, 0.08373755, 0.08913008, 0.09843734, 0.13329563,
       0.11552636, 0.09053202, 0.09256303, 0.086791  , 0.1083578 ,
       0.11222759, 0.12001501, 0.09023458, 0.08763544, 0.1558857 ,
       0.08499531, 0.10553095, 0.09246749, 0.09689844, 0.09572295,
       0.09229324, 0.09349225, 0.0868763 , 0.08762465, 0.08293932,
       0.115886  , 0.09226014, 0.11530093, 0.09956799, 0.09639168,
       0.09456088, 0.11174799, 0.09929322, 0.08369549, 0.08491331,
       0.10363193, 0.08938786, 0.09784507, 0.08725069, 0.09191351,
       0.08264145, 0.08827208, 0.09573588, 0.09180776, 0.14618959,
       0.10894548, 0.09384678, 0.09060506, 0.09051782, 0.09210131,
       0.09256736, 0.1196814 , 0.08718984, 0.08313397, 0.08934328,
       0.13438259, 0.08693606, 0.08574415, 0.11668205, 0.08457993,
       0.09288432, 0.0862871 , 0.10771292, 0.11873471, 0.08467294,
       0.10529213, 0.08230794, 0.08764806, 0.08276673, 0.08903323,
       0.09442522, 0.08326339, 0.08653919, 0.08429316, 0.08244993,
       0.09813815, 0.08850008, 0.08494958, 0.08924226, 0.09000114,
       0.10142002, 0.09192486, 0.10013231, 0.08613267, 0.08501504,
       0.08778606, 0.10714885, 0.11020584, 0.08782236, 0.08868995,
       0.09453127, 0.09245607, 0.08581695, 0.08477712, 0.08776182,
       0.08331066, 0.08629296, 0.08222082, 0.0848739 , 0.09895638,
       0.08407755, 0.08693475, 0.10100821, 0.08529245, 0.08445062,
       0.0952312 , 0.08910356, 0.08457031, 0.12039817, 0.08470421,
       0.08440898, 0.08387437, 0.09776554, 0.08528996, 0.09099888,
       0.08366857, 0.0851595 , 0.09966239, 0.09108777, 0.08245232,
       0.1011567 , 0.1065575 , 0.09422009, 0.09042533, 0.12000003,
       0.09062915, 0.08859961, 0.08891573, 0.10225887, 0.08642749,
       0.0847725 , 0.08519588, 0.11078598, 0.08898734, 0.1026753 ,
       0.08540823, 0.10230672, 0.09276436, 0.09050436, 0.08451413,
       0.11507995, 0.08879651, 0.09095504, 0.08797507, 0.09615225,
       0.09481039, 0.09765521, 0.09640387, 0.08560289, 0.08810526,
       0.09155442, 0.08372422, 0.11156779, 0.08431899, 0.0999336 ,
       0.09092841, 0.08372881, 0.09706937, 0.09257457, 0.09058829,
       0.0911554 , 0.09692807, 0.09479734, 0.08793776, 0.09396121,
       0.11329793, 0.09021594, 0.08674034, 0.08530443, 0.08639775,
       0.08692493, 0.08687479, 0.08795124, 0.08745407, 0.12602156,
       0.08839986, 0.09004394, 0.10749372, 0.08348818, 0.09672064,
       0.1011048 , 0.08477207, 0.09119226, 0.10303029, 0.08810002,
       0.0870122 , 0.09272736, 0.09756708, 0.08309946, 0.10730246,
       0.12723139, 0.09374155, 0.08300699, 0.0913125 , 0.11589056,
       0.08745719, 0.09992716, 0.10921431, 0.08754379, 0.08854156,
       0.08971756, 0.08416536, 0.08662701, 0.10252215, 0.11354035,
       0.09441962, 0.08627132, 0.09834143, 0.0947872 , 0.09546987,
       0.09244817, 0.09075937, 0.08338645, 0.09737126, 0.09565493,
       0.08418122, 0.08605988, 0.08699281, 0.08591166, 0.10205997,
       0.1055906 , 0.08481628, 0.10268954, 0.08750101, 0.0929862 ,
       0.08659418, 0.09144756, 0.0893215 , 0.08753647, 0.0947637 ,
       0.09559843, 0.12031191, 0.08987252, 0.08741712, 0.0836771 ,
       0.10948431, 0.09124433, 0.09125667, 0.09505545, 0.08469899,
       0.10076757, 0.08975718, 0.09385504, 0.09607641, 0.08750997,
       0.0845971 , 0.09240533, 0.09252618, 0.09823988, 0.10248442,
       0.09241445, 0.0971535 , 0.1168104 , 0.09509386, 0.08237249,
       0.10677999, 0.09133703, 0.08796132, 0.09184071, 0.0886541 ,
       0.09061099, 0.08532857, 0.093374  , 0.09179719, 0.08647104,
       0.0935949 , 0.08802132, 0.0885272 , 0.09395237, 0.08571203,
       0.12361889, 0.10328378, 0.09171807, 0.10695444, 0.09079976,
       0.10730071, 0.08634883, 0.08623619, 0.09012933, 0.11406232,
       0.15307777, 0.08896458, 0.08454463, 0.08318727, 0.09454808,
       0.08491884, 0.10255893, 0.08635612, 0.09979257, 0.08583632,
       0.09939683, 0.09478183, 0.08447868, 0.09311555, 0.1021056 ,
       0.09878478, 0.11678417, 0.09900057, 0.08280828, 0.08515044,
       0.10213166, 0.08639693, 0.08367536, 0.08869505, 0.09634843,
       0.09002957, 0.10919491, 0.11618594, 0.09587717, 0.09037114,
       0.09878529, 0.09835657, 0.08901148, 0.08575818, 0.09028301,
       0.08410191, 0.09156589, 0.08931351, 0.12469648, 0.12050477,
       0.10147972, 0.08693346, 0.13109075, 0.08521894, 0.13644724,
       0.0911755 , 0.09088949, 0.10040895, 0.08471904, 0.09375056,
       0.08684225, 0.0918543 , 0.08986396, 0.08513478, 0.08929083,
       0.08785915, 0.12568729, 0.10170773, 0.09710506, 0.08564112,
       0.08341105, 0.09113532, 0.08386339, 0.08633363, 0.08261777,
       0.0951123 , 0.08278327, 0.08834479, 0.08400348, 0.08262021,
       0.08982148, 0.09899747, 0.09714273, 0.08361825, 0.08651668,
       0.08293689, 0.09570522, 0.08381414, 0.09857813, 0.13369733,
       0.08884948, 0.08914389, 0.08502406, 0.11070602, 0.0838581 ,
       0.09082781, 0.08474927, 0.09586995, 0.0965308 , 0.11082498,
       0.08652623, 0.10839608, 0.08424412, 0.10454623, 0.10112078,
       0.09898563, 0.09207176, 0.09123127, 0.08511665, 0.10195374,
       0.08345384, 0.0913267 , 0.08481744, 0.08502494, 0.08341534,
       0.08333217, 0.10192815, 0.09417592, 0.08737297, 0.08730529,
       0.09566408, 0.09381957, 0.08723027, 0.08514712, 0.08608617,
       0.09212963, 0.08597729, 0.10337481, 0.1030387 , 0.08729984,
       0.10029242, 0.08681442, 0.08433814, 0.08814319, 0.08593354,
       0.08933165, 0.09564041, 0.09800813, 0.09682249, 0.08647286,
       0.08449057, 0.08898506, 0.09110609, 0.09101134, 0.13355887,
       0.10145584, 0.0816482 , 0.08401362, 0.1110404 , 0.0904664 ,
       0.15792626, 0.09197085, 0.08574647, 0.09207597, 0.09422144,
       0.09959693, 0.08679882, 0.08226026, 0.09957553, 0.08525181,
       0.14445898, 0.13518865, 0.09220535, 0.09141635, 0.0856574 ,
       0.08536255, 0.08384867, 0.09442814, 0.09458321, 0.08731422,
       0.08946425, 0.09175078, 0.09253814, 0.08701776, 0.09304161,
       0.08610878, 0.08389466, 0.09762651, 0.10053984, 0.08501783,
       0.09090443, 0.10925405, 0.08792925, 0.09373   , 0.1176876 ,
       0.08562236, 0.08917367, 0.0895267 , 0.09804121, 0.09027542,
       0.08945542, 0.08779643, 0.08490824, 0.09149648, 0.08781153,
       0.08674204, 0.08805504, 0.09262348, 0.08884584, 0.08574087,
       0.10809816, 0.0990964 , 0.08734837, 0.09322672, 0.08571897,
       0.11588181, 0.0863786 , 0.08343781, 0.09769044, 0.09552602,
       0.09217355, 0.08648441, 0.09267179, 0.09226051, 0.08609236,
       0.10023943, 0.08508984, 0.09256467, 0.08355852, 0.08268104,
       0.08586974, 0.09061146, 0.09726232, 0.0880041 , 0.08861293,
       0.08767569, 0.08220895, 0.08605427, 0.08813137, 0.09942014,
       0.12406883, 0.11058078, 0.08925219, 0.08413535, 0.08426368,
       0.08716471, 0.09715132, 0.08283732, 0.10362516, 0.08592749,
       0.08792567, 0.0962798 , 0.08895311, 0.08926092, 0.08646645,
       0.09632144, 0.08362446, 0.09550849, 0.13530102, 0.08600402,
       0.08637175, 0.09155785, 0.09172159, 0.09774652, 0.08601162,
       0.08344015, 0.08554868, 0.09092211, 0.08979124, 0.08518009,
       0.08967728, 0.09604634, 0.085221  , 0.08713908, 0.08889446,
       0.08471031, 0.08720664, 0.08836237, 0.09248751, 0.11532559,
       0.08423676, 0.09716114, 0.10021846, 0.0875395 , 0.0968513 ,
       0.08988392, 0.11138778, 0.09983051, 0.09403037, 0.0990606 ,
       0.08583228, 0.08568681, 0.08587763, 0.1213717 , 0.08402496,
       0.08372143, 0.09602463, 0.08440179, 0.08780468, 0.08958019,
       0.08429778, 0.09214488, 0.08997797, 0.08933835, 0.08664766,
       0.11132105, 0.09071326, 0.11993358, 0.10545842, 0.09657268,
       0.09932793, 0.10366103, 0.09789742, 0.09987087, 0.09602018,
       0.0864516 , 0.08654989, 0.09259252, 0.08295081, 0.08971059,
       0.09188599, 0.11994743, 0.08423885, 0.08668572, 0.09888756,
       0.10679118, 0.08764579, 0.08993528, 0.10235848, 0.08317607,
       0.10321326, 0.09901302, 0.10810211, 0.09791246, 0.10061544,
       0.09636854, 0.08727299, 0.08578636, 0.09129233, 0.09260579,
       0.09767658, 0.09120779, 0.09183849, 0.11216758, 0.09661518,
       0.08178718, 0.08296655, 0.08652691, 0.08386271, 0.08392956,
       0.10227881, 0.10336313, 0.09374921, 0.09253389, 0.09078482,
       0.09852937, 0.0981876 , 0.08363602, 0.09448463, 0.13148618,
       0.08266212, 0.09651615, 0.08274344, 0.10198475, 0.09421746,
       0.08801154, 0.11814662, 0.0897961 , 0.0956862 , 0.08595563,
       0.1186685 , 0.08442582, 0.09244468, 0.09128308, 0.08920372,
       0.10595246, 0.09336115, 0.09533581, 0.08908611, 0.09175023,
       0.09220007, 0.08624857, 0.08513088, 0.09437448, 0.08456443,
       0.08682136, 0.09521502, 0.09082476, 0.10363171, 0.08843693,
       0.08381467, 0.11757492, 0.10285071, 0.09166098, 0.08661621,
       0.12762645, 0.09544417, 0.0954228 , 0.08895806, 0.11502355,
       0.09214204, 0.1014009 , 0.10853974, 0.09958234, 0.09735352,
       0.085733  , 0.088264  , 0.08276512, 0.08843715, 0.09175746,
       0.08957347, 0.08847237, 0.09543208], dtype=float32), array([[[[-0.0376824 ],
         [ 0.01880074],
         [ 0.02767923],
         ...,
         [ 0.0044116 ],
         [-0.00935979],
         [ 0.01125882]],

        [[-0.01510424],
         [ 0.00592392],
         [ 0.01393557],
         ...,
         [ 0.00348633],
         [ 0.00866397],
         [-0.01766415]],

        [[-0.02786038],
         [ 0.00932509],
         [ 0.01216884],
         ...,
         [-0.01167265],
         [-0.00764167],
         [ 0.01749228]]],


       [[[ 0.00967097],
         [-0.00106257],
         [ 0.02145427],
         ...,
         [ 0.03310584],
         [-0.02994897],
         [-0.0232435 ]],

        [[ 0.01308542],
         [ 0.01871017],
         [ 0.01458963],
         ...,
         [-0.0266655 ],
         [-0.02788752],
         [-0.02370832]],

        [[ 0.01097371],
         [ 0.01074911],
         [-0.0065611 ],
         ...,
         [ 0.00308471],
         [-0.00103087],
         [-0.0329767 ]]],


       [[[-0.00748974],
         [-0.01865344],
         [ 0.02366376],
         ...,
         [ 0.02448405],
         [ 0.00032813],
         [-0.03527988]],

        [[-0.01364007],
         [-0.03549372],
         [ 0.00568118],
         ...,
         [ 0.02670919],
         [ 0.01005392],
         [-0.00365805]],

        [[ 0.02269938],
         [ 0.00151194],
         [-0.02819564],
         ...,
         [-0.01854972],
         [ 0.01958499],
         [ 0.01121697]]]], dtype=float32), array([[[[-0.02654539, -0.03477568, -0.07281887, ...,  0.04012911,
          -0.00334031, -0.02169107],
         [ 0.01993058,  0.00302281, -0.01832249, ...,  0.03222639,
          -0.00496013,  0.02023077],
         [ 0.03360159,  0.00776249,  0.02886486, ...,  0.03347096,
          -0.01830711,  0.05857304],
         ...,
         [-0.06484719,  0.00376868, -0.02916679, ..., -0.02797321,
          -0.03523457, -0.04323223],
         [ 0.00375415,  0.03321843,  0.0715259 , ..., -0.00687081,
          -0.0277093 ,  0.03489756],
         [-0.01547358, -0.01849549, -0.01230526, ..., -0.0095196 ,
          -0.01091854,  0.00774416]]]], dtype=float32), array([0.99051684, 0.9970145 , 0.99592483, 1.0018779 , 1.0001907 ,
       0.99719507, 1.0000465 , 0.9738121 , 1.002098  , 1.012195  ,
       0.9964642 , 0.9928009 , 1.017888  , 1.0478948 , 0.9838102 ,
       1.003336  , 1.0113224 , 1.0109835 , 1.0588613 , 1.0027821 ,
       1.0046338 , 1.0056871 , 1.002477  , 0.9955364 , 0.9963202 ,
       1.0072001 , 0.99918014, 0.9960592 , 1.0120643 , 1.0095942 ,
       0.9911567 , 1.0190021 , 1.0097675 , 0.992493  , 0.99873173,
       1.0244325 , 1.0135798 , 1.0028199 , 1.012708  , 1.0114869 ,
       0.9917045 , 1.0134872 , 1.0235409 , 0.99520314, 1.0028073 ,
       0.9932095 , 1.0018868 , 0.9817618 , 1.0199554 , 1.0345205 ,
       1.0332937 , 1.0063004 , 1.0187902 , 0.99490523, 1.0368901 ,
       1.0053271 , 1.0404705 , 1.0111052 , 0.99801815, 1.0000026 ,
       0.983337  , 0.9965265 , 0.9824387 , 0.9945754 , 1.0001322 ,
       0.99518824, 1.0207711 , 0.9882808 , 1.0135765 , 0.9874919 ,
       1.0089366 , 1.0023683 , 1.0059708 , 1.0056822 , 1.0158117 ,
       1.0066178 , 1.0018528 , 0.98765117, 0.9954445 , 0.9884116 ,
       1.0091863 , 1.0068982 , 1.00989   , 1.0008721 , 1.016954  ,
       0.9919269 , 0.99065655, 0.99962455, 1.0125554 , 1.0196534 ,
       1.0149997 , 0.9986762 , 1.0066601 , 1.0000728 , 0.99144673,
       0.9903579 , 0.9998054 , 1.0066869 , 1.0023029 , 1.0245638 ,
       1.0221317 , 1.0014222 , 0.984215  , 0.9969512 , 1.0142668 ,
       1.0102255 , 0.9948909 , 0.9967486 , 1.0002507 , 1.0361383 ,
       1.0056956 , 0.9871843 , 0.99386144, 1.0092796 , 1.0036947 ,
       0.9845998 , 0.9944444 , 1.0024326 , 1.0054904 , 1.0000585 ,
       0.99862653, 1.0035173 , 1.0088081 , 1.0001681 , 1.0135877 ,
       0.99535215, 0.98852354, 0.98778266, 1.0096245 , 0.9945873 ,
       1.0022757 , 1.0131438 , 1.0091307 , 0.99653316, 1.0075145 ,
       1.011156  , 1.0031365 , 1.0175395 , 1.0075289 , 1.0025879 ,
       1.017273  , 0.99896497, 1.0021511 , 0.9804749 , 1.007075  ,
       1.0142205 , 1.0026507 , 0.98481375, 1.0062364 , 1.0006353 ,
       0.9924664 , 1.0094306 , 0.99723506, 1.0116898 , 1.0021695 ,
       1.0060055 , 0.99734414, 0.99054694, 0.9931229 , 0.9876891 ,
       0.99735844, 0.9881042 , 0.9992788 , 0.98043174, 0.99569064,
       1.0262544 , 0.9980611 , 0.99974364, 0.9894131 , 1.0037476 ,
       0.9830628 , 0.9967725 , 1.0100657 , 0.99506474, 0.9863754 ,
       1.0188279 , 0.9991057 , 1.018106  , 0.9891792 , 0.99125093,
       1.0043207 , 1.0107133 , 1.0007414 , 1.010207  , 0.9990719 ,
       0.99501103, 0.9474542 , 0.9942196 , 1.0017294 , 1.011206  ,
       1.0124495 , 1.0034736 , 0.9956775 , 1.0023206 , 1.010575  ,
       0.9815523 , 1.0081831 , 1.0032079 , 0.9661173 , 0.9996329 ,
       0.9974041 , 1.0035152 , 1.0243967 , 1.0131804 , 0.9970239 ,
       0.9986269 , 1.0081074 , 0.9779329 , 1.0146756 , 0.99934816,
       1.0002624 , 1.0019758 , 0.9904441 , 0.998104  , 1.0051532 ,
       0.9945109 , 0.9784406 , 1.0101004 , 1.005796  , 1.014198  ,
       1.0234126 , 1.001669  , 1.0006787 , 0.99102765, 1.0239483 ,
       0.99299264, 1.0122266 , 1.0078019 , 0.999303  , 1.0423341 ,
       1.0177307 , 1.0092341 , 0.99739784, 1.0318328 , 0.99193144,
       0.9972659 , 0.9993599 , 0.9840075 , 1.0265404 , 1.0067923 ,
       1.0011879 , 1.0240201 , 0.9983339 , 0.98930067, 0.99736476,
       1.0160701 , 0.9882468 , 0.9811126 , 1.0086968 , 1.0260788 ,
       0.9955902 , 0.9946529 , 0.98401296, 0.99922746, 1.031461  ,
       1.0021749 , 0.9977892 , 1.009499  , 1.0334946 , 0.9986824 ,
       0.997106  , 0.99825436, 0.9994319 , 1.0313333 , 0.98519534,
       1.0173469 , 0.9995558 , 0.9812776 , 1.0013103 , 0.99171937,
       1.0228224 , 0.98573524, 1.0031403 , 1.0109612 , 1.0163134 ,
       1.0033088 , 1.0055172 , 1.0135417 , 0.9985273 , 1.0056429 ,
       1.0129868 , 1.0039831 , 0.9926009 , 0.996845  , 1.0014951 ,
       1.0061753 , 0.9928791 , 0.9986529 , 1.0245408 , 0.9886455 ,
       1.0021505 , 1.0000706 , 0.9930918 , 0.9933274 , 0.9918858 ,
       0.9908182 , 1.0121703 , 1.0180774 , 1.0106732 , 0.9959705 ,
       1.0040126 , 1.005006  , 0.9914575 , 1.0019053 , 0.98070025,
       0.9989182 , 1.0036609 , 1.0043911 , 0.9896057 , 0.9926731 ,
       1.0040693 , 1.0064548 , 1.0012357 , 1.0134104 , 0.9972995 ,
       1.0115465 , 1.0028119 , 1.0097495 , 1.0281892 , 0.99639827,
       0.9944009 , 0.99974656, 0.9986298 , 0.99645394, 1.0024861 ,
       1.0007981 , 0.97460634, 1.0077298 , 0.9968029 , 1.001469  ,
       1.0327746 , 1.0003972 , 1.0238667 , 0.99998635, 1.0094125 ,
       1.0158964 , 0.99840224, 1.0176622 , 1.0098644 , 0.9958929 ,
       0.9742028 , 0.99819523, 1.0167927 , 1.0009233 , 1.0072455 ,
       0.99846995, 0.99639   , 1.0274762 , 1.0097408 , 0.9953556 ,
       0.98706245, 1.0112629 , 0.99459946, 1.0126598 , 0.98561025,
       1.0015944 , 0.9804389 , 1.0029    , 1.0015709 , 0.98499674,
       1.0200156 , 1.0186244 , 1.0066742 , 1.0207789 , 0.9906269 ,
       1.003203  , 0.980859  , 1.0155623 , 0.9975922 , 1.0088065 ,
       1.0407957 , 0.9888477 , 0.9991809 , 1.0022736 , 1.0053074 ,
       1.0101225 , 0.9997427 , 1.0075433 , 1.0104328 , 0.9887854 ,
       1.0111159 , 0.995088  , 0.9988894 , 0.9938412 , 1.010573  ,
       0.97409785, 1.0080165 , 0.9893008 , 1.0051692 , 1.0203414 ,
       1.0232888 , 0.9974338 , 0.992075  , 0.988699  , 0.99688953,
       1.0328101 , 1.0150963 , 1.0116992 , 1.0031087 , 0.9798394 ,
       0.9809465 , 0.9763218 , 0.99320656, 1.003475  , 1.0163871 ,
       0.9984917 , 1.0126928 , 0.99629104, 0.9780634 , 0.9975865 ,
       1.0093782 , 1.0031046 , 1.0033755 , 0.99522436, 0.9970368 ,
       1.0213343 , 0.9903923 , 1.0188175 , 1.0109423 , 0.9948963 ,
       0.98544395, 1.0085847 , 1.0029578 , 1.0007473 , 1.0129092 ,
       0.9969159 , 0.9994824 , 1.0057448 , 1.0270072 , 1.0021186 ,
       1.0261698 , 0.9926121 , 1.0021111 , 1.0285383 , 0.99907106,
       0.9973623 , 0.9984153 , 1.0001962 , 1.019865  , 1.0005081 ,
       0.9915482 , 0.992123  , 1.0055758 , 1.0228525 , 0.9966092 ,
       0.9918098 , 0.99984574, 1.0101606 , 1.0236986 , 0.9879798 ,
       0.9978391 , 0.99950254, 0.9957579 , 0.9838705 , 1.020836  ,
       1.0350643 , 1.0028528 , 1.0144981 , 1.0066626 , 0.9883772 ,
       1.016628  , 0.9981732 , 1.0021127 , 0.9977907 , 0.99292976,
       1.0029241 , 1.0033807 , 0.99389464, 1.0099866 , 1.0117011 ,
       1.007328  , 1.0123149 , 1.0166756 , 1.006197  , 0.9949669 ,
       0.9852091 , 1.013976  , 1.0017662 , 0.9943736 , 1.0092119 ,
       0.9839638 , 1.0196332 , 0.99862003, 0.9944776 , 1.00179   ,
       1.0138465 , 1.0350355 , 1.0040338 , 1.006194  , 0.994519  ,
       1.013154  , 0.99068123, 0.99865794, 0.9969463 , 1.0110492 ,
       1.0236559 , 1.0037851 , 0.98719984, 0.97916585, 1.0246336 ,
       1.0223502 , 1.0020505 , 1.0019177 , 1.0098044 , 0.99133676,
       0.99789757, 0.993816  , 1.0119653 , 0.98699373, 1.0071343 ,
       1.0040615 , 0.9977517 , 0.99147487, 1.0003456 , 1.0159072 ,
       0.99409866, 0.9892464 , 0.99587303, 0.98624843, 1.0224866 ,
       0.98678267, 1.0040958 , 1.0216719 , 1.0025662 , 0.99118406,
       1.017421  , 1.0046512 , 0.99256563, 1.0233624 , 1.0064497 ,
       1.0137495 , 0.9947305 , 0.986571  , 0.9974132 , 1.0073572 ,
       0.98304   , 1.0010192 , 0.99925995, 0.9859994 , 1.0126574 ,
       1.0125687 , 1.0047175 , 0.9912438 , 0.9905798 , 1.0042862 ,
       1.0242192 , 1.0072815 , 0.9933566 , 1.005352  , 0.9819208 ,
       0.9968236 , 0.99479413, 0.9974763 , 0.991919  , 0.9859464 ,
       0.9977851 , 1.019815  , 0.9989685 , 1.0101455 , 1.0002607 ,
       0.9956006 , 0.99729735, 1.0134735 , 1.0066301 , 1.0182183 ,
       1.0350043 , 1.0314094 , 1.0147094 , 0.99115986, 1.0020823 ,
       1.0020263 , 0.98602396, 0.9949599 , 0.987963  , 1.0128148 ,
       1.0001485 , 1.0084558 , 0.9850727 , 1.0274819 , 0.99244076,
       0.9841038 , 1.0231056 , 1.0127573 , 1.0026802 , 1.0106021 ,
       0.9897613 , 1.0090711 , 0.9924866 , 1.0086731 , 0.9955085 ,
       0.9963903 , 0.9964797 , 1.0114107 , 1.0006344 , 1.0215944 ,
       0.9863751 , 1.0032122 , 0.99459153, 0.9936271 , 1.0149902 ,
       0.9921586 , 0.99146587, 0.9992578 , 1.0030118 , 1.0045648 ,
       0.9977029 , 0.9904683 , 0.99658346, 0.9986152 , 0.9996233 ,
       0.99312454, 1.0197786 , 1.03896   , 1.0061005 , 1.0049233 ,
       0.99815917, 0.9994049 , 0.96996444, 0.9882163 , 0.9926989 ,
       0.98530895, 1.0103445 , 1.0150129 , 1.0075064 , 0.9950681 ,
       0.99110335, 0.9983036 , 0.98658055, 1.0121361 , 1.0079112 ,
       1.0102094 , 0.9996009 , 0.99715126, 0.98981637, 1.0046505 ,
       1.0211821 , 0.9763767 , 1.004889  , 0.99525964, 1.0153502 ,
       0.99338806, 0.9910125 , 1.0135769 , 1.0022067 , 1.0032046 ,
       1.0023252 , 0.99483067, 1.0033766 , 1.0057064 , 0.9989195 ,
       0.99745226, 0.99581516, 0.985122  , 0.9996022 , 1.0221362 ,
       0.97546923, 0.9897554 , 0.98957276, 0.9857985 , 0.9928027 ,
       1.0093695 , 1.0072529 , 1.0033586 , 1.0164105 , 0.99240124,
       0.99257445, 0.99066055, 1.00394   , 0.98442763, 0.99042475,
       0.993234  , 1.0021089 , 1.0045174 , 0.98264205, 0.9908226 ,
       1.0015564 , 0.9931226 , 1.0033733 , 1.03232   , 1.0032626 ,
       1.0016421 , 1.0004535 , 0.99445   , 1.0041173 , 0.9879954 ,
       0.99194324, 0.988385  , 1.0021424 , 0.97894096, 1.0113496 ,
       0.99586993, 0.9981444 , 1.012735  , 0.99350303, 1.0134339 ,
       1.008875  , 0.99573207, 1.0091863 , 1.00812   , 0.99986416,
       1.0085878 , 1.0213326 , 1.0048871 , 0.9968945 , 1.0143353 ,
       0.9948378 , 1.0091021 , 0.9978495 , 1.0215404 , 1.0058603 ,
       1.0121113 , 1.0064089 , 0.9990214 , 1.0051918 , 1.0189909 ,
       1.0002023 , 0.99282426, 1.0026016 , 0.9967856 , 1.0041307 ,
       1.0029777 , 1.018586  , 0.99169296, 1.0072917 , 1.00356   ,
       1.0000843 , 0.9898377 , 0.9888437 ], dtype=float32), array([ 4.30381764e-03,  1.52496826e-02, -9.86842904e-03, -4.19464475e-03,
        6.27325568e-03, -2.92015150e-02, -3.17295082e-03, -3.47670056e-02,
        8.50276090e-03, -4.77120606e-03,  1.02350302e-02,  3.68745974e-03,
        1.43443234e-03, -2.85852654e-03,  8.56526848e-03,  4.84848069e-03,
       -1.45763867e-02,  3.84773035e-03, -1.65704824e-02, -1.09389164e-02,
       -1.39659587e-02, -1.47129362e-02, -1.08819278e-02, -1.50692547e-02,
       -1.07490532e-02,  1.94492638e-02,  1.11619178e-02,  1.91307999e-02,
       -3.12487537e-04, -1.60468407e-02,  1.33231725e-03, -9.86793451e-03,
        6.42923033e-03, -2.47508790e-02, -2.86231586e-03, -4.95293224e-03,
       -9.30343848e-03, -1.92084871e-02, -1.13075357e-02, -1.90981978e-03,
        1.49651984e-04,  8.61202716e-04, -5.29128406e-03, -1.37426322e-02,
       -3.91035294e-03, -3.38241421e-02, -5.74388308e-03, -3.23895225e-03,
       -4.05737385e-02,  4.32519615e-03, -1.35066761e-02,  1.89873651e-02,
       -1.76327713e-02,  1.60344746e-02, -2.64248392e-03, -4.20767203e-04,
       -4.19846410e-03, -1.72953196e-02, -1.27991755e-02, -6.50625385e-04,
       -5.16613247e-04,  5.40088443e-03, -2.30925940e-02, -5.49540343e-03,
        2.99862656e-03, -4.82137036e-03, -1.21916644e-02,  1.48126315e-02,
        2.81286542e-03, -6.79130387e-03, -2.05751974e-03, -5.80992224e-03,
       -7.36696413e-03, -1.08101359e-03,  1.11969290e-02, -2.07043663e-02,
        1.55619634e-02,  2.31069978e-03,  5.45380171e-04, -2.06632838e-02,
       -1.89678557e-02,  2.67129159e-03, -1.04810996e-03, -4.23215982e-03,
        1.66698126e-03,  7.31164822e-04,  2.60601658e-03, -6.04256941e-03,
        8.80018063e-03,  6.19319733e-03, -8.71228054e-03, -2.00460088e-02,
       -9.99389961e-03, -1.00065479e-02, -1.04351705e-02, -2.37473333e-03,
        2.13401928e-03, -1.09790694e-02, -2.69000442e-03,  1.29574463e-02,
        3.23530822e-03,  2.84375763e-03,  8.38571414e-03, -1.24712149e-02,
       -4.07693116e-03, -1.33201545e-02, -2.12987997e-02, -2.22986918e-02,
       -3.30812507e-03, -2.80941557e-02, -6.52057678e-03, -2.36732420e-02,
       -1.07302167e-03,  9.28122178e-03, -2.60140863e-03,  2.18956568e-03,
        8.46046861e-03, -9.21130739e-03,  2.03606696e-03, -3.03694676e-03,
       -8.19134805e-03, -1.92902815e-02, -9.96449031e-03,  5.37879672e-03,
       -1.69829503e-02, -1.55568086e-02,  6.79224497e-03,  2.54717302e-02,
        9.87718813e-03, -1.15867215e-03, -8.57089926e-03,  1.37028862e-02,
       -7.13557936e-03, -8.28306191e-04, -1.05700409e-02, -1.98150501e-02,
        4.48294468e-02, -2.60680839e-02, -8.08555074e-03, -1.45693691e-02,
        1.06019583e-02, -1.00253578e-02,  6.69017294e-03, -1.03744157e-02,
       -1.53342048e-02,  1.19794803e-02,  4.72558546e-04, -2.75628958e-02,
       -2.08913311e-02, -4.31664474e-03, -1.51655152e-02, -1.09864864e-02,
        1.27044186e-05, -1.82949454e-02,  4.23562899e-03, -3.83444666e-03,
        8.81052285e-04, -1.43183535e-02, -1.10217594e-02,  9.92154470e-04,
        5.76338125e-03, -1.48727437e-02, -1.27043016e-02, -1.37619218e-02,
       -2.74509308e-03, -3.94119173e-02,  1.35351690e-02, -2.13700128e-04,
        1.02299759e-02, -1.57350805e-02,  2.29753014e-02, -2.01332569e-02,
        1.03999302e-03, -1.15526048e-02, -2.06001829e-02, -1.31702460e-02,
       -3.73232272e-03,  4.17758990e-03, -4.88014100e-03, -4.26809117e-03,
       -3.97577835e-03, -1.44823911e-02, -7.70340813e-03, -1.81288943e-02,
       -4.74358583e-03, -6.19994570e-03,  5.06328698e-03, -9.31837421e-04,
        1.00889690e-02,  1.41828763e-03, -7.59800104e-03, -9.61617287e-03,
       -1.15947826e-02, -9.71129909e-03,  1.72130782e-02,  9.05565731e-03,
        5.12379780e-03, -1.19926110e-02,  1.54533368e-02, -6.74963370e-03,
        1.99967027e-02, -8.70794582e-04,  1.08356299e-02, -2.79740784e-02,
        4.40839073e-03, -4.10897424e-03,  7.46818399e-03, -2.01492887e-02,
        5.32509945e-03,  3.55086732e-03, -1.89219657e-02, -1.77592132e-02,
       -1.23223867e-02, -9.10142157e-03, -2.43833680e-02, -9.43638943e-03,
        4.16882941e-03,  1.11308405e-02,  1.18364831e-02, -1.36081837e-02,
       -1.14243347e-02,  2.97010364e-03,  2.37771450e-03, -7.50017026e-03,
        6.42204308e-04,  1.60663575e-02,  3.36425117e-04,  5.14143221e-02,
       -1.60178989e-02, -1.24544743e-02,  1.56261921e-02,  1.39408978e-03,
       -2.16022087e-03, -8.55949149e-03, -2.45080851e-02, -5.59416716e-04,
       -1.67003013e-02, -1.07751461e-02, -2.35135164e-02,  4.18468937e-03,
       -6.44076616e-03,  1.85861345e-02,  6.88357139e-03, -1.69939094e-03,
       -6.54230174e-03, -2.47381609e-02,  2.74988008e-03,  1.19467697e-03,
       -7.46675348e-03, -1.35162072e-02, -6.65239803e-03, -8.12818762e-03,
       -1.21316621e-02,  4.26119380e-03, -6.80925604e-03, -2.17497107e-02,
       -2.30395794e-02, -5.27701667e-03,  3.71496123e-03, -1.70806074e-03,
       -1.16237085e-02, -8.90553184e-03, -4.42392705e-03, -2.39042956e-02,
       -6.18418388e-04,  1.85706392e-02,  3.11338948e-03,  4.72921785e-03,
       -5.81966247e-03,  4.17087413e-03,  1.55639704e-02,  1.18634358e-04,
       -6.95600593e-03, -6.39755279e-03, -2.53163166e-02, -1.02633908e-02,
       -1.14770290e-02, -3.25528570e-02,  9.65503696e-03, -3.86877321e-02,
        4.07680171e-03,  1.66291429e-05, -5.86045615e-04, -1.53401718e-02,
       -3.97612825e-02, -3.30426265e-03, -1.63803585e-02, -9.30916145e-03,
       -8.76716152e-03, -2.08754987e-02,  1.02382037e-03,  2.09361929e-02,
        1.57822401e-03, -2.48485226e-02, -8.51454400e-03, -1.05846906e-02,
       -3.75832012e-03,  1.84399281e-02, -1.10152485e-02, -3.57817073e-04,
       -1.23908324e-02, -1.05710989e-02, -1.57129485e-02, -2.98484936e-02,
        5.30329440e-03, -1.67375058e-02, -2.88034845e-02, -2.80632148e-03,
        6.80171046e-03,  2.35165888e-03,  1.16484854e-02, -3.36653949e-03,
        9.29050520e-03, -3.71993636e-03,  3.64840426e-03, -1.78816095e-02,
       -1.05142342e-02,  6.43627206e-03,  1.81061532e-02, -1.24298874e-02,
       -9.34023131e-03,  1.44317644e-02, -2.78282631e-02, -1.52734593e-02,
        2.68829335e-02, -1.84855214e-03,  1.80855691e-02, -4.39697644e-03,
       -7.44666532e-03, -2.49796584e-02, -2.13462356e-02, -2.34001200e-03,
       -2.33873236e-03,  2.00142376e-02,  4.89888992e-03, -5.48678311e-03,
        9.65244416e-03, -2.53475159e-02,  4.74614091e-04, -1.23810032e-02,
        2.92943530e-02, -1.77268479e-02,  1.99068850e-03, -1.11031123e-02,
       -5.46861021e-03,  7.54614267e-03,  8.37308541e-03, -1.20463148e-02,
        7.62046315e-03, -4.19032993e-03,  9.16453660e-04,  2.37087440e-02,
        1.80015359e-02,  1.31381257e-02, -1.48264496e-02, -1.55430064e-02,
       -9.22793895e-03, -1.81493035e-03, -8.63691233e-03,  7.65173137e-03,
       -7.06488360e-03, -1.20372539e-02,  1.13079380e-02, -5.56421513e-03,
        2.12257598e-02,  6.77116099e-04, -1.13580460e-02, -1.15565043e-02,
       -2.09330162e-03, -7.59831304e-03, -2.37386245e-02, -1.14955241e-02,
       -6.01423020e-03, -2.03840025e-02, -1.10829761e-02,  9.57175717e-03,
       -4.74976026e-04, -3.03782690e-02,  3.73381143e-03, -1.25423763e-02,
       -2.64374539e-02, -1.64055247e-02, -2.35346821e-03, -5.29115647e-03,
       -4.01721522e-03, -3.13014910e-02, -2.12840196e-02, -7.77569739e-03,
        2.67188484e-03, -5.88318985e-03, -1.87603701e-02,  1.81887869e-03,
       -7.41382223e-03, -1.10405246e-02, -4.27488936e-03, -2.70730611e-02,
       -1.16347952e-03, -8.31701979e-03,  2.86113797e-03,  7.56899361e-03,
       -1.49667654e-02, -1.53941847e-03,  1.02649406e-02, -1.23755075e-03,
       -1.45918783e-02, -1.66027248e-02,  3.33273550e-03, -2.56479867e-02,
       -9.32975113e-03, -5.20677399e-03, -1.13053769e-02, -1.51375495e-02,
        1.21291354e-02, -3.42726447e-02,  1.32513916e-04, -1.76541209e-02,
        6.86836988e-03, -1.66396741e-02, -8.78738065e-05, -2.24360246e-02,
        3.91728617e-03, -1.50091872e-02, -1.56562105e-02, -8.25411826e-03,
        6.91380817e-03, -6.67074369e-03, -1.86524875e-02, -4.52614343e-03,
        5.07015560e-04,  1.71882864e-02, -2.45592240e-02,  1.53344823e-02,
       -7.30551314e-04, -4.51416187e-02, -9.84366704e-03, -1.65392589e-02,
        1.53383734e-02, -1.30724395e-02, -2.93894336e-02, -2.47830525e-03,
       -1.47342412e-02,  3.54057457e-03, -8.70582927e-03,  6.15963759e-03,
       -9.28602368e-03,  1.05429096e-02, -1.22758597e-02, -5.24677243e-03,
        1.92227606e-02, -4.55283839e-03, -1.66597515e-02, -5.48632955e-03,
        3.30478651e-04, -2.52476986e-02,  4.74382052e-03, -7.85783026e-03,
       -8.78542289e-03,  1.04905162e-02, -5.06099686e-03, -9.51671228e-03,
       -5.11198165e-03,  5.84599189e-03,  1.35162035e-02,  6.66546728e-03,
        1.39055110e-03, -1.29218651e-02, -5.57692721e-03, -1.93263181e-02,
        2.85437680e-03, -7.82221463e-03, -1.16617270e-02, -2.18992960e-02,
       -1.12189027e-02, -9.49273817e-03,  6.18603686e-03, -6.38376735e-03,
       -2.80613583e-02, -2.28737332e-02, -6.18075719e-03,  9.05865710e-03,
       -1.04243243e-02, -1.98724903e-02, -1.43057795e-03, -5.47191454e-03,
        1.76258795e-02, -3.88149247e-02, -1.19922468e-02, -3.16401385e-03,
        1.03525873e-02, -5.97540010e-03, -7.15506403e-03, -1.10918777e-02,
       -1.32724615e-02, -2.36017052e-02, -3.19084339e-03,  3.32386568e-02,
       -1.82748605e-02, -4.28454019e-03,  1.36425076e-02, -1.97802875e-02,
       -1.21869957e-02,  6.65352028e-03,  2.49336082e-02, -3.79593950e-03,
       -7.65091740e-03, -1.89533979e-02, -8.22040252e-03, -2.05999240e-05,
       -3.29928799e-03,  9.38547077e-04,  1.30018173e-02, -1.11077428e-02,
        1.91623699e-02, -1.23039335e-02,  1.66738816e-02, -4.75419499e-03,
       -4.01457865e-03, -1.41624715e-02, -1.51305655e-02, -2.01172922e-02,
       -1.12677356e-02, -1.40529824e-02, -3.34056909e-04,  1.28211407e-02,
       -2.27531302e-03, -1.33523168e-02, -1.06333010e-02,  1.67403923e-04,
       -3.09039839e-02, -5.47862845e-03, -5.32444520e-03, -1.03477426e-02,
       -2.30418611e-02, -2.35884869e-03,  5.44291548e-03,  1.91981869e-03,
       -1.33115249e-02, -2.07472648e-02, -1.40647625e-03, -2.01812666e-02,
       -3.39610758e-03, -1.24623319e-02, -1.11745596e-02, -2.63757771e-03,
       -2.89465673e-03,  1.44742830e-02,  1.12092169e-03,  9.23588872e-03,
       -7.67391315e-03,  5.34596911e-04, -1.08474893e-02, -1.32434936e-02,
       -7.85575900e-03,  8.33060592e-03,  5.52108418e-03, -7.95003492e-03,
       -3.18581350e-02, -5.10288309e-03,  9.71507560e-03,  8.76507629e-03,
        5.89249842e-03, -3.70132946e-03,  1.32999402e-02,  1.35898786e-02,
        2.15102509e-02, -3.30763385e-02,  1.51335215e-02, -1.74909141e-02,
        2.13220692e-03, -3.03305569e-06, -2.03769095e-02, -9.48923547e-03,
       -2.98471004e-02,  4.22659982e-03, -1.43770026e-02,  4.53295565e-04,
       -2.59298515e-02,  6.67551300e-03, -1.77063700e-02, -1.02682114e-02,
       -5.73222199e-03,  7.77984690e-03, -3.91033303e-04, -7.63701927e-03,
        3.62158613e-03, -4.45899367e-03, -1.22358659e-02, -1.17548520e-03,
       -1.48599560e-04,  5.53170126e-03,  1.38735063e-02, -1.60441957e-02,
        1.00105535e-02, -8.69804062e-04,  1.79658774e-02, -3.54845484e-04,
        3.48917674e-03, -1.28175449e-02, -6.53716316e-03,  1.35142729e-02,
       -7.82639813e-03, -3.61512671e-03,  3.75660136e-04, -3.54431942e-03,
       -6.27743453e-03,  8.37734062e-03,  1.78363435e-02, -9.08973254e-03,
       -5.24306856e-03, -1.41122937e-02, -1.90313510e-03,  1.90472568e-03,
       -3.51493396e-02, -9.28346347e-03, -1.16386507e-02, -8.50322098e-03,
       -2.97368784e-02, -2.05419715e-02,  3.79502866e-03, -1.61853246e-02,
       -8.74711387e-03, -1.19984802e-02, -1.08417906e-02,  1.42098861e-02,
       -1.05947093e-03, -1.60526577e-02, -3.07640266e-02, -3.86849651e-03,
        1.03017851e-03, -3.28358915e-03,  3.53493937e-03,  1.31048271e-02,
        6.80036750e-03, -5.39431395e-03, -1.23960841e-02,  2.29199696e-02,
       -8.98623094e-03,  3.16507649e-03, -2.02119909e-02,  3.80142825e-04,
       -4.53025848e-03, -4.41971235e-03,  1.79930683e-02, -4.80598118e-03,
        5.29622054e-03,  3.01060709e-03, -5.13172755e-03,  1.16627030e-02,
        2.98605789e-03, -1.11931171e-02, -4.70649591e-03, -1.54659720e-02,
       -5.35820052e-03, -3.80023685e-03,  7.97852594e-03, -1.21346861e-02,
       -5.98691497e-03,  3.58011504e-03, -1.13860397e-02, -1.85937881e-02,
        1.82825059e-03,  2.07784902e-02, -2.36174520e-02, -2.18918943e-03,
       -1.08863125e-02,  1.58830676e-02, -1.51364552e-02, -8.03253334e-03,
        1.16503369e-02, -2.19878927e-02, -2.05755290e-02,  6.12983853e-03,
        2.35996791e-03,  2.28071250e-02, -1.07017308e-02, -1.19874459e-02,
       -8.52865353e-03, -3.39388326e-02, -3.06392205e-03,  2.29343912e-03,
        6.56358339e-03,  6.67484524e-03, -1.80526078e-02, -8.43712036e-03,
       -1.35719087e-02,  1.61116850e-02, -3.92299052e-03,  1.48435077e-03,
        5.07527497e-03, -5.17617539e-02, -1.28735357e-03,  8.65192898e-03,
        4.41769976e-03,  6.58027455e-03,  7.41428346e-04,  2.82552256e-03,
        5.57550788e-03, -1.33633297e-02, -1.23000462e-02, -1.56029372e-03,
       -4.01254324e-03, -7.95104541e-03, -3.65041988e-03,  1.24926271e-03,
        4.08539874e-03, -1.70051516e-03, -2.96563585e-03, -6.82136603e-03,
        5.04536647e-03,  8.93850345e-03,  9.90253687e-03, -3.92591907e-03,
        5.68476599e-03, -8.46042763e-03,  2.38879491e-02,  3.59338075e-02,
       -1.11179729e-03, -2.89681368e-03, -4.62229317e-03,  2.69469201e-05,
       -5.44880005e-03, -2.23240126e-02, -2.14364957e-02, -1.98344886e-02,
       -1.96437463e-02, -3.04671787e-02,  5.69349108e-03, -2.05185208e-02],
      dtype=float32), array([ 1.86296385e-02,  7.35400617e-02,  2.50772759e-02,  3.73586565e-02,
       -3.74904200e-02,  2.21546702e-02, -5.40622473e-02, -3.20070721e-02,
       -7.58904517e-02,  5.31451441e-02, -4.78288680e-02, -2.14005448e-02,
        3.15434969e-04,  6.57095462e-02, -4.27309684e-02, -3.38731296e-02,
        3.09759807e-02,  1.26802968e-02,  7.08635822e-02,  5.10292724e-02,
        2.44882721e-02,  5.60560934e-02,  1.43751372e-02,  5.75725138e-02,
       -2.78878659e-02,  1.39947170e-02, -1.85650568e-02, -4.41383831e-02,
       -2.36089509e-02,  1.66306831e-02, -8.56936537e-03,  1.38740689e-02,
       -4.00377102e-02,  3.95243727e-02, -4.16747630e-02,  4.90631647e-02,
        3.83834541e-02, -3.99694741e-02, -3.23337764e-02,  2.59340722e-02,
       -9.08688363e-03,  1.82116334e-03, -4.04470973e-02, -2.81938538e-02,
       -3.00333183e-02,  2.02738866e-02, -2.02223230e-02, -7.15971598e-03,
        5.01118526e-02, -4.57448103e-02,  1.12314359e-03, -4.77943718e-02,
       -2.02117804e-02,  9.24935937e-03,  3.66938673e-02,  1.65861417e-02,
        2.48178896e-02,  3.71395238e-02,  1.61956414e-03,  1.17996782e-02,
        1.80153288e-02,  3.23114879e-02, -4.08348292e-02, -6.28960785e-03,
       -4.69116531e-02,  4.17836495e-02,  7.40848258e-02, -2.12983079e-02,
       -4.21506874e-02, -3.74017395e-02,  7.32315425e-03, -1.73985530e-02,
       -2.53468603e-02,  3.55253480e-02, -3.64489146e-02,  4.29917984e-02,
       -3.20033021e-02,  6.49684966e-02, -1.79370139e-02,  1.15885036e-02,
       -2.18171496e-02, -1.65642649e-02,  4.91455756e-02, -4.54942808e-02,
       -5.95279969e-02, -3.40906694e-03, -2.01153196e-02,  2.26910245e-02,
       -4.90130484e-02,  1.11194942e-02,  3.06862406e-02,  5.00024483e-02,
        1.95172112e-02, -1.51410336e-02, -9.25040920e-04, -5.50988168e-02,
       -6.79212436e-03,  2.52448209e-02, -1.93009321e-02,  1.66337908e-04,
       -8.01184401e-02,  1.33918868e-02, -1.59249958e-02,  4.35621589e-02,
        1.03896959e-02,  8.43257643e-03, -1.82360655e-03,  2.18895487e-02,
       -2.51328498e-02,  5.32972701e-02, -5.51160611e-02, -3.00263651e-02,
        1.24072237e-03,  3.02859694e-02, -5.20920334e-03, -1.92925264e-03,
        1.94836408e-02,  5.72338402e-02, -3.26719396e-02,  5.61086424e-02,
        3.57683636e-02, -2.03726208e-03,  6.50634542e-02, -2.34557446e-02,
        5.89775629e-02,  2.66780034e-02, -6.52568508e-03, -2.14458257e-02,
       -2.69253533e-02,  2.73926128e-02,  5.63936755e-02, -5.05829938e-02,
       -2.05790251e-02, -2.15381738e-02, -1.17836159e-03,  3.01238559e-02,
       -1.05146784e-02,  5.84685542e-02, -4.81152907e-03,  2.69251820e-02,
       -3.24189663e-02,  4.14593555e-02,  1.24233160e-02, -1.96009353e-02,
        4.61347587e-02, -1.17226476e-02,  1.16890222e-02, -2.47088801e-02,
        3.63922827e-02,  2.05010232e-02,  1.26320804e-02,  2.42094137e-02,
        1.64558310e-02,  6.02625683e-02, -2.76439656e-02, -1.05815986e-02,
       -2.75628064e-02,  5.71085103e-02,  3.28320004e-02, -1.90176051e-02,
       -5.32378294e-02,  3.03018652e-02, -1.75394230e-02, -1.51335457e-02,
        3.33341956e-02,  2.06349231e-02, -4.09334153e-02, -2.89322902e-02,
       -3.29909548e-02, -1.67853925e-02, -2.72830296e-02,  3.96373495e-02,
        3.53573672e-02, -5.51568940e-02,  1.00418981e-02,  1.01044867e-02,
       -2.27003451e-02, -4.22333032e-02,  1.12564396e-02,  1.31550739e-02,
       -2.52666250e-02,  5.15081994e-02, -3.50505337e-02,  1.62636414e-02,
        2.95686047e-03,  3.71525809e-02, -3.33053321e-02, -3.92516516e-02,
        6.78719813e-03, -2.98042409e-02,  4.53852154e-02,  1.56637430e-02,
       -3.28911208e-02,  2.35835202e-02, -5.66098019e-02, -1.92869306e-02,
       -3.75214666e-02,  2.33496446e-02,  2.54388945e-03,  8.02811608e-02,
       -8.12492741e-04,  5.78397559e-03, -5.19234538e-02, -3.10568046e-02,
        1.51550695e-02,  4.07390520e-02, -3.32479365e-02, -1.57726929e-02,
        3.62334959e-02, -3.99099290e-02,  2.25542150e-02,  4.42612581e-02,
       -4.00017994e-03,  7.19835842e-03, -6.13697693e-02, -2.12067156e-03,
        2.87451781e-02, -3.00965346e-02, -5.38359992e-02,  4.79514077e-02,
        4.05156203e-02, -3.47637199e-02,  3.92575897e-02, -9.73158702e-03,
       -5.78123108e-02,  2.76500899e-02, -4.31601889e-02, -6.42798543e-02,
        4.09764498e-02,  4.04274613e-02, -4.23262864e-02,  3.58908400e-02,
       -3.38442449e-04,  2.78788339e-02,  5.43533266e-02,  1.61155146e-02,
       -5.90136042e-03, -3.12368553e-02,  4.08690842e-03,  1.16885696e-02,
        3.48569639e-02, -6.77222535e-02, -3.96031933e-03,  3.06880511e-02,
       -3.24445032e-02,  5.08785620e-02,  4.61781509e-02, -1.64024383e-02,
        9.42006428e-03,  3.02045867e-02,  5.56746274e-02,  5.20129921e-03,
       -3.76327932e-02, -5.56831108e-03,  5.97044416e-02,  3.88975069e-02,
        2.39557046e-02,  4.32374030e-02,  3.74388844e-02,  2.81326771e-02,
        6.54096976e-02, -4.00468111e-02, -2.30846722e-02,  6.43394291e-02,
       -2.07484104e-02, -1.44175198e-02, -3.07495929e-02,  3.18652466e-02,
       -6.62896363e-03,  4.09445651e-02, -4.33498062e-02,  3.36447172e-02,
       -2.10276265e-02,  5.11093102e-02,  2.45513208e-02,  5.69141135e-02,
       -1.04502095e-02,  4.10455950e-02, -8.32122343e-04,  1.82612687e-02,
        3.86000015e-02, -1.47289112e-02, -3.80060147e-03,  5.03846630e-03,
       -2.31601335e-02,  4.08988670e-02,  6.82100886e-03, -2.48474255e-02,
       -6.45294378e-04,  2.50858045e-03, -4.05657478e-02, -1.37999346e-02,
        1.45845888e-02,  5.37470765e-02, -1.93974134e-02,  3.18982974e-02,
        2.76597012e-02, -4.24910821e-02,  2.67595239e-02, -5.84251061e-02,
        4.13260423e-02, -1.32476427e-02,  4.25357260e-02,  2.31527314e-02,
       -2.22187266e-02,  3.01752649e-02, -1.53696574e-02,  6.22460581e-02,
       -2.13658698e-02,  4.41978723e-02, -1.51145356e-02, -5.31437099e-02,
        1.32364789e-02, -1.27916122e-02, -7.84632401e-04,  5.55862896e-02,
        3.14449668e-02,  3.46331634e-02, -5.12391031e-02,  4.07898091e-02,
        6.71623833e-03,  2.76473630e-02,  4.33059521e-02,  2.90245786e-02,
       -4.94333655e-02,  1.46721285e-02, -1.34997638e-02,  5.60350902e-02,
        5.24895079e-02,  3.64158973e-02,  7.48664513e-02, -2.31157430e-02,
        3.84952873e-02, -5.74772172e-02, -1.67383882e-03,  6.17908798e-02,
        3.18508819e-02,  5.61663210e-02,  3.24922502e-02, -1.99718792e-02,
       -3.94371077e-02,  7.45250434e-02,  3.81892584e-02,  2.73128599e-02,
       -4.27021347e-02,  2.42189430e-02,  4.36897278e-02,  3.00814807e-02,
       -4.92659621e-02,  4.24512848e-02,  3.42059731e-02, -5.09322211e-02,
       -8.26601908e-02, -3.14346664e-02, -1.64674539e-02,  1.36777207e-05,
        4.27587144e-02, -1.93046755e-03, -8.22383817e-03,  2.89399158e-02,
        5.19286431e-02,  4.04104032e-02, -6.19481020e-02,  2.75616664e-02,
       -6.86528832e-02, -1.42236920e-02,  1.94057599e-02,  6.38524964e-02,
       -2.60331798e-02,  3.18768695e-02,  6.61294535e-02,  6.81384187e-03,
        2.12003440e-02,  2.10711882e-02,  4.66219299e-02, -2.04627160e-02,
       -3.93789001e-02, -2.60017952e-03,  6.23318483e-04,  4.62063849e-02,
        4.62614708e-02,  1.98288150e-02, -2.12930776e-02, -3.79702896e-02,
        5.17203026e-02, -2.02246662e-02,  4.80520390e-02,  5.40421754e-02,
       -4.85570170e-02,  4.36971486e-02,  3.21548060e-02,  3.89201902e-02,
       -1.66227967e-02,  5.08980937e-02,  1.26093812e-02, -9.05659981e-03,
        3.82520445e-02,  5.47435135e-02,  5.60744517e-02, -4.13813256e-03,
        3.56949866e-02, -8.06198735e-03, -2.38624010e-02, -5.20243868e-02,
        3.31415571e-02,  1.29943285e-02,  4.80624065e-02,  2.65618023e-02,
       -1.61707159e-02,  2.82925684e-02,  2.94939652e-02,  3.67613137e-02,
       -4.35792729e-02, -1.38766989e-02, -1.06000137e-02,  4.47990596e-02,
       -2.51988806e-02,  2.98203100e-02, -3.54746655e-02,  1.32397702e-02,
       -2.70552009e-05,  3.82349417e-02,  1.23156644e-02,  4.93166037e-02,
        1.61762014e-02,  2.41832100e-02,  4.33856212e-02, -1.19051626e-02,
        3.10619511e-02, -3.07560638e-02,  3.90904285e-02, -6.70471787e-02,
       -5.22948392e-02,  2.32513808e-02, -4.52767983e-02, -4.03895751e-02,
       -4.18834314e-02,  4.99897078e-02,  4.05195132e-02,  4.50260229e-02,
        8.12321436e-03, -4.50629257e-02,  4.94555123e-02,  2.20203046e-02,
        3.53946351e-02,  2.51543298e-02, -1.66072659e-02,  3.15413326e-02,
        3.31512950e-02, -5.47982007e-03,  5.90821728e-02,  1.81570109e-02,
        9.71816666e-03, -4.57131246e-04, -4.65809815e-02,  5.46140000e-02,
       -1.41188800e-02, -4.16535251e-02, -5.13282232e-02, -9.32044536e-03,
        5.53522632e-02,  9.11019742e-03, -3.25148925e-02,  4.68645170e-02,
       -1.77367665e-02, -1.60856768e-02, -2.00030152e-02, -4.22497801e-02,
        4.71140034e-02, -1.89527851e-02,  6.81010932e-02,  3.18406709e-02,
        2.87425667e-02,  6.06273580e-03,  6.97264401e-03,  1.57052111e-02,
        5.51356152e-02,  5.07742353e-02,  2.21821410e-03, -4.08358015e-02,
       -2.19617020e-02,  2.54302975e-02, -2.35646870e-02, -2.88337767e-02,
       -2.54013035e-02, -8.58529843e-03,  1.33836530e-02,  4.62228246e-02,
        2.12263525e-03,  6.52685389e-02, -5.16625829e-02,  3.78660634e-02,
        3.30390818e-02,  1.37387663e-02, -2.79472768e-02, -4.49213758e-02,
       -1.01762712e-02, -1.48403002e-02, -1.20120300e-02,  8.66200123e-03,
        2.57886318e-03, -3.19499485e-02,  3.90210338e-02, -1.47594800e-02,
        4.87999059e-02,  6.63877428e-02, -1.26833739e-02, -2.32322123e-02,
       -2.98596490e-02,  3.83693650e-02,  3.48660536e-02,  5.77570172e-03,
       -6.39187917e-02,  5.20245433e-02, -5.71687371e-02, -4.63485252e-03,
       -2.18430832e-02,  4.57089394e-02, -1.28520913e-02,  3.88193280e-02,
       -1.51947942e-02,  4.36740480e-02,  5.13896458e-02, -3.20214368e-02,
        3.57478894e-02,  5.24580553e-02,  3.42058353e-02,  9.06708956e-05,
        5.93307912e-02, -3.47378515e-02,  4.48954366e-02, -3.94755788e-02,
        1.13328872e-02, -3.62329632e-02, -3.66117293e-03, -4.61346321e-02,
        1.66995339e-02,  4.61068042e-02,  3.45682725e-02, -2.32983585e-02,
        3.33010964e-02,  4.76375259e-02, -4.52527143e-02, -2.15632208e-02,
       -4.00576293e-02, -5.82070202e-02,  2.84297075e-02,  2.91684829e-02,
        6.48396090e-03,  2.92888307e-03, -9.03394446e-02,  3.66317108e-02,
        7.22489087e-03, -5.14688380e-02, -1.27468084e-03,  3.62022482e-02,
        6.85444027e-02,  5.71933314e-02, -4.04066965e-02,  1.74510647e-02,
        4.30110929e-04, -5.91656156e-02,  1.98015608e-02, -5.65954074e-02,
       -2.48543341e-02,  4.04862016e-02, -3.48358713e-02, -2.70409752e-02,
        5.77220786e-03,  5.98923303e-02,  1.79760903e-02,  3.78530212e-02,
        5.34864441e-02,  9.45010595e-03,  3.13021080e-03,  7.76249496e-03,
        7.35793039e-02,  1.88751519e-02,  5.02813645e-02, -7.49663886e-05,
        4.06607315e-02, -2.97268406e-02, -4.75405194e-02,  3.40691023e-02,
       -3.91379856e-02,  1.21553140e-02,  4.80363052e-03,  4.04872522e-02,
       -3.49427052e-02, -4.84885238e-02, -1.33155873e-02, -1.10640107e-02,
        2.77370941e-02,  3.59461829e-02, -6.79875910e-02, -1.94342900e-02,
       -3.38052809e-02, -6.40909597e-02, -1.24627622e-02,  3.37340981e-02,
       -2.32439227e-02, -3.73583287e-03,  4.46867086e-02, -3.07372343e-02,
        4.24041972e-02, -1.80208702e-02, -1.54364780e-02, -1.73950791e-02,
        5.85257215e-03,  1.24107068e-02, -2.39876807e-02, -3.07126772e-02,
        7.84657076e-02, -4.22313251e-02,  4.97060418e-02, -1.51994666e-02,
        3.88281904e-02,  2.16305386e-02,  4.70124707e-02, -1.60209481e-02,
       -3.01841963e-02,  3.67310233e-02,  7.72085562e-02, -4.47099954e-02,
       -2.27660164e-02, -2.22971700e-02,  3.61016467e-02,  3.74857411e-02,
        4.79245111e-02,  2.45219674e-02, -1.40040740e-02,  2.65104435e-02,
        4.47878018e-02, -2.94698775e-02,  2.03601569e-02, -4.70548272e-02,
       -1.27515066e-02, -1.34485550e-02,  5.21485601e-03, -5.28410450e-02,
       -4.48809937e-02, -4.70624305e-03,  2.56255101e-02, -1.84349939e-02,
       -1.20185874e-02, -6.15751296e-02, -4.22421470e-02, -7.81144341e-03,
       -5.10911606e-02, -8.42724368e-03,  8.06028862e-03,  4.44275886e-02,
       -2.66397689e-02, -3.08157112e-02, -5.35215028e-02,  5.80766723e-02,
        1.65248439e-02, -4.08048443e-02,  2.77229073e-03,  3.66553217e-02,
       -1.08204726e-02, -4.51034047e-02, -3.41419205e-02, -4.50235754e-02,
       -4.98617962e-02, -3.54020409e-02,  2.69413330e-02,  1.47288274e-02,
       -2.70893108e-02, -3.15321274e-02, -2.32797246e-02,  3.26750837e-02,
       -4.47707549e-02, -6.04091063e-02, -3.47624416e-03, -6.94459975e-02,
        3.85403596e-02,  5.51939756e-02,  2.51767319e-02, -2.24220380e-02,
        1.84291489e-02, -1.08448248e-02, -7.14588389e-02, -9.28592682e-03,
       -1.60692558e-02, -5.16200028e-02, -5.65557799e-04, -6.46153092e-03,
       -3.76435404e-04,  1.82867385e-02,  8.06451309e-03,  1.64801013e-02,
       -3.66031043e-02,  4.67975177e-02,  5.24640679e-02,  4.03638789e-03,
       -2.18386818e-02,  3.51769403e-02,  5.31762689e-02, -6.07144507e-03,
        2.50528537e-04,  5.66425920e-02,  1.69412009e-02, -1.07912039e-02,
       -4.76335287e-02, -1.46205360e-02,  4.98698391e-02, -5.42822294e-02,
       -3.11386324e-02,  3.70770916e-02, -3.69535312e-02, -2.53516100e-02,
        3.32339332e-02,  3.14902775e-02, -1.49122197e-02, -4.61583845e-02,
       -2.36197915e-02, -1.12887966e-02,  3.87625247e-02, -3.25386412e-02,
        7.04030320e-02,  3.31933126e-02, -7.56348949e-03,  3.21093351e-02,
        6.09789193e-02, -6.76181260e-03, -3.00225411e-02, -2.26543332e-03],
      dtype=float32), array([0.08358483, 0.0962936 , 0.09508848, 0.09801728, 0.10074812,
       0.09006474, 0.09332946, 0.09575647, 0.13891183, 0.11029734,
       0.09454983, 0.08910352, 0.09168052, 0.13760814, 0.09577537,
       0.09085987, 0.1091328 , 0.09294643, 0.10756892, 0.11272114,
       0.08781095, 0.11104918, 0.09472183, 0.10303671, 0.09402119,
       0.08449416, 0.083566  , 0.11147953, 0.10709613, 0.08471446,
       0.09668497, 0.09430505, 0.10312074, 0.09304869, 0.09053357,
       0.11772347, 0.10752951, 0.100912  , 0.08866155, 0.08474764,
       0.08372267, 0.08742341, 0.10205498, 0.08481428, 0.08736474,
       0.09368058, 0.08893097, 0.08766942, 0.10316169, 0.1059437 ,
       0.09129179, 0.10547616, 0.09320579, 0.08464198, 0.09633396,
       0.08516557, 0.10035995, 0.10688253, 0.082423  , 0.08415655,
       0.09153575, 0.0855877 , 0.09664156, 0.08862451, 0.09195891,
       0.09361863, 0.11763336, 0.0857828 , 0.09770802, 0.08769526,
       0.08711351, 0.09489217, 0.08857288, 0.08992548, 0.08871306,
       0.10491022, 0.09623074, 0.09941028, 0.09100704, 0.08514116,
       0.08865338, 0.10817862, 0.09740523, 0.08706386, 0.10704724,
       0.08440701, 0.08639968, 0.08444278, 0.10933072, 0.09816915,
       0.08976881, 0.0965627 , 0.09937491, 0.09005559, 0.08786781,
       0.09794819, 0.08927162, 0.10359564, 0.09255675, 0.09159689,
       0.11413056, 0.08849924, 0.08751901, 0.10186384, 0.08649597,
       0.09049445, 0.09468543, 0.09223301, 0.09848928, 0.10522086,
       0.10935393, 0.09484081, 0.08530595, 0.08795029, 0.08538572,
       0.09365975, 0.10023569, 0.11286154, 0.0980373 , 0.11330891,
       0.10886819, 0.0886452 , 0.10054873, 0.09514511, 0.13412993,
       0.09045841, 0.08667067, 0.08839703, 0.0962534 , 0.10612743,
       0.10600771, 0.0905468 , 0.08662285, 0.09016871, 0.08566859,
       0.09001455, 0.10214152, 0.1241391 , 0.09192301, 0.09823678,
       0.09801596, 0.08932489, 0.09478585, 0.09234493, 0.10440116,
       0.09298627, 0.08362225, 0.09682847, 0.09779207, 0.08423533,
       0.08671462, 0.08828939, 0.0885584 , 0.11750224, 0.09091347,
       0.08586151, 0.10703745, 0.093775  , 0.11638569, 0.08644275,
       0.09616724, 0.08858263, 0.09005962, 0.08756636, 0.08528641,
       0.11272663, 0.10615382, 0.09145723, 0.08884016, 0.08857284,
       0.08630324, 0.11815804, 0.0899732 , 0.1146331 , 0.08988132,
       0.1045929 , 0.08708823, 0.09451982, 0.08542813, 0.08553313,
       0.09532642, 0.10685447, 0.08910884, 0.09713643, 0.09167458,
       0.08977948, 0.09247991, 0.10007977, 0.09207979, 0.08711878,
       0.09069279, 0.09884406, 0.09269296, 0.0874428 , 0.11386337,
       0.08525876, 0.09446967, 0.09364192, 0.08750361, 0.1150594 ,
       0.08569499, 0.08866543, 0.11026842, 0.1080649 , 0.09073588,
       0.09179553, 0.10367   , 0.0911853 , 0.08892903, 0.0961263 ,
       0.09016361, 0.09542616, 0.0950186 , 0.08165609, 0.12562938,
       0.08849327, 0.08848321, 0.0860745 , 0.10871203, 0.08486237,
       0.10908324, 0.09857515, 0.09614129, 0.08865496, 0.09744945,
       0.08772721, 0.09690425, 0.13724978, 0.09602545, 0.11157992,
       0.10765964, 0.0892151 , 0.0923084 , 0.09806434, 0.11082985,
       0.09443938, 0.08793077, 0.08826926, 0.09182508, 0.08991786,
       0.08638431, 0.11550533, 0.08550217, 0.08819534, 0.09948903,
       0.12910722, 0.08988076, 0.08527015, 0.09444747, 0.09160769,
       0.10903607, 0.0859211 , 0.08591694, 0.08828582, 0.11529515,
       0.10506167, 0.08811248, 0.09646978, 0.09916738, 0.0901615 ,
       0.09675616, 0.08808338, 0.10020335, 0.12710254, 0.08327062,
       0.0984586 , 0.08931962, 0.08867161, 0.09264892, 0.0941582 ,
       0.09655622, 0.086115  , 0.08391228, 0.10466751, 0.10506828,
       0.09501745, 0.09498511, 0.13096818, 0.08470444, 0.10294736,
       0.08703849, 0.09338302, 0.08953795, 0.09199078, 0.09356684,
       0.10827139, 0.08387511, 0.08477393, 0.08930172, 0.08584809,
       0.09620736, 0.09000777, 0.08476063, 0.10302281, 0.09100953,
       0.09427851, 0.09311131, 0.09790749, 0.09173826, 0.10841402,
       0.09447104, 0.08483534, 0.11036103, 0.10150678, 0.09841315,
       0.08815002, 0.09795396, 0.108781  , 0.09464829, 0.09381182,
       0.08769228, 0.10106954, 0.08347578, 0.10069044, 0.08796996,
       0.10065235, 0.10409415, 0.08525752, 0.10816335, 0.10352687,
       0.0968044 , 0.08629716, 0.10514821, 0.10367113, 0.09537612,
       0.0894949 , 0.08964715, 0.12256487, 0.09992278, 0.0860858 ,
       0.1564654 , 0.08927363, 0.10067967, 0.09494577, 0.08892857,
       0.11562357, 0.08744259, 0.09927901, 0.09786428, 0.08999613,
       0.09009799, 0.10674658, 0.09559671, 0.08710576, 0.08825377,
       0.10106351, 0.09726805, 0.08549065, 0.10824653, 0.08889724,
       0.08543389, 0.10744442, 0.1138329 , 0.0966264 , 0.08584947,
       0.09052979, 0.08538715, 0.08365321, 0.09053256, 0.08731376,
       0.11254387, 0.11179281, 0.10411555, 0.09483769, 0.10617008,
       0.08517481, 0.08589692, 0.15686508, 0.09019142, 0.09844138,
       0.14514953, 0.0887721 , 0.09424337, 0.10013478, 0.09203035,
       0.08547489, 0.10046888, 0.09244442, 0.08995913, 0.09726084,
       0.08734156, 0.08409985, 0.09465317, 0.09208736, 0.10407832,
       0.09088513, 0.10918067, 0.09420212, 0.10050711, 0.10946471,
       0.09572453, 0.10082693, 0.08846539, 0.0885378 , 0.0839948 ,
       0.09693104, 0.0910791 , 0.12235488, 0.09431566, 0.09351243,
       0.09372672, 0.08755717, 0.08497178, 0.09406512, 0.12020751,
       0.09724101, 0.10053686, 0.10030942, 0.08395689, 0.10188524,
       0.10641759, 0.09466049, 0.10767509, 0.09422632, 0.0840591 ,
       0.11132996, 0.09345263, 0.09093703, 0.09925351, 0.0955997 ,
       0.09227963, 0.08962803, 0.08960571, 0.09542093, 0.10004069,
       0.08464167, 0.0874526 , 0.08853281, 0.09427729, 0.08646627,
       0.09434082, 0.11512551, 0.10288627, 0.11777863, 0.095489  ,
       0.08992411, 0.0973776 , 0.09104396, 0.1078901 , 0.10124128,
       0.09383083, 0.09304626, 0.11514051, 0.09292524, 0.09770866,
       0.08879508, 0.08738866, 0.0988048 , 0.10800885, 0.08775914,
       0.09459455, 0.08221849, 0.08721431, 0.09313285, 0.09288266,
       0.10450052, 0.08880671, 0.09003446, 0.11299443, 0.08521026,
       0.10840277, 0.09351104, 0.09110172, 0.09047724, 0.08594158,
       0.08893416, 0.09016916, 0.09638062, 0.09448351, 0.08741963,
       0.10713976, 0.10993799, 0.10181182, 0.10321127, 0.0850237 ,
       0.0901495 , 0.10598107, 0.10085793, 0.08524628, 0.09804149,
       0.09435219, 0.10064298, 0.0860942 , 0.08836598, 0.09205001,
       0.09896597, 0.10119151, 0.09922377, 0.08854597, 0.1002132 ,
       0.09466006, 0.09141837, 0.09079816, 0.09413183, 0.10109776,
       0.10596458, 0.08387943, 0.09462255, 0.08467926, 0.09106457,
       0.0899131 , 0.0964375 , 0.09653815, 0.08746243, 0.08939541,
       0.10679694, 0.0841275 , 0.09335457, 0.09982221, 0.10155088,
       0.09650104, 0.08569491, 0.11259507, 0.08991376, 0.11576024,
       0.08679298, 0.08294012, 0.08597724, 0.08310749, 0.10258155,
       0.08710246, 0.08554343, 0.1051347 , 0.10026428, 0.08789453,
       0.12412079, 0.10051468, 0.08682039, 0.11372726, 0.09769771,
       0.10020623, 0.08567713, 0.09081485, 0.09586778, 0.08636604,
       0.09977674, 0.08432401, 0.0947828 , 0.095586  , 0.09155616,
       0.10075055, 0.0902002 , 0.09007677, 0.08403424, 0.09731969,
       0.11899062, 0.09135242, 0.08450511, 0.10256025, 0.09210195,
       0.12356781, 0.09604613, 0.08560479, 0.10120762, 0.08485895,
       0.0980887 , 0.12182767, 0.09577306, 0.09773541, 0.08566056,
       0.08708171, 0.10758367, 0.09564313, 0.11705235, 0.09439124,
       0.10666277, 0.092876  , 0.09462383, 0.08363484, 0.10153069,
       0.08583005, 0.09599554, 0.12876949, 0.09020142, 0.08771104,
       0.08807439, 0.12487696, 0.09090528, 0.11488613, 0.08813988,
       0.0919436 , 0.09619626, 0.10451065, 0.09036768, 0.09068766,
       0.0904076 , 0.08792751, 0.09489251, 0.09525844, 0.1087703 ,
       0.09096914, 0.08276362, 0.09302322, 0.10480321, 0.09745016,
       0.08700743, 0.0940816 , 0.11080243, 0.09687689, 0.08825067,
       0.09337938, 0.08288328, 0.0981416 , 0.08829246, 0.09391783,
       0.10089621, 0.08762576, 0.08555127, 0.08474258, 0.09213753,
       0.09232645, 0.0887883 , 0.14961459, 0.09880954, 0.11016528,
       0.08458675, 0.09802499, 0.08676555, 0.10374022, 0.09025224,
       0.09035209, 0.09874952, 0.12792207, 0.09585158, 0.08497461,
       0.09475345, 0.10756758, 0.08625743, 0.09313164, 0.08933437,
       0.08707314, 0.08835147, 0.10442594, 0.08809479, 0.0850675 ,
       0.09830733, 0.08962348, 0.09245181, 0.08917932, 0.10123809,
       0.09285118, 0.09947602, 0.08600366, 0.08771988, 0.09125393,
       0.12746257, 0.08756904, 0.08823053, 0.09964792, 0.09678454,
       0.09003371, 0.09601028, 0.083643  , 0.08408099, 0.10598933,
       0.09178876, 0.0883993 , 0.09940863, 0.08503959, 0.09110855,
       0.08386391, 0.10344433, 0.10848819, 0.09376665, 0.09971254,
       0.08808091, 0.08950949, 0.10043993, 0.08922101, 0.08797249,
       0.10697058, 0.09634554, 0.11336421, 0.09445611, 0.08233573,
       0.10478567, 0.08686578, 0.12013346, 0.09383889, 0.0958079 ,
       0.09508652, 0.09005851, 0.1363618 , 0.08841272, 0.08376441,
       0.09312193, 0.0863792 , 0.0876364 , 0.09520894, 0.0967493 ,
       0.09097642, 0.08579375, 0.10548148, 0.09197561, 0.10040337,
       0.0843546 , 0.08428753, 0.09301359, 0.12269264, 0.08597878,
       0.08506861, 0.11981855, 0.08482519, 0.08371642, 0.10848585,
       0.09187949, 0.09527899, 0.1014924 , 0.09669203, 0.09059124,
       0.11211398, 0.09591912, 0.0859087 , 0.08789714, 0.09306571,
       0.09647481, 0.08870251, 0.09596522, 0.09571709, 0.11559302,
       0.09837413, 0.09998743, 0.08844309, 0.09326427, 0.12126485,
       0.08870723, 0.08627401, 0.09053123], dtype=float32), array([[[[ 0.01249137],
         [ 0.01230484],
         [ 0.00305863],
         ...,
         [-0.00075438],
         [-0.01255541],
         [ 0.00918152]],

        [[-0.03263822],
         [-0.01009231],
         [-0.0050386 ],
         ...,
         [-0.02342788],
         [ 0.00150926],
         [-0.01052732]],

        [[-0.02785376],
         [-0.02550238],
         [-0.0232511 ],
         ...,
         [ 0.01014469],
         [ 0.00738992],
         [ 0.01555908]]],


       [[[ 0.01100659],
         [-0.00882781],
         [-0.02170436],
         ...,
         [ 0.00835408],
         [-0.01339853],
         [ 0.02553824]],

        [[-0.01906596],
         [ 0.00035902],
         [-0.03146338],
         ...,
         [ 0.00561263],
         [ 0.00516496],
         [-0.02161384]],

        [[-0.02679804],
         [-0.01031173],
         [ 0.01605758],
         ...,
         [-0.00958079],
         [-0.00149062],
         [-0.02014504]]],


       [[[ 0.01148097],
         [-0.01856408],
         [ 0.00075469],
         ...,
         [-0.03429488],
         [ 0.01663213],
         [ 0.0080408 ]],

        [[-0.00066726],
         [-0.02932223],
         [-0.0010218 ],
         ...,
         [-0.04054554],
         [ 0.03024576],
         [ 0.01147315]],

        [[-0.01385228],
         [ 0.00897383],
         [-0.02908582],
         ...,
         [ 0.01224093],
         [ 0.01289113],
         [ 0.00540418]]]], dtype=float32), array([[[[-1.7236806e-02,  3.9285257e-02, -6.1156556e-02, ...,
          -8.1835096e-05, -1.6887054e-02, -5.5606704e-02],
         [ 5.7527341e-02, -4.1563738e-02,  2.2131734e-02, ...,
           1.9549668e-02, -2.2583511e-02, -5.4752260e-02],
         [-7.7853291e-03,  3.6403604e-02, -7.2337493e-02, ...,
          -4.1516762e-02,  4.0373513e-03, -1.5728100e-03],
         ...,
         [ 2.0119667e-02, -1.9057162e-02,  2.0655653e-02, ...,
          -2.1098441e-02, -3.9253838e-02, -1.8611334e-02],
         [ 4.8450325e-03, -3.2536585e-02, -2.4261873e-02, ...,
           2.6559319e-02,  3.0835304e-02, -6.0103763e-02],
         [-5.9680082e-03,  3.0132486e-02,  1.8207232e-02, ...,
           2.2505755e-02, -3.4777507e-02, -3.5460056e-03]]]],
      dtype=float32), array([1.0037073 , 0.98522985, 0.9948086 , 0.9948483 , 1.0055214 ,
       0.9971819 , 0.9885208 , 0.9955408 , 0.9987669 , 0.995125  ,
       0.9944948 , 1.0080674 , 1.002575  , 1.0000693 , 1.0011296 ,
       0.98280585, 0.9871356 , 0.99174094, 0.99629235, 1.0076667 ,
       0.98845476, 0.99281436, 1.0036762 , 0.99762875, 0.99065816,
       1.0082952 , 1.0062394 , 1.0109335 , 0.99721897, 0.9960813 ,
       0.9911371 , 0.9971496 , 1.0129758 , 1.008988  , 1.0165735 ,
       1.0215547 , 0.9971403 , 0.9943562 , 1.0201147 , 0.9947989 ,
       0.99174917, 0.99939877, 1.0038122 , 0.9907226 , 1.012592  ,
       1.0146654 , 1.0023067 , 0.9967269 , 1.0128884 , 0.99776113,
       1.0012764 , 0.98757863, 0.9932681 , 0.9960215 , 0.99542385,
       1.0034568 , 0.999733  , 0.9918812 , 0.9915571 , 0.9979259 ,
       0.98810786, 0.9988169 , 0.995422  , 0.99336874, 1.0052395 ,
       1.0212514 , 0.99588805, 0.98650235, 0.99891347, 0.980965  ,
       1.0141188 , 1.0275074 , 1.0106725 , 0.99459416, 0.9918556 ,
       0.9974223 , 0.9922969 , 1.0019128 , 1.0005914 , 0.993172  ,
       1.0018082 , 1.0042503 , 0.99927676, 1.0042568 , 0.98467124,
       0.9977786 , 0.99214387, 1.0182184 , 1.004731  , 1.0096493 ,
       0.98832965, 0.9926982 , 0.99838483, 0.9990017 , 1.0081953 ,
       0.9995006 , 0.98544633, 0.99399716, 1.0022339 , 0.9898521 ,
       1.0200272 , 0.9992127 , 0.9948638 , 1.0047858 , 0.9912583 ,
       0.99081147, 0.98728347, 0.99570245, 1.005954  , 0.99246883,
       0.9958572 , 1.0043536 , 0.9982714 , 0.99879694, 1.0029213 ,
       0.9882781 , 0.97938657, 1.0184244 , 0.99806356, 1.0068654 ,
       0.99311996, 0.99662185, 0.9908662 , 0.9882987 , 0.9938361 ,
       1.0073167 , 0.99970263, 0.99328065, 0.9965535 , 0.9966085 ,
       1.0118589 , 0.99545175, 0.9929361 , 1.0067339 , 0.9872904 ,
       0.9945491 , 0.9955359 , 0.99411976, 1.0093036 , 1.0032328 ,
       0.9893287 , 0.99430656, 0.9983699 , 0.9983517 , 1.0081166 ,
       1.0039754 , 0.994997  , 0.9873143 , 1.008107  , 0.991956  ,
       1.0004741 , 0.9923478 , 0.9988079 , 1.0090575 , 0.9974198 ,
       0.99836797, 1.0142825 , 0.99225414, 1.0014987 , 0.99614674,
       0.9970666 , 1.0002992 , 1.0016721 , 1.0097336 , 1.005866  ,
       1.0058391 , 1.0206153 , 1.003287  , 1.0013168 , 0.986521  ,
       0.98471385, 0.9958051 , 1.0012323 , 0.9917846 , 1.0196475 ,
       0.9968742 , 0.9934893 , 0.9994245 , 1.0005742 , 1.006303  ,
       1.0067405 , 0.9973439 , 0.9949954 , 0.99461544, 1.0044297 ,
       1.0022811 , 1.005261  , 1.0122206 , 1.0000072 , 0.9962832 ,
       1.0070767 , 1.0042242 , 1.0309684 , 0.99915445, 0.9975946 ,
       0.99432915, 0.9933534 , 0.9946199 , 1.0296767 , 0.99105906,
       0.9897872 , 0.99567205, 1.0050948 , 1.0039515 , 0.99922353,
       0.9960023 , 1.0086617 , 0.9908063 , 0.993551  , 1.0030975 ,
       0.9926198 , 0.99201256, 1.0039587 , 0.9971416 , 0.9991156 ,
       1.0045122 , 0.99241215, 0.9854675 , 1.0073137 , 1.0040325 ,
       0.9836068 , 0.9838076 , 0.99313885, 0.9919734 , 1.0049714 ,
       1.0038923 , 1.0013989 , 1.0120052 , 0.9896345 , 0.9932974 ,
       0.9958647 , 0.99122465, 1.0053724 , 0.9995648 , 0.9895961 ,
       0.99976444, 1.0146645 , 0.99263966, 0.99835163, 1.0107    ,
       0.98757267, 0.9908257 , 0.9993673 , 0.98578256, 0.9993816 ,
       0.9961606 , 1.0030696 , 0.9969313 , 1.0205255 , 0.99708974,
       0.9939309 , 0.9936807 , 1.0077951 , 0.9986422 , 0.9922288 ,
       0.993399  , 0.9876587 , 0.99988556, 0.9921239 , 1.005462  ,
       0.99570274, 0.99290085, 1.0027221 , 0.9940563 , 0.984549  ,
       0.9963641 , 1.0093764 , 1.0037628 , 1.0064307 , 1.0080622 ,
       1.0000571 , 0.9922191 , 0.9996588 , 1.0255783 , 0.9946189 ,
       0.99628025, 0.98525894, 0.9922213 , 1.0073444 , 0.9928688 ,
       0.998371  , 0.99997777, 0.98926157, 1.0016656 , 0.99425113,
       1.0159656 , 0.9935956 , 0.99499035, 1.0134938 , 0.99329245,
       0.99664044, 0.99227846, 1.0018622 , 0.99886614, 0.9979466 ,
       1.0053295 , 0.98899007, 0.99916005, 0.99937594, 0.99076885,
       1.0062025 , 0.99159074, 0.99099684, 0.99681044, 1.010084  ,
       1.0209305 , 0.99734426, 0.99387664, 1.0036724 , 0.99007595,
       0.9991163 , 0.9928997 , 0.9935993 , 1.0214344 , 1.0083214 ,
       1.0169252 , 1.0005327 , 1.0015968 , 1.0098157 , 1.0168059 ,
       1.0005001 , 1.0016223 , 0.9834488 , 0.9860938 , 1.0015341 ,
       0.9904423 , 0.98848426, 1.0016427 , 1.014456  , 0.99340165,
       0.9982542 , 0.9881078 , 0.9982189 , 0.98658425, 1.0069524 ,
       0.9871794 , 0.98969823, 0.9970627 , 0.98749286, 0.996734  ,
       0.99727345, 1.0069654 , 1.0122799 , 0.9936597 , 0.9961804 ,
       0.9880934 , 1.0047932 , 0.9991638 , 0.9926464 , 0.9942773 ,
       0.9993924 , 0.99628246, 1.0140606 , 0.98961884, 0.9875028 ,
       1.0011206 , 0.99017155, 0.99970293, 1.0034235 , 0.98623115,
       1.0094616 , 1.0019695 , 0.995792  , 1.0151951 , 1.0172698 ,
       0.9971254 , 0.99549055, 0.99384195, 1.0061014 , 0.99225324,
       0.9961865 , 0.99760604, 0.99911773, 0.9907973 , 0.99479073,
       1.0012081 , 1.0007834 , 1.0183614 , 0.999518  , 0.9924156 ,
       1.0051408 , 1.0236704 , 0.98830885, 1.0079048 , 1.0016482 ,
       0.98833776, 1.0103313 , 0.999101  , 0.9870704 , 0.9969183 ,
       1.0085014 , 0.9967404 , 0.99035865, 0.9930478 , 0.9896234 ,
       1.016623  , 0.98845434, 1.0019969 , 0.99632436, 0.98754436,
       0.9997521 , 1.0026559 , 0.99895334, 0.99029297, 0.9905138 ,
       1.0005227 , 1.0105008 , 1.0041407 , 0.9970733 , 0.99881804,
       0.98315215, 1.0080682 , 1.0201572 , 1.0098853 , 0.98886985,
       1.0057485 , 1.0026617 , 0.9972028 , 1.0190104 , 1.0187316 ,
       1.0126104 , 0.991421  , 1.0019231 , 1.0019118 , 0.9906186 ,
       0.9985441 , 1.0056126 , 1.0015223 , 0.99978423, 0.9982117 ,
       0.99300086, 1.0306439 , 0.99070543, 1.0069209 , 0.987532  ,
       0.9914204 , 0.9856499 , 0.99513346, 1.0058874 , 1.0042845 ,
       0.9972489 , 1.0073814 , 0.9961439 , 0.9901281 , 0.9907722 ,
       0.98532575, 1.0016739 , 1.0142334 , 1.0057555 , 0.99027497,
       1.0089035 , 0.99327385, 1.0019634 , 1.0027345 , 0.9937871 ,
       0.99650234, 0.99514717, 0.9975719 , 0.98955196, 1.0051606 ,
       1.0174661 , 0.99205685, 0.9872677 , 0.995925  , 0.99562925,
       1.000716  , 1.0116631 , 0.99414873, 1.0150446 , 1.0038767 ,
       1.0198833 , 1.00511   , 0.9969213 , 0.9900972 , 1.0288619 ,
       0.99531096, 0.9876802 , 0.9973677 , 1.0192906 , 0.994866  ,
       0.9857404 , 1.0077286 , 0.9928968 , 0.9770599 , 0.9960625 ,
       0.9980174 , 1.0020177 , 1.0112568 , 1.0227376 , 1.0013134 ,
       1.0028096 , 1.0061746 , 1.0126951 , 0.99979883, 0.99682325,
       0.9985058 , 0.99698347, 0.9900047 , 1.0373679 , 0.9962265 ,
       1.0063584 , 0.9931489 , 0.999745  , 1.0255241 , 1.0075175 ,
       1.0024939 , 0.9841368 , 1.0025893 , 0.99558806, 0.9995837 ,
       0.9994964 , 1.0051233 , 1.0134166 , 1.0020696 , 0.9990094 ,
       1.0375144 , 0.9977587 , 0.99165404, 0.9931746 , 0.984512  ,
       1.0027072 , 0.99905443, 0.99823976, 1.0000086 , 0.99451107,
       1.0052677 , 1.0101881 , 1.0007371 , 1.0117422 , 1.0017809 ,
       0.9963324 , 1.0134431 , 0.991763  , 0.99672383, 0.99084693,
       0.9877191 , 0.99611783, 0.9970212 , 1.0116854 , 1.0142685 ,
       0.99504066, 1.0023749 , 0.9932311 , 0.9945784 , 1.0018133 ,
       0.98846215, 0.99754095, 1.0065249 , 0.99930704, 0.99645555,
       0.9892218 , 0.9872244 , 0.9937218 , 0.98752743, 0.99187154,
       0.9992621 , 0.9910445 , 0.9980307 , 1.0153748 , 0.9987238 ,
       0.99284446, 0.99999285, 1.0037827 , 1.015139  , 1.0037397 ,
       1.0106313 , 0.9974043 , 0.9894833 , 1.009114  , 0.9905913 ,
       0.99508417, 1.0051267 , 0.99416137, 1.002671  , 1.0011109 ,
       1.012131  , 1.0009134 , 0.99516666, 0.9956988 , 0.99852973,
       1.0093478 , 1.0012147 , 1.0072005 , 0.994044  , 0.99504614,
       1.003948  , 1.0121299 , 1.0038091 , 1.0158097 , 0.9959667 ,
       0.99799025, 0.9993589 , 0.99293184, 1.010691  , 0.99818397,
       0.99049836, 1.0121261 , 0.9938534 , 0.990502  , 0.9950466 ,
       0.99376184, 0.98901224, 1.0012025 , 0.9950489 , 1.0085317 ,
       0.99428624, 1.0375957 , 1.0150623 , 0.9946925 , 0.9985869 ,
       1.029804  , 0.9831603 , 1.0054357 , 1.0120099 , 0.9967522 ,
       1.0041158 , 0.9911118 , 0.9984271 , 0.9987619 , 1.0068262 ,
       0.99738723, 0.9858835 , 1.0207862 , 1.0021919 , 0.99383074,
       0.99979824, 0.9932718 , 0.9836902 , 1.0317163 , 0.99714935,
       0.99345255, 0.993008  , 1.0057567 , 0.99758536, 1.0101787 ,
       0.98760706, 0.99386925, 0.9980321 , 0.9990356 , 0.9871018 ,
       0.9972499 , 1.0019903 , 0.9908699 , 0.9987104 , 1.003244  ,
       1.0161976 , 1.0073689 , 0.9938631 , 0.98939997, 1.0051262 ,
       0.99736613, 1.016442  , 0.9902122 , 1.0143108 , 1.0074474 ,
       0.9920826 , 1.0017344 , 1.000505  , 0.98499733, 0.9841337 ,
       0.99116266, 0.9879625 , 1.0000463 , 0.993308  , 1.0125588 ,
       0.9854097 , 1.0019481 , 0.99646115, 0.991633  , 1.0150013 ,
       0.99692154, 0.99435556, 0.9925845 , 1.007866  , 0.99472797,
       0.9934972 , 0.9982106 , 0.9964288 , 0.99815786, 1.0017631 ,
       0.99483764, 1.019998  , 1.010826  , 1.0233481 , 0.9965623 ,
       0.98755187, 0.9903068 , 0.9909407 , 1.0027558 , 1.000701  ,
       1.0069559 , 1.0203767 , 0.99672425, 1.0085273 , 0.99856496,
       0.9869693 , 1.0029324 , 0.9875338 , 1.006219  , 1.0160913 ,
       0.9921315 , 0.99562454, 1.0118151 , 0.99554366, 0.98842156,
       0.99322826, 0.9904702 , 0.9977538 , 0.99858797, 0.99977463,
       1.0056849 , 0.9950567 , 0.9958711 , 0.99468815, 0.9960206 ,
       0.9930616 , 1.0001761 , 1.025992  , 1.0026579 , 0.9921776 ,
       0.99581635, 1.0076586 , 1.0024576 , 0.9911511 , 0.99938667,
       1.0000755 , 1.0016185 , 0.99513745], dtype=float32), array([-7.40656583e-03, -1.85963381e-02, -3.90316080e-03,  1.62164262e-03,
        9.31797177e-03,  2.62631074e-04, -1.38393203e-02, -8.80606286e-03,
        2.09987891e-04, -2.75323726e-03, -4.41361126e-03,  1.43083399e-02,
        1.20777022e-02,  1.57970786e-02,  4.66508092e-03, -8.19761679e-03,
       -1.81990694e-02, -1.31735913e-02, -2.15882678e-02,  3.82704809e-02,
       -2.58384161e-02, -1.96066443e-02,  2.52423659e-02, -1.84666220e-04,
       -9.97074414e-03, -2.37036888e-02,  1.25305774e-03,  2.20489092e-02,
       -5.16154745e-04, -4.08950262e-03, -6.82602590e-03, -3.79685173e-03,
        2.44849250e-02,  2.84772106e-02,  3.92678455e-02, -2.58070063e-02,
       -1.94600094e-02, -1.48582261e-03, -1.61781497e-02,  1.35152526e-02,
       -1.02841929e-02, -3.11366515e-03,  6.56593032e-03, -3.47026139e-02,
        2.44248565e-02, -1.43137258e-02,  2.60925316e-03, -2.25257073e-02,
        1.00903604e-02, -1.20335920e-02,  8.70191783e-04, -1.20365946e-02,
       -8.45369976e-03,  4.50357888e-03, -4.84170392e-03,  1.41531499e-02,
       -9.20762680e-03, -1.12762135e-02, -1.88376906e-03,  6.38771476e-03,
       -6.73211971e-03,  4.03788267e-03, -4.28579655e-03, -8.13459232e-03,
        4.30935435e-03, -2.52524056e-02,  1.30700099e-03, -1.55419121e-02,
       -8.39494914e-03, -1.09427851e-02,  2.17120838e-03,  2.10709255e-02,
        1.61579810e-02, -1.36988042e-02, -1.39693050e-02, -1.01803504e-02,
       -8.54445249e-03,  1.78190158e-03,  1.84121926e-03, -5.84567245e-03,
        4.22834791e-03, -6.98122010e-03, -1.95251266e-03,  4.37103648e-04,
       -9.53487866e-03, -2.25727097e-03, -1.35302348e-02,  6.46180194e-03,
        4.68381541e-03, -2.29100529e-02, -3.81816574e-03, -1.65118314e-02,
       -1.90754533e-02,  6.07192330e-03,  2.06666645e-02,  5.59090462e-04,
       -2.58890335e-02,  6.22750213e-03, -9.47643828e-04, -7.01624027e-04,
       -3.84341716e-03, -4.04842151e-03, -5.83833270e-03,  1.55020168e-03,
        5.92084648e-03, -6.79686526e-03, -2.79910257e-03, -6.97735837e-03,
        7.19328551e-03, -1.48541769e-02,  6.90410263e-04, -1.61321647e-02,
       -8.36064224e-04, -2.85799941e-03,  2.98130815e-03, -7.76347518e-03,
       -1.82271544e-02,  6.96396362e-03, -1.04061151e-02,  8.47743731e-03,
       -4.17745067e-03,  2.89579271e-03, -3.74918664e-03,  1.51534507e-03,
       -1.77763235e-02,  4.69056983e-03,  1.47102866e-03, -3.08587085e-02,
        2.76860804e-03, -4.33766749e-03, -2.66850442e-02, -2.89455242e-03,
       -1.39476070e-02,  2.07494181e-02, -1.51800336e-02,  2.44279299e-03,
       -3.86411266e-04, -2.82312427e-02, -3.65961827e-02,  7.08743511e-03,
       -4.46497602e-03, -7.86134601e-03,  5.85609348e-03, -6.65732659e-04,
       -1.55000053e-02, -1.36354044e-02,  6.37230789e-03, -1.43783111e-02,
       -6.06202148e-02, -3.22789862e-03, -2.71828915e-03,  9.56186187e-03,
       -2.64737830e-02,  3.01243588e-02,  2.93341960e-04, -1.28626707e-03,
        1.37093132e-02, -1.93816191e-03,  7.46860635e-03, -8.48541688e-03,
       -1.09551633e-02,  2.71570892e-03, -7.59633910e-03, -7.14278668e-02,
        1.01172514e-02, -5.06298756e-03,  3.00679822e-03, -2.24119681e-03,
       -1.15930010e-02, -1.53977582e-02, -1.10815810e-02,  3.12939137e-02,
       -8.03338457e-03, -5.44721354e-03,  7.09375367e-04, -8.15699808e-03,
        4.45373822e-03,  1.12425229e-02, -1.32990314e-03,  1.41526675e-02,
       -2.18920503e-02, -1.54126203e-02,  3.45104188e-03, -6.54630270e-03,
        1.96089372e-02,  1.60644413e-05,  5.95497666e-03,  8.82999413e-03,
        9.58796032e-03,  2.38441971e-05,  2.73691420e-03,  1.32468967e-02,
        1.35550303e-02, -1.37891583e-02, -1.27945263e-02, -8.48314352e-03,
       -5.56038460e-03, -2.03600270e-03,  3.10535692e-02, -1.35424817e-02,
        4.20902716e-03, -5.12566825e-04,  1.81421246e-02,  5.95496222e-03,
       -7.00663775e-03, -4.38505318e-03, -4.19785967e-03, -9.79348645e-03,
       -8.67007114e-03, -7.60447234e-04,  1.51034317e-03, -5.86569170e-03,
        1.59582235e-02,  2.46699969e-03,  3.72611545e-03,  2.15781573e-03,
       -2.59113591e-02, -4.53323498e-03, -6.32503629e-03, -1.40861962e-02,
       -1.92900654e-02, -1.41235990e-02,  3.08954832e-03, -6.40316680e-03,
        1.67961381e-02, -6.48413086e-03,  3.82463681e-03, -2.65397155e-03,
       -5.38260443e-03, -1.60441101e-02, -7.57176103e-03, -1.04359500e-02,
        7.65094161e-03,  1.18144620e-02, -6.26022788e-03, -6.78102311e-04,
       -5.97604783e-03, -1.51815871e-02, -2.32859142e-02,  7.83449039e-03,
       -1.09545598e-02, -1.67750148e-03,  7.89982826e-03, -1.14921639e-02,
       -3.59602855e-03, -1.82399666e-03,  1.80052302e-05,  6.52429089e-03,
       -3.54921296e-02,  1.82306138e-03, -1.02101779e-02, -3.52863967e-03,
       -7.33181369e-03, -1.80288905e-03, -5.96440956e-03, -1.10516399e-02,
       -5.46137383e-03, -1.23431254e-02, -1.00131799e-02, -7.79268518e-03,
        1.23187564e-02, -1.33614838e-02,  1.37346806e-02, -9.94445104e-03,
       -9.71556827e-03,  4.67021950e-03,  1.53897619e-02,  1.31535809e-02,
        2.26533506e-02,  1.33737316e-02,  6.00676145e-03, -6.38691662e-03,
        1.26345828e-02, -2.88768727e-02, -1.93170141e-02, -9.64397006e-03,
       -1.14535913e-02, -6.32367656e-03, -3.22291106e-02, -1.45642888e-02,
       -3.85800912e-03,  3.27485078e-03, -8.44976585e-03, -2.55918992e-03,
       -1.31108072e-02,  2.55779214e-02,  1.77993765e-03, -1.86168179e-02,
       -1.17517868e-03, -2.68400228e-03,  1.11489429e-03, -7.15073617e-03,
       -1.29756425e-02, -1.85181070e-02, -1.24991033e-02,  2.14718264e-02,
       -1.07798884e-02, -4.10648482e-03, -5.50805312e-03, -5.97499870e-03,
       -3.86536168e-03, -6.06067758e-03, -6.31564390e-03, -4.67934133e-03,
       -7.52732297e-03,  2.57126223e-02, -6.63105224e-04, -2.68175714e-02,
        2.44908006e-05,  6.75590849e-03,  1.21098319e-02, -6.95827883e-03,
       -9.59366746e-03, -3.29984501e-02,  4.73965378e-03,  1.04065910e-02,
       -4.74639656e-03,  9.52806138e-03,  2.22113822e-02,  2.74716243e-02,
        4.05102922e-03, -1.94342062e-02, -2.57296814e-03, -7.31283147e-03,
       -5.06268116e-03, -1.75918769e-02, -2.66477577e-02,  7.26640783e-03,
        2.64511863e-03, -1.05352765e-02,  1.19281635e-02, -6.78127492e-03,
        3.11251776e-03, -1.27000744e-02,  9.23448894e-03, -8.56455136e-03,
       -8.17842409e-03, -9.00805579e-04, -4.03919145e-02, -1.82956588e-02,
       -1.82912610e-02,  4.18697018e-03,  3.20142843e-02, -2.50015408e-02,
       -5.91018889e-03, -1.92928296e-02,  5.62954089e-03, -2.52823979e-02,
       -3.95484781e-03, -2.59802886e-03, -1.38634741e-02, -6.56913547e-03,
        5.04159182e-03, -4.39813687e-03, -1.22804232e-02,  2.23466870e-03,
        2.31564115e-03,  7.49155600e-03,  9.88182332e-03, -8.44449550e-03,
        4.39610519e-03,  2.11935258e-03,  5.54485992e-03,  1.74786802e-02,
        3.56211253e-02,  1.17789097e-02, -9.55541059e-03, -2.30764295e-03,
        2.61823535e-02, -9.14372597e-03, -4.49503493e-03, -5.77689707e-03,
        1.43496534e-02, -1.24117946e-02, -2.12211479e-02,  5.05757425e-03,
        6.29075617e-03,  1.30560631e-02, -3.96668306e-03, -8.71146005e-03,
       -9.36492439e-03,  2.56148148e-02, -2.51345430e-02,  2.12820098e-02,
       -2.71952190e-02, -1.19566452e-02,  2.19636168e-02, -1.95436995e-03,
       -1.29575580e-02, -3.57143469e-02,  1.97478035e-03, -2.13372963e-03,
        6.73077861e-03, -9.54162795e-03, -1.03297960e-02,  3.15959230e-02,
        3.60613718e-04, -9.52603295e-03, -6.18531602e-03, -9.71203484e-03,
       -5.14360191e-03,  5.68393804e-03,  1.37459068e-02, -1.15045346e-02,
       -1.98650695e-02,  8.12166929e-03, -9.74874012e-03, -1.13492161e-02,
        3.10829096e-03, -3.53913642e-02, -2.38907844e-04,  1.72726233e-02,
        3.79040316e-02, -6.43615518e-03, -1.54749202e-02, -9.32481792e-03,
       -6.38475176e-04, -8.73370562e-03, -8.98088422e-03,  1.89213268e-02,
        3.19848256e-03, -7.02019176e-03, -1.38266608e-02,  5.47696196e-04,
       -4.11241082e-03, -6.14908664e-03,  1.95356198e-02, -2.44220011e-02,
       -9.80610726e-04, -1.16870962e-02,  1.78994946e-02,  1.02951853e-02,
       -1.43125048e-02, -2.81952298e-03, -4.79267677e-03, -1.38617214e-03,
       -6.46343967e-03, -1.79547037e-03, -2.04574462e-04,  4.78664599e-03,
       -1.07722275e-03,  2.12109908e-02, -6.90427958e-04, -7.12820841e-03,
       -6.13893988e-03, -1.05614681e-02,  2.03618803e-03, -2.93179266e-02,
       -1.51380831e-02, -5.07026166e-03, -5.19844284e-03, -1.03718322e-02,
        5.87477768e-03,  1.78363752e-02, -2.69542895e-02, -2.09723040e-02,
       -1.17664714e-03, -9.80831683e-03, -1.93204172e-02, -5.61586209e-03,
        4.37131785e-02, -5.04104234e-03, -1.11640636e-02, -7.47116096e-03,
       -4.61221300e-03,  1.91378556e-02,  1.45476148e-03, -4.48107487e-03,
        1.40799051e-02,  1.49468742e-02, -1.58078838e-02, -5.84249385e-03,
        5.11623966e-03, -5.03950892e-03,  1.80892218e-02, -5.49644278e-03,
       -5.43603022e-03, -1.04679521e-02,  9.04743746e-03,  2.07125698e-03,
        3.27448291e-03, -2.02398770e-03, -4.20062151e-03, -2.32805368e-02,
       -1.61207863e-04, -1.45342378e-02, -2.65229251e-02,  1.55781833e-02,
       -1.58142275e-03, -8.99869556e-05,  2.91155558e-03,  3.77779342e-02,
       -4.00984753e-03,  3.11981793e-02,  9.45766922e-03, -3.90361971e-03,
        2.51871627e-03, -1.96863860e-02, -5.28189465e-02, -2.34245975e-02,
       -8.74125306e-03, -9.65972152e-03, -1.26619376e-02,  2.26311050e-02,
        2.91616227e-02,  6.50831405e-03, -2.85208039e-02, -8.22337251e-03,
       -5.40870754e-03, -7.68310783e-05,  1.78503257e-03, -1.20613687e-02,
       -1.39687369e-02, -3.10845859e-02, -1.61499879e-03, -1.48229748e-02,
       -6.99649053e-03,  6.25976361e-04, -1.56604371e-03, -7.78178172e-03,
        1.14940088e-02, -3.56943496e-02,  4.45055543e-03,  7.29464507e-03,
       -6.65577361e-03,  3.22804004e-02, -1.40383113e-02,  8.52942932e-03,
        3.79052176e-03,  1.31314881e-02,  5.98133868e-03,  2.74063218e-02,
       -1.36946246e-03, -1.73736305e-03,  3.65561363e-03, -1.52060529e-02,
       -3.57950665e-02,  5.54026710e-03, -1.16010765e-02,  7.19818333e-03,
        5.15783858e-03,  1.14037860e-02,  4.76604421e-03, -1.96004938e-03,
        6.36078697e-03, -1.53335584e-02, -3.04671004e-03, -1.00814532e-02,
        2.82663968e-03, -4.68734372e-03, -1.73967388e-02, -9.09179170e-03,
        5.50688128e-04, -1.06194206e-02, -8.05533212e-03, -3.83533910e-02,
       -9.12612583e-03, -1.52138527e-02,  2.19049770e-03, -1.33484340e-04,
       -1.25455568e-02,  4.49162116e-03,  3.09649343e-03, -1.13760224e-02,
       -7.15615321e-03,  1.20136440e-02, -3.64888050e-02, -9.23004840e-03,
        3.04096658e-02, -1.12829572e-02, -3.50248255e-02,  1.10787451e-02,
        3.89344105e-03,  2.99790432e-03,  6.40640408e-03,  6.86257612e-03,
       -6.00973610e-04, -1.95297028e-03, -3.00602126e-03, -2.37989109e-02,
       -7.51056289e-03, -2.31180675e-02, -2.56074648e-02, -1.02648083e-02,
        2.53055561e-02, -3.01557053e-02,  2.83342749e-02,  1.25395507e-02,
       -2.22929358e-03, -4.99168150e-02,  2.13847999e-02, -2.54677981e-02,
       -9.56544746e-03,  5.03691584e-02, -2.56923749e-03, -4.64992924e-03,
       -1.27819935e-02, -1.07567310e-02, -1.67623144e-02, -1.13306139e-02,
        4.73927765e-04, -1.12087131e-02,  1.01189418e-02, -2.76505784e-03,
       -5.14938980e-02,  8.81711952e-03,  1.75577346e-02,  2.75835730e-02,
       -5.08267293e-03,  1.24958642e-02, -3.95021625e-02, -1.99446976e-02,
        3.74091230e-03,  5.98071143e-03, -1.36861941e-04,  6.94773300e-03,
       -9.30530764e-03, -3.27889039e-03,  1.88405777e-03, -9.35246702e-03,
        7.28962361e-04, -4.54474287e-03, -1.10138822e-02, -7.24623259e-03,
       -9.13357176e-03, -8.23126175e-03, -1.15102138e-02, -6.35126652e-03,
       -2.58635730e-02, -4.15661326e-03, -7.20248558e-03,  8.11555889e-03,
        1.93635691e-02,  1.21735437e-02, -4.22361419e-02, -6.64910488e-03,
        2.34348746e-03, -1.72266290e-02, -2.48288903e-02, -1.44231971e-02,
        5.92780067e-04,  2.17854585e-02, -1.40797282e-02,  1.14911664e-02,
        8.04538652e-03, -2.92767789e-02, -2.01653130e-02,  6.59908541e-03,
       -2.49921102e-02,  8.90651718e-03, -3.50261144e-02,  1.36495670e-02,
       -9.03699361e-03, -2.85053533e-02,  1.62309017e-02, -1.15799382e-02,
        8.11730418e-03, -1.88074377e-03, -6.61068177e-03, -1.56666785e-02,
       -8.09349306e-03,  2.38768780e-03, -1.37183256e-03, -9.52527858e-03,
       -1.05980523e-02, -2.28722505e-02, -7.11263996e-03, -3.27287568e-03,
       -9.01657064e-03,  2.04585791e-02, -3.32288654e-03, -8.95637926e-03,
       -1.87856294e-02, -2.67592538e-02, -1.95768233e-02, -1.38652381e-02,
        5.91887254e-03, -2.22943869e-04,  2.46698176e-03, -3.17337476e-02,
       -4.65324055e-03, -3.26966308e-02, -1.89167149e-02,  2.62890733e-03,
        7.88722746e-03, -1.50647806e-02, -3.09973955e-02, -1.55585017e-02,
        4.58422070e-03, -1.50967687e-02,  1.42630795e-02,  2.67843641e-02,
       -2.37459373e-02, -1.41384394e-03, -3.06473370e-03, -1.87200438e-02,
       -2.08224659e-03, -1.60494503e-02, -2.24968176e-02, -3.84719227e-03,
        2.87169334e-03,  3.16015398e-03, -5.45548275e-03, -4.34855232e-03,
       -1.17172729e-02, -6.70018094e-03, -6.61040004e-03, -6.15148223e-04,
        1.59975886e-02,  6.62996527e-03,  1.23666860e-02, -1.11404597e-03,
       -7.88261462e-03, -1.13252015e-03, -1.00626452e-02,  2.97681871e-03,
        1.00994157e-02,  8.63253884e-03, -1.60923775e-03, -7.59250671e-03,
       -2.19095644e-04,  2.83532795e-02, -2.79802419e-02,  2.03843089e-03,
        1.28381336e-02,  1.19662164e-02,  1.30448984e-02, -9.43737198e-03],
      dtype=float32), array([ 2.58817166e-01,  1.28260061e-01, -4.41621207e-02, -2.25400612e-01,
       -3.01807784e-02,  7.08680972e-02,  1.09821998e-01,  1.48539394e-01,
       -2.24566180e-02, -1.30802885e-01, -1.20843425e-01, -1.64782897e-01,
       -4.04909439e-03, -2.68089473e-01, -6.66823536e-02,  1.52172625e-01,
        1.79480493e-01, -2.84955185e-02,  2.93373048e-01, -1.88514397e-01,
       -1.07031070e-01, -1.61522463e-01, -2.29779601e-01,  4.41121086e-02,
        1.22017071e-01, -3.00517697e-02, -1.42982513e-01, -1.41020790e-01,
        2.38329947e-01,  7.40007013e-02,  7.47878551e-02,  5.46057746e-02,
       -6.82723150e-02, -1.71487376e-01, -1.14065804e-01,  1.16961531e-01,
        2.27783829e-01,  8.49614199e-03,  1.46515176e-01, -2.15749204e-01,
        2.15113178e-01, -2.45526329e-01, -1.38227671e-01,  1.56917185e-01,
       -6.11323630e-03, -7.08227009e-02, -1.05131127e-01,  2.09191859e-01,
       -5.77652976e-02, -2.02563167e-01, -9.07608792e-02,  1.32457778e-01,
        1.45056307e-01, -1.19698443e-01, -2.44607832e-02, -2.61625767e-01,
        1.69225708e-01, -1.30070522e-01, -9.30136591e-02, -5.38021028e-02,
       -1.57006770e-01, -1.44493461e-01, -1.35595933e-01, -1.46561190e-01,
       -1.18959501e-01,  3.06583107e-01, -2.83246636e-01, -3.45356673e-01,
       -7.87745491e-02,  1.46595255e-01,  2.23164082e-01,  7.86988959e-02,
       -5.41806333e-02,  1.56774342e-01, -1.27387121e-01,  4.91034724e-02,
        2.87423670e-01, -1.70127347e-01, -8.57847854e-02, -3.11701775e-01,
        5.50489314e-02, -1.92060485e-01,  3.16536278e-02,  1.70195833e-01,
        1.77543566e-01, -1.82816312e-01,  9.50835273e-02,  1.21111400e-01,
       -1.19744375e-01,  2.41012380e-01, -8.22596997e-02, -1.35664597e-01,
        2.78755486e-01, -1.76967770e-01, -1.36599362e-01, -1.35989606e-01,
        2.28176475e-01, -5.08203134e-02, -1.67270780e-01, -1.39828935e-01,
       -4.43890095e-02, -1.25868767e-01, -2.83440351e-02,  1.62270203e-01,
       -2.17580646e-01,  4.12699617e-02, -5.73804937e-02,  8.75836462e-02,
       -1.62286520e-01,  1.49965018e-01, -1.36753976e-01,  1.55935824e-01,
       -9.55994055e-02, -1.01714298e-01, -6.32807016e-02,  6.21031523e-02,
        2.60276496e-01,  2.38915488e-01,  1.58251762e-01,  8.27317536e-02,
       -1.83546349e-01, -1.98532268e-02, -2.88827896e-01,  3.77617180e-02,
        7.84038901e-02, -1.12036631e-01,  9.23857540e-02,  2.58024722e-01,
       -1.54593095e-01,  1.24700181e-01,  2.77622521e-01, -5.93414679e-02,
        1.79902717e-01, -9.60012451e-02, -2.98923254e-01,  1.20838806e-01,
       -2.95094162e-01, -6.71188459e-02,  3.10978770e-01, -1.60639524e-01,
        1.23279884e-01,  9.84007716e-02,  7.23636895e-02, -1.81237802e-01,
        1.35782316e-01, -8.03398341e-02, -1.08366743e-01,  2.08343416e-02,
        3.69282871e-01, -2.24724486e-01,  1.38311282e-01, -4.70069163e-02,
        2.95545459e-01,  1.81519017e-02, -1.77573577e-01, -2.10336268e-01,
       -2.29024477e-02,  2.60276925e-02, -3.68910916e-02, -9.83613804e-02,
        2.42358893e-01, -1.15000792e-01,  2.15151444e-01,  2.81860441e-01,
        1.29209291e-02, -1.19901881e-01,  1.41579732e-01,  3.50132883e-02,
        2.07904503e-01, -1.14814602e-01, -1.22939095e-01, -9.01491269e-02,
        2.16137748e-02,  6.94297627e-02,  8.06207061e-02,  7.14677647e-02,
       -2.01284558e-01, -1.12531617e-01,  2.71537244e-01, -7.47707635e-02,
        2.77355283e-01,  2.44143382e-01,  1.13675989e-01, -4.92163487e-02,
       -1.59652263e-01,  1.04808360e-01,  1.14849947e-01,  3.69287394e-02,
        8.01484063e-02, -2.64402460e-02,  5.43174893e-02, -2.52507031e-01,
        5.55399358e-02,  8.83033499e-02,  1.26080468e-01, -7.77824875e-03,
       -2.11161450e-01,  1.54064596e-01,  1.04722798e-01, -1.00984804e-01,
        7.05352798e-02, -5.77377006e-02, -8.28669295e-02, -1.33557111e-01,
        6.04458712e-02,  1.04668306e-03, -3.68241109e-02, -3.04684341e-02,
       -1.75604746e-01, -1.64025635e-01, -4.43477780e-02, -1.30476728e-01,
        5.66529296e-03, -2.28468522e-01,  2.09452718e-01,  5.40359803e-02,
        2.62974113e-01,  1.99645199e-03,  1.84649870e-01,  2.10239589e-01,
       -8.15909356e-02, -9.40205976e-02, -1.91067427e-01, -6.62688091e-02,
        1.66171148e-01,  2.07162246e-01, -3.21528055e-02,  2.52269383e-04,
       -7.93668553e-02,  6.40622228e-02, -2.75112659e-01,  1.62143588e-01,
       -5.84586821e-02,  1.42147683e-03, -1.09033860e-01, -1.57701895e-01,
        2.34214544e-01,  3.03528495e-02,  6.17728978e-02, -2.12084681e-01,
        1.34218216e-01,  7.64818341e-02, -2.12316334e-01,  3.06246690e-02,
        7.81559348e-02, -8.35398063e-02,  2.04084843e-01, -5.32108247e-02,
        3.24221939e-01,  9.32023823e-02, -7.24824443e-02, -1.33084625e-01,
       -1.92407280e-01,  1.36156783e-01,  2.57350236e-01,  1.70635670e-01,
       -1.34240566e-02, -3.41959804e-01, -1.23910636e-01,  7.94601366e-02,
        1.68525547e-01, -2.43974645e-02, -1.18684858e-01,  7.94177800e-02,
        2.53347397e-01, -1.42705232e-01, -1.74484685e-01, -1.22384556e-01,
       -2.67332017e-01, -2.40406498e-01, -9.18067023e-02,  1.48920983e-01,
       -8.92565027e-02,  2.06861004e-01,  5.86321093e-02,  1.36053488e-01,
        2.15837553e-01,  5.93661740e-02, -9.91093814e-02,  1.19575731e-01,
       -1.36503711e-01, -9.75375623e-03,  1.54209547e-02, -2.63079088e-02,
       -6.86336160e-02, -1.03693545e-01, -2.05158651e-01,  2.76102155e-01,
        1.24249724e-03,  5.38335964e-02, -1.27715111e-01, -9.60190222e-02,
        8.19892436e-02,  2.35936120e-02, -1.15716472e-01, -1.62307084e-01,
        9.51216742e-02,  2.64295787e-01, -3.59330326e-02, -1.27610803e-01,
       -3.21320854e-02,  1.40262276e-01, -8.85751694e-02,  7.16744140e-02,
        3.52765583e-02, -3.65145840e-02, -7.50757456e-02,  1.57453343e-01,
       -5.88292629e-02, -2.07935184e-01, -2.40901038e-02,  1.30607098e-01,
        1.90796629e-01,  3.03080201e-01, -3.92901711e-02, -2.91397627e-02,
       -1.55886382e-01, -6.99581876e-02, -2.39318669e-01, -1.88376810e-02,
       -1.30067661e-01,  1.24658726e-01, -2.96471193e-02,  1.87394500e-01,
        1.55087009e-01, -1.39948010e-01,  1.27112985e-01, -9.65175778e-02,
       -1.49751112e-01, -1.34189814e-01, -1.49607033e-01,  8.79273191e-02,
       -6.40968978e-02, -1.58511579e-01, -1.24113008e-01,  2.15823337e-01,
        9.79214907e-02, -5.84225617e-02,  3.64390880e-01,  1.30089119e-01,
        1.72259837e-01,  1.53807402e-01, -2.80243587e-02,  3.96525003e-02,
       -1.03910521e-01,  1.13368437e-01, -1.00834072e-01,  2.48651996e-01,
       -3.50554772e-02, -1.21116228e-01,  1.82440743e-01,  2.10617743e-02,
        1.49667859e-01,  9.33743492e-02,  1.57754228e-01, -2.70071756e-02,
       -8.67759362e-02, -1.13603309e-01, -2.26201266e-01,  1.39272764e-01,
        1.79513738e-01,  6.72074705e-02, -2.52628386e-01,  2.08058897e-02,
       -1.02094576e-01, -4.51791883e-02,  3.54310423e-02, -4.42366302e-02,
        1.44513161e-03,  1.12711720e-01, -9.37907398e-02,  1.17013186e-01,
       -1.68422729e-01,  3.97495786e-03,  2.25327626e-01, -1.94601789e-01,
       -2.20123261e-01, -1.14888854e-01,  2.18564719e-01, -8.06408096e-03,
        1.40491739e-01,  1.45841673e-01,  2.16778368e-01, -9.90531817e-02,
       -1.29633978e-01, -4.83184792e-02, -1.05331682e-01, -1.06136620e-01,
        6.25234321e-02,  2.20427513e-01, -1.40352845e-01,  3.69906537e-02,
        2.36768365e-01, -7.01456368e-02, -5.43340482e-02, -7.55467499e-03,
        1.07186966e-01, -1.58361435e-01, -4.69071679e-02, -5.25500700e-02,
        1.07262738e-01, -3.26125398e-02, -7.82896206e-02,  3.31355929e-02,
        2.16951266e-01, -5.20089567e-02,  2.01611489e-01,  1.79668918e-01,
       -1.50218993e-01,  2.32009694e-01,  7.99891129e-02, -2.39724904e-01,
       -9.07371342e-02,  8.76805484e-02, -2.21842244e-01,  1.52250171e-01,
        2.79366910e-01,  7.89532959e-02,  1.64719194e-01, -1.08244136e-01,
        1.80718005e-01,  2.37089336e-01, -1.09381981e-01,  9.80211869e-02,
       -1.45233765e-01,  1.64937824e-01, -1.01911679e-01,  1.57401636e-01,
       -2.71669626e-01,  7.26645738e-02, -1.17059998e-01,  7.40604699e-02,
        2.42522523e-01,  1.28958225e-01,  1.56052157e-01,  9.23030078e-02,
       -5.04693538e-02, -1.03486508e-01,  1.70312732e-01,  8.49682093e-02,
       -2.70837307e-01,  3.75249307e-04, -1.33308932e-01, -1.94041535e-01,
       -1.93490654e-01, -8.90023857e-02,  2.24577766e-02,  1.46036536e-01,
        5.33908308e-02,  1.54625267e-01,  1.29570484e-01, -4.44509648e-02,
       -3.61978412e-02, -1.40315950e-01, -8.28761235e-02,  2.36409009e-01,
        8.06848556e-02,  8.66181329e-02,  9.55611989e-02,  1.43716186e-01,
       -1.11075580e-01, -1.00558512e-01, -5.50173782e-02,  5.36379106e-02,
        1.49466127e-01, -2.20011279e-01, -2.40764115e-02, -1.47989139e-01,
       -1.59933820e-01,  5.06620817e-02,  2.52767622e-01, -8.36579949e-02,
       -8.84103179e-02, -1.60599828e-01,  1.45331338e-01, -2.39352770e-02,
        2.40023956e-02,  1.47210872e-02, -1.29232600e-01, -2.25979239e-01,
        1.63347796e-01,  1.47573456e-01, -1.53393403e-01,  7.75938481e-02,
       -1.62225753e-01,  1.87083572e-01, -5.11087552e-02, -5.70048112e-03,
        1.18110411e-01, -2.01932862e-02, -1.34714276e-01, -1.06382564e-01,
        2.40517245e-03, -6.20278493e-02, -8.56044069e-02,  1.56653807e-01,
       -8.04726407e-02,  1.79807201e-01,  3.43017340e-01,  2.43522689e-01,
        1.54137956e-02,  4.84781340e-02,  7.65909329e-02,  3.08632571e-02,
       -1.43930390e-01, -8.95143822e-02,  1.35036588e-01,  1.90100357e-01,
       -1.88271716e-01, -4.07393388e-02, -2.10178465e-01, -5.97904921e-02,
        1.17764629e-01,  1.38450995e-01, -8.20935052e-03,  8.57565850e-02,
       -7.43869983e-04,  4.21116874e-02, -2.26691086e-02,  1.49545133e-01,
        4.65647727e-02,  3.82705361e-01, -3.51355076e-02, -8.67895931e-02,
       -1.99174270e-01,  1.88492483e-03,  1.58734336e-01, -1.07160889e-01,
        1.19782329e-01, -7.06219450e-02, -1.10682525e-01, -8.62174407e-02,
       -1.73026919e-01, -8.78720060e-02, -1.48259550e-01,  6.43558893e-03,
        4.89911228e-01, -2.04571083e-01, -3.29675525e-02, -2.17145700e-02,
        1.27191152e-02, -2.83938110e-01,  7.51828700e-02,  1.56749822e-02,
       -2.38702148e-01, -2.60526717e-01, -8.79987776e-02,  2.54764780e-02,
       -5.69466949e-02, -1.89526796e-01,  1.69316962e-01, -9.79857892e-02,
       -1.50097266e-01, -2.17863083e-01,  9.05278847e-02,  3.98969412e-01,
       -9.65682939e-02,  1.73161179e-01,  5.88501878e-02, -2.22779855e-01,
       -9.41027775e-02, -3.34461108e-02, -8.39915276e-02,  7.53594786e-02,
        7.69337118e-02, -1.07887238e-01,  2.16937497e-01,  1.67063728e-01,
       -1.47998005e-01,  2.16966778e-01, -1.07336052e-01, -2.85431445e-02,
       -1.46344990e-01,  5.72138727e-02,  6.14331141e-02,  4.89701293e-02,
        1.40821129e-01, -1.86747223e-01, -1.17451444e-01,  3.49201649e-01,
        1.54915914e-01,  1.14521220e-01,  1.21696867e-01, -4.54735048e-02,
       -1.63365364e-01,  1.72725156e-01,  3.07463538e-02, -1.62760183e-01,
       -1.63362741e-01,  3.45836043e-01, -7.48198181e-02,  2.58511961e-01,
       -1.21050172e-01, -1.57781899e-01, -2.93894690e-02, -3.39264236e-02,
        1.16231836e-01,  1.35063767e-01,  1.79171965e-01, -9.91681293e-02,
        5.41507974e-02,  1.40846103e-01,  6.52159452e-02, -3.78550962e-02,
        1.75671905e-01, -5.71034737e-02, -4.43885736e-02, -9.90851521e-02,
        2.50236206e-02, -1.17652342e-02,  2.67053515e-01,  1.36755243e-01,
        6.96502700e-02, -6.25874475e-02, -3.54773626e-02,  6.70088530e-02,
       -8.42823684e-02, -1.65195778e-01, -1.28797814e-01,  1.00784950e-01,
        4.59389463e-02,  2.98135262e-02,  7.32832104e-02,  2.00507179e-01,
       -8.73557702e-02, -5.67433052e-03, -1.90703779e-01,  7.26061165e-02,
        4.35851544e-01, -1.67060331e-01,  9.96136442e-02, -1.07788898e-01,
       -1.31189032e-02, -1.32715449e-01,  2.73322165e-01,  3.69050950e-02,
       -7.56707713e-02,  6.75686151e-02,  1.52075380e-01, -6.27221167e-02,
        8.89901519e-02, -1.57050356e-01,  1.98405445e-01, -1.34635508e-01,
       -4.84394133e-02,  3.25505763e-01,  2.40644827e-01, -5.64020611e-02,
       -1.41617097e-03,  2.88565028e-02,  1.28086761e-01,  1.83435559e-01,
        1.22929342e-01,  2.66798884e-01, -4.91086021e-02,  1.55922145e-01,
       -5.97649328e-02, -3.36671174e-01, -2.30633229e-01,  2.45531395e-01,
        5.16992388e-03, -7.71872401e-02, -4.48071994e-02,  4.98542003e-03,
       -4.71731611e-02, -5.25434017e-02, -2.41788439e-02,  2.69677848e-01,
        1.62851021e-01,  1.79167271e-01, -6.27407059e-02,  1.90463495e-02,
        1.16901450e-01,  2.38538876e-01,  1.79455817e-01, -1.42292917e-01,
       -2.63125271e-01,  1.73297480e-01, -8.88614729e-02,  1.49664223e-01,
        1.53544262e-01,  5.30860007e-01,  6.21023364e-02,  2.99815595e-01,
        1.33046314e-01,  3.38718258e-02,  4.74032573e-02,  1.60366744e-01,
        1.32085711e-01, -1.76036164e-01,  4.09871973e-02, -3.46638337e-02,
        1.26713648e-01,  2.02711344e-01, -1.03175066e-01, -2.00790867e-01,
       -6.24829009e-02, -2.41514131e-01,  1.92634672e-01,  1.89395860e-01,
       -1.74100891e-01, -1.62395597e-01,  1.32768616e-01, -1.81028008e-01,
        1.32222474e-01, -6.57201782e-02,  2.89479680e-02,  1.34109512e-01,
       -1.13060288e-01, -2.27856666e-01,  3.04015856e-02,  2.27287002e-02,
        1.70467764e-01,  3.65979075e-02,  1.50453433e-01, -1.58258900e-01,
       -2.20529869e-01,  5.51356375e-02, -1.69964463e-01, -6.62947744e-02,
       -9.05647874e-02, -9.77385566e-02,  2.09259495e-01, -1.00461327e-01,
       -1.22738473e-01, -3.38109769e-02,  1.69163063e-01,  2.29178086e-01],
      dtype=float32), array([0.2628246 , 0.25889444, 0.17865627, 0.4248553 , 0.28905597,
       0.18029633, 0.1511457 , 0.2939201 , 0.10617677, 0.24329548,
       0.45629743, 0.52894753, 0.49391645, 0.54122967, 0.22479981,
       0.26693678, 0.46643835, 0.35284033, 0.64352757, 0.34649807,
       0.36285374, 0.3834878 , 0.7854376 , 0.16857958, 0.26275256,
       0.76073265, 0.38827574, 0.48014235, 0.37088835, 0.22467211,
       0.3370087 , 0.26637182, 0.22582492, 0.64727783, 0.49934018,
       0.39428812, 0.37201288, 0.2800297 , 0.31368074, 0.81803215,
       0.62539876, 0.34431002, 0.20792107, 0.39103737, 0.39224127,
       1.1799124 , 0.27305183, 0.5020223 , 0.21485943, 0.8568806 ,
       0.24217185, 0.29276177, 0.21505132, 0.5531763 , 0.17736603,
       0.653379  , 0.35419276, 0.13585794, 0.18143326, 0.21714662,
       0.34523508, 0.28137174, 0.1804729 , 0.21997298, 0.6287723 ,
       1.0717903 , 0.5253319 , 1.1269758 , 0.7077878 , 0.28989348,
       0.45885888, 0.55551887, 0.3085287 , 0.46190086, 0.20758858,
       0.14875321, 1.0149972 , 0.1547572 , 0.20538998, 0.7344237 ,
       0.22597738, 0.25917232, 0.23045361, 0.51911145, 0.3398393 ,
       0.5855553 , 0.13216917, 0.18791988, 0.35679162, 0.43227184,
       0.26473603, 0.53311276, 0.52319   , 0.53581065, 0.599725  ,
       0.3881006 , 0.70105743, 0.20630619, 1.3681009 , 0.5945201 ,
       0.7502437 , 0.401337  , 0.12089791, 0.20669939, 0.6829578 ,
       0.1945989 , 0.20815615, 0.30898327, 0.47021562, 0.19896221,
       0.1882722 , 0.6418206 , 0.19922403, 0.2687506 , 0.19695106,
       0.18999277, 0.4323225 , 0.5252479 , 0.326248  , 0.49963275,
       0.46924302, 0.20365098, 0.93486065, 0.13861503, 0.29341152,
       0.24689078, 0.35560733, 0.34569743, 0.2139981 , 0.4092737 ,
       0.3700184 , 0.1987112 , 0.41060865, 0.54224545, 0.56803095,
       0.22626723, 0.47853002, 0.82539433, 1.3951749 , 0.23078287,
       0.5010107 , 0.3545562 , 0.19929425, 0.32480326, 0.26581854,
       0.28765616, 0.17590961, 0.17934489, 1.3597698 , 0.50639534,
       0.29042986, 0.25621375, 0.9525213 , 0.22695196, 0.23897779,
       0.4538189 , 0.23427984, 0.16557747, 0.33007863, 0.16582376,
       0.49448052, 0.15467754, 1.0160798 , 0.65706766, 0.20193441,
       0.5902369 , 0.43712777, 0.17822862, 1.5176287 , 0.59183997,
       0.16269785, 0.41520032, 0.25558266, 0.32829732, 0.40908012,
       0.28359187, 0.23118544, 0.31952643, 0.40507382, 0.27409634,
       0.4806559 , 0.65074605, 0.29915974, 0.2126322 , 0.8101267 ,
       0.14237662, 0.45032573, 0.4868123 , 0.34339887, 0.20455746,
       0.32995993, 0.53346735, 0.17973281, 0.23840171, 0.22129603,
       0.62150836, 0.22654559, 0.3371173 , 1.0498192 , 0.17866346,
       0.35285625, 0.20186603, 0.49690077, 0.24555607, 0.42823455,
       0.1714595 , 0.23308584, 0.1812634 , 0.22105555, 0.28634766,
       0.19229425, 0.2954382 , 0.28783405, 0.48698905, 0.49880758,
       0.30869016, 1.2654583 , 0.14983493, 0.38986468, 0.26854843,
       0.56373185, 0.32769194, 0.5689818 , 0.1319138 , 0.74836135,
       0.351386  , 0.13576472, 0.67347246, 0.25035483, 0.300206  ,
       0.7201854 , 0.20887445, 0.20089832, 0.42780742, 0.15181775,
       0.35231474, 0.26885885, 0.17796102, 0.2156874 , 0.25649303,
       0.42151555, 0.3843969 , 0.31198388, 0.38349384, 0.36662543,
       0.23310634, 0.4412572 , 0.32574418, 0.74090785, 0.23053366,
       0.27182332, 0.19858588, 0.2969459 , 0.3373107 , 0.47149175,
       0.20405489, 0.144018  , 1.1049482 , 0.2156066 , 0.522706  ,
       0.49260038, 0.52927893, 0.34508878, 0.2806437 , 0.43723384,
       0.2396088 , 0.39332056, 0.5460543 , 0.6926521 , 0.5555858 ,
       0.22237138, 0.38528425, 0.17606956, 0.5829696 , 0.16718306,
       0.24081162, 0.20722075, 0.12162919, 0.9266567 , 0.3757712 ,
       0.21789025, 0.18520997, 0.13776296, 0.16798906, 0.16758648,
       0.5546452 , 0.32456157, 0.75261104, 0.24912417, 0.20092875,
       0.32082945, 0.1648718 , 0.22299413, 0.22326782, 0.3981288 ,
       0.35925618, 0.30756983, 1.0032258 , 0.09954882, 0.4564741 ,
       0.38073108, 0.2719191 , 0.22259705, 0.27678296, 0.58679575,
       0.41839445, 0.32215798, 0.3282718 , 0.19162352, 0.3342654 ,
       0.18355472, 0.30080274, 0.33036438, 1.121696  , 0.1271762 ,
       0.30756173, 0.39862692, 0.44156918, 0.82196414, 0.43223256,
       0.2662245 , 0.35342354, 0.09903885, 0.40474975, 0.35089132,
       0.30996743, 0.20556943, 0.30183196, 0.13292164, 0.21080428,
       0.3676775 , 0.28129476, 0.2541334 , 0.3564778 , 0.41279966,
       0.37678537, 0.26531872, 0.3329837 , 1.0463388 , 0.24781303,
       0.3437741 , 0.42092252, 0.36058342, 0.3632147 , 0.22553807,
       0.2115966 , 0.1844745 , 0.40466467, 0.16862023, 0.45359465,
       0.66923255, 0.1581341 , 0.26164252, 0.15111943, 0.23161873,
       0.30226132, 0.3341722 , 0.20964606, 0.4936025 , 0.387587  ,
       0.2531701 , 0.12112582, 0.6237794 , 0.1990107 , 0.26660514,
       0.40300617, 0.19689347, 0.15054643, 0.31739908, 0.4660518 ,
       0.23315696, 0.3554738 , 0.5273084 , 0.15909855, 0.46190342,
       0.3945067 , 0.55566204, 0.43949562, 0.33502543, 0.14315023,
       0.5149111 , 0.37628818, 0.69480735, 0.4181192 , 0.92919505,
       0.17828315, 0.3202227 , 0.17365326, 0.1542966 , 0.7553217 ,
       0.23265916, 0.14574519, 0.5650304 , 0.17381665, 0.1056975 ,
       0.3133579 , 0.21434765, 0.2894807 , 0.12283716, 0.23231195,
       0.42326996, 0.12614559, 0.2741339 , 0.14224117, 0.88652194,
       0.13979828, 0.5212857 , 0.26884043, 0.8129844 , 0.43892336,
       0.28456116, 0.42059642, 0.3103595 , 0.23610505, 0.21694903,
       0.21422072, 0.44988537, 0.15247007, 0.33323687, 0.37611213,
       0.49140802, 0.5246431 , 1.151724  , 0.24535336, 0.2410014 ,
       0.24489222, 0.30225685, 0.48468217, 0.42514712, 0.23740824,
       0.30871505, 0.24288352, 0.57363755, 0.15455203, 0.39942756,
       0.25659397, 0.1715994 , 0.26336494, 0.45000395, 0.4117494 ,
       0.48198748, 0.26735848, 0.34289768, 0.46442193, 0.2950746 ,
       0.17663239, 0.13520037, 0.19692351, 0.3848326 , 0.5133765 ,
       0.3315139 , 0.13289694, 0.22210085, 0.5058991 , 0.6251601 ,
       0.39443782, 0.21540904, 0.27453902, 0.3741853 , 0.34736273,
       0.7261209 , 0.42442325, 0.24983488, 0.19234073, 0.25058836,
       0.9161777 , 0.31096822, 0.4683772 , 0.44984937, 0.3626846 ,
       0.28936863, 0.52030647, 0.31784835, 0.19212244, 0.44979462,
       0.15251072, 0.1323405 , 0.10442281, 0.27489054, 0.3679614 ,
       1.2088097 , 0.24476142, 0.411287  , 0.15936601, 0.29856277,
       0.28010532, 0.559603  , 0.46945187, 0.1916062 , 0.26587403,
       0.473523  , 0.29135883, 0.3141269 , 0.29383817, 0.3945519 ,
       0.19356947, 0.3855881 , 0.43567246, 0.77414125, 0.7127231 ,
       0.32492432, 0.15354498, 0.28003672, 1.2205554 , 0.27859864,
       0.26783133, 0.24413528, 0.3798003 , 0.35912436, 0.19215058,
       0.3019679 , 0.22687311, 0.30066267, 0.40204754, 0.20639624,
       0.32851595, 0.27093464, 0.34784293, 0.10698614, 0.8620023 ,
       0.6996844 , 0.6555907 , 0.27195486, 0.30451587, 0.6961087 ,
       0.2677542 , 0.3061765 , 0.40381607, 0.36731097, 0.39549726,
       0.59880185, 0.5533403 , 0.33056873, 0.28435913, 0.6746633 ,
       0.2037188 , 1.4390681 , 0.7258138 , 0.20879154, 0.29498988,
       0.15738542, 1.2647082 , 0.28715557, 0.10984856, 0.3456967 ,
       0.6196898 , 0.40580425, 0.3445599 , 0.46222103, 0.29758722,
       0.26802474, 0.2919977 , 0.2624101 , 0.47145873, 0.29275414,
       0.6493555 , 0.21284825, 0.30967373, 0.3317626 , 0.6453985 ,
       0.22183576, 0.16349122, 0.20666003, 0.42027178, 0.17264372,
       0.46144107, 0.44594133, 0.33789086, 0.6960892 , 0.53263277,
       0.27468807, 0.2515157 , 0.28952426, 0.2773908 , 0.26279706,
       0.3552832 , 0.25625476, 0.46557474, 0.26155886, 0.65872824,
       1.1203738 , 0.3760713 , 0.45059368, 0.15521754, 0.38404974,
       0.54801536, 0.30224013, 0.36180472, 1.3641286 , 1.0531181 ,
       0.46202037, 0.6016436 , 0.22583243, 0.9195105 , 0.10525091,
       0.19265142, 0.2278962 , 0.3861243 , 0.44922075, 0.21216686,
       0.35711014, 0.38955352, 0.20107588, 0.20318212, 0.4146547 ,
       0.16253702, 0.3782285 , 0.40344557, 0.1682446 , 0.28315765,
       0.92412287, 0.5802973 , 0.34784675, 0.8383439 , 0.25869042,
       0.3251025 , 0.25364593, 0.34696266, 0.2711011 , 0.28396037,
       0.18996963, 0.1975288 , 0.4048511 , 0.713038  , 0.24441217,
       0.20768698, 0.20769489, 0.14585966, 2.0624115 , 0.33730796,
       0.28472236, 0.21070382, 0.36609936, 0.2235513 , 0.7702935 ,
       0.15754464, 0.20693891, 0.24473454, 0.4248834 , 0.53141254,
       0.11169058, 0.7135867 , 0.2509479 , 0.2697003 , 0.20657173,
       0.8076777 , 0.7457471 , 0.35818216, 0.32126474, 0.22358842,
       0.3938882 , 0.4221818 , 0.25997794, 0.5743797 , 0.5154033 ,
       0.50123656, 0.18575159, 0.43282   , 0.6924882 , 0.31800961,
       0.12436825, 0.17201406, 0.1636716 , 0.23295116, 0.7888542 ,
       0.5971635 , 0.3237781 , 0.4761071 , 0.5770297 , 0.22598803,
       0.15288863, 0.26394433, 0.30445924, 0.30210933, 0.33413118,
       0.2571784 , 0.396975  , 0.63171047, 0.16948076, 0.4233882 ,
       0.2525596 , 2.6397033 , 0.34996068, 0.21479887, 0.4343515 ,
       0.4490528 , 0.42258635, 0.6633154 , 0.71567327, 1.1432093 ,
       0.2653453 , 0.33082476, 0.22959782, 1.0895663 , 0.23540838,
       0.39007849, 0.25874722, 0.48358288, 0.2937208 , 0.20782883,
       0.38974056, 0.18455501, 0.3066178 , 0.32617322, 0.14731684,
       0.19954008, 0.11552545, 0.22998162, 0.22031553, 0.36876434,
       0.26483375, 0.45247898, 0.36123297, 0.19819699, 0.31592104,
       0.18201987, 0.62179506, 0.38428625, 0.15170102, 0.18690887,
       0.3260567 , 0.35888827, 0.5241166 , 0.5765973 , 0.21894874,
       0.19608498, 0.28775892, 0.32431427], dtype=float32), array([[[[-0.02465088],
         [ 0.01619857],
         [ 0.01541819],
         ...,
         [ 0.01547779],
         [-0.00829789],
         [-0.00508578]],

        [[ 0.00378051],
         [ 0.00743193],
         [ 0.00552983],
         ...,
         [ 0.02345256],
         [ 0.02488823],
         [-0.00053371]],

        [[ 0.02743079],
         [-0.01490775],
         [-0.00111389],
         ...,
         [-0.0163822 ],
         [ 0.00971728],
         [ 0.02143463]]],


       [[[-0.01926273],
         [-0.03358023],
         [-0.00415649],
         ...,
         [-0.00765204],
         [ 0.02985245],
         [-0.02040909]],

        [[-0.01176631],
         [ 0.01194253],
         [-0.01395889],
         ...,
         [ 0.02269962],
         [ 0.03145791],
         [-0.02864663]],

        [[ 0.02379454],
         [-0.03037239],
         [ 0.00457268],
         ...,
         [ 0.00874092],
         [ 0.00516247],
         [-0.01440757]]],


       [[[ 0.01865972],
         [-0.0155425 ],
         [ 0.00118925],
         ...,
         [-0.02788645],
         [ 0.02868056],
         [ 0.01697169]],

        [[ 0.03219984],
         [ 0.00740594],
         [-0.01022348],
         ...,
         [-0.03190015],
         [ 0.02713462],
         [-0.02112083]],

        [[ 0.03126211],
         [ 0.03043802],
         [-0.00612043],
         ...,
         [-0.01339357],
         [-0.02008246],
         [-0.01212715]]]], dtype=float32), array([[[[ 0.03032894, -0.05596289,  0.02111686, ...,  0.01506044,
           0.01472515,  0.01632685],
         [ 0.02022434, -0.01776742, -0.06635749, ...,  0.06544778,
          -0.056312  , -0.00966813],
         [ 0.05976683, -0.00395412,  0.0076172 , ...,  0.01443305,
          -0.02429987,  0.01344653],
         ...,
         [-0.01063834, -0.02063251, -0.00493782, ...,  0.04560397,
           0.04264775, -0.02003147],
         [ 0.01412262, -0.04945107,  0.04993906, ...,  0.02191688,
           0.02026361, -0.02266901],
         [-0.0650124 , -0.0054142 , -0.02810103, ..., -0.05834919,
          -0.04075284,  0.02208506]]]], dtype=float32), array([0.9948521 , 0.9942827 , 0.99381566, 1.0110848 , 1.0095145 ,
       1.0062563 , 0.9912597 , 0.98952866, 1.0136248 , 1.0046862 ,
       1.0031066 , 0.994749  , 1.0150506 , 1.0026169 , 0.99049217,
       1.022988  , 0.99502355, 0.98237836, 0.9973641 , 0.9852158 ,
       1.0101048 , 1.0141054 , 0.9915429 , 0.9957119 , 0.99429065,
       0.99438536, 0.9918985 , 0.99728066, 0.99551064, 1.0035356 ,
       1.001939  , 1.00053   , 1.0063152 , 0.9869046 , 0.99798006,
       1.0131698 , 0.99854153, 0.991587  , 0.9892    , 1.0105522 ,
       0.9953759 , 0.9988789 , 1.0104634 , 0.9960111 , 1.0081123 ,
       0.99372166, 1.0020885 , 0.99349207, 1.0093054 , 0.98868847,
       1.00122   , 0.98463774, 0.992834  , 0.9941926 , 0.9903364 ,
       1.0020065 , 0.99841833, 0.9944335 , 1.0582174 , 0.99738336,
       0.99347174, 0.99041194, 0.99330443, 1.0117598 , 0.9944568 ,
       0.99237216, 1.0119647 , 1.0029734 , 0.99646497, 0.9930694 ,
       0.99832714, 0.9961937 , 0.9977243 , 1.0361997 , 1.0100132 ,
       1.0154777 , 0.99408907, 0.9995896 , 1.013808  , 0.99307793,
       0.99811435, 0.9951912 , 1.002468  , 1.0082695 , 0.992561  ,
       0.99218434, 0.9904791 , 0.98671603, 0.9976188 , 1.0180005 ,
       1.0035015 , 1.0060835 , 0.9986539 , 1.003143  , 1.0058279 ,
       0.9980239 , 0.9930303 , 1.0016663 , 1.0108079 , 0.99136376,
       0.9889846 , 0.99442154, 1.002435  , 0.9968056 , 1.0084502 ,
       1.039986  , 0.99079084, 1.0007552 , 0.99530995, 0.99034256,
       0.9890243 , 1.0009189 , 1.0173888 , 1.0126086 , 0.9943184 ,
       1.0031295 , 0.9961886 , 1.0041823 , 0.9955982 , 0.98701674,
       0.99639446, 1.0227497 , 0.99774647, 1.0224701 , 0.9980085 ,
       1.014667  , 1.0196692 , 0.99693304, 0.9941838 , 0.994559  ,
       0.9893334 , 0.993118  , 0.9967994 , 1.0269654 , 0.99944323,
       1.0029383 , 1.0043427 , 1.0057684 , 1.0029519 , 0.99553823,
       0.9958817 , 1.0372381 , 1.0138851 , 0.9905121 , 1.0044999 ,
       0.9937625 , 0.9937569 , 0.9885399 , 1.0116922 , 0.996013  ,
       1.0096784 , 0.99237204, 1.0412042 , 1.0022655 , 0.99717176,
       1.0204346 , 1.0312313 , 0.99577254, 0.9956669 , 0.9914203 ,
       0.9940639 , 1.0006139 , 1.0356355 , 0.99541456, 1.0088509 ,
       1.0046425 , 1.0019332 , 0.99921197, 0.9957099 , 0.9948417 ,
       0.9988959 , 1.0012573 , 0.98288524, 0.9916174 , 1.0017625 ,
       0.984071  , 0.98623264, 1.0012454 , 0.9943727 , 0.9956234 ,
       0.99505883, 0.9949534 , 0.98864436, 0.9742624 , 0.99433684,
       0.9933728 , 0.9959809 , 1.0200062 , 0.99223864, 0.9934748 ,
       1.0021262 , 1.0199289 , 0.9927323 , 1.0181997 , 0.9965518 ,
       0.9943761 , 1.006084  , 0.9916358 , 1.0000416 , 0.997026  ,
       0.9954925 , 1.0162323 , 1.0102684 , 0.98820364, 1.0087384 ,
       0.9965954 , 0.9950126 , 1.0010582 , 0.9958501 , 0.9953157 ,
       0.9966893 , 0.9946785 , 0.9960829 , 0.99270475, 0.9942362 ,
       1.0130553 , 0.98545754, 0.98512954, 0.99160177, 1.0052694 ,
       0.9988741 , 1.006423  , 0.99692476, 1.003772  , 1.0056812 ,
       0.99599934, 0.99325794, 1.0041898 , 0.99060947, 1.0494249 ,
       0.99872446, 0.991524  , 0.98936945, 0.99159616, 1.0123541 ,
       1.0268128 , 1.0005583 , 1.0005113 , 0.99015474, 0.9993986 ,
       1.0094463 , 0.99938625, 1.0052992 , 0.9894601 , 0.9980125 ,
       0.99471444, 1.0111293 , 0.99746674, 1.0013907 , 0.9904378 ,
       0.99585986, 0.9876568 , 0.9896128 , 0.9944709 , 0.99451274,
       0.98523974, 1.010769  , 1.014138  , 0.99493814, 0.98489857,
       0.99703115, 0.99965334, 0.9958414 , 0.9931079 , 0.99826443,
       1.0001708 , 0.98843396, 1.004445  , 1.0007821 , 0.9933832 ,
       1.0174186 , 0.99869835, 1.0093367 , 1.0068429 , 1.0004705 ,
       1.0011154 , 0.99465615, 0.9933333 , 1.0079663 , 1.001973  ,
       0.99671865, 0.9959879 , 1.0158051 , 0.9906537 , 0.99177104,
       0.9991111 , 0.9910302 , 0.9868892 , 1.0111232 , 0.9943987 ,
       1.0088595 , 1.0523176 , 0.9908384 , 0.99666345, 0.9957097 ,
       0.9963844 , 1.0038062 , 0.99399614, 0.99454504, 1.0094371 ,
       1.0062462 , 1.0029433 , 1.0212885 , 0.9957681 , 0.98883635,
       1.0018921 , 0.99447876, 1.0038638 , 1.0007235 , 0.9899679 ,
       1.0116531 , 1.006925  , 0.9911485 , 0.99066365, 0.98442316,
       0.9919924 , 0.99506414, 0.9939505 , 0.99558395, 0.9945372 ,
       1.0012685 , 0.9923923 , 1.0073951 , 1.011434  , 0.99789023,
       0.9971799 , 0.99000716, 0.9893589 , 0.99395984, 0.9918027 ,
       0.9969044 , 1.0227444 , 1.00958   , 0.9962953 , 0.99776536,
       0.99585813, 1.0040447 , 1.0036609 , 1.053206  , 1.0094749 ,
       1.0053653 , 0.9972981 , 0.99529886, 1.0005424 , 1.0106801 ,
       0.99682945, 1.0107296 , 0.9962353 , 1.0050367 , 0.99593616,
       0.998481  , 0.99652034, 0.9971687 , 1.0029213 , 0.9929833 ,
       1.0043586 , 1.0043688 , 1.0331562 , 0.99631333, 1.0111208 ,
       1.0034072 , 0.9957832 , 0.99521494, 0.9940906 , 1.0043968 ,
       0.9823795 , 1.0005101 , 1.0107752 , 0.98854375, 1.0024303 ,
       1.0004436 , 0.99345464, 0.9934179 , 0.99375874, 1.0047141 ,
       0.9925446 , 0.9909331 , 0.9934437 , 0.9959981 , 0.997787  ,
       1.0005022 , 0.995218  , 1.016725  , 0.99105996, 0.99651146,
       0.9997272 , 0.9983645 , 1.0210147 , 0.9922856 , 1.0343817 ,
       1.0036091 , 1.0022086 , 1.0269675 , 1.00101   , 0.99497986,
       1.0030615 , 0.9992329 , 1.0111563 , 0.9949877 , 0.9991366 ,
       0.99766207, 0.9959412 , 0.9918839 , 0.9940114 , 1.0259045 ,
       1.0075461 , 1.0009826 , 0.9954834 , 1.0031582 , 0.98510987,
       0.9919262 , 0.9951733 , 1.0040712 , 0.9873316 , 0.99387723,
       1.0141462 , 0.9987041 , 1.0064886 , 1.004435  , 0.9842396 ,
       1.0007751 , 0.9924748 , 1.0113958 , 1.0209537 , 1.0269961 ,
       0.9997817 , 0.98930603, 0.982986  , 1.0040207 , 0.99833024,
       1.0067965 , 0.99541336, 0.9928591 , 1.0077255 , 0.9918555 ,
       0.99840343, 0.9872907 , 1.0069321 , 1.0016469 , 0.9884497 ,
       0.9893316 , 0.9885788 , 0.9758683 , 1.0036731 , 0.99883443,
       1.0060765 , 1.0026065 , 0.9808028 , 1.0146174 , 1.011312  ,
       1.0077852 , 1.0041451 , 0.9857813 , 1.0061932 , 0.998927  ,
       0.9960189 , 1.0008587 , 1.0122687 , 1.0324746 , 0.9921505 ,
       0.99052453, 1.0039886 , 1.0176281 , 1.0157161 , 1.0000368 ,
       0.9767136 , 1.0054756 , 0.99724853, 1.0076699 , 0.99944717,
       1.0006241 , 0.9919685 , 1.0228934 , 0.99322546, 1.0097378 ,
       0.98712546, 0.9758296 , 0.9946422 , 0.9866758 , 0.99608934,
       0.99524117, 1.0000821 , 0.9990848 , 0.9978296 , 1.0075375 ,
       1.0239189 , 0.9971154 , 0.9935079 , 0.9843651 , 0.9972833 ,
       0.9927796 , 1.0051751 , 0.99373794, 0.994803  , 1.000791  ,
       0.9916891 , 0.984878  , 1.0177541 , 0.9948051 , 1.0040865 ,
       0.99742824, 0.9925669 , 0.9891646 , 0.99966264, 0.9986477 ,
       1.0073798 , 0.9912754 , 0.99946004, 0.9928067 , 1.0384319 ,
       0.993117  , 0.98727316, 1.0076276 , 1.0029141 , 1.0016232 ,
       1.0007187 , 1.0002302 , 1.0320847 , 1.0015094 , 1.0042164 ,
       0.98292845, 0.9915883 , 0.992397  , 0.99573344, 0.9940065 ,
       1.0015045 , 0.9931568 , 1.004184  , 1.0096496 , 0.9888814 ,
       0.9973865 , 1.027738  , 1.0083702 , 1.0139899 , 0.9857422 ,
       0.9919606 , 0.99268645, 0.99177724, 0.9993622 , 0.99482477,
       0.9867251 , 0.99747765, 0.9938451 , 0.9924621 , 0.9909407 ,
       0.99535435, 0.99430186, 0.9932382 , 0.99589306, 0.99799234,
       0.99350995, 0.9935692 , 1.0064697 , 1.0064803 , 0.99422365,
       0.9952579 , 0.98364127, 1.0212357 , 1.0038867 , 0.9971869 ,
       0.99436206, 1.0120329 , 0.98426056, 1.0021665 , 1.0216324 ,
       1.0017797 , 1.0003597 , 1.0034577 , 1.0048084 , 0.997158  ,
       1.00441   , 0.9934091 , 0.9999068 , 0.9871996 , 1.0051637 ,
       0.99663514, 1.0043579 , 1.0186847 , 1.0126339 , 1.0009551 ,
       1.024495  , 1.0011647 , 0.9913025 , 0.9941104 , 0.9983928 ,
       0.9967927 , 0.9991511 , 1.0168227 , 1.0012759 , 1.0049596 ,
       0.9903572 , 0.99787366, 1.0093845 , 0.9989215 , 0.9987377 ,
       0.99991894, 0.9954847 , 1.0048797 , 0.9964997 , 0.9951044 ,
       1.0030296 , 0.9925428 , 1.0000637 , 1.0001242 , 0.99239147,
       0.9906344 , 0.98999286, 1.0037206 , 0.98502225, 0.99302465,
       1.0125991 , 0.996772  , 0.98783875, 0.99270475, 1.015588  ,
       1.0114087 , 0.9799074 , 0.98002094, 0.9993876 , 1.0022835 ,
       0.9825747 , 0.99650323, 1.0115435 , 0.98919374, 0.9931948 ,
       0.9896063 , 0.9936219 , 0.9983118 , 0.98590285, 0.99714357,
       0.99614954, 0.9970086 , 0.99913967, 0.9988492 , 0.9990763 ,
       1.0019032 , 0.9984494 , 0.9827475 , 0.9967466 , 1.0037844 ,
       0.998097  , 0.9936515 , 1.0043145 , 1.0013168 , 0.9991491 ,
       0.9793107 , 0.993952  , 0.9923281 , 1.0075979 , 0.98407644,
       0.999882  , 0.9900896 , 1.0160004 , 0.9936334 , 0.99038607,
       0.98856556, 0.9880086 , 0.9943831 , 1.0463008 , 1.0075426 ,
       0.99918646, 0.9930071 , 0.9987831 , 1.0077158 , 1.0085088 ,
       0.9938402 , 1.0187725 , 0.99470407, 0.98486865, 0.9974128 ,
       1.0060437 , 0.994563  , 1.0056922 , 1.0035079 , 0.99845517,
       0.9972525 , 0.99739987, 0.99432486, 0.9955299 , 0.9974386 ,
       0.9876425 , 0.99973017, 0.99536127, 1.0072287 , 1.0003003 ,
       0.99720365, 0.9996989 , 0.9994657 , 0.9888192 , 0.9959434 ,
       0.99972945, 0.9966457 , 1.0000315 , 1.0086391 , 1.0097524 ,
       0.9923205 , 1.0375544 , 0.9985632 , 0.9975224 , 0.99160254,
       1.0080011 , 1.0021648 , 1.0029044 , 0.99785364, 0.9882148 ,
       0.99807626, 0.99569046, 1.0004417 , 0.99428934, 0.9947563 ,
       0.99901736, 0.99108595, 0.9846942 , 0.99472857, 0.9917392 ,
       1.0040132 , 1.0085529 , 1.0032251 , 1.0018178 , 0.99583083,
       0.9841145 , 1.0097065 , 0.99793816, 0.9900396 , 1.010141  ,
       1.00577   , 0.989482  , 1.0014341 ], dtype=float32), array([-5.93597628e-03, -9.61268693e-03, -2.81487107e-02, -2.01990474e-02,
        1.73405278e-02,  1.06931003e-02,  9.75583447e-04, -1.19720800e-02,
        1.14112394e-02, -2.69812681e-02, -5.75835444e-03, -4.29352326e-03,
       -4.02958989e-02, -3.59394541e-03, -8.13760608e-03,  7.05427164e-03,
        3.15890834e-03, -6.73801405e-03, -1.25369402e-02, -4.94163157e-03,
       -1.58656910e-02,  2.23520100e-02, -5.93910180e-03, -7.44041800e-03,
       -1.01622669e-02,  6.46571442e-03,  1.02906274e-02, -1.71578408e-03,
       -5.03221527e-03, -9.83408373e-03, -2.39226688e-03,  3.43024358e-03,
        1.07810767e-02, -8.50737374e-03,  7.98558723e-03, -1.95224658e-02,
       -5.93587803e-03, -8.33219104e-03, -3.09313685e-02,  6.41543244e-04,
       -4.03304631e-03,  6.20019855e-03, -3.02175432e-02, -1.94393971e-03,
        7.29171978e-03, -8.56113387e-04, -1.60398241e-02,  2.47848895e-03,
        2.66324114e-02, -9.95088462e-03,  6.90380577e-03, -6.80196425e-03,
       -5.15850587e-03, -6.82558166e-04, -3.10797244e-03, -1.08723547e-02,
        1.34725366e-02, -4.84769279e-03, -3.24793607e-02, -1.97651125e-02,
       -1.07126571e-02, -1.18748154e-02, -1.79707222e-02,  1.20247034e-02,
        1.88626465e-03, -3.28554236e-03,  1.64406523e-02, -1.55274803e-03,
       -2.66770665e-02, -6.56612869e-03, -7.53210392e-03, -2.67255795e-03,
       -2.96466006e-03,  9.60281957e-03,  1.16764707e-02,  1.42192999e-02,
       -5.45215327e-03, -6.16927957e-03, -8.50167219e-03, -7.66574591e-03,
        9.03593027e-04, -1.55362813e-02,  2.24386770e-02, -1.09907836e-02,
       -1.36987263e-04, -1.19052846e-02, -2.09746752e-02, -6.11949991e-03,
        1.12655794e-03,  1.53018851e-02, -2.47610733e-02, -1.64270902e-03,
       -1.75687787e-03,  1.75371263e-02, -9.34569631e-03,  8.29515886e-03,
       -4.73975204e-03,  3.59426509e-03,  2.55793221e-02, -7.31532369e-03,
       -2.03451831e-02, -4.54583671e-03, -1.00185839e-03, -9.46324412e-03,
       -1.90288108e-02, -4.01223674e-02, -4.01150389e-03, -1.97114912e-03,
       -2.54778322e-02, -6.11103093e-03, -7.31636025e-03,  1.91644835e-03,
       -3.34337167e-02, -4.76913340e-03, -6.95802877e-03,  1.38051454e-02,
       -5.63871861e-03, -2.24035587e-02,  3.30616557e-03, -2.67921332e-02,
       -1.31446458e-02, -4.62844148e-02, -1.70044979e-04, -2.16006525e-02,
       -5.50977001e-03, -8.06685770e-04, -1.68261398e-03, -3.77067318e-03,
        2.91686435e-03, -8.81077722e-03, -4.95169498e-03, -6.86963974e-03,
       -1.73423812e-02, -2.08215676e-02, -2.27017086e-02,  1.08492766e-02,
        6.19446347e-03,  1.08677929e-03,  9.47949942e-03, -2.01030076e-02,
        9.60611366e-03,  8.66143219e-03, -2.51317713e-02, -2.08530948e-03,
       -1.96867399e-02, -5.25201438e-03, -8.97087250e-03, -4.68736468e-03,
       -6.53478596e-03, -4.06473689e-03,  1.61328036e-02,  4.80531575e-03,
       -2.54283566e-02, -2.05529714e-03,  5.50109893e-03, -3.77301127e-03,
       -4.81031351e-02, -6.42258441e-03, -1.15333879e-02, -1.14833806e-02,
       -1.22687351e-02,  8.53680819e-03, -4.58544604e-02, -4.34058020e-03,
       -1.19443778e-02, -2.38069389e-02, -6.95151044e-04, -3.54582421e-03,
       -1.05909223e-03, -1.38487052e-02, -1.73943769e-02,  1.22162970e-02,
       -4.47870465e-03, -7.08108069e-03, -2.23130062e-02,  5.96609758e-03,
        1.88676277e-05, -1.80564225e-02, -2.17145169e-03, -1.30942762e-02,
       -1.95021108e-02, -5.35757467e-03, -1.29082697e-02, -2.88929977e-03,
        4.71394742e-03, -2.07798183e-03,  2.32806592e-03,  1.35419227e-03,
       -6.76362403e-03, -3.18197394e-03,  7.92593136e-03, -4.74747969e-03,
       -3.17946598e-02, -4.85125072e-02, -3.91980354e-03, -7.78595032e-03,
        1.34066306e-02, -1.22368494e-02,  6.05220068e-03,  1.34964166e-02,
       -2.23147552e-02, -3.51534709e-02,  5.21906139e-03, -1.45864729e-02,
        1.58026982e-02, -7.63057498e-03, -3.59410280e-03, -1.08408900e-02,
       -1.55744259e-04, -5.10272430e-03,  3.74660944e-04, -2.17218359e-04,
       -1.88887194e-02, -7.91539345e-03, -1.08226866e-03, -7.60723837e-04,
       -6.25610910e-03, -1.07578356e-02, -5.00204321e-03, -1.34948986e-02,
       -9.99002997e-03, -7.56284362e-03, -2.39231233e-02,  9.42009501e-03,
        4.03710734e-03,  2.57838704e-03, -5.91974785e-05,  1.07763205e-02,
       -1.33730741e-02, -4.26878780e-02, -1.35887472e-03, -2.35454901e-03,
       -6.74740737e-03, -7.16004707e-03,  2.30556191e-03, -9.10478365e-03,
       -5.26293821e-04,  2.27319100e-03, -3.06437761e-02, -1.57838538e-02,
       -2.74528768e-02, -1.49688509e-03, -1.27418520e-04,  1.72608823e-03,
        8.82866513e-03, -1.08314434e-03, -1.73903164e-02, -1.51127167e-02,
        2.59948801e-02, -7.80432299e-03, -4.86532832e-03,  4.58168378e-03,
       -3.18048988e-03, -2.23315842e-02,  4.60373005e-03, -1.63024832e-02,
        1.94012769e-03, -7.55736546e-04, -2.79399264e-03, -1.35075990e-02,
        2.79906351e-04, -2.77683744e-03,  1.02820725e-03, -3.17237293e-03,
       -7.04869535e-03, -7.54267257e-03, -1.60358641e-02,  7.55954208e-03,
        1.40095772e-02, -4.64614248e-03,  1.87229067e-02, -6.73244335e-03,
        1.79951265e-03,  5.32647409e-03,  9.44273081e-03,  1.39592020e-02,
       -8.49712454e-03, -1.25441083e-03,  1.90463308e-02, -3.75182112e-03,
       -3.43252607e-02, -4.99277469e-03, -2.73073670e-02,  8.74141057e-04,
        1.21699425e-03, -1.58001052e-03, -3.10713472e-03, -1.42008588e-02,
        4.76648653e-04, -7.05884211e-03,  1.84375308e-02, -3.30379680e-02,
       -1.45768290e-02, -4.48333740e-04, -1.64311696e-02, -1.66521799e-02,
        5.45817474e-03, -6.15577260e-03, -9.76122636e-03, -1.94157511e-02,
       -4.26635426e-03, -2.06582323e-02, -9.04194266e-03,  7.37656315e-04,
       -2.27700621e-02,  9.17321909e-03, -1.06387213e-02, -2.04615667e-03,
        1.08104758e-02, -1.64838545e-02,  3.23933456e-03, -6.59560412e-03,
       -9.75407846e-03, -1.24038281e-02, -2.85759047e-02, -1.48743056e-02,
        1.01505639e-03, -2.74287048e-03, -2.35853028e-02, -8.08234140e-03,
       -2.27131502e-04, -4.58178110e-03,  1.41014569e-02,  4.96135373e-03,
       -9.04775108e-04,  1.79882278e-03, -1.50332283e-02, -2.75631640e-02,
       -1.41695077e-02, -1.14651080e-02,  4.75448370e-03, -1.26081181e-03,
       -4.71927924e-03,  1.45958140e-02,  1.24670593e-02,  4.62090509e-04,
        1.72968395e-02,  9.32297017e-03, -4.39724028e-02,  3.18931066e-03,
       -3.00931204e-02, -1.56414858e-03, -2.38936045e-03,  6.99409109e-04,
       -2.38825493e-02,  4.48814547e-03,  1.47917017e-03,  4.15901514e-03,
       -6.17546309e-03,  3.65812797e-04, -1.52022199e-04, -1.37038622e-02,
       -6.02710340e-03, -2.00244673e-02, -8.96375813e-03,  1.88760611e-03,
       -4.14749421e-03, -1.76495649e-02, -1.64559367e-03,  1.06082978e-02,
       -2.44604759e-02, -4.96340496e-03, -7.94286188e-03, -7.47232698e-03,
       -2.95914225e-02, -1.09540978e-02,  2.75239325e-03,  1.06765470e-02,
        4.19200445e-03, -9.21064243e-03,  1.47252134e-03, -3.10845878e-02,
       -2.22508404e-02, -4.79432894e-03, -1.12515930e-02,  2.47546146e-03,
       -8.42997432e-03, -1.13853784e-02,  1.00233695e-02, -3.51406820e-03,
       -9.81198903e-03,  2.66895909e-03,  1.59990657e-02, -3.01826908e-03,
       -1.69854108e-02,  8.84734467e-03,  1.32948207e-03,  2.94174384e-02,
       -7.98906758e-03, -4.04576324e-02,  2.72461446e-03, -4.84511766e-05,
        1.04868822e-02, -4.83875675e-03, -5.84246544e-03, -1.33269536e-03,
       -2.07837429e-02,  2.29978003e-02, -1.04970774e-02, -4.38182941e-03,
       -1.12892492e-02, -1.56180281e-03, -6.95216097e-03, -3.90451844e-03,
        4.96922992e-03, -1.08638182e-02,  1.80249605e-02, -2.29348913e-02,
       -2.32423120e-03, -3.68681084e-03, -5.09634800e-03,  1.88405253e-03,
       -1.24179304e-03, -1.79972854e-02,  1.50549621e-03, -1.25089129e-02,
        2.28400668e-03,  3.13534110e-04,  5.68384118e-03, -1.44046554e-02,
       -3.53637408e-03, -8.63393303e-03, -1.67680867e-02, -3.64675969e-02,
       -3.92516926e-02, -1.82935800e-02, -4.93237004e-03, -1.76155977e-02,
       -2.94936541e-03, -1.02226343e-03,  9.00817104e-03, -2.50187423e-02,
       -3.69570032e-03,  1.24787316e-02, -6.00233441e-03, -3.97431152e-03,
       -1.50255598e-02,  5.51002705e-03, -3.21154576e-03,  7.43201177e-04,
       -9.11689550e-03, -1.70461349e-02, -1.17482832e-02, -1.29333977e-02,
        9.14699805e-04,  7.67610595e-03,  3.10952892e-03, -1.35739325e-02,
        5.67960832e-03,  1.08798118e-02,  7.13605387e-03,  6.42723404e-03,
       -9.62126255e-03, -7.37911963e-04, -8.08279403e-03, -1.37807261e-02,
       -6.61491463e-03, -6.20071543e-03, -1.90524161e-02, -1.26222651e-02,
       -1.42444605e-02, -1.98294073e-02,  6.92478195e-03, -8.43025465e-03,
       -1.43483635e-02, -5.63420728e-03,  1.97167764e-03, -3.01170861e-04,
       -2.12375261e-02,  7.55158020e-03, -1.22619150e-02, -7.93159660e-03,
       -8.39381851e-03, -7.87184015e-03,  8.74095410e-03, -6.19788701e-03,
       -8.77912622e-03, -2.82283593e-03,  1.56977912e-03, -1.69060063e-02,
       -2.79230066e-03,  1.52751449e-02,  1.27866259e-02,  3.28919617e-03,
        4.63021966e-03,  3.48437726e-02,  2.75875046e-03, -8.42149369e-03,
       -1.16024734e-02, -3.49686568e-04, -5.88583015e-03,  5.83534548e-03,
       -9.37394518e-03, -3.65964341e-04, -5.12777315e-03, -9.55052860e-03,
       -5.94882667e-03, -7.84122199e-03, -2.76947045e-03,  2.99102650e-03,
       -7.24631734e-03, -4.82312776e-03, -5.75602637e-04, -1.28477085e-02,
       -1.26356492e-03, -1.03535913e-02, -2.51523894e-03,  7.77391670e-03,
        8.43582395e-03, -1.21585801e-02, -1.12139918e-02, -1.21540604e-02,
        2.36811414e-02,  2.14948179e-03, -1.86925288e-02,  5.29626710e-03,
        4.56854841e-03, -2.44114287e-02, -1.54599722e-03, -9.35239810e-03,
       -8.53030477e-03,  3.51983891e-03, -7.57571077e-03, -5.27982507e-03,
        5.24702948e-04, -2.46680900e-02, -1.76614635e-02, -1.36066489e-02,
       -2.34396756e-03, -1.05147921e-02, -4.81722993e-04, -4.58031483e-02,
        1.80454887e-02, -9.51641181e-04, -2.21397541e-02,  4.80434624e-03,
       -1.49465827e-02, -1.37367155e-02,  4.38172044e-03, -1.04771089e-02,
       -6.86912565e-03, -3.74784251e-03, -4.42990195e-03, -3.44283059e-02,
       -2.06228308e-02, -5.77577483e-03,  2.44187713e-02, -4.56840079e-03,
       -1.66630966e-03, -9.80261434e-03, -8.39486718e-03, -3.57949664e-03,
       -1.16460714e-02,  9.10242833e-03, -6.78896625e-03, -7.67591689e-03,
       -7.51322135e-03,  1.30467489e-03, -1.59858249e-03, -7.98631646e-03,
       -1.79803148e-02,  1.98466666e-02, -2.80092028e-03,  6.40898664e-03,
       -5.29646575e-02,  7.48012261e-03, -5.05047850e-03,  2.46578734e-02,
        1.47364999e-03, -1.18543266e-03,  2.08892990e-02,  2.27939710e-03,
       -2.07052613e-03, -6.92087412e-03, -1.09680099e-02, -7.06617022e-03,
       -2.21268162e-02, -3.22618685e-03,  6.55232463e-03,  9.39285092e-05,
       -2.94385888e-02,  5.45777334e-03, -3.54856020e-03, -1.30789690e-02,
       -1.14139542e-02,  7.86244578e-04, -2.93640490e-03, -2.22094655e-02,
        6.08530315e-03, -3.31762969e-03, -4.92925756e-03, -2.89670890e-03,
        4.76546446e-03,  1.34668285e-02, -4.44272626e-03, -4.40351525e-03,
       -8.29879753e-03, -8.18887632e-03, -7.20888702e-03, -4.96574491e-03,
        7.72514706e-03, -1.04218163e-02, -3.84973758e-03,  1.50662940e-02,
       -5.15835267e-03, -9.73921549e-03, -1.26192309e-02, -1.14592826e-02,
       -9.68774315e-03, -1.55867301e-02,  2.32840097e-03, -1.23554487e-02,
       -1.40141137e-02, -8.33857711e-03, -1.92145128e-02,  1.27986644e-03,
       -1.02731586e-02, -2.35067345e-02, -7.30672898e-03,  2.15429347e-03,
       -1.04497112e-02, -1.82450283e-03, -1.14820506e-02, -9.32883844e-03,
       -1.32027231e-02, -1.98061336e-02, -2.74464302e-03, -9.33289411e-04,
       -2.07176004e-02,  2.41995999e-03,  1.36011848e-02,  6.32164767e-04,
       -5.20549482e-03, -2.49385950e-03,  4.96821478e-03,  1.86340418e-02,
       -8.61471891e-03,  1.28128510e-02, -8.52131378e-03,  9.91397351e-03,
       -3.58778331e-03, -1.21617187e-02,  8.19761120e-03, -5.47947944e-04,
       -6.39375858e-03, -2.09245943e-02, -1.50731243e-02, -6.27116160e-03,
       -1.48583585e-02, -2.33825622e-03, -1.62458550e-02, -9.60270409e-03,
       -3.23182787e-03,  9.98936710e-04, -1.44929141e-02,  4.45102528e-03,
       -5.68281487e-03, -5.44246938e-03, -1.38527472e-02,  1.68592541e-03,
       -1.77449454e-02, -1.16851297e-03,  1.11276167e-03,  5.05475746e-03,
       -4.75099683e-03, -4.55164025e-03, -2.85154767e-03, -5.78996772e-03,
       -2.30401605e-02, -4.05880529e-03,  1.82221382e-04, -9.80309397e-03,
        1.06293177e-02, -2.03291373e-03,  3.46846064e-03, -1.64850336e-02,
        1.56852230e-03, -1.08495273e-03, -4.90631722e-03, -1.44579252e-02,
        1.03643350e-02,  1.42342586e-03, -1.76487081e-02,  1.24341613e-02,
        5.29900519e-03, -3.35040386e-03, -2.29974817e-02, -2.56552757e-03,
       -1.81759689e-02, -2.09618220e-03,  1.00168225e-03, -5.91589790e-03,
       -1.57976581e-03,  1.37285981e-02, -9.11548547e-03, -1.86254643e-02,
       -2.13485453e-02, -2.30694152e-02, -7.04193080e-04,  5.38332295e-03,
       -6.18765014e-04,  5.14198979e-03, -6.97192643e-03,  3.81751452e-03,
        2.98267603e-02, -3.95970093e-03,  1.96215976e-03,  1.38359028e-03,
       -6.39172411e-03, -1.07592558e-02, -6.59875246e-03, -9.30313207e-03,
       -9.69442725e-03, -7.80378375e-03, -3.53300804e-03,  1.10267019e-02,
        7.95182772e-03,  1.16655305e-02, -2.24010479e-02, -9.63007100e-03,
       -2.75527546e-03, -2.73734145e-03, -3.77408951e-03, -1.49864126e-02,
       -1.34127820e-03,  1.14332074e-02,  2.62885820e-03, -2.05820752e-03],
      dtype=float32), array([ 1.79251637e-02, -3.71933654e-02,  5.26515990e-02, -7.11545721e-03,
       -8.47826526e-03, -8.27071816e-03,  2.93827965e-03, -1.60476286e-02,
        8.99266568e-04,  6.02114871e-02,  2.20500734e-02, -2.65124701e-02,
        4.00714427e-02,  3.38563174e-02,  7.05646258e-03,  8.10296368e-03,
        2.18431978e-03, -1.68458149e-02,  1.31249940e-02, -1.14866029e-02,
       -1.41836246e-02, -1.14886919e-02,  3.87258716e-02,  1.82662755e-02,
        2.96239201e-02, -2.67851129e-02, -2.83127073e-02, -7.89287034e-03,
        1.89688511e-03,  9.17094573e-03,  1.86270159e-02,  2.70908549e-02,
       -4.66896966e-03,  2.89248787e-02, -7.99581595e-03,  3.53795961e-02,
       -7.42285629e-04,  1.04470421e-02,  1.82112250e-02, -2.94563584e-02,
        5.12004038e-03,  1.82430297e-02,  4.33417074e-02,  3.18684056e-02,
        3.87709737e-02, -1.55749153e-02,  2.62734778e-02, -2.00934578e-02,
       -3.45784612e-02, -1.20255314e-02, -1.36620123e-02,  6.62797305e-04,
       -2.17706561e-02, -6.77549979e-03, -2.51683425e-02,  1.09270727e-02,
       -2.63061784e-02, -3.05745713e-02,  1.03982352e-01,  4.52650860e-02,
        4.65538502e-02,  2.58995593e-02, -3.95770092e-03, -1.10658910e-02,
       -3.65365073e-02,  5.36529347e-03, -1.61335915e-02,  4.48321067e-02,
        4.01778407e-02,  2.78624520e-03, -3.46080363e-02,  1.21321632e-02,
       -3.63537222e-02,  5.31551614e-02, -8.81291460e-03,  1.39099564e-02,
        1.14145502e-02,  1.08498614e-02,  4.52448279e-02,  6.30047247e-02,
        2.36573946e-02,  3.75892711e-03, -5.34362160e-02,  5.92326745e-02,
        2.17073783e-02,  1.67554766e-02,  6.38201982e-02, -4.47921418e-02,
       -3.62097919e-02,  8.05199891e-03,  2.98503842e-02, -5.83197214e-02,
        2.86793076e-02,  8.74216761e-03,  4.83121872e-02, -3.64248976e-02,
        3.75861451e-02, -3.83320567e-03, -2.73029730e-02, -2.74110045e-02,
        5.88352419e-02, -4.15409822e-03,  1.46383289e-02,  4.23309766e-02,
        1.50352030e-03,  1.06799640e-01, -1.45936944e-03, -7.05471262e-03,
        1.83372982e-02, -2.34847851e-02, -2.57035550e-02, -2.26465333e-02,
        4.97900173e-02,  2.26100292e-02, -1.50962099e-02, -9.19337850e-03,
        2.57786606e-02,  7.41553530e-02, -1.65497558e-03, -3.02106421e-02,
        4.38013747e-02,  8.70153010e-02, -4.17270921e-02,  8.02142918e-02,
        1.46280602e-02, -2.22609956e-02,  1.70716997e-02, -6.79794000e-03,
       -2.48103887e-02,  6.82125939e-03,  1.56136034e-02, -3.42875570e-02,
        3.15261632e-02,  6.81448802e-02,  2.56923307e-02, -5.83500648e-03,
       -6.39708573e-03,  3.01826801e-02, -2.11292170e-02, -3.79206240e-03,
       -2.61893123e-02,  9.26707834e-02,  6.82228431e-02, -4.16074954e-02,
        4.15831059e-02,  2.32732072e-02,  1.98878497e-02,  2.66386643e-02,
        1.67300962e-02, -3.18654627e-02, -1.99993644e-02,  1.06518101e-02,
        7.38812387e-02, -1.17002102e-03, -2.64493469e-03,  7.03584328e-02,
        4.79292572e-02,  5.76693611e-03, -1.04368469e-02,  3.94768715e-02,
       -2.68697608e-02, -6.11592736e-03,  9.26885679e-02,  6.36927830e-03,
        6.77126348e-02,  5.30439951e-02, -2.27876902e-02, -4.27203253e-02,
        7.77669623e-03,  3.14103509e-03,  3.88776744e-03,  2.40653399e-02,
       -4.08390462e-02, -2.11920124e-02,  5.30801378e-02, -2.99675409e-02,
       -1.48976780e-02,  2.94156764e-02, -3.04394122e-03,  3.84146459e-02,
       -4.82612178e-02,  3.86631154e-02,  3.50535139e-02,  2.35606041e-02,
       -3.64199020e-02, -2.10647061e-02, -4.02543172e-02, -5.32396361e-02,
        6.58973083e-02,  9.76877869e-04, -7.49913976e-03,  2.20457069e-03,
        5.15629426e-02,  6.15648367e-02,  7.36315176e-03, -2.58362256e-02,
       -2.23546755e-02,  1.08680045e-02, -8.64161830e-03,  4.04570997e-02,
        1.69790126e-02,  5.24812192e-02, -1.21883908e-02, -1.99411493e-02,
       -1.16261765e-02,  1.16177117e-02, -2.27611866e-02,  4.63252962e-02,
       -3.05968206e-02, -5.86408237e-03,  3.53732184e-02,  1.97661184e-02,
       -4.45357412e-02,  3.11812945e-02, -7.06143025e-03, -1.86027810e-02,
        1.34139480e-02,  3.60030234e-02, -3.47626209e-02,  2.59564035e-02,
        1.98235195e-02,  2.46566925e-02,  2.35788655e-02,  1.61675606e-02,
       -3.46003920e-02, -2.14366131e-02,  8.66707228e-03, -5.17808758e-02,
       -3.51004256e-03,  4.83646393e-02, -2.63094786e-03, -3.47932242e-02,
        1.82566978e-02, -1.54861771e-02,  5.93123306e-03,  6.27226084e-02,
       -3.01282965e-02,  8.80954880e-03,  6.05486296e-02, -1.63305532e-02,
        3.06107253e-02, -2.06359234e-02,  7.86162540e-03, -2.35879943e-02,
        3.92031185e-02,  2.64302120e-02, -2.24420079e-03, -1.29921874e-02,
       -7.49689862e-02,  1.17784785e-02,  3.18350717e-02, -2.85503436e-02,
       -1.78382676e-02,  1.94577109e-02, -1.47513766e-02,  3.70360203e-02,
       -4.31220932e-03, -3.67042869e-02,  1.16461619e-04, -1.12204882e-03,
       -1.30485259e-02, -5.25864735e-02, -8.94777849e-03, -3.94619256e-02,
        1.97183099e-02,  5.85400499e-03,  5.30335903e-02, -1.64440684e-02,
       -3.07734441e-02,  6.84180576e-03, -5.82480046e-04,  2.04187445e-02,
        1.16324145e-02,  3.16273468e-03, -4.28418666e-02,  3.05504282e-03,
       -6.09719660e-03, -5.83778415e-03, -3.59061398e-02,  2.42553782e-02,
        1.17053250e-02, -3.27218417e-03,  3.25535238e-02,  1.52283767e-02,
       -4.15947177e-02, -2.47235652e-02, -2.35706773e-02,  2.25988822e-03,
        2.28254292e-02, -2.91373115e-02, -4.00417373e-02,  7.17438459e-02,
        2.76712012e-02, -1.23952944e-02,  5.68427928e-02, -6.06472827e-02,
       -3.91582679e-03,  2.14548428e-02,  4.68851849e-02,  6.51903823e-02,
        1.97548252e-02,  3.86897847e-02,  2.87381932e-02,  7.58351016e-05,
        4.99580391e-02, -2.48267855e-02,  1.84202995e-02, -3.01795062e-02,
       -3.21765170e-02, -1.97873358e-02,  1.58950947e-02, -9.06944927e-03,
       -2.98904404e-02,  8.56498908e-03,  2.15288270e-02,  8.58703069e-03,
       -4.04360667e-02, -3.56971622e-02,  2.63509806e-02,  2.26083174e-02,
       -3.10688894e-02, -1.46954991e-02, -3.38819548e-02, -3.45665179e-02,
        3.33425924e-02, -3.42596509e-02,  8.86433292e-03,  2.21927222e-02,
        2.71838307e-02,  1.81344878e-02, -1.52889434e-02,  2.21428089e-02,
       -4.68571745e-02, -1.59580652e-02, -3.50172557e-02,  2.02945853e-03,
       -4.12786938e-02, -2.50571556e-02,  1.06019534e-01, -5.18399738e-02,
        4.85606939e-02,  3.70674618e-02,  5.06262388e-03, -1.10667069e-02,
        3.04439161e-02, -1.64351836e-02,  4.40096334e-02, -2.11536139e-02,
        1.09379664e-02, -4.01839539e-02,  4.73304912e-02,  2.71739718e-02,
       -2.57997215e-02,  1.58880465e-02, -8.73572752e-03,  6.80042664e-03,
       -1.50670782e-02,  6.35074452e-02,  2.07456332e-02, -4.74443883e-02,
        4.17899676e-02,  3.95946950e-02,  4.38949652e-03, -2.32580234e-03,
        1.85987260e-02, -3.18728574e-02, -3.71648520e-02, -4.68494482e-02,
        1.26874885e-02,  1.89211611e-02,  2.45302916e-02,  5.34218997e-02,
        1.73713472e-02,  2.33306121e-02,  2.51912083e-02, -5.18013199e-04,
        5.97389787e-03, -1.32390568e-02, -4.48110653e-03, -9.91481822e-04,
        3.86344902e-02, -2.49571018e-02,  3.52501087e-02,  2.32175240e-04,
        2.45164987e-02,  1.80296432e-02, -3.66985798e-02, -1.99316815e-02,
       -1.13173379e-02,  5.01893312e-02, -4.81286012e-02,  1.40251834e-02,
        2.66718175e-02, -1.06625259e-02,  2.42311992e-02,  2.62550488e-02,
        9.22251865e-03,  3.97895835e-02,  6.84975507e-03,  1.24889761e-02,
       -9.02011804e-03, -1.50209200e-02, -4.13419493e-02, -1.67354345e-02,
       -7.48296175e-03, -6.30880296e-02, -1.18167214e-02,  4.85354364e-02,
       -1.92949027e-02, -4.11978252e-02, -2.94189807e-02, -2.21824814e-02,
        1.30534153e-02, -3.74941301e-04, -6.93700276e-03, -8.91133491e-03,
       -1.07805459e-02, -4.25549671e-02, -1.52372494e-02, -6.70309039e-03,
        3.12443338e-02, -9.89065389e-04,  4.50644456e-02,  6.59495592e-02,
        7.58279264e-02,  3.84272039e-02,  1.33559303e-02, -3.78199993e-03,
        1.66620780e-02,  4.23769951e-02,  2.01340206e-02,  5.76281473e-02,
        3.29801925e-02, -2.33755205e-02,  1.03410920e-02, -1.17452238e-02,
       -8.10010883e-04,  2.98243645e-03,  2.70845890e-02, -3.16631459e-02,
        1.20235803e-02, -1.33591350e-02,  1.17042689e-02,  1.86739769e-02,
       -3.01378351e-02, -7.02738063e-03,  2.88933571e-02, -4.54901792e-02,
       -3.58100701e-03, -2.54786164e-02,  7.16820685e-03, -2.16145217e-02,
       -2.86778901e-02, -2.88033765e-03, -6.38531800e-03,  9.32396296e-03,
        1.79793518e-02, -7.06515601e-03,  6.43453076e-02, -6.76626991e-03,
       -4.18353872e-03,  2.47942097e-02, -1.06138075e-02,  4.04206887e-02,
        3.20350681e-03, -3.91616188e-02, -3.30769233e-02, -1.63126644e-02,
        2.63683256e-02, -4.42302153e-02,  3.99735197e-02, -1.33663043e-02,
        1.68141164e-02, -3.76766105e-03,  2.14839708e-02,  1.36211161e-02,
       -7.39034265e-03,  2.03412101e-02, -3.52391638e-02, -3.69429514e-02,
        3.85957630e-03, -4.02849242e-02,  1.96177233e-03, -2.01441944e-02,
        2.43832450e-02, -4.69292887e-02, -2.46305726e-02,  3.20522599e-02,
       -3.35009582e-02, -1.84195079e-02, -1.65943038e-02, -1.57299414e-02,
       -3.61925624e-02, -2.18354575e-02,  3.45544220e-04,  7.90256541e-03,
       -2.41357908e-02, -4.69562635e-02,  1.45093855e-02,  5.04100323e-03,
        3.45986485e-02, -1.02537945e-02, -9.29220300e-03,  3.86695899e-02,
       -1.38350269e-02,  2.51145978e-02,  2.06625089e-02, -3.17295967e-03,
       -3.73251922e-02,  4.44476567e-02,  4.25165072e-02,  1.28334174e-02,
       -3.44050154e-02,  3.35462466e-02,  6.28030300e-02, -5.53919096e-03,
        9.98025760e-04,  5.34555353e-02,  1.65568443e-03, -7.12275431e-02,
        8.80983658e-03, -2.96528321e-02, -3.32923271e-02,  5.43892058e-03,
        2.52551548e-02, -3.24601755e-02,  9.48858261e-03,  2.11076308e-02,
       -1.56387500e-02, -1.67057198e-02, -5.30265905e-02,  8.76516849e-02,
       -3.49160135e-02, -3.67536694e-02,  2.66339816e-02,  2.36659544e-03,
       -5.94179425e-03,  4.38726656e-02, -4.51846235e-02,  2.33922582e-02,
        1.28212692e-02,  1.73200555e-02,  1.33133605e-02,  4.97437902e-02,
       -2.42820941e-02, -2.85736639e-02, -3.18049565e-02, -7.41518894e-03,
       -1.38807260e-02,  1.87547598e-02, -1.02950316e-02, -2.47517936e-02,
       -2.99602989e-02, -2.42709816e-02,  1.49743212e-02, -3.71913388e-02,
        3.89550440e-02, -2.87859924e-02, -8.57599545e-03,  3.39817791e-03,
        3.83968954e-03, -1.91459041e-02,  3.43102477e-02, -5.30118961e-03,
        8.60337541e-02, -5.74712921e-03,  4.37122956e-03, -2.38227528e-02,
       -1.97694376e-02,  7.44559942e-03, -4.67240904e-03, -4.72362526e-03,
       -3.60363275e-02,  4.65825945e-02, -6.09621145e-02,  2.00721305e-02,
        4.28547040e-02,  8.15143809e-04, -3.47849838e-02,  1.71260964e-02,
        6.45257160e-02,  6.39689295e-03,  1.52807599e-02,  3.93101536e-02,
       -9.83752497e-03, -2.13235859e-02, -1.41499401e-03,  4.09973003e-02,
       -3.49512324e-02, -1.10877920e-02, -4.50809766e-03,  6.00690488e-03,
       -6.77386904e-03, -2.66858395e-02, -2.51020002e-03, -1.52175752e-02,
        8.61447677e-03,  3.68736684e-02,  1.96258072e-02, -1.08734211e-02,
       -6.08955277e-03,  3.10399048e-02,  8.53305496e-03, -1.40467435e-02,
       -8.12133215e-03, -1.57769453e-02, -1.08531397e-02,  1.50936458e-03,
        3.19338702e-02,  4.65271138e-02,  4.42695990e-03,  3.26176509e-02,
        2.69240402e-02,  1.99063756e-02,  4.02875990e-02,  4.76058200e-03,
       -3.88528593e-02,  4.87754345e-02, -8.19470268e-03, -7.18507636e-03,
        2.27659047e-02, -3.25825475e-02,  1.68429278e-02,  1.30646639e-02,
       -1.13449898e-02,  7.88378809e-03,  9.50999837e-03,  1.30144926e-02,
        1.33425870e-03, -4.91059991e-03, -3.75186913e-02, -1.74100231e-02,
        2.85738576e-02, -3.69810942e-03, -2.50227638e-02, -5.63350618e-02,
        1.87940449e-02, -6.33657798e-02,  2.44664047e-02, -3.26612256e-02,
       -9.97836795e-03, -9.44004767e-03, -4.34216559e-02,  7.66350981e-03,
       -1.45313200e-02,  4.00521746e-03,  2.13413239e-02, -2.47453693e-02,
        1.27820652e-02,  2.49256697e-02,  2.38378737e-02, -1.80996545e-02,
        4.35459986e-02, -6.09379786e-04,  3.83765972e-03, -6.71142153e-03,
       -2.88118273e-02, -1.66221485e-02,  6.25238791e-02,  9.71930102e-03,
       -4.67833802e-02,  8.45289137e-03, -8.96145182e-04, -2.17880048e-02,
       -3.40548269e-02, -3.02692372e-02,  1.19724059e-02, -2.93675475e-05,
        4.78663146e-02,  2.20550969e-02, -6.11531781e-04,  6.08893372e-02,
       -4.00041044e-02,  2.71903537e-02, -2.56301295e-02, -9.13883385e-04,
        1.68660805e-02,  4.03484516e-02,  6.93928497e-03, -7.19627813e-02,
       -1.47660505e-02, -3.12751196e-02, -7.18218228e-03, -2.23235469e-02,
       -4.55986448e-02, -2.52105854e-03,  1.29151782e-02,  6.58869073e-02,
        3.08089778e-02, -1.57970879e-02, -4.14548405e-02,  6.74286531e-03,
        8.07265379e-03, -3.26072760e-02,  3.40545438e-02,  4.16294634e-02,
        5.16304038e-02,  1.74569115e-02, -2.58683879e-02,  2.70216782e-02,
        2.79095732e-02, -4.69106510e-02,  2.10779486e-03, -4.32421640e-03,
       -5.15564829e-02, -2.47447919e-02, -4.62819524e-02, -4.90791276e-02,
        2.39377674e-02,  3.76904234e-02,  3.08525432e-02, -4.62526921e-03,
       -4.68220795e-03,  4.37595556e-03, -8.02018913e-05, -2.79178452e-02,
       -2.68162992e-02, -4.60369475e-02, -5.24339117e-02,  7.24983811e-02,
       -1.04056979e-02,  1.15679717e-03,  2.76050474e-02,  2.44706832e-02,
        1.10788289e-02, -1.74250379e-02,  1.66381001e-02, -2.62411293e-02],
      dtype=float32), array([0.08878608, 0.10632759, 0.10112032, 0.10634732, 0.08744803,
       0.09253349, 0.08356471, 0.08268663, 0.09101121, 0.1084342 ,
       0.09844612, 0.095621  , 0.09539472, 0.10215883, 0.09421197,
       0.09191857, 0.08737269, 0.08842742, 0.08697274, 0.08277156,
       0.09814093, 0.08931144, 0.08491856, 0.08640171, 0.08787215,
       0.08261906, 0.09281214, 0.08379611, 0.08655014, 0.08393195,
       0.08641692, 0.08547793, 0.08737969, 0.08750059, 0.08359476,
       0.09811476, 0.08744656, 0.0854332 , 0.08923351, 0.08731455,
       0.09859857, 0.09048366, 0.0944253 , 0.08194617, 0.0960022 ,
       0.08685574, 0.09096286, 0.08528403, 0.09235886, 0.08350548,
       0.08562025, 0.09182295, 0.09133711, 0.0869272 , 0.08590134,
       0.08659769, 0.08944175, 0.08547454, 0.14636621, 0.09450413,
       0.0892652 , 0.08926597, 0.08651417, 0.09275123, 0.08548541,
       0.08339159, 0.08804426, 0.09399065, 0.09015915, 0.08582909,
       0.08692445, 0.08672993, 0.0892196 , 0.10307224, 0.08943674,
       0.09059713, 0.08720218, 0.08813754, 0.1055096 , 0.09555344,
       0.08661604, 0.089164  , 0.11074974, 0.12443429, 0.0824381 ,
       0.08683581, 0.10189941, 0.0864315 , 0.08370312, 0.11251168,
       0.09876097, 0.09772142, 0.09705856, 0.09790656, 0.10284371,
       0.09619998, 0.10643161, 0.08572697, 0.09434184, 0.10118751,
       0.09221645, 0.08252893, 0.08754648, 0.08844855, 0.08831669,
       0.14124408, 0.08278717, 0.09144207, 0.09873375, 0.08266448,
       0.084914  , 0.09187298, 0.11085206, 0.08582178, 0.08551332,
       0.08932419, 0.10017692, 0.13288715, 0.08949993, 0.09183144,
       0.10342629, 0.11006662, 0.08884538, 0.10919328, 0.08552046,
       0.09872068, 0.0916194 , 0.08329482, 0.08968872, 0.08353972,
       0.08443287, 0.08729159, 0.09141786, 0.11891603, 0.09016279,
       0.08717661, 0.09224905, 0.08988086, 0.08778627, 0.08632597,
       0.09011665, 0.1498481 , 0.11366615, 0.10469542, 0.09244515,
       0.09708859, 0.08473697, 0.0878091 , 0.09582129, 0.09380489,
       0.08978891, 0.08424055, 0.14749461, 0.09028603, 0.08456608,
       0.12075674, 0.11914504, 0.08820067, 0.08373511, 0.09508593,
       0.08704647, 0.08718968, 0.11421452, 0.08449464, 0.1090797 ,
       0.09987666, 0.09039494, 0.09930494, 0.08257665, 0.0852227 ,
       0.09132372, 0.08797293, 0.08719096, 0.09723628, 0.10915585,
       0.09064001, 0.09130075, 0.086955  , 0.08779815, 0.10880892,
       0.09785092, 0.09071237, 0.08350252, 0.09210043, 0.09503856,
       0.08502468, 0.09548701, 0.09946851, 0.11358027, 0.08426224,
       0.08526486, 0.08757437, 0.09413064, 0.12110097, 0.10357651,
       0.08448734, 0.1061315 , 0.08333966, 0.09208406, 0.1038139 ,
       0.09617194, 0.09434102, 0.09272779, 0.10192816, 0.08997781,
       0.08324829, 0.09029211, 0.10263817, 0.08508585, 0.08740673,
       0.1101016 , 0.08459197, 0.10291387, 0.09155103, 0.08351741,
       0.09006135, 0.09084547, 0.09951709, 0.09233825, 0.08686664,
       0.09175082, 0.09561364, 0.08990509, 0.08963726, 0.10554741,
       0.08826828, 0.08469405, 0.09910303, 0.08499692, 0.11603253,
       0.08762278, 0.09002434, 0.08553926, 0.08285692, 0.0852809 ,
       0.10306629, 0.08649742, 0.09152332, 0.09369513, 0.10468689,
       0.09419885, 0.09318875, 0.09838151, 0.08330197, 0.08985332,
       0.08711749, 0.1055431 , 0.09744199, 0.11176741, 0.08485018,
       0.09378164, 0.10152938, 0.08310406, 0.09476063, 0.08809669,
       0.09277851, 0.08478995, 0.10383734, 0.081765  , 0.08413085,
       0.08436209, 0.09098595, 0.08226553, 0.1076683 , 0.08253729,
       0.09012002, 0.10473594, 0.08555163, 0.08992036, 0.08510265,
       0.10199491, 0.0942128 , 0.08986811, 0.09683782, 0.10550202,
       0.08472338, 0.08348729, 0.08264795, 0.10524955, 0.08383951,
       0.08848771, 0.08424859, 0.09171057, 0.08622871, 0.09845129,
       0.09645113, 0.09186237, 0.08516934, 0.08661582, 0.08418481,
       0.0916684 , 0.13738424, 0.0831826 , 0.08248185, 0.09455756,
       0.09991699, 0.08525953, 0.08843496, 0.08571272, 0.10441434,
       0.09142563, 0.08986054, 0.09131501, 0.08846062, 0.1057317 ,
       0.09406232, 0.08479322, 0.08679665, 0.08664504, 0.08427655,
       0.08936779, 0.09336243, 0.09601138, 0.08298249, 0.08861538,
       0.09384342, 0.091801  , 0.09546083, 0.08788106, 0.09102464,
       0.09203856, 0.08207346, 0.090515  , 0.0905402 , 0.09397847,
       0.10002141, 0.09297797, 0.09066121, 0.08596268, 0.08377659,
       0.08920071, 0.08926992, 0.10828464, 0.08580658, 0.10586081,
       0.08544432, 0.09094816, 0.08678693, 0.15087578, 0.10549448,
       0.10143999, 0.09539243, 0.08266286, 0.08183938, 0.0886844 ,
       0.09525273, 0.10502727, 0.08681037, 0.08480635, 0.08679086,
       0.09263378, 0.08789093, 0.08985101, 0.09243537, 0.08512525,
       0.09028531, 0.12132565, 0.11632857, 0.08529837, 0.09290066,
       0.09743129, 0.09334406, 0.0908085 , 0.08296148, 0.09569772,
       0.08431495, 0.08828747, 0.08602424, 0.08800034, 0.10334054,
       0.09376746, 0.09637318, 0.09510658, 0.08654235, 0.08972052,
       0.08296628, 0.08283628, 0.08212504, 0.09865833, 0.08361334,
       0.09032652, 0.09007917, 0.12071218, 0.08683116, 0.09513194,
       0.0836958 , 0.08642857, 0.0882602 , 0.08814386, 0.12706485,
       0.10083262, 0.08672453, 0.09447635, 0.08259485, 0.09384541,
       0.09063441, 0.08457834, 0.09027296, 0.08372454, 0.08622254,
       0.10118195, 0.08897469, 0.09088535, 0.08910375, 0.08772882,
       0.11926649, 0.10261936, 0.09449722, 0.09936816, 0.09891931,
       0.09782526, 0.0879464 , 0.08638579, 0.08745537, 0.08472814,
       0.09535704, 0.08373558, 0.09034364, 0.0838137 , 0.08738957,
       0.09959314, 0.08342845, 0.09940625, 0.10125149, 0.13024342,
       0.09931276, 0.08450875, 0.08491074, 0.0923221 , 0.08903265,
       0.0871883 , 0.09514133, 0.08563977, 0.0981649 , 0.08673465,
       0.09510687, 0.08261626, 0.08663972, 0.09254631, 0.09598578,
       0.08911823, 0.08426568, 0.08721432, 0.08888158, 0.0845284 ,
       0.09624096, 0.08741626, 0.09162336, 0.10136636, 0.09350143,
       0.09116901, 0.09511443, 0.08597146, 0.09087098, 0.08729873,
       0.08988306, 0.08469295, 0.10454028, 0.12482908, 0.08551544,
       0.08344147, 0.09113252, 0.09847303, 0.09784876, 0.09223734,
       0.09712631, 0.08303382, 0.08271682, 0.09468494, 0.10273057,
       0.10065999, 0.08844192, 0.1016067 , 0.08715258, 0.09367035,
       0.08686545, 0.0866807 , 0.08381239, 0.10710806, 0.08371047,
       0.08400926, 0.09859478, 0.08836181, 0.08600885, 0.09093235,
       0.0925611 , 0.08791218, 0.09002521, 0.08661281, 0.09012333,
       0.08498082, 0.10065452, 0.08784824, 0.09564835, 0.0900297 ,
       0.08307004, 0.09014761, 0.10292066, 0.08708591, 0.08641093,
       0.08635292, 0.08508373, 0.0901681 , 0.106598  , 0.09094301,
       0.1043659 , 0.09471212, 0.08444183, 0.10356966, 0.11254105,
       0.10336544, 0.08999812, 0.0918016 , 0.09088774, 0.10110589,
       0.08715608, 0.08269659, 0.13282658, 0.08645917, 0.12277084,
       0.08186783, 0.0953944 , 0.08725684, 0.08667862, 0.08815107,
       0.09522713, 0.08509537, 0.08535117, 0.08920809, 0.09504271,
       0.09803791, 0.12045382, 0.08854665, 0.09414715, 0.0927956 ,
       0.0872556 , 0.08668271, 0.09212203, 0.09595308, 0.0888216 ,
       0.08921652, 0.08221485, 0.09366408, 0.09883465, 0.08897091,
       0.0876639 , 0.09128195, 0.08589287, 0.08374187, 0.0856585 ,
       0.08256999, 0.09717906, 0.10410547, 0.08498956, 0.08417865,
       0.08400352, 0.0921186 , 0.09568028, 0.08751452, 0.08311308,
       0.08543776, 0.08754165, 0.08836987, 0.09426305, 0.12892964,
       0.08695863, 0.09777275, 0.08715142, 0.08559135, 0.08222061,
       0.09162004, 0.08314116, 0.08759548, 0.11527077, 0.09867825,
       0.08835558, 0.10144316, 0.10414466, 0.08690705, 0.09163254,
       0.11099355, 0.08327968, 0.08783241, 0.08998728, 0.09391534,
       0.08946228, 0.08740241, 0.10092554, 0.10189033, 0.08491831,
       0.0855427 , 0.08516923, 0.08533251, 0.08972692, 0.08759212,
       0.08985719, 0.08922454, 0.08803546, 0.09066731, 0.08190282,
       0.08557045, 0.09065276, 0.08788817, 0.09220583, 0.08358829,
       0.08291723, 0.08364499, 0.09160742, 0.09714133, 0.08972006,
       0.08941409, 0.09496229, 0.09542276, 0.08508859, 0.09683472,
       0.0922006 , 0.11035551, 0.09423456, 0.08595336, 0.09224665,
       0.08320083, 0.08453505, 0.08805417, 0.08380692, 0.09733222,
       0.09450997, 0.09692449, 0.0842412 , 0.09411531, 0.08786421,
       0.08975558, 0.09320083, 0.10099432, 0.09063061, 0.09549596,
       0.09029199, 0.08855361, 0.1018742 , 0.08544961, 0.08941349,
       0.08470395, 0.08739781, 0.09732855, 0.09092493, 0.08368497,
       0.08531282, 0.09319523, 0.08870667, 0.10186593, 0.08934002,
       0.09555286, 0.10524251, 0.09469028, 0.10046104, 0.08189423,
       0.08750069, 0.08381957, 0.08328549, 0.11450737, 0.08997866,
       0.11505075, 0.08489948, 0.08750819, 0.09813134, 0.09703559,
       0.08562407, 0.1006996 , 0.08408384, 0.10259008, 0.09255072,
       0.08901521, 0.11382788, 0.10800097, 0.1129637 , 0.08555207,
       0.08540241, 0.08671921, 0.08687862, 0.0881997 , 0.10355687,
       0.08258   , 0.08441696, 0.08229307, 0.09244384, 0.09330143,
       0.08739355, 0.08937276, 0.10229999, 0.10409916, 0.0858651 ,
       0.09450713, 0.08457039, 0.09256934, 0.0954229 , 0.08930933,
       0.08806205, 0.11101165, 0.09479133, 0.08741943, 0.08949134,
       0.09549157, 0.10470435, 0.08692954, 0.08784383, 0.12734324,
       0.09165362, 0.11452111, 0.09499842, 0.0917692 , 0.0864593 ,
       0.09311161, 0.09017845, 0.0825863 , 0.08222649, 0.08447424,
       0.09121944, 0.10362   , 0.08791129, 0.10733218, 0.1044527 ,
       0.09248748, 0.08602092, 0.0878066 , 0.08860648, 0.08950712,
       0.08980374, 0.08504505, 0.09261782], dtype=float32), array([[[[ 0.0026816 ],
         [-0.02934938],
         [-0.01775249],
         ...,
         [-0.00044226],
         [ 0.00217323],
         [ 0.02219043]],

        [[-0.02856271],
         [-0.02584338],
         [-0.00160714],
         ...,
         [ 0.01689859],
         [ 0.01707627],
         [-0.01623651]],

        [[ 0.01240841],
         [ 0.02657466],
         [ 0.01048774],
         ...,
         [ 0.01267601],
         [ 0.01255772],
         [ 0.00330045]]],


       [[[ 0.02533061],
         [-0.00552193],
         [ 0.0139031 ],
         ...,
         [ 0.00035916],
         [ 0.02663396],
         [ 0.03229698]],

        [[ 0.00607284],
         [-0.01271398],
         [ 0.00649936],
         ...,
         [ 0.01061327],
         [-0.003692  ],
         [ 0.03160423]],

        [[-0.02577517],
         [-0.00462546],
         [-0.01144006],
         ...,
         [-0.01809651],
         [ 0.02012363],
         [-0.02293783]]],


       [[[ 0.01321153],
         [ 0.00341026],
         [ 0.01633764],
         ...,
         [ 0.03027552],
         [-0.01475425],
         [-0.01936854]],

        [[-0.02686907],
         [ 0.01803121],
         [-0.00899358],
         ...,
         [ 0.03948463],
         [-0.02791632],
         [ 0.01199027]],

        [[-0.02579174],
         [-0.01395927],
         [ 0.02433692],
         ...,
         [ 0.00362967],
         [-0.01779826],
         [ 0.00828041]]]], dtype=float32), array([[[[ 1.3946519e-02, -3.6624290e-02, -4.1368455e-02, ...,
          -2.2622807e-02, -5.3177342e-02,  9.6094999e-03],
         [ 4.5877885e-02, -5.6180503e-02, -3.7753738e-02, ...,
           4.1925993e-02, -1.6479188e-03,  4.8282642e-02],
         [-3.0794077e-02,  1.7815251e-02,  1.3977484e-02, ...,
           3.6186662e-02, -2.8896429e-02, -5.0810136e-02],
         ...,
         [ 5.9652641e-02, -1.3732722e-02, -4.0501148e-02, ...,
          -5.7056192e-02,  1.6381120e-05,  3.8514931e-02],
         [ 3.6150441e-02, -6.1456423e-02,  4.9130458e-02, ...,
          -2.9916171e-02,  2.0100055e-02, -2.3275120e-02],
         [ 1.6457947e-02,  2.2888413e-02, -1.9843329e-02, ...,
          -5.5409808e-02,  4.4518813e-02, -2.7151406e-02]]]],
      dtype=float32), array([1.0004224 , 1.0103599 , 1.004651  , 1.0163171 , 1.0131196 ,
       0.9873264 , 1.0085852 , 1.0133029 , 0.9950294 , 1.0163714 ,
       1.0099735 , 1.023104  , 0.9960951 , 1.0261322 , 1.0031323 ,
       1.0042175 , 0.9951245 , 1.001236  , 1.0274019 , 1.0010839 ,
       0.98402965, 1.0241464 , 1.0080913 , 1.0060894 , 1.0219728 ,
       0.9976933 , 1.0051706 , 1.0057341 , 1.0009292 , 1.0018476 ,
       0.99528605, 0.9940188 , 1.0130894 , 0.9991113 , 1.0169555 ,
       1.0331671 , 0.99677235, 1.0115876 , 1.0112298 , 0.9943821 ,
       0.99895906, 1.0108372 , 1.012561  , 0.9900611 , 1.0093138 ,
       1.0249999 , 0.99724644, 0.99501777, 1.0150092 , 1.0193828 ,
       1.0270083 , 1.0084522 , 1.0067757 , 0.9999214 , 1.0445838 ,
       1.0044167 , 1.0325788 , 1.0286999 , 0.9953701 , 0.9993726 ,
       0.9867068 , 0.9932501 , 1.0172547 , 1.0037129 , 0.98658437,
       1.0298221 , 1.0261611 , 1.0031557 , 1.01984   , 0.99123603,
       1.0143967 , 1.000497  , 0.99843633, 0.9812365 , 1.0041841 ,
       1.0235935 , 1.0048077 , 0.9975395 , 0.9721947 , 0.9922653 ,
       1.007176  , 1.0101666 , 1.0153242 , 0.9984348 , 1.0201943 ,
       0.99357146, 1.0063658 , 0.9951507 , 1.01004   , 0.99579734,
       1.0032825 , 0.999772  , 1.0134231 , 1.0238367 , 1.0214918 ,
       1.0073339 , 1.0129302 , 1.0106013 , 0.99675184, 0.98381186,
       1.0167481 , 0.9891719 , 0.9844797 , 1.0263451 , 1.0450888 ,
       1.0336843 , 0.9971924 , 1.0180144 , 1.0061433 , 1.0088551 ,
       1.0016754 , 1.0120531 , 0.9854343 , 1.0076337 , 1.0021421 ,
       0.9963416 , 1.0113627 , 1.0192478 , 1.0220588 , 1.0035627 ,
       1.0066686 , 1.0128597 , 0.99036604, 1.0088274 , 1.0333191 ,
       0.99373454, 0.9958961 , 0.9968334 , 0.99777484, 1.0091085 ,
       1.0089871 , 0.99810725, 0.9966421 , 0.9916635 , 0.97286725,
       0.99587256, 1.0288875 , 1.0438074 , 0.9923596 , 1.0100262 ,
       1.0034568 , 0.99357635, 0.9999019 , 0.98867303, 1.0235606 ,
       1.0085386 , 0.99439335, 0.9948684 , 1.0294852 , 0.9947124 ,
       0.9999331 , 0.97648036, 1.0039748 , 1.03191   , 0.9997994 ,
       1.007719  , 1.0072381 , 0.9915846 , 1.000158  , 0.9945337 ,
       1.0102059 , 0.9932021 , 1.0064938 , 1.0083274 , 0.99581486,
       1.0112902 , 0.9974787 , 0.99379754, 1.0094107 , 1.006448  ,
       0.998684  , 1.0257366 , 1.0021584 , 1.0182785 , 1.0138922 ,
       1.0019908 , 1.0013751 , 1.004689  , 1.014022  , 1.0159864 ,
       0.9878555 , 1.0156977 , 0.98558855, 1.005938  , 0.9864113 ,
       0.9988976 , 1.0216147 , 0.99365807, 0.99502647, 0.99987406,
       0.9937757 , 1.0000154 , 1.0071701 , 1.0052654 , 1.0153283 ,
       0.98142785, 1.0088383 , 1.0247492 , 0.9891379 , 1.0154368 ,
       1.004801  , 0.99090326, 1.0215132 , 0.9876705 , 1.000368  ,
       0.99604017, 1.0165125 , 1.0064093 , 1.0178586 , 0.9916523 ,
       0.9968899 , 0.98369396, 1.0025263 , 0.9970071 , 0.9958662 ,
       0.99558043, 0.9964808 , 1.004265  , 1.0140228 , 0.9960981 ,
       1.0048743 , 1.0224355 , 1.0100284 , 1.0079238 , 1.030262  ,
       0.99613523, 1.0127262 , 1.0252694 , 1.0016563 , 1.0122712 ,
       1.01634   , 1.0075729 , 0.98780084, 1.0254399 , 1.0054761 ,
       1.0102295 , 1.0077003 , 1.0127903 , 1.0026475 , 0.9862498 ,
       1.0077026 , 1.0267675 , 1.0032125 , 1.0088329 , 0.9955647 ,
       1.0048152 , 1.0034561 , 0.9905855 , 0.9959828 , 1.0175904 ,
       1.015054  , 1.0106435 , 0.9961912 , 0.98229563, 1.0322626 ,
       1.0271133 , 1.0039814 , 1.0028765 , 1.0166028 , 0.99879813,
       0.9954542 , 0.9973254 , 0.9971245 , 1.0389042 , 1.012572  ,
       1.0219216 , 1.0137467 , 1.0020235 , 1.0145441 , 0.99926966,
       1.0070075 , 1.0060043 , 0.99903995, 1.0097891 , 1.0396726 ,
       1.0061725 , 0.9773774 , 1.0292406 , 0.9956178 , 1.0335244 ,
       0.9869542 , 0.989594  , 0.99024636, 0.9999996 , 1.0254513 ,
       1.0129894 , 1.0049136 , 1.0090475 , 1.0036627 , 1.0021294 ,
       0.9978769 , 1.0174701 , 0.99651515, 1.0206422 , 0.9925839 ,
       0.9972464 , 1.0159414 , 1.017846  , 0.9901508 , 1.0248462 ,
       1.004592  , 1.0131232 , 1.0141331 , 1.0360937 , 0.99818563,
       1.0133919 , 1.0310498 , 1.0118002 , 0.9996308 , 1.0062585 ,
       1.002398  , 1.0056614 , 0.9980756 , 1.014517  , 1.0054444 ,
       0.99606997, 1.0081854 , 1.0149089 , 1.0162907 , 0.9986263 ,
       1.0025667 , 1.0028551 , 1.02224   , 1.0072553 , 0.99804026,
       1.0090886 , 1.0004845 , 1.0089017 , 1.0172378 , 0.99492055,
       1.0418549 , 0.99359286, 1.0079802 , 1.0038625 , 1.0468245 ,
       1.0175198 , 1.002983  , 1.0254571 , 1.0050873 , 1.0060575 ,
       1.0158637 , 1.0220455 , 0.9988914 , 0.9904896 , 1.0143247 ,
       1.0258061 , 1.0089561 , 0.98609334, 1.0128363 , 0.9934098 ,
       0.99439746, 1.0216142 , 1.0289338 , 1.0124724 , 1.0125705 ,
       1.0103387 , 1.004669  , 1.0000037 , 0.993007  , 1.0044818 ,
       1.0102528 , 1.020705  , 1.0119146 , 1.0324855 , 1.005723  ,
       1.0099436 , 0.998032  , 1.0317719 , 0.9920432 , 0.99476594,
       1.0529662 , 1.0305996 , 1.0044304 , 1.0278411 , 1.0054629 ,
       1.0060579 , 0.9975681 , 1.0415226 , 1.0035135 , 0.9707799 ,
       0.99275756, 1.0120612 , 0.98908275, 1.0096085 , 1.0011965 ,
       0.9734907 , 1.0212989 , 0.993351  , 1.0091743 , 1.01874   ,
       1.0265949 , 1.0161425 , 0.99584556, 1.0003282 , 0.9977522 ,
       1.0120515 , 1.0030825 , 1.023476  , 0.99529785, 0.99219596,
       0.98671806, 0.9908994 , 1.0016233 , 1.0054567 , 1.0293549 ,
       1.0032568 , 0.9931694 , 1.0187725 , 0.9919093 , 0.9882556 ,
       1.0293554 , 0.99602616, 1.0095798 , 1.0238178 , 1.0026515 ,
       1.0207657 , 0.9961298 , 1.02037   , 1.0182027 , 1.0063821 ,
       0.9970796 , 1.0068284 , 1.009117  , 1.0060354 , 1.0057285 ,
       1.0034305 , 0.9980447 , 1.0038176 , 1.0251445 , 0.9997636 ,
       1.0111699 , 0.9963389 , 1.0022577 , 1.0280575 , 0.99494207,
       0.99957865, 0.9990434 , 0.99841255, 1.0161402 , 1.0098026 ,
       0.9967501 , 0.99633515, 0.9982382 , 1.0088845 , 1.0063671 ,
       0.9995962 , 1.0070723 , 1.0094799 , 1.0244292 , 0.9969569 ,
       0.9934477 , 0.98925465, 0.9960859 , 1.011557  , 1.0070065 ,
       1.0118369 , 1.0022557 , 0.9987206 , 0.99700403, 0.994291  ,
       1.0299233 , 1.0080974 , 1.0080595 , 1.0118225 , 1.0252609 ,
       0.9912477 , 0.99939895, 0.9952947 , 1.0100876 , 1.0110152 ,
       0.9867851 , 1.032744  , 1.0165514 , 1.0359929 , 1.006422  ,
       1.0032892 , 0.99795324, 1.0162137 , 0.99516135, 1.0148046 ,
       0.9802789 , 1.0357736 , 1.0205787 , 1.0070854 , 1.0136052 ,
       1.0252142 , 1.0362498 , 1.015372  , 1.0255996 , 1.0072194 ,
       1.022509  , 1.0049584 , 0.99491626, 0.9851258 , 1.009961  ,
       1.0120527 , 0.99725264, 0.99099135, 0.9998893 , 1.0144172 ,
       0.9880515 , 1.0002506 , 1.006104  , 1.0098952 , 1.0170792 ,
       1.0019265 , 0.99732757, 1.0160066 , 0.99043924, 1.0385591 ,
       0.9966061 , 1.0035129 , 1.0073609 , 1.004791  , 1.0159754 ,
       0.99538636, 1.0251582 , 0.9911352 , 0.9981918 , 1.0479537 ,
       1.0035564 , 1.002762  , 1.0362017 , 0.9996598 , 0.9878342 ,
       1.0180581 , 1.0029228 , 0.9982421 , 1.0120633 , 1.0021535 ,
       1.0038882 , 0.99770623, 1.0073166 , 1.0041358 , 0.9988884 ,
       1.0047386 , 1.0008334 , 1.011687  , 1.0100831 , 0.9970835 ,
       1.0055473 , 1.0218143 , 0.99862516, 0.99467015, 1.0105206 ,
       1.0148593 , 1.0134299 , 0.9858326 , 1.0265639 , 1.0134511 ,
       0.9927097 , 1.0351007 , 1.0010576 , 1.0045508 , 0.99301225,
       1.0126652 , 1.0230645 , 0.9973333 , 0.994827  , 0.99782604,
       0.99534565, 0.99964553, 1.0265727 , 1.003317  , 1.0254604 ,
       1.0308108 , 1.0246428 , 1.0300235 , 1.0094435 , 0.99866843,
       1.0047339 , 1.0048522 , 1.0273888 , 0.997363  , 1.0146745 ,
       1.000579  , 1.0296537 , 0.9994321 , 1.0203142 , 1.0104302 ,
       1.0293196 , 1.0173696 , 0.99766517, 0.99963826, 0.9960888 ,
       0.9977847 , 0.9974771 , 0.99832016, 1.0132976 , 0.9977667 ,
       0.99368656, 1.0027006 , 1.0110327 , 1.0228641 , 1.0044727 ,
       1.0095555 , 1.0087065 , 1.006845  , 0.9980405 , 0.9994646 ,
       1.0064641 , 0.9946625 , 1.0091588 , 1.0003414 , 0.9987634 ,
       0.99384844, 1.008955  , 0.99566495, 1.0116199 , 1.0084277 ,
       1.0097346 , 1.0156415 , 1.0468843 , 1.0050223 , 1.0217613 ,
       0.9851463 , 1.0039439 , 0.99329793, 0.99534935, 0.9906439 ,
       1.012211  , 1.0118922 , 1.0046005 , 0.98479056, 0.9954143 ,
       1.0224327 , 1.0238864 , 0.9990121 , 0.9958112 , 1.0014845 ,
       1.0078728 , 0.9988501 , 1.0081458 , 0.9919375 , 1.0010757 ,
       1.0236508 , 1.0026699 , 1.0169389 , 0.99513376, 1.0020944 ,
       0.992281  , 0.9937472 , 1.021638  , 0.9893153 , 1.0016865 ,
       1.0111064 , 0.9954043 , 0.99247086, 1.0222107 , 0.97969604,
       0.9952911 , 1.0185422 , 0.99307674, 1.0082742 , 1.0186257 ,
       0.9880355 , 1.0053884 , 0.99429566, 0.9966938 , 1.0107561 ,
       0.9964685 , 1.0043256 , 1.0289394 , 1.0130831 , 1.0049713 ,
       1.0129335 , 1.0039052 , 0.99976856, 0.98241955, 1.014061  ,
       1.0286558 , 1.0027972 , 1.0057244 , 0.99566215, 0.9996274 ,
       0.9941628 , 1.0004425 , 1.0340989 , 1.00063   , 1.0042406 ,
       1.0171088 , 1.0065941 , 1.0150945 , 0.99698156, 0.9968558 ,
       1.0051104 , 1.0051342 , 1.0258955 , 1.0023017 , 1.0395632 ,
       1.0149456 , 1.0148376 , 1.0237424 , 0.9968132 , 1.0345161 ,
       1.0011985 , 1.0074096 , 0.979402  , 1.0325606 , 1.0044928 ,
       1.0165545 , 1.0084064 , 0.9917211 , 0.9942403 , 0.99978936,
       1.0014046 , 1.0113724 , 0.99946123, 1.0055873 , 1.010856  ,
       1.0077666 , 1.0084171 , 0.99653256, 0.99109304, 1.0137421 ,
       1.0109109 , 0.9864337 , 1.0088319 , 0.9927605 , 1.0048952 ,
       1.001994  , 1.0350969 , 0.9915115 , 1.0220858 , 1.0111691 ,
       1.0139816 , 0.99451166, 1.0023842 ], dtype=float32), array([ 3.19380709e-03,  1.29964268e-02, -1.14205806e-02, -5.46565698e-03,
       -5.93634276e-03, -2.52831392e-02, -1.69898709e-03, -3.32307331e-02,
        1.44578144e-02, -2.20401655e-03,  1.40641872e-02,  2.25710752e-03,
        1.84266432e-03, -6.66836463e-03,  7.90178217e-03,  4.48783394e-03,
       -1.42781567e-02, -4.82522557e-03, -2.87014176e-03, -4.12120018e-03,
       -1.54435989e-02, -2.12525073e-02, -6.20237645e-03, -1.12723624e-02,
       -8.20842199e-03,  7.39113521e-03,  1.13080097e-02,  2.10061427e-02,
        1.24712649e-03, -1.23179685e-02,  1.61972444e-03, -9.65544116e-03,
        8.94138310e-03, -1.05889793e-02,  6.87104184e-03, -2.01432277e-02,
       -7.09578162e-03, -1.06581161e-02, -6.77868119e-03,  5.06785186e-03,
        2.97901337e-03,  3.67643684e-03, -8.22269823e-03, -1.08625321e-02,
       -5.62813226e-03, -3.28138210e-02, -1.31840296e-02, -1.20846997e-03,
       -4.03445475e-02,  5.24502667e-03, -1.29596060e-02,  1.31310206e-02,
       -1.51311057e-02,  1.51474811e-02, -1.96297583e-03, -1.75326271e-03,
       -6.53104112e-03, -2.46986952e-02, -7.16413930e-03,  3.39987106e-04,
       -3.12892906e-03,  7.32550863e-04, -2.00705528e-02, -6.09305548e-03,
        1.45253725e-02, -7.28521496e-03, -1.02434941e-02,  1.59178916e-02,
       -4.27474472e-04, -1.80248939e-03, -2.49095552e-04, -1.41805841e-03,
       -8.15806352e-03,  3.30192415e-05, -5.90939121e-03, -1.88391451e-02,
        5.61124319e-03, -8.14718136e-04, -3.42826126e-03, -1.91597175e-02,
       -1.41826430e-02,  2.77954922e-03, -1.13979587e-03, -3.98889743e-03,
        2.22090562e-03,  8.04887444e-04,  3.29010980e-03, -2.69760820e-03,
        9.45928507e-03,  4.20153746e-03, -9.55135003e-03, -1.74469259e-02,
       -6.03582058e-03, -1.27709471e-02, -3.60899698e-03, -1.81912351e-03,
       -8.23856238e-03, -1.05204349e-02, -2.38626148e-03,  8.01976491e-03,
        3.92383244e-03,  2.45771511e-03,  1.02580348e-02, -1.57888010e-02,
       -3.70353693e-03, -1.51497396e-02, -2.68481672e-02, -7.89549202e-03,
        9.39099211e-03, -1.95605983e-03, -8.71946570e-03, -2.19257437e-02,
       -1.43555319e-02,  2.73002917e-03, -2.75751413e-03,  6.52531208e-03,
        8.91712122e-03, -8.97962134e-03,  2.54703849e-03, -2.27170717e-03,
       -8.95681325e-03, -3.39325070e-02, -1.04361260e-02,  2.08903803e-03,
       -1.71878040e-02, -1.62878931e-02,  8.26124393e-04,  1.16467848e-02,
        7.67449709e-03,  2.49992416e-04, -7.11498316e-03,  1.32097593e-02,
       -6.42606197e-03, -4.25935630e-03, -9.39811952e-03, -2.26313286e-02,
        2.44391505e-02, -2.32919324e-02, -1.39049608e-02, -7.93154072e-03,
        8.01006705e-03, -1.00782523e-02, -2.56148120e-03, -9.74117592e-03,
       -1.75284240e-02,  1.18455598e-02, -8.41316418e-04, -2.76515931e-02,
       -2.10224111e-02, -4.54296358e-03, -1.44697959e-02, -9.31722671e-03,
       -8.84944480e-03, -2.66574211e-02,  8.74422304e-03, -7.81301036e-03,
       -3.11860675e-03, -9.86057706e-03, -1.15247555e-02, -1.97612052e-03,
        4.44359379e-03, -1.33064967e-02, -1.44126546e-02, -1.23931328e-02,
       -6.20555365e-03, -3.39232199e-02,  7.12682586e-03, -1.15109014e-03,
        8.28647148e-03, -1.52509492e-02,  7.67017715e-03, -1.38767315e-02,
       -3.10201081e-03, -1.35570494e-02, -1.96192116e-02, -1.06672682e-02,
       -1.95695157e-03,  2.25962116e-03, -2.76924088e-03, -3.62522947e-03,
       -4.70621092e-03, -1.32483235e-02, -4.48455522e-03, -4.86867270e-03,
       -3.22863529e-03, -7.06914533e-03,  1.73268598e-02,  3.54273128e-03,
        4.85746982e-03,  2.03961600e-03, -6.42021466e-03, -1.76335592e-02,
       -1.18431523e-02, -1.26435626e-02,  2.06614342e-02,  8.87381658e-03,
       -2.81681214e-03, -9.29811411e-03,  5.44544915e-03, -3.12983128e-03,
        1.84784289e-02, -5.63263986e-03,  1.29485531e-02, -1.28415208e-02,
       -4.85430332e-03, -4.53492953e-03,  8.52344837e-03, -1.80440396e-02,
        4.35845321e-03,  5.41594764e-03, -1.40184471e-02, -7.31337490e-03,
       -1.18036717e-02, -7.78803229e-03, -1.48711354e-02, -9.02099442e-03,
        3.49631789e-03,  1.62380747e-02,  7.57694524e-03, -2.76336772e-03,
       -3.37264640e-03, -7.77611835e-03, -8.68620723e-03, -1.80657171e-02,
        5.97717147e-03,  1.75167173e-02,  8.71019205e-04,  3.39447707e-02,
       -1.40750734e-02, -6.30944176e-03,  1.51538616e-02,  4.46911855e-03,
        1.81296666e-03, -7.44482968e-03, -2.55669598e-02, -5.46860741e-04,
       -1.70523804e-02, -1.05832126e-02, -2.37893872e-02,  2.45092693e-03,
       -2.45084544e-03,  2.37068366e-02,  5.31930476e-03, -1.27655128e-02,
       -3.94586800e-03, -2.42713112e-02,  5.08412078e-04,  5.53038111e-03,
       -5.90187963e-03, -8.77575949e-03, -1.01744826e-03, -2.46051396e-03,
       -9.42367036e-03,  2.78590666e-03,  3.36187426e-03, -1.71319805e-02,
       -2.82063559e-02, -9.04128514e-03,  6.31013792e-03,  3.90451460e-04,
       -8.65061209e-03, -8.62194505e-03, -1.03878314e-02, -2.13856939e-02,
       -7.19600730e-03,  1.41466660e-02,  4.60571982e-03,  4.09193011e-03,
       -8.21476057e-03,  2.62307329e-03,  9.42657422e-03,  7.65940815e-04,
       -6.73224032e-03, -7.91012589e-03, -2.54483335e-02, -5.20015275e-03,
       -1.21103879e-02, -3.01428065e-02,  9.74000990e-03, -3.60992551e-02,
       -4.05191444e-04, -1.17174769e-03,  9.40748665e-04, -1.62800737e-02,
       -3.29559706e-02, -1.06169442e-02, -8.46924633e-03, -1.60412695e-02,
       -9.54581238e-03, -1.75719652e-02, -7.97918998e-03, -2.67331442e-03,
        6.79570949e-04, -1.21950628e-02, -8.76163878e-03, -1.48396818e-02,
       -2.31768494e-03,  2.84725688e-02,  2.67811090e-04, -1.13137874e-04,
       -2.01258939e-02, -6.46511698e-03, -1.53530827e-02, -2.79602576e-02,
       -3.66602675e-03, -1.83039308e-02, -2.60852799e-02, -9.23169963e-03,
        4.82935179e-03,  9.64154396e-03,  1.20919077e-02, -1.92146911e-03,
        7.61794113e-03,  6.06800709e-03,  1.93554175e-03, -1.36248851e-02,
       -4.40366939e-03,  5.81261050e-03,  2.06934866e-02, -5.69536863e-03,
       -5.24737081e-03,  9.65150911e-03, -2.12238189e-02, -6.22448279e-03,
        1.54812448e-02, -2.44362489e-03,  1.81009285e-02, -8.36476125e-03,
       -6.29280182e-03, -2.05592588e-02, -1.96630564e-02,  6.44670727e-05,
       -9.54755954e-03,  2.21467409e-02,  2.90105905e-04,  9.43555031e-04,
        1.00445086e-02, -1.82189681e-02, -5.61818574e-03, -1.27093801e-02,
        1.14247119e-02, -3.63438507e-03,  1.21589075e-03, -1.10864835e-02,
       -1.43860362e-03,  7.85951503e-03,  1.11173866e-02, -8.62657372e-03,
        1.14026330e-02, -3.31403851e-03,  4.91071318e-04,  1.49837313e-02,
        1.16211399e-02,  1.23996530e-02, -1.90299489e-02, -1.44176073e-02,
       -6.71835896e-03, -5.69456443e-03, -1.02178464e-02,  6.20996580e-03,
       -9.29142232e-04, -8.06741975e-03,  1.55071709e-02, -8.03673931e-04,
        1.93939228e-02, -1.24066684e-03, -8.61090142e-03, -1.04972413e-02,
       -2.40441761e-03, -8.78311787e-03, -2.27204207e-02, -1.79739855e-02,
       -8.29607528e-03, -1.80108566e-02, -1.04099046e-02,  9.22469702e-03,
       -3.51486332e-03, -2.68835519e-02,  4.98307589e-03, -1.25402752e-02,
       -2.68545710e-02, -1.21340472e-02,  4.78950143e-03, -9.32324026e-03,
        3.62791331e-03, -2.94760875e-02, -2.00967472e-02, -5.57312276e-03,
        3.35380668e-03,  2.34104134e-03, -1.69641040e-02, -9.39487654e-04,
       -4.84063243e-03, -3.44409398e-03, -4.89079766e-03, -2.18183920e-02,
       -1.70053716e-03, -8.41260981e-03,  4.47413931e-03,  1.35914991e-02,
       -1.08264619e-02, -4.81255818e-03, -1.76885480e-03,  6.06451323e-03,
       -1.14364298e-02, -1.15498397e-02,  3.25109274e-03, -2.44853627e-02,
       -8.11625551e-03, -8.46807845e-03, -6.69415155e-03, -1.16209816e-02,
        2.25882158e-02, -3.15191783e-02,  7.43777165e-03, -1.74062476e-02,
        3.83787090e-03, -1.49396239e-02,  1.20748356e-02, -1.66181400e-02,
        3.81118921e-03, -1.50143951e-02, -1.26590589e-02, -7.85184279e-03,
       -3.93701065e-03, -6.19830284e-03, -1.71385948e-02, -5.32689411e-03,
       -5.35025261e-04,  6.93524443e-03, -2.48933211e-02,  9.65314079e-03,
       -7.16286199e-03, -3.68721969e-02, -1.16046183e-02, -1.33528449e-02,
       -1.13691180e-03, -1.28070787e-02, -2.48117577e-02, -1.86766428e-03,
       -1.37016615e-02, -4.70310962e-03, -1.35968551e-02,  1.28246844e-02,
       -8.96650273e-03,  1.24955932e-02, -1.21257240e-02, -4.49166633e-03,
        1.80915035e-02, -1.65362132e-03, -1.29689686e-02, -2.60512461e-03,
       -2.07445165e-03, -2.12887265e-02,  1.41292019e-02, -7.22158793e-03,
       -8.90071690e-03,  1.00231171e-02, -2.96130631e-04, -6.38755923e-03,
       -4.32091765e-03, -3.70511226e-03, -2.06354400e-03,  1.08060718e-03,
        2.45913427e-04, -1.20185222e-02, -4.30710986e-03, -1.74172260e-02,
        6.18468621e-05, -7.15801492e-03, -8.36642180e-03, -3.12896334e-02,
       -9.63603612e-03, -8.68184213e-03, -1.12677319e-03, -4.98579536e-03,
       -1.41490838e-02, -1.98451225e-02, -7.38015398e-03,  4.55549965e-03,
       -9.95714962e-03, -2.15559751e-02, -1.51985732e-03, -5.60208689e-03,
        1.71649866e-02, -3.44322212e-02, -2.24742573e-02,  2.25789932e-04,
        7.89400283e-03, -1.33292740e-02, -5.63709112e-03, -1.10058989e-02,
       -9.91946086e-03, -2.80646048e-02,  2.01814924e-03,  2.94782892e-02,
       -1.33660175e-02, -1.58560742e-02,  8.37085117e-03, -7.63923768e-03,
       -9.90673155e-03,  2.84646172e-03,  2.15158537e-02, -1.77141477e-03,
       -1.00546135e-02, -1.55925602e-02, -4.29399172e-03,  7.04613142e-03,
       -3.07400525e-03,  2.62850849e-03,  7.12719653e-03, -4.58292384e-03,
        1.79283731e-02, -1.06384996e-02,  1.18801082e-02, -2.77496967e-03,
       -4.24810406e-03, -1.42481094e-02, -1.80952847e-02, -1.93565786e-02,
       -8.38302542e-03, -1.30947484e-02, -2.80177244e-03,  1.11406762e-02,
       -1.65970286e-03, -7.31704384e-03, -1.04478365e-02, -2.33432627e-03,
       -2.64115557e-02, -1.66131824e-03,  2.07418343e-03, -9.98871308e-03,
       -2.30183899e-02, -3.47674428e-03, -4.93945880e-03, -1.47801090e-03,
       -1.36956470e-02, -2.78919414e-02, -2.30343151e-03, -1.67702772e-02,
       -2.85163708e-03, -1.09059047e-02, -1.50586683e-02, -8.67986120e-03,
       -6.08624332e-03,  1.51397800e-02,  2.51459330e-03,  2.39598402e-03,
       -7.57109653e-03,  4.23040986e-03, -8.32200516e-03, -1.30951991e-02,
       -6.37850724e-03,  7.66470004e-03, -2.15832423e-03, -6.71913102e-03,
       -3.27306762e-02, -4.86109545e-03,  1.63658448e-02, -3.68793932e-04,
        3.43364896e-03,  8.06533499e-05,  1.34173930e-02,  1.48159144e-02,
        1.84998065e-02, -2.02348270e-02,  1.80538222e-02, -9.26078577e-03,
        6.92846766e-03, -1.33914303e-03, -2.15747934e-02, -1.81427989e-02,
       -2.52608173e-02,  3.24985507e-04, -2.65673175e-03,  6.37835066e-04,
       -2.29144488e-02, -4.26010042e-03, -1.82078909e-02, -8.35129432e-03,
       -9.13266093e-03,  7.23847467e-03, -2.82359472e-03, -5.07675251e-03,
        2.92139361e-03, -2.78135925e-03, -1.39042446e-02,  4.18548658e-03,
        5.63825961e-05, -4.78065107e-03,  1.14677008e-02, -1.21683087e-02,
        8.32963362e-03,  7.48959649e-03,  1.26998806e-02, -2.43543321e-03,
        2.75470852e-03, -9.11887363e-03, -2.71526095e-03,  1.20152570e-02,
       -1.06115332e-02, -3.62043327e-04,  4.49876301e-03, -3.16669676e-03,
       -6.13518571e-03, -1.01350099e-02,  1.64324678e-02, -3.88782425e-03,
       -9.13550518e-03, -1.01523865e-02,  9.78779048e-04,  3.63339297e-03,
       -3.41466703e-02, -6.00586971e-03, -1.24341743e-02, -1.10933529e-02,
       -3.06631699e-02, -2.35966947e-02,  2.31359387e-03, -1.57883279e-02,
       -9.93763190e-03, -1.49247786e-02, -2.50548939e-03,  1.11382073e-02,
        1.00115372e-03, -1.48252016e-02, -2.04149149e-02, -2.05796212e-03,
       -1.31652446e-03, -8.20144732e-03,  6.67533837e-03,  6.87287888e-03,
        1.62453316e-02, -7.29992520e-03, -1.06832776e-02,  1.31953740e-02,
       -2.16123951e-03,  3.10926628e-03, -2.72643305e-02,  2.21422408e-03,
       -5.53238392e-03, -5.61141269e-03,  1.58038363e-02, -6.54348638e-04,
        6.05643401e-03, -9.93343629e-03, -5.10725519e-03,  1.13092652e-02,
        1.51195307e-03, -1.22576561e-02, -6.06987253e-03, -1.39196832e-02,
       -8.00565910e-03, -7.62048038e-03,  8.05685390e-03, -5.78927202e-03,
       -4.20524320e-03, -7.29139196e-03, -1.14259925e-02, -1.54858474e-02,
        1.63278065e-03,  9.14835371e-03, -2.23173089e-02, -4.04186547e-03,
       -1.39925871e-02,  9.43806430e-04, -1.00093093e-02, -6.22382015e-03,
        1.41401272e-02, -2.08935030e-02, -1.81207024e-02,  7.16051972e-03,
        9.29876883e-03,  1.50379557e-02, -2.97912280e-03, -1.11430008e-02,
       -5.69649646e-03, -2.93540247e-02,  6.21245336e-03,  3.54652549e-03,
        5.90218836e-03, -2.44730618e-03, -1.55559564e-02, -6.69362955e-03,
       -1.23985475e-02,  1.07703032e-02, -2.60816142e-03,  1.08124223e-03,
        4.95202467e-03, -5.04011214e-02,  2.48341166e-05,  8.47221352e-03,
        4.70299600e-03, -5.01402095e-03,  2.30546622e-03,  2.67175352e-03,
        4.38514026e-03, -1.08393170e-02, -1.24859801e-02,  3.68918903e-04,
       -2.81644694e-04, -5.94924949e-03, -4.84039541e-04,  4.57779795e-04,
        3.83456447e-03, -1.20346632e-03,  4.10071108e-04, -5.52040339e-03,
        3.52037651e-03,  8.82131420e-03,  1.96941546e-05, -2.28516292e-03,
        1.54079078e-02, -8.74742772e-03,  2.21815240e-02,  3.25423926e-02,
       -9.36070178e-03,  4.30988206e-04, -4.81589790e-03,  7.41325726e-04,
       -6.58271648e-03, -3.26242410e-02, -2.33428776e-02, -1.59544051e-02,
       -1.85809769e-02, -3.44941318e-02,  3.44360899e-03, -1.61311477e-02],
      dtype=float32), array([ 3.61873694e-02, -4.01840359e-02,  2.61131153e-02,  4.58156243e-02,
       -1.71761662e-02,  4.99263592e-02, -6.13068081e-02, -1.22101977e-02,
        6.19601808e-04,  3.16935144e-02, -1.75420102e-02,  6.58764765e-02,
       -1.96406078e-02,  6.70420751e-02,  3.14077139e-02, -2.69424487e-02,
        2.13423893e-02, -8.24860763e-03,  2.63523869e-02,  4.58723791e-02,
        1.00008501e-02,  1.52662816e-02,  1.29751200e-02,  1.48146050e-02,
       -2.55292002e-02, -1.09640183e-02, -2.90703438e-02, -4.46810536e-02,
       -6.73635751e-02,  2.82734875e-02, -2.98501328e-02, -1.01341764e-02,
       -3.47393639e-02,  8.66531581e-03, -3.89001034e-02,  8.61022901e-03,
        1.41882394e-02, -5.17696403e-02, -1.90593582e-02, -3.03677134e-02,
        3.05162501e-02, -2.77089085e-02, -4.61378582e-02, -1.05774160e-02,
       -2.52550282e-02,  5.18116988e-02,  2.67800223e-02,  3.55097204e-02,
        3.81824970e-02, -4.21417616e-02,  4.98723909e-02, -3.35706025e-02,
        6.93583712e-02, -2.02709492e-02,  2.08290312e-02,  8.13338999e-03,
        3.77367586e-02,  3.67099009e-02, -6.45442493e-03,  1.95329301e-02,
       -2.92305406e-02,  1.85477678e-02,  5.24692098e-03, -1.51664456e-02,
        1.70446057e-02,  2.82385182e-02,  4.63220552e-02,  5.77764679e-03,
       -6.12069294e-02,  1.25151873e-02, -5.69130469e-04, -3.39628756e-02,
       -5.44936163e-03, -8.67094845e-03, -4.05194350e-02,  2.53361668e-02,
       -2.46342886e-02, -4.75126924e-03,  2.62275096e-02,  2.03894102e-03,
        2.09006704e-02,  3.94630153e-03,  7.05969660e-03, -1.92993209e-02,
       -2.83289552e-02,  7.24158157e-03,  2.35464312e-02,  5.27507849e-02,
       -3.66953984e-02, -1.02159858e-03,  2.57412083e-02,  3.60236801e-02,
        4.56629023e-02, -5.16011268e-02, -3.50489281e-02,  2.99486071e-02,
       -1.59987174e-02, -3.08987927e-02, -4.89955880e-02, -5.18730143e-04,
       -3.13471183e-02,  9.48846247e-03, -1.30870603e-02,  4.47217226e-02,
        4.55794074e-02,  2.84789577e-02,  2.17113923e-03,  2.01731808e-02,
       -5.65899163e-02,  3.23396884e-02, -5.68349436e-02,  5.65204509e-02,
        6.21198909e-03,  3.16719264e-02,  1.28186960e-02, -8.57717125e-04,
        3.09828278e-02,  3.04913353e-02, -4.90441211e-02,  2.63581928e-02,
        1.48333972e-02, -4.70984448e-03,  9.31131374e-03, -2.63667516e-02,
        4.51405607e-02,  2.62086987e-02, -2.15594880e-02, -4.47653979e-02,
       -1.54908635e-02,  3.97149548e-02,  6.47708699e-02, -1.59217063e-02,
        2.82474235e-03, -2.35128719e-02,  4.81729116e-03, -5.57800755e-02,
       -4.30200025e-02,  3.39976773e-02, -1.30994311e-02,  4.87666540e-02,
       -2.27893200e-02,  3.56355160e-02, -3.70624661e-02,  5.82138486e-02,
        3.42651345e-02,  2.63287276e-02, -2.05201618e-02,  1.76777765e-02,
        5.18055223e-02,  1.85843073e-02,  4.27128561e-02,  3.91847119e-02,
        2.41485871e-02,  4.95523475e-02,  2.58231051e-02, -3.44960429e-02,
       -6.25146478e-02,  2.64964085e-02,  3.13037969e-02,  1.02324942e-02,
        3.15335952e-02, -2.52230349e-03, -1.02758892e-02,  2.55269445e-02,
        1.05614951e-02, -1.53905712e-02,  2.62740883e-04,  4.25043292e-02,
       -2.37279497e-02,  2.27999538e-02,  2.31744461e-02,  5.53964488e-02,
       -1.98165644e-02,  2.14420967e-02,  5.50641939e-02,  3.02836020e-02,
       -1.19247884e-02, -3.26321051e-02, -3.92374285e-02, -2.93372422e-02,
       -3.88142690e-02,  5.19957319e-02, -1.89470332e-02,  2.34587416e-02,
       -9.95462667e-03, -2.22883504e-02,  1.84137952e-02, -3.18569280e-02,
        1.45124132e-02,  2.23416425e-02, -2.32477635e-02,  4.05132361e-02,
        4.22007330e-02,  5.77237085e-03, -2.70360634e-02,  2.27585975e-02,
        4.31206310e-03,  4.76791747e-02, -1.09817609e-02,  1.85702685e-02,
        3.70674953e-02,  3.17509063e-02, -6.14002086e-02,  1.84756669e-03,
       -9.58196167e-03, -7.67230568e-03, -6.05528988e-02,  3.16840485e-02,
        5.40425219e-02, -9.80424508e-03,  5.08167893e-02, -8.20763223e-03,
       -2.44283490e-02,  1.53444782e-02,  3.03459316e-02, -6.57596719e-03,
       -1.30289758e-03, -3.34339403e-02, -5.41522205e-02, -7.46394927e-03,
        4.00743634e-02, -4.76944819e-02,  2.94279829e-02, -1.50631089e-02,
       -4.69606258e-02, -7.77510926e-03, -4.86282706e-02, -6.61854595e-02,
       -5.15788123e-02,  3.11977752e-02, -4.33770716e-02,  2.12617405e-02,
       -2.55097561e-02,  3.83794196e-02,  5.69223799e-02, -5.34042157e-02,
       -2.02666316e-02,  4.31199782e-02,  2.83291172e-02, -2.60402076e-02,
        3.98401683e-03, -6.79369494e-02, -2.89254133e-02, -3.75068635e-02,
        4.54945769e-03,  5.33852354e-02, -4.40012701e-02,  1.40974885e-02,
        3.94148640e-02,  4.93204482e-02,  2.44346894e-02, -3.02412175e-02,
        1.57932211e-02, -2.78020203e-02,  4.45545912e-02,  3.38495672e-02,
        3.11914855e-03,  3.31889950e-02,  1.99211407e-02, -6.79741148e-04,
       -2.58486904e-03,  3.98832932e-02, -1.99198555e-02,  6.11802824e-02,
       -4.72914428e-03, -4.17638347e-02, -3.11276428e-02,  1.06289824e-02,
        3.74639183e-02, -3.45020778e-02, -3.58614661e-02,  2.04412565e-02,
       -2.10273471e-02,  5.10035343e-02,  4.36006226e-02,  4.97579575e-02,
        2.23062746e-02,  5.79043701e-02,  2.09754370e-02,  4.86047678e-02,
        3.24341585e-03,  2.42611337e-02,  1.95935518e-02,  2.15107854e-02,
        6.46049231e-02,  5.49107529e-02, -1.12401964e-02, -2.86820009e-02,
        2.94770440e-03,  3.22504342e-02,  3.25632654e-02, -5.29558249e-02,
        2.83845197e-02, -1.20550430e-04, -1.85684357e-02,  5.44014089e-02,
        1.71832014e-02, -4.27675471e-02,  3.03472988e-02, -2.01110430e-02,
        4.36091498e-02,  2.97144987e-02,  2.76003163e-02,  4.21952382e-02,
        8.28189868e-03,  3.30585130e-02,  2.56582610e-02,  5.00067696e-02,
       -2.43970845e-02,  5.05686970e-03,  2.60017850e-02, -2.92283427e-02,
       -4.46723476e-02, -4.07756045e-02, -1.51935350e-02,  1.19410176e-02,
        3.71371843e-02,  3.01435813e-02, -3.24413218e-02,  5.17127290e-03,
       -2.19369698e-02, -2.47333311e-02,  3.30935940e-02,  2.66307853e-02,
       -5.90910728e-04,  8.97795800e-03, -3.01009417e-02,  5.47210202e-02,
        4.81508113e-02,  1.60209741e-02,  8.25375840e-02, -4.94455956e-02,
        3.49981710e-02, -1.71071105e-02,  3.55581455e-02,  3.82861085e-02,
       -1.82742067e-02,  5.03012203e-02, -6.15465604e-02,  4.80795093e-02,
        1.95670743e-02,  3.24362293e-02, -1.95723753e-02,  4.52720411e-02,
       -1.82342660e-02,  3.14529836e-02, -3.40213366e-02, -1.56316478e-02,
       -4.98773120e-02,  2.71641579e-03,  1.49810372e-03, -4.62980382e-02,
       -4.86326264e-03, -3.29066291e-02, -7.51650019e-04,  3.43651623e-02,
       -5.16340733e-02, -3.33944075e-02,  2.51824316e-03, -8.02100822e-03,
        2.23329421e-02,  2.74396893e-02, -2.89659481e-02,  3.70520391e-02,
       -5.86119555e-02, -3.47763076e-02,  3.00047975e-02,  6.66165799e-02,
       -3.02606709e-02,  1.53932460e-02,  6.76716566e-02,  8.19815397e-02,
       -2.29555406e-02,  4.89530638e-02,  5.04656956e-02, -2.56626401e-02,
        1.84358135e-02,  2.99035255e-02, -1.27944704e-02, -1.91382077e-02,
        4.93072905e-03,  4.42518899e-03,  2.11879704e-02, -4.31839265e-02,
        2.74380464e-02,  2.28103064e-02,  5.39990254e-02, -1.82948615e-02,
       -4.09623273e-02,  5.45031354e-02,  5.32502867e-02,  5.26229776e-02,
       -3.47477570e-02,  5.63003309e-02, -1.09935682e-02,  4.51214723e-02,
        2.08521578e-02, -1.95352687e-03, -1.21794371e-02, -4.26263809e-02,
        2.46536192e-02,  1.76042132e-02,  2.17558276e-02, -4.34436575e-02,
        4.33388613e-02,  2.76876544e-03,  1.98527165e-02,  5.52914999e-02,
       -2.36020852e-02, -1.90903861e-02,  4.19325829e-02, -3.29533592e-02,
       -5.84727116e-02,  1.28846169e-02, -2.18599718e-02,  3.84833887e-02,
        2.94663291e-02,  3.86036560e-02, -4.58434336e-02,  3.04371081e-02,
       -4.95298058e-02,  4.95766662e-02,  4.19082418e-02,  2.33481098e-02,
        3.05846054e-02,  4.58010659e-02,  5.07252589e-02,  1.94099210e-02,
        3.22357342e-02, -3.35375965e-02, -3.25685483e-03,  2.45349621e-03,
       -1.77107807e-02,  1.51572162e-02, -4.17257287e-02,  4.48223278e-02,
       -1.33874547e-02,  9.88388620e-03,  3.27630565e-02,  4.58009988e-02,
       -2.77986601e-02, -3.10274847e-02,  6.30320515e-03, -2.68267170e-02,
       -4.27814806e-03, -2.62886677e-02, -3.88301238e-02,  5.22911511e-02,
        2.86093093e-02,  1.11649269e-02,  4.00796533e-02,  2.00839341e-02,
        5.43503324e-04,  4.14731354e-02, -2.53384397e-03,  4.42975275e-02,
        1.96917411e-02, -1.15779638e-02,  1.45567947e-05, -8.67842638e-04,
        1.54602109e-02,  2.82464828e-02, -3.44165899e-02,  3.68397459e-02,
        4.01631780e-02, -2.79903896e-02,  8.05985555e-03, -9.09229554e-03,
        8.08295421e-03, -2.79607177e-02,  5.22973016e-04,  4.05103788e-02,
        3.52239683e-02,  6.14306219e-02, -3.16391438e-02, -2.81192958e-02,
        4.30730917e-02,  2.97272410e-02, -5.39411046e-02, -4.60064150e-02,
       -3.57566439e-02,  4.32881527e-02,  1.77266188e-02, -5.05770631e-02,
       -5.59398495e-02,  6.66280910e-02,  4.76829298e-02,  5.71360961e-02,
       -4.07525860e-02,  1.54706771e-02, -1.31977871e-02, -4.57090791e-03,
        1.79482698e-02, -3.21444646e-02, -2.10824162e-02, -6.57417178e-02,
       -3.91277932e-02,  1.84584962e-04,  4.61439975e-03,  2.02042181e-02,
        3.95341702e-02, -1.33766774e-02, -1.96312182e-02, -2.89913882e-02,
        4.43146080e-02, -1.41344126e-02, -3.68558951e-02, -5.63271306e-02,
        5.28617986e-02,  4.48366702e-02,  3.56770828e-02,  2.79417750e-03,
       -3.07995062e-02, -8.57190788e-03, -4.95722219e-02,  3.76165621e-02,
        4.07670625e-02,  1.68740507e-02,  4.36877050e-02,  4.06796858e-02,
       -2.98816455e-03,  2.04383451e-02,  6.62165135e-02, -2.40408233e-03,
       -1.16841765e-02,  4.91433255e-02,  6.37560934e-02,  3.66926864e-02,
        4.61457409e-02, -5.77817000e-02,  4.41998290e-03, -4.56210691e-03,
        7.64873847e-02,  1.09355645e-02,  1.84683576e-02,  2.21205913e-02,
       -1.99643262e-02,  5.91772869e-02, -1.30729284e-02, -5.07159904e-03,
        4.94458154e-02,  1.77195221e-02, -3.81729715e-02, -1.98721495e-02,
       -3.67857516e-02, -5.99661022e-02, -4.34248373e-02,  1.64937358e-02,
        4.66146804e-02, -2.88509578e-02, -7.91937858e-02,  7.42924362e-02,
        1.35691269e-04, -3.60830463e-02, -1.98282674e-02,  2.15460286e-02,
        4.58859988e-02,  3.74514759e-02, -3.87243442e-02,  3.24933901e-02,
        1.40038878e-02, -3.96203883e-02,  5.11275455e-02, -5.59710525e-02,
       -3.78760584e-02,  3.25729400e-02, -5.45777418e-02, -5.41399419e-02,
       -3.18091400e-02,  4.49783206e-02,  4.86023910e-02,  3.78579050e-02,
        5.74868731e-02,  6.81848358e-03,  1.34200696e-02,  3.70850437e-03,
        8.03817585e-02,  3.01912744e-02,  3.98220196e-02,  2.49065887e-02,
        4.72921431e-02, -3.76143083e-02, -1.65243801e-02,  1.09461825e-02,
       -2.44508255e-02,  2.73741242e-02,  9.90844145e-03, -6.10182248e-02,
       -9.24289040e-03,  1.07160509e-02, -1.94245856e-02, -2.40972526e-02,
        5.02487160e-02,  3.59086320e-02, -2.33324040e-02, -1.64423268e-02,
       -2.88071018e-02, -1.27234291e-02, -1.45343887e-02, -3.23957279e-02,
       -1.55177228e-02,  1.14189386e-02,  4.91329618e-02, -2.52594333e-02,
        2.18845941e-02,  5.40962815e-02,  1.77299287e-02, -3.02059781e-02,
        1.39134945e-02,  1.66635606e-02, -8.43744166e-03, -2.32955068e-02,
        3.02477516e-02, -3.68085876e-02,  5.92180118e-02, -2.49862466e-02,
        2.90289018e-02, -3.18376347e-02, -2.34308541e-02,  2.00477429e-02,
       -5.03895013e-03,  3.54954191e-02,  4.10635918e-02, -4.25282866e-02,
       -3.48854549e-02,  5.42029664e-02,  4.73664701e-02,  1.44404070e-02,
        3.76400468e-03,  4.47484804e-03, -4.84419465e-02,  2.09789518e-02,
       -2.53256373e-02,  3.48023698e-03, -3.27898860e-02, -5.60117811e-02,
       -4.29206900e-03, -5.56507744e-02,  7.07310438e-03, -1.32812103e-02,
       -4.59559672e-02, -2.21855938e-02,  1.15975039e-02, -4.42499556e-02,
       -4.31382395e-02, -3.51523049e-02, -3.10592763e-02,  6.69759698e-03,
       -4.13450859e-02,  1.26939742e-02,  2.19384264e-02,  2.35111061e-02,
       -2.17848960e-02, -4.18495163e-02, -4.39764112e-02, -7.58165075e-03,
       -1.63994972e-02, -4.69790772e-02,  6.93139015e-03,  1.54334875e-02,
        2.55779978e-02, -3.28917541e-02, -4.78315204e-02, -4.80253622e-02,
        6.31167321e-03, -2.25039255e-02,  4.52472530e-02,  1.64244380e-02,
       -3.06858625e-02,  1.54878218e-02, -8.09962004e-02,  3.67811732e-02,
       -2.32275147e-02, -4.10486618e-03, -1.90195926e-02,  1.18497210e-02,
        1.91914674e-03,  4.12417985e-02,  1.50791584e-02, -2.34364383e-02,
        1.19934911e-02, -3.42001952e-03, -3.73244621e-02, -3.97866368e-02,
        2.08808314e-02, -1.96957719e-02, -9.46451630e-03,  2.19509155e-02,
       -5.65863475e-02,  4.98431399e-02,  5.68789691e-02,  2.75796652e-02,
       -3.75572741e-02,  8.77961796e-03,  4.77064699e-02,  1.23763969e-02,
        1.78876780e-02, -3.01069543e-02,  3.50232869e-02,  5.54056428e-02,
        3.48044448e-02,  6.81420639e-02, -2.25916598e-02,  9.89556592e-03,
       -2.07571704e-02,  4.23906334e-02,  4.16336060e-02, -1.67666283e-02,
       -4.61354963e-02, -3.30255479e-02, -4.92666885e-02, -1.22899497e-02,
       -1.89880747e-02,  1.08521841e-02, -2.19756067e-02, -5.43637462e-02,
       -7.22839637e-03, -4.09295931e-02,  2.43815314e-02, -2.36669760e-02,
        4.64976691e-02,  4.56755795e-02,  2.77211866e-03,  1.94551628e-02,
        4.05015796e-02,  2.07845829e-02,  2.93772966e-02, -2.45444290e-02],
      dtype=float32), array([0.09383199, 0.1226365 , 0.10528981, 0.11115995, 0.08433434,
       0.09355072, 0.11703825, 0.09326658, 0.08710885, 0.11423087,
       0.10182596, 0.13164815, 0.09176278, 0.17756349, 0.10266969,
       0.09334048, 0.11165953, 0.08442932, 0.09574355, 0.11665441,
       0.08670007, 0.09751619, 0.09804195, 0.08466674, 0.10386182,
       0.08633773, 0.09400377, 0.11550955, 0.14497912, 0.10243125,
       0.10120019, 0.09068421, 0.10754538, 0.0946182 , 0.08793329,
       0.10845123, 0.09502926, 0.12867692, 0.08630609, 0.0912676 ,
       0.08859478, 0.10083783, 0.11096228, 0.08637682, 0.09207312,
       0.12411947, 0.0892372 , 0.10785121, 0.11230917, 0.0953493 ,
       0.12265114, 0.09820992, 0.13984588, 0.11174385, 0.09676232,
       0.08853481, 0.11013549, 0.12195388, 0.08396118, 0.09161489,
       0.08978237, 0.08584651, 0.09979835, 0.10238593, 0.0881617 ,
       0.09325639, 0.1366707 , 0.08632708, 0.10712564, 0.09214809,
       0.08747225, 0.09902009, 0.08488125, 0.08707622, 0.0984287 ,
       0.10242032, 0.09528342, 0.10191453, 0.08501448, 0.08333169,
       0.11128493, 0.09120261, 0.10526991, 0.09937689, 0.10037366,
       0.0852079 , 0.11589019, 0.09165196, 0.11839216, 0.08327936,
       0.0971642 , 0.09286948, 0.12774377, 0.08895406, 0.13054551,
       0.10478529, 0.08887216, 0.08547429, 0.09303291, 0.09454513,
       0.09752315, 0.08304087, 0.08906591, 0.11962345, 0.11373992,
       0.10163332, 0.09278467, 0.0953172 , 0.1525959 , 0.10303997,
       0.11978193, 0.13849206, 0.084827  , 0.08664869, 0.08988144,
       0.08757084, 0.09679152, 0.11669843, 0.10299461, 0.11748875,
       0.10184915, 0.09055641, 0.08837774, 0.10161024, 0.13053891,
       0.08414835, 0.08471613, 0.11782839, 0.09259743, 0.11533545,
       0.11408228, 0.08657718, 0.08476692, 0.1030236 , 0.08409015,
       0.11951887, 0.11326717, 0.12339225, 0.10987139, 0.10999871,
       0.0938148 , 0.09514289, 0.13087694, 0.10052507, 0.14173904,
       0.10193071, 0.09210324, 0.08737729, 0.11495259, 0.0881566 ,
       0.09147712, 0.09237806, 0.09835476, 0.12254982, 0.09548129,
       0.10545825, 0.11050635, 0.09347333, 0.14018506, 0.09240089,
       0.09778063, 0.08391616, 0.09570975, 0.10745241, 0.08743606,
       0.10270075, 0.09688243, 0.09580246, 0.08832315, 0.10083125,
       0.09371023, 0.16452463, 0.08643014, 0.09623778, 0.12399419,
       0.11311297, 0.09039093, 0.09912286, 0.12068476, 0.13456906,
       0.09823828, 0.09566721, 0.08833942, 0.09342375, 0.0869019 ,
       0.08838088, 0.09248811, 0.09208441, 0.09473811, 0.09144509,
       0.0982192 , 0.11488909, 0.0858649 , 0.09150963, 0.10468765,
       0.10930229, 0.08876463, 0.11990168, 0.09240466, 0.09113687,
       0.09956315, 0.08864298, 0.13306952, 0.08877879, 0.0874776 ,
       0.0978285 , 0.12056173, 0.09386581, 0.10731253, 0.09213429,
       0.10270839, 0.09796803, 0.09023517, 0.08398372, 0.0888939 ,
       0.10083584, 0.08451577, 0.09146731, 0.11281168, 0.0991409 ,
       0.10975426, 0.12954175, 0.10538309, 0.09393802, 0.15741372,
       0.09222762, 0.11750684, 0.13224806, 0.10968205, 0.10612008,
       0.12600462, 0.09790635, 0.09570979, 0.11166809, 0.11081285,
       0.14365207, 0.10029655, 0.10712174, 0.10053421, 0.08748103,
       0.0969979 , 0.12345332, 0.10503932, 0.10659044, 0.09151107,
       0.12043379, 0.11035715, 0.09007882, 0.11182743, 0.0975505 ,
       0.09854355, 0.09149321, 0.08911519, 0.08417534, 0.11700962,
       0.12561378, 0.09330294, 0.10795977, 0.09790291, 0.09223856,
       0.09768736, 0.10140994, 0.09965972, 0.14275987, 0.08843079,
       0.11531697, 0.09127698, 0.09736604, 0.10927381, 0.11686237,
       0.11032783, 0.08690484, 0.08376072, 0.11174224, 0.12480176,
       0.10016878, 0.09274796, 0.13610096, 0.0933249 , 0.12001508,
       0.0847249 , 0.08922013, 0.09581545, 0.08563167, 0.13829905,
       0.12713425, 0.08827481, 0.09671743, 0.08813052, 0.09337111,
       0.08531985, 0.10840058, 0.11018818, 0.09279647, 0.09518861,
       0.10544186, 0.0927846 , 0.11251871, 0.09130245, 0.1004318 ,
       0.08728711, 0.09066068, 0.08989047, 0.10966107, 0.09473905,
       0.0867306 , 0.10860751, 0.12277041, 0.09773071, 0.09892672,
       0.09215623, 0.11704927, 0.11874517, 0.10397081, 0.08747556,
       0.08583514, 0.10212772, 0.09421515, 0.11359779, 0.09662234,
       0.08906116, 0.08878027, 0.10772929, 0.10368915, 0.08936424,
       0.08783646, 0.10090914, 0.11742958, 0.11161944, 0.09098732,
       0.21156693, 0.11590777, 0.10511299, 0.09002994, 0.10959657,
       0.11436455, 0.11178571, 0.13786212, 0.12931594, 0.10598598,
       0.08790997, 0.11349002, 0.08280581, 0.09002852, 0.08736919,
       0.12896265, 0.09840155, 0.08727161, 0.10300055, 0.08671617,
       0.08767569, 0.12614514, 0.0913079 , 0.09767228, 0.09391309,
       0.12818372, 0.13991825, 0.09536839, 0.085933  , 0.09638352,
       0.10321482, 0.11285984, 0.09533875, 0.12885259, 0.11040629,
       0.09701887, 0.1025592 , 0.1677033 , 0.10273869, 0.08876909,
       0.1433252 , 0.13383584, 0.09878598, 0.11776806, 0.09703723,
       0.10180783, 0.08405368, 0.10938317, 0.09794988, 0.09004351,
       0.08841714, 0.09609511, 0.08851004, 0.1041593 , 0.09973253,
       0.10875007, 0.1279352 , 0.08871626, 0.09763785, 0.11360449,
       0.10664796, 0.10687815, 0.1118184 , 0.11975029, 0.09072768,
       0.10745605, 0.09227708, 0.10536574, 0.10107633, 0.09361435,
       0.08924112, 0.08717471, 0.08907262, 0.10125748, 0.12516977,
       0.08546128, 0.08381534, 0.1350336 , 0.09153717, 0.08677128,
       0.13682541, 0.08801437, 0.11569844, 0.10831404, 0.08518673,
       0.11031391, 0.08509596, 0.13898194, 0.10543194, 0.10339638,
       0.09638015, 0.10708367, 0.11754335, 0.09112373, 0.11926567,
       0.0958552 , 0.09697562, 0.09871712, 0.10460134, 0.09158193,
       0.09569974, 0.09392133, 0.09704087, 0.10613061, 0.0937871 ,
       0.09483443, 0.08569762, 0.09584055, 0.10826108, 0.10297087,
       0.11937771, 0.09218565, 0.10359897, 0.09713142, 0.09419212,
       0.10923288, 0.09978712, 0.12030114, 0.12025473, 0.08736627,
       0.10538241, 0.08416723, 0.09034813, 0.1297442 , 0.08596081,
       0.11319023, 0.10194871, 0.09475552, 0.09759934, 0.08998152,
       0.10529105, 0.1118202 , 0.09991602, 0.09790252, 0.1015963 ,
       0.0892848 , 0.08442047, 0.09745695, 0.08900458, 0.09887583,
       0.09231079, 0.11169284, 0.10153781, 0.13539347, 0.09074895,
       0.09035604, 0.09409705, 0.10682392, 0.09335318, 0.10861325,
       0.09983222, 0.131879  , 0.09585565, 0.10813199, 0.13531886,
       0.12417004, 0.11989213, 0.10024016, 0.12403862, 0.08378033,
       0.10857769, 0.09232853, 0.08897148, 0.09151933, 0.09799312,
       0.11370937, 0.0895278 , 0.10349254, 0.08998645, 0.10473293,
       0.0964627 , 0.08553037, 0.11051232, 0.09493016, 0.12430353,
       0.08764714, 0.08986453, 0.12872426, 0.09098425, 0.1186805 ,
       0.09090754, 0.08560457, 0.09238221, 0.08836631, 0.10862751,
       0.10828336, 0.11414138, 0.08446526, 0.12545216, 0.1254351 ,
       0.08650605, 0.09443818, 0.12720622, 0.08756417, 0.08903756,
       0.11261023, 0.11316755, 0.11146592, 0.10196488, 0.11950465,
       0.08438375, 0.08945126, 0.11890682, 0.09319498, 0.08344803,
       0.10431617, 0.09343602, 0.11595602, 0.1310384 , 0.09030399,
       0.11378227, 0.0942903 , 0.08787017, 0.08289183, 0.1107187 ,
       0.12101176, 0.11172426, 0.08640669, 0.11673967, 0.1020043 ,
       0.12994325, 0.14660828, 0.08842867, 0.1375303 , 0.08537344,
       0.09535164, 0.12678029, 0.09604844, 0.09373183, 0.09636234,
       0.09372623, 0.114673  , 0.1124729 , 0.13116077, 0.10545956,
       0.11311284, 0.11106213, 0.11369949, 0.09517283, 0.09426501,
       0.09082983, 0.09945679, 0.12589812, 0.08785275, 0.09412348,
       0.08728822, 0.14927045, 0.09744642, 0.11751499, 0.10879278,
       0.114808  , 0.09937588, 0.08798032, 0.08944387, 0.0906584 ,
       0.09338864, 0.09271351, 0.1008701 , 0.09337126, 0.08538131,
       0.09160545, 0.08657668, 0.09749655, 0.09917624, 0.09335124,
       0.0896986 , 0.08574709, 0.09036601, 0.1020584 , 0.08757601,
       0.08912842, 0.09411893, 0.11364676, 0.08670777, 0.09134886,
       0.09502888, 0.08635622, 0.08519451, 0.09321438, 0.09191838,
       0.09194021, 0.08937079, 0.12298162, 0.09821481, 0.11721727,
       0.0902274 , 0.09566115, 0.11327104, 0.09036858, 0.10208142,
       0.08530344, 0.09538915, 0.10280409, 0.08894134, 0.08890846,
       0.13979226, 0.10959528, 0.0977136 , 0.08774186, 0.08921589,
       0.11922934, 0.10453282, 0.09727112, 0.08734731, 0.08917124,
       0.11972538, 0.09890795, 0.11810562, 0.09653051, 0.09699129,
       0.09586909, 0.10329388, 0.09285009, 0.09863164, 0.10655771,
       0.11755494, 0.10450395, 0.08676931, 0.10749526, 0.09304681,
       0.09232439, 0.10475711, 0.08420791, 0.08573707, 0.10306628,
       0.09198095, 0.09078734, 0.11057297, 0.09607113, 0.08971673,
       0.08776656, 0.09376313, 0.12490045, 0.09638049, 0.08822994,
       0.09708788, 0.11461388, 0.10544274, 0.09007131, 0.10669923,
       0.17982462, 0.10031841, 0.09707738, 0.0870625 , 0.09797402,
       0.08342   , 0.09179956, 0.11771616, 0.0979601 , 0.09353587,
       0.09478825, 0.08501147, 0.14917716, 0.10482579, 0.08764862,
       0.08844905, 0.09137177, 0.11050168, 0.10848188, 0.14444806,
       0.12754816, 0.08644674, 0.10449621, 0.08636998, 0.11967036,
       0.08591545, 0.08453497, 0.08536126, 0.11989383, 0.10226037,
       0.1028327 , 0.12585607, 0.09914082, 0.09089237, 0.10570903,
       0.10452352, 0.11725446, 0.08427472, 0.1053081 , 0.11893465,
       0.11026469, 0.10063798, 0.09766181, 0.08872941, 0.10385998,
       0.10714008, 0.0916073 , 0.11171988, 0.09199381, 0.09571084,
       0.09896898, 0.10812642, 0.09453683, 0.10120674, 0.10179541,
       0.11637433, 0.08438425, 0.09101317], dtype=float32), array([[[[-0.02216044],
         [-0.00073532],
         [ 0.00389512],
         ...,
         [-0.0151705 ],
         [ 0.00902005],
         [ 0.0011575 ]],

        [[-0.01654349],
         [ 0.01097478],
         [-0.01901242],
         ...,
         [ 0.01451752],
         [ 0.02018486],
         [ 0.03515881]],

        [[-0.01150921],
         [ 0.03322558],
         [ 0.03136538],
         ...,
         [ 0.01571844],
         [ 0.0036373 ],
         [-0.0297657 ]]],


       [[[-0.01903389],
         [ 0.01570511],
         [-0.01257824],
         ...,
         [-0.02669745],
         [-0.00597296],
         [-0.02558237]],

        [[-0.01808938],
         [ 0.03061168],
         [-0.00651605],
         ...,
         [-0.00605437],
         [ 0.02694712],
         [ 0.01101229]],

        [[-0.02269706],
         [ 0.03763429],
         [ 0.0098336 ],
         ...,
         [-0.00325541],
         [ 0.02638325],
         [ 0.02318574]]],


       [[[-0.00269417],
         [ 0.01508135],
         [-0.01417839],
         ...,
         [ 0.01861374],
         [-0.01608657],
         [ 0.01425322]],

        [[-0.03644377],
         [-0.00478788],
         [ 0.01259191],
         ...,
         [-0.00746794],
         [ 0.03313919],
         [ 0.00314798]],

        [[-0.01487436],
         [ 0.01035564],
         [ 0.02309947],
         ...,
         [ 0.01097747],
         [-0.00852033],
         [ 0.0033339 ]]]], dtype=float32), array([[[[-0.0241331 ,  0.01391963, -0.04657822, ...,  0.02592468,
          -0.02064358, -0.02463061],
         [-0.0661319 , -0.02522981,  0.03837452, ..., -0.03199501,
           0.01687598,  0.0518117 ],
         [-0.02554962, -0.02444598,  0.0201476 , ..., -0.01243334,
          -0.05639822,  0.03450831],
         ...,
         [-0.02651447,  0.00915048, -0.04888899, ..., -0.03584006,
          -0.01905565, -0.0348412 ],
         [-0.03244985,  0.00406178,  0.01140981, ..., -0.04736242,
           0.00162723,  0.02114354],
         [ 0.05895194, -0.05610641,  0.03808339, ..., -0.01863659,
          -0.04093465, -0.01385561]]]], dtype=float32), array([1.0094538 , 0.9937469 , 0.9994366 , 0.9903511 , 0.9968756 ,
       0.99737304, 0.9947424 , 1.0193486 , 1.0038701 , 1.0006696 ,
       0.99464023, 0.9898267 , 1.0042808 , 1.0222414 , 1.0052799 ,
       1.0125102 , 0.995563  , 0.99366474, 1.0419906 , 0.9926616 ,
       0.99607855, 0.980544  , 0.9987164 , 0.9942695 , 1.0032824 ,
       0.99847716, 1.0023726 , 1.0006737 , 1.0006117 , 1.0081893 ,
       0.98272634, 1.011594  , 1.0402898 , 1.0136051 , 0.9979596 ,
       1.0039581 , 0.99913454, 1.0131202 , 0.9934455 , 1.0531353 ,
       0.996971  , 1.0013318 , 1.0013641 , 1.009008  , 0.99058896,
       1.0050359 , 0.994243  , 0.9928876 , 0.997444  , 1.0124185 ,
       0.9957358 , 1.0007168 , 1.0087188 , 1.0075899 , 1.0154395 ,
       1.0099634 , 0.9945838 , 1.0031408 , 0.993765  , 0.9983071 ,
       1.0043025 , 0.99796647, 1.0240644 , 0.99967796, 0.9901041 ,
       1.027671  , 0.9905922 , 0.9961997 , 1.0089438 , 0.9878978 ,
       1.0106783 , 1.0097597 , 0.9763906 , 0.99792343, 0.99753565,
       0.9988529 , 1.0164605 , 1.0018058 , 0.9942396 , 0.98591584,
       1.0135213 , 0.9974514 , 0.98867   , 0.9940532 , 0.99563265,
       1.0004613 , 0.9882298 , 0.9921456 , 1.0127914 , 0.9962407 ,
       0.9961922 , 0.99961674, 0.9956329 , 1.0024953 , 0.99436647,
       0.9992462 , 0.99233776, 1.0047784 , 0.99279904, 0.9956646 ,
       0.99471974, 0.991952  , 0.9938943 , 1.0037707 , 1.0018483 ,
       0.9932561 , 1.0166466 , 0.99340045, 0.99590987, 0.991496  ,
       1.0039945 , 0.99166155, 0.9955923 , 1.0002382 , 1.016236  ,
       0.9988927 , 1.0051935 , 0.9970946 , 0.9966182 , 0.9914048 ,
       0.99116004, 1.0073423 , 0.9930538 , 0.9893084 , 0.9983249 ,
       0.9903738 , 1.0120082 , 0.99819595, 0.99304175, 1.0035809 ,
       0.9919033 , 1.0058832 , 1.0065506 , 0.99705815, 1.0039678 ,
       0.99251014, 0.99734104, 0.9894757 , 1.0183488 , 1.0056628 ,
       1.0042602 , 0.99244875, 0.9941037 , 1.001354  , 0.9997943 ,
       0.99277925, 1.020952  , 1.0076599 , 0.99660784, 0.99359614,
       0.99735343, 1.0146115 , 1.019307  , 1.0022209 , 0.99948204,
       0.9927565 , 0.9872001 , 0.9868533 , 1.0017763 , 0.9977113 ,
       0.99959093, 0.991168  , 0.9958705 , 0.98952556, 0.986143  ,
       1.0115371 , 0.9825688 , 0.99304074, 0.994531  , 1.030752  ,
       1.0051037 , 0.9887199 , 0.99479073, 1.0082532 , 0.99608827,
       0.9938072 , 1.0058732 , 0.98704416, 0.99109006, 0.9997653 ,
       0.99942654, 1.0116401 , 0.99939346, 0.99623156, 0.9916522 ,
       0.99489576, 0.98780054, 0.9958726 , 0.9925675 , 0.99075186,
       0.98081553, 1.0079772 , 1.0030017 , 0.98923373, 0.99518967,
       1.0010656 , 0.9907569 , 0.9946159 , 1.0141206 , 0.9979678 ,
       1.0067666 , 0.99402   , 0.9937474 , 0.99463814, 0.9906775 ,
       1.0089701 , 1.0055774 , 0.99630547, 1.0071148 , 1.0006387 ,
       1.0068023 , 0.9828798 , 0.98720074, 0.9931474 , 0.991877  ,
       0.9983304 , 0.9983979 , 0.99312854, 0.99057996, 1.0047234 ,
       1.0159589 , 0.9991436 , 1.007835  , 0.9892123 , 0.99711245,
       0.9995758 , 1.0080304 , 1.0116838 , 1.0180644 , 1.0148039 ,
       0.99124956, 0.9922558 , 1.0005807 , 1.0167596 , 1.0118787 ,
       0.99105364, 0.9934235 , 1.0034006 , 0.99206907, 0.99457806,
       0.9896324 , 1.0112337 , 1.0069352 , 0.9993232 , 0.9877558 ,
       0.99527854, 1.0016142 , 0.9845722 , 0.99203116, 0.9947084 ,
       0.99105835, 1.0005485 , 1.0025843 , 0.9819064 , 1.0103133 ,
       1.0133271 , 0.99572724, 0.99748373, 1.0006149 , 1.0001843 ,
       1.0352565 , 1.0109767 , 0.99179965, 1.0095911 , 0.993232  ,
       0.9990902 , 0.99480426, 1.0110902 , 0.99436635, 0.9918726 ,
       0.9989686 , 1.0024015 , 1.0094367 , 0.991481  , 1.0168905 ,
       0.99296886, 1.0166787 , 1.0013855 , 0.99366766, 0.9994323 ,
       0.9922125 , 0.9724007 , 0.99600804, 0.98923206, 1.0117661 ,
       1.0109296 , 0.9735961 , 0.99950504, 1.0063723 , 0.99882483,
       0.9957558 , 0.99876535, 1.0009127 , 1.0079978 , 0.99358135,
       1.0108894 , 1.0031912 , 0.98886794, 0.99225813, 0.9962248 ,
       0.9950329 , 1.0003197 , 1.0044516 , 0.9918958 , 1.0170455 ,
       0.9974549 , 0.9949566 , 0.9935866 , 0.9913064 , 0.9930025 ,
       0.994257  , 0.9992794 , 0.99377805, 0.99906856, 0.99771637,
       0.9899912 , 0.99017745, 0.9981821 , 1.00107   , 0.99969923,
       0.991821  , 0.98961824, 1.0047768 , 0.99594337, 0.9855482 ,
       0.99507314, 1.0120265 , 0.9950593 , 0.9963922 , 0.9893984 ,
       1.0054616 , 1.0118659 , 0.9958879 , 0.99717396, 0.99119425,
       0.9981748 , 1.0291467 , 0.99772024, 0.9961786 , 0.9953324 ,
       0.9973645 , 0.99801785, 0.99792695, 0.9934185 , 1.0102888 ,
       1.0165882 , 1.0043308 , 1.0160583 , 0.99193627, 0.99488366,
       0.9938925 , 0.9987542 , 0.99650514, 0.9897587 , 0.98260397,
       0.99623185, 1.0011284 , 0.9956103 , 0.9775097 , 0.995634  ,
       1.0075004 , 0.9905852 , 0.98586273, 0.99049354, 1.0057566 ,
       1.0059043 , 0.99377346, 0.9920411 , 0.988527  , 0.99989605,
       1.0034356 , 0.99171793, 0.9954724 , 0.9902779 , 1.0035903 ,
       1.0346712 , 0.9999577 , 0.9965523 , 0.9767283 , 1.0224264 ,
       0.9863178 , 1.01712   , 1.0060782 , 0.988232  , 0.9884321 ,
       0.9970911 , 0.9961826 , 0.99194926, 0.9840048 , 0.99813575,
       1.0106702 , 0.99803287, 0.9891259 , 1.0107231 , 1.0010774 ,
       0.99881434, 0.9970045 , 1.0130163 , 0.9970881 , 0.9902384 ,
       0.99629736, 1.0147381 , 1.0125786 , 0.9867438 , 0.9922446 ,
       1.0124636 , 1.0358806 , 0.98890644, 0.9927703 , 0.996006  ,
       1.0024757 , 0.98791635, 0.99433464, 1.0191783 , 1.0044626 ,
       0.99615276, 1.0084636 , 1.0074152 , 1.0052844 , 1.0402584 ,
       0.9995458 , 0.99084276, 0.9938424 , 1.0011715 , 1.0004752 ,
       0.9886427 , 0.99510306, 0.9932649 , 1.0115194 , 0.9997183 ,
       1.0263664 , 1.0077859 , 0.982749  , 1.0030942 , 0.9907005 ,
       1.006395  , 0.9881582 , 0.9978389 , 1.0010881 , 0.9915614 ,
       0.9942357 , 1.0100414 , 1.0043925 , 1.0084532 , 1.0104077 ,
       1.004718  , 1.007309  , 1.0044193 , 0.9899316 , 0.9889644 ,
       1.0052352 , 0.9905526 , 1.006167  , 1.0073755 , 0.99416506,
       1.0133    , 1.0085753 , 1.0028838 , 1.0156784 , 0.9971237 ,
       1.0029322 , 0.9900928 , 0.99714416, 0.9967674 , 0.9912468 ,
       0.99579245, 0.9953254 , 0.9934763 , 0.99646515, 0.9928016 ,
       0.9858235 , 0.99011964, 0.9901517 , 1.0240288 , 0.99898326,
       0.9920878 , 0.99721587, 0.9885963 , 0.9905528 , 0.9886329 ,
       0.9919202 , 0.9962768 , 0.9840403 , 0.9961106 , 0.98056996,
       1.0083857 , 0.996296  , 0.99514174, 0.99845713, 1.006049  ,
       1.0089867 , 1.0028163 , 0.9967648 , 1.0023733 , 1.0024538 ,
       1.0030355 , 1.0061041 , 0.99610436, 1.0218407 , 0.993692  ,
       1.0109367 , 0.99476856, 1.0023834 , 0.9864109 , 0.9894508 ,
       1.000387  , 0.9945546 , 1.0090097 , 0.99913263, 1.003118  ,
       0.9776799 , 0.99593055, 1.002385  , 1.0152413 , 0.9964403 ,
       0.9921112 , 1.0066688 , 0.98958254, 1.0303797 , 1.0083096 ,
       0.99210674, 1.0009018 , 1.0058291 , 0.99384713, 1.0083377 ,
       1.0000169 , 1.0204626 , 0.9901127 , 1.0318109 , 1.0020263 ,
       1.0014219 , 0.98725253, 1.0053262 , 1.0032344 , 0.98345405,
       0.998607  , 1.0163492 , 0.9994099 , 0.9948588 , 0.99229205,
       0.99246854, 0.99788445, 0.9899581 , 0.98958975, 1.0025234 ,
       0.9976993 , 0.9970017 , 0.9950393 , 0.9983672 , 0.98826885,
       0.99646497, 0.99809724, 0.9721913 , 1.0025121 , 1.0023737 ,
       0.9987547 , 1.0197772 , 1.011372  , 1.0009999 , 0.9952254 ,
       1.0012572 , 1.008678  , 1.00096   , 1.0213776 , 0.99089026,
       0.99029773, 0.9957246 , 0.9968631 , 0.99268097, 0.9958742 ,
       0.995358  , 0.98941725, 0.9969324 , 1.0152953 , 1.019831  ,
       0.9996086 , 0.99324745, 0.9889083 , 1.0036142 , 0.99243647,
       0.99732995, 1.0033445 , 0.99630356, 1.0293834 , 0.99440163,
       1.0027587 , 0.99098563, 0.99279547, 0.99711794, 0.99908304,
       0.9890264 , 1.0019974 , 0.9947195 , 0.989373  , 0.9964736 ,
       0.9879789 , 0.9987217 , 1.0099984 , 0.99724996, 0.99718857,
       1.0048754 , 1.0011661 , 0.9933729 , 1.0221487 , 0.99639726,
       0.99955344, 1.0011115 , 0.9939624 , 1.0061963 , 0.9943521 ,
       1.0032802 , 1.0210973 , 0.9932816 , 0.99487716, 0.99677557,
       1.0021998 , 0.99149984, 0.99779624, 0.98974776, 0.9944114 ,
       0.9931716 , 1.0073556 , 0.99910855, 0.99330586, 0.99704635,
       1.0016541 , 1.001209  , 0.99581164, 0.9997719 , 1.0035188 ,
       1.0080898 , 1.0013978 , 0.9980253 , 0.9937486 , 0.99306816,
       1.0053122 , 0.9980193 , 0.99287283, 0.9982874 , 1.0068944 ,
       0.99582833, 1.0026104 , 0.99850273, 0.99225223, 1.0021316 ,
       1.021563  , 1.0043719 , 0.99561423, 0.9985727 , 0.98830056,
       0.9872775 , 0.99069095, 0.99790215, 0.9922878 , 1.0101846 ,
       0.9903106 , 1.0039608 , 1.007343  , 0.9950857 , 0.9963039 ,
       0.9926873 , 1.0238583 , 1.0024366 , 0.9898483 , 0.98863775,
       0.99517184, 0.99644077, 0.97952026, 0.9920763 , 0.9977902 ,
       0.9937811 , 1.0341246 , 0.99764013, 0.9851032 , 1.0056577 ,
       0.9950401 , 0.9988366 , 0.9880426 , 0.99639297, 1.0020248 ,
       1.0182635 , 0.999624  , 1.0075442 , 0.9963413 , 1.002915  ,
       0.9894637 , 0.98960155, 0.99766725, 0.9978949 , 0.9991842 ,
       1.0067983 , 0.9905236 , 0.9826367 , 1.0018138 , 0.99483377,
       1.0206625 , 0.9930673 , 1.0133783 , 0.99478954, 0.9885013 ,
       1.0151231 , 0.99605507, 1.008498  , 1.0014372 , 1.000208  ,
       1.0147555 , 1.0006545 , 0.9860109 , 0.99193394, 0.9884943 ,
       0.9962622 , 1.0014611 , 1.0150015 , 0.99842256, 1.0048597 ,
       1.0013485 , 1.0000874 , 0.99376434, 1.0200148 , 0.99379855,
       1.0017195 , 0.99146914, 1.008502  , 0.99099547, 1.003314  ,
       1.0032926 , 1.010612  , 0.9955674 ], dtype=float32), array([ 3.06643099e-02, -2.72679492e-04,  5.79231244e-04, -8.09587725e-03,
       -1.19290957e-02, -5.38696331e-05, -2.48283660e-03,  1.54035473e-02,
        1.93650536e-02,  4.36270563e-03, -6.60860166e-03, -6.06672280e-03,
        4.64509521e-03,  2.15734672e-02, -1.25667555e-02, -1.18580349e-02,
       -3.92451370e-03, -1.65553372e-02, -9.63276438e-03, -1.00800293e-02,
       -4.33972385e-03, -1.11662196e-02,  2.01764796e-03, -7.36684725e-03,
        4.88060713e-03, -3.47273634e-03, -2.12922469e-02,  6.42995024e-03,
       -1.05886059e-02,  2.11143438e-02, -3.17520648e-02,  1.23320911e-02,
        4.57226746e-02, -7.59023428e-03,  2.15452001e-03, -3.13147008e-02,
        3.62708629e-03,  2.71358695e-02, -1.61569938e-02,  3.21930870e-02,
        9.25127591e-04, -1.87757239e-03,  2.11008824e-03, -6.86778175e-03,
       -3.33525091e-02,  8.01035669e-03, -7.44963065e-03,  1.88425183e-03,
       -2.25814413e-02, -1.32972114e-02, -5.59772411e-03, -1.16357617e-02,
        1.10762594e-02,  5.34485001e-03, -2.46538278e-02,  2.07936168e-02,
       -3.48826521e-03, -1.76058002e-02, -1.27562890e-02,  3.22480872e-03,
       -1.27280746e-02, -1.15812188e-02,  7.79780746e-03, -1.07564945e-02,
       -1.39324581e-02, -1.14960484e-02,  1.91060943e-03,  1.06117306e-02,
        1.65990386e-02, -3.33015691e-03,  2.91734580e-02, -2.45573558e-02,
       -1.19361207e-02, -2.24448019e-03,  1.66240986e-03,  3.52082625e-02,
        1.43233417e-02, -9.94038675e-03, -1.45203592e-02,  1.25460159e-02,
        2.07652152e-02, -1.61359962e-02,  1.92785141e-04, -6.77184900e-03,
        1.36680366e-03,  2.42702868e-02, -8.79550353e-03, -3.96219362e-03,
       -9.82708298e-04,  7.31902488e-04,  1.70833599e-02, -2.26036459e-02,
       -3.26382220e-02, -1.93186058e-03, -6.74125226e-03,  1.40490038e-02,
       -3.37737426e-02, -2.19651293e-02, -1.28446352e-02, -4.20617918e-03,
        1.80584961e-03,  2.31312811e-02, -1.78537406e-02, -4.21928195e-03,
        3.17452359e-04,  1.03815692e-02, -5.14214346e-03, -2.04465468e-03,
        1.07357986e-02,  5.25357027e-04,  1.41208358e-02, -3.50686908e-03,
       -2.28093122e-03, -1.72125883e-02, -4.08767583e-03,  4.31657908e-03,
        3.23259868e-02,  1.84398377e-04, -5.63458912e-03, -8.32647365e-03,
       -1.25619201e-02, -1.13149146e-02, -3.45299114e-03, -2.45054881e-03,
        4.39509004e-03, -8.83049052e-03,  8.46613944e-03, -6.50482113e-03,
       -7.41128298e-03, -2.03514304e-02,  5.06413961e-03,  5.06648188e-03,
       -1.21040512e-02,  2.36475863e-03,  1.06802052e-02, -1.86198228e-03,
        3.93777713e-03, -1.31392013e-02, -1.75420195e-02, -8.10588535e-05,
        4.47865896e-04,  2.22469767e-04, -4.18410054e-04, -3.91477421e-02,
        1.04207033e-02, -1.48785510e-03,  1.04949521e-02,  3.76978256e-02,
       -5.98821882e-03,  1.49148138e-04, -4.25304240e-03,  4.70135780e-03,
       -2.95565911e-02,  4.12959009e-02,  1.04792435e-02, -2.42369343e-03,
       -3.59098334e-03,  8.82906374e-03,  3.29998438e-03,  9.66899854e-04,
       -1.16040641e-02, -1.70881972e-02, -4.58711199e-03,  1.24817314e-02,
       -9.70026571e-03,  2.44812369e-02, -1.88474115e-02, -1.10892253e-03,
       -2.44240602e-03, -4.61225957e-02,  1.46708172e-02, -8.68527312e-03,
        3.42657720e-03, -8.23022783e-05, -4.38935962e-03, -1.88805293e-02,
       -1.24991396e-02, -1.81485452e-02, -5.79538615e-03,  2.27334611e-02,
       -2.61959899e-03,  1.62103195e-02,  9.93904541e-04, -5.43566374e-03,
       -1.42190475e-02,  2.24692002e-03, -1.62959453e-02, -3.47478539e-02,
        1.61150377e-03, -7.33609451e-03, -7.02701649e-03, -3.02820699e-03,
       -1.68377534e-03, -3.97448614e-02, -4.17965325e-03,  2.16799485e-03,
       -8.79824534e-03,  3.69219575e-04, -8.47118441e-03, -1.65646933e-02,
        4.71066404e-03, -1.74013283e-02, -1.06567354e-03, -3.48775135e-03,
       -1.92487054e-02, -2.43417528e-02,  2.18112301e-02, -1.33196106e-02,
        5.46751730e-03, -6.02842448e-03, -2.56359968e-02, -2.56960802e-02,
       -3.45100043e-03,  1.60826258e-02, -3.06596770e-03, -3.63197387e-03,
        4.22947778e-04, -4.74306569e-03, -9.36643593e-03,  2.77742185e-02,
        2.09354144e-02,  3.73305916e-03, -9.90199158e-04,  4.02552402e-03,
       -3.94798350e-04,  1.10811237e-02,  1.61166117e-02, -2.32057534e-02,
       -1.34518379e-02,  2.28829533e-02, -2.08176449e-02, -8.00237153e-03,
       -1.78086534e-02,  1.04417056e-02,  2.23052949e-02, -5.94066456e-03,
       -5.92726516e-03,  3.59739945e-03, -1.90827306e-02, -8.75506829e-03,
       -1.71216931e-02,  8.63381382e-03,  1.48545774e-02,  9.01465712e-04,
       -9.21416562e-03,  1.11616228e-03, -2.35122181e-02, -1.69435311e-02,
       -2.27070004e-02, -2.13085152e-02, -5.84979914e-03,  1.60888657e-02,
       -4.70256712e-03, -3.45049687e-02, -1.15239492e-03, -5.71248541e-03,
       -1.00866286e-02,  7.39641860e-03, -9.14799108e-04, -1.13472492e-02,
        1.18285343e-02,  1.03207286e-02, -5.40031586e-03, -1.14144839e-03,
       -1.01651652e-02, -2.31177788e-02, -5.01997955e-03,  2.55291220e-02,
       -6.38959417e-03, -2.64207274e-02, -2.82536214e-03,  1.65233016e-02,
       -1.21683376e-02, -1.15852887e-02, -5.20704873e-02,  1.02806743e-02,
       -2.54049804e-03,  6.43030973e-03, -1.75223518e-02,  1.01248985e-02,
       -1.19430693e-02, -1.87822934e-02, -8.19892529e-03, -2.05828398e-02,
       -5.92260039e-04, -3.80876521e-03, -1.54282954e-02, -2.16647377e-03,
       -9.48611367e-03,  8.35700240e-03, -9.08239838e-03, -2.22564228e-02,
       -5.88829629e-03,  1.47668608e-02,  7.32930191e-03,  2.29903422e-02,
        8.02671816e-03, -9.98488627e-03, -1.23104174e-02,  5.96960168e-03,
        7.31508480e-04,  3.48228328e-02, -3.68758396e-04, -5.75984828e-03,
        1.20047573e-02, -1.64259207e-02,  2.19948808e-04, -9.25056450e-03,
       -1.08609516e-02, -2.93602142e-03, -2.71667894e-02, -1.94806012e-03,
       -5.34487423e-03, -1.13042453e-02, -5.49436407e-03,  2.50574062e-03,
       -7.58153759e-03, -1.53946197e-02, -8.39206576e-03,  1.32771377e-02,
       -3.43215186e-04,  1.05830736e-03, -1.47953304e-02, -1.30110290e-02,
       -1.47526218e-02, -9.35875159e-03,  2.48374953e-03, -8.59778374e-03,
       -1.44306652e-03, -1.05862329e-02,  3.90197593e-03, -3.39232339e-03,
       -2.10766140e-02, -3.49210412e-03, -6.02706103e-03,  3.48410686e-03,
       -3.46833691e-02, -1.17142044e-03, -9.07874387e-03,  7.12872250e-03,
       -1.21051203e-02,  9.64329205e-03, -4.36267210e-03, -5.37015637e-03,
        9.37851146e-03,  2.00555567e-03,  2.01601721e-02,  3.64801614e-03,
       -1.60367340e-02, -5.07636741e-03,  9.17824218e-04, -1.61681417e-02,
       -1.23529723e-02, -1.04722315e-02, -1.87013987e-02,  6.66083815e-03,
        2.48055495e-02, -6.80606160e-03, -1.45819904e-02, -8.59261770e-03,
       -5.59104560e-03, -1.30606480e-02, -1.07428944e-02,  1.13233384e-02,
        1.04146162e-02, -1.15059083e-02, -8.27492215e-03, -1.04219571e-03,
       -3.79740726e-03, -2.27042418e-02,  2.11312957e-02, -1.63507299e-03,
        5.74807113e-04, -1.04506146e-02, -2.10614316e-03,  4.00919607e-03,
       -7.87233468e-03, -3.09105474e-03, -3.55454944e-02,  1.54502224e-03,
       -1.44163277e-02, -1.02237705e-02, -3.08455608e-04, -8.97484832e-03,
       -1.24621084e-02,  1.31568452e-02, -1.77747365e-02,  1.71505357e-03,
       -1.23359542e-02, -1.28393322e-02, -5.39832254e-05,  6.64787949e-04,
       -1.11695202e-02,  1.92992743e-02, -3.72282742e-03, -3.02148121e-03,
        1.72886662e-02, -3.93086672e-02, -1.30901784e-02, -6.69807708e-03,
       -2.65928917e-03, -1.79961119e-02, -2.29304750e-02, -8.52152798e-03,
       -1.67588666e-02,  9.42033529e-03,  7.51919672e-03, -1.44858975e-02,
        5.90231782e-03, -7.99530558e-03,  8.37222952e-03, -2.45081838e-02,
        1.20144142e-02, -1.63856260e-02,  1.10861156e-02, -6.27999846e-03,
        1.68716554e-02, -1.28429746e-02, -4.42220494e-02,  6.01402745e-02,
       -5.19971736e-03, -1.05478931e-02, -4.76512779e-03, -2.48279627e-02,
        3.75252403e-03, -2.46478245e-02, -5.67627279e-03, -3.17366025e-03,
       -1.17537687e-02,  1.17153265e-02,  1.24937044e-02,  2.13571335e-03,
       -2.44704336e-02,  3.20845493e-03, -2.74884999e-02,  1.87405385e-02,
       -9.02255531e-03,  5.09507721e-03, -1.18643455e-02, -5.13865938e-03,
       -1.16353082e-02,  5.82345761e-03, -9.03871283e-03,  2.93913297e-03,
        1.19082639e-02,  1.68036893e-02, -1.67832393e-02,  8.19284702e-04,
       -1.15282461e-02, -9.27184802e-03,  9.77770053e-03,  1.69602595e-02,
        3.38924192e-02,  1.80180334e-02, -3.73675022e-03, -1.63348448e-02,
        2.07446162e-02,  2.14394629e-02, -1.25449961e-02, -1.23980024e-03,
       -5.64250280e-04, -7.50776846e-03, -2.01567705e-03, -6.44192379e-03,
       -2.19222228e-03, -8.18999484e-03,  4.12950525e-03, -4.73040482e-03,
       -5.43433148e-03, -7.75776245e-03, -1.54423779e-02, -7.57117243e-03,
       -4.59544733e-03, -2.73947641e-02,  7.17228418e-03, -8.81921034e-03,
       -7.53644761e-03, -1.03860106e-02, -1.11847371e-02, -1.00121759e-02,
       -3.03012668e-04,  1.01465154e-02, -3.38700302e-02, -5.28264791e-03,
       -1.88170690e-02, -4.16029617e-02, -2.42651207e-03, -8.84042773e-03,
       -1.32755497e-02, -2.31806673e-02, -2.39638519e-02,  1.57896336e-02,
        1.00030238e-02,  8.93467478e-03,  6.82331761e-03,  7.75132654e-03,
        6.15447294e-03,  6.65248779e-04, -1.24596488e-02, -2.96861376e-03,
        1.17875123e-02, -8.02521128e-03,  1.05089406e-02, -1.15906505e-03,
        4.35139192e-03,  2.29924452e-03, -3.67919425e-03,  1.27548436e-02,
       -2.34393706e-03,  2.38136854e-02, -1.10049015e-02, -6.95557892e-03,
       -5.65850269e-03, -2.65815910e-02,  1.29896011e-02,  7.66195869e-03,
        1.58721227e-02, -1.29022012e-02, -4.19775397e-02,  1.00972122e-02,
       -6.97960553e-04,  1.45509401e-02,  1.68686640e-02, -3.74267949e-03,
       -2.90050823e-02,  6.14170916e-03, -2.00853422e-02, -1.39964344e-02,
        2.74107177e-02, -2.94039515e-03, -1.72486715e-02, -1.31697934e-02,
       -1.13574099e-02,  1.56558622e-02, -1.56167066e-02, -6.19600806e-03,
        1.62453018e-02, -3.37967910e-02,  2.32492927e-02,  1.22366687e-02,
        3.87944188e-03, -5.43362135e-03, -9.34676547e-03, -1.38966059e-02,
       -2.86136698e-02,  5.49970544e-04,  1.78626238e-03, -8.58751405e-03,
       -1.23160821e-03, -1.24898814e-02, -1.13990046e-02, -2.03684671e-03,
       -2.16786843e-02, -1.99935399e-02,  1.82856228e-02, -3.19220871e-03,
        1.82069442e-03,  1.10437516e-02,  4.83363261e-03,  5.82636660e-03,
        5.60991175e-04,  9.45635047e-03, -1.05842734e-02, -5.17204590e-03,
       -1.30459964e-02, -1.16339028e-02,  4.99106292e-03, -6.51548710e-03,
        1.15079796e-02, -6.41355198e-03, -1.55356200e-02, -1.12405680e-02,
       -7.06166122e-03, -7.91864190e-03,  6.71442016e-04, -7.58343237e-03,
       -1.02661084e-02, -1.48998471e-02,  6.57070475e-03,  1.60764698e-02,
        8.66715854e-04, -5.61108813e-03,  1.00739310e-02,  1.46844694e-02,
       -5.52292820e-03,  1.88506171e-02, -1.14310058e-02, -9.90878232e-03,
       -1.02342383e-05, -7.35286507e-04, -1.20236175e-02,  2.06810776e-02,
       -4.75743553e-03, -3.18939500e-02, -1.75120644e-02, -8.63130111e-03,
       -3.40378284e-03, -4.97898739e-03,  2.87462841e-03, -2.86019151e-03,
       -3.94214317e-03, -1.01529639e-02, -9.69937723e-03, -3.10296379e-02,
       -7.47856731e-03,  4.93095536e-03,  1.04320031e-02,  8.34458321e-03,
        1.05750759e-03, -3.76738631e-03, -1.01127978e-02, -7.92114437e-03,
       -1.24112563e-02,  5.73133444e-03, -1.81873366e-02,  3.44977132e-03,
       -7.58638792e-03, -4.79653710e-03, -1.23140961e-02, -6.10496092e-04,
       -1.04505382e-02,  3.26212943e-02,  1.62579212e-03, -1.67419165e-02,
        1.21148687e-03,  1.17497297e-03, -3.49595887e-03, -3.86194792e-03,
       -2.79450184e-03, -1.64134279e-02, -2.64795832e-02,  3.04758712e-03,
       -3.05340416e-03, -1.50748892e-02, -1.45257404e-02,  2.06210781e-02,
       -1.13849277e-02, -3.31019014e-02, -7.79924355e-03, -9.59531963e-03,
       -3.25746206e-03, -3.23902443e-02,  1.90077315e-03, -1.52333090e-02,
       -2.75723599e-02,  5.18715568e-02,  1.93829611e-02,  6.17448566e-03,
       -1.46678870e-03,  5.30753168e-04,  1.54184597e-02, -4.32997523e-03,
       -8.81012157e-03, -1.67618599e-02, -3.97841334e-02, -1.31149506e-02,
       -2.91704703e-02, -6.23899559e-03, -4.60655382e-03,  3.89810331e-04,
       -2.44926708e-03, -2.85873879e-02,  1.34610636e-02, -1.25482101e-02,
       -2.89881439e-03, -1.57783870e-02, -7.17517640e-03, -1.25926677e-02,
       -9.59079247e-03,  1.19896727e-02, -1.46115944e-02,  1.89472288e-02,
       -7.96563644e-03, -7.33356876e-03, -3.12948530e-03, -2.88471952e-03,
       -1.15513941e-02, -1.25444606e-02, -2.08492856e-02, -2.70556584e-02,
        1.05141699e-02,  4.28227242e-03,  1.60165932e-02, -4.02054191e-03,
        1.97759294e-03, -8.30210093e-03, -3.21981609e-02, -3.81498523e-02,
        6.36181515e-03, -2.86348630e-02, -4.31698887e-03, -5.92069700e-03,
        9.11218021e-03,  1.64391694e-03, -2.36485638e-02,  8.81161541e-03,
       -5.20204194e-03,  2.53300858e-03, -7.81803392e-03,  4.74557048e-03,
        3.14461216e-02,  3.54745379e-03, -2.30132486e-03, -7.09040882e-03,
       -9.56823118e-03, -6.49872515e-03,  1.29841678e-02, -1.40447933e-02,
       -1.76446885e-02, -1.33877071e-02, -1.74785070e-02,  5.29090548e-03,
        1.29529452e-02, -1.13412533e-02,  1.17044616e-02,  1.71717834e-02,
       -3.24281910e-03, -2.59140003e-02, -6.02524076e-03, -7.87384529e-03,
       -2.53977645e-02, -2.31206566e-02, -2.13066358e-02, -6.73710043e-03,
        5.30948071e-03,  5.36698243e-03, -5.00497129e-03, -3.07444371e-02],
      dtype=float32), array([-1.21151149e-01,  1.34210393e-01,  5.61758876e-02, -5.81440218e-02,
       -1.74032077e-01, -4.53183725e-02, -7.25638568e-02, -2.52624840e-01,
        4.01505902e-02,  9.51871648e-03,  1.57118902e-01,  5.44367917e-02,
       -9.49158743e-02,  1.52459946e-02, -6.07993752e-02,  2.13926494e-01,
        9.81134698e-02, -2.25097865e-01,  1.09255321e-01, -7.90192466e-03,
        4.94829677e-02,  4.16250303e-02, -2.12340683e-01, -9.36893597e-02,
       -2.41749123e-01, -9.94216353e-02, -1.02891903e-02, -4.49975431e-01,
        1.36915788e-01, -1.39779910e-01,  2.23642677e-01,  1.25321627e-01,
       -3.92713666e-01,  1.11803852e-01,  1.89852029e-01,  2.74013072e-01,
       -1.28100723e-01, -2.22017631e-01,  1.50004894e-01, -8.43463913e-02,
       -2.05503389e-01,  1.03136078e-01, -1.40395328e-01,  1.53924972e-01,
        2.50833690e-01, -9.42554101e-02,  7.07302466e-02,  8.76770616e-02,
       -1.21025696e-01,  6.56729937e-02, -1.15141176e-01, -8.43709409e-02,
       -7.57078007e-02,  1.27441844e-03,  9.55133960e-02, -1.15471303e-01,
        2.39300616e-02,  1.62878975e-01,  3.47588770e-02, -1.14180416e-01,
        4.78131734e-02,  9.91304442e-02,  1.77391395e-01,  9.41425338e-02,
        3.38470668e-01,  2.09948927e-01, -1.50334060e-01, -1.10787399e-01,
       -1.48225799e-01, -2.60886252e-01, -1.48754135e-01,  1.02080710e-01,
       -3.47526580e-01, -1.04376793e-01,  7.40540028e-02, -1.61270082e-01,
        4.22165245e-02,  2.38915309e-01,  2.05995500e-01, -2.40941167e-01,
       -1.02618761e-01,  4.90316916e-06, -1.84771121e-01, -1.29261762e-01,
        6.01586252e-02, -3.86132970e-02, -4.13339399e-02, -1.20667703e-01,
       -1.70586839e-01, -1.96625561e-01, -8.95346552e-02, -3.15773189e-01,
       -1.44489065e-01,  7.79997930e-02, -5.16801067e-02, -1.60671741e-01,
       -8.66774991e-02,  2.00332090e-01,  2.20050827e-01, -1.16298065e-01,
       -1.13885880e-01, -9.17532891e-02,  1.71080917e-01,  2.79194981e-01,
        1.44207999e-01, -1.32206351e-01,  1.88625336e-01,  6.15873560e-02,
       -3.22896764e-02, -4.69412059e-02,  2.23736912e-01, -7.23318681e-02,
       -1.48924887e-01,  1.79012224e-01,  9.43460315e-02, -1.71988532e-01,
       -1.78174749e-01,  1.28956422e-01, -5.46266846e-02, -5.08115776e-02,
        1.37305349e-01, -1.13908961e-01, -2.15940207e-01, -1.64023206e-01,
       -1.78534508e-01, -1.45103186e-01, -4.86181006e-02,  2.95218974e-02,
        1.92130610e-01,  1.91253975e-01, -1.27717376e-01, -4.87396903e-02,
        3.21356297e-01, -2.31272995e-01,  9.97104496e-03, -4.80134934e-02,
        1.01991571e-01, -2.15952158e-01,  1.61260813e-01,  1.92166328e-01,
       -1.07703373e-01, -1.22050405e-01, -7.46514350e-02,  3.01501781e-01,
       -2.62629330e-01, -2.63576489e-02, -1.58349723e-01, -2.17021257e-01,
       -5.66782840e-02, -1.42924592e-01, -2.36717105e-01,  1.11565113e-01,
        4.32237476e-01, -1.31151721e-01, -1.62547365e-01, -1.99289322e-01,
        1.70164425e-02,  2.45795250e-02, -6.70876056e-02,  9.63462889e-02,
        1.84017777e-01,  6.32273853e-02, -1.54190257e-01, -2.45798171e-01,
       -1.94998831e-02, -2.41827130e-01, -1.06655352e-01,  1.14462957e-01,
       -8.62074792e-02,  2.58770794e-01, -1.32929370e-01,  2.01760069e-01,
       -1.59832798e-02,  5.18909059e-02, -3.49042043e-02,  1.99615806e-01,
        1.31686747e-01, -2.25143835e-01,  3.17909509e-01, -1.19087398e-01,
       -8.68133828e-02, -9.57513526e-02,  7.73888603e-02, -5.88046722e-02,
       -2.31215417e-01,  6.86278567e-02,  1.26654193e-01,  1.93151951e-01,
       -1.98531494e-01, -6.33446798e-02, -1.94382355e-01, -2.22226307e-01,
        1.65835842e-02,  2.30954498e-01,  9.67429355e-02, -2.25771993e-01,
        1.79246455e-01, -2.05491558e-01, -1.29725202e-03,  2.56122231e-01,
       -9.81196389e-02, -1.83568820e-01, -1.49873435e-01,  5.44905774e-02,
        2.48157218e-01, -5.86220324e-02, -9.13842544e-02,  6.87327087e-02,
        2.95826662e-02,  6.64986745e-02,  2.95284271e-01, -2.00488597e-01,
       -2.22812489e-01,  3.95978302e-01,  1.06655173e-02,  1.62211731e-01,
       -1.89095408e-01, -1.19673476e-01, -6.60266355e-02, -2.25948039e-02,
       -6.11639433e-02, -1.03073463e-01,  4.78595756e-02, -1.80609658e-01,
        6.26772270e-02, -9.71815512e-02, -2.81015486e-01,  1.68119758e-01,
        2.67267436e-01, -1.52076825e-01,  1.69506371e-01, -5.71849272e-02,
       -1.63706660e-01,  6.58053299e-03, -5.83429262e-02, -1.16946399e-01,
        1.13710538e-01, -1.22786261e-01,  1.84175476e-01, -1.18570343e-01,
        2.17195585e-01, -3.29620409e-04, -1.48220792e-01, -1.15785981e-02,
       -7.44610503e-02, -2.05263793e-01,  1.60731766e-02,  3.27445008e-02,
        2.51261562e-01,  2.50349820e-01, -5.47123142e-02, -2.21814420e-02,
       -2.81726290e-02,  2.65744418e-01, -2.69081648e-02,  1.78382233e-01,
       -8.63526165e-02, -2.38679890e-02, -6.71635643e-02,  1.80369154e-01,
       -2.73930490e-01,  3.88486832e-02, -5.71431927e-02,  2.47897997e-01,
        1.24954209e-01,  2.59154648e-01, -9.19862986e-02, -1.08667322e-01,
       -1.42746687e-01,  2.62944281e-01, -7.84679204e-02,  2.82617379e-02,
        1.48608178e-01,  1.63126335e-01,  3.98987889e-01, -2.30555162e-01,
       -1.01884961e-01, -6.34501874e-02,  6.60356134e-02, -1.59143075e-01,
        2.08131850e-01,  8.53326097e-02,  2.55425900e-01,  9.41249281e-02,
        1.18828282e-01, -2.08331212e-01,  6.66021630e-02, -2.52419740e-01,
       -5.14416173e-02, -2.58626044e-01,  8.89199302e-02,  2.23778114e-01,
        1.01108193e-01, -1.52488634e-01, -8.24729055e-02, -2.09836349e-01,
       -6.38446957e-02,  1.33047611e-01, -1.04677886e-01, -1.35705143e-01,
       -1.51066542e-01, -6.88237324e-02,  2.00386271e-02, -1.74726453e-02,
        1.89390928e-01,  4.27747406e-02, -1.25001669e-01,  7.64540508e-02,
        1.99841082e-01,  4.59368601e-02,  2.17002362e-01,  1.36888683e-01,
        2.00648710e-01,  2.13991225e-01, -1.46681994e-01, -8.36489797e-02,
       -8.53732286e-04,  5.57250716e-02,  2.31690586e-01, -6.71957955e-02,
        1.35640293e-01, -7.26490468e-02,  1.69499323e-01,  1.32349595e-01,
       -8.21546391e-02,  9.38894153e-02,  8.47128034e-02,  1.94734409e-01,
       -3.39147374e-02, -1.06839165e-01,  2.95576125e-01,  1.68996036e-01,
        2.04724044e-01, -1.60864592e-01,  1.07850097e-02,  2.35869866e-02,
        1.51792571e-01, -1.67913839e-01,  1.46126360e-01, -1.14740096e-01,
        1.29315495e-01,  1.46305010e-01,  6.65878803e-02, -1.73296124e-01,
        2.34012946e-01, -9.88375619e-02, -1.55807391e-01,  1.60093009e-01,
        7.18280300e-02,  1.62692755e-01,  1.67358235e-01,  1.74372703e-01,
       -2.30006397e-01,  7.29088187e-02, -1.41455278e-01, -4.24457267e-02,
       -1.38353959e-01,  2.24090621e-01,  1.42247006e-01, -1.30567729e-01,
        8.34462419e-03,  1.66163668e-01, -2.49371547e-02, -2.06827894e-01,
       -1.67079166e-01, -4.34683450e-02,  1.13685817e-01, -9.14309248e-02,
       -1.69471845e-01,  2.90335089e-01,  8.42362419e-02,  1.87663510e-01,
       -1.61870316e-01,  1.18037872e-01,  2.94410348e-01,  1.17029510e-01,
        1.35865688e-01, -3.97522971e-02,  3.39029022e-02,  1.15428932e-01,
        1.49150357e-01, -1.70040298e-02,  6.07012622e-02,  5.24313040e-02,
        5.81151135e-02, -1.43132165e-01,  8.46673399e-02, -1.25544369e-01,
       -1.54793277e-01,  1.55029789e-01,  3.00366133e-01,  3.70556042e-02,
        1.61057323e-01, -9.04680565e-02,  2.22339123e-01,  1.85541920e-02,
       -1.10785216e-01,  2.58139729e-01,  3.98251377e-02, -8.24986249e-02,
       -8.17401633e-02,  3.29184920e-01,  2.64550984e-01, -9.21682939e-02,
        1.10345170e-01,  1.09504320e-01,  1.70327023e-01,  2.23622650e-01,
       -2.32685789e-01,  2.02678651e-01, -3.43952537e-01,  1.36332035e-01,
       -1.17430329e-01,  7.47583508e-02, -8.83676037e-02, -1.41839221e-01,
       -1.21968128e-01,  1.24097981e-01,  2.78613210e-01, -1.51560515e-01,
        2.09409762e-02,  1.34605080e-01, -1.16944328e-01,  1.34094670e-01,
       -2.10202366e-01, -5.74157424e-02, -3.56289186e-02, -2.48784840e-01,
        1.75054729e-01, -1.79003760e-01,  4.60957363e-02,  7.43861943e-02,
        2.97144592e-01, -1.95794418e-01,  2.43258998e-01, -4.67627384e-02,
        1.74933702e-01, -3.76163572e-02,  9.63959545e-02, -5.24839610e-02,
        2.06855983e-01, -1.41930608e-02, -9.49969664e-02, -2.13499263e-01,
       -1.88927967e-02,  1.21070720e-01,  2.55917549e-01, -9.79969352e-02,
       -1.44158534e-04, -1.78542584e-01, -1.92981839e-01, -2.26907015e-01,
       -1.13902070e-01,  2.26483401e-02,  3.30397040e-02,  8.01226646e-02,
       -1.35729223e-01, -1.21881559e-01,  2.14131519e-01, -1.41845897e-01,
       -1.03724599e-01,  4.17516828e-02, -2.86913905e-02, -2.02333450e-01,
        1.11024566e-01, -1.17108986e-01, -2.09321201e-01,  3.13546397e-02,
       -1.37337416e-01, -1.52514085e-01, -5.99950179e-02, -1.09039627e-01,
        1.61810532e-01,  1.22085735e-01, -4.22081761e-02, -9.46462676e-02,
       -1.01089463e-01,  1.38924047e-01,  1.54850423e-01,  6.49040043e-02,
        1.70641944e-01,  1.37738079e-01,  2.46562660e-01, -2.18565539e-01,
        1.24139413e-01,  2.18790710e-01, -8.78168717e-02,  4.72499877e-02,
        1.60218194e-01,  2.60939956e-01,  1.62507907e-01, -1.88750982e-01,
       -1.18508242e-01,  2.64811832e-02, -9.54344720e-02,  8.26519132e-02,
        1.40061483e-01, -1.60392672e-02,  3.44366357e-02, -2.07341552e-01,
       -1.15082912e-01, -1.78399429e-01, -1.69677004e-01,  9.96885076e-02,
       -8.28549191e-02, -1.62402228e-01, -6.78750947e-02, -1.58218354e-01,
       -2.05537200e-01, -2.08618641e-01,  1.65924728e-01,  5.01697548e-02,
        9.60115250e-03,  1.73052385e-01, -3.12310569e-02, -5.82811683e-02,
       -1.71314180e-01,  3.03064957e-02,  2.54750282e-01, -1.79447144e-01,
        6.29571229e-02, -6.88925311e-02, -1.46519020e-01, -2.85492819e-02,
        1.58236668e-01, -8.93786848e-02, -3.45615577e-03, -2.90604811e-02,
       -4.24151085e-02, -1.43091679e-01,  1.50270984e-01,  2.56532226e-02,
        1.27464890e-01, -6.67258650e-02, -1.66751787e-01,  2.20003992e-01,
        3.04683417e-01,  3.01681787e-01, -1.58920348e-01, -8.31235051e-02,
       -1.03066452e-01, -2.61823535e-01,  1.92791820e-01, -1.64389666e-02,
        2.61561692e-01,  1.07751697e-01, -4.96926717e-02,  1.46302566e-01,
       -1.17565870e-01,  9.07146707e-02,  7.04389587e-02,  1.13857836e-01,
       -8.30066297e-03,  2.10442007e-01,  2.32769400e-02, -1.19694285e-01,
        5.48621081e-02,  5.05557172e-02, -8.37304071e-02, -5.27403131e-02,
       -1.33825004e-01, -1.12190001e-01,  2.42128465e-02, -8.31155702e-02,
        8.82810503e-02,  5.41741624e-02, -3.06045194e-03,  6.41210452e-02,
       -1.19361021e-01,  8.80529583e-02,  2.28095382e-01,  1.32805854e-01,
        1.27777830e-01,  1.05374061e-01, -7.42736310e-02,  3.53429541e-02,
       -1.76825240e-01,  1.93588242e-01, -1.55950040e-01, -1.24566682e-01,
       -1.11057147e-01, -3.37307528e-03,  4.19847183e-02, -9.61011276e-02,
       -1.04349409e-03, -2.32734364e-02, -1.29049644e-01, -2.93098064e-03,
       -2.22068995e-01, -1.79522112e-02, -2.34383672e-01, -1.77793667e-01,
        1.08801417e-01,  1.90222383e-01,  7.57032782e-02, -5.95891252e-02,
       -1.76626593e-01,  1.06366694e-01, -4.16238904e-02, -1.29492125e-02,
        6.33338019e-02,  3.27049851e-01,  2.69842267e-01,  2.48614162e-01,
        1.10219650e-01,  1.57006770e-01, -6.43666089e-02, -1.43948048e-01,
       -3.90609913e-02,  1.71765819e-01,  1.30566418e-01,  6.91659153e-02,
        6.67057633e-02,  2.00983256e-01,  4.68495041e-02, -2.22541794e-01,
       -3.62155139e-02,  1.82483554e-01, -1.66034803e-01, -2.35664070e-01,
       -3.45560461e-02, -7.18978196e-02,  3.58679533e-01, -2.04103217e-01,
        5.62971979e-02, -3.68943177e-02,  2.10624352e-01, -2.18760759e-01,
       -1.18377812e-01,  2.54123360e-01,  2.13849440e-01, -4.49307263e-02,
        3.24713849e-02,  8.32705423e-02, -1.04825743e-01, -1.39674515e-01,
        1.55586913e-01,  2.78965533e-01,  1.29949138e-01,  2.60793239e-01,
       -1.61157504e-01,  2.02024594e-01, -1.66936651e-01,  1.48245111e-01,
       -1.13919126e-02, -9.54872668e-02, -5.62611930e-02, -1.38645440e-01,
       -1.36905834e-01, -3.15658413e-02, -1.43869698e-01, -1.72829032e-01,
        8.75512585e-02, -1.24711774e-01,  4.49763209e-01,  2.31423110e-01,
        2.19202101e-01, -2.00356785e-02, -3.35562862e-02, -1.89790219e-01,
       -1.48332909e-01,  2.84928888e-01, -6.27711862e-02,  1.74948871e-01,
       -2.07374357e-02,  2.29053587e-01,  2.99470294e-02, -1.71235844e-01,
        1.27457246e-01, -3.57336104e-02,  1.03467055e-01,  8.66477005e-03,
       -2.10711941e-01, -2.26554349e-01,  1.21524870e-01, -1.70730338e-01,
        1.53798983e-01,  2.03853831e-01,  8.15943629e-02,  3.17326903e-01,
       -1.37156859e-01,  1.07023135e-01, -1.52229622e-01, -1.04544736e-01,
       -9.76322591e-02,  4.77544256e-02,  1.42037705e-01,  2.45321259e-01,
       -3.02323550e-01,  1.62490159e-01,  1.00589924e-01,  6.08875230e-02,
       -1.79770738e-01, -2.15224624e-01,  1.35824859e-01,  1.58502519e-01,
       -1.74732387e-01, -7.07292333e-02, -2.44562328e-02, -5.41592725e-02,
       -1.83466911e-01,  4.37777601e-02,  3.27209458e-02,  2.06267625e-01,
        1.49012908e-01, -6.35771900e-02, -1.54927164e-01,  1.88395113e-01,
        1.38751060e-01, -1.20819822e-01,  1.81894630e-01, -1.06011763e-01,
       -1.93041209e-02,  1.74277872e-01,  4.03217562e-02, -1.12548918e-01,
       -9.79779512e-02,  1.52813718e-01,  1.17184393e-01, -8.42020065e-02,
        2.42086142e-01,  3.01618755e-01,  2.31265619e-01, -2.36355767e-01,
       -1.87686697e-01, -1.70317084e-01, -2.69354507e-02,  2.19270632e-01],
      dtype=float32), array([0.7979577 , 0.27775624, 0.19003066, 0.11113074, 0.46618572,
       0.18396248, 0.32817003, 0.35462472, 0.17750047, 0.25446984,
       0.424162  , 0.23232399, 0.3977387 , 0.28369206, 0.3030212 ,
       0.65334713, 0.21259688, 0.6830497 , 0.3825818 , 0.13307372,
       0.47812378, 0.11744043, 0.9793874 , 0.17910971, 0.71041155,
       0.1811703 , 0.3572582 , 1.071511  , 0.35626462, 0.26464593,
       0.5825693 , 0.43176156, 1.278723  , 0.20120956, 1.1662873 ,
       0.9068217 , 0.4393444 , 0.45667508, 0.5734084 , 0.4422192 ,
       0.43392894, 0.3340027 , 0.24219084, 0.21558347, 0.6314734 ,
       0.4560972 , 0.16466196, 0.48942906, 0.14089182, 0.37205163,
       0.3302148 , 0.20374903, 0.32545483, 0.30613402, 0.6206954 ,
       0.30347875, 0.1244163 , 0.30091205, 0.1840206 , 0.24965888,
       0.21786249, 0.29276332, 0.20962068, 0.5027261 , 1.4017526 ,
       0.5121005 , 0.30278096, 0.22514187, 0.28578913, 0.62303233,
       0.67724174, 0.3666826 , 1.247573  , 0.25521728, 0.28069773,
       0.45595166, 0.24057388, 0.5550964 , 0.50197446, 0.4511992 ,
       0.23624966, 0.27137247, 0.27242425, 0.27891362, 0.3639593 ,
       0.5812676 , 0.33281878, 0.15742049, 0.38854048, 0.27019045,
       0.42600486, 0.94829476, 0.39120328, 0.39885396, 0.4182962 ,
       0.56908846, 0.42625886, 0.46290085, 0.6880805 , 0.6247663 ,
       0.4305161 , 0.31112856, 0.65140337, 0.46813467, 0.46266517,
       0.2992352 , 0.5818276 , 0.12924507, 0.23858024, 0.37317896,
       0.6415685 , 0.15777236, 0.29636663, 0.1970715 , 0.41661218,
       0.62585247, 0.27685574, 0.15743794, 0.31234968, 0.25128943,
       0.4076509 , 0.2862688 , 0.63396525, 0.55213165, 0.5853696 ,
       0.3431174 , 0.86814016, 0.23388115, 0.44311816, 0.25173572,
       0.3360873 , 0.3390107 , 0.6490656 , 0.30605137, 0.20632415,
       0.26031575, 0.30138904, 0.5324642 , 0.5882429 , 0.42911193,
       0.9922879 , 0.23885868, 0.24694593, 0.61264014, 0.7018992 ,
       0.19635291, 0.4518861 , 0.78569925, 0.1761232 , 0.29444897,
       0.18165831, 0.20708916, 1.0728408 , 0.40762076, 0.3498491 ,
       0.30080095, 0.23019822, 0.12612595, 0.25104812, 0.20439006,
       1.1928178 , 0.21941851, 0.4892349 , 0.31577954, 0.17299786,
       0.6088665 , 0.4620251 , 0.35564357, 0.25822103, 0.97665524,
       0.7847926 , 0.21433884, 0.6212447 , 0.2136458 , 0.25539058,
       0.40135983, 0.32827893, 0.18134584, 0.842365  , 0.49550492,
       0.34350756, 0.45094448, 0.26526743, 0.17824389, 0.2122708 ,
       0.15900156, 0.38507178, 0.5653796 , 0.5537375 , 0.204707  ,
       0.43239143, 0.8247939 , 0.30495808, 0.47018817, 0.19512518,
       0.37876514, 0.27374586, 0.45208365, 0.26272428, 0.8410704 ,
       0.28722423, 0.24240914, 0.39324906, 0.21967794, 0.70961   ,
       0.73189604, 0.58955306, 0.35201252, 0.1551806 , 0.42014948,
       0.5112443 , 0.44375467, 0.6195514 , 1.0944235 , 0.15437952,
       0.38952312, 0.6564055 , 0.29135963, 0.294459  , 0.33720586,
       0.33088103, 0.24017338, 0.22863646, 0.63277006, 0.28145364,
       0.652383  , 0.5398534 , 0.33598405, 0.32247406, 0.42009684,
       0.27848467, 0.16042389, 0.39664423, 0.6777224 , 0.24374282,
       0.24306846, 0.22574376, 0.14941882, 0.42536107, 0.31628096,
       0.47449496, 0.35686967, 0.50425404, 0.15439567, 0.22396028,
       0.2376265 , 0.7623628 , 0.10678711, 0.34145227, 0.43878105,
       0.2633896 , 0.6881568 , 0.24294993, 0.7109518 , 0.2680404 ,
       0.8875876 , 0.12992576, 0.29903105, 0.3193907 , 0.32618734,
       0.9413223 , 0.28359768, 0.33773205, 0.42247424, 0.22678609,
       0.6530217 , 0.19853282, 0.25549677, 0.49257904, 0.6190925 ,
       0.38889813, 0.36863154, 0.5888151 , 0.3492736 , 1.4372238 ,
       0.78476477, 0.6378681 , 0.23718175, 0.3834698 , 0.23014633,
       0.28461972, 0.18936303, 0.82755417, 0.21540275, 0.46644905,
       0.43946594, 0.23859085, 0.5939844 , 0.5002671 , 0.19349842,
       0.21164024, 0.38730517, 0.26828325, 0.5692559 , 0.16845591,
       0.75808674, 0.22820717, 0.21502085, 0.26724422, 0.5883858 ,
       0.2878204 , 0.3162203 , 0.29927447, 0.18541926, 0.46243724,
       0.4301531 , 0.17528808, 0.14265889, 0.42405665, 0.28091154,
       0.502479  , 0.2385691 , 0.36873785, 0.39228567, 0.291309  ,
       0.29139435, 0.17443371, 0.14915167, 0.63919055, 0.20157811,
       0.44373003, 0.18845746, 0.64857155, 0.49272868, 0.1928395 ,
       0.4105518 , 0.4933439 , 0.40110844, 0.25828847, 0.2993679 ,
       0.47202745, 0.28992113, 0.45302287, 0.46692026, 0.15565507,
       0.533414  , 0.5271787 , 0.23739827, 0.198837  , 0.4608247 ,
       0.34077775, 0.34572875, 0.17527555, 0.22726454, 0.5368347 ,
       0.5000647 , 0.2775981 , 0.59596264, 0.29577178, 0.28434387,
       0.2631796 , 0.49049515, 1.0702225 , 0.16967484, 0.26442638,
       0.24043973, 0.5260766 , 0.6374677 , 0.3057706 , 0.24853268,
       0.23085453, 0.4084017 , 0.27162647, 0.27918693, 0.2940531 ,
       0.42337227, 0.2447847 , 0.3966841 , 0.29849896, 1.4803369 ,
       0.29546404, 0.40384534, 0.3194055 , 0.28069967, 0.43780997,
       0.2989637 , 0.2576761 , 0.13295269, 0.20588252, 0.24088213,
       0.3031704 , 0.8214015 , 0.25027642, 0.2250317 , 0.23693025,
       0.21128365, 0.48192796, 0.3558332 , 0.51499766, 0.35612503,
       1.1102567 , 0.3170366 , 0.4327322 , 0.19261536, 0.1939821 ,
       0.11534694, 0.3826725 , 0.67881423, 0.13235216, 0.22286683,
       0.4041461 , 0.30443284, 0.75477743, 0.37327635, 0.23049146,
       0.35747728, 0.33217785, 0.43244997, 0.59781414, 0.6263509 ,
       0.91258925, 0.3075087 , 0.41615346, 0.4094468 , 0.27038315,
       0.22286832, 0.36104798, 0.27121183, 0.86792356, 0.629467  ,
       0.38305414, 0.16845994, 0.201697  , 0.2728218 , 0.61287963,
       0.44249344, 0.36526242, 0.32933366, 0.5474501 , 0.45699993,
       0.39217272, 0.17174277, 0.5065327 , 0.45689914, 0.77317345,
       0.46683967, 0.4043253 , 0.29370084, 0.23692033, 0.10559453,
       0.4347329 , 0.47654837, 0.32095268, 0.38579303, 0.3733331 ,
       0.34701914, 0.62300915, 0.19446473, 0.12319633, 0.16572413,
       0.16385435, 0.62904376, 0.32672796, 0.2632857 , 0.3687995 ,
       0.5851303 , 0.54840106, 0.6145406 , 0.51155794, 0.2530998 ,
       0.34327233, 0.12254654, 0.26046282, 0.6406664 , 0.39337906,
       0.4102698 , 0.34899426, 0.22133072, 0.38938653, 0.21351446,
       0.17649204, 0.38206172, 0.31801122, 0.49001613, 0.1427106 ,
       0.1961976 , 0.43252093, 0.30701652, 0.3418815 , 0.1735922 ,
       0.3177069 , 0.23153059, 0.4719933 , 0.9089797 , 0.22146086,
       0.57453114, 0.46772912, 0.1297762 , 0.6604672 , 0.7419576 ,
       0.47881573, 0.5015485 , 0.34172058, 0.12559842, 0.2701027 ,
       0.22430491, 0.13833067, 0.34205928, 0.5696308 , 0.15867008,
       0.30677804, 0.27171582, 0.39411765, 0.3211901 , 0.2850352 ,
       0.6414532 , 0.28060943, 0.48464388, 0.44872704, 0.4538519 ,
       0.17240728, 0.21337621, 0.20265684, 0.35752267, 0.34855062,
       0.32751074, 0.63026947, 0.16122773, 0.5792494 , 0.51246727,
       0.23502214, 0.25702015, 0.5402247 , 0.20532137, 0.36532962,
       0.19861998, 0.68711925, 0.33898956, 0.3585073 , 0.42247817,
       0.70628893, 0.18093707, 0.30211473, 0.39510584, 0.16443864,
       0.20414059, 0.78051496, 0.7071584 , 0.8390162 , 0.17462745,
       0.404996  , 0.6815133 , 0.39768344, 0.23389308, 0.5506895 ,
       0.27138022, 0.3369959 , 0.706527  , 0.2314865 , 0.2742691 ,
       0.29802418, 0.17259414, 0.20922051, 0.35389987, 0.16879846,
       0.22185077, 0.31941184, 0.32490197, 0.16639318, 0.13862945,
       0.25694484, 0.19678953, 0.25329658, 0.86548984, 0.34430236,
       0.12953798, 0.15032694, 0.30773866, 0.43269914, 0.32452607,
       0.6305575 , 0.2553598 , 0.79267806, 0.34706303, 0.33767757,
       0.36447582, 0.32413015, 0.37765026, 0.7972115 , 0.68299234,
       0.28003755, 0.13644174, 0.14043507, 0.5754356 , 0.19987315,
       0.38626155, 0.25001138, 0.17235641, 0.3410469 , 0.38025403,
       1.1775932 , 0.5071478 , 0.24593773, 0.38427934, 0.1476583 ,
       0.28427514, 0.43310443, 0.26376826, 0.3071509 , 0.29647684,
       0.24897721, 0.6969143 , 1.0714731 , 0.27625808, 0.22817369,
       0.5973438 , 0.18685368, 0.23945232, 0.5334606 , 0.15487908,
       0.25286758, 0.6083771 , 0.27279803, 0.58261186, 0.22946231,
       0.6267087 , 0.11752245, 0.33476958, 0.30602598, 0.7453603 ,
       0.31505707, 0.5143577 , 0.96190107, 0.27470288, 0.27820787,
       0.1537915 , 0.38264105, 0.52723795, 0.16814414, 0.26390228,
       0.7767926 , 0.34737659, 0.23992546, 0.17668551, 0.1868524 ,
       0.40763962, 0.38129872, 1.1656879 , 0.38889614, 0.37773317,
       0.4020579 , 0.5488212 , 0.26606944, 0.49033087, 0.21646257,
       0.6411247 , 0.27858368, 0.5198066 , 0.22224031, 0.35379094,
       0.84651005, 0.53025323, 0.12856106, 0.6754854 , 1.7565714 ,
       0.46042526, 0.40127575, 0.45379147, 0.32525778, 0.47328615,
       0.31317335, 0.92892903, 0.3076941 , 0.44634762, 0.16497855,
       0.34191555, 0.22576676, 0.3055394 , 0.28876546, 0.26099476,
       0.42306852, 0.30770454, 0.39913568, 0.2727626 , 0.3202683 ,
       0.2917112 , 0.42214835, 0.4393561 , 0.37040624, 1.0556998 ,
       0.31441745, 0.5054645 , 0.20844752, 0.4475244 , 0.1527054 ,
       0.1979862 , 0.43404135, 0.70394766, 0.8403628 , 0.5333824 ,
       0.29320958, 0.16329405, 0.5136632 , 0.28678653, 0.5002169 ,
       0.4117542 , 0.24943843, 0.27011198, 0.23127258, 0.28383493,
       0.517485  , 0.18798044, 0.33095986, 0.42722675, 0.32910216,
       1.4478694 , 0.51573217, 0.5614771 , 0.30395222, 0.34985265,
       0.6446666 , 0.38134953, 0.43896493, 0.5742042 , 0.1754937 ,
       0.3620779 , 0.18298529, 0.39281738, 0.4518863 , 0.13458894,
       0.68314385, 0.56790745, 0.3404843 , 0.46826634, 0.6736003 ,
       0.4442683 , 0.611277  , 0.44550404], dtype=float32), array([[[[-2.64618360e-03],
         [-1.25523480e-02],
         [-1.65318903e-02],
         ...,
         [-1.98805649e-02],
         [-9.16902442e-03],
         [ 8.78408551e-03]],

        [[-3.60090695e-02],
         [-2.10754406e-02],
         [ 1.13061229e-02],
         ...,
         [-1.27052506e-02],
         [ 3.02448422e-02],
         [-5.39024640e-03]],

        [[ 2.13503808e-05],
         [-8.99005868e-03],
         [ 1.48548081e-03],
         ...,
         [ 9.33622010e-03],
         [ 9.01956856e-03],
         [ 3.17523703e-02]]],


       [[[-3.29128318e-02],
         [-1.34452200e-02],
         [-6.32972131e-03],
         ...,
         [-2.77708340e-02],
         [-1.27267595e-02],
         [ 1.89935435e-02]],

        [[-1.81603916e-02],
         [ 1.24006988e-02],
         [ 3.00892200e-02],
         ...,
         [ 9.07465909e-03],
         [ 2.46287547e-02],
         [-3.33130825e-04]],

        [[-2.25023665e-02],
         [ 1.35281896e-02],
         [ 3.21944244e-02],
         ...,
         [-1.65869426e-02],
         [ 3.84898670e-02],
         [ 4.35851840e-03]]],


       [[[ 5.88427018e-03],
         [ 7.79649941e-03],
         [ 2.86606122e-02],
         ...,
         [ 1.80500560e-02],
         [ 2.94050630e-02],
         [-2.27988958e-02]],

        [[ 1.30849215e-03],
         [ 1.84996836e-02],
         [-4.88693826e-03],
         ...,
         [-4.00741445e-03],
         [ 2.96538733e-02],
         [ 5.76875033e-03]],

        [[ 1.62561145e-02],
         [-1.14923343e-02],
         [ 2.60198805e-02],
         ...,
         [-1.34935565e-02],
         [ 1.56576335e-02],
         [ 2.05683112e-02]]]], dtype=float32), array([[[[ 0.02211971,  0.00394004,  0.07362094, ...,  0.02224598,
          -0.03064118, -0.00549973],
         [ 0.00097093,  0.01486109, -0.05220751, ..., -0.05636235,
          -0.00873778,  0.04334402],
         [ 0.01628594,  0.0387939 ,  0.04851506, ..., -0.0573838 ,
           0.01650797,  0.01185393],
         ...,
         [ 0.02722306,  0.04411721, -0.03537076, ...,  0.00795226,
           0.05052747, -0.01333305],
         [ 0.02738447,  0.03005598, -0.02236748, ..., -0.0024549 ,
          -0.02321774, -0.02765727],
         [-0.02827774,  0.02581043, -0.03197446, ..., -0.00907111,
          -0.00500605,  0.05662595]]]], dtype=float32), array([0.9881597 , 0.9885151 , 1.0011445 , 1.035853  , 1.003276  ,
       1.0053623 , 1.0019479 , 0.9858455 , 0.9949118 , 0.9952622 ,
       0.99212855, 1.0034982 , 1.0027598 , 0.9897968 , 0.998628  ,
       1.0057765 , 1.004171  , 1.0024385 , 0.99486494, 1.0020729 ,
       0.9926921 , 0.9945071 , 0.98992914, 0.9967283 , 0.9908397 ,
       0.9943521 , 0.99906623, 0.9984815 , 1.0022752 , 0.9889713 ,
       1.0089003 , 1.0041735 , 0.9955872 , 0.9988054 , 0.9983593 ,
       0.99843353, 0.9903039 , 0.99316496, 0.9921136 , 0.99894714,
       0.98772305, 0.99040896, 1.002721  , 1.0032859 , 1.0173823 ,
       0.9924513 , 1.0130291 , 1.0076361 , 0.9914933 , 1.0171733 ,
       0.9970676 , 1.0173507 , 1.0007815 , 1.0127772 , 1.0029676 ,
       0.99492675, 1.003258  , 1.0489908 , 1.0104485 , 1.0528463 ,
       0.99770224, 1.0043079 , 0.9992984 , 0.9958284 , 0.99571216,
       1.0088786 , 0.99185723, 1.003813  , 0.996694  , 0.9965167 ,
       0.9900905 , 0.9931233 , 0.9898499 , 1.0130119 , 0.99280745,
       1.0067941 , 0.9877858 , 0.9989045 , 0.9868474 , 0.9898189 ,
       0.9954891 , 1.0292834 , 0.9912584 , 1.0054046 , 0.98982656,
       0.99473524, 1.0002071 , 0.9752428 , 0.99544674, 1.0042636 ,
       0.99717414, 0.9965747 , 0.9981796 , 0.99625254, 1.000982  ,
       0.996269  , 0.9939366 , 0.9901678 , 0.9908459 , 0.9945035 ,
       1.0011352 , 1.004735  , 0.9974665 , 1.0024525 , 0.9986355 ,
       1.010867  , 0.98983514, 1.0065582 , 1.0048648 , 0.995191  ,
       1.002829  , 0.99758   , 0.99983656, 0.9978888 , 0.99274266,
       0.9923188 , 1.0031095 , 1.0108012 , 0.998522  , 1.0102413 ,
       0.9899671 , 1.0089899 , 1.0023412 , 1.0055937 , 1.0051337 ,
       0.9909245 , 0.9959873 , 1.0145946 , 1.0018431 , 0.99960333,
       0.9887994 , 1.0115684 , 1.0197062 , 0.9974324 , 0.99794745,
       1.0002606 , 1.0205469 , 1.0020956 , 0.99761134, 1.0046546 ,
       0.99260896, 0.99358016, 0.9831871 , 1.0038955 , 0.99664587,
       0.99384373, 0.9910709 , 1.0047618 , 1.0004978 , 1.0007455 ,
       1.000325  , 0.98584044, 1.0056449 , 1.0209557 , 1.003337  ,
       0.99114656, 1.0020559 , 0.9923389 , 1.0040569 , 1.0043497 ,
       0.9940664 , 0.999843  , 1.0023876 , 0.9880763 , 1.0017219 ,
       1.0388011 , 1.0051649 , 0.99747366, 0.9908857 , 0.9945315 ,
       0.9993452 , 1.0073972 , 0.9997907 , 0.9948376 , 1.0006915 ,
       1.0254953 , 1.0141251 , 0.9895787 , 0.9929509 , 0.9951749 ,
       1.0145892 , 0.98533595, 0.9985128 , 0.9996529 , 0.9903956 ,
       0.9906825 , 1.0054022 , 0.9929726 , 0.9974953 , 0.9988937 ,
       0.9971949 , 1.010069  , 1.0073547 , 0.9928097 , 1.0089539 ,
       1.0126007 , 1.0010206 , 0.9918257 , 1.0055325 , 0.9938835 ,
       1.0032353 , 0.98549813, 0.999336  , 0.99272346, 0.9974486 ,
       0.994657  , 0.99364203, 1.0061198 , 1.0004275 , 1.0128404 ,
       1.0009288 , 1.0160716 , 1.0034279 , 0.99434793, 0.990531  ,
       0.9939853 , 0.99323857, 1.0037283 , 0.9940054 , 1.0014564 ,
       1.0011437 , 1.0042374 , 1.0008357 , 0.99399406, 0.9889063 ,
       0.9977414 , 1.0060468 , 0.9934734 , 0.9977128 , 0.9919817 ,
       0.9979945 , 0.9954681 , 1.0222051 , 0.9876854 , 0.99673504,
       1.0185628 , 1.0000968 , 0.99215454, 1.0138206 , 0.9963632 ,
       0.9898666 , 0.9958386 , 0.9972941 , 0.98957384, 0.9994389 ,
       1.0195776 , 1.0030448 , 0.9931485 , 1.0219727 , 0.9905037 ,
       1.0053381 , 0.98141265, 0.9904031 , 1.0006057 , 1.0090503 ,
       0.99429667, 0.9906503 , 0.997221  , 0.993933  , 0.9826788 ,
       1.0121815 , 1.010461  , 0.99621326, 0.9975121 , 0.9993246 ,
       0.9886875 , 1.0032406 , 0.9947316 , 1.002928  , 1.01468   ,
       1.005808  , 1.0273789 , 1.0013454 , 0.9837495 , 0.9996389 ,
       0.99825066, 0.99797547, 0.9930286 , 1.0040989 , 1.0074902 ,
       0.99893373, 1.0003331 , 1.007878  , 1.0071454 , 0.9958138 ,
       0.9915786 , 0.98728496, 1.0012611 , 0.99260503, 0.98645073,
       0.992312  , 0.9867094 , 1.0085318 , 0.9993903 , 0.9932961 ,
       1.0053982 , 0.9987592 , 0.9962851 , 0.99480623, 0.99683136,
       0.9962787 , 0.9883545 , 0.9946352 , 0.9901463 , 0.98826385,
       1.0046613 , 1.0079833 , 0.9933948 , 0.99434876, 0.99736476,
       1.0002501 , 0.9888429 , 1.0219218 , 1.0112655 , 0.99631584,
       1.0082312 , 1.0021868 , 1.0104773 , 1.0051116 , 1.002027  ,
       0.9877538 , 0.9950902 , 0.9943804 , 0.99419093, 0.9962914 ,
       0.9960828 , 0.9939975 , 1.0041646 , 1.0070442 , 1.0261327 ,
       1.0093154 , 0.99413174, 0.99561185, 0.99514914, 0.99823993,
       1.0046222 , 1.0012424 , 0.99831825, 1.0014886 , 0.99531937,
       0.9911227 , 1.0307016 , 1.0049162 , 0.9898225 , 1.0125021 ,
       0.9892188 , 1.0001831 , 0.9913917 , 0.9993309 , 0.9979321 ,
       0.9967356 , 1.0089096 , 0.99891436, 0.9947335 , 1.0028884 ,
       0.98590004, 1.0159566 , 0.99772835, 0.99395597, 0.98903984,
       0.99498016, 1.0064026 , 0.99215484, 0.9959542 , 0.9867502 ,
       0.99931854, 0.993073  , 1.0001692 , 0.998441  , 1.0105213 ,
       0.9942235 , 0.99853206, 1.0092434 , 1.0043528 , 1.0041188 ,
       0.9971393 , 1.0091046 , 0.9883227 , 0.9955466 , 0.9978302 ,
       0.99329394, 0.99346244, 0.99301195, 0.9955281 , 0.98721695,
       0.9985069 , 0.9911927 , 0.98353755, 1.0076814 , 1.0106221 ,
       0.9984993 , 0.9993966 , 0.9894398 , 0.99378264, 0.99298286,
       0.99481255, 0.99676645, 0.9963134 , 0.993892  , 0.99094415,
       1.0063719 , 1.0155606 , 1.0006967 , 1.024083  , 0.9924707 ,
       0.98811364, 1.0094991 , 0.99855655, 1.0036445 , 0.98927635,
       1.0030396 , 0.9942137 , 0.9982268 , 0.99868274, 1.0007049 ,
       0.99208397, 1.0019602 , 1.0061768 , 0.9991504 , 0.99665755,
       0.9963841 , 1.03166   , 1.0036438 , 0.99976695, 0.99772614,
       1.0498807 , 0.9988757 , 0.99469906, 0.9876743 , 1.000354  ,
       0.99837035, 0.999405  , 0.99091864, 1.009514  , 1.006378  ,
       0.9972509 , 1.0097327 , 1.0214291 , 0.9949103 , 1.0018705 ,
       0.994722  , 0.9937651 , 1.0058497 , 0.9915865 , 0.99530244,
       1.0082575 , 0.9901238 , 0.9965278 , 1.0026335 , 1.0042853 ,
       0.9988628 , 1.0117319 , 0.99339044, 0.9821941 , 0.994825  ,
       0.9939913 , 0.9930331 , 1.0323664 , 0.9975579 , 0.99845755,
       0.9917401 , 1.0010983 , 1.0088855 , 1.0206343 , 0.99581796,
       1.0045859 , 1.0001951 , 1.0136951 , 0.99449533, 0.99432355,
       1.0213646 , 0.9925749 , 1.0164361 , 1.0019892 , 0.9954607 ,
       1.0094306 , 0.99832946, 0.99982554, 0.9970475 , 0.9902763 ,
       0.996174  , 0.9927916 , 1.0082035 , 0.9945458 , 1.0103374 ,
       0.9912113 , 1.0027694 , 0.99221146, 0.9875772 , 1.0311106 ,
       0.9972445 , 0.99651235, 1.0164189 , 0.99120116, 0.99457586,
       0.9999925 , 0.9996503 , 0.9953975 , 0.99261814, 0.9975003 ,
       0.9864249 , 0.99085796, 1.0081253 , 0.9991776 , 1.0166246 ,
       0.99207824, 0.99176204, 0.99056894, 0.98770964, 0.9881569 ,
       1.0049945 , 0.9912673 , 1.0236838 , 0.9896028 , 0.99358106,
       0.9921307 , 0.9753147 , 0.99307746, 1.0084082 , 0.99516696,
       0.9999708 , 0.9959732 , 0.9913867 , 1.002945  , 0.9999999 ,
       0.99440265, 0.9976186 , 0.9920481 , 1.0069307 , 1.0015012 ,
       1.0035453 , 0.9861766 , 0.9943111 , 1.0037379 , 0.9912616 ,
       0.98855007, 0.9905137 , 1.0114053 , 0.9856303 , 0.9914587 ,
       0.99551636, 1.0041679 , 1.0017728 , 0.98955154, 0.993759  ,
       0.9932853 , 0.99578714, 0.9906219 , 1.0023832 , 0.994816  ,
       0.9798943 , 1.0052775 , 0.9927413 , 1.0110164 , 0.997609  ,
       0.9911071 , 0.9952879 , 1.0144148 , 0.99280113, 1.0017034 ,
       1.0097718 , 0.99195224, 1.0024145 , 1.000256  , 1.000863  ,
       1.0041058 , 1.0043364 , 0.98909414, 0.97782797, 1.0095618 ,
       1.0264658 , 1.0022384 , 0.9950193 , 0.99264246, 1.0044241 ,
       0.9963397 , 1.0057715 , 0.998919  , 0.98768145, 0.9971304 ,
       0.9989953 , 1.0079938 , 1.0044421 , 0.99179447, 0.99525833,
       1.0102297 , 1.0010926 , 1.0184216 , 0.9832812 , 0.99173135,
       0.9984063 , 0.99927825, 0.9953444 , 0.99895996, 0.9928673 ,
       0.99857664, 0.99922633, 0.98837197, 1.0011628 , 1.0049703 ,
       0.9984303 , 0.9958871 , 1.0112878 , 0.99981135, 0.9930157 ,
       0.9920977 , 1.0118757 , 0.99663144, 0.99312997, 0.9995268 ,
       0.99183273, 1.001737  , 1.0010375 , 0.9979998 , 0.9970059 ,
       0.9918536 , 0.99836344, 0.99485356, 0.99192816, 1.0028911 ,
       0.99171567, 0.9932186 , 0.9912473 , 1.0207107 , 1.0047734 ,
       0.9777939 , 0.9991954 , 0.9990028 , 0.9922899 , 1.0218565 ,
       0.99115163, 0.9936501 , 0.99535275, 1.0432837 , 1.0082114 ,
       1.0001314 , 0.9907768 , 0.99762356, 0.9960791 , 1.0037731 ,
       1.0033199 , 0.99638367, 1.0032871 , 1.012272  , 1.0014814 ,
       0.9953067 , 1.0018256 , 0.99228585, 1.0007592 , 0.9966322 ,
       1.0035454 , 0.9948053 , 0.9937653 , 0.992384  , 1.0139947 ,
       1.0018348 , 0.9919247 , 0.9977291 , 0.9956213 , 0.99492687,
       0.997082  , 1.0270376 , 1.0050658 , 0.9855326 , 1.0008743 ,
       0.99522233, 0.99029475, 1.0227681 , 0.9998623 , 0.9890616 ,
       0.9915887 , 1.0127779 , 0.99311095, 0.99539036, 0.9900983 ,
       0.9930525 , 1.0131088 , 0.99548507, 0.99023825, 0.99225295,
       1.0005342 , 1.0087924 , 0.99039036, 1.0247068 , 1.0047596 ,
       1.0225264 , 0.99263334, 0.9832855 , 1.0013312 , 0.99784493,
       1.0033809 , 0.993279  , 0.9939236 , 1.0000622 , 0.9960005 ,
       0.99853885, 1.0099964 , 0.9941896 , 1.033885  , 0.99787223,
       0.9974219 , 0.98643106, 1.0037035 , 1.0051594 , 0.9851325 ,
       0.98877037, 1.0019705 , 0.997003  , 1.0103953 , 1.0083957 ,
       0.98636127, 1.0110432 , 1.0229498 , 0.9964093 , 0.98449385,
       1.0033872 , 0.9950195 , 0.9910404 , 0.99796635, 0.9903561 ,
       1.0010933 , 1.0047979 , 0.9905618 , 0.9996161 , 0.99575496,
       1.0011411 , 0.9977144 , 1.0174373 ], dtype=float32), array([-5.46131190e-03, -8.21533147e-03,  1.38029149e-02,  8.78983457e-03,
        6.78021135e-03, -2.77017578e-02,  1.06695937e-02, -1.75743476e-02,
       -3.96445114e-03, -5.81491925e-03, -6.96337549e-03, -4.65276726e-02,
        1.22069111e-02, -9.00271535e-03, -2.21171547e-02,  1.02227670e-03,
        5.65552339e-03,  2.14120117e-03, -8.92699044e-03, -1.06044738e-02,
       -3.83309717e-03,  1.29652873e-03, -1.50475539e-02, -8.68599210e-03,
       -2.38775671e-03,  5.94814832e-04, -2.81721819e-02, -4.27128701e-03,
        5.13377925e-03,  7.31130014e-04,  5.32552972e-03,  1.65300872e-02,
       -1.37372408e-02, -3.20857158e-03,  1.69395888e-03, -1.73849706e-02,
       -9.02163424e-03,  2.24504974e-02, -7.42489751e-03, -1.72533124e-04,
       -1.15208616e-02, -1.55152045e-02, -3.21056992e-02,  9.92693007e-03,
       -6.85761273e-02, -1.83494703e-03, -1.42321242e-02, -1.27580287e-02,
       -2.47513817e-04, -3.04160709e-03, -7.19169853e-03, -3.06932931e-03,
       -1.00411777e-03,  1.73729472e-03,  6.76555932e-03, -3.13641992e-03,
       -3.92674981e-03, -1.96661912e-02,  3.17942677e-03, -2.25861575e-02,
        1.48085263e-02, -1.93801280e-02, -2.67382478e-03,  1.98785984e-03,
       -8.76762439e-03, -1.28529556e-02, -9.91277490e-03,  3.10536008e-03,
        9.02939239e-04, -6.57356635e-04, -3.11587770e-02, -7.89380539e-03,
        4.48438386e-03,  1.45311398e-03, -2.03817151e-03, -2.50771549e-02,
        6.65602041e-03,  3.92076466e-03,  2.89266906e-03, -1.08011654e-02,
        1.24010677e-02, -1.57997627e-02, -1.14294444e-03,  7.58957723e-03,
       -7.33315712e-03,  2.77996715e-03,  1.01420386e-02, -1.68707483e-02,
       -3.18832463e-03, -1.11238211e-02, -1.46423595e-03, -7.64881168e-03,
       -5.48765808e-03, -4.14582202e-03,  2.39153998e-03, -1.91384472e-03,
       -5.73262991e-03, -9.97237023e-03,  3.96261271e-03,  5.07001299e-03,
        1.20359939e-02, -1.13610448e-02, -8.37864541e-03, -1.06455060e-02,
       -3.87287844e-04,  1.67393368e-02, -1.08446414e-02, -7.88574759e-03,
       -2.28485931e-02, -9.40641109e-03,  5.28708752e-03, -1.03852414e-02,
       -8.00830219e-03, -1.39205037e-02, -3.68767022e-03, -3.83507228e-03,
       -1.45059852e-02, -1.95295922e-02,  5.37781860e-04,  1.01967501e-02,
       -9.82979219e-03,  2.42509432e-02, -1.34264620e-03,  1.30799748e-02,
       -3.54272239e-02, -5.03342040e-03,  2.44650175e-03, -1.62810273e-02,
        2.59785354e-03, -7.39872921e-03, -2.13236734e-02,  1.62101742e-02,
        2.27846634e-02,  7.20157474e-03,  9.86894965e-03, -1.50003918e-02,
       -4.09392966e-03, -1.04089333e-02, -2.13543512e-02, -3.73758702e-03,
       -1.38696684e-02, -3.34787110e-05, -8.87693744e-03,  1.54442200e-03,
       -1.07058836e-02, -1.28836948e-02, -7.03393621e-03,  4.61831776e-04,
       -4.40991996e-03, -7.57934805e-03,  3.11908149e-03, -9.46805906e-03,
       -1.45561146e-02,  2.83470731e-02,  1.65506843e-02, -2.89983186e-03,
       -2.24363152e-02, -6.21192483e-03,  1.50013072e-02,  1.00834970e-03,
       -1.11877406e-02, -2.69118082e-02, -4.80512477e-04, -9.94556956e-03,
       -6.47446560e-03, -1.04876859e-02,  8.93547479e-03,  1.04280189e-02,
       -3.69262719e-03,  1.34739419e-03,  9.80064925e-03, -5.59290359e-03,
       -2.88650556e-03, -1.70743056e-02,  8.88171344e-05, -2.62671486e-02,
        1.17148599e-03, -6.77266950e-03, -8.87617655e-03, -8.54467507e-03,
       -5.05533768e-03, -6.42881542e-03, -7.04137376e-03,  1.56997200e-02,
       -1.26370694e-02,  6.30945852e-03,  2.71330215e-03, -7.85982609e-03,
       -2.93374248e-03, -1.47839054e-03, -6.19428931e-03, -1.24107879e-02,
       -5.60033321e-03, -2.18722969e-03,  1.26439845e-02,  1.39007391e-02,
        8.33588187e-03, -8.00593104e-03,  5.87603543e-03, -2.60686432e-03,
        1.00237494e-02, -1.85187291e-02,  1.78639684e-02, -1.99707993e-03,
       -5.79189695e-03, -7.07955891e-03, -4.47306177e-03,  4.02949098e-03,
       -6.39677839e-03,  2.36083679e-02,  1.32312756e-02, -3.19418758e-02,
        9.27805342e-03, -2.97335722e-03, -3.60018536e-02,  1.36123002e-02,
       -5.89378970e-03,  1.32933063e-02,  2.26078718e-03,  2.88055069e-03,
        1.64356977e-02,  2.94331810e-03,  5.14540821e-03,  2.58589745e-04,
       -4.76459600e-03, -4.25469549e-03,  1.46869533e-02, -4.22584498e-03,
       -2.70288961e-04, -8.46042484e-03, -1.68151427e-02, -9.78826452e-03,
       -3.16007137e-02, -9.14124586e-03, -9.95841809e-03, -2.87901028e-03,
       -1.87380277e-02, -1.69417504e-02, -1.63768642e-02, -5.03477594e-03,
       -7.55670434e-03,  1.89896254e-03, -3.86131788e-03, -1.69493034e-02,
       -5.74788311e-03, -8.70214403e-03,  5.08344313e-03, -1.74361444e-03,
       -1.61190089e-02, -7.76953949e-03, -4.19942720e-04, -1.28395008e-02,
       -2.73963548e-02,  4.83406149e-03, -2.82021575e-02, -1.15333851e-02,
       -2.32545510e-02, -3.23445973e-04, -1.05327647e-02, -5.77379717e-03,
        7.52524892e-03,  2.33972929e-02, -5.74236270e-03,  4.12526680e-03,
        1.58146303e-02, -4.38821549e-03, -1.55145386e-02, -9.36184358e-03,
       -2.18362063e-02, -3.61966947e-03, -2.03587692e-02, -3.32274139e-02,
       -2.21883394e-02, -5.91342524e-03,  3.26399952e-02, -2.35552271e-03,
       -1.20552527e-02, -1.16144316e-02,  5.53505030e-03,  1.06955478e-02,
       -9.14398488e-03,  1.94933568e-03,  1.05058551e-02,  1.45358713e-02,
       -4.40763310e-03, -5.71356807e-03, -1.22771850e-02,  5.86280460e-03,
       -1.19985929e-02, -1.16732763e-02, -8.29073042e-03, -1.13329301e-02,
       -2.49178801e-03,  4.31310292e-03, -9.56359226e-03,  9.18649696e-03,
       -1.11985598e-02,  2.29983634e-04, -2.19616879e-04,  1.56929262e-03,
       -1.07241282e-02, -2.48923264e-02, -6.27550529e-03, -9.46026109e-03,
        4.52898722e-03, -3.67242023e-02,  1.59049407e-02, -2.61061080e-03,
       -6.42187521e-03, -1.76793651e-03, -1.50873121e-02, -1.29018323e-02,
       -2.21628733e-02,  3.52725503e-03, -1.58320391e-03, -1.99661162e-02,
        3.55323311e-03,  2.23085401e-03, -8.92084464e-03, -5.98568062e-04,
       -1.69322565e-02, -1.16861910e-02, -3.26638645e-03, -5.46824187e-03,
       -7.79824378e-03, -1.77410984e-04, -4.01543081e-03,  1.77882351e-02,
       -8.61947890e-03, -2.38695014e-02,  8.88451189e-03, -9.08271130e-03,
        6.07182505e-03, -2.07706098e-03,  4.22798982e-03, -6.95160404e-03,
        2.61417311e-03,  2.84513785e-03, -1.55539615e-02, -1.24971392e-02,
       -9.04759858e-03, -2.70402767e-02,  3.42121185e-03, -1.13342023e-02,
       -1.73784215e-02, -7.04474561e-03,  1.42012956e-02, -5.67440782e-03,
        2.47098133e-03, -1.68142479e-03, -3.39869340e-03,  1.82528216e-02,
       -6.29369775e-03, -9.51803476e-03,  1.22533292e-02, -3.97896068e-03,
       -4.42211609e-03, -1.23782661e-02, -9.18647740e-03, -4.60855896e-03,
       -4.35359689e-04, -8.36107787e-03, -9.08772461e-03, -3.79282719e-04,
       -1.20880296e-02, -9.55888908e-03, -1.52191175e-02,  1.60630327e-03,
        7.23720435e-03, -1.24929836e-02,  1.19766695e-02, -2.86251213e-03,
        1.64658632e-02, -2.55577397e-02, -3.83467367e-03, -5.95677237e-04,
       -2.13252734e-02, -8.59156810e-03,  6.21420378e-03,  2.67833215e-03,
        6.18729880e-03, -1.99940475e-03, -2.46623904e-03, -3.85378138e-03,
       -9.61813144e-03, -3.28766182e-02, -8.62683170e-03, -6.81583816e-03,
       -3.11163478e-02,  6.91425055e-03, -1.45854009e-02, -1.19751124e-02,
       -6.56579901e-03, -4.26790677e-03, -3.86589603e-03, -1.96202192e-03,
       -2.74855783e-03,  2.22445291e-04, -8.59546475e-03, -5.05364221e-03,
        7.68624479e-03, -1.09069496e-02,  4.82467498e-04, -2.44879052e-02,
       -8.35702941e-03, -1.77347399e-02, -2.29716487e-02,  1.70294626e-03,
       -6.41561579e-03, -9.27226432e-03,  8.37765913e-03, -2.12470647e-02,
       -2.01549917e-03, -5.57177421e-03,  8.58933851e-03,  3.55439819e-03,
        8.79734755e-03, -6.09070435e-02, -9.72244702e-03, -4.29544039e-03,
       -2.37352541e-03, -4.23484854e-02, -9.95672494e-03,  4.57857409e-03,
       -6.29590172e-03, -2.29141340e-02, -2.02209670e-02, -5.02039073e-03,
       -1.88116804e-02, -2.04087216e-02,  6.61862176e-03, -8.02531093e-03,
       -3.84455174e-03,  7.61843938e-03, -3.36629478e-03, -8.89446819e-04,
        1.98600665e-02, -2.66891085e-02, -3.04136518e-02, -1.25233363e-02,
        1.90139748e-03, -5.69440797e-03,  8.78601056e-03, -1.41654315e-03,
       -6.80819433e-03,  1.06745660e-02, -5.59271965e-03,  2.61945534e-03,
       -1.27352793e-02, -1.19439512e-02,  1.96953813e-04, -1.63293276e-02,
       -1.20019112e-02, -5.07074350e-04, -7.21662818e-03, -1.09268259e-02,
        3.66798183e-03, -4.43264879e-02,  8.31734296e-03,  1.11346161e-02,
       -6.04608329e-03, -8.60767253e-03,  2.10283659e-02, -4.29894663e-02,
       -1.10942544e-02, -2.69948435e-03, -1.68176722e-02, -9.73410998e-03,
       -5.10925287e-03, -1.50374277e-02,  4.21269424e-03, -5.80801861e-03,
        4.44454188e-03,  6.01515546e-03, -6.81183999e-03, -2.36372910e-02,
        2.98860599e-03, -1.05839670e-02, -3.06248874e-03, -2.35131267e-03,
       -5.09649795e-03, -1.52832288e-02,  1.82719696e-02, -7.76382256e-03,
        1.13557111e-02, -2.35450733e-03,  6.48847362e-03,  1.11674878e-03,
       -7.67853204e-03, -1.09501155e-02,  1.42344623e-03, -3.23201064e-03,
        7.69374752e-03, -4.44622664e-03, -1.66583639e-02,  3.96335777e-03,
        4.34420770e-03, -1.13778347e-02, -5.44794789e-03, -8.85339361e-03,
       -1.85320079e-02, -5.26578585e-03, -2.61201896e-02, -1.41024133e-02,
       -2.74366438e-02, -6.23362744e-03, -7.40025192e-03, -1.27974385e-02,
       -8.19749944e-03, -3.13511826e-02,  1.24740861e-02, -4.87835566e-03,
       -5.66190593e-02, -6.53274124e-03, -2.86077475e-03, -2.48265117e-02,
       -8.73242412e-03, -4.10987670e-03,  1.54434219e-02,  1.53423194e-02,
       -1.55798448e-02,  3.23168491e-03, -4.11974918e-03, -1.08021954e-02,
       -4.19107312e-03, -7.61932507e-03, -2.25072615e-02, -1.60984285e-02,
        7.53243687e-03,  2.68635602e-04,  7.58085400e-04,  1.27045838e-02,
       -3.00969719e-03,  9.40314960e-03, -1.00517897e-02, -6.70638867e-03,
       -2.50801034e-02,  1.14480546e-02, -9.44947824e-03, -1.35662286e-02,
       -5.52057475e-03,  1.00084385e-02, -3.03325057e-03, -4.18505073e-03,
       -1.02853170e-02, -5.51922992e-03, -1.17231552e-02, -1.76058449e-02,
       -7.41541944e-03, -3.75579880e-03, -5.99238556e-03,  2.20179372e-03,
       -1.82953645e-02, -5.23288269e-03, -7.20096100e-03, -4.58277157e-03,
       -1.97463925e-03, -3.59843224e-02, -8.90510622e-03,  1.26234337e-03,
        8.68534483e-03, -1.01909870e-02, -8.83424561e-03, -1.89707205e-02,
       -6.06581196e-03,  6.37766020e-03, -1.54041511e-03, -1.26772737e-02,
       -1.22799948e-02,  4.06474108e-03,  4.75470573e-02, -1.41690075e-02,
       -5.65478299e-03, -4.74184658e-03, -1.02356244e-02, -6.78268308e-03,
       -4.11198363e-02, -5.20429900e-03, -6.31282944e-03, -1.48232337e-02,
        7.94391427e-03,  1.91413146e-02,  8.77620652e-03, -1.39870970e-02,
       -1.97347775e-02,  4.06674258e-02,  4.10678703e-03, -1.27380211e-02,
       -1.14872884e-02,  1.78408285e-04,  1.85933488e-03, -1.29867969e-02,
       -9.36406478e-03, -6.53963210e-03, -2.91691273e-02, -5.77345816e-03,
       -5.65227494e-03,  1.30221825e-02,  1.12562848e-03,  1.15022687e-02,
        2.69628991e-03, -6.25397405e-03,  1.51145346e-02, -6.34854892e-03,
       -1.21873589e-02, -5.00609633e-03, -1.87884122e-02, -2.18095500e-02,
       -1.07771130e-02, -1.79026183e-03, -8.57076049e-03, -1.68805644e-02,
        8.32588691e-03, -3.11950105e-03, -1.95926637e-03, -1.95698328e-02,
       -1.87040754e-02, -7.94581603e-03, -1.15807336e-02, -2.93202698e-03,
        9.31394170e-04, -1.02887945e-02, -4.89852484e-03, -2.88834348e-02,
       -1.70219154e-03, -1.28068682e-02,  1.20070418e-02, -6.23571919e-03,
        1.53069419e-03,  7.84052629e-03,  1.18460483e-03, -6.30661985e-03,
        2.18244791e-02, -2.05611046e-02,  7.07337167e-03, -4.72142186e-04,
       -5.40887145e-03, -1.50431944e-02, -1.13929063e-02,  3.75991175e-03,
       -1.89323407e-02, -3.68485460e-03, -1.35246548e-04, -4.93014380e-02,
        5.43151144e-03,  8.75360798e-03,  1.07058196e-03, -1.00368299e-02,
       -9.48652998e-03,  1.01578971e-02,  8.18942767e-03, -1.97076413e-04,
       -8.85789574e-04, -1.25869038e-02, -1.69044230e-02,  8.52148701e-03,
       -3.55861033e-03, -5.57425758e-03,  2.25873082e-03, -2.94936844e-03,
       -2.03853520e-03, -2.49050763e-02, -8.08870129e-04, -6.78975601e-03,
       -2.26835385e-02, -1.08510079e-02, -6.47677248e-03, -1.30843930e-02,
        2.11649900e-03, -2.46939287e-02, -1.29941236e-02,  2.06926875e-02,
       -7.12853856e-03, -3.41516716e-06, -1.03834774e-02, -1.49300124e-03,
       -1.45415626e-02, -6.73840754e-03, -3.30269220e-04, -5.04382839e-03,
        5.77469356e-03, -1.67646222e-02, -9.95074213e-03, -1.17009664e-02,
       -3.16283703e-02,  9.37802903e-03, -1.47668151e-02, -9.25119407e-03,
        1.78189226e-03, -4.69401851e-03, -4.69214469e-02, -1.05048725e-02,
       -1.01294313e-02,  4.71223518e-03,  3.63679556e-03, -2.28322037e-02,
        3.31711536e-03, -1.95346540e-03,  4.48187202e-05, -2.12450381e-02,
        7.03919586e-03, -1.43555580e-02, -4.33863461e-04,  1.06861787e-02,
       -1.16127376e-02, -8.61069560e-03, -1.94975547e-02, -2.22192034e-02,
       -1.83905307e-02,  1.33638047e-02, -4.74453205e-03, -1.18603986e-02,
        3.87834944e-02, -2.16149166e-03, -7.36467366e-04, -4.00368497e-03,
        2.53888406e-03, -1.43811498e-02, -1.33104017e-03, -1.09425606e-02,
        3.00907041e-03, -7.71075534e-03,  8.99710227e-03,  6.31363364e-03,
       -7.58418487e-03, -3.02429684e-02, -9.46294051e-03,  3.73999681e-03],
      dtype=float32), array([-0.00250695, -0.03247833, -0.02217387,  0.02348665,  0.0047669 ,
        0.00341307, -0.04615863, -0.0261693 , -0.01271311, -0.00965342,
       -0.00898484,  0.03289299, -0.03354069, -0.00708472,  0.00644233,
       -0.04480459, -0.02980788, -0.02865181,  0.04306722, -0.00246032,
       -0.00858415, -0.00563604,  0.0040095 ,  0.01120519,  0.02000202,
       -0.01056743,  0.06137899, -0.00937823,  0.02610401,  0.01412062,
        0.00529644, -0.01515303, -0.04019322,  0.0011711 , -0.0340332 ,
        0.02847598, -0.04309107,  0.02086326,  0.03572891, -0.01476303,
       -0.01392416,  0.03377919,  0.01804538, -0.00950146,  0.09332557,
       -0.01174129,  0.02908394, -0.00181371, -0.02408829,  0.02700978,
        0.00515622, -0.01032313, -0.00506374,  0.03648479, -0.05342896,
       -0.02214602,  0.05566701,  0.04681059, -0.01440901,  0.08088075,
       -0.04446704,  0.02951972,  0.00314037, -0.03286429,  0.01926525,
        0.06527734,  0.02234138, -0.03550079, -0.03023021,  0.02061946,
        0.00852943,  0.0092114 , -0.00794223,  0.00439523, -0.02069227,
       -0.02196036, -0.01324567,  0.01410365,  0.02788182,  0.0275711 ,
       -0.05100278,  0.06696984, -0.01171457, -0.03713903, -0.03403757,
       -0.0173623 , -0.04784364, -0.00808516,  0.00725356, -0.01069895,
       -0.01256786,  0.02495956, -0.02456119, -0.00633099, -0.01983876,
       -0.01274712, -0.03185442,  0.01798454, -0.01148707, -0.02545785,
       -0.00989971,  0.01621464,  0.03158854,  0.03480962,  0.01874387,
       -0.02508359,  0.0103835 , -0.01888407,  0.01856257,  0.05720876,
       -0.01004008,  0.04884963,  0.01412842,  0.03268211,  0.04825153,
       -0.04402735,  0.0193559 , -0.03021376, -0.01323367, -0.0234258 ,
       -0.00193037, -0.05020498, -0.02512139, -0.0400597 ,  0.05150587,
       -0.00386082, -0.03831741, -0.00427916,  0.00358911,  0.05333008,
        0.02571702, -0.02755195, -0.0368859 , -0.00161417,  0.00575477,
       -0.01477965,  0.02924206,  0.00735272,  0.01789094, -0.00318836,
        0.00388013, -0.03277806,  0.02323345, -0.02800426,  0.03304616,
       -0.01762899, -0.01420217, -0.01663088,  0.01339247,  0.00752377,
       -0.00800894,  0.04523128,  0.02681596, -0.01977049,  0.00826078,
       -0.05302707, -0.03282822, -0.01502565, -0.02813418,  0.01303647,
        0.02082168,  0.06329828,  0.00695641, -0.00502979,  0.02122844,
        0.07273297,  0.0013822 , -0.04002254, -0.00444077, -0.04810519,
       -0.05326993, -0.00047631,  0.01320188,  0.01779589, -0.02010083,
        0.07765026, -0.00249437,  0.03036854,  0.01364507, -0.01669749,
        0.00218787,  0.03539488, -0.02387629, -0.03413052,  0.02605933,
        0.01023618, -0.01864461,  0.04292424, -0.02737144, -0.03610099,
        0.02534309, -0.01985482,  0.01796165, -0.02090578, -0.04989336,
       -0.04258021, -0.03324617, -0.04234815, -0.04296334, -0.01654248,
       -0.04044251,  0.01556373, -0.02611316, -0.01703407,  0.03227187,
       -0.06301594,  0.00363883,  0.01707456,  0.01098577, -0.05030354,
       -0.06047607,  0.06907373, -0.05065427,  0.04568687,  0.06647969,
       -0.05045564,  0.0021653 , -0.04856484, -0.01635989,  0.00207534,
       -0.01149457,  0.00125158, -0.04917762, -0.03279442, -0.05698692,
       -0.00919033,  0.00350727,  0.00374693,  0.03508686, -0.01848039,
        0.03056064,  0.04138131,  0.07058291,  0.03379334, -0.02882895,
       -0.04528461,  0.02091858,  0.01991803,  0.03839486,  0.00566498,
       -0.00261028, -0.01633906,  0.02702861,  0.00834001, -0.00680446,
       -0.0050573 , -0.01438225, -0.03529903,  0.05190625,  0.01961848,
        0.01389592,  0.00154333,  0.05550065, -0.03668116,  0.0627911 ,
        0.03450715,  0.02771281,  0.02882075,  0.01748052, -0.07822713,
       -0.02044188, -0.04017647,  0.030166  , -0.01885798, -0.05466548,
       -0.02880481,  0.03847099, -0.0088038 ,  0.05474231,  0.01737645,
       -0.01162186,  0.04998446,  0.03061517,  0.02652311, -0.01158257,
        0.0369136 ,  0.04424245,  0.00546628, -0.06549254, -0.01798353,
        0.01885224,  0.00508382, -0.03574681, -0.0407585 ,  0.01216687,
       -0.0061861 , -0.02355337,  0.00695503,  0.02995829,  0.02936869,
        0.02970011, -0.03324032,  0.00257321, -0.00506829, -0.0282372 ,
       -0.03315718, -0.01695688, -0.0146026 , -0.0222255 , -0.00254467,
        0.02074032,  0.03150404,  0.03570408,  0.03831362,  0.02096131,
        0.0703886 , -0.01828607, -0.03935675,  0.0175678 ,  0.00179259,
        0.03363184, -0.02946254,  0.071101  , -0.04312144, -0.00530659,
        0.00532759,  0.00049557,  0.00982929, -0.03584953,  0.0245695 ,
       -0.00232214, -0.02236486, -0.04633297, -0.00688794,  0.03036885,
       -0.01314035, -0.00426663, -0.06668576, -0.01935821,  0.06240081,
       -0.01790763,  0.00587198, -0.04331594, -0.03536967, -0.03687732,
        0.03542883, -0.01513103, -0.01535952, -0.02110425,  0.05460017,
        0.00011519,  0.05517127,  0.02607154, -0.05146089,  0.05720755,
       -0.01657874, -0.05621656, -0.02975316, -0.02865661, -0.0066402 ,
        0.01774836, -0.02993312,  0.01879968, -0.00254693,  0.01521698,
       -0.05769663, -0.03786562, -0.03569844,  0.01477485, -0.02979118,
        0.00563948,  0.00762561, -0.01710326, -0.05362379, -0.04108965,
        0.02475545,  0.03014684, -0.0093747 , -0.04053647, -0.04181867,
       -0.03710103, -0.02399367,  0.00202586,  0.06253841, -0.00629431,
       -0.02493261,  0.01931452,  0.04584128, -0.00723317, -0.01208977,
        0.00743242,  0.00488952,  0.01128414,  0.02145634, -0.0012534 ,
        0.05263745, -0.02474937, -0.02595831,  0.03071445,  0.00416733,
        0.03453534,  0.01569359, -0.04465061, -0.00445183, -0.01200502,
       -0.0078708 , -0.0200791 , -0.03528209,  0.01802088,  0.01018191,
        0.02101385, -0.03553744,  0.00442977, -0.03953739, -0.04909356,
        0.03324331,  0.03323022, -0.04149685,  0.01546311, -0.01975894,
       -0.03543679,  0.02834625,  0.00636504, -0.00799781, -0.0081752 ,
       -0.03157125, -0.02712741,  0.04260909, -0.0184241 ,  0.00368554,
        0.01628582,  0.0643317 ,  0.02233414, -0.01920049, -0.01976068,
        0.09506851,  0.06523499, -0.0165007 , -0.0281106 ,  0.01941495,
       -0.05338316,  0.02302882,  0.05929588, -0.00810491, -0.00694221,
        0.0044795 , -0.02245798,  0.05965145,  0.00762043,  0.04536125,
       -0.03358078,  0.00575667, -0.04877114, -0.03632237, -0.0225194 ,
        0.03721894,  0.00129868,  0.00567934, -0.02687946,  0.03456237,
       -0.05642769,  0.03903073,  0.02639052,  0.02547823,  0.02594836,
       -0.01624542,  0.00463184,  0.02950407,  0.01396103,  0.03783732,
       -0.00326575,  0.08663362, -0.00332814,  0.07885856,  0.01558301,
        0.01141022,  0.04506383, -0.00920973, -0.02857986,  0.02102928,
        0.05403024,  0.01141655, -0.01394175, -0.01010967, -0.01539267,
        0.04753759, -0.02187601,  0.06165216,  0.02382789, -0.02755907,
        0.01254854,  0.031641  , -0.03872206, -0.01506169, -0.02014276,
       -0.03735012, -0.02065949,  0.02357502, -0.04581676,  0.0648486 ,
       -0.04512554, -0.02055337, -0.02396588, -0.01235715, -0.03395955,
       -0.03272843,  0.00507628,  0.01364787,  0.03127148, -0.04605494,
        0.05416346, -0.01051158,  0.05709809,  0.02484622,  0.0242871 ,
       -0.00180939, -0.01069254,  0.00493609, -0.02501842,  0.03688207,
       -0.00827001, -0.0308547 ,  0.07038768, -0.02191779, -0.01285225,
       -0.01997931,  0.00580163, -0.02384903, -0.02812794, -0.03506573,
        0.01724248, -0.04966773,  0.00325037,  0.03903692, -0.03001044,
        0.01481258,  0.04057728,  0.04436836,  0.02900549,  0.0295932 ,
       -0.04192819, -0.04352251, -0.00637284,  0.02297298, -0.03560346,
        0.02229893,  0.0147866 , -0.04241996,  0.00647928,  0.0091727 ,
       -0.01827468,  0.02693573, -0.00729995, -0.05150532,  0.00787297,
        0.02143796, -0.0030608 ,  0.02273555,  0.01296624, -0.00339011,
        0.0326085 , -0.00551906, -0.04680852,  0.02196799, -0.02553711,
       -0.00399989,  0.00263809,  0.04931194,  0.04175042, -0.03354695,
       -0.00891462,  0.0167917 , -0.02724331, -0.0564564 ,  0.01206663,
       -0.04736387, -0.00683196, -0.02432339,  0.03083011, -0.02659412,
       -0.04872571, -0.00881685, -0.00666116, -0.02128756,  0.02346671,
       -0.02215759,  0.06787425, -0.02336324, -0.00372437,  0.02851168,
        0.01284068, -0.04013535, -0.00494354, -0.00263297,  0.03185974,
        0.00767091, -0.01417676,  0.03539754,  0.0322099 ,  0.01439339,
        0.01487388,  0.03664478,  0.0285071 ,  0.05958582,  0.05829385,
        0.00256084, -0.05153237, -0.0295432 , -0.04279847, -0.03612543,
       -0.02008121,  0.02821828, -0.05946786, -0.00869653,  0.07092009,
       -0.00209108,  0.05448276, -0.01599267, -0.02633114,  0.04119002,
        0.02746817,  0.01894147,  0.00373486,  0.02381431,  0.00652677,
        0.02123169,  0.04114309, -0.00076391,  0.0517141 ,  0.05642569,
       -0.02444249,  0.01683315, -0.01441138,  0.08749455,  0.02556128,
        0.00453774, -0.04298143, -0.00776459, -0.01916425, -0.01698198,
        0.01753274,  0.01296615, -0.05830463,  0.07763293, -0.00729631,
       -0.02582446,  0.02171239,  0.03204841,  0.01193437, -0.05782541,
        0.02021226,  0.02009767, -0.01994226,  0.06307607, -0.0246686 ,
       -0.03356369,  0.02283469, -0.05162908,  0.04750729, -0.03927249,
       -0.00787988, -0.01955981,  0.01100296, -0.02501083,  0.05293261,
       -0.03028235, -0.01956533,  0.0415258 , -0.01382255,  0.0460113 ,
       -0.01704212,  0.05899566,  0.04681505,  0.03043673,  0.02726728,
        0.02230407, -0.00739576,  0.05007622,  0.00919546,  0.03294949,
       -0.01715541, -0.01981585, -0.01963359,  0.00845991, -0.016246  ,
        0.00029895,  0.06746196, -0.04246763, -0.03685001,  0.03490074,
       -0.00431197,  0.03450909,  0.02312877,  0.04376917,  0.06226921,
       -0.04128126, -0.04381856, -0.03912851,  0.0038186 ,  0.01772959,
        0.05011072,  0.01725405,  0.03398079, -0.00661714, -0.03991856,
        0.02787198,  0.01353411, -0.00706132,  0.05622521,  0.01300308,
       -0.04413667, -0.01024631,  0.00787364, -0.04410942,  0.02460747,
       -0.02825372,  0.0559167 ,  0.01746259,  0.03835283, -0.02391873,
        0.03793468, -0.00770139, -0.03006068, -0.03672612, -0.03760777,
        0.00456153, -0.00225526,  0.06293778,  0.0142607 ,  0.04589367,
       -0.00854212, -0.04283992, -0.05639446, -0.05782337, -0.00628647,
       -0.01222836,  0.02108711,  0.04128927], dtype=float32), array([0.08551696, 0.09818551, 0.08919756, 0.09269023, 0.08465382,
       0.10448866, 0.10320956, 0.08662722, 0.09620637, 0.08677718,
       0.0835389 , 0.10566638, 0.08735213, 0.08195361, 0.09160678,
       0.09017112, 0.08817272, 0.08708046, 0.09213937, 0.0956281 ,
       0.08221874, 0.08254151, 0.08850979, 0.08682672, 0.08460651,
       0.08194645, 0.10360219, 0.094281  , 0.08916692, 0.08273287,
       0.08810055, 0.08512913, 0.0950358 , 0.08856913, 0.08940481,
       0.09413523, 0.08429319, 0.08371032, 0.09265658, 0.09715103,
       0.08218754, 0.09208792, 0.09412821, 0.10382044, 0.12191688,
       0.09301145, 0.09165911, 0.10043871, 0.08710272, 0.09239179,
       0.08240197, 0.09575104, 0.08359256, 0.10222621, 0.10036935,
       0.0901344 , 0.09259187, 0.11271664, 0.08529472, 0.12379631,
       0.09940878, 0.13240442, 0.08641102, 0.1048748 , 0.08399062,
       0.11568237, 0.08645999, 0.09079101, 0.08404515, 0.0840872 ,
       0.09180009, 0.08458479, 0.08322849, 0.08386268, 0.08413266,
       0.11469183, 0.09415416, 0.09145557, 0.08596426, 0.08477686,
       0.09234153, 0.13743153, 0.08615376, 0.08616308, 0.08925727,
       0.08543985, 0.0885912 , 0.08463733, 0.08252353, 0.09956273,
       0.0848119 , 0.08319741, 0.08873558, 0.08298341, 0.08952862,
       0.09195727, 0.08494583, 0.08531514, 0.0985618 , 0.0896612 ,
       0.08526581, 0.08494343, 0.10091136, 0.09065693, 0.08326406,
       0.10630866, 0.08196865, 0.08718212, 0.09194224, 0.0929109 ,
       0.08842455, 0.09781943, 0.0833352 , 0.0977484 , 0.087152  ,
       0.09185261, 0.08661501, 0.11184585, 0.08529599, 0.09347619,
       0.08742482, 0.11174875, 0.0856334 , 0.09344774, 0.1130849 ,
       0.08706079, 0.09323873, 0.11661869, 0.09153189, 0.08954599,
       0.08792081, 0.08810327, 0.14197035, 0.08330977, 0.08692751,
       0.09759013, 0.09845865, 0.0859274 , 0.08965505, 0.09772225,
       0.08680344, 0.08954813, 0.08506598, 0.08868199, 0.09654973,
       0.09579322, 0.08440045, 0.08414458, 0.08322465, 0.08443931,
       0.08950834, 0.09440078, 0.09017584, 0.09599537, 0.09021637,
       0.10868424, 0.10323094, 0.08662249, 0.09533102, 0.09725232,
       0.0849941 , 0.10990665, 0.09010356, 0.0836726 , 0.09120458,
       0.10723975, 0.09222979, 0.09767716, 0.08588953, 0.09729902,
       0.09721076, 0.09348696, 0.08888157, 0.09007841, 0.08651362,
       0.11428734, 0.09565056, 0.08577499, 0.08798352, 0.0819461 ,
       0.12863089, 0.09947971, 0.08431461, 0.0928863 , 0.08465318,
       0.0898664 , 0.09593267, 0.08882666, 0.09505265, 0.08518926,
       0.08565193, 0.09976806, 0.1068498 , 0.08640158, 0.11195186,
       0.08824193, 0.10333281, 0.10248419, 0.09435725, 0.08765114,
       0.08540688, 0.09544597, 0.08834967, 0.10434944, 0.09077765,
       0.08958602, 0.0835347 , 0.09376757, 0.08258966, 0.11258568,
       0.10213967, 0.11806995, 0.09839575, 0.09357093, 0.11885566,
       0.09980938, 0.08248834, 0.08907446, 0.08631894, 0.0892758 ,
       0.08674422, 0.08418092, 0.08849549, 0.09190211, 0.08874524,
       0.09545477, 0.08533634, 0.08498291, 0.09542075, 0.08779098,
       0.09010943, 0.08614549, 0.09961662, 0.08555248, 0.09486104,
       0.09992549, 0.09253722, 0.08817371, 0.09546327, 0.08504806,
       0.0819249 , 0.08529954, 0.086823  , 0.09156394, 0.09500433,
       0.10702737, 0.08811776, 0.0964092 , 0.09948807, 0.0825332 ,
       0.09374672, 0.08450232, 0.10984512, 0.08827361, 0.10525118,
       0.08649079, 0.08632538, 0.08634287, 0.09933903, 0.10028117,
       0.09005176, 0.08954258, 0.08821595, 0.09017321, 0.10690501,
       0.08692212, 0.1012481 , 0.08620697, 0.09782666, 0.09734301,
       0.10538394, 0.11067598, 0.09526909, 0.08634414, 0.0870788 ,
       0.08898475, 0.09189461, 0.08422253, 0.10026875, 0.08481968,
       0.08706249, 0.08526557, 0.09515972, 0.09126097, 0.09427429,
       0.08520997, 0.09527279, 0.08211263, 0.09179766, 0.08509098,
       0.0838193 , 0.08754469, 0.09204932, 0.08217639, 0.08559139,
       0.09877603, 0.1016675 , 0.09586106, 0.09103941, 0.08499557,
       0.10314725, 0.08873739, 0.08857254, 0.0968767 , 0.0876066 ,
       0.10778921, 0.09888579, 0.08345453, 0.09138242, 0.09078494,
       0.09134451, 0.08423704, 0.1324885 , 0.08595066, 0.08725578,
       0.09262624, 0.08826844, 0.08845551, 0.09291515, 0.08781125,
       0.09156067, 0.08523189, 0.08799011, 0.08235417, 0.09195339,
       0.09603166, 0.08633106, 0.09472857, 0.1045621 , 0.11301874,
       0.09330504, 0.08509198, 0.09213307, 0.08608975, 0.09793307,
       0.0861193 , 0.09438129, 0.08325571, 0.08736502, 0.09920373,
       0.09340079, 0.09624115, 0.09906912, 0.08717734, 0.11256807,
       0.09008984, 0.10782667, 0.08660012, 0.08572382, 0.08750673,
       0.08993487, 0.09178249, 0.08637378, 0.09237035, 0.0892841 ,
       0.0998963 , 0.10403432, 0.08753292, 0.08524381, 0.08685725,
       0.0835868 , 0.09907635, 0.08471791, 0.09681194, 0.09130498,
       0.09182669, 0.0967989 , 0.0995781 , 0.09051647, 0.11320639,
       0.0891303 , 0.08882757, 0.09031994, 0.09603346, 0.08354068,
       0.09074912, 0.10101766, 0.0838834 , 0.09933505, 0.08541252,
       0.08348268, 0.08303867, 0.08330098, 0.09299748, 0.08485167,
       0.09069118, 0.08642642, 0.08578318, 0.0935458 , 0.10137469,
       0.0957311 , 0.09488168, 0.09579264, 0.08350234, 0.08548448,
       0.08602348, 0.08478763, 0.08878916, 0.08569326, 0.0870517 ,
       0.09493332, 0.0976209 , 0.0892208 , 0.11428708, 0.1061272 ,
       0.09009283, 0.09144817, 0.09434143, 0.0955514 , 0.08670065,
       0.09117343, 0.10122626, 0.09297066, 0.08659875, 0.08760829,
       0.09092192, 0.08860632, 0.10149156, 0.08946034, 0.08353481,
       0.08531576, 0.10429727, 0.08857194, 0.08809777, 0.08483436,
       0.14772601, 0.10110819, 0.08643628, 0.09119985, 0.08684248,
       0.08661346, 0.09053503, 0.09734533, 0.09050643, 0.09370896,
       0.09126665, 0.0910973 , 0.12158975, 0.09259201, 0.09497829,
       0.08434483, 0.08748827, 0.09051852, 0.08627888, 0.08865304,
       0.09439775, 0.08346314, 0.0862525 , 0.11586706, 0.09258574,
       0.09521902, 0.0963626 , 0.09531297, 0.08613085, 0.08953993,
       0.09139583, 0.08296713, 0.10943863, 0.08591671, 0.10056014,
       0.08392183, 0.12013898, 0.09265064, 0.12100352, 0.09735205,
       0.09386782, 0.11459123, 0.09205204, 0.09207682, 0.08820684,
       0.13010675, 0.08194965, 0.0953491 , 0.0845982 , 0.08724844,
       0.11183855, 0.08933624, 0.08800876, 0.08584808, 0.08653439,
       0.086961  , 0.08779919, 0.09866105, 0.08409721, 0.09060559,
       0.09168209, 0.10778112, 0.08728082, 0.09307535, 0.09940497,
       0.10085993, 0.08823497, 0.08459073, 0.09397782, 0.10425504,
       0.1087456 , 0.08488505, 0.08617032, 0.09492151, 0.11244321,
       0.08618914, 0.10054321, 0.10443683, 0.09323207, 0.09328894,
       0.0845952 , 0.08361686, 0.08419553, 0.0880091 , 0.11356284,
       0.08688882, 0.10647432, 0.11193185, 0.09399649, 0.08310848,
       0.09737452, 0.09065826, 0.08231772, 0.09347779, 0.10494544,
       0.09672093, 0.10047743, 0.09996776, 0.08967321, 0.0844297 ,
       0.08580093, 0.09301559, 0.08655055, 0.08749459, 0.09121635,
       0.09425032, 0.08621044, 0.08253238, 0.0995768 , 0.09371059,
       0.08599115, 0.08899017, 0.0976193 , 0.08426803, 0.08406451,
       0.08373596, 0.08766071, 0.08233782, 0.09373862, 0.08581425,
       0.08555787, 0.08446062, 0.11556638, 0.08329705, 0.0833011 ,
       0.09847027, 0.08318602, 0.08701097, 0.1280309 , 0.08210434,
       0.08497236, 0.08470834, 0.11028621, 0.09417026, 0.08679474,
       0.08454446, 0.08604115, 0.12192909, 0.11156046, 0.08371571,
       0.08977208, 0.08810034, 0.08785129, 0.09289686, 0.09897934,
       0.10282756, 0.09011787, 0.08355334, 0.08653943, 0.08689302,
       0.08541502, 0.1114057 , 0.09412908, 0.08309665, 0.0838792 ,
       0.08337218, 0.09566434, 0.0849153 , 0.09332985, 0.09237567,
       0.08853041, 0.09075725, 0.09641938, 0.08581486, 0.08597236,
       0.08266784, 0.09821402, 0.08555823, 0.1013176 , 0.10229999,
       0.09650198, 0.11802642, 0.08737832, 0.10455654, 0.0923401 ,
       0.0853567 , 0.0917675 , 0.10217194, 0.09120021, 0.13758959,
       0.08337908, 0.10318749, 0.09706847, 0.08232702, 0.08879846,
       0.09326084, 0.10154565, 0.09060147, 0.09068716, 0.08553779,
       0.10795705, 0.09911433, 0.08260176, 0.0900786 , 0.08996049,
       0.09654973, 0.08874465, 0.08831186, 0.11480992, 0.08783191,
       0.08988156, 0.09276312, 0.08431203, 0.08318697, 0.09815028,
       0.09889916, 0.08654267, 0.090555  , 0.1168118 , 0.08884396,
       0.11517475, 0.09551422, 0.09044635, 0.08957918, 0.10364362,
       0.09483991, 0.08640382, 0.0823868 , 0.12101675, 0.09390637,
       0.09252862, 0.0916505 , 0.09644801, 0.13829897, 0.08797746,
       0.0846269 , 0.08487372, 0.10375899, 0.0823554 , 0.10283099,
       0.085081  , 0.08789714, 0.09639782, 0.08555638, 0.0923427 ,
       0.08458175, 0.09477249, 0.09568448, 0.08628529, 0.09235555,
       0.08961596, 0.08502219, 0.09499753, 0.08444664, 0.09268358,
       0.10238951, 0.08562776, 0.09587815, 0.09471444, 0.08521749,
       0.08532816, 0.14112374, 0.09685304, 0.09178776, 0.08545013,
       0.0838514 , 0.09565284, 0.09048105, 0.09428991, 0.10058834,
       0.08897308, 0.0925254 , 0.09954628, 0.08254829, 0.08590497,
       0.10590923, 0.08793758, 0.09683254, 0.08628149, 0.08748148,
       0.09311864, 0.09061152, 0.08678581, 0.09214412, 0.08653363,
       0.09021264, 0.08374162, 0.09575497, 0.09151451, 0.08401112,
       0.08505983, 0.10452524, 0.08482475, 0.09608617, 0.11229067,
       0.08473284, 0.1060466 , 0.09861626, 0.08875521, 0.08876859,
       0.09250557, 0.09308866, 0.09915799, 0.08803654, 0.08858933,
       0.08862042, 0.10376044, 0.09998565, 0.09764068, 0.08679367,
       0.1019076 , 0.09031647, 0.08989064], dtype=float32), array([[[[-0.02449532],
         [ 0.01922023],
         [-0.02323675],
         ...,
         [-0.03081661],
         [ 0.03337869],
         [-0.01182551]],

        [[-0.00400127],
         [ 0.00243397],
         [-0.00599363],
         ...,
         [-0.02362115],
         [ 0.02914258],
         [ 0.03539859]],

        [[-0.00186325],
         [ 0.02127484],
         [-0.00259145],
         ...,
         [ 0.01149903],
         [-0.02337932],
         [ 0.00735003]]],


       [[[-0.02919305],
         [-0.00914871],
         [-0.01662201],
         ...,
         [-0.02768024],
         [ 0.01770152],
         [ 0.00971885]],

        [[ 0.0001592 ],
         [-0.02348473],
         [-0.02783287],
         ...,
         [-0.0298501 ],
         [ 0.0067304 ],
         [-0.00101246]],

        [[ 0.01592551],
         [-0.00262561],
         [-0.00144523],
         ...,
         [ 0.00946877],
         [-0.00746571],
         [ 0.03094157]]],


       [[[ 0.00497157],
         [-0.01788105],
         [ 0.00515939],
         ...,
         [ 0.01856349],
         [ 0.03159088],
         [ 0.03357521]],

        [[-0.01380038],
         [ 0.0117469 ],
         [ 0.00677128],
         ...,
         [ 0.02147032],
         [-0.00876207],
         [ 0.00074274]],

        [[ 0.01833875],
         [-0.00536836],
         [ 0.01135685],
         ...,
         [-0.02940871],
         [-0.01856073],
         [ 0.02321963]]]], dtype=float32), array([[[[ 0.0109308 ,  0.0058956 , -0.04521349, ...,  0.040454  ,
           0.00410111, -0.04378662],
         [ 0.01618311,  0.02690268, -0.00459503, ..., -0.06401026,
           0.00855674, -0.01669397],
         [ 0.03343324, -0.00416445, -0.0524589 , ..., -0.02805869,
          -0.05551488,  0.03078721],
         ...,
         [ 0.04292367,  0.04416046,  0.0542223 , ...,  0.05154648,
           0.04772818,  0.04349787],
         [-0.01217759,  0.06063055,  0.02652577, ..., -0.05078175,
           0.00714157,  0.01933009],
         [ 0.03387704, -0.03991716,  0.03849208, ..., -0.0360616 ,
           0.01678654, -0.0428537 ]]]], dtype=float32), array([0.9966396 , 1.005261  , 0.9848986 , 0.9979014 , 1.0157229 ,
       1.0059985 , 0.99924195, 1.0063698 , 1.0173982 , 0.994603  ,
       1.0071267 , 0.99997324, 0.9944174 , 1.0102271 , 0.99632293,
       1.0029093 , 0.99170434, 0.9912804 , 1.0174786 , 1.0175867 ,
       0.9975937 , 1.0170946 , 1.0143493 , 0.9939041 , 1.002722  ,
       1.0130275 , 0.9918731 , 0.9928912 , 0.9749354 , 1.0082182 ,
       1.0067574 , 0.9991613 , 1.0061646 , 0.99562275, 0.9958092 ,
       1.0167087 , 0.9841196 , 0.9994562 , 0.9913266 , 1.0030543 ,
       1.0074745 , 1.003748  , 1.0138707 , 0.9975681 , 1.0087847 ,
       1.0268523 , 0.9855961 , 0.99410665, 1.0278159 , 1.0097476 ,
       1.0043472 , 1.0109153 , 1.0054778 , 1.0087768 , 1.0129591 ,
       1.0083688 , 1.0069695 , 1.0134517 , 0.9980776 , 1.0097129 ,
       0.9994866 , 0.99820274, 1.0125668 , 1.0132415 , 0.99019355,
       1.0170844 , 1.0297284 , 1.0068638 , 1.0029856 , 0.99490404,
       0.9968899 , 0.9964114 , 0.99151045, 0.9869544 , 1.01379   ,
       1.017805  , 1.0123314 , 1.002904  , 0.99935955, 0.9914623 ,
       1.0201255 , 1.0033127 , 1.0077842 , 0.9923841 , 1.0038538 ,
       0.99020344, 1.006567  , 0.99710745, 1.0019983 , 0.9963684 ,
       1.0054827 , 0.9986758 , 1.011648  , 1.011312  , 1.0031793 ,
       1.0015717 , 1.0155389 , 0.98746186, 1.0053779 , 1.0251541 ,
       1.0184234 , 1.0033654 , 0.9900554 , 1.019632  , 0.9931052 ,
       0.99657434, 1.0107802 , 1.0114816 , 0.9738374 , 1.0045313 ,
       1.0206823 , 1.0333481 , 0.9886861 , 0.99100125, 1.0070238 ,
       1.0061399 , 1.0299768 , 0.9910372 , 1.0036769 , 1.000427  ,
       1.0113698 , 1.0103799 , 0.98375636, 1.0057106 , 1.0293052 ,
       0.98969704, 1.0019585 , 1.0193063 , 1.001662  , 1.0253392 ,
       0.9998096 , 1.0239234 , 1.0089904 , 0.9872746 , 0.9975211 ,
       0.9968085 , 1.0174233 , 1.0210176 , 1.0014687 , 1.0182997 ,
       1.0056163 , 0.99127007, 0.99121   , 1.0005567 , 1.0254189 ,
       1.0078764 , 0.9992898 , 0.99838614, 1.0272437 , 1.0066217 ,
       0.99546105, 0.9815043 , 0.9971824 , 1.0288236 , 1.0063447 ,
       1.0050691 , 1.0043118 , 0.9843922 , 1.0104071 , 1.0054406 ,
       0.9957264 , 0.99790365, 0.9979041 , 0.9956583 , 0.9966648 ,
       1.0305169 , 0.99459   , 1.0028331 , 0.9997491 , 1.0143409 ,
       1.0024532 , 1.0102447 , 1.0052695 , 1.0147909 , 1.0101837 ,
       1.0070354 , 0.99826914, 1.018618  , 1.0142336 , 0.991198  ,
       0.9986529 , 1.0257446 , 1.0111563 , 1.0063028 , 0.9987944 ,
       0.98776937, 1.0197595 , 1.026106  , 0.9913268 , 1.0106232 ,
       0.98659086, 1.0015205 , 1.0061737 , 0.9973261 , 1.0052885 ,
       1.0176121 , 1.0005486 , 1.0097594 , 0.98130465, 1.0089449 ,
       0.9999155 , 1.0001117 , 1.0292842 , 0.98855215, 1.0098605 ,
       0.99718714, 0.9991487 , 0.9974122 , 1.0121189 , 1.0106208 ,
       0.99139655, 0.99013585, 0.9950466 , 1.0036091 , 0.9989462 ,
       0.9891558 , 0.9887901 , 1.0010204 , 1.0077527 , 1.0106258 ,
       1.0080374 , 1.0215462 , 1.0120102 , 0.9983023 , 0.99802184,
       0.9990761 , 1.0069482 , 1.0230545 , 1.0164527 , 1.03509   ,
       0.99937385, 1.0063878 , 0.9925505 , 1.0208522 , 1.0162629 ,
       1.0119478 , 1.01181   , 1.0054808 , 1.0174162 , 0.9983971 ,
       0.9955514 , 1.0260941 , 0.9977355 , 1.014722  , 0.99620664,
       1.0105249 , 0.9997852 , 0.9971972 , 0.99516463, 1.0048184 ,
       1.0080659 , 0.99079597, 1.0104398 , 0.9933071 , 1.0378282 ,
       1.0029974 , 0.99973005, 1.004805  , 1.0105168 , 1.0088885 ,
       0.9845756 , 1.0178813 , 1.0068109 , 1.0261889 , 1.003549  ,
       1.0064732 , 1.0124438 , 1.0084902 , 1.0128387 , 0.9970483 ,
       1.0264189 , 1.0108804 , 0.9928    , 1.0058485 , 1.01349   ,
       1.0107459 , 1.002013  , 1.0272666 , 1.0060769 , 1.0238771 ,
       0.9976178 , 0.99531144, 1.0017924 , 0.99232686, 1.0109322 ,
       1.002531  , 0.9935626 , 1.0112875 , 1.0008147 , 1.0103316 ,
       0.99777997, 1.0040936 , 0.9922286 , 1.0225223 , 1.0034354 ,
       0.98177415, 1.0118489 , 1.0272613 , 1.0008625 , 1.0039893 ,
       1.0086641 , 0.99753493, 1.0174649 , 1.0219332 , 0.99312663,
       0.9975699 , 1.03655   , 0.9745967 , 1.0026734 , 1.0072165 ,
       0.99858856, 1.0087922 , 0.9960258 , 1.020199  , 1.0117856 ,
       0.99494153, 1.004829  , 1.0203712 , 1.0013427 , 1.001718  ,
       1.0110599 , 1.0021498 , 1.0194446 , 1.0036914 , 1.010748  ,
       1.0036187 , 0.99030256, 1.0139859 , 1.0102396 , 0.9928103 ,
       1.0244967 , 1.001053  , 0.9991381 , 1.0057727 , 1.0294267 ,
       1.0064996 , 0.9986673 , 1.0105542 , 1.0038701 , 1.0072494 ,
       1.0122918 , 1.019038  , 1.0037667 , 0.9917391 , 1.0064362 ,
       1.0173568 , 1.0041604 , 0.9907222 , 1.0055772 , 0.99769425,
       0.9938816 , 1.0136765 , 1.0220978 , 1.0108529 , 1.0018622 ,
       0.9999757 , 0.98907924, 1.0037444 , 0.9962258 , 1.0027864 ,
       1.0074923 , 1.0101626 , 1.0068382 , 1.0397725 , 1.0050461 ,
       1.0034118 , 0.99712825, 1.019786  , 0.993959  , 0.99866986,
       1.0398057 , 0.9976807 , 0.9855963 , 1.0187469 , 1.0051827 ,
       1.0043827 , 1.0028539 , 1.0139086 , 1.000293  , 0.99930644,
       1.0261459 , 1.028414  , 1.0067762 , 0.9993668 , 1.0059361 ,
       0.99158233, 1.0148666 , 0.99788713, 0.99870116, 1.006844  ,
       1.0284349 , 1.0131129 , 0.9942042 , 0.99305177, 0.99136925,
       1.0253954 , 0.99573857, 1.0120888 , 0.99497056, 1.0163807 ,
       0.98704475, 0.9939889 , 1.0059642 , 1.0071934 , 1.0145231 ,
       0.9974606 , 1.000721  , 1.0213197 , 1.0102593 , 0.99176204,
       1.0358188 , 0.99096245, 1.020662  , 1.002845  , 0.9924612 ,
       1.0220995 , 0.9995174 , 1.011877  , 1.0105147 , 1.0189173 ,
       0.9921238 , 1.007266  , 1.0026239 , 1.0176792 , 1.0023131 ,
       0.9928363 , 0.99706703, 1.0305314 , 1.00245   , 1.01143   ,
       1.002472  , 1.013554  , 1.0190977 , 1.020946  , 1.0059035 ,
       0.99637914, 0.99857634, 0.9894916 , 0.98517823, 0.9920748 ,
       0.98537487, 0.99544096, 1.0041156 , 1.0014411 , 0.9874259 ,
       0.9842883 , 0.998721  , 1.0135107 , 1.0144683 , 1.0023273 ,
       1.0118119 , 0.9919764 , 1.0054991 , 1.0304428 , 0.9963624 ,
       1.0063417 , 1.013439  , 0.9922583 , 1.0182549 , 1.021138  ,
       1.0232077 , 1.0083649 , 0.9954627 , 1.0199834 , 1.0025986 ,
       1.0000297 , 0.9882497 , 1.0094919 , 0.9886831 , 0.9955983 ,
       1.0091796 , 1.0242625 , 1.0099008 , 1.0388453 , 0.9923897 ,
       0.99347156, 1.0124397 , 1.0144609 , 0.9996574 , 1.0081345 ,
       0.99890274, 1.0338084 , 1.0034207 , 0.99810535, 1.0119139 ,
       1.0081306 , 1.0086477 , 0.99184513, 1.0031805 , 1.0090896 ,
       1.0220637 , 1.0051309 , 1.0073847 , 0.9962892 , 1.0009614 ,
       1.0221307 , 1.0027945 , 0.98855084, 0.99250066, 0.9963916 ,
       0.99929017, 0.9884994 , 0.99953014, 0.9998444 , 1.0076718 ,
       0.9841911 , 0.99982977, 1.0142009 , 0.98910993, 1.031202  ,
       0.98857677, 1.0085851 , 1.0010366 , 0.9975022 , 1.0007247 ,
       1.0076371 , 1.0033219 , 0.9935204 , 0.9978885 , 1.0276169 ,
       0.9982268 , 0.9956597 , 1.0124067 , 0.9969213 , 1.0028389 ,
       1.0124615 , 0.9997636 , 1.0128216 , 0.9989804 , 0.99988323,
       1.0006434 , 0.9908842 , 1.0032738 , 1.0198793 , 0.99930286,
       1.0009607 , 0.9994258 , 0.9934647 , 1.0074103 , 0.9910029 ,
       1.0256197 , 1.0022472 , 0.99921924, 0.9989089 , 1.0256883 ,
       1.0216137 , 1.0108473 , 0.9959751 , 1.0197208 , 1.0036706 ,
       1.0020654 , 1.0159087 , 0.9963028 , 1.0039546 , 0.9965496 ,
       1.0092766 , 1.0316235 , 1.0134057 , 1.0022312 , 0.98421323,
       0.99279183, 1.0186054 , 0.9882645 , 1.016939  , 1.026764  ,
       1.0182432 , 1.0300598 , 1.0038272 , 0.99391264, 1.0087748 ,
       1.0064533 , 1.0059385 , 0.99695754, 0.98981464, 1.0099324 ,
       0.99854094, 1.0270367 , 1.000832  , 1.0247554 , 0.99778914,
       1.0237461 , 1.0242298 , 1.0163642 , 0.9982522 , 1.0105035 ,
       0.99933285, 0.9956487 , 0.9896827 , 1.0241092 , 0.9944243 ,
       1.0103115 , 0.9845932 , 1.0065469 , 1.0299922 , 1.0268362 ,
       1.0041742 , 0.9896999 , 0.9861631 , 0.9966665 , 0.996725  ,
       1.0080764 , 0.98942286, 0.984428  , 1.001277  , 0.9827486 ,
       0.9976909 , 0.9951189 , 0.9914758 , 1.0109308 , 1.0036166 ,
       1.0046245 , 1.0350269 , 1.0381227 , 0.9967768 , 0.99218744,
       0.994664  , 1.0072602 , 0.9898118 , 0.994563  , 1.0066788 ,
       0.998086  , 1.0113765 , 1.0079705 , 1.0113002 , 1.002437  ,
       1.0198019 , 1.020549  , 0.9913331 , 1.0099608 , 1.0077773 ,
       1.0164993 , 1.0070764 , 0.996379  , 0.99595314, 0.99349236,
       1.0147269 , 1.0039706 , 1.012566  , 1.000868  , 1.0030404 ,
       1.0149362 , 0.99003357, 1.0108799 , 1.0063555 , 0.9939964 ,
       1.0020947 , 1.00186   , 0.9981265 , 1.0171081 , 1.0074522 ,
       0.9992288 , 1.0194565 , 0.99173176, 0.9924835 , 1.0163276 ,
       1.0022458 , 0.99716103, 0.9875359 , 0.99683315, 1.005518  ,
       0.99797404, 0.9915233 , 1.0190142 , 1.0168093 , 1.0099295 ,
       0.9946834 , 1.0012028 , 1.0089699 , 0.9882894 , 1.0007678 ,
       1.0046465 , 1.0081555 , 1.0222106 , 1.0148026 , 0.9866687 ,
       0.9955989 , 1.0080107 , 1.0086074 , 1.0205022 , 1.0153997 ,
       0.99294364, 0.9903241 , 1.0110565 , 1.0077217 , 0.99129456,
       0.99766093, 1.0011965 , 1.0114928 , 0.9978554 , 1.023235  ,
       1.0200717 , 0.98691756, 1.0053073 , 0.98753536, 1.0045005 ,
       1.0039504 , 0.9971776 , 1.0000753 , 1.0303514 , 1.002784  ,
       1.0068356 , 1.0347993 , 0.99426377, 0.9998875 , 1.0069646 ,
       0.9946827 , 1.0112281 , 0.99795526, 1.0182132 , 1.0179435 ,
       1.0125084 , 1.0125926 , 0.99621737, 0.9963064 , 1.0117395 ,
       1.0012503 , 1.0004679 , 1.0091245 , 0.990619  , 1.0340581 ,
       0.99154794, 1.0101554 , 1.002543  , 1.0043539 , 1.0083412 ,
       1.0073198 , 1.0008702 , 0.9954808 ], dtype=float32), array([ 9.87591455e-04,  6.35629799e-03, -9.37904231e-03, -1.12004774e-02,
        2.77278852e-03, -1.38010383e-02, -1.81072834e-03, -3.73688228e-02,
        1.00804521e-02,  8.79208848e-04,  1.21806525e-02,  4.13993979e-03,
        1.40553731e-02, -1.07452215e-03,  8.55112821e-03, -2.80446047e-03,
       -3.55929602e-03, -5.17360028e-03,  4.17775038e-04, -1.49313640e-03,
       -1.52847441e-02, -2.64278185e-02, -1.17696030e-02, -1.06043285e-02,
       -1.69492941e-02,  7.06265029e-03,  9.80651472e-03,  1.29279997e-02,
       -5.28053031e-04, -1.28801577e-02,  4.59110318e-03, -1.06781526e-02,
        2.43914343e-04, -9.11567360e-03, -6.82766549e-03, -9.12049785e-03,
       -8.09243321e-03, -1.01814428e-02, -1.25037106e-02,  5.38575416e-03,
        3.53248301e-03,  6.27724337e-04, -7.16951489e-03, -1.35271875e-02,
       -4.28024307e-03, -2.83119585e-02, -5.92795806e-03,  2.77347723e-03,
       -2.86712255e-02,  3.87371122e-03, -1.05875107e-02,  1.44752851e-02,
       -1.33234067e-02,  9.26781725e-03,  1.74801226e-03, -1.41319248e-03,
       -8.72257445e-03, -1.90912131e-02, -8.55242554e-03, -1.18961080e-03,
       -7.64327822e-03,  6.80412073e-03, -2.09074300e-02, -7.01847533e-03,
        1.37786455e-02, -7.64308032e-03, -1.84513461e-02,  1.45238806e-02,
        1.50389094e-02,  1.15041423e-03,  2.38146307e-03, -1.14375376e-03,
       -7.78020825e-03,  3.58044682e-03,  9.11330525e-03, -2.01685652e-02,
        7.27706449e-03, -2.02029198e-03,  9.40091442e-03, -1.28595755e-02,
       -1.17851933e-02,  2.84702145e-03,  5.21851063e-04, -8.19258112e-03,
        1.62054424e-03, -2.64077471e-03,  1.00752981e-02, -3.06321937e-03,
        6.93013659e-03,  4.21317341e-03, -1.04581332e-02, -1.17584718e-02,
       -7.19288364e-03, -1.19980201e-02, -3.38197220e-03, -2.86565488e-03,
       -7.31253810e-03, -1.20880706e-02, -4.42677550e-03,  5.44723682e-03,
       -3.04032117e-03,  3.03789740e-03,  1.04539273e-02, -1.77670438e-02,
        5.22350101e-03, -1.69628467e-02, -2.66908742e-02, -6.59686374e-03,
        8.98694247e-03,  3.46415699e-03, -1.11433547e-02, -1.99392904e-02,
       -1.23193720e-02,  7.24216865e-04,  1.11939507e-02,  8.43237154e-03,
        9.08948388e-03, -9.87298042e-03,  4.90602199e-03, -6.45463681e-03,
       -1.14404233e-02, -2.76545193e-02, -1.06470147e-02,  3.75133683e-03,
       -1.73996892e-02, -1.51862083e-02,  6.13373355e-04,  1.20974192e-02,
        1.08123617e-02,  1.14364130e-03, -4.02547792e-03,  1.49142742e-02,
       -3.89959459e-04, -3.13200080e-03, -3.88360745e-03, -2.35440210e-02,
        1.57089513e-02, -1.83535162e-02, -1.03243487e-02, -9.06495843e-03,
        1.19825602e-02, -6.28882321e-03, -1.75392104e-03, -9.39046778e-03,
       -1.74837299e-02,  1.34212701e-02,  4.85129451e-04, -2.53256410e-02,
       -2.18095649e-02, -3.43952258e-03, -1.67300161e-02, -9.49059427e-03,
       -8.06534477e-03, -2.39544176e-02,  1.14086624e-02, -8.89405608e-03,
       -3.67096765e-03, -1.29612572e-02, -1.09916823e-02, -3.56436637e-03,
        1.76290877e-03, -1.23685393e-02, -5.53149730e-03, -1.20118717e-02,
       -5.93500724e-03, -3.21688280e-02,  1.24658206e-02,  9.76626761e-05,
        4.43935813e-03, -1.68021675e-02, -6.42408500e-04, -1.71025600e-02,
        8.12705912e-06, -2.30897665e-02, -2.65285280e-02, -1.02464780e-02,
       -1.32559298e-03,  4.13444825e-03, -4.26786952e-03, -3.79660144e-03,
       -5.91759244e-03,  4.40025749e-03, -1.41246347e-02, -9.37794242e-03,
       -2.38895044e-03, -7.30531570e-03,  1.46246795e-03, -2.52153212e-03,
        3.87934619e-03,  2.51573301e-03, -6.06711535e-03, -1.44025404e-02,
       -6.25667581e-03, -1.02391625e-02,  1.51735488e-02,  6.14147121e-03,
       -5.91918593e-03,  3.00859241e-03,  6.97936304e-03, -4.99936845e-03,
        1.85320470e-02, -4.28730529e-03,  1.29788574e-02, -1.35431308e-02,
        3.49914562e-03, -5.08571276e-03,  1.09086093e-02, -1.44293196e-02,
        2.34370143e-03, -6.48608990e-03, -1.59580074e-02, -1.42995140e-03,
       -2.66673393e-03, -9.10153892e-03, -4.15779138e-03, -7.02813640e-03,
        7.38023408e-03,  1.31443851e-02,  3.62655940e-03, -4.15021507e-03,
        4.15544678e-03, -7.15348171e-03, -8.39570817e-03, -1.68712661e-02,
        8.24869890e-03,  2.17932779e-02,  4.57350677e-03,  2.21740715e-02,
       -1.25466641e-02, -4.81310254e-03,  1.72592197e-02,  8.15127604e-03,
        1.20095676e-03, -6.16056379e-03, -2.77828015e-02, -6.87627820e-03,
       -1.51078757e-02, -1.02814510e-02, -2.13327408e-02, -6.50084252e-03,
        9.73025803e-04,  2.22897269e-02,  2.45536515e-03, -1.11223776e-02,
       -3.17375030e-04, -2.51098759e-02,  1.86655868e-03,  4.79606446e-03,
       -4.27229935e-03, -3.65879410e-03,  2.01273104e-03, -1.87179411e-03,
       -1.01649649e-02, -4.57858853e-03,  1.01310322e-02, -2.00972259e-02,
       -2.11751498e-02, -2.04322068e-03,  3.64080514e-03,  2.66601681e-03,
       -5.74617554e-03, -7.57774292e-03, -1.17115686e-02, -2.06762943e-02,
       -2.05119816e-03,  1.90569833e-02,  5.16231125e-03,  1.17951101e-02,
       -6.73055556e-03,  6.70865760e-04,  9.19404067e-03,  2.84262840e-03,
       -1.90584187e-03, -9.08559375e-03, -2.04046424e-02, -9.09452047e-03,
       -1.17384577e-02, -3.40331234e-02,  1.12732379e-02, -1.70519855e-02,
       -6.44933153e-03, -1.17253195e-02,  2.68927938e-03, -1.74258426e-02,
       -2.84319315e-02, -8.62769876e-03, -1.00911641e-02, -1.31226406e-02,
       -1.09446114e-02, -2.00837869e-02, -4.01252462e-03, -3.95432627e-03,
       -3.82696255e-03, -7.11274380e-03,  4.98422282e-03, -1.30500793e-02,
        4.37289564e-04,  2.61974074e-02,  1.87961455e-03, -7.58273818e-04,
       -1.99327823e-02, -1.43233733e-02, -1.81900300e-02, -2.83157788e-02,
       -1.16271544e-02, -1.41949384e-02, -2.89431214e-02, -9.08601750e-03,
       -1.67009362e-04,  3.49694490e-03,  1.34842340e-02,  2.11322866e-03,
        3.45742027e-03,  7.33935973e-03, -3.19673214e-03, -5.26999542e-03,
       -1.95994391e-04,  1.16661694e-02,  1.98845547e-02, -4.61553503e-03,
       -6.87560672e-03,  1.20945573e-02, -2.24355347e-02, -3.57533991e-03,
        1.57587603e-02, -5.90878539e-03,  2.03530081e-02, -1.06359124e-02,
       -1.34084066e-02, -1.81727130e-02, -1.86155476e-02, -3.22055974e-04,
       -1.12413820e-02,  1.17254490e-02,  5.97063871e-03, -6.62506674e-04,
        9.22825094e-03, -1.80851519e-02, -9.96479299e-03, -1.40988966e-02,
        1.38371801e-02, -5.61228255e-03, -3.57472943e-03, -1.07763978e-02,
        8.33004806e-03,  4.15671663e-03,  1.03987753e-02, -7.84078799e-03,
        1.02911778e-02, -1.32653862e-03,  1.49701687e-03,  9.47282463e-03,
        1.60267781e-02,  1.67066641e-02, -2.49197055e-02, -1.23505890e-02,
       -5.72884595e-03, -2.03362796e-02, -9.09946859e-03,  7.18220277e-03,
       -1.02951878e-03, -4.08996549e-03,  1.73178148e-02,  2.87773251e-03,
        2.05972958e-02, -3.60828335e-03, -7.45787285e-03, -7.92880170e-03,
       -4.40170337e-03, -7.72930728e-03, -2.79954039e-02, -1.97075401e-02,
       -8.81514046e-03, -1.63955633e-02, -7.79136596e-03,  8.92762281e-03,
       -1.44821021e-03, -3.64600085e-02,  2.59701698e-03, -1.37036350e-02,
       -2.63249055e-02, -1.11069828e-02, -8.33802484e-03, -9.02912021e-03,
        6.81025023e-03, -2.58125570e-02, -3.54056666e-03, -5.98678645e-03,
        9.90609918e-03,  1.39771018e-03, -1.64532345e-02, -1.67073842e-04,
       -7.53430277e-03, -4.73891944e-03, -3.40206362e-03, -2.16200892e-02,
       -2.93558813e-03, -8.25066119e-03,  6.08972646e-03,  1.60615556e-02,
       -1.09204305e-02, -8.30640364e-03, -1.64184230e-03, -5.56701748e-03,
       -9.65743233e-03, -7.92878959e-03,  7.02312216e-03, -2.11613402e-02,
       -7.79184652e-03, -8.44067615e-03, -6.56262645e-03, -1.34657910e-02,
        2.70873755e-02, -2.98200175e-02,  7.00086122e-03, -1.51000237e-02,
        3.27487849e-03, -1.45526482e-02,  1.34464111e-02, -3.23537812e-02,
        2.56419135e-03, -1.69005934e-02, -6.69647241e-03, -1.19497804e-02,
       -3.47746210e-03, -6.81520905e-03, -6.81687938e-03, -2.39717122e-03,
       -1.04799829e-02,  3.74164665e-04, -2.39903275e-02,  7.79226702e-03,
       -2.10591615e-03, -3.60006057e-02, -7.33672362e-03, -1.89182665e-02,
       -9.27714864e-05, -1.61804613e-02, -2.69282404e-02, -1.48568306e-05,
       -1.45277577e-02, -2.34130118e-03, -1.03774024e-02,  1.05466312e-02,
       -8.13992042e-03,  1.35915456e-02, -1.20462654e-02, -3.84816504e-03,
        1.57085732e-02, -3.71783099e-04, -1.48258489e-02, -7.68399704e-03,
       -3.79106775e-03, -2.52941921e-02,  1.19776428e-02, -5.49669098e-03,
       -1.09059177e-02,  8.65365006e-03, -1.09036686e-03,  1.73634221e-03,
        5.60567831e-04,  1.57219300e-03, -6.93569798e-03,  3.97638138e-03,
        3.13759316e-03, -2.43897997e-02, -7.38206739e-03, -1.50620146e-02,
       -3.60663515e-04, -7.70964101e-03, -3.31291440e-03, -2.33817790e-02,
       -1.26040569e-02, -9.19912197e-03,  5.60237095e-06, -3.29554477e-03,
       -1.66668072e-02, -1.38807548e-02, -7.06888922e-03,  1.63888827e-03,
       -7.25366687e-03, -1.81953087e-02, -3.68989742e-04, -6.28496846e-03,
        2.67557637e-03, -3.19434665e-02, -2.38483176e-02,  1.30894288e-04,
       -7.37857958e-03, -9.10250749e-03, -4.42377478e-03, -1.12066856e-02,
       -8.08179844e-03, -2.85088178e-02, -3.93128255e-03,  1.88277047e-02,
       -7.45403161e-03, -1.17315026e-02,  8.76028743e-03, -3.18522099e-03,
       -8.09668563e-03,  6.64952211e-03,  1.43315401e-02, -3.02069727e-03,
       -8.07592552e-03, -7.58338161e-03, -5.25348727e-03,  8.81615933e-03,
       -2.17455765e-03,  2.26112385e-03,  8.57531652e-03,  4.48673381e-04,
        1.71417873e-02, -8.44568107e-03,  1.13303801e-02, -1.39498396e-03,
       -4.36982792e-03, -1.38512673e-02, -1.96048692e-02, -2.02944428e-02,
       -8.31567310e-03, -1.13211395e-02, -9.04830173e-04,  1.01399766e-02,
       -4.59947856e-03, -1.20175257e-02, -6.51348662e-03, -1.09965762e-03,
       -2.77523212e-02, -1.52792176e-03,  1.14492339e-03, -8.77552852e-03,
       -2.64563616e-02, -3.53429423e-05, -6.29105885e-03, -4.91580693e-03,
       -2.01757755e-02, -2.06346475e-02, -3.25878873e-03, -1.95484906e-02,
       -4.77542308e-05, -9.94552299e-03, -9.87808220e-03, -3.29077989e-03,
       -2.25302414e-03,  1.55725451e-02,  8.05307459e-03,  6.79201563e-04,
       -6.99143670e-03, -1.83970276e-02, -3.66436923e-03, -1.68359727e-02,
       -8.42078589e-03,  7.70435296e-03, -2.29674578e-03, -3.42934672e-03,
       -3.65458205e-02, -1.88596174e-02,  1.92627683e-02, -1.36621541e-03,
        1.61014486e-03, -4.29783977e-04,  1.28419641e-02,  1.45097477e-02,
        1.58491358e-02, -3.03020347e-02,  2.19871085e-02, -7.78864557e-03,
        2.97274790e-03,  1.47958368e-03, -2.06072237e-02, -4.47475957e-03,
       -2.44156085e-02, -6.03888184e-04, -6.37964159e-03,  9.64756007e-04,
       -1.55413933e-02, -6.15823176e-03, -1.58311389e-02, -7.43143074e-03,
       -1.75895412e-02,  4.98089823e-04, -1.27771096e-02, -4.53847041e-03,
       -8.87051225e-03, -6.80878293e-03, -2.07708180e-02,  3.13667720e-03,
       -2.80778762e-03, -8.52486864e-03, -1.02174192e-04, -9.50758252e-03,
        1.17343273e-02,  8.01831111e-03,  1.34485941e-02, -5.63579286e-03,
        3.01797874e-03, -1.23252049e-02, -4.27193986e-03,  1.05914446e-02,
       -4.33164602e-03, -8.99719261e-03,  1.57886781e-02, -7.12848781e-03,
       -6.76586386e-03, -5.86985750e-03,  1.37478001e-02, -3.70643218e-03,
       -1.92443375e-02, -1.13603771e-02, -1.00298697e-04,  2.73163384e-03,
       -3.38446833e-02, -9.60735977e-03, -7.90011790e-03, -7.32296379e-03,
       -2.40596514e-02, -1.80855822e-02,  1.00155640e-02, -1.46705871e-02,
       -8.23257118e-03, -1.75520349e-02, -3.64262844e-03,  1.40999490e-02,
        8.58458970e-03, -2.20849086e-02, -1.96866672e-02, -7.88976252e-03,
        3.47340340e-03, -9.30683594e-03,  6.27224008e-03,  5.82692074e-03,
        1.64712258e-02, -7.55077787e-03, -1.15047731e-02,  1.16306236e-02,
       -2.06308183e-03,  2.44023604e-03, -2.49419138e-02, -1.17246795e-03,
       -6.47615036e-03, -2.34245625e-03,  1.23244384e-02, -9.55394562e-03,
       -1.39557268e-03, -6.68892264e-03, -5.24244504e-03,  1.05006378e-02,
       -1.92396473e-02, -1.13182776e-02, -8.54911841e-03, -6.76621217e-03,
       -5.69237338e-04, -3.91724240e-03, -4.97188931e-03, -6.77129673e-03,
       -4.22843639e-03, -8.20565689e-03, -1.10299336e-02, -1.72084793e-02,
        3.06092901e-04,  1.18361879e-02, -1.99120995e-02, -2.46759993e-03,
       -7.71495374e-03,  1.58789684e-04, -6.86701527e-03, -8.83093942e-03,
       -2.59204395e-03, -1.79819390e-02, -1.66851021e-02,  1.26996404e-02,
        5.18291676e-03,  1.38176233e-02, -5.50014246e-03, -1.11544449e-02,
       -6.42734813e-03, -2.24923138e-02,  8.00207444e-03,  2.17837701e-03,
        7.67295342e-03, -9.25135240e-03, -1.27055040e-02, -1.01861255e-02,
       -1.99420517e-03,  6.05878234e-03,  2.14232088e-04, -1.67437817e-03,
       -1.04558456e-03, -4.91196103e-02,  9.32596566e-04, -6.42291829e-03,
        5.05517283e-03, -5.78802917e-03, -6.98662363e-03,  1.23764004e-03,
        4.49253526e-03, -1.09460996e-02, -1.06855296e-02, -1.43557659e-03,
       -6.28637010e-03, -9.54351760e-03,  8.34741455e-04, -2.34189007e-04,
       -1.18851231e-03, -7.83593932e-05,  9.44048725e-03, -8.43941513e-03,
        1.42525416e-02,  3.65417777e-03, -7.76787929e-04, -6.08523749e-03,
        1.34899542e-02, -6.77671656e-03,  2.42508929e-02,  2.59970259e-02,
       -7.74971815e-03,  9.43985942e-04, -1.50313266e-02, -4.83051699e-05,
       -1.35925971e-02, -4.44792286e-02, -1.83431040e-02, -2.00754940e-03,
       -1.53664276e-02, -3.51240709e-02, -1.05710737e-02, -1.46505348e-02],
      dtype=float32), array([-0.00247573, -0.0382253 , -0.01463379,  0.02174743, -0.00487442,
        0.01551171, -0.02197421, -0.01377553, -0.01189063,  0.04232914,
       -0.05163105,  0.01620263,  0.01770305,  0.02792064,  0.00045219,
       -0.04502974,  0.00245906, -0.01287066,  0.05581214,  0.066747  ,
       -0.02595003,  0.02784923,  0.0504048 ,  0.01069675, -0.00842034,
        0.02091204, -0.03731504, -0.02175224, -0.00539668,  0.01125493,
       -0.0329848 ,  0.03001099, -0.0137034 ,  0.04770746, -0.00745353,
        0.00642568,  0.00421166, -0.04475385, -0.00227413, -0.01657198,
        0.04012952, -0.01092433, -0.03706253,  0.02731365, -0.06683372,
        0.0512061 ,  0.0026817 ,  0.03712731,  0.02610559, -0.03002228,
        0.00794491, -0.05846769,  0.0606611 , -0.01121465,  0.02880921,
       -0.01659099,  0.00073366,  0.05376289, -0.02520045,  0.04883577,
       -0.02857373, -0.00692925,  0.07230605, -0.04895952, -0.00042368,
        0.04207451,  0.02383862,  0.00475468, -0.01930538,  0.01490179,
       -0.01680066,  0.01834597, -0.00146515,  0.00302155, -0.04078547,
        0.05627538, -0.04322256, -0.00323501,  0.03407795, -0.01790953,
        0.04502369,  0.0077513 ,  0.0259753 , -0.00515374, -0.03604569,
       -0.02344066,  0.04590581, -0.00182302, -0.03175984,  0.00767481,
        0.03318089,  0.03713599,  0.02381813, -0.01505283, -0.00775479,
        0.01080329, -0.01822715,  0.02947318, -0.00477604, -0.02379514,
       -0.03350757, -0.02950241, -0.02260233,  0.05375566, -0.00687838,
        0.03285112, -0.01117461,  0.03833804,  0.03330824,  0.04033615,
       -0.06083998,  0.05885137, -0.01710515,  0.03018034, -0.01058513,
        0.00019393,  0.05252999,  0.02448501, -0.01284943,  0.03409564,
        0.03630196,  0.05300198, -0.01521017, -0.03200958,  0.04783339,
        0.00164377, -0.02509988, -0.01752003, -0.01505603,  0.06125961,
        0.00450746, -0.01330403, -0.02215984,  0.01815407,  0.00613092,
        0.0108581 , -0.01431378,  0.06110376, -0.01362464,  0.05385393,
       -0.00743331,  0.02827281, -0.0072662 , -0.02374577,  0.07051574,
        0.01152331, -0.00451447,  0.02103062,  0.02444964,  0.01315085,
        0.01638239, -0.01074732,  0.00467764,  0.05811678,  0.00586191,
       -0.05225096, -0.04167163, -0.02081365,  0.02283425, -0.03210239,
       -0.01708249,  0.02288565,  0.00738746, -0.01113104,  0.01369367,
        0.0121519 , -0.02538958,  0.01799133, -0.01401841,  0.06100355,
        0.03332023,  0.05007574, -0.01096574, -0.01868047,  0.02674039,
       -0.0065337 , -0.00571192, -0.05059455, -0.02107364, -0.01070321,
        0.00680243,  0.04490064,  0.00947242,  0.00163619,  0.00264323,
        0.01777803,  0.0313563 , -0.05891033,  0.01925707,  0.01280908,
       -0.02353298,  0.04510825, -0.02645004,  0.00686742, -0.0597478 ,
        0.03079062,  0.05191269,  0.0428766 ,  0.01064845,  0.0167089 ,
        0.03710267,  0.01984044, -0.06230332, -0.02022698,  0.04566297,
        0.04400707, -0.02566102,  0.03713968,  0.03974933, -0.03468254,
        0.04655095, -0.01228264,  0.02193098,  0.00844151,  0.0054977 ,
        0.02985708,  0.03352237, -0.0280669 , -0.04200664, -0.00703461,
        0.04663086, -0.05789113, -0.00099342, -0.00984251, -0.01654574,
       -0.04146582, -0.0358162 , -0.08445754, -0.03456385,  0.05596148,
       -0.04746395, -0.00297594,  0.01877993,  0.06217279,  0.05809233,
       -0.06254419, -0.01409898,  0.01793236,  0.01940314, -0.00019345,
       -0.00853275, -0.04060116, -0.01239991, -0.04306527, -0.04537736,
        0.07135872, -0.02225007,  0.02869246, -0.01272228,  0.03999922,
       -0.00778224, -0.00516868,  0.04741749,  0.02170468,  0.04545417,
        0.01089158,  0.02407321,  0.03856844, -0.01190202,  0.0408587 ,
        0.02760473,  0.00084775, -0.02969077,  0.03586762,  0.03143277,
       -0.04638208, -0.0378548 ,  0.00148982, -0.00276872,  0.00161684,
       -0.0420077 ,  0.04360137, -0.01561905,  0.03471782,  0.00464647,
        0.02604836, -0.0144138 ,  0.06189118, -0.01108968,  0.00569536,
        0.02466862, -0.04555361, -0.01205041, -0.00439671,  0.01165949,
        0.0313681 , -0.02174968, -0.02462961, -0.00294706,  0.0536244 ,
       -0.00263356, -0.03829504, -0.001629  ,  0.01296037, -0.02799337,
        0.04438196,  0.01328609, -0.05615501,  0.00099356, -0.00278887,
        0.02775563,  0.00174255,  0.07070641,  0.01696251,  0.04717394,
        0.00441773,  0.05337323,  0.00969107,  0.01860528, -0.02965091,
        0.01693837, -0.03934819, -0.00972923, -0.04469778, -0.02589697,
        0.0404751 ,  0.03804435,  0.03953481, -0.04817607,  0.03499352,
        0.01842704,  0.05043967,  0.06203694,  0.04527998, -0.0347684 ,
        0.02373013, -0.02253693,  0.03776   ,  0.05291939, -0.0028044 ,
        0.04581537, -0.0223459 ,  0.03514096, -0.02979386,  0.04050811,
        0.04667263,  0.01041819,  0.06309719, -0.03502551,  0.01297336,
        0.03477601,  0.01466925,  0.022639  , -0.01357518, -0.01099185,
        0.05805854, -0.05120972, -0.03467883, -0.03990623,  0.0024735 ,
       -0.02026607, -0.0512085 ,  0.0020033 , -0.0433116 ,  0.04235813,
        0.02744363, -0.00575931,  0.02358552, -0.05219169, -0.06223909,
        0.01766901,  0.02890045, -0.03169094,  0.02679126, -0.03272669,
       -0.01939059, -0.02535978,  0.0586724 ,  0.052066  ,  0.0142323 ,
        0.05070726,  0.0127205 , -0.04365861,  0.04333141,  0.05273879,
       -0.04557994, -0.03458131,  0.03859163, -0.00796394,  0.02800626,
        0.05527789,  0.00542085, -0.03827096,  0.04117443,  0.02176544,
        0.04619287,  0.07385349, -0.01610409, -0.04290648, -0.00585603,
        0.02821109,  0.04070029,  0.00849357,  0.05187651, -0.02609594,
        0.06907494,  0.04399406,  0.02991441, -0.03693371, -0.01833373,
       -0.00148488, -0.00016072, -0.03571258, -0.03001798,  0.03754241,
       -0.00988017,  0.0245729 ,  0.06082893,  0.05144323,  0.02169626,
        0.07561952,  0.009578  , -0.04549889, -0.00446084, -0.02764123,
        0.03450844,  0.00293291,  0.01602578, -0.04641512,  0.0493753 ,
       -0.01443005,  0.0518619 ,  0.02642066,  0.03294581,  0.02970355,
        0.0039235 ,  0.01548547,  0.02249188,  0.02931042, -0.03415721,
       -0.01837331,  0.00571058, -0.0461091 , -0.00924107, -0.03187803,
       -0.01983422, -0.02273149,  0.0381038 , -0.00309926,  0.02322408,
       -0.02712194, -0.06159538,  0.01425894, -0.03318499, -0.01318298,
       -0.00350697, -0.04098357,  0.03706561,  0.06482235, -0.01605751,
        0.03187004,  0.01177789, -0.03423395,  0.034306  , -0.03291564,
        0.05941463,  0.04462233, -0.00582382, -0.03917734,  0.05044269,
        0.05878813,  0.02135222, -0.01510149,  0.05688639, -0.00368325,
       -0.02561544,  0.03826477, -0.02447394,  0.00534635, -0.03735861,
        0.0403511 ,  0.05437499,  0.02264611,  0.06460814,  0.00606528,
        0.03640096,  0.04063255,  0.04543319, -0.02271519, -0.04374203,
        0.02661851,  0.08080883, -0.01263294, -0.0191645 , -0.03699349,
        0.00995615,  0.01285025,  0.00242794, -0.04510991,  0.03488981,
       -0.04824051, -0.00958835, -0.01907365,  0.03895627, -0.02991777,
       -0.05021774, -0.02773791, -0.02242128,  0.00602636,  0.03255066,
       -0.00705975, -0.05186125, -0.00521794, -0.01967458, -0.00552575,
       -0.01382023, -0.04065863, -0.03750255,  0.01873231,  0.05457843,
       -0.0287032 ,  0.00579587, -0.01746251, -0.01270262, -0.03133055,
        0.03634174,  0.06943434, -0.02940974,  0.04236144,  0.03485538,
       -0.00968031, -0.02239934,  0.02686167,  0.00407967, -0.01114781,
        0.05374089,  0.04154197,  0.0125124 ,  0.06801722, -0.00702149,
        0.00770044,  0.01211296, -0.01893666, -0.03426953,  0.02906576,
        0.01735652, -0.03161063,  0.03012726, -0.00684257,  0.00370495,
        0.01061984,  0.02555538, -0.02390705, -0.03834461, -0.10013904,
       -0.0086405 , -0.04636443, -0.00929839,  0.06967819, -0.06886036,
       -0.06037467,  0.07645929,  0.02289679, -0.06325158, -0.01050263,
        0.0295375 ,  0.05195599,  0.0194288 , -0.02510946,  0.00753333,
        0.01137571, -0.06370836,  0.00845442, -0.05606498, -0.05544214,
        0.00712926, -0.06884956, -0.04686488, -0.0096186 ,  0.03502855,
        0.02816865,  0.0148533 ,  0.03119843, -0.00645746,  0.03032316,
       -0.00723735,  0.04524815,  0.0377042 ,  0.03567998,  0.01553125,
        0.04822168, -0.04202908, -0.03412427,  0.01686719,  0.03244496,
        0.02644623, -0.04333249, -0.04135408, -0.01458169,  0.00379422,
       -0.02745346,  0.00428207, -0.04672251,  0.00858649, -0.04584419,
       -0.02247917, -0.02464963, -0.04798702, -0.02260865,  0.00787885,
       -0.01932362,  0.00052454, -0.03575964, -0.00822081, -0.02520019,
        0.01582754, -0.0397731 ,  0.00318965,  0.02886431,  0.0454652 ,
       -0.03441513, -0.05033429,  0.05699586,  0.0089044 , -0.02621486,
        0.00514946, -0.00508009, -0.03751711,  0.00383695,  0.03947714,
       -0.00600646,  0.04838225,  0.07131483, -0.03079181, -0.01838226,
        0.03922104,  0.05436805,  0.0024181 ,  0.05261772,  0.04837048,
       -0.04449501,  0.00782089,  0.03016803, -0.02660189,  0.03693451,
       -0.05064313,  0.00073089, -0.0359747 ,  0.06771193,  0.01908596,
       -0.05662408,  0.05438015,  0.01006426, -0.01140781, -0.04864424,
       -0.03604573, -0.0322182 ,  0.00130988, -0.04393774,  0.0588222 ,
        0.02834263,  0.04641839,  0.02728721,  0.00948821, -0.04410546,
       -0.00871127, -0.00870303,  0.0124546 ,  0.01918331,  0.00498773,
       -0.02996346,  0.01147468, -0.02877087, -0.02202552, -0.03432054,
       -0.03063426, -0.00600438,  0.02181513,  0.03671649,  0.01770366,
       -0.01725223,  0.04787329, -0.05277202, -0.00938723, -0.01554864,
       -0.00810413,  0.04492704,  0.02852646,  0.05957776,  0.00255752,
       -0.02010728,  0.01145054, -0.0549642 , -0.01069537,  0.03843813,
       -0.01774413, -0.03605883,  0.04219007, -0.01964779,  0.03161934,
        0.05800956, -0.01635248, -0.0337442 ,  0.02909813,  0.02831972,
       -0.0349045 , -0.03884496,  0.01713385,  0.03509285,  0.0156054 ,
        0.04397354,  0.0558435 ,  0.00917732,  0.00776702, -0.04349754,
       -0.03619439,  0.06015585,  0.00256521, -0.0576303 , -0.00919898,
       -0.0477938 , -0.03290256, -0.01776449,  0.03629872, -0.02219933,
       -0.01441145, -0.00542244, -0.03194003,  0.00279248, -0.03587059,
        0.00228619,  0.03190435,  0.02424123,  0.01736672,  0.01926647,
        0.02719633,  0.02628086,  0.02186591], dtype=float32), array([0.08635353, 0.09530371, 0.08981845, 0.10590661, 0.08331519,
       0.08721547, 0.08842865, 0.10140977, 0.10098378, 0.10275313,
       0.10331394, 0.10405304, 0.08399211, 0.112891  , 0.09037088,
       0.10384107, 0.10361524, 0.09098318, 0.09789193, 0.11522585,
       0.09042124, 0.10380062, 0.09881218, 0.08533472, 0.0906443 ,
       0.08496416, 0.10059524, 0.10722727, 0.09202557, 0.0897118 ,
       0.09450793, 0.10057878, 0.09496943, 0.10559523, 0.09000728,
       0.09981788, 0.08620396, 0.11634009, 0.08592668, 0.08395339,
       0.09913492, 0.09290674, 0.10992619, 0.09368338, 0.10762674,
       0.1076024 , 0.08707217, 0.09412991, 0.0983046 , 0.10681722,
       0.0883784 , 0.11214829, 0.10515112, 0.10161366, 0.10755853,
       0.08644064, 0.10041384, 0.14442855, 0.08408607, 0.09853539,
       0.08676124, 0.09010736, 0.10517688, 0.10241544, 0.08533879,
       0.10031922, 0.09538158, 0.08501463, 0.09205736, 0.09144706,
       0.08314197, 0.08298922, 0.08726736, 0.08300893, 0.10074172,
       0.10901061, 0.09740604, 0.08401301, 0.09099828, 0.09171876,
       0.11771619, 0.09176988, 0.11134055, 0.08649966, 0.11637385,
       0.08961616, 0.10354136, 0.09044656, 0.11123016, 0.08725629,
       0.08909977, 0.08999266, 0.10323545, 0.08850806, 0.09304583,
       0.08886485, 0.0933933 , 0.09065206, 0.08812281, 0.08454426,
       0.10200192, 0.08742552, 0.09232218, 0.12891626, 0.08581846,
       0.09959094, 0.09332396, 0.1228689 , 0.0987852 , 0.09884837,
       0.10949397, 0.14925699, 0.08388085, 0.09671221, 0.09203747,
       0.08598275, 0.10991444, 0.11209832, 0.09501375, 0.10993165,
       0.10209981, 0.09975088, 0.09046355, 0.0880569 , 0.11931738,
       0.08513057, 0.0912473 , 0.09486795, 0.10459109, 0.10303432,
       0.09565155, 0.08902131, 0.09323451, 0.08799178, 0.09112202,
       0.08545341, 0.08680051, 0.12578984, 0.10715248, 0.11748834,
       0.10009439, 0.08569968, 0.10048851, 0.09070325, 0.1338507 ,
       0.09077436, 0.08495096, 0.08552953, 0.1073717 , 0.08246243,
       0.08843727, 0.09352889, 0.08588868, 0.10481545, 0.08329841,
       0.11965844, 0.10626414, 0.09579667, 0.15113842, 0.10805998,
       0.08954763, 0.09132737, 0.09074201, 0.08438758, 0.08788317,
       0.09581398, 0.10108407, 0.08797147, 0.08283602, 0.12315478,
       0.10146841, 0.12038904, 0.08789929, 0.08592464, 0.10266176,
       0.09751561, 0.0841575 , 0.10150428, 0.09331322, 0.09981852,
       0.08630178, 0.10508653, 0.0931479 , 0.09143271, 0.08958531,
       0.09205221, 0.09208874, 0.1291568 , 0.0859018 , 0.08394217,
       0.0985668 , 0.09736824, 0.0850993 , 0.094005  , 0.11146577,
       0.12064275, 0.10247602, 0.10467084, 0.08352388, 0.10762414,
       0.08544939, 0.09716544, 0.12143333, 0.09736971, 0.09705295,
       0.10031143, 0.09704366, 0.10032891, 0.1027147 , 0.08430103,
       0.08911106, 0.08830669, 0.09254874, 0.08383048, 0.08966943,
       0.08888535, 0.08837046, 0.09789911, 0.11110035, 0.09294552,
       0.09549178, 0.11572733, 0.0914453 , 0.08967322, 0.08823993,
       0.09510878, 0.09299065, 0.13809448, 0.10041122, 0.11227781,
       0.09698014, 0.08709631, 0.08815128, 0.1054824 , 0.12970765,
       0.11455655, 0.09267965, 0.10282284, 0.1022784 , 0.08805975,
       0.08912262, 0.10400213, 0.08354496, 0.09476153, 0.09194746,
       0.12714522, 0.09309637, 0.09711405, 0.09084187, 0.1026788 ,
       0.09027345, 0.08444179, 0.10437226, 0.09332385, 0.12029827,
       0.0951035 , 0.10680925, 0.09947499, 0.08907122, 0.10536097,
       0.08575789, 0.08628464, 0.10726873, 0.1121308 , 0.10206468,
       0.1117836 , 0.10426012, 0.09572575, 0.09060301, 0.0942737 ,
       0.111357  , 0.09385567, 0.08744606, 0.09171738, 0.09295012,
       0.09046209, 0.10085833, 0.12314574, 0.10056552, 0.10088047,
       0.0900308 , 0.10182229, 0.09961086, 0.08512367, 0.09550817,
       0.10588679, 0.08758905, 0.0892501 , 0.08917262, 0.0969196 ,
       0.08455069, 0.09533058, 0.08558419, 0.08839273, 0.09116022,
       0.09650213, 0.08736711, 0.0999457 , 0.09356461, 0.09603707,
       0.08773603, 0.08843134, 0.10853431, 0.09434783, 0.1049002 ,
       0.087569  , 0.09785386, 0.09272113, 0.09625524, 0.09225852,
       0.08692966, 0.09717146, 0.08575931, 0.11754048, 0.09302802,
       0.09848209, 0.0947722 , 0.11348829, 0.09705883, 0.10296246,
       0.09668101, 0.10154427, 0.10585384, 0.11626727, 0.09479094,
       0.09031484, 0.09130432, 0.11318772, 0.1268236 , 0.09581521,
       0.13331325, 0.086803  , 0.11287142, 0.08932883, 0.10195957,
       0.09810401, 0.09202532, 0.1154709 , 0.10540363, 0.09860829,
       0.09127264, 0.09913713, 0.09019223, 0.09074459, 0.08842713,
       0.11212949, 0.10440572, 0.08383708, 0.09064806, 0.09254307,
       0.09078564, 0.11564861, 0.0870929 , 0.0970748 , 0.09840722,
       0.10637242, 0.09332594, 0.08526485, 0.10905707, 0.1313645 ,
       0.09427025, 0.10546655, 0.09663711, 0.0990721 , 0.09220969,
       0.09614426, 0.09028241, 0.12844044, 0.09039079, 0.09077803,
       0.14028153, 0.0958751 , 0.09463429, 0.1107782 , 0.09864424,
       0.08942463, 0.09937641, 0.11725625, 0.09200887, 0.09675895,
       0.09152583, 0.09301166, 0.10292876, 0.09490599, 0.08999623,
       0.10500009, 0.10299288, 0.09867407, 0.09119076, 0.09091824,
       0.1138616 , 0.0944187 , 0.0874797 , 0.09100512, 0.0992491 ,
       0.15105931, 0.09665675, 0.11109808, 0.09677646, 0.09243059,
       0.0956308 , 0.09205171, 0.09005208, 0.09323506, 0.10981305,
       0.0894753 , 0.10108849, 0.13357508, 0.10252501, 0.08593911,
       0.14485267, 0.08459901, 0.10482632, 0.0894535 , 0.08354204,
       0.10477865, 0.08513089, 0.10288963, 0.10341114, 0.11414468,
       0.08508741, 0.1037549 , 0.09899189, 0.10023897, 0.10820845,
       0.0888259 , 0.09538711, 0.10078353, 0.10357264, 0.09380913,
       0.101447  , 0.08777301, 0.09506871, 0.10260904, 0.09680539,
       0.08498047, 0.09658857, 0.09098095, 0.09388135, 0.09452858,
       0.10001881, 0.11344901, 0.10791873, 0.10175887, 0.09027003,
       0.08719587, 0.09887685, 0.09513157, 0.11361168, 0.08802257,
       0.09293699, 0.08979941, 0.09306274, 0.10056479, 0.08550116,
       0.11909864, 0.10662368, 0.08599191, 0.11037125, 0.1106648 ,
       0.13836671, 0.09103046, 0.09293196, 0.09616402, 0.08637278,
       0.0832538 , 0.08634054, 0.09628484, 0.08558584, 0.10126239,
       0.11105091, 0.11293247, 0.08843404, 0.13681842, 0.08490276,
       0.10838021, 0.0949921 , 0.10642498, 0.08599067, 0.11553903,
       0.09143155, 0.16500908, 0.09053875, 0.09312548, 0.0966111 ,
       0.09354729, 0.09942881, 0.09641959, 0.13166428, 0.08923613,
       0.11593077, 0.09115351, 0.08757975, 0.09274177, 0.09456784,
       0.09992269, 0.09196893, 0.09019943, 0.08400016, 0.09403225,
       0.08951108, 0.10042721, 0.09033523, 0.08595642, 0.08997729,
       0.08694003, 0.0915505 , 0.09461682, 0.0854274 , 0.11033694,
       0.08524367, 0.08771656, 0.09003967, 0.09164361, 0.09862623,
       0.09655681, 0.13584904, 0.09516139, 0.09909093, 0.11688628,
       0.09005408, 0.09145206, 0.10914642, 0.08837964, 0.09248409,
       0.11247148, 0.10295256, 0.09358287, 0.13966575, 0.09075397,
       0.09852019, 0.09109621, 0.09780288, 0.08734538, 0.08736124,
       0.09312458, 0.09916062, 0.08845824, 0.09095442, 0.0865633 ,
       0.10099293, 0.0995328 , 0.09169603, 0.08568428, 0.14095563,
       0.10224716, 0.13034539, 0.08672562, 0.11874917, 0.12804388,
       0.09624013, 0.11485327, 0.08676068, 0.11572677, 0.08261348,
       0.09271488, 0.11394247, 0.10202511, 0.08910976, 0.08227008,
       0.08436004, 0.12310258, 0.08562931, 0.10720826, 0.10653092,
       0.09392519, 0.14007539, 0.09467917, 0.08717514, 0.0923488 ,
       0.09594963, 0.09911944, 0.11200997, 0.09060699, 0.09926776,
       0.09315093, 0.09529348, 0.09794149, 0.1132772 , 0.09743843,
       0.10355716, 0.09494862, 0.09878801, 0.08535706, 0.11684345,
       0.10137951, 0.12554708, 0.09463179, 0.10603725, 0.09223482,
       0.09559385, 0.08280973, 0.11640927, 0.09263425, 0.09362221,
       0.09353857, 0.10022164, 0.10409195, 0.10106186, 0.09211074,
       0.09624661, 0.08775627, 0.10076842, 0.08331586, 0.09907012,
       0.08510558, 0.09534793, 0.08384264, 0.11910674, 0.09043501,
       0.09684811, 0.08934969, 0.12171225, 0.08535219, 0.09220593,
       0.08481396, 0.08784325, 0.10152444, 0.08307979, 0.11089813,
       0.08888688, 0.10082839, 0.12897642, 0.09133644, 0.08607981,
       0.13208462, 0.10795996, 0.09158055, 0.0920174 , 0.09455577,
       0.09522943, 0.08640373, 0.09847159, 0.08856146, 0.09624093,
       0.10054741, 0.08820775, 0.10807523, 0.10666443, 0.09624586,
       0.10124671, 0.09080593, 0.09270272, 0.08543111, 0.09707869,
       0.10213619, 0.08300461, 0.08315632, 0.1064821 , 0.0951537 ,
       0.10075273, 0.10405326, 0.08914664, 0.08794118, 0.11215789,
       0.08671409, 0.09185269, 0.08811793, 0.09067137, 0.09306047,
       0.0964228 , 0.08734857, 0.12054325, 0.09587843, 0.10693058,
       0.08820888, 0.08729686, 0.08826016, 0.10391255, 0.10306037,
       0.11137362, 0.10603457, 0.09943949, 0.08630754, 0.09657858,
       0.09834709, 0.08854616, 0.10018919, 0.1191176 , 0.0835456 ,
       0.08817893, 0.09468625, 0.11302494, 0.08495019, 0.08738995,
       0.08849755, 0.0887081 , 0.1082776 , 0.09448598, 0.10658249,
       0.1001818 , 0.08423325, 0.09627173, 0.08818187, 0.09532356,
       0.08929839, 0.09655802, 0.09683034, 0.12453831, 0.09161133,
       0.09979618, 0.1149738 , 0.08702595, 0.09232045, 0.10655402,
       0.11119708, 0.12210675, 0.08430561, 0.11480182, 0.09892751,
       0.10832638, 0.106884  , 0.08629204, 0.08888835, 0.10183066,
       0.08775979, 0.09214342, 0.1045435 , 0.08287433, 0.09225777,
       0.08415222, 0.09862821, 0.09282824, 0.09353545, 0.09731487,
       0.09903637, 0.08842043, 0.09261552], dtype=float32), array([[[[-0.02135496],
         [ 0.0036261 ],
         [-0.01803181],
         ...,
         [-0.01082589],
         [-0.00534287],
         [-0.00879072]],

        [[-0.010353  ],
         [ 0.00996925],
         [-0.02066023],
         ...,
         [-0.01066149],
         [ 0.01075876],
         [-0.00941186]],

        [[-0.00943517],
         [-0.00112839],
         [ 0.02455453],
         ...,
         [ 0.02283568],
         [ 0.01429764],
         [-0.00433765]]],


       [[[-0.0131245 ],
         [-0.01408019],
         [ 0.00561211],
         ...,
         [-0.00542222],
         [-0.00803138],
         [-0.01616593]],

        [[-0.01448228],
         [-0.00307905],
         [-0.00964695],
         ...,
         [-0.00021047],
         [-0.00031522],
         [ 0.02205514]],

        [[ 0.00331409],
         [-0.01730066],
         [-0.01890688],
         ...,
         [-0.0151845 ],
         [ 0.03461245],
         [-0.01543188]]],


       [[[-0.00435387],
         [ 0.00529694],
         [-0.01601152],
         ...,
         [ 0.01494035],
         [-0.00761675],
         [-0.00087613]],

        [[-0.00707018],
         [ 0.01136071],
         [-0.01032654],
         ...,
         [-0.01265922],
         [ 0.00927777],
         [ 0.00473021]],

        [[-0.02406694],
         [ 0.0149306 ],
         [ 0.00181124],
         ...,
         [ 0.02353073],
         [ 0.00137469],
         [ 0.02715275]]]], dtype=float32), array([[[[-0.0343159 ,  0.02804921, -0.04493508, ..., -0.02822783,
           0.05241945,  0.04555121],
         [ 0.05206225, -0.03021527,  0.02988211, ...,  0.02794247,
          -0.06833702, -0.03714393],
         [ 0.05427207, -0.00074735, -0.00061253, ..., -0.01605362,
           0.00692781, -0.04965509],
         ...,
         [ 0.00583094, -0.03631574, -0.03490522, ..., -0.05435447,
          -0.00427391,  0.02726635],
         [ 0.01851898, -0.01996987, -0.04946213, ..., -0.06468169,
           0.02482755, -0.02979287],
         [-0.03678501, -0.05635962, -0.03411262, ...,  0.02699128,
           0.01892723, -0.01997751]]]], dtype=float32), array([1.0047607 , 0.99922717, 1.0237335 , 1.0060524 , 0.9900367 ,
       1.0122137 , 1.0062665 , 0.991498  , 0.99142176, 0.9954604 ,
       0.9987568 , 0.9849281 , 0.9910744 , 0.987671  , 0.9862306 ,
       0.99262565, 0.99734014, 0.99025667, 1.0149045 , 0.98977345,
       0.99819833, 0.9942312 , 0.9958942 , 1.0330149 , 0.99626106,
       1.0314548 , 1.0072294 , 1.0014976 , 0.9992148 , 0.98647785,
       1.0026159 , 1.0083349 , 0.99539226, 1.0002838 , 1.0047263 ,
       0.99546415, 0.9965851 , 1.0066292 , 1.0083027 , 0.98903865,
       0.998184  , 0.9966479 , 1.0054283 , 1.0116421 , 1.0116235 ,
       0.9930179 , 0.9945921 , 1.0065339 , 0.99338984, 0.989156  ,
       1.0009476 , 0.99539554, 1.0120091 , 0.9981793 , 0.9959434 ,
       0.993544  , 1.0103852 , 0.98915124, 1.005891  , 0.99485064,
       1.0019443 , 0.9865836 , 1.0004773 , 0.98914677, 0.99881846,
       0.9885672 , 0.9912889 , 0.99657327, 0.9976239 , 1.0029633 ,
       1.0190848 , 0.99026275, 0.98443455, 0.9896071 , 0.9868814 ,
       0.99585956, 1.0029641 , 0.9972379 , 0.99737644, 0.99059623,
       1.0069306 , 1.0003557 , 0.9923423 , 1.0069959 , 0.9925483 ,
       1.0066612 , 0.99482244, 0.9992829 , 1.0100405 , 0.99758494,
       1.0222598 , 0.99834263, 1.0140597 , 0.9911703 , 0.9869821 ,
       0.9946838 , 0.99118304, 1.0004842 , 0.9924852 , 1.0187842 ,
       0.990505  , 1.0234783 , 0.99933034, 1.0027163 , 0.99583805,
       0.99420583, 0.9983675 , 1.003037  , 1.0014155 , 0.99730873,
       0.99629694, 1.0007586 , 0.9983568 , 1.0183916 , 1.0101554 ,
       0.9878204 , 1.0033607 , 1.0131857 , 0.9974911 , 0.98254913,
       1.0186691 , 1.002001  , 1.0188732 , 1.003504  , 0.99667794,
       0.9986706 , 1.0105014 , 1.0079815 , 1.0193019 , 0.9889027 ,
       1.0060456 , 0.99384654, 1.0086529 , 0.99212074, 1.0015591 ,
       0.9913469 , 1.0023288 , 0.98802006, 1.0036879 , 1.0083216 ,
       1.0116196 , 0.9970603 , 1.013544  , 1.0050092 , 1.0067534 ,
       1.0077803 , 0.99258435, 0.99420726, 0.9941852 , 0.99236244,
       0.9858321 , 1.0061302 , 0.99408853, 0.99548846, 1.0005628 ,
       0.99396086, 0.9992284 , 1.0022941 , 0.9963457 , 1.0031176 ,
       0.99771214, 1.0006256 , 0.97812366, 1.0030749 , 0.99610716,
       0.99149066, 0.9906128 , 1.0118005 , 1.0081583 , 0.99426186,
       0.9899545 , 1.0000246 , 1.0037805 , 0.9982014 , 1.0168779 ,
       0.9945603 , 0.9914482 , 1.0097098 , 0.99134713, 0.9948152 ,
       0.98826194, 1.0009831 , 1.0048289 , 0.99052393, 0.9911561 ,
       0.9980496 , 0.9987098 , 0.99543285, 1.0169615 , 0.9787709 ,
       0.9999983 , 1.0069358 , 0.99752843, 1.0021642 , 0.99926525,
       0.9967331 , 0.98843586, 0.99139625, 0.99076545, 1.0099028 ,
       0.9973911 , 1.001945  , 0.9987513 , 1.005618  , 1.0155038 ,
       1.0151882 , 1.0027472 , 0.9940201 , 1.0014626 , 0.9906176 ,
       0.99321556, 0.99817455, 1.000167  , 1.0116575 , 0.99570024,
       1.0061905 , 0.99592304, 0.9945776 , 1.0013962 , 0.9906788 ,
       0.9954909 , 1.0036572 , 1.0505191 , 0.9978491 , 0.9884973 ,
       0.99572057, 0.9899832 , 0.9906745 , 0.9896501 , 0.99382234,
       1.0016408 , 0.9912655 , 1.0176384 , 1.0094668 , 0.99517   ,
       1.0146699 , 1.0152984 , 0.9880609 , 0.99930876, 0.9966002 ,
       0.9928243 , 1.0248934 , 0.99690205, 1.0158736 , 1.0037692 ,
       0.9895841 , 0.99647874, 1.005336  , 0.9977453 , 1.0009508 ,
       0.99205923, 0.987892  , 1.000876  , 1.0303911 , 0.99759597,
       0.988248  , 0.98879457, 1.0013494 , 0.99730366, 1.022277  ,
       1.0125854 , 1.0067798 , 1.0110586 , 0.99481106, 0.99860823,
       0.9969575 , 1.005849  , 0.98372597, 0.9949834 , 1.004181  ,
       1.0301511 , 1.0058751 , 0.9860484 , 0.99918437, 0.994653  ,
       0.99581593, 1.0037724 , 1.0087323 , 1.0017961 , 0.9980942 ,
       0.9995624 , 1.0107887 , 0.9928061 , 1.0206105 , 1.006698  ,
       1.0170536 , 0.9948582 , 1.0207369 , 1.0000548 , 0.9933504 ,
       0.9993624 , 0.9920768 , 1.0101097 , 0.99924237, 0.9910945 ,
       1.0103561 , 0.9840734 , 0.9957737 , 0.988898  , 1.013416  ,
       0.99335194, 0.9990058 , 0.9937865 , 1.009643  , 0.9924003 ,
       0.99229866, 0.99377865, 0.99273026, 0.99517673, 1.022172  ,
       1.0010058 , 1.0033919 , 1.0017669 , 0.9950666 , 1.0013188 ,
       0.9951768 , 0.9990934 , 1.0362004 , 1.0187466 , 0.9889868 ,
       1.0048238 , 0.9931784 , 0.99941427, 0.99965125, 0.9979791 ,
       0.9925083 , 0.99306715, 1.0083121 , 0.9878555 , 0.9881481 ,
       1.0020626 , 1.0082388 , 1.0012558 , 0.98299843, 0.9958622 ,
       0.99214494, 0.9959728 , 0.99365103, 0.99351686, 1.0023041 ,
       0.99827456, 0.99240947, 0.99725205, 0.9914817 , 0.9957162 ,
       0.997645  , 1.008161  , 0.9992204 , 0.99365044, 0.9972215 ,
       1.0052675 , 0.99175453, 1.0276533 , 0.9942058 , 1.0124352 ,
       0.99030775, 0.99831796, 0.9920966 , 0.99024594, 0.9978601 ,
       1.0104744 , 1.0078624 , 0.99166495, 0.9962276 , 0.9906116 ,
       0.9860937 , 1.0198536 , 0.99271715, 0.984928  , 0.99641836,
       0.99749035, 0.999671  , 0.9880626 , 0.99748975, 1.0016524 ,
       1.0008332 , 0.9902051 , 0.9949022 , 1.0028373 , 0.9887917 ,
       0.9983594 , 1.0005432 , 0.98237497, 0.9996319 , 1.0051126 ,
       1.0279346 , 0.99292606, 0.9892411 , 0.9960003 , 1.0072184 ,
       1.0026883 , 1.0068772 , 0.9901575 , 1.0062426 , 0.99779946,
       0.9955958 , 0.9976582 , 1.0012565 , 1.0002446 , 0.99313754,
       0.99868834, 0.9999873 , 0.99146795, 1.0036815 , 0.9924209 ,
       0.9907974 , 1.01524   , 0.9891731 , 1.0024503 , 1.000703  ,
       1.0051186 , 0.99308103, 1.0077304 , 0.9849527 , 0.99131125,
       1.0136006 , 1.0036409 , 1.0050169 , 1.0356067 , 1.0058701 ,
       0.99972194, 0.9949039 , 0.9932725 , 1.0230882 , 0.9952146 ,
       1.0125686 , 0.98736227, 1.0107706 , 0.99737614, 1.008226  ,
       0.9908227 , 1.0049672 , 1.0060463 , 1.0033801 , 0.9955072 ,
       0.991749  , 1.0019126 , 1.0001338 , 0.99994946, 0.9935837 ,
       1.0050145 , 0.9988018 , 0.99087125, 1.0160517 , 0.9985241 ,
       0.9964202 , 0.9976391 , 1.0014646 , 1.0036551 , 1.0154146 ,
       0.9957898 , 1.0107148 , 0.9915448 , 0.9951496 , 0.9929696 ,
       1.002522  , 0.99027693, 0.99895465, 0.9904422 , 0.99823064,
       1.0013429 , 1.003425  , 0.98979384, 1.0012493 , 0.99726766,
       1.0086418 , 0.9920456 , 0.9939987 , 1.010637  , 0.9913816 ,
       1.0019513 , 0.9888006 , 0.9982291 , 0.9904367 , 0.99152416,
       0.99276245, 0.99599034, 0.9992894 , 1.001353  , 0.99712485,
       0.9932813 , 1.0234586 , 1.0030259 , 0.99487585, 1.0190543 ,
       1.0142584 , 0.9935564 , 1.0013498 , 0.9943531 , 1.0138415 ,
       0.9882926 , 0.9992447 , 0.99620104, 0.996105  , 0.99257815,
       0.99490035, 0.9979683 , 0.9908149 , 0.9980004 , 1.0128661 ,
       1.0095527 , 1.0057857 , 1.0044521 , 0.99881655, 1.0016525 ,
       0.9922194 , 1.0003679 , 1.0085851 , 0.99105614, 0.99736154,
       0.9959285 , 0.9985992 , 0.99736714, 0.997183  , 0.9871412 ,
       1.0017685 , 0.9900559 , 0.9970202 , 0.99806726, 0.9951227 ,
       1.0055494 , 0.9893468 , 0.9991754 , 1.0071226 , 0.9966033 ,
       1.0052967 , 0.99559176, 1.0158088 , 1.0064039 , 1.0211632 ,
       1.017694  , 1.0014253 , 0.99422187, 1.0087498 , 0.9929814 ,
       0.98741186, 0.99005765, 0.9976243 , 0.9933614 , 1.0051    ,
       0.99945366, 0.9964501 , 1.0064777 , 1.0039512 , 0.9973149 ,
       0.99317753, 1.0029455 , 1.0044863 , 0.99458754, 0.9965542 ,
       1.0140826 , 0.9897474 , 1.0175831 , 0.99610716, 1.0047303 ,
       0.9988954 , 0.9997375 , 1.0025988 , 0.99158716, 1.0054374 ,
       0.9931024 , 0.99969137, 0.98851025, 1.0271835 , 1.0017501 ,
       1.0094641 , 1.0021963 , 1.0018706 , 0.98216814, 0.98372513,
       1.0149443 , 1.0003414 , 0.9994398 , 1.0013133 , 1.0024905 ,
       1.0131035 , 0.99831706, 0.9904181 , 0.99534136, 1.0023928 ,
       0.9924177 , 1.0200809 , 0.9957086 , 0.99488825, 1.007739  ,
       1.0120425 , 1.0129044 , 1.0079594 , 1.0024929 , 0.9911528 ,
       0.99485046, 0.98427856, 1.0120348 , 1.0008335 , 1.0025123 ,
       1.0041842 , 1.0041146 , 0.9956631 , 1.0016997 , 0.99808896,
       1.0002507 , 0.9986311 , 1.00993   , 0.99690145, 1.0000443 ,
       0.9969195 , 0.99589366, 0.98682505, 1.0246912 , 0.9995004 ,
       1.000594  , 0.9899875 , 0.9919328 , 0.9946792 , 0.99660647,
       1.0027068 , 0.9923443 , 0.9839772 , 1.0157437 , 1.007249  ,
       1.0000714 , 1.0024179 , 1.00345   , 1.012612  , 1.0026053 ,
       0.99509484, 1.0014004 , 1.0093275 , 0.9871889 , 0.99393994,
       1.0045923 , 0.9876102 , 0.9974767 , 1.0222074 , 0.98441267,
       0.9883281 , 1.0330746 , 0.9899612 , 1.0029094 , 0.9907972 ,
       0.9960122 , 0.9939426 , 0.99155897, 0.996288  , 0.99731827,
       1.0079225 , 1.0066578 , 0.9956044 , 0.9975215 , 1.0075693 ,
       0.9897247 , 0.9925105 , 1.0040567 , 0.98562646, 1.0072155 ,
       1.0058402 , 1.0063113 , 0.9978713 , 0.9942822 , 0.9855699 ,
       0.9899669 , 0.9968128 , 1.0051531 , 1.0051702 , 1.0124843 ,
       1.0057386 , 1.0189841 , 1.000571  , 1.0057244 , 1.0050834 ,
       0.99683   , 0.98859763, 0.9934703 , 1.0140938 , 1.0035903 ,
       0.9941938 , 1.0131823 , 0.99601215, 1.0050385 , 1.0043285 ,
       0.98946863, 0.98793095, 1.0085711 , 1.0003268 , 0.9923824 ,
       0.9952478 , 1.0260022 , 1.007631  , 0.9855541 , 1.0016853 ,
       0.9903432 , 1.0032971 , 1.0020062 , 1.0193892 , 1.0007161 ,
       0.996419  , 0.9808334 , 0.99337703, 1.0047029 , 0.9988093 ,
       0.99803346, 0.9959778 , 0.9959769 , 0.9794227 , 0.99605435,
       0.9833175 , 0.99495625, 1.0325165 , 0.98798066, 1.0062038 ,
       1.0025489 , 0.99452746, 0.9923511 , 1.0103952 , 0.9951869 ,
       1.0051866 , 0.9977302 , 0.9962194 , 0.99547046, 0.98729897,
       1.0110222 , 1.0003852 , 0.9946013 , 0.9953326 , 0.991555  ,
       1.0041875 , 1.0099567 , 0.9908242 ], dtype=float32), array([-2.14723311e-02,  3.19134118e-03, -2.04804391e-02,  1.58844441e-02,
       -2.34079324e-02, -1.08463969e-02, -4.15353887e-02, -1.54289678e-02,
       -1.05547737e-02, -1.50846150e-02, -9.37361922e-03, -2.79996190e-02,
        6.48175273e-03, -5.46666933e-03, -9.11709201e-03,  2.74551869e-03,
        3.05171474e-03, -1.54166510e-02,  2.05885675e-02, -5.89542976e-03,
       -4.47354559e-03,  1.61136012e-03, -4.70269052e-03, -3.21874768e-03,
       -1.27981557e-02, -1.27204636e-04, -8.37614480e-03,  1.78245399e-02,
       -1.00179343e-03, -2.31386516e-02, -1.16838180e-02,  1.10232076e-02,
       -2.88851839e-02,  2.29661576e-02,  2.25952435e-02, -1.97573099e-02,
       -3.73131875e-03, -1.06400428e-02,  2.60072034e-02, -7.71524897e-03,
       -3.62170883e-03,  1.13224005e-02,  1.97875090e-02,  4.47402708e-03,
       -6.27652928e-03, -3.68248709e-02, -6.24387525e-03, -1.73374917e-02,
       -5.59732504e-03, -1.17652984e-02, -1.66375644e-03,  2.64220347e-04,
       -8.20976216e-03, -1.94822915e-03, -4.92412271e-03, -2.49129720e-02,
       -9.93452221e-03, -6.25754707e-03,  6.18002517e-03, -9.13259573e-03,
       -8.85819923e-03,  8.53237417e-03, -1.32272916e-03, -4.69469838e-03,
        1.36750378e-02,  1.36871599e-02, -9.20061115e-03, -5.30984020e-03,
       -5.03940322e-03, -7.70085864e-03,  3.59562668e-03, -1.03744492e-02,
       -1.55667653e-02, -1.01742838e-02, -4.69962088e-03, -9.38044023e-03,
        3.27443914e-03, -3.44041851e-03,  6.48209173e-03, -5.05893910e-03,
        1.14173042e-02,  7.80634396e-03,  9.81122954e-04, -9.87330102e-04,
       -8.41744430e-03,  1.09352814e-02, -1.10660261e-02,  6.21194253e-03,
       -3.33644752e-03,  2.12339684e-03,  8.21215007e-03, -4.07980569e-03,
        2.44707223e-02, -3.58693441e-03, -1.64181311e-02, -9.49313457e-04,
       -6.65583834e-03, -2.29117721e-02, -1.23961093e-02, -9.65896528e-03,
       -7.63596129e-03,  2.73662657e-02, -1.05389552e-02,  3.77848861e-03,
       -7.71971140e-03, -7.06087006e-03, -3.28330025e-02,  3.43802944e-02,
        3.13045713e-03, -9.64308344e-03, -3.94271165e-02, -1.10199209e-02,
        5.97866718e-03,  1.08330958e-02, -4.51128464e-03, -2.67103892e-02,
        1.57802869e-02,  1.59352552e-02,  4.19481439e-05, -1.33320512e-02,
       -2.77416722e-04,  4.00683470e-03, -9.01771069e-04,  2.04799846e-02,
       -4.34158929e-03,  8.02335516e-03,  1.70572009e-02, -6.23363117e-03,
       -1.84927247e-02, -3.93377198e-03,  8.39597732e-03, -2.16326918e-02,
        3.14741433e-02, -7.95205589e-03,  2.01135650e-02, -2.83769751e-03,
       -1.86963603e-02,  1.82967354e-02, -7.14478968e-03, -1.17226588e-02,
       -1.12719648e-02,  1.89231057e-02, -2.04896592e-02,  2.26848666e-03,
        5.11956261e-03,  1.60856564e-02, -3.43742664e-03, -4.58647124e-03,
        1.43283959e-02, -1.01335719e-03, -3.60686402e-03, -3.53504368e-03,
        2.12598406e-03, -8.25115480e-03,  1.13107301e-02, -1.29312146e-02,
        6.05983287e-03,  6.71331724e-03, -8.51612724e-03, -4.29319637e-03,
       -1.40369553e-02,  1.10227196e-03, -1.16262659e-02, -7.76189147e-03,
       -6.85841031e-03, -1.38765303e-02, -1.39139136e-02, -2.20439192e-02,
       -1.37812002e-02, -2.59380462e-03, -2.02442594e-02,  1.01914768e-04,
        1.02756526e-02, -1.62107451e-03, -1.25883557e-02,  9.37852717e-04,
       -3.63187777e-04,  3.82975601e-02, -3.13314958e-03,  4.25933424e-04,
       -1.61536094e-02, -1.99741032e-03,  3.97488615e-03, -1.19025959e-02,
       -6.09293533e-03, -5.71939349e-03, -2.53351580e-04,  1.45227741e-03,
        3.19508016e-02, -1.54048577e-02, -2.17105215e-03,  3.17572989e-03,
       -2.20652693e-03, -1.42373256e-02, -3.13977734e-03,  7.09180487e-03,
       -1.11525627e-02, -4.70543950e-04,  1.63762132e-04, -6.74365694e-03,
       -1.11326936e-03,  1.95623818e-03,  7.67396064e-03, -1.56535171e-02,
        4.69936728e-02, -9.32258554e-03, -2.33629392e-03, -1.13774184e-02,
       -4.25038999e-03, -1.69053450e-02, -4.88457130e-03,  2.31429166e-03,
       -2.15586126e-02, -2.64583691e-03, -1.22993188e-02,  1.69421983e-04,
        1.83182545e-02, -3.22506833e-03,  8.01968295e-03, -1.53684488e-03,
       -3.07096285e-03, -1.47168413e-02,  1.35445669e-02, -1.64135615e-03,
        3.93950194e-03, -1.30445370e-02, -4.79602301e-03,  6.17981190e-03,
       -8.24116636e-03, -2.93162768e-03, -2.22299853e-03, -9.39059723e-03,
        2.54774708e-02,  2.75830887e-02, -1.27935503e-02, -2.99772876e-03,
       -7.05053052e-03, -9.35077947e-03, -1.20054344e-02,  6.67182077e-03,
        5.96507499e-03,  1.60737876e-02,  1.74685102e-03,  1.47479083e-02,
       -2.15858743e-02,  1.72437821e-03, -8.62816721e-03,  6.30823476e-03,
       -1.82703091e-03,  3.45105422e-03,  9.26214457e-03, -3.98793910e-03,
        3.49987624e-03, -9.94642079e-03, -5.69833256e-03, -1.48602501e-02,
       -1.93721149e-02,  1.32092517e-02, -9.83094797e-03, -8.17750581e-03,
       -8.86263791e-03,  3.34531604e-03, -3.75983231e-02, -2.49743112e-03,
       -3.88650130e-03, -3.48453439e-04,  2.45912690e-02, -1.10526523e-02,
       -1.15177277e-02,  1.75469592e-02, -1.46406307e-03, -2.93944441e-02,
       -1.78462826e-02, -1.67046804e-02,  4.15573502e-03,  1.01953903e-02,
        8.87280330e-03,  1.56321749e-02,  2.22447026e-03, -2.30352394e-02,
        5.78312483e-03, -9.35974531e-03, -3.00694462e-02, -1.92511063e-02,
        1.12225199e-02, -3.91805032e-03, -9.09179915e-03,  2.87717581e-02,
       -4.22866130e-03, -1.07847098e-02, -1.08026108e-02,  8.72452278e-03,
       -4.25529527e-03,  1.50138447e-02, -5.49171399e-03,  1.04364497e-03,
       -1.35523640e-02, -9.25065111e-03, -7.53025059e-03,  1.07146967e-02,
       -2.49420060e-03,  4.89072008e-05, -8.39691842e-04, -5.23980446e-02,
       -1.08818254e-02, -5.26870415e-03, -9.86956898e-03, -1.24060381e-02,
        5.74802700e-03,  3.45007540e-03,  9.45876539e-03,  1.16210049e-02,
        1.79274101e-02, -1.22434879e-02, -5.81498677e-03, -3.74562386e-03,
        1.06273666e-02,  2.40069125e-02,  1.56608261e-02,  6.59028592e-04,
        1.02010220e-02,  7.62202777e-04,  1.46915223e-02,  6.43803645e-03,
       -1.71078667e-02,  5.21167589e-04, -1.23786426e-03,  1.43336114e-02,
       -8.14527459e-03, -1.47902092e-03,  3.47525403e-02, -5.10099670e-03,
       -2.66767992e-03, -1.32628214e-02,  2.01986462e-04, -3.19126481e-03,
       -3.64445359e-03, -3.43383588e-02, -1.16028832e-02,  1.71803162e-02,
       -3.95761104e-04, -9.74421389e-03, -2.79614865e-03, -7.57582812e-03,
        2.89725955e-04, -1.11585110e-03, -2.13384479e-02, -8.89634807e-03,
       -5.08906366e-03, -2.99066547e-02,  1.31279826e-02,  2.35291384e-03,
        3.96445096e-02, -7.87184387e-03, -9.04843584e-03, -6.19586930e-03,
        2.12385698e-04,  8.48315004e-03,  1.41430995e-04, -3.66108987e-04,
       -2.08048578e-02, -3.90314078e-03, -5.63011738e-04, -1.54742561e-02,
       -8.80258996e-03, -1.28949126e-02,  1.85077719e-03,  1.15746455e-02,
       -1.58945434e-02, -6.05600933e-03, -5.07842889e-03, -8.57704692e-03,
       -1.56243872e-02, -2.88807228e-02, -4.80562309e-03,  2.39303010e-03,
       -7.79967988e-03, -6.13219757e-03,  8.89210962e-03, -8.48063827e-03,
       -1.49036571e-02, -1.38336350e-03, -1.29087642e-02, -1.07314195e-02,
        2.29320340e-02, -3.34079042e-02, -5.01080742e-03, -2.35576052e-02,
        1.08838445e-02,  5.60307875e-03, -2.25614756e-02,  5.41285705e-03,
       -1.19355666e-02,  3.71652935e-03,  4.19849344e-03, -2.64839679e-02,
        3.23228794e-03, -1.36037627e-02, -1.06820762e-02, -1.80231240e-02,
        7.03986560e-04, -7.48591032e-04, -7.81706907e-03, -2.51041912e-03,
       -1.22584505e-02, -1.49526056e-02, -1.75978001e-02, -2.03799829e-02,
       -7.63315335e-03,  8.41094926e-03,  1.32979443e-02, -7.97057804e-03,
       -6.82333112e-03,  5.11443149e-03, -9.97369923e-03,  2.64596120e-02,
       -3.17387923e-04, -3.16028297e-03,  4.86332364e-02, -2.44052056e-02,
        1.21265650e-02, -6.53822906e-03, -2.00167345e-03,  3.03274523e-02,
       -3.56442831e-03, -1.23755205e-02, -1.45164132e-02, -2.44796406e-02,
       -4.78981063e-03,  1.29882609e-02,  1.69144787e-05, -1.41105857e-02,
        4.12241672e-04, -2.43989117e-02, -4.47747996e-03, -2.21696496e-02,
       -1.13820126e-02, -8.20737239e-03,  1.14132790e-03, -5.10746753e-03,
        1.38636185e-02,  1.09851258e-02, -1.08398283e-02,  1.06060971e-02,
       -4.41206852e-03, -4.81368881e-03,  5.65035734e-03,  7.30639731e-05,
       -6.11405773e-03,  1.34961652e-02, -2.85400986e-03, -1.03738555e-03,
       -8.64635129e-03, -1.51316868e-03,  2.38731341e-03,  4.22109803e-03,
       -1.08393785e-02,  5.55752404e-03, -9.38999373e-03, -3.18475328e-02,
        1.58652209e-03, -9.72777326e-03, -5.62938116e-03, -1.20365489e-02,
        3.91086191e-03, -1.27867935e-02, -4.98007983e-03, -3.37281683e-03,
       -6.56139199e-03, -7.96102080e-03, -6.39415951e-03, -1.33347940e-02,
       -6.35859789e-03, -8.67873430e-03, -7.15112966e-03, -6.95148902e-03,
       -6.95725763e-03,  1.17684640e-02,  5.26077521e-04, -5.43733081e-03,
       -1.66764874e-02, -1.94910206e-02,  4.24522068e-03, -5.78784849e-03,
        9.72031266e-04,  3.05121075e-02, -5.71080763e-03,  1.02781719e-02,
       -4.43481328e-03, -1.78197883e-02, -1.49358076e-03,  1.05150742e-03,
       -5.61579177e-03, -3.27727534e-02, -8.06602929e-03, -2.00758944e-03,
        1.01748463e-02, -6.48899842e-03, -1.22040920e-02, -5.89991268e-03,
        7.76721979e-04,  1.12548657e-03, -1.26054380e-02, -3.00859101e-03,
        1.40003264e-02, -1.06438287e-02,  1.64019433e-03,  7.13875750e-03,
       -1.97734032e-02, -3.65366996e-03,  1.69222914e-02,  2.22990452e-03,
        1.69797381e-03, -8.42891540e-03, -1.09428661e-02,  2.92703905e-03,
       -8.62007216e-03,  3.25744157e-03, -1.24181164e-02,  9.59798880e-03,
       -3.80342528e-02,  1.72071962e-03,  1.97133329e-02, -2.75998637e-02,
       -7.08285579e-03,  7.11075449e-03,  2.56204954e-03,  2.36487016e-02,
        1.67605712e-03,  5.72975632e-03,  2.60515958e-02, -2.43318398e-02,
       -1.72457360e-02, -1.59217622e-02,  6.09863037e-03, -1.53884236e-02,
       -7.30494782e-03,  1.01929810e-02,  7.08759530e-03, -1.27833169e-02,
       -1.90576836e-02, -1.91473626e-02,  1.96445156e-02, -1.36017511e-02,
       -2.36017108e-02, -3.54771572e-03,  6.80617942e-03, -2.60583404e-02,
        1.72144338e-03,  8.19115341e-03,  4.56832442e-03, -6.31389534e-03,
        2.43182462e-02, -1.55679611e-02, -1.23017458e-02,  4.22729924e-03,
       -4.79000667e-03, -4.57239710e-03,  1.49746314e-02, -1.39726214e-02,
       -1.46204149e-02, -6.17774017e-03, -7.94132147e-03, -3.02263275e-02,
       -2.81917048e-03,  2.54880097e-02, -4.14641167e-04, -9.24125779e-03,
       -2.98900455e-02, -1.37752974e-02,  1.43085641e-03,  5.27592748e-03,
       -1.23366434e-03, -2.41987873e-03,  9.99961514e-03,  2.30528429e-04,
       -4.70496994e-03, -1.11308915e-03,  3.35102901e-04,  1.83781830e-03,
       -2.92641371e-02, -3.74037190e-03, -5.05004218e-03,  2.91460380e-03,
       -2.50796974e-02,  5.96363191e-03, -5.50265424e-03,  5.58395591e-03,
        2.42912211e-03, -8.35514744e-04, -6.29378250e-03, -1.20306136e-02,
        8.27270374e-03, -1.25311818e-02,  6.71579794e-04,  1.27167897e-02,
       -3.56945465e-03, -2.21954193e-03,  2.87168939e-02, -9.13841184e-03,
       -1.26612990e-03, -1.66478113e-03,  2.05420889e-02, -9.95315518e-03,
       -5.93609642e-03, -5.58133470e-03, -3.57871526e-03, -9.53967404e-03,
        5.14367223e-03,  3.58761288e-02, -8.84590670e-03, -1.39452731e-02,
        3.20481625e-03, -6.06417703e-03,  4.38823365e-03, -5.22755086e-03,
       -1.40877615e-04, -1.66139640e-02, -1.89516880e-02, -3.36553715e-03,
       -2.59934645e-03,  3.35063785e-02,  1.06829721e-02,  1.95574425e-02,
        8.70353915e-03, -4.05155169e-03, -1.56186149e-02,  1.26501322e-02,
       -1.70460548e-02, -2.87440401e-02, -1.32760210e-02, -1.47949997e-02,
       -1.37321811e-04,  2.79498519e-03,  1.03976065e-02, -1.51908146e-02,
       -6.07491797e-03, -2.95850961e-03, -2.02437877e-05, -2.54958626e-02,
       -2.00006994e-03,  9.58534237e-03, -4.58379090e-03, -9.85116977e-03,
       -5.91562269e-03,  1.12371398e-02,  8.29481892e-03, -1.28466086e-02,
       -8.16312898e-03,  1.81222539e-02, -1.95804425e-03, -3.16579215e-04,
       -2.61619799e-02, -7.80219352e-03,  1.26659768e-02, -9.01061669e-03,
       -1.35270376e-02, -1.12879490e-02, -8.74802563e-03, -8.71409290e-03,
       -2.24673608e-03, -6.43705111e-03,  9.74613940e-04,  2.94025871e-03,
       -8.05734377e-03, -3.00013050e-02,  3.13494466e-02,  1.53321251e-02,
        1.07970582e-02, -2.16321889e-02, -6.12067850e-03, -1.80940400e-03,
       -7.50846229e-03,  6.12680102e-03,  9.96938813e-03, -1.53797790e-02,
       -1.24875391e-02,  7.10066035e-03, -1.60418786e-02,  6.48375368e-03,
       -6.91916142e-03, -6.08771760e-03,  3.01300827e-03,  1.07336547e-02,
       -2.58679967e-03, -8.91958177e-03, -6.30622637e-03, -4.03595902e-02,
       -2.33625229e-02, -1.99483410e-02, -8.15862790e-03,  3.32301995e-03,
       -1.38849411e-02,  3.97805078e-03, -2.57197786e-02,  9.35611548e-04,
       -1.59703121e-02,  2.45614187e-03, -2.63375067e-03,  4.15302673e-03,
       -5.19584818e-03,  1.55238286e-02, -4.46593668e-03, -1.80152450e-02,
       -2.48525455e-03, -1.30628608e-02,  1.83548511e-03,  3.99159417e-02,
       -1.62636489e-02,  4.89803555e-04,  6.31032698e-03,  2.85263523e-04,
       -1.03500662e-02,  1.02315806e-02, -2.48695770e-03, -3.64152603e-02,
       -2.68508680e-03, -2.66775908e-03,  7.82014336e-03, -1.98997855e-02,
        1.10942582e-02, -1.82559099e-02, -9.33163799e-03, -7.17006763e-03,
       -1.77809019e-02,  8.79817363e-03, -7.12344470e-03, -1.36903496e-02],
      dtype=float32), array([ 2.03675002e-01, -1.82265773e-01, -1.32744731e-02, -1.02208227e-01,
        2.86235601e-01,  2.05170661e-02,  3.67746025e-01,  8.15668032e-02,
       -1.39518976e-01,  1.12369359e-01,  9.76226404e-02,  3.47915620e-01,
       -1.44401357e-01, -2.03015044e-01, -8.40236768e-02, -2.81478614e-01,
        4.76764375e-03,  7.78458863e-02, -9.87182930e-02, -2.05467686e-01,
        2.32829973e-01, -2.27853507e-01,  9.03868526e-02,  5.45115396e-02,
        9.04235244e-03, -1.29196998e-02,  2.11609662e-01, -8.53245109e-02,
       -2.09633887e-01,  2.58270919e-01,  7.79451132e-02, -1.98640347e-01,
        2.15344280e-01, -9.78176892e-02, -4.34211409e-03,  2.60885924e-01,
        7.59943277e-02, -1.60975188e-01, -1.07146226e-01, -1.77720636e-01,
       -7.20827878e-02,  7.74215348e-03, -3.46467435e-01,  3.23461592e-01,
        1.00290947e-01,  2.20890671e-01, -4.82414737e-02,  3.50064158e-01,
       -2.40126491e-01, -2.00933293e-01, -3.69272679e-01,  2.41937399e-01,
        2.36860275e-01, -3.00120622e-01,  2.01020673e-01,  4.60612178e-01,
        1.22784555e-01,  1.62723020e-01, -1.62812918e-01,  3.56013954e-01,
        2.28417423e-02, -1.93658620e-01, -1.06590316e-01,  3.16628367e-02,
       -2.63420671e-01, -3.04946840e-01,  2.26009846e-01,  1.88838691e-01,
        1.36383638e-01,  2.28085920e-01,  2.19593272e-01,  3.42577063e-02,
       -1.49720684e-02,  7.74702802e-02, -3.01003665e-01,  2.67936260e-01,
       -2.30184615e-01, -2.00246811e-01, -1.05053827e-01, -1.64003730e-01,
       -1.18583433e-01, -5.61631657e-02,  1.08094066e-01,  2.74023324e-01,
       -5.25490791e-02, -2.74465829e-01,  1.77777424e-01, -8.24458227e-02,
        2.67877609e-01, -2.94101804e-01,  5.44980526e-01, -9.33856517e-02,
        1.12272948e-01,  4.28724997e-02, -5.27568609e-02,  1.97464705e-01,
       -4.41869423e-02,  1.41949013e-01, -2.57689029e-01,  3.45699161e-01,
       -1.57795772e-01, -1.72386259e-01,  1.74905181e-01, -1.18366256e-01,
        1.47967622e-01, -1.29722401e-01,  1.94179207e-01, -2.27390289e-01,
       -1.16755910e-01, -2.36754548e-02,  7.38327056e-02,  1.83093786e-01,
       -3.09895337e-01, -1.90556124e-01,  1.84062168e-01,  1.28672570e-01,
       -5.03125489e-01, -2.25066051e-01, -4.00033355e-01,  1.40797317e-01,
        2.61943936e-02, -1.65150195e-01,  1.56632736e-01, -1.30051196e-01,
        2.07252391e-02, -1.80775121e-01, -1.65915057e-01,  1.86059419e-02,
        3.10897946e-01,  3.58635634e-02,  5.74092455e-02,  2.55748630e-01,
       -1.37751341e-01,  2.22381458e-01, -1.40532777e-01, -8.10545236e-02,
        7.04135075e-02, -3.41621712e-02,  2.84710824e-02,  1.73316613e-01,
        6.42788261e-02, -2.54625440e-01,  2.86126047e-01,  2.88765151e-02,
       -2.43997257e-02, -6.17523231e-02,  2.13783875e-01, -3.20996165e-01,
        7.50943320e-04, -1.06061332e-01, -2.21687511e-01,  1.94710955e-01,
       -2.74767578e-01,  5.07770851e-02, -1.74026623e-01, -2.92413831e-02,
       -2.09184960e-02, -3.96734364e-02,  1.85520679e-01,  1.93768471e-01,
        1.11731835e-01, -3.35456163e-01,  3.13220710e-01,  2.54803240e-01,
        3.21887247e-02,  6.63262978e-02,  1.48209602e-01,  5.32591522e-01,
        1.43949226e-01,  1.96105331e-01, -1.02086663e-01, -1.49419859e-01,
       -3.52771074e-01,  1.56778738e-01, -1.69007003e-01,  2.62822777e-01,
       -2.14998111e-01, -9.09404755e-02, -1.74609244e-01, -2.72440135e-01,
       -2.16157243e-01,  2.46416539e-01,  9.72288176e-02, -1.13068387e-01,
       -1.81065336e-01,  1.89354509e-01, -2.11812288e-01, -1.11430682e-01,
       -1.26068994e-01,  1.97181344e-01, -2.47782245e-01, -2.16781363e-01,
        9.71335266e-03,  6.67603463e-02, -1.14271883e-02, -2.58245736e-01,
       -1.53080970e-01, -1.64266974e-01, -4.95453268e-01,  1.06178485e-01,
       -2.24197879e-01, -1.43931340e-02, -1.84004709e-01,  9.37800705e-02,
       -1.99778885e-01,  2.69237250e-01,  7.03812689e-02,  1.64515972e-01,
        1.72623709e-01, -1.36000201e-01,  1.04676344e-01, -3.40589397e-02,
        3.21536928e-01,  2.67390460e-02,  5.18612005e-02, -3.02109212e-01,
       -2.55736679e-01,  1.29479676e-01, -1.69751495e-01,  1.15040250e-01,
       -1.76161960e-01,  1.05817422e-01, -5.81058711e-02, -1.34130433e-01,
       -3.24975520e-01,  3.84780973e-01, -2.84088820e-01,  3.71611938e-02,
        1.33616865e-01, -1.97875023e-01, -2.64397740e-01,  1.34525537e-01,
       -3.49532031e-02, -1.75852627e-01, -6.19692877e-02,  1.43587947e-01,
        1.01861462e-01,  6.86778277e-02,  2.03505978e-01, -2.61738479e-01,
       -2.27576420e-01, -2.39556909e-01, -2.35247597e-01, -6.14802316e-02,
        2.84719318e-01, -6.24780580e-02,  8.48692879e-02, -1.34123385e-01,
       -1.68273393e-02, -3.09797168e-01,  1.17311694e-01, -3.10006976e-01,
       -1.19505607e-01,  3.39555889e-01,  1.58795770e-02, -1.09535225e-01,
        3.56906235e-01,  2.45782509e-01,  1.91767827e-01,  2.84715563e-01,
        1.85519308e-01, -1.62952188e-02,  2.45070219e-01,  3.23415250e-01,
        9.07905698e-02, -2.00393364e-01, -1.95719361e-01,  5.49820364e-02,
        1.96789458e-01, -2.15055868e-01,  2.37497404e-01,  1.80794552e-01,
        2.08678737e-01,  2.60011137e-01,  2.10893005e-01, -2.11543038e-01,
       -3.02678466e-01, -3.85183804e-02, -1.68929771e-01,  2.38639057e-01,
       -2.86388695e-01,  1.41808856e-02,  2.05985576e-01,  3.39843363e-01,
       -7.32329413e-02,  6.81410637e-03,  1.65928259e-01, -9.25425589e-02,
        1.87909469e-01,  1.43654570e-01,  2.28858680e-01, -4.28705841e-01,
        7.44360983e-02,  8.46072286e-02, -3.61096077e-02,  2.51576096e-01,
       -6.51122108e-02,  8.55360404e-02, -8.60496610e-02,  6.83818245e-03,
       -9.24312249e-02, -4.35194105e-01, -2.28253663e-01,  3.51870656e-01,
       -1.90418899e-01, -4.50602658e-02,  1.08052023e-01,  3.38495612e-01,
        1.43253999e-02,  1.77971020e-01, -1.64141387e-01, -1.43273667e-01,
       -3.30105424e-01, -9.66819003e-02,  6.94224164e-02, -2.13043734e-01,
       -3.75114709e-01,  4.12312388e-01,  8.31852332e-02, -1.83197990e-01,
        5.15294075e-02, -6.22115098e-02, -1.29446700e-01, -2.54359722e-01,
        1.94844157e-01, -2.33865902e-01, -2.04892129e-01,  1.60652362e-02,
       -1.35284096e-01,  9.82945114e-02, -1.83676645e-01,  2.32111588e-01,
       -1.12035304e-01,  1.72391385e-01, -3.68205369e-01,  3.25009584e-01,
       -3.85806300e-02,  4.19241041e-01, -1.91442236e-01, -1.36702463e-01,
        6.86121266e-03,  7.14252144e-02,  7.86861628e-02, -1.35150149e-01,
       -4.70010452e-02, -6.55741245e-02,  1.53085396e-01,  5.84372552e-03,
        1.32766724e-01,  2.77446121e-01, -4.07833606e-01,  3.05411905e-01,
       -1.82976544e-01,  8.81725773e-02,  7.80124217e-02, -1.52554572e-01,
       -2.18690291e-01, -1.90394610e-01,  1.09132729e-01, -2.26580232e-01,
        5.49927175e-01,  2.69867748e-01,  5.05986549e-02,  2.58061409e-01,
        5.70889525e-02, -7.77837113e-02,  4.76801768e-02, -2.04435021e-01,
       -2.95301855e-01,  3.65291759e-02,  2.73257732e-01,  1.38217121e-01,
        8.01425874e-02,  1.79399967e-01,  3.87429595e-02, -1.83846146e-01,
       -1.86470821e-01,  2.45314658e-01, -2.19009072e-01, -1.26332566e-01,
        2.59743780e-01, -2.29499534e-01,  6.00140505e-02,  1.66726813e-01,
       -2.23867178e-01,  2.08363876e-01, -1.36989504e-01,  8.27734321e-02,
       -1.31611481e-01,  1.35652676e-01,  3.58856738e-01, -2.06877574e-01,
        1.14102394e-03, -1.80742487e-01,  1.18968770e-01, -1.91650346e-01,
       -3.29261154e-01, -1.07146837e-01,  1.97790578e-01,  1.00835830e-01,
       -2.33562529e-01, -1.21585190e-01, -2.41556674e-01, -2.62135584e-02,
       -1.25612006e-01,  6.17518835e-02,  3.36379349e-01, -1.25898004e-01,
        2.75666893e-01,  1.05800843e-02, -2.16210589e-01, -2.84034163e-02,
        7.45537281e-02,  2.02507585e-01,  1.64238095e-01,  5.74475788e-02,
        1.63939714e-01,  1.45460576e-01,  1.33963034e-01,  3.33010703e-01,
       -5.79101026e-01,  2.03514829e-01,  1.09556451e-01, -3.79000723e-01,
        1.43384218e-01,  2.07801357e-01,  5.99432923e-02,  3.48141813e-03,
       -3.32720935e-01, -1.54542089e-01,  3.11161548e-01, -3.90438825e-01,
        1.07139677e-01,  3.14588368e-01, -1.29712641e-01, -6.28559738e-02,
        2.07511812e-01, -4.79695387e-02,  7.77323693e-02,  2.09563851e-01,
       -1.35594502e-01,  7.17267543e-02,  4.71598543e-02, -2.57862769e-02,
       -2.12120831e-01, -5.06129190e-02, -1.75919056e-01, -7.08319843e-02,
       -2.89570652e-02,  8.15503150e-02,  1.05572939e-01,  1.32919252e-01,
       -2.57790715e-01, -3.74711715e-02, -3.43161561e-02, -6.15650453e-02,
        1.03554830e-01, -9.10841674e-02,  1.40479639e-01, -1.76429287e-01,
       -9.33672581e-03,  2.37044066e-01, -2.20660865e-01, -8.07818919e-02,
       -2.06807956e-01,  2.07528621e-01,  4.74306475e-03, -3.90915684e-02,
        1.33911610e-01, -3.31413187e-02,  2.70781070e-01,  1.01711981e-01,
        6.13294691e-02, -9.02776793e-02, -5.83793670e-02, -2.86400467e-01,
       -1.12872541e-01, -3.43391687e-01, -6.66634664e-02,  1.57670096e-01,
       -1.88879073e-01,  5.53962700e-02, -1.71845675e-01,  2.72965208e-02,
        6.30104765e-02, -4.21773821e-01,  1.32458672e-01, -1.09792523e-01,
       -1.18666351e-01,  5.86678125e-02, -2.52659827e-01,  1.16859652e-01,
        1.23697355e-01,  3.52716595e-01, -1.42213523e-01, -1.95782229e-01,
       -5.70744872e-02, -1.80598557e-01,  1.36395767e-01,  1.78749457e-01,
       -8.77179503e-02,  1.61452293e-01,  3.02370548e-01, -1.74791783e-01,
       -1.18662268e-01, -9.62375253e-02,  9.26522762e-02, -1.63555548e-01,
        1.72637179e-02,  2.04509526e-01, -9.75809544e-02, -1.65722862e-01,
       -1.84820652e-01,  1.51490688e-01, -1.91395700e-01, -9.07018557e-02,
        1.56353384e-01, -9.18985251e-03,  1.63883865e-01, -1.41248241e-01,
       -6.96897060e-02,  2.59158134e-01, -2.09676176e-01,  2.40276545e-01,
        1.61192253e-01,  2.33565434e-03,  1.27530053e-01, -7.28925541e-02,
        4.91800494e-02,  1.15161620e-01,  2.02465191e-01,  1.98580310e-01,
        1.39541209e-01,  2.96180338e-01, -3.56650986e-02,  1.26308367e-01,
       -1.46033302e-01, -1.18900321e-01, -1.88525006e-01, -2.53830794e-02,
       -7.75869340e-02,  3.23974103e-01, -2.40970105e-01,  1.15741149e-01,
        2.70031363e-01, -1.90191701e-01, -2.88326871e-02,  2.37639874e-01,
       -2.55570143e-01, -2.43891776e-01, -2.02955276e-01, -2.49187090e-03,
       -2.06345126e-01,  3.33227247e-01, -6.97756335e-02, -2.69747525e-02,
        8.98433253e-02,  1.42123863e-01, -2.60557950e-01,  2.81257808e-01,
        4.10831049e-02,  1.07661903e-01,  5.24143465e-02,  3.63649547e-01,
        1.12456039e-01, -6.61911592e-02,  8.45897421e-02,  2.24449560e-01,
       -2.22392008e-01, -2.16361314e-01, -1.31595194e-01,  5.07995896e-02,
        6.88569695e-02, -1.76388353e-01,  1.46781597e-02,  3.48697715e-02,
        1.72044441e-01, -2.27324918e-01,  1.58883959e-01, -8.23304057e-02,
        6.33842126e-02,  2.25922853e-01, -6.24862760e-02, -2.65567839e-01,
        3.04955512e-01, -1.34543618e-02,  3.15839320e-01, -1.51756167e-01,
       -2.59972721e-01, -9.90345702e-02, -1.29836917e-01,  1.60606518e-01,
       -2.66238898e-01,  1.69745371e-01, -2.86334362e-02,  3.42358761e-02,
        3.00237834e-02,  2.85153747e-01, -6.26122355e-02,  2.38508731e-02,
       -1.95171341e-01, -1.39235944e-01, -2.02095404e-01,  1.87303081e-01,
       -1.89854980e-01,  5.09576164e-02,  2.09352970e-01,  4.83214110e-02,
        1.70892011e-02, -1.40353873e-01,  5.45667484e-02,  4.46284860e-02,
       -5.83731420e-02,  1.95440590e-01, -9.57518294e-02,  1.55811524e-02,
        1.93337277e-01,  1.57225743e-01,  3.10724020e-01, -1.91449672e-01,
        4.69639115e-02, -1.46934413e-03,  1.35216536e-02, -2.55921809e-03,
       -1.55331254e-01,  1.09969869e-01,  2.93033659e-01, -1.90966576e-01,
        1.90735713e-01,  1.80617601e-01, -1.79537654e-01,  5.11384942e-02,
       -2.00316101e-01,  2.27963671e-01, -2.71417558e-01, -6.75648823e-02,
       -4.84764623e-03, -6.85845241e-02, -9.41090062e-02, -1.74372029e-02,
       -2.49677990e-03, -2.55963027e-01, -2.82305002e-01, -4.95327115e-02,
       -1.70772478e-01, -9.06325504e-02,  8.38308856e-02,  6.26387149e-02,
        1.33815601e-01, -4.31374311e-01,  1.06480964e-01, -2.80356765e-01,
        6.00434765e-02, -2.02267542e-01, -1.98762327e-01, -8.60923436e-03,
        1.46478154e-02,  1.08274989e-01, -6.11850098e-02,  1.27286181e-01,
       -2.20626041e-01,  1.76270396e-01,  8.51869956e-02, -8.52088705e-02,
       -1.50499344e-01,  2.89007753e-01, -8.60681832e-02, -3.30142826e-02,
       -1.29734531e-01,  2.27448061e-01, -1.41954541e-01,  1.17218085e-01,
       -3.91255617e-01,  1.20204955e-01,  1.36186570e-01,  4.90155071e-02,
        1.34399235e-01, -3.38018179e-01,  5.93010001e-02,  3.17770362e-01,
       -3.18423770e-02, -1.66602939e-01,  2.57549405e-01, -1.69876203e-01,
       -4.09383446e-01, -8.21779370e-02,  1.25728905e-01,  4.78206962e-01,
        2.07734361e-01,  2.27784008e-01,  1.14725515e-01,  8.50885138e-02,
        2.74161011e-01, -6.38174191e-02,  4.34403449e-01,  8.25153068e-02,
        2.11516947e-01, -1.48679078e-01, -3.64625938e-02,  7.15902597e-02,
       -1.40503138e-01, -1.45889893e-01, -1.48197898e-04,  1.66806400e-01,
       -1.04892440e-01,  5.27798608e-02,  4.70941961e-02, -2.36362949e-01,
        9.40982550e-02,  1.59251720e-01,  3.40146422e-01, -2.42665336e-01,
       -5.84885255e-02,  2.69126117e-01, -6.33289069e-02, -2.60188699e-01,
       -2.80895591e-01, -2.95816362e-01, -1.34550437e-01,  9.78109539e-02,
        9.43490490e-03,  2.10825801e-01, -8.40907320e-02,  4.33803871e-02,
        3.85255069e-01, -4.33655120e-02,  1.71225727e-01, -1.09965123e-01],
      dtype=float32), array([1.5291684 , 0.4258139 , 0.5835331 , 0.32509792, 0.9116624 ,
       0.5232143 , 2.0472426 , 0.2736769 , 0.81711435, 0.4733453 ,
       0.34392047, 1.3256271 , 0.6252306 , 0.47919914, 0.19682528,
       0.6193481 , 0.5995473 , 0.4033187 , 0.64418846, 0.5387347 ,
       0.27185893, 0.51920784, 0.26047173, 0.6935454 , 0.5781871 ,
       0.5033029 , 1.6433276 , 0.37123343, 0.38943198, 0.850608  ,
       0.3406927 , 0.4190109 , 0.7241026 , 0.74900186, 0.5181968 ,
       0.6955461 , 0.13750245, 1.1060554 , 0.81855005, 0.41983235,
       0.45924988, 0.42054453, 1.8967832 , 1.3356575 , 0.4358699 ,
       0.9686047 , 0.29615936, 0.77531767, 0.6260752 , 0.53398603,
       1.1295803 , 0.65646774, 0.8046262 , 0.87836623, 0.46971458,
       1.4766544 , 0.40341565, 0.4345543 , 0.4315975 , 0.9867971 ,
       0.3669688 , 0.42394865, 0.169324  , 0.37665448, 0.7725776 ,
       1.2135447 , 0.23970222, 0.62055176, 0.33003932, 0.5968307 ,
       0.5201901 , 0.5254641 , 0.10240687, 0.1497514 , 1.1404985 ,
       1.5222737 , 0.77213824, 0.30335218, 0.48482937, 0.4719141 ,
       0.43359622, 0.88732177, 0.2505942 , 0.6750648 , 0.2065913 ,
       0.9199937 , 0.4995532 , 0.48200202, 0.64254475, 1.2485136 ,
       2.2924004 , 0.2289702 , 0.4435889 , 0.20382193, 0.5289625 ,
       0.66510665, 0.24701428, 0.44900337, 0.40718132, 1.4125074 ,
       0.3970328 , 0.96078527, 0.82718277, 0.33137295, 0.68498445,
       0.32902   , 0.36547083, 1.0199157 , 0.71924555, 0.30341208,
       0.43387654, 0.9103471 , 1.6055859 , 0.36647722, 0.93466306,
       0.39059663, 3.1136997 , 1.5662943 , 1.3651489 , 0.27848074,
       0.6769802 , 0.74954605, 0.99205345, 0.5088099 , 0.21887867,
       0.29298887, 0.48815593, 0.43777174, 1.549171  , 0.1321089 ,
       0.31547943, 0.5940993 , 0.5953443 , 0.7579027 , 0.84308684,
       0.5618894 , 0.22893324, 0.30684593, 0.5331927 , 0.49697906,
       0.2472944 , 1.0960747 , 0.8357297 , 0.18486834, 0.51884335,
       0.38969156, 0.32649425, 0.8588175 , 0.7365801 , 0.3197249 ,
       0.772393  , 0.86986333, 0.56702024, 0.38040257, 0.7042744 ,
       0.26359248, 0.14862005, 0.27216348, 0.45912114, 0.7136171 ,
       0.27211908, 1.5587484 , 0.8434467 , 0.514467  , 0.20576833,
       0.32924494, 0.13261513, 3.5462117 , 0.6536406 , 0.20981656,
       0.444697  , 0.6235793 , 1.8955401 , 0.61082786, 1.8627886 ,
       0.85049707, 0.75779796, 0.5169355 , 0.45933107, 0.79490185,
       0.46805024, 0.31118238, 0.54034144, 0.3317121 , 0.67758405,
       0.5525729 , 0.7079303 , 0.39321426, 0.572431  , 0.54485595,
       0.5908002 , 0.46737754, 0.31187543, 0.3391222 , 0.2839072 ,
       0.98455805, 0.3913315 , 0.4953306 , 2.3258626 , 0.33821344,
       0.5350899 , 0.2227696 , 0.46351805, 0.2431173 , 0.89659923,
       0.6697205 , 0.5818104 , 0.5673458 , 0.5750403 , 0.33054516,
       0.2629764 , 0.35163778, 1.4093759 , 0.5667217 , 0.37286124,
       0.38080543, 0.7945717 , 0.15575472, 1.0265332 , 0.24691768,
       0.5108503 , 0.64390934, 0.8684431 , 0.42839697, 1.5058249 ,
       1.0787305 , 1.0206808 , 0.3083436 , 0.42158395, 0.3402866 ,
       0.680535  , 0.23286194, 0.42273054, 0.5220666 , 0.4645024 ,
       0.37890065, 0.4650981 , 0.24065384, 0.5878322 , 1.0245501 ,
       0.71661   , 0.9359801 , 1.2608714 , 0.8723634 , 1.3408699 ,
       0.5086071 , 0.33964768, 0.6432984 , 0.27885902, 0.51959175,
       0.4098356 , 1.2891713 , 0.53397846, 0.77793425, 0.97679305,
       1.397723  , 2.2667022 , 0.3663358 , 0.3588667 , 0.8967148 ,
       0.62342805, 0.368533  , 0.5842398 , 0.5549466 , 0.37807176,
       0.890607  , 1.1321719 , 0.30885848, 0.51740235, 1.1863164 ,
       0.8849184 , 1.3200948 , 0.38757357, 1.6157197 , 0.4962437 ,
       0.8767012 , 1.620223  , 0.5627543 , 0.5424746 , 0.8203379 ,
       0.54935265, 0.86653286, 0.7440961 , 0.35378203, 0.52175874,
       0.53918386, 0.5035674 , 0.5836242 , 0.40588087, 0.4909817 ,
       1.5626688 , 1.5472624 , 0.69195694, 0.45875648, 0.22917229,
       0.6265966 , 0.29429474, 0.6286835 , 0.3534753 , 0.61276823,
       0.1824758 , 1.5874475 , 0.5180448 , 1.336733  , 0.37976786,
       0.37270916, 0.65787727, 1.5369725 , 0.14522737, 0.5360516 ,
       0.60169655, 0.48036465, 1.2994429 , 0.5218858 , 0.42750767,
       0.87909   , 1.5347593 , 1.80812   , 0.55635136, 0.8245016 ,
       0.47697937, 0.24998507, 0.3400976 , 0.8111903 , 0.73001903,
       0.6539958 , 0.25473067, 0.31532186, 0.6324854 , 0.51353467,
       0.67492974, 0.65881354, 0.6154429 , 0.59160095, 1.025773  ,
       1.1709495 , 0.38582414, 1.8573424 , 0.9885939 , 0.78756076,
       0.2591774 , 0.23945107, 0.5444384 , 0.3844465 , 0.20235679,
       0.2557616 , 0.73038566, 0.19013874, 0.567111  , 0.5966154 ,
       1.8290639 , 0.65351486, 1.3562475 , 0.36681524, 0.7811388 ,
       0.63401985, 0.871318  , 0.6727169 , 0.2825748 , 0.46293575,
       2.0809035 , 0.29783884, 0.38746616, 0.4419997 , 0.17968872,
       0.59171057, 0.7763885 , 0.99382526, 1.2189761 , 0.35002765,
       0.6374706 , 0.2967785 , 0.5007904 , 0.40877828, 0.4387481 ,
       0.7987111 , 0.27855793, 0.43943256, 0.8978769 , 0.3343006 ,
       1.095302  , 0.428785  , 0.26054955, 0.30216545, 0.8773573 ,
       0.54504603, 0.25978315, 0.33710176, 0.34892732, 0.31070805,
       1.2710934 , 0.99447614, 0.18709825, 0.76888835, 0.64956194,
       0.48113582, 0.9190343 , 0.25023437, 0.524484  , 0.45731434,
       0.40220928, 0.32537577, 0.9261357 , 1.3992728 , 1.0974324 ,
       0.26663038, 1.179248  , 0.25224495, 1.370506  , 0.2633035 ,
       1.0959932 , 0.4448613 , 0.26473212, 0.83736664, 0.29452705,
       0.28739882, 0.61088294, 0.5349383 , 0.28024295, 0.736521  ,
       2.4877748 , 0.34045076, 0.24028449, 1.4850229 , 0.35494012,
       0.7237626 , 0.43989855, 1.2902534 , 1.2183189 , 0.9716419 ,
       0.7577541 , 0.97435105, 0.6332545 , 0.8167418 , 0.6946347 ,
       0.4917521 , 0.5596351 , 0.38581383, 0.39696905, 0.6112065 ,
       0.32900408, 0.34141725, 0.2905249 , 0.31188878, 0.5841047 ,
       0.19040976, 0.4981909 , 1.1802263 , 0.3918588 , 0.6087079 ,
       0.4521162 , 0.4800396 , 0.82799923, 0.52493054, 0.26602367,
       0.57655764, 0.63259506, 0.46928185, 0.42568082, 2.301089  ,
       0.14748518, 0.79367834, 0.69727546, 0.3266873 , 0.88238686,
       0.26585543, 0.3569687 , 0.41381153, 0.6890576 , 0.2910234 ,
       0.56337947, 1.0983858 , 0.21052794, 0.6576797 , 0.16592756,
       0.645149  , 1.4310887 , 1.1572554 , 0.87061846, 0.27590564,
       1.1360066 , 0.8143507 , 0.2882944 , 0.19422917, 0.73503584,
       2.1676779 , 0.76234436, 0.21515219, 0.36367407, 0.34996316,
       0.597229  , 0.7144151 , 0.50244886, 1.833076  , 0.15685435,
       0.27580985, 0.5007381 , 0.25373536, 0.26683137, 0.36568028,
       0.7656575 , 0.362638  , 0.9120975 , 0.503456  , 0.45296445,
       0.16132772, 0.45457506, 0.81320536, 0.19342841, 0.28806204,
       0.37710655, 0.80110985, 0.4887489 , 0.34639713, 0.5106529 ,
       0.27595523, 0.24766153, 0.23810828, 0.44209695, 1.0457673 ,
       1.1193647 , 0.89951915, 0.46661943, 0.38875434, 0.19965822,
       0.24624929, 0.2631634 , 0.87974524, 0.24760583, 0.45824108,
       0.65258974, 1.1020699 , 0.25218818, 0.61326563, 0.9933487 ,
       0.26370785, 0.6789613 , 0.39709243, 0.28434265, 0.5566785 ,
       0.5097191 , 0.985942  , 0.89704937, 0.7368938 , 0.70068336,
       0.34902897, 0.3281605 , 0.42775577, 0.6979148 , 1.0449708 ,
       1.2487515 , 0.24988319, 0.981705  , 0.537426  , 0.5020113 ,
       0.40630314, 0.63366497, 0.59273255, 0.8847864 , 0.8372667 ,
       0.32447606, 0.47626656, 0.4574444 , 1.1019856 , 0.83012813,
       0.2957058 , 0.39232004, 0.613206  , 0.31002676, 0.60329884,
       1.3761015 , 0.35001194, 0.37787658, 1.0528785 , 0.31339243,
       0.59813136, 0.8018237 , 0.77236587, 0.37768304, 0.25645804,
       0.66663474, 0.79402435, 0.2921132 , 0.9455266 , 1.2090042 ,
       1.0595058 , 1.3581858 , 0.51322365, 0.6865762 , 0.23356684,
       0.42421892, 0.5049468 , 1.0043718 , 0.57895297, 0.8282364 ,
       0.3743431 , 0.49277624, 0.7891838 , 0.34317544, 0.17745441,
       0.25012887, 0.53211963, 0.631521  , 0.58454055, 0.3492375 ,
       0.28388244, 0.5132289 , 0.3987869 , 0.6703148 , 0.44768792,
       0.5875825 , 0.25632238, 0.48018983, 0.5137345 , 0.56344956,
       0.50099313, 0.7206019 , 0.24589898, 1.454679  , 0.5363227 ,
       0.16422006, 0.62391853, 0.48308927, 0.6625799 , 0.9466168 ,
       0.4822925 , 0.79112846, 0.39448133, 0.9494046 , 0.8934371 ,
       0.6705716 , 0.27721986, 0.47539914, 0.82900554, 0.928763  ,
       0.4413217 , 0.8785621 , 0.4275134 , 0.80735296, 0.5901474 ,
       0.27490863, 0.7788582 , 0.7027397 , 0.2582225 , 0.9090747 ,
       0.7052638 , 0.68931186, 0.6345745 , 0.5638901 , 2.1188056 ,
       0.43604064, 0.43563777, 0.2244114 , 0.89155614, 0.4482065 ,
       0.45000654, 0.5670802 , 0.23444547, 0.20614102, 0.25094023,
       0.8086498 , 0.36222473, 0.62376946, 1.0418506 , 1.7401458 ,
       0.7733741 , 0.5184814 , 0.39678076, 0.67405397, 0.778296  ,
       0.32828754, 0.267086  , 1.4276757 , 0.55510336, 0.33108202,
       0.4018427 , 0.6088101 , 1.1269597 , 0.33604008, 0.8660574 ,
       0.16845036, 0.30330208, 1.3085825 , 0.5487096 , 1.8092629 ,
       0.29506788, 0.74058366, 1.4336456 , 0.63587797, 0.61167294,
       0.31764758, 0.45294955, 0.7165723 , 1.2774655 , 1.4311322 ,
       0.56080955, 0.38924074, 0.32280734, 0.6784196 , 0.3384752 ,
       0.26749006, 0.41493675, 0.32640564, 0.5878902 , 0.32346022,
       0.4313069 , 0.5283332 , 0.9821805 , 0.1840846 , 0.2673211 ,
       0.62076813, 0.5744605 , 0.30888906, 1.0379767 , 0.22496921,
       1.8823546 , 0.8661529 , 0.9937266 , 0.49045292, 0.3995292 ,
       0.2870568 , 0.5241505 , 1.2116343 , 0.33187515, 1.0033447 ,
       0.38923863, 0.51699275, 0.32464805], dtype=float32), array([[[[ 0.01794613],
         [-0.01918304],
         [ 0.03519172],
         ...,
         [-0.01687154],
         [ 0.00456832],
         [ 0.01515176]],

        [[-0.00152169],
         [ 0.03043389],
         [ 0.04485168],
         ...,
         [-0.02730357],
         [ 0.01564294],
         [-0.03213478]],

        [[ 0.02712382],
         [ 0.01288054],
         [ 0.02795936],
         ...,
         [ 0.00493571],
         [-0.00995739],
         [ 0.01188038]]],


       [[[ 0.01855104],
         [ 0.03104295],
         [ 0.01403865],
         ...,
         [-0.00233107],
         [ 0.02951425],
         [ 0.00573218]],

        [[ 0.04220886],
         [-0.02027931],
         [ 0.00569017],
         ...,
         [ 0.01033987],
         [ 0.0267135 ],
         [-0.01873086]],

        [[-0.00428346],
         [ 0.00875759],
         [ 0.00385523],
         ...,
         [-0.02424354],
         [ 0.02437839],
         [ 0.00371957]]],


       [[[ 0.00556248],
         [-0.00045251],
         [ 0.00927087],
         ...,
         [-0.009172  ],
         [ 0.01894744],
         [ 0.01865565]],

        [[ 0.02920013],
         [ 0.00393639],
         [ 0.00648544],
         ...,
         [-0.02804268],
         [ 0.00611284],
         [-0.01134116]],

        [[-0.00122923],
         [ 0.02417613],
         [ 0.04510582],
         ...,
         [ 0.00319549],
         [ 0.00025307],
         [ 0.01142636]]]], dtype=float32), array([[[[ 0.04869322,  0.04936458,  0.01719256, ...,  0.05332721,
           0.0061193 , -0.07030134],
         [ 0.02633731, -0.01803029, -0.01189808, ..., -0.02939073,
          -0.00204131, -0.04766402],
         [-0.07363052, -0.04337477,  0.029121  , ..., -0.02036421,
          -0.01177176, -0.04879652],
         ...,
         [-0.02536896, -0.06893484, -0.02890034, ..., -0.01333188,
          -0.04993685,  0.04054125],
         [-0.05647317, -0.00961563,  0.06781807, ..., -0.02561454,
           0.0598213 , -0.05860655],
         [-0.06412601,  0.06353048,  0.00735762, ..., -0.03439409,
           0.02145952,  0.06375851]]]], dtype=float32), array([0.9986115 , 1.0016339 , 1.0047065 , 0.9946087 , 0.9901803 ,
       0.9936077 , 1.0117805 , 1.0053782 , 0.9975337 , 1.0054864 ,
       0.99637306, 1.008109  , 1.0003146 , 1.0349951 , 1.0021126 ,
       0.9981109 , 0.99458003, 0.99049866, 0.9919081 , 0.9976894 ,
       1.0057228 , 0.9963512 , 0.9922233 , 1.0238363 , 0.9948872 ,
       1.0087367 , 0.99912775, 0.994694  , 0.991988  , 0.9887681 ,
       0.9930197 , 0.9899083 , 1.0059952 , 0.9988834 , 1.0074248 ,
       0.98685896, 1.0085837 , 1.0213902 , 0.99322516, 0.99990994,
       0.99398875, 1.0058056 , 0.99808365, 1.0024906 , 0.99594957,
       1.0038084 , 1.001585  , 0.9986277 , 0.9856907 , 1.0053974 ,
       0.98217994, 1.0058937 , 1.012123  , 0.99313337, 1.0085335 ,
       0.99657804, 1.017266  , 1.0023819 , 0.9908146 , 0.988538  ,
       1.0057392 , 0.99279964, 0.9981113 , 0.9992184 , 0.99815834,
       0.9968942 , 1.0123539 , 1.0001916 , 1.0039126 , 0.99561477,
       0.9983025 , 0.99637467, 0.9861847 , 0.99978155, 0.9939069 ,
       0.9949649 , 0.9999379 , 1.0064232 , 1.0051019 , 1.0089037 ,
       1.0035887 , 1.0471746 , 0.9983719 , 0.99102557, 1.0009472 ,
       1.0005643 , 0.9979523 , 1.0036088 , 0.9932498 , 0.9911511 ,
       1.0128082 , 0.99265915, 0.9956375 , 1.0038272 , 0.99102193,
       0.9992848 , 0.98761535, 1.0125109 , 1.0094206 , 1.002605  ,
       0.9936163 , 0.99563855, 1.0088981 , 0.98320794, 0.9951069 ,
       0.99988353, 0.9941049 , 1.0050757 , 1.0000108 , 0.99629056,
       1.008763  , 1.019253  , 0.9991494 , 1.001446  , 0.99720246,
       1.0041102 , 0.9953395 , 1.0181956 , 1.003338  , 0.9883483 ,
       1.0122578 , 1.0140307 , 0.99282503, 0.9924126 , 0.99693584,
       0.9899712 , 0.98882204, 0.99552655, 1.0046889 , 1.0042015 ,
       0.9942921 , 0.9936677 , 0.9933941 , 0.989576  , 0.9924467 ,
       1.0162134 , 0.99787706, 0.99325883, 0.9989552 , 1.0053345 ,
       1.008552  , 0.9940093 , 1.0143828 , 0.99932194, 0.9825086 ,
       0.9994608 , 0.99458843, 1.0449934 , 0.99455535, 0.99542546,
       0.99325436, 1.0033021 , 1.0030146 , 1.0192655 , 0.99308634,
       0.9927627 , 1.0079274 , 1.0009845 , 0.98067003, 1.0171642 ,
       0.99419147, 0.9946099 , 0.9999422 , 1.0062988 , 1.0005993 ,
       1.0139068 , 0.99988115, 0.9940186 , 1.012273  , 1.0125613 ,
       0.98815525, 0.99703836, 0.99223286, 0.99939984, 0.9972168 ,
       1.004913  , 0.99549466, 0.99347407, 1.0299739 , 1.0170004 ,
       1.0015339 , 0.9945329 , 0.9798966 , 1.0251385 , 0.9839459 ,
       0.9882884 , 1.0079408 , 1.0010239 , 1.004952  , 0.9894828 ,
       1.0038091 , 0.99761045, 1.0038424 , 0.99932873, 1.0028259 ,
       0.99465287, 0.9976914 , 0.9826966 , 1.0000179 , 1.0006257 ,
       1.0068191 , 0.992026  , 1.0207549 , 0.9945937 , 0.99573857,
       0.9999482 , 1.0130824 , 1.0177028 , 0.9956341 , 1.0005463 ,
       1.0240359 , 1.0084076 , 0.9963124 , 0.9931355 , 1.0099653 ,
       0.9957347 , 0.98628753, 1.000019  , 0.99712527, 0.99928725,
       0.99139243, 1.0167803 , 0.9944427 , 0.9870708 , 1.0253712 ,
       0.99178046, 0.99970424, 0.99944866, 0.99877626, 0.9913116 ,
       1.0076811 , 0.99074256, 0.98786676, 0.99737585, 0.994955  ,
       0.9943089 , 0.98872215, 0.9942211 , 1.0085032 , 0.9939864 ,
       1.0001225 , 1.0084234 , 1.0011489 , 0.99252605, 0.9942457 ,
       0.9965181 , 0.9946934 , 0.9989922 , 0.99470085, 1.0115814 ,
       0.9923935 , 0.9908985 , 0.98891914, 1.0013382 , 0.99578345,
       0.9868546 , 1.0011569 , 0.99689007, 0.993267  , 0.99514556,
       0.9965841 , 0.98842996, 0.9932365 , 1.0192828 , 1.00042   ,
       0.98934275, 0.9919546 , 0.99622804, 0.99734   , 0.9959232 ,
       0.99910456, 0.99794334, 1.0118978 , 1.0186026 , 0.9905898 ,
       0.9950855 , 0.9947602 , 0.99240327, 1.0195088 , 0.99944526,
       0.99565834, 0.9911533 , 1.0006247 , 0.9993245 , 0.993259  ,
       1.0038271 , 1.0023452 , 0.99877036, 1.0018559 , 1.0039846 ,
       0.99006796, 0.99611413, 0.9994999 , 0.9919503 , 1.003844  ,
       1.0087444 , 1.0187439 , 0.9880587 , 0.9998219 , 1.0045326 ,
       1.0076619 , 1.005477  , 0.99752307, 1.0043505 , 0.99563634,
       0.9979445 , 1.000923  , 0.98491293, 0.9945011 , 1.0040586 ,
       1.0074221 , 1.0165359 , 0.99889755, 0.99578863, 0.99896187,
       1.000169  , 0.99728775, 1.0041921 , 1.0139575 , 0.99717265,
       1.043732  , 0.99700654, 1.0025429 , 1.0030354 , 1.0068474 ,
       0.9953059 , 0.99642885, 0.99510217, 0.99010664, 0.9965431 ,
       0.99932635, 0.99536973, 0.99890566, 0.9980762 , 0.9975916 ,
       0.99887484, 1.0024567 , 0.9992214 , 0.9917228 , 1.0082271 ,
       0.99604005, 1.0053067 , 1.0085758 , 0.99584156, 0.99528646,
       1.0106827 , 0.99559057, 0.9873521 , 0.9978686 , 0.9885878 ,
       0.9965182 , 0.9951193 , 1.0028907 , 0.98461246, 0.9970425 ,
       0.99170774, 0.99393684, 1.0001736 , 0.98709947, 0.99913925,
       1.027462  , 1.0225834 , 1.0097073 , 1.0127234 , 1.0002505 ,
       0.9863324 , 0.99734205, 0.99705225, 0.987326  , 1.0060025 ,
       0.9926681 , 1.0059994 , 0.99883705, 1.0036788 , 1.0063845 ,
       0.9916637 , 1.0070394 , 1.0010612 , 1.0156653 , 1.002242  ,
       1.0225624 , 0.99087256, 1.0049796 , 1.0033287 , 1.020406  ,
       1.0000794 , 0.989549  , 0.987317  , 1.0089768 , 0.9997356 ,
       0.98809844, 0.9957169 , 0.99647194, 0.9941709 , 0.9929925 ,
       0.993516  , 1.0057693 , 0.9898517 , 0.9933012 , 0.99123937,
       0.99792004, 1.0020367 , 1.0066987 , 1.0047903 , 0.99808836,
       0.9984529 , 1.002748  , 1.0001619 , 0.99326855, 0.9931361 ,
       0.9974046 , 0.99947804, 1.0115498 , 0.99462974, 0.9938218 ,
       1.0078886 , 1.00034   , 0.9982322 , 0.9939781 , 1.0018486 ,
       0.99919033, 1.0108935 , 0.99808323, 1.0013846 , 0.99975884,
       1.0080782 , 0.9959328 , 1.0126365 , 0.99164915, 0.9936188 ,
       1.0189394 , 1.0053107 , 0.9972496 , 0.99610263, 0.99613893,
       0.99262875, 0.99895334, 1.0058678 , 0.98929274, 0.99816895,
       0.9859299 , 0.9962006 , 0.99866456, 1.0029587 , 0.9925956 ,
       0.99873966, 0.9930676 , 1.0007092 , 1.0058084 , 1.0045094 ,
       1.0223227 , 0.99889565, 0.9910321 , 0.98965806, 0.9931365 ,
       1.0002941 , 0.9852484 , 1.0052332 , 1.0025266 , 1.0140027 ,
       0.98890936, 0.9904527 , 1.0148025 , 1.0046436 , 0.99786896,
       1.0041962 , 0.9919412 , 0.9938111 , 1.0077603 , 1.0059221 ,
       0.9858737 , 0.9907761 , 1.00693   , 0.99375975, 0.99997824,
       0.9903355 , 0.99291   , 0.99492955, 0.9861093 , 1.0200286 ,
       0.99796367, 1.0121663 , 0.99821925, 1.0021687 , 1.0109096 ,
       0.99435925, 1.0021354 , 0.98662305, 0.9989378 , 1.0043942 ,
       1.0009446 , 1.0028055 , 1.0025667 , 0.9884405 , 0.9981877 ,
       0.9905795 , 1.0009398 , 1.0066113 , 0.9996449 , 1.0154718 ,
       1.0094355 , 1.0160924 , 0.99244845, 1.0091913 , 0.99569535,
       1.0010993 , 1.0041083 , 1.0047467 , 0.99878645, 1.0098724 ,
       0.9935832 , 0.9937332 , 1.0014994 , 0.99563307, 0.98807913,
       1.0061669 , 0.9991747 , 0.9965902 , 1.0038016 , 0.99872947,
       0.990516  , 1.0071483 , 0.9969309 , 1.0401534 , 0.9861713 ,
       0.99732345, 1.0091431 , 1.0109608 , 1.0027504 , 0.99481696,
       1.0106741 , 1.0048223 , 0.99458647, 0.98847467, 1.0132384 ,
       0.99283344, 1.0054448 , 0.9901804 , 1.0033462 , 1.0021758 ,
       1.0063164 , 1.006368  , 0.99883884, 0.989974  , 0.99679   ,
       1.0111526 , 0.98618376, 1.0040437 , 0.98662406, 1.0032344 ,
       0.9805007 , 1.012249  , 0.9953636 , 1.0054567 , 0.9925015 ,
       0.9976737 , 1.000056  , 0.99769104, 0.9884463 , 0.99296206,
       1.0155343 , 0.98917717, 1.0051383 , 1.0027417 , 0.99236256,
       0.9959771 , 1.0049483 , 1.0051546 , 0.9987371 , 1.0083888 ,
       0.99800783, 0.99206924, 1.0177019 , 0.99267375, 1.0105118 ,
       0.9917764 , 0.9997434 , 0.9990852 , 1.0144664 , 1.0061164 ,
       1.0035584 , 1.0070088 , 1.007017  , 1.0029551 , 0.99470407,
       0.99657106, 0.98687136, 0.9842172 , 1.0076075 , 0.98721665,
       0.996767  , 1.0073627 , 1.002995  , 1.0001543 , 0.99691796,
       0.9857303 , 0.9916355 , 1.0026157 , 0.9970832 , 1.0003577 ,
       1.0005541 , 1.0075294 , 0.9942455 , 1.026222  , 0.9880209 ,
       0.9989372 , 0.99339336, 1.0069203 , 1.0025213 , 0.9888799 ,
       0.98971176, 0.99851584, 0.9906077 , 0.99886394, 0.99365395,
       0.9967325 , 1.0032867 , 1.0010974 , 1.0195966 , 0.99779063,
       1.0021864 , 1.0004616 , 0.99058485, 1.0015314 , 0.9963074 ,
       0.9993037 , 0.99810725, 0.99706274, 1.0303884 , 1.0031834 ,
       0.99775004, 0.99884397, 0.9987961 , 0.99221087, 0.9855708 ,
       1.0024017 , 0.9922245 , 1.0168927 , 0.9797179 , 0.99127203,
       0.9980436 , 0.9910286 , 0.99476206, 0.9915858 , 1.0083233 ,
       1.0064825 , 0.99737906, 0.9998018 , 0.9907251 , 1.0077989 ,
       1.0037128 , 0.9993386 , 0.990948  , 0.99223125, 1.0011846 ,
       1.0031207 , 1.0010536 , 0.9936433 , 1.0046686 , 1.0088907 ,
       0.99652416, 0.99879706, 1.0017103 , 0.9930759 , 0.9935247 ,
       0.9936403 , 1.0042316 , 1.0294489 , 1.047158  , 1.0007961 ,
       0.99680823, 0.9931788 , 1.0033548 , 0.99087673, 0.99745923,
       0.9889383 , 0.99606156, 0.97942066, 0.99188465, 0.9972693 ,
       1.0297197 , 0.9905248 , 1.0121974 , 0.99615604, 0.9988633 ,
       0.9932335 , 0.99424523, 0.98987746, 1.0016439 , 0.99837315,
       1.0114431 , 0.9973602 , 1.0065818 , 1.0012255 , 0.9856721 ,
       0.99518955, 0.9976408 , 0.99905115, 0.9940551 , 0.99584186,
       0.9984337 , 0.99014056, 0.9984387 , 0.9940945 , 1.0450099 ,
       1.0010548 , 1.0042626 , 0.99468315, 0.9914818 , 0.99746704,
       0.99758106, 0.9901097 , 0.993589  , 1.0148861 , 0.9962336 ,
       0.9947548 , 1.0049479 , 0.9956906 , 0.9975382 , 1.0034896 ,
       0.9994806 , 1.0016015 , 0.9966741 , 0.99409765, 1.0112091 ,
       1.0224489 , 1.0173192 , 0.99789286], dtype=float32), array([ 5.55082411e-03,  1.07604852e-02,  1.17406575e-03, -7.33399764e-03,
       -6.90151984e-03, -3.82548873e-03, -1.60941798e-02,  6.71418523e-03,
       -3.44755873e-03,  3.46630439e-03,  2.20899354e-04, -6.85581425e-03,
       -1.79295782e-02,  3.96261644e-03,  4.78002056e-03, -2.09585670e-03,
       -3.11200554e-03, -5.47101721e-03, -2.11730157e-03, -2.47206725e-02,
        9.44425538e-03,  7.30371056e-03, -6.21521100e-03,  2.18947157e-02,
       -1.05768591e-02, -5.98065881e-03,  4.50849952e-03, -7.36559695e-03,
        1.00269970e-02, -1.61440335e-02,  1.77158020e-03,  4.72704851e-04,
        3.60417413e-03, -4.47834004e-03, -1.07679702e-02, -8.77524912e-03,
       -2.54654288e-02, -4.38752547e-02, -3.97558510e-03, -5.22758055e-04,
       -6.42504916e-03, -1.85976066e-02, -7.72068161e-04,  7.53588835e-03,
       -3.48806428e-03, -2.41421093e-03,  1.16643561e-02, -2.76147369e-02,
       -1.25201344e-02,  1.27399685e-02, -2.21131672e-03, -1.90303661e-02,
       -1.92863811e-02, -5.30130789e-03, -3.41495462e-02, -1.08564936e-03,
        1.18559068e-02,  1.18076354e-02, -6.91362098e-03, -7.49052782e-03,
        1.35448892e-02,  1.15055928e-03, -4.40436928e-03, -3.50701390e-03,
       -2.18771119e-03, -1.71543453e-02,  2.09155101e-02,  1.30935917e-02,
       -3.51181515e-02, -2.83665769e-03,  1.20879794e-02, -6.26546377e-03,
       -8.19809921e-03, -1.52321672e-03, -1.10758124e-02,  9.29443457e-04,
       -8.88491631e-05,  5.49617922e-03, -1.08574806e-02, -4.28195531e-03,
       -1.77869550e-03, -6.96477015e-03, -1.35022048e-02,  2.09594239e-03,
        1.47497943e-02,  2.07671858e-02,  1.25814963e-03, -2.57564113e-02,
        3.37931258e-03, -1.14158196e-02,  2.08887774e-02, -1.60872377e-02,
       -1.20035568e-02,  1.03560798e-02, -8.84781184e-04, -5.81405638e-03,
       -1.27465064e-02,  7.28377048e-03,  4.48485883e-03, -2.00172377e-04,
       -4.35523223e-03, -9.18668881e-03, -6.12628460e-03, -2.09160186e-02,
        3.49653908e-03, -6.71891682e-03, -6.95724459e-03, -1.94295729e-03,
        8.17621686e-03, -1.82599295e-02, -1.26673961e-02,  6.41528750e-03,
       -9.04107559e-03, -3.42212012e-03,  3.69754946e-03, -2.24969722e-03,
       -1.26009453e-02,  2.87928209e-02,  3.48178460e-03, -8.31266493e-03,
        2.67018434e-02, -6.62811799e-04, -9.04063415e-03, -9.12206247e-03,
       -1.06278621e-02, -8.80487729e-03,  6.66793727e-04, -3.11811594e-03,
       -1.92525443e-02,  2.18590721e-02, -1.08223818e-02, -3.44931567e-03,
       -1.57202780e-02, -9.73578356e-03, -1.57620776e-02,  4.33585001e-03,
       -2.43135262e-03, -1.20017966e-02,  6.62655057e-03,  4.51202411e-03,
       -9.34350397e-03, -1.05264038e-02, -1.43280001e-02, -3.13903368e-03,
        1.05161257e-02, -2.02110526e-03,  1.75662048e-04, -2.29900926e-02,
        1.21566206e-02,  8.21187906e-03, -7.63792172e-03,  6.38216082e-03,
       -1.69215351e-03, -8.13880656e-03, -5.10825729e-03, -4.71517537e-03,
       -5.80194267e-03, -8.58184509e-03, -2.16351859e-02, -9.26440116e-03,
       -3.64544243e-03,  5.40381647e-04, -3.95725146e-02,  1.16563905e-02,
        9.42203868e-03, -3.01624611e-02,  6.09377772e-03, -9.61551536e-03,
        7.07712350e-03, -3.79527779e-03, -5.36673097e-03,  2.97152996e-03,
       -4.65780264e-04, -1.64415464e-02, -3.64529504e-03,  1.51511084e-03,
        1.10091139e-02, -2.71766051e-03, -1.30092027e-02, -1.70523711e-02,
        1.41501864e-02, -4.82233055e-03, -2.19297390e-02,  3.39236595e-02,
       -1.95011143e-02, -2.68899333e-02,  9.92961787e-03,  1.26207173e-02,
        1.00236516e-02, -1.67501420e-02, -3.48893274e-03, -1.73933746e-03,
        6.38942281e-03, -1.10120662e-02,  2.93821213e-03, -7.29570445e-03,
       -2.09393539e-03, -1.28605040e-02,  6.50473172e-03, -6.13231817e-03,
       -1.30992522e-02,  1.43331243e-03, -4.78313193e-02,  1.55017280e-03,
        1.66780353e-02, -3.28090653e-04, -2.61320174e-02, -2.43836660e-02,
        7.78463902e-03,  2.49196962e-03, -1.15144467e-02,  5.25862584e-03,
       -7.86743779e-03, -1.00942666e-03,  7.38829258e-04, -5.50039578e-03,
       -1.58800352e-02,  1.73803233e-02,  1.06492918e-02, -9.95166227e-03,
       -1.36298174e-02,  1.95045620e-02,  3.08624073e-03, -3.81770288e-03,
        4.68187174e-03, -4.80212644e-03,  3.16498778e-03,  9.79563314e-03,
       -2.55053816e-03,  1.18198767e-02,  7.75674079e-03, -2.87493836e-04,
       -6.37658127e-03, -3.27928038e-03, -5.68142300e-03,  4.20876400e-04,
       -1.37711586e-02, -6.25420187e-04, -3.39405350e-02,  8.12256336e-03,
       -2.85355560e-03, -7.93164596e-03,  2.19068583e-02, -1.46355480e-03,
       -5.61367674e-03, -4.48072841e-03, -3.07115703e-03, -1.60888955e-02,
       -7.86580518e-03,  8.76490586e-03, -4.34041908e-03, -9.26432572e-03,
       -8.34655017e-03,  7.04227539e-04,  8.93871859e-03, -2.35671215e-02,
       -7.43381865e-03,  1.39850879e-03, -2.79409508e-03, -2.02802432e-04,
        2.17779283e-03,  4.97106987e-04,  7.03926617e-03, -3.83971632e-02,
       -5.98283950e-03, -1.69915687e-02, -1.05503360e-02,  9.81212873e-03,
       -6.88763941e-03, -1.04356678e-02,  7.01661222e-03, -9.61379893e-03,
        8.85148998e-03, -1.26617961e-02, -1.27608897e-02, -1.39928227e-02,
       -1.02340709e-02, -4.71587013e-03,  2.09465460e-03, -1.34764882e-02,
        2.45742733e-03, -1.04811741e-02,  4.26451024e-03, -2.62104813e-02,
       -6.72787987e-03,  6.19152794e-03,  1.47616658e-02,  3.59268929e-03,
       -3.27935372e-03, -2.75982134e-02, -9.23523679e-03, -5.63744130e-03,
        2.91164080e-03, -8.90356489e-03, -9.14180279e-03,  2.91826180e-03,
       -1.36527391e-02, -8.36764928e-03,  1.96056743e-03,  6.10495312e-03,
       -1.45281870e-02,  2.88652931e-03, -4.07824107e-03, -2.68715806e-02,
       -9.28417686e-03, -3.89295048e-03, -1.19545739e-02, -2.11604219e-02,
       -4.83102025e-03, -7.38584087e-04, -3.61923985e-02, -1.04784742e-02,
       -1.96306705e-02, -1.55584626e-02, -9.04815085e-03, -1.04028052e-02,
       -5.68332989e-03, -1.29125528e-02, -4.01377818e-03, -2.07958859e-03,
       -9.22199991e-03,  2.04316410e-03,  4.15674923e-03, -7.10720755e-03,
        2.91711360e-04, -3.74100660e-03, -1.50636295e-02, -1.43059166e-02,
       -3.66784661e-04, -1.19248619e-02, -4.38774703e-03, -2.28059967e-03,
       -7.63486372e-04, -3.69431596e-04, -3.31517286e-03, -7.95248803e-03,
       -3.02518671e-03, -1.11531150e-02, -1.24041447e-02,  8.89935717e-03,
       -2.83905002e-03, -1.39377406e-02, -8.87033902e-03, -6.90583093e-03,
       -3.35740740e-03, -4.00922494e-03,  1.84581790e-03, -1.50366649e-02,
       -1.60581470e-02, -9.76588484e-03, -1.34808905e-02, -2.59339390e-03,
        1.59797892e-02, -2.12821532e-02, -3.57955042e-03, -1.06918756e-02,
       -7.13544257e-04, -2.52627535e-03, -9.98344831e-03,  8.63697659e-03,
        2.83903982e-02, -4.75459620e-02, -2.71790735e-02,  1.34485271e-02,
       -1.98778547e-02, -1.81979407e-02,  7.10783293e-03, -3.06465337e-03,
       -7.39631476e-03, -1.18742650e-03, -1.64530333e-02,  9.64982342e-03,
        6.44560903e-03,  7.29609421e-03, -1.25381313e-02, -8.18902813e-03,
       -3.31927883e-03, -1.36542572e-02, -1.85847618e-02, -7.78352469e-03,
       -3.19693089e-02, -6.16442272e-03,  1.39591971e-03,  1.47607047e-02,
       -2.48073903e-03, -6.22255169e-03, -8.49409774e-03, -1.56320643e-03,
       -1.24573885e-02,  1.46510787e-02, -2.31785402e-02,  7.44132209e-04,
       -6.60093874e-03,  4.71849926e-03, -6.80859573e-03,  5.57187712e-03,
        3.17408587e-03, -1.10500669e-02, -6.36906736e-03, -2.20069923e-02,
       -1.12484703e-02, -5.14500169e-03,  1.10913040e-02, -3.01539479e-03,
       -4.15558601e-03, -2.72581205e-02, -3.70926689e-04, -8.11525621e-03,
       -7.81880133e-03, -7.97275826e-03, -2.98421062e-03, -9.45257582e-03,
       -9.88268759e-04, -7.24691013e-03, -2.10301224e-02,  2.49503623e-03,
       -1.86584946e-02, -1.37708643e-02,  1.07589522e-02,  2.06130762e-02,
       -1.56371817e-02, -1.20933987e-02,  2.56844959e-03,  7.26299779e-03,
       -1.26778083e-02, -7.15515576e-04,  2.92579294e-03, -8.11363291e-03,
        3.69297049e-04,  3.29821184e-03, -2.70911623e-02, -2.39013303e-02,
       -5.05867787e-03, -1.83105078e-02, -2.56488491e-02,  3.48801003e-03,
        1.84370689e-02,  3.87762603e-03, -5.09905536e-03, -6.51869457e-03,
       -4.91285417e-03, -4.75902017e-03,  7.84917455e-03, -3.43956016e-02,
       -3.76956468e-03,  4.31263819e-03, -3.94157693e-03, -2.00483799e-02,
        1.77316647e-02, -3.10884090e-04, -1.87140703e-02,  1.02013946e-02,
        1.15011826e-05, -2.41211499e-03,  5.01081627e-03, -1.85426436e-02,
       -1.66364964e-02,  2.91302260e-02, -1.74277332e-02, -2.14499235e-02,
       -1.66322477e-02, -3.77055199e-04, -5.83288027e-03,  8.77253804e-03,
        1.02966586e-02,  6.39669690e-03,  6.93777984e-04, -1.03723351e-02,
       -2.94395927e-02,  1.67000666e-02, -3.83360405e-03, -4.93875565e-03,
       -2.53595002e-02,  6.60026958e-03,  2.21832260e-03, -8.69582500e-03,
       -1.18523166e-02, -1.53537383e-02, -1.51913939e-03, -1.33884400e-02,
        3.54412128e-03,  1.18950177e-02, -2.46072165e-03,  1.85422953e-02,
        4.93208552e-03, -1.06208883e-02,  6.10137917e-03,  1.53374886e-02,
        2.27106991e-03,  6.91595161e-03, -3.54927289e-03, -1.54359220e-02,
        1.60628930e-03, -6.72594877e-03, -1.18711861e-02, -5.17283985e-03,
       -2.01255120e-02, -9.95788607e-04,  5.01219928e-03, -2.66350303e-02,
        5.80207165e-03,  8.01968761e-03, -2.29348242e-03, -2.20674779e-02,
       -7.82154500e-03,  2.17222981e-02, -1.18059684e-02,  1.75924674e-02,
        4.08873986e-03, -2.29406897e-02, -4.29135608e-03, -6.72840234e-03,
        5.61399793e-04,  4.21436271e-03,  5.76735893e-03,  1.29538064e-03,
        2.71514477e-03,  5.57515770e-04,  6.90233661e-03,  1.69497542e-03,
        9.57261678e-03, -9.83969495e-03, -3.91706405e-03, -2.61974074e-02,
       -2.57775616e-02, -5.56900445e-03, -1.82060248e-04, -1.58984996e-02,
       -2.62308586e-02, -6.26483373e-03, -9.47152171e-03,  9.04929824e-04,
        1.02699024e-03, -1.82795133e-02, -3.24483737e-02,  6.18269481e-03,
        1.24880848e-02,  1.81600358e-02, -2.06789584e-03,  6.16596546e-03,
       -1.88332088e-02,  1.65016036e-02, -2.43537803e-03, -8.56241118e-03,
       -4.59229527e-03, -6.10552868e-03, -6.16538059e-03,  3.60922352e-03,
       -2.45181937e-02, -1.68385450e-02,  1.07310351e-03,  1.35986647e-02,
       -2.02528230e-04, -1.88502707e-02, -5.64557826e-03, -5.04525471e-03,
       -1.03899864e-02, -5.90944989e-03, -1.77334286e-02, -8.40753969e-03,
       -6.57640863e-03, -2.98133167e-03, -1.34602599e-02,  2.36575003e-03,
        1.99540891e-03, -6.02456369e-03, -1.14842327e-02, -2.57457327e-02,
        1.00423172e-02, -1.76024977e-02, -1.63212251e-02, -7.97669031e-03,
       -1.89335275e-04, -7.90855382e-03,  1.67638287e-02, -5.62463375e-03,
        1.13159791e-03, -3.24035399e-02, -9.69272200e-03,  2.51025837e-02,
        8.15561600e-03,  2.41837231e-03, -1.52956613e-03, -2.20242720e-02,
        1.34618767e-02,  5.44661283e-03, -2.29600985e-02, -4.07400075e-03,
        6.04122365e-03, -8.64191726e-03,  1.29789975e-03, -1.16663259e-02,
       -2.28236336e-02, -4.04986273e-03,  5.94642770e-05,  1.90953037e-03,
       -1.01132328e-02,  9.54414625e-03, -9.13659483e-03, -3.57073708e-03,
        3.79275484e-03,  2.02642884e-02, -1.14091383e-02, -1.78019963e-02,
       -4.95732250e-03, -4.84101940e-03,  1.27847763e-02,  1.57413073e-02,
       -1.26579199e-02, -2.11413261e-02, -1.17950598e-02,  9.64057259e-03,
       -4.96127177e-03,  8.31879769e-03, -1.75757450e-03, -7.96502549e-03,
        3.06850416e-03, -5.57924435e-03, -2.68817022e-02,  1.81928929e-02,
        1.39171779e-02, -8.74137599e-03, -2.85287891e-02, -8.15209234e-04,
       -1.18417351e-03,  4.48573427e-03, -6.64982013e-03,  4.28172760e-03,
       -3.31766307e-02,  4.90216678e-03, -1.78183592e-03, -1.27883235e-04,
        1.68724991e-02, -5.22753410e-03, -1.73483696e-02, -2.88877892e-03,
       -6.28925301e-03, -4.50715646e-02, -2.43380517e-02, -1.86101533e-03,
        4.66071162e-03, -2.81495750e-02, -2.49535125e-02, -9.51640715e-04,
       -5.91590069e-03,  1.02906618e-02, -4.74867353e-04, -1.06445942e-02,
       -7.02806050e-03,  9.53822955e-03,  2.79031158e-03, -2.10071658e-03,
       -1.13043822e-02, -3.21872765e-03, -1.10782553e-02, -3.59198521e-03,
        1.12149771e-03, -5.12966095e-03, -2.31246743e-02,  8.68578849e-04,
       -1.62920402e-03,  1.17108347e-02, -1.06630046e-02, -9.31191538e-03,
       -5.62543515e-03,  1.42754463e-03,  8.37457180e-03, -9.35377786e-04,
       -3.06085665e-02, -2.07172614e-02, -6.26209239e-03, -5.84505219e-03,
       -1.87495016e-02, -1.56478677e-02, -2.36120746e-02,  2.66909576e-03,
       -4.00862610e-03, -2.28957403e-02, -1.83567703e-02, -1.29586493e-03,
       -5.17555811e-02, -1.01002110e-02,  2.19525490e-02,  6.12922385e-03,
       -9.50559916e-04, -1.99923422e-02, -4.75589186e-03,  1.37511222e-02,
       -1.07596582e-02,  1.04851286e-04,  5.22588659e-03,  6.59947097e-03,
       -6.43339893e-03, -2.49084458e-02, -2.27758717e-02, -7.10344501e-03,
        1.31667813e-03,  8.28982424e-03, -8.96698050e-03, -5.16688824e-03,
       -3.75792384e-03, -7.55838212e-03, -3.72556504e-03, -1.66296901e-03,
       -2.15915572e-02, -1.01176482e-02,  1.46005617e-03, -5.42828161e-03,
       -7.20168138e-03, -1.09826485e-02, -1.08547730e-03,  5.58344414e-03,
       -1.21221226e-02, -4.28587105e-03, -6.01948053e-03,  8.93784501e-03,
       -1.70313229e-03, -1.83626497e-03, -3.86068434e-03,  7.43053528e-03,
       -1.07018882e-02, -2.29237918e-02, -1.08204624e-02, -1.35995131e-02,
        8.63800175e-04,  1.68312131e-03, -5.90973115e-03, -8.93403403e-03],
      dtype=float32), array([-3.61242844e-03, -2.33038571e-02, -4.65452950e-03, -2.63093486e-02,
       -4.92290687e-03, -2.21768431e-02,  4.95485738e-02, -4.70934920e-02,
       -4.36885022e-02,  2.04373691e-02,  2.25770776e-03,  3.80154327e-02,
        4.24743108e-02, -2.28700694e-02, -1.90114006e-02,  1.56798102e-02,
       -8.39279819e-05,  9.38702840e-03, -4.68558781e-02, -3.88131514e-02,
       -2.92173810e-02, -2.51503941e-02,  2.58253491e-03, -3.51125449e-02,
        3.35115269e-02,  3.47773992e-02, -1.71906836e-02,  4.17534215e-03,
       -5.49303815e-02, -3.72755975e-02, -3.62533815e-02, -1.75133366e-02,
        4.19344902e-02, -2.27356218e-02, -2.97676325e-02,  1.95529517e-02,
        5.57044744e-02,  4.96528782e-02, -4.96993102e-02, -4.72428426e-02,
       -8.39255378e-03,  5.49037233e-02, -4.21865173e-02, -4.14663665e-02,
       -8.43583792e-03, -2.86606047e-02, -4.53772135e-02,  4.39726328e-03,
        7.17079565e-02, -7.45944381e-02, -4.48500440e-02, -2.59499289e-02,
        7.43695274e-02, -2.44910214e-02,  7.36068189e-02, -1.83189455e-02,
       -3.89417112e-02, -2.28204038e-02, -1.11285578e-02, -6.88287150e-03,
       -6.38934076e-02, -2.02231836e-02, -2.04759333e-02,  2.88319588e-03,
        4.45380853e-03,  4.36612479e-02, -2.00824738e-02, -4.47604805e-02,
        3.17815877e-02, -3.76109220e-02, -1.19217308e-02,  3.62339988e-02,
       -2.69749574e-02,  5.42759970e-02,  7.57256150e-03,  1.07050400e-04,
       -3.92982438e-02, -1.36609767e-02,  3.21545191e-02,  4.22723927e-02,
        1.51249254e-02,  7.51005933e-02,  3.18231869e-05, -4.35299706e-03,
       -3.32649797e-02, -4.09195051e-02, -4.41309474e-02,  4.39574197e-02,
       -4.61640134e-02, -7.80419912e-03,  5.63192833e-03,  4.84468155e-02,
       -3.70151876e-03,  2.47104019e-02,  2.20911931e-02,  2.56064497e-02,
        6.85246754e-03, -1.38326101e-02, -2.95380550e-03, -7.54293241e-03,
       -1.93221550e-02,  2.44620647e-02,  1.34591535e-02, -2.62281764e-02,
        2.40243673e-02,  2.81023420e-02, -2.78556894e-04,  1.86428502e-02,
        4.96904040e-03, -1.85594372e-02, -2.80957129e-02,  1.43697404e-03,
        1.92684960e-02, -2.97905877e-02, -3.29326652e-02,  1.08947307e-02,
        2.17588451e-02, -1.43666901e-02,  1.79428495e-02, -4.16103192e-02,
       -2.46938989e-02,  1.89784989e-02, -1.25602838e-02, -2.05722712e-02,
        1.18649807e-02,  5.88730094e-04, -4.76376377e-02, -1.72282942e-02,
        1.06330132e-02, -3.66039984e-02,  4.15159687e-02,  1.15203932e-02,
        7.31459111e-02, -1.46154463e-02, -1.49681205e-02,  3.00289094e-02,
        1.57922544e-02, -6.97204331e-03, -3.58384997e-02,  1.66875441e-02,
       -4.31395369e-03,  8.86283163e-03, -7.93366041e-03,  8.30717559e-04,
        5.89380227e-03, -1.79545558e-03, -8.22168775e-03,  6.78431541e-02,
       -3.32039706e-02, -2.23435760e-02,  5.28798886e-02, -3.01798619e-03,
        3.08593661e-02,  1.10659532e-01, -4.65281010e-02, -3.28983888e-02,
        3.30161676e-02,  9.79988184e-03,  4.76029553e-02,  4.41009272e-03,
       -1.85835864e-02, -2.03543138e-02,  7.83454850e-02,  7.96660036e-03,
       -5.63827995e-03,  6.02598228e-02, -2.08693240e-02,  1.24339955e-02,
        3.54771614e-02,  4.61371094e-02, -3.50838229e-02,  5.39491251e-02,
        2.12903600e-03,  3.41101922e-03, -4.48469408e-02, -1.12845507e-02,
       -2.76034959e-02, -1.77558083e-02,  2.34698523e-02,  5.33568226e-02,
       -4.03695442e-02, -4.10684012e-02,  1.79561172e-02, -1.00165650e-01,
       -4.94770426e-03,  5.77103198e-02, -2.68529616e-02, -2.08285935e-02,
       -4.05380875e-02, -3.86221893e-02, -1.84913515e-03, -1.00701964e-02,
       -4.15508971e-02, -1.56226661e-02,  2.36808825e-02,  2.03976762e-02,
       -7.24842958e-03,  2.23404635e-02, -1.91429984e-02, -2.67476160e-02,
        2.19880715e-02,  1.01187937e-02,  6.03968427e-02, -1.30292289e-02,
       -4.47277017e-02, -6.71275333e-03,  9.10491347e-02,  2.96993442e-02,
       -3.39056961e-02, -1.31983878e-02,  1.70695391e-02,  8.14922992e-03,
        2.47382279e-02, -1.87199134e-02,  8.36260431e-03,  9.38492641e-03,
       -1.19243031e-02, -4.51003946e-02, -5.33217900e-02, -5.22982888e-03,
        3.04224622e-02, -1.79655962e-02, -6.52184784e-02, -2.64730379e-02,
        1.70935690e-02, -2.10145302e-02, -3.28095257e-02, -2.86512636e-02,
       -1.94039177e-02, -4.09124941e-02,  2.10344922e-02, -6.05560169e-02,
        1.42263685e-04,  1.70474760e-02,  2.37259530e-02, -2.93796677e-02,
       -3.20290797e-03,  1.36148995e-02,  4.16906923e-02, -5.70738539e-02,
       -9.92883835e-03, -2.56423000e-02, -3.82846110e-02, -8.47480260e-03,
        3.37131321e-03, -1.39413048e-02, -1.14548495e-02, -8.57866276e-03,
       -8.20278097e-03,  1.25820776e-02,  1.81293767e-02, -1.51623189e-02,
       -2.38588843e-02, -5.10638170e-02,  4.73808125e-02,  2.68415478e-03,
       -1.29979262e-02,  3.58224468e-04,  2.90235616e-02, -2.76036784e-02,
       -7.38792419e-02, -9.83315986e-04, -1.94640248e-03,  8.63403454e-02,
        2.39384323e-02,  1.95395984e-02,  3.55359800e-02, -2.68568806e-02,
        4.66128290e-02,  2.69681625e-02,  5.96938133e-02,  5.25341369e-02,
       -2.44651381e-02,  3.32746431e-02,  8.45014397e-03, -3.76693793e-02,
        2.53330730e-02,  1.70801710e-02,  1.17848767e-03,  3.10241692e-02,
       -2.47282963e-02,  2.59686657e-03, -3.51588167e-02,  1.95046153e-03,
       -2.55262163e-02,  3.02393157e-02, -5.70186637e-02,  1.10583566e-02,
        1.41283125e-02, -1.46098984e-02, -1.17523561e-03,  2.71645207e-02,
       -5.10879699e-03,  9.98277217e-03,  5.63705079e-02,  8.90193135e-03,
        4.27345149e-02, -1.83358672e-03,  3.04291700e-03, -2.13668812e-02,
        3.95345129e-02,  1.28724044e-02,  1.01104872e-02,  6.40872028e-03,
       -7.13928696e-03, -3.22884507e-02, -3.69331613e-02, -3.60480021e-03,
       -1.03778681e-02, -2.68427618e-02,  7.02751353e-02, -4.32781652e-02,
       -2.49470212e-03,  1.12557877e-02,  3.09740193e-02,  3.43174078e-02,
       -3.08853127e-02,  3.35649215e-02,  4.86783823e-03, -3.95686850e-02,
        7.44296685e-02, -6.08412968e-03, -4.65112515e-02, -1.24288108e-02,
       -9.25285742e-03,  2.08221432e-02, -7.16098770e-03,  9.64113628e-04,
       -4.10454310e-02,  1.31221265e-02,  1.22585874e-02,  8.07727221e-03,
       -3.34546790e-02, -2.82940920e-02,  4.15668301e-02,  6.41765306e-03,
        8.87503102e-03, -4.33111563e-03, -5.29461615e-02, -4.30945605e-02,
       -1.41081046e-02,  4.46869321e-02,  1.46410177e-02, -8.57164152e-03,
        2.65643615e-02,  3.76836285e-02, -5.38174771e-02, -2.69263349e-02,
       -2.94072600e-03, -2.24159788e-02,  2.32188925e-02, -1.67683959e-02,
       -6.23831935e-02,  1.73628386e-02, -1.19460318e-02,  2.10264232e-03,
       -2.37549543e-02, -2.42266804e-02, -2.74395496e-02, -3.20910029e-02,
       -4.43849936e-02,  5.01481555e-02, -3.50277014e-02,  1.91982817e-02,
        2.09115334e-02,  1.78101901e-02, -1.01992274e-02,  1.96104627e-02,
        1.96377169e-02,  3.19170803e-02, -2.23573484e-02, -8.01528897e-03,
       -3.15049142e-02, -3.35956328e-02,  5.47241494e-02, -2.88808700e-02,
        2.18096152e-02,  1.96249560e-02,  6.07400686e-02,  2.27927919e-02,
        2.99850162e-02, -6.41086884e-03, -2.68864054e-02, -6.62002489e-02,
        2.67275702e-02,  2.42779218e-02, -8.16840958e-03, -1.53132947e-02,
        5.10027781e-02,  4.68163099e-03,  1.59033947e-02,  2.81087346e-02,
       -3.76637802e-02, -3.49890664e-02, -1.60732809e-02,  2.38070581e-02,
       -7.06976419e-03, -3.78536582e-02, -1.63591858e-02,  1.42297652e-02,
       -5.53658558e-03,  1.97555721e-02, -4.31503057e-02,  9.15572979e-03,
       -1.59704760e-02,  1.56755205e-02, -1.87885277e-02,  1.67563204e-02,
       -3.47384922e-02, -2.53523067e-02, -4.68517095e-02,  1.01559963e-02,
        5.16070053e-02,  1.61278341e-02,  5.87369166e-02, -4.14585173e-02,
        8.69026221e-03,  3.07267699e-02, -4.76841554e-02, -3.63038667e-02,
        2.89893541e-02,  3.64083275e-02,  1.75661109e-02,  1.04187075e-02,
       -2.47846339e-02,  3.92714180e-02, -4.81567672e-03,  5.29767806e-03,
        2.52261944e-02,  1.77059807e-02,  2.69490834e-02,  6.92564622e-02,
        7.29590235e-03, -9.66292340e-03,  4.58391458e-02, -3.11126318e-02,
       -5.83657436e-02, -6.42499095e-03, -1.00769280e-02, -4.76254299e-02,
       -6.19746512e-03, -5.75108500e-03, -1.36716533e-02,  2.40577776e-02,
        1.27311721e-02, -1.01889661e-02, -5.38577419e-03,  3.23935449e-02,
       -5.84827773e-02, -2.60891989e-02,  3.69807780e-02, -5.70045225e-03,
        1.52391791e-02,  1.18409684e-02,  1.02555973e-03, -6.55536714e-05,
        2.15730332e-02, -1.28911622e-02, -2.08707321e-02,  8.20277333e-02,
        2.61953827e-02, -1.91838592e-02, -4.76945657e-03, -2.80048121e-02,
       -1.95799619e-02, -1.27060562e-02, -1.63053758e-02,  7.06836209e-03,
        4.93198968e-02, -3.31208631e-02,  9.45921708e-03, -4.12663855e-02,
       -2.01483760e-02, -2.76646689e-02, -6.19084351e-02,  1.29939569e-02,
        1.94810014e-02,  4.60576154e-02,  2.93310564e-02,  2.23116055e-02,
        2.56097391e-02, -4.29274999e-02,  2.98073683e-02, -2.30432469e-02,
        3.18592153e-02,  1.02746719e-02, -4.11179066e-02, -3.41238976e-02,
       -3.49111902e-03, -7.05068887e-05, -1.81083884e-02, -4.01470764e-03,
       -1.78422984e-02, -2.37584393e-02,  4.76222448e-02,  1.62366387e-02,
        2.93968581e-02,  1.56779084e-02, -4.82051820e-02,  3.92838418e-02,
        2.51282211e-02, -3.44364233e-02,  2.70159636e-02,  6.29675239e-02,
       -5.03354110e-02, -4.75044809e-02,  4.09826152e-02, -4.63370681e-02,
       -3.53155495e-03,  5.14235981e-02, -2.66096536e-02, -1.81580354e-02,
       -4.29695286e-02, -2.65403707e-02, -1.84328370e-02,  9.49872890e-04,
        3.12745273e-02, -2.70449463e-02, -3.90364043e-02, -4.77424152e-02,
       -2.43362199e-04, -1.71901304e-02,  4.75656660e-03,  8.06658491e-02,
       -2.80251931e-02,  9.84006654e-03,  5.30517474e-02, -2.30269618e-02,
        3.95872667e-02, -2.30289213e-02,  3.26425433e-02, -5.46481945e-02,
       -4.49066684e-02, -2.36123037e-02,  5.84583841e-02, -2.93127019e-02,
        6.45249058e-03, -6.90420717e-03,  3.42866518e-02,  5.92628978e-02,
        5.07105179e-02, -2.19296515e-02,  1.19819567e-02, -1.87678877e-02,
       -3.83738838e-02, -6.61674794e-03, -2.62259762e-03, -3.45307365e-02,
        2.33906116e-02, -1.74592726e-03, -1.22348517e-02,  7.66000571e-03,
        1.50647908e-02,  4.40848880e-02,  2.63135042e-02, -1.04911150e-02,
        1.48885269e-02, -2.46723532e-04,  6.41818792e-02, -1.40060931e-02,
       -3.87631208e-02,  2.50419392e-03,  4.95089889e-02, -2.30089831e-03,
       -3.16817984e-02,  2.20968090e-02,  3.22587751e-02, -1.09476484e-02,
       -4.56979265e-03,  2.89652869e-02, -1.83671876e-03,  5.04013114e-02,
       -3.16492170e-02,  3.89954192e-03, -4.50705811e-02, -1.63186789e-02,
       -5.37980385e-02,  2.24848595e-02,  4.82814759e-02, -2.12582611e-02,
       -4.29519117e-02, -5.57064638e-02, -3.84103358e-02,  4.64616865e-02,
       -2.97289956e-02,  1.81922363e-03,  5.07355668e-02,  4.87937294e-02,
        6.90558329e-02, -3.61049053e-04, -1.92040820e-02,  4.07623649e-02,
        3.83264087e-02,  2.09754286e-03,  4.24816012e-02, -1.27047999e-02,
        3.36123370e-02, -1.64563488e-02, -2.54074894e-02,  1.46078197e-02,
       -6.80931807e-02, -5.56450970e-02,  5.29387817e-02,  4.29670513e-02,
       -1.35507332e-02, -6.66992599e-03, -4.99066487e-02, -5.29648103e-02,
        4.91121560e-02,  2.50997278e-03,  2.23457138e-03, -3.74883413e-02,
       -2.15832144e-02, -4.14645635e-02,  3.69949825e-02, -1.89028084e-02,
       -2.66122110e-02, -7.21377227e-03,  6.66704848e-02, -7.04470184e-03,
       -4.10568826e-02,  1.95015501e-02,  1.63449980e-02, -2.27973238e-02,
       -8.27805884e-03,  1.92148853e-02, -4.66501992e-03, -3.22534703e-02,
        1.11837924e-01, -3.53416018e-02, -3.39491442e-02, -2.39134096e-02,
       -1.55513249e-02, -3.17375362e-02,  4.40324508e-02, -4.90775593e-02,
        8.63935798e-03,  5.46887293e-02,  9.86369327e-03, -4.06154338e-03,
        1.70269459e-02,  3.02079823e-02, -4.45933677e-02,  2.68001668e-03,
        3.41466889e-02, -6.23907410e-02,  2.84013934e-02,  1.69630274e-02,
       -1.62729975e-02, -1.89077295e-02, -1.65315066e-02, -1.98597033e-02,
        1.69690158e-02, -1.11634294e-02, -9.14240163e-03, -7.67965242e-02,
       -1.14321895e-02, -1.34996390e-02,  2.82161757e-02, -1.66803133e-03,
       -6.20246958e-03,  2.88428226e-03,  3.41012143e-02,  2.25257892e-02,
        1.52047565e-02, -2.00649425e-02, -2.85793077e-02,  6.56786636e-02,
        9.08695161e-02,  4.68940996e-02,  2.01013274e-02,  3.00250817e-02,
        4.50856164e-02,  3.01240068e-02,  3.87708121e-03, -2.55932137e-02,
        5.40101118e-02,  1.47068566e-02,  3.52980979e-02, -2.79392451e-02,
        1.02115542e-01,  3.13011780e-02, -4.05644067e-02, -4.88166288e-02,
       -4.50591594e-02, -5.50246099e-04,  2.42149029e-02, -7.08256662e-02,
        2.62370259e-02, -7.75594078e-03, -1.90283880e-02, -1.00428462e-02,
        3.68731171e-02, -2.95346766e-03, -4.26906534e-03,  2.86003910e-02,
       -2.45234389e-02, -2.50606444e-02, -2.88608670e-02, -3.12058982e-02,
       -2.46716272e-02,  1.79466810e-02, -4.27828431e-02, -1.42018804e-02,
        6.51204139e-02,  9.89431515e-03,  1.35790568e-03, -3.42747271e-02,
        4.04207408e-02, -1.53943701e-02,  1.22825836e-03, -6.73834160e-02,
       -2.08593644e-02,  2.83137206e-02,  1.90108996e-02, -2.54140794e-02,
       -1.67371966e-02, -3.78993899e-02,  4.48176712e-02, -4.78964336e-02,
       -8.83866940e-03,  1.98034067e-02, -4.52637188e-02,  7.30681196e-02,
        1.10087858e-03,  3.70461941e-02,  2.93336599e-03,  3.32872123e-02],
      dtype=float32), array([0.08747148, 0.11056682, 0.08275592, 0.08676197, 0.09429184,
       0.08694913, 0.08958368, 0.09014795, 0.09716894, 0.08976815,
       0.08220889, 0.16395213, 0.08832586, 0.11016113, 0.09415645,
       0.09158769, 0.0842486 , 0.0870323 , 0.09230319, 0.10459326,
       0.08636954, 0.09748586, 0.08632417, 0.09607975, 0.09818558,
       0.08953933, 0.09065586, 0.08218189, 0.09402932, 0.0895442 ,
       0.09436814, 0.08406184, 0.12170608, 0.08884612, 0.10260977,
       0.08747166, 0.10443141, 0.10332961, 0.09947639, 0.08982904,
       0.08727797, 0.11527748, 0.08739892, 0.09077743, 0.09450911,
       0.0903781 , 0.09261893, 0.11178882, 0.10796976, 0.13001741,
       0.0989804 , 0.10551249, 0.10999545, 0.08573706, 0.10687709,
       0.08563805, 0.13619736, 0.09484468, 0.08564887, 0.08652447,
       0.11222672, 0.0860716 , 0.08196955, 0.10565911, 0.08949389,
       0.08798613, 0.09658304, 0.10087261, 0.09985986, 0.09480715,
       0.08995472, 0.09882426, 0.093118  , 0.10128342, 0.08613286,
       0.09422407, 0.08663836, 0.08923671, 0.09671517, 0.08859147,
       0.09380355, 0.1270669 , 0.11910978, 0.08251826, 0.08679364,
       0.0942099 , 0.09071366, 0.09946465, 0.10909605, 0.08335787,
       0.08330812, 0.11985826, 0.08465067, 0.12961386, 0.08664394,
       0.09080707, 0.08428585, 0.09515678, 0.09119611, 0.08427782,
       0.10317988, 0.08388057, 0.09334355, 0.08513085, 0.08777919,
       0.095819  , 0.08228005, 0.09659401, 0.08930994, 0.09426124,
       0.09904489, 0.09495329, 0.09625743, 0.09684087, 0.0945692 ,
       0.09048615, 0.09399939, 0.09501894, 0.12633714, 0.09938566,
       0.09124305, 0.09095699, 0.08234576, 0.08251625, 0.09088919,
       0.08289462, 0.09673426, 0.08431389, 0.08600713, 0.10235653,
       0.09789097, 0.08293955, 0.12019129, 0.08709762, 0.08368745,
       0.1688088 , 0.0901404 , 0.08717957, 0.08756641, 0.08804455,
       0.1005962 , 0.08422077, 0.10212965, 0.09646042, 0.08527472,
       0.08622342, 0.08532467, 0.13294025, 0.11422137, 0.08628765,
       0.10108507, 0.09419734, 0.132027  , 0.19587937, 0.09254486,
       0.08551924, 0.09422581, 0.10258836, 0.09457325, 0.10594972,
       0.09149905, 0.08804033, 0.10810354, 0.0863295 , 0.10963619,
       0.11354917, 0.08320794, 0.08646641, 0.13047855, 0.21109307,
       0.09084111, 0.10858326, 0.08511496, 0.08418004, 0.10622294,
       0.11156425, 0.08975849, 0.0836122 , 0.09513457, 0.09601852,
       0.09471164, 0.08694703, 0.08902899, 0.16015993, 0.08454613,
       0.09912717, 0.08862892, 0.08679993, 0.09256566, 0.0869524 ,
       0.08505666, 0.08967339, 0.0975372 , 0.08770151, 0.10283564,
       0.08732782, 0.09752045, 0.08229167, 0.08770492, 0.10909471,
       0.11963227, 0.08686659, 0.11175504, 0.09754618, 0.09948634,
       0.08992794, 0.13400523, 0.10115633, 0.09208217, 0.08750266,
       0.09764646, 0.09543812, 0.08369216, 0.0847071 , 0.09666651,
       0.08403473, 0.09639202, 0.09781766, 0.09786845, 0.08770829,
       0.08893461, 0.09843647, 0.09048631, 0.09370138, 0.10268284,
       0.08965707, 0.09390181, 0.08933116, 0.08884258, 0.09132227,
       0.08519413, 0.10149962, 0.08344094, 0.08721634, 0.08774658,
       0.09672385, 0.08328486, 0.08429275, 0.10462516, 0.08726595,
       0.08323469, 0.10381462, 0.10318535, 0.08355213, 0.08271866,
       0.08323061, 0.09011894, 0.08368427, 0.08932632, 0.0891032 ,
       0.08421053, 0.08568963, 0.09328555, 0.09394888, 0.12300676,
       0.09167754, 0.08425499, 0.08674973, 0.08689574, 0.08201813,
       0.10893761, 0.09025362, 0.09276208, 0.11572432, 0.1437312 ,
       0.09150591, 0.09008831, 0.08963335, 0.09031751, 0.08881135,
       0.09865681, 0.1077414 , 0.13360193, 0.09405609, 0.08281872,
       0.09551567, 0.08558603, 0.08878756, 0.10433771, 0.09408658,
       0.0894102 , 0.08585549, 0.08993691, 0.09110729, 0.08615594,
       0.11652949, 0.10582909, 0.08539081, 0.08855929, 0.11995181,
       0.08402091, 0.09194107, 0.09147969, 0.0868212 , 0.09205534,
       0.11370412, 0.11176051, 0.09058239, 0.09758016, 0.08796798,
       0.10055403, 0.09117816, 0.08448315, 0.09309309, 0.08667915,
       0.0842316 , 0.11499519, 0.09267953, 0.08249988, 0.10554648,
       0.13793425, 0.10946994, 0.08802255, 0.08746944, 0.08610322,
       0.09682209, 0.09840409, 0.11540193, 0.08225637, 0.09113229,
       0.12508701, 0.08318927, 0.10325322, 0.08953024, 0.08920653,
       0.0875643 , 0.09801681, 0.1008161 , 0.09597524, 0.0902683 ,
       0.11141085, 0.094648  , 0.09249581, 0.09092432, 0.09356555,
       0.0817849 , 0.08503465, 0.10089534, 0.09894867, 0.10292997,
       0.09660804, 0.09061506, 0.08584183, 0.08193859, 0.0837165 ,
       0.09779254, 0.09717915, 0.09312598, 0.09543885, 0.08513368,
       0.1189508 , 0.10307987, 0.13875714, 0.08746137, 0.08787347,
       0.08282851, 0.08527587, 0.09687233, 0.08578078, 0.08371364,
       0.0953583 , 0.11701911, 0.12547009, 0.09022141, 0.0899656 ,
       0.08908978, 0.08374303, 0.08982059, 0.08509024, 0.09422163,
       0.08674238, 0.08753823, 0.11657051, 0.09020554, 0.10548587,
       0.09622367, 0.08364345, 0.10688736, 0.11956733, 0.09153689,
       0.09202945, 0.08403407, 0.09336764, 0.11489894, 0.10977333,
       0.08847418, 0.08580007, 0.0876669 , 0.09307253, 0.08996472,
       0.08433335, 0.08552604, 0.09692838, 0.08725101, 0.08530612,
       0.08805177, 0.09378884, 0.09268509, 0.08972666, 0.09921076,
       0.08643263, 0.08933119, 0.11737338, 0.087983  , 0.08533659,
       0.10216335, 0.09022254, 0.09181045, 0.08489862, 0.0862268 ,
       0.10736565, 0.09407188, 0.10831917, 0.0850595 , 0.10227968,
       0.09356604, 0.09054187, 0.08480772, 0.08902681, 0.11308108,
       0.0929158 , 0.12805995, 0.09143431, 0.08874434, 0.09792256,
       0.09072025, 0.08802238, 0.09229528, 0.0862722 , 0.08287181,
       0.096188  , 0.12332047, 0.0968615 , 0.10177422, 0.08915642,
       0.09134665, 0.10189248, 0.08696957, 0.0845967 , 0.11275346,
       0.087275  , 0.08364303, 0.08786798, 0.10150421, 0.08575975,
       0.08830853, 0.08367106, 0.09533853, 0.10346522, 0.10183991,
       0.0992673 , 0.08383787, 0.08600447, 0.08772594, 0.08243264,
       0.089956  , 0.08612431, 0.09948385, 0.09742245, 0.15114284,
       0.08398315, 0.09104406, 0.10916438, 0.08715729, 0.08352438,
       0.10298133, 0.08542812, 0.08714496, 0.11671101, 0.08496564,
       0.08829332, 0.09495056, 0.13661966, 0.08687048, 0.10951559,
       0.08923989, 0.10173054, 0.09753736, 0.09304694, 0.09190451,
       0.08647111, 0.09442992, 0.09902073, 0.09053642, 0.11346018,
       0.08335025, 0.0958995 , 0.09234229, 0.08933586, 0.08486534,
       0.10806392, 0.09712248, 0.08750478, 0.08930591, 0.09757666,
       0.10306714, 0.09301462, 0.10076665, 0.11819885, 0.09580896,
       0.08550509, 0.11434241, 0.09662216, 0.11276456, 0.09763286,
       0.10962921, 0.10577261, 0.09323475, 0.08557527, 0.10264047,
       0.09165863, 0.09993484, 0.08769216, 0.08682169, 0.09137562,
       0.09892478, 0.10730918, 0.08771495, 0.10374492, 0.10072189,
       0.08996412, 0.0966636 , 0.08715113, 0.12487995, 0.11215561,
       0.09449903, 0.09956519, 0.10596082, 0.10438347, 0.0974329 ,
       0.09237088, 0.10065986, 0.0897662 , 0.08956487, 0.10954516,
       0.08374225, 0.0894447 , 0.08594119, 0.09191006, 0.10712829,
       0.09442105, 0.1161066 , 0.1014364 , 0.08242305, 0.11357223,
       0.08671935, 0.08246313, 0.08727414, 0.09457935, 0.09794512,
       0.0974324 , 0.09324934, 0.08525463, 0.09173318, 0.09017003,
       0.09007464, 0.08501541, 0.09427623, 0.1006047 , 0.0863438 ,
       0.09714957, 0.0835392 , 0.11049449, 0.08543359, 0.08678734,
       0.08660887, 0.09133021, 0.0989387 , 0.0845869 , 0.1076172 ,
       0.08987221, 0.09137959, 0.12250977, 0.08484469, 0.09473251,
       0.08555562, 0.09320381, 0.09439728, 0.09792442, 0.12524794,
       0.13656558, 0.09044214, 0.12162604, 0.09712859, 0.09021166,
       0.09151931, 0.09161957, 0.10522338, 0.11683093, 0.09280707,
       0.08607899, 0.08770219, 0.09075622, 0.08402909, 0.09556095,
       0.08639181, 0.08694006, 0.09894498, 0.08181872, 0.08491108,
       0.10983699, 0.1241773 , 0.10194574, 0.10797346, 0.08651114,
       0.09784515, 0.10486548, 0.09517644, 0.09902358, 0.09278948,
       0.08847331, 0.09272246, 0.0894642 , 0.09072448, 0.09594517,
       0.08537316, 0.08454966, 0.08497085, 0.12360436, 0.09690408,
       0.09739441, 0.09304503, 0.10405639, 0.10541253, 0.08502555,
       0.09145311, 0.08572359, 0.08885153, 0.14937653, 0.08895375,
       0.09376722, 0.08507162, 0.08382902, 0.08763075, 0.08739127,
       0.09069705, 0.0915746 , 0.10318407, 0.09123623, 0.09199089,
       0.08628333, 0.08724193, 0.10440513, 0.08364791, 0.09423621,
       0.11890996, 0.0915929 , 0.0959762 , 0.08710803, 0.08556285,
       0.08620894, 0.08695864, 0.09338071, 0.0832757 , 0.10046819,
       0.12615663, 0.09557728, 0.0825853 , 0.08677948, 0.08793399,
       0.08319642, 0.08800247, 0.10439871, 0.10013121, 0.08515697,
       0.0935493 , 0.09071685, 0.09846561, 0.11765012, 0.11820456,
       0.108344  , 0.08395131, 0.09979508, 0.09629665, 0.09606487,
       0.09199902, 0.09509694, 0.08567419, 0.0934931 , 0.11591426,
       0.13389315, 0.09575697, 0.1019659 , 0.08732427, 0.08726336,
       0.10006851, 0.08467321, 0.11658245, 0.09325063, 0.116115  ,
       0.08985432, 0.09007134, 0.08747664, 0.08944833, 0.0855407 ,
       0.09045533, 0.08403764, 0.09773549, 0.09950385, 0.10651097,
       0.08750793, 0.08440337, 0.10667472, 0.08234007, 0.12226312,
       0.09369729, 0.09758469, 0.08578324, 0.08740246, 0.08360146,
       0.08341052, 0.11499196, 0.0866347 , 0.09010338, 0.12121272,
       0.09001537, 0.0911065 , 0.08876266, 0.09266321, 0.09459654,
       0.10186036, 0.09259351, 0.10254446, 0.10772119, 0.09437159,
       0.10336094, 0.09981415, 0.1009913 ], dtype=float32), array([[[[-1.7327780e-02],
         [-1.5685525e-02],
         [ 9.6028391e-03],
         ...,
         [-2.4052445e-02],
         [-2.3704192e-02],
         [ 1.0460587e-02]],

        [[-2.7148442e-02],
         [-2.8314397e-02],
         [-1.4128139e-02],
         ...,
         [-8.2434644e-04],
         [-4.6455745e-02],
         [-2.0738902e-02]],

        [[ 1.7339645e-02],
         [-2.5067965e-02],
         [ 2.4503618e-02],
         ...,
         [-2.5722144e-02],
         [-8.9921588e-03],
         [-1.0798893e-02]]],


       [[[ 2.8930442e-02],
         [-2.5252722e-02],
         [ 6.9261077e-03],
         ...,
         [-1.2306806e-02],
         [-5.9725303e-04],
         [ 2.6579324e-02]],

        [[-1.1269483e-02],
         [ 1.0673653e-05],
         [ 3.6028914e-02],
         ...,
         [-3.8135730e-02],
         [-2.3168128e-02],
         [ 2.1065006e-02]],

        [[ 2.2583492e-02],
         [-1.6314706e-02],
         [ 1.4053837e-03],
         ...,
         [-2.0311784e-02],
         [ 1.1062655e-02],
         [ 8.9700324e-03]]],


       [[[ 2.4050592e-02],
         [-1.0566084e-03],
         [ 7.9017580e-03],
         ...,
         [-3.6592405e-02],
         [-3.8347307e-03],
         [ 1.9304277e-02]],

        [[-1.8568043e-02],
         [ 1.8588183e-02],
         [ 1.2539993e-02],
         ...,
         [-8.5294703e-03],
         [-4.4487461e-02],
         [-3.3103656e-02]],

        [[ 7.1888333e-03],
         [ 1.3178273e-02],
         [ 2.5913414e-02],
         ...,
         [-1.3759863e-02],
         [-5.2271495e-03],
         [ 4.3717413e-03]]]], dtype=float32), array([[[[ 0.04492042, -0.00714931, -0.04268027, ..., -0.00038733,
          -0.00668067, -0.04919471],
         [ 0.04916609,  0.04367913,  0.05084135, ..., -0.02542689,
           0.05199339,  0.02992641],
         [-0.04191367, -0.02124519,  0.00176212, ...,  0.02912908,
          -0.03994837, -0.04299219],
         ...,
         [ 0.05118365,  0.01631642, -0.03135632, ..., -0.0375278 ,
           0.02910323, -0.03583531],
         [ 0.06007391,  0.01682366,  0.02174331, ...,  0.05208811,
          -0.05621184, -0.03539365],
         [-0.03015519, -0.03006009, -0.03409832, ..., -0.04386938,
          -0.04314579, -0.02235753]]]], dtype=float32), array([0.987428  , 1.015876  , 0.9993453 , 1.0106465 , 1.0088454 ,
       1.0153553 , 0.98619056, 1.0230271 , 1.0217584 , 1.0104055 ,
       1.0028075 , 1.024872  , 0.98776203, 1.0045279 , 0.9899233 ,
       1.013196  , 1.0107701 , 1.0030837 , 1.018292  , 1.013493  ,
       1.0032808 , 1.0250401 , 1.0147641 , 1.0055802 , 1.0178461 ,
       1.0034032 , 1.0027688 , 1.0079354 , 1.005369  , 1.0125285 ,
       0.98973936, 1.0050626 , 1.0010345 , 1.0012606 , 1.0150081 ,
       1.0277895 , 0.9983878 , 1.007879  , 1.0019416 , 1.0031853 ,
       0.995008  , 1.0095178 , 1.0248282 , 0.9883103 , 1.0169302 ,
       1.0257107 , 0.99631387, 0.9984795 , 1.0304108 , 1.0099472 ,
       0.9938898 , 0.99931556, 1.0108812 , 1.0103487 , 1.0146037 ,
       1.0116557 , 1.0211103 , 1.027146  , 0.9962578 , 1.0146558 ,
       1.0048033 , 0.9885856 , 1.0128498 , 1.0031642 , 1.0091647 ,
       1.0101742 , 1.032582  , 1.0117024 , 1.0150552 , 1.0040778 ,
       0.997439  , 0.9929728 , 1.0039376 , 0.9891078 , 1.0010059 ,
       1.0111897 , 1.0284008 , 0.9924684 , 1.001979  , 0.99833006,
       0.9872016 , 1.0082201 , 1.0111115 , 1.0072128 , 1.0114591 ,
       0.9969762 , 1.0068278 , 0.9898711 , 1.0152322 , 1.0013149 ,
       1.007123  , 0.9889527 , 1.0180848 , 1.0313236 , 1.0234768 ,
       0.99469095, 1.0182537 , 1.0052805 , 1.0015266 , 1.0125617 ,
       1.0164156 , 0.99278504, 1.0101537 , 1.0247029 , 0.9959323 ,
       0.99583066, 0.9916888 , 1.012534  , 0.99795544, 1.0223757 ,
       0.9992019 , 1.0042415 , 0.99139833, 0.9877446 , 1.0137706 ,
       1.0054554 , 1.0106207 , 1.0100745 , 1.0112072 , 0.9848499 ,
       1.0021955 , 1.0161502 , 1.0063012 , 1.0086603 , 1.0213468 ,
       1.003069  , 1.0001156 , 1.0154132 , 1.0021617 , 1.0217519 ,
       1.0228145 , 0.97603816, 1.0120853 , 1.0062978 , 1.0097078 ,
       0.9898511 , 1.0082445 , 1.020212  , 1.0179331 , 1.0203489 ,
       0.9858698 , 1.0066628 , 1.0126868 , 0.99156284, 1.04977   ,
       1.0121262 , 0.9937085 , 1.0049133 , 1.0259522 , 0.98849267,
       1.0094281 , 1.0032653 , 0.9935652 , 1.0253949 , 0.9976614 ,
       1.0005447 , 1.0058048 , 0.98462623, 1.0164897 , 1.010042  ,
       1.0175071 , 0.99876446, 1.0153801 , 0.9979955 , 1.0098988 ,
       1.0229586 , 1.0094153 , 0.9975265 , 0.9993617 , 1.007197  ,
       0.99479187, 1.0302335 , 1.0098413 , 0.9961643 , 1.0096734 ,
       1.0240704 , 1.0046386 , 1.0068244 , 1.0129001 , 1.0028075 ,
       1.003864  , 1.0204684 , 1.005438  , 1.0205694 , 0.9994124 ,
       1.0033919 , 1.0169399 , 1.014613  , 1.0032253 , 0.99487305,
       1.0109819 , 0.9887583 , 1.0004264 , 1.000314  , 0.9863778 ,
       1.0001142 , 1.0083361 , 1.0092697 , 0.99141157, 0.98525345,
       1.003769  , 0.99121845, 1.0054909 , 0.992397  , 0.99988246,
       0.9883789 , 1.0092839 , 0.9948478 , 1.0081196 , 1.0119858 ,
       1.0054291 , 0.9955095 , 1.0181506 , 0.99898785, 1.0044883 ,
       0.99751556, 0.989142  , 1.0023525 , 1.0009153 , 1.0011015 ,
       1.0094666 , 1.0269065 , 1.0183228 , 1.0022541 , 1.0097697 ,
       0.9966698 , 0.99486476, 1.0213867 , 1.0233938 , 1.0270814 ,
       1.0115916 , 1.0123744 , 1.0122391 , 1.0304861 , 1.0191742 ,
       1.0307215 , 1.0068562 , 1.0117779 , 1.0302156 , 1.0049038 ,
       0.98802286, 1.032005  , 0.999338  , 1.0153724 , 0.9942388 ,
       1.0094497 , 1.0087764 , 0.9993011 , 1.005595  , 1.0130149 ,
       0.99498796, 1.0084918 , 1.0192324 , 0.9999296 , 1.0176121 ,
       1.0138217 , 1.0011984 , 1.0044291 , 0.99966073, 1.0091623 ,
       0.9929225 , 0.9982635 , 0.99313706, 1.0400432 , 1.0023854 ,
       1.019118  , 1.0046116 , 1.0083727 , 1.0079477 , 1.0114099 ,
       1.0278451 , 1.0018828 , 0.99637794, 0.979473  , 1.0128976 ,
       0.9968775 , 0.988232  , 1.0204922 , 0.9941512 , 1.0408083 ,
       1.001787  , 1.0071951 , 0.9968981 , 0.99668396, 1.020409  ,
       0.9973503 , 1.0199499 , 1.0060831 , 0.984737  , 1.008892  ,
       1.0106622 , 1.0104518 , 0.9924783 , 1.0278728 , 0.99688625,
       0.98814625, 0.99299383, 1.0229236 , 1.0091469 , 1.0191429 ,
       1.0022786 , 1.0065062 , 1.010445  , 1.0131499 , 1.0114878 ,
       0.9919438 , 1.0257847 , 1.0162398 , 1.0076258 , 0.99947757,
       1.010058  , 1.0172272 , 0.99363977, 1.0101428 , 1.0107136 ,
       1.0146229 , 1.0183789 , 1.0018485 , 1.0264897 , 1.016875  ,
       0.99739015, 1.0164187 , 1.0184662 , 1.0070997 , 1.0030909 ,
       1.0059431 , 1.0038981 , 1.0107069 , 1.0048102 , 0.9959417 ,
       1.035755  , 1.0024614 , 1.0148948 , 0.9927563 , 1.0091878 ,
       0.997381  , 1.0028671 , 1.0261015 , 1.0032078 , 1.0291915 ,
       0.9989917 , 1.0078368 , 0.9899648 , 0.9863146 , 1.0117029 ,
       1.0145502 , 1.007464  , 1.0031154 , 1.0074689 , 0.9940066 ,
       1.0128462 , 1.0179693 , 1.0128245 , 1.0247709 , 0.99880296,
       1.018167  , 0.9875224 , 1.0027118 , 0.9868615 , 0.98393714,
       1.0154549 , 1.0165249 , 1.0139983 , 1.0118356 , 1.0236121 ,
       1.0063921 , 1.0007521 , 1.0202769 , 0.9856134 , 0.99112934,
       1.0435677 , 1.0227506 , 1.0090119 , 1.0175385 , 1.0002662 ,
       0.9976892 , 0.9992605 , 1.0319993 , 0.99333733, 1.003276  ,
       1.0005908 , 1.0006753 , 0.99716526, 0.9909745 , 1.0039092 ,
       1.0089328 , 1.0038532 , 0.9996951 , 1.0140733 , 1.0192776 ,
       1.036582  , 0.9954671 , 0.9996956 , 0.99520624, 0.9935855 ,
       1.0135794 , 0.99476236, 1.0049738 , 0.99880016, 0.99259794,
       0.98107296, 0.99739945, 0.99082595, 1.007776  , 0.9876386 ,
       1.0041506 , 0.995359  , 1.0064882 , 1.0004983 , 0.9962245 ,
       1.0114422 , 0.9956211 , 1.0142065 , 1.0196303 , 0.98916835,
       1.0322402 , 0.98830765, 1.0235852 , 1.0193986 , 1.0116061 ,
       0.99161035, 1.023381  , 1.0122014 , 1.0063746 , 0.99667066,
       0.99013656, 1.0006754 , 1.0070174 , 1.0110245 , 0.97812605,
       0.9940974 , 0.99800897, 1.0122975 , 1.0263755 , 1.0087013 ,
       1.0092837 , 1.0126215 , 1.0009907 , 1.0000858 , 0.9933266 ,
       0.9926164 , 1.0047209 , 1.006068  , 1.0225549 , 1.0005139 ,
       1.0058509 , 0.9826182 , 1.0165219 , 1.0238742 , 0.99794275,
       1.0021169 , 0.996096  , 1.0087053 , 1.0125986 , 1.0161914 ,
       1.015728  , 1.0220709 , 1.0180186 , 1.0041265 , 1.0086898 ,
       1.0391097 , 1.0058513 , 1.010467  , 1.0238659 , 1.0226117 ,
       0.99022967, 0.9941008 , 1.0016761 , 1.0058436 , 0.9938598 ,
       1.0242882 , 1.0239601 , 1.0031365 , 1.038978  , 0.9945407 ,
       1.0040287 , 1.0053344 , 1.0222558 , 0.9990388 , 1.018155  ,
       1.002084  , 1.0313485 , 1.0246235 , 1.002848  , 1.0083107 ,
       1.0188038 , 1.0253241 , 0.99299926, 1.019051  , 1.0107133 ,
       1.0126712 , 1.0050888 , 0.9947885 , 0.9983206 , 1.023777  ,
       1.0076444 , 0.99413055, 1.004614  , 1.0078381 , 1.0120051 ,
       0.98473394, 1.0053902 , 1.0051084 , 1.0008161 , 1.0102713 ,
       0.9923141 , 0.9902262 , 1.00469   , 0.9840108 , 1.0367364 ,
       0.99836844, 1.0143756 , 1.0006698 , 0.98750806, 1.0124944 ,
       1.0039548 , 1.0024917 , 1.0025206 , 1.0067943 , 1.0424966 ,
       0.99626505, 0.99735034, 1.0069637 , 1.0107961 , 1.0051401 ,
       1.0138187 , 1.0192978 , 1.0146264 , 0.99612206, 0.99960667,
       1.0038481 , 0.98957807, 0.99971944, 0.98896205, 0.99808556,
       0.99362546, 0.9962367 , 0.96757936, 0.98681426, 1.0067406 ,
       0.9930229 , 1.0216602 , 1.005236  , 0.99673045, 1.0102499 ,
       1.027763  , 1.0020059 , 0.9979627 , 1.0255525 , 1.0163902 ,
       1.0163075 , 1.0284171 , 0.99777764, 1.0112568 , 0.9964948 ,
       0.99858123, 1.0286046 , 1.0102346 , 0.9821829 , 0.99737513,
       0.9869259 , 1.026724  , 1.0050733 , 1.009917  , 1.0058228 ,
       1.0181365 , 1.044417  , 1.0221827 , 1.0118208 , 0.9949726 ,
       0.9939787 , 1.001468  , 1.020594  , 0.9948787 , 1.0128502 ,
       1.0124834 , 1.015228  , 1.0198784 , 1.0069193 , 1.0122468 ,
       1.0186187 , 1.0149647 , 1.0149682 , 1.0000006 , 0.9991481 ,
       1.0040041 , 0.98190457, 0.997005  , 1.010441  , 0.9949238 ,
       1.0159172 , 0.99302876, 1.0009595 , 1.0229319 , 1.0206794 ,
       1.0021467 , 1.006077  , 0.9960381 , 0.9954752 , 1.0040258 ,
       0.9840053 , 0.99389625, 1.0126498 , 1.0096784 , 1.0094883 ,
       0.97857565, 0.99105006, 1.0082713 , 1.0127527 , 0.99404955,
       1.0241241 , 1.0263158 , 1.038083  , 1.008146  , 0.9870071 ,
       0.9864177 , 1.0138577 , 0.99674743, 0.992851  , 1.0066031 ,
       1.0114222 , 1.0061989 , 1.0205938 , 1.016205  , 1.0054815 ,
       1.0289706 , 1.0218747 , 1.0080884 , 1.0095072 , 1.0016719 ,
       1.043193  , 0.99795413, 1.0143112 , 1.0028569 , 0.9924465 ,
       1.0139729 , 0.9996446 , 1.0110195 , 1.00561   , 0.99049777,
       1.0190982 , 0.993432  , 0.9932775 , 0.99764204, 1.0055628 ,
       1.0204927 , 0.99086577, 1.0025883 , 0.9991983 , 0.9892131 ,
       0.9935856 , 1.0039064 , 0.9971113 , 0.9960642 , 1.0155485 ,
       1.0029609 , 1.0024642 , 0.9856438 , 0.99612993, 1.0138617 ,
       0.99663925, 1.0176644 , 1.0276318 , 0.9988465 , 1.0011076 ,
       1.0084517 , 0.9862891 , 0.99773484, 1.0040097 , 1.0156565 ,
       1.0129626 , 1.0150256 , 1.0178988 , 1.0185477 , 1.0010227 ,
       0.99961406, 1.0037246 , 1.0219506 , 1.0193303 , 0.99544114,
       1.0005374 , 0.9963701 , 1.0103396 , 1.0042558 , 0.9989798 ,
       1.0107661 , 1.0113887 , 1.001803  , 1.0024121 , 1.0106763 ,
       1.0240064 , 0.99531114, 1.0040469 , 0.997763  , 1.0026716 ,
       1.0006539 , 1.0036583 , 0.99332213, 1.0378493 , 1.0037507 ,
       1.0004746 , 1.0203404 , 0.9973971 , 1.0006831 , 1.0212464 ,
       1.0041724 , 1.0189457 , 0.9966793 , 1.0245069 , 1.0177556 ,
       1.0167716 , 1.0113089 , 0.99082136, 0.9995371 , 1.0172538 ,
       1.0064733 , 1.0052308 , 1.0075319 , 1.0009142 , 1.0254074 ,
       0.9958912 , 1.0173897 , 1.0051966 , 0.9976479 , 1.0253568 ,
       1.0101225 , 0.98946416, 0.98916465], dtype=float32), array([ 2.26165121e-03,  7.97480531e-03, -9.88044869e-03, -8.41941033e-03,
       -3.37172393e-03, -1.77914128e-02, -1.62673742e-03, -3.53938788e-02,
        1.65200252e-02,  1.67178875e-03,  3.73835745e-03,  1.28413960e-02,
        1.84092056e-02, -8.88122479e-04,  9.76090506e-03,  1.54870015e-03,
       -2.81130546e-03, -4.10753861e-03, -2.85954610e-03, -1.25510548e-03,
       -1.57529246e-02, -3.59588377e-02,  1.75582874e-03, -1.25001734e-02,
       -1.64172016e-02, -1.26798684e-02,  9.23825242e-03,  3.23109515e-03,
        1.96662406e-03, -1.38510987e-02, -7.42720556e-04, -1.01958076e-02,
        1.82917726e-03, -5.72632393e-03, -1.32871419e-02, -9.58717428e-03,
       -7.52303377e-03, -1.05222370e-02, -9.92623065e-03, -5.62652992e-03,
        2.03346787e-03, -2.15931004e-03, -6.03779964e-03, -9.87669546e-03,
        8.11488135e-04, -2.98888665e-02, -5.01649734e-03,  1.21758727e-03,
       -2.89788488e-02,  7.04781711e-03, -6.81525376e-03,  1.47081083e-02,
       -1.40763782e-02,  7.82357529e-03, -4.00115736e-03, -4.14014299e-04,
       -6.77935826e-03, -1.56439953e-02, -1.10218888e-02, -4.47963458e-03,
       -7.50184478e-03, -1.65798224e-03, -1.71119478e-02, -8.68382398e-03,
        1.55156525e-02, -1.39121376e-02, -1.79317128e-02,  1.19695524e-02,
       -5.43689355e-03, -6.56859577e-03,  2.59611360e-03,  3.32178455e-03,
       -7.13000493e-03,  3.08378832e-03,  2.26267450e-03, -1.54792406e-02,
        5.82469488e-03, -8.13013036e-03,  4.86445008e-03, -1.13587137e-02,
       -5.72697865e-03,  2.96876580e-03, -1.25353632e-03, -7.98144098e-03,
        3.48318741e-03, -2.49418733e-03,  1.10094612e-02, -5.36530698e-03,
       -5.76029299e-03,  4.57238080e-03, -1.57170705e-02, -2.90188240e-03,
        1.22587977e-03, -1.00087700e-02, -2.75307731e-03, -7.03391212e-04,
       -8.29251949e-03, -1.39131080e-02, -8.48255586e-03,  4.56676725e-03,
       -5.79083059e-03, -4.43141209e-03, -4.69091348e-03, -1.71471648e-02,
        4.50153742e-03, -1.36658195e-02, -2.33463719e-02, -1.72996689e-02,
        5.87980077e-03,  8.72617308e-03, -1.10850362e-02, -1.86599735e-02,
       -1.22197391e-02,  8.87616363e-04,  1.45096413e-03,  1.16544189e-02,
       -4.29917220e-03, -3.35715595e-03, -6.10703789e-03, -6.23056665e-03,
       -7.37458793e-03, -2.57486273e-02, -1.16674704e-02,  4.37686732e-03,
       -1.85424685e-02, -1.17972679e-02, -1.24425965e-03,  8.69746506e-03,
        3.47717851e-03,  2.92485696e-03, -1.40540046e-03, -4.76710033e-03,
        3.14272847e-03, -4.13700845e-03, -3.27303773e-03, -2.16494426e-02,
        1.05712060e-02, -1.95046254e-02, -9.02862567e-03, -5.33394283e-03,
        1.41951097e-02, -8.24691821e-03, -1.38631021e-03, -1.11340182e-02,
       -1.39238974e-02,  1.78742781e-02, -5.07892983e-04, -1.69898961e-02,
       -2.44664941e-02, -5.86620159e-03, -2.05658451e-02, -1.13036949e-02,
       -6.88718632e-03, -1.32646495e-02, -7.92028208e-04, -4.51275753e-03,
       -2.08357465e-03, -1.40442355e-02, -7.55638396e-03, -3.89702874e-03,
        8.03242717e-03, -1.16598206e-02, -1.03656901e-02, -1.11198183e-02,
       -5.35904616e-03, -3.42963412e-02,  1.62699763e-02, -3.22730280e-03,
        5.09597873e-03, -1.39130121e-02, -1.12439878e-03, -1.70866884e-02,
        6.23920467e-04, -1.74494032e-02, -1.36752147e-02, -1.56078311e-02,
       -9.43735184e-04,  9.94431321e-03, -7.89041922e-04, -2.27474980e-03,
       -3.06072831e-03, -2.31478643e-03, -1.35264182e-02, -3.23530217e-03,
        7.36434944e-04, -1.04424935e-02,  3.82692408e-04, -3.54781607e-03,
       -1.65623371e-02,  1.55520043e-03, -6.10352075e-03, -4.83116601e-03,
       -4.22268407e-03, -2.39336286e-02,  9.85196512e-03,  6.97359070e-03,
       -2.39788042e-03,  2.86246673e-03,  2.45475439e-05, -6.58682873e-03,
        1.83486938e-02, -7.71518657e-03, -6.61968661e-04, -1.54493200e-02,
       -1.96798821e-03, -1.49567844e-03,  3.05809430e-03, -6.10121759e-03,
       -9.16729739e-04, -6.36106124e-03, -1.35352630e-02, -4.10256023e-03,
        6.04348164e-03, -6.88497070e-03, -1.26303192e-02, -7.47684622e-03,
        4.56666993e-03,  2.55217799e-03, -2.68366071e-03, -8.01680144e-03,
        3.50649958e-03, -5.55698061e-03, -2.86210608e-03, -1.57168470e-02,
        1.28002809e-02,  1.59170423e-02,  6.78913528e-03,  1.79888587e-02,
       -1.82489548e-02, -2.65152613e-03,  4.45698854e-03,  7.13432254e-03,
        1.18080049e-03, -3.04234941e-02, -2.56324559e-02, -1.16538089e-02,
       -9.18793119e-03, -7.20532145e-03, -2.22705062e-02, -2.80381390e-03,
       -8.37627915e-04, -7.09687918e-03, -5.97151835e-03, -1.19307619e-02,
       -7.77017267e-04, -2.31650472e-02,  2.67662574e-03, -4.85229725e-03,
       -4.24826844e-03, -6.07622368e-03, -8.88403374e-05, -2.20102351e-03,
       -1.10936640e-02, -8.16629361e-03, -1.29396329e-02, -2.08352748e-02,
       -9.51037183e-03,  1.85933732e-03,  3.80724901e-03,  1.28798408e-03,
       -3.65582877e-03, -9.50619951e-03, -7.80169037e-04, -2.04354059e-02,
        7.25530228e-03, -1.79332029e-02, -9.69508011e-03,  5.44988131e-03,
       -4.92727477e-03,  1.18630189e-04,  7.67785311e-03,  5.23911789e-04,
       -5.48855821e-03, -5.83278621e-03, -1.61180887e-02, -1.08278794e-02,
       -1.30164986e-02, -3.20024081e-02,  1.36460681e-02, -1.54961031e-02,
       -1.72639650e-03, -1.66516136e-02,  8.93250387e-03, -1.60955098e-02,
       -2.69282348e-02, -4.11558850e-03, -1.04327649e-02, -8.05242173e-03,
        2.91212532e-03, -1.25760147e-02, -5.73050464e-03, -2.12440710e-03,
       -4.06813854e-03, -1.55199757e-02,  3.78809846e-03, -6.71960413e-03,
       -1.25297124e-03,  1.44030498e-02,  7.62043195e-03, -1.39177609e-02,
       -1.89588666e-02, -1.39717525e-02, -1.94208771e-02, -2.20969524e-02,
       -1.33681884e-02, -1.23730395e-02, -2.71612015e-02, -1.24954330e-02,
       -3.63163394e-03,  7.29734404e-03, -6.32376084e-03, -2.68278236e-05,
        6.28105830e-03, -1.25993404e-03, -9.09899734e-03, -1.52557448e-03,
       -2.11982895e-03,  8.68698675e-03,  3.26426737e-02, -9.44395433e-04,
       -4.23924020e-03,  7.91451894e-03, -1.51590575e-02, -2.61818175e-03,
        1.11227129e-02, -6.97681634e-03,  2.20730100e-02, -1.08375074e-02,
       -7.47266086e-03, -1.98566820e-02, -1.53549947e-02,  2.48336606e-03,
       -1.17356535e-02,  2.36428436e-03,  5.89446491e-03, -1.64692104e-03,
        6.07522856e-03, -1.84470229e-02, -1.28602078e-02, -1.22526400e-02,
        2.88992701e-03, -5.38271619e-03, -5.40342822e-04, -1.08177988e-02,
        7.78977992e-03,  1.34659477e-03,  8.69720150e-03, -7.43981078e-03,
        8.50260910e-03, -2.34445883e-03,  4.38237243e-04,  9.25970171e-03,
        1.65680833e-02,  1.01081850e-02, -2.15180479e-02, -1.06460899e-02,
       -1.06888004e-02, -1.26397088e-02, -9.83550586e-03,  9.36643593e-03,
       -2.35669012e-03,  5.48569625e-03,  1.97049081e-02, -1.59524120e-02,
        1.57482736e-02, -2.78627011e-03, -7.85536692e-03, -8.22071079e-03,
        1.99658703e-03, -7.52304774e-03, -3.01993527e-02, -2.06385087e-02,
       -6.34749001e-03, -1.52384192e-02, -7.03274319e-03,  2.13850476e-03,
       -7.84292724e-03, -2.58826111e-02,  3.89291393e-03, -1.74678750e-02,
       -1.94386821e-02, -7.06259627e-03, -8.97477567e-03, -7.91070051e-03,
        4.60194191e-03, -2.11728010e-02, -4.04314976e-03, -5.38161211e-03,
        1.42198894e-02, -2.33723782e-03, -2.49872766e-02,  1.66641187e-03,
       -3.36369267e-03, -1.25235412e-02, -2.89527117e-03, -2.32988466e-02,
        3.57012474e-03, -8.23225640e-03, -3.51101015e-04,  1.18573597e-02,
       -1.21692633e-02, -1.95713900e-03, -1.03778555e-03, -4.95386031e-03,
       -8.71691294e-03, -7.38864858e-03,  6.57810550e-03, -1.99527219e-02,
       -4.15179506e-03, -4.64418810e-03, -7.73325283e-03, -1.30160498e-02,
        2.27801055e-02, -3.16053703e-02, -7.71143800e-03, -1.48364231e-02,
       -1.36490846e-02, -1.26005020e-02,  1.02433925e-02, -5.73895173e-03,
        1.70585187e-03, -1.54635943e-02, -5.16970083e-03, -5.99883869e-03,
       -3.79072619e-03, -2.85938196e-03, -8.54293350e-03, -1.21651078e-02,
       -2.73149051e-02, -1.03395972e-02, -1.19849350e-02,  9.46066622e-03,
        1.54314060e-02, -2.86986902e-02, -7.50372093e-03, -1.65941641e-02,
       -7.68189598e-03, -6.80486672e-03, -2.27348935e-02,  3.54513340e-03,
       -1.32109979e-02,  2.37695858e-05, -1.10074505e-02,  1.00188293e-02,
       -7.42299529e-03,  1.24883028e-02, -1.02248341e-02, -6.05246192e-03,
        2.25139391e-02, -1.40313082e-03, -8.31910223e-03, -7.06797047e-03,
       -4.26742854e-03, -1.23669030e-02,  7.81596638e-03, -6.01960532e-03,
       -8.61597713e-03,  6.82690926e-03, -3.40627600e-03,  1.29952503e-03,
        4.52298578e-03,  8.46067350e-03, -5.90824615e-03,  4.54401970e-03,
        4.28805314e-03, -2.14996748e-02,  7.88741745e-04, -1.22152781e-02,
        2.86852196e-03, -3.95274581e-03, -2.81938724e-03, -1.03749922e-02,
       -1.08018685e-02, -8.70350283e-03, -4.26919153e-03, -1.40573143e-03,
       -1.52526740e-02, -1.44798327e-02, -6.80069299e-03, -2.14239117e-03,
       -6.89929118e-03, -2.51324587e-02, -2.64888804e-04, -2.72111548e-03,
        4.65464266e-03, -3.83955799e-02, -2.73592528e-02, -4.88925958e-04,
        3.22672469e-03, -1.23485755e-02, -1.47272053e-03, -5.58295194e-03,
       -1.11509347e-02, -2.71755736e-02, -5.35275601e-03,  1.72662511e-02,
       -1.13372644e-02, -1.09781176e-02,  8.20135232e-03, -2.56322650e-03,
        5.09367185e-03,  6.34578429e-03,  1.19683892e-02,  1.22675765e-03,
       -9.25343484e-03, -4.21266211e-03, -3.01247044e-03,  1.24275861e-02,
       -4.24805470e-03, -1.19053172e-02,  1.28220487e-02,  9.17005877e-04,
        6.75850455e-03, -5.75225847e-03, -2.42609050e-04,  5.72557736e-04,
       -5.02890861e-03, -2.24593133e-02, -5.76644996e-03, -1.91399027e-02,
       -1.57666241e-03, -8.70542508e-03, -1.20392861e-03,  6.65135216e-03,
       -5.09546185e-03, -1.11544486e-02, -6.84829149e-03,  1.40978605e-03,
       -2.73114294e-02, -8.23347014e-04, -1.93778630e-02, -8.40677787e-03,
       -3.56953926e-02,  2.79600426e-05, -3.56343063e-03, -2.68524443e-03,
       -1.98179521e-02, -1.52808931e-02, -2.54045730e-03, -1.54743083e-02,
       -4.73563181e-04, -1.46348486e-02, -1.76910553e-02, -3.71288334e-04,
       -1.00558053e-03,  1.74108073e-02,  2.60332902e-03,  2.97332788e-03,
       -1.19206924e-02, -2.24853922e-02, -8.11424456e-04, -2.24253759e-02,
       -1.00137154e-02,  8.10723286e-03, -2.32375995e-03, -6.08441746e-03,
       -4.51460145e-02, -1.38026550e-02,  1.99670102e-02, -1.44822849e-03,
        2.61075632e-03,  4.08502994e-03,  1.03507321e-02,  1.64483935e-02,
        1.65364631e-02, -1.41982418e-02,  2.22223252e-02, -6.63964311e-03,
        2.26061908e-03,  3.59516172e-03, -1.84954461e-02, -3.79662612e-03,
       -2.15548128e-02,  8.14436097e-03, -1.01968022e-02,  1.54166343e-03,
       -1.37686264e-02, -1.32666226e-03, -1.60061382e-02, -1.47307962e-02,
       -2.08874997e-02,  2.20756032e-04, -7.61963753e-03, -3.89260799e-03,
       -6.56326162e-03, -4.88668727e-03, -2.47553661e-02,  1.06458347e-02,
       -2.96211825e-03, -1.50556201e-02, -4.08431236e-03, -5.89679880e-03,
        2.09212815e-03,  8.97457637e-03,  1.25769218e-02, -9.67945065e-03,
        2.99505191e-03, -1.06534371e-02, -3.81557201e-03, -4.83965082e-03,
       -8.09385441e-03, -7.12302187e-03,  1.76044945e-02, -9.59338155e-03,
       -1.60714649e-02,  2.29733973e-03,  1.45131228e-02,  1.05214349e-06,
       -1.30734546e-02, -1.51549578e-02,  1.24990642e-02,  4.59489319e-03,
       -2.59924252e-02, -1.05733164e-02, -6.85550831e-03, -1.54653806e-02,
       -1.98784377e-02, -1.93957537e-02,  3.79469548e-03, -1.47468634e-02,
       -5.06718829e-03, -1.63987298e-02, -8.26531556e-03,  1.21953785e-02,
       -3.71997105e-03, -1.73940603e-02, -2.31708530e-02, -3.76989180e-03,
        3.96988122e-03, -9.35995393e-03,  7.55505357e-03, -6.32809242e-03,
        2.29631234e-02, -1.60985459e-02, -4.01663687e-03,  1.63137575e-03,
       -1.02144049e-03,  1.41944049e-03, -9.53258667e-03, -6.72485493e-03,
        7.74907588e-04,  2.75373901e-03, -6.00755122e-03, -1.39904767e-02,
       -5.19211637e-03, -3.48188356e-03, -5.05459774e-03,  1.06704514e-02,
       -1.97587311e-02, -1.09076723e-02, -8.49592779e-03, -3.98957590e-03,
        7.79826369e-04, -8.53468571e-03,  3.53452214e-03, -6.01253845e-03,
       -3.87201761e-03, -8.37230776e-03, -9.39568691e-03, -1.69451553e-02,
       -6.25586184e-03,  1.46773485e-02, -2.06485055e-02, -3.02118482e-04,
       -8.62798281e-03, -9.90303233e-04, -1.30736548e-03, -6.75735017e-03,
       -1.39380037e-03, -1.76220294e-02, -1.12099843e-02,  1.21988952e-02,
        7.20446184e-03,  5.61761670e-03, -7.02680741e-03, -6.39456138e-03,
       -9.17197298e-03, -1.52246905e-02,  3.43483291e-03,  1.47479190e-03,
        7.67678814e-03, -9.28902160e-03, -7.42138270e-03, -6.07760949e-03,
        6.00982821e-05,  4.98263806e-04,  7.94790965e-03, -4.01739171e-03,
        1.41042517e-04, -2.96805482e-02,  1.03982550e-03, -6.57090591e-03,
        2.44545862e-02, -1.28079643e-02, -7.52228312e-03,  3.07249487e-03,
        3.73355346e-03, -1.10082282e-02, -1.38807138e-02, -2.53087783e-04,
        2.23150896e-03, -9.20627080e-03,  4.72000474e-03, -1.31586299e-03,
       -7.26749608e-03, -6.65558910e-04,  1.20878434e-02, -7.84381386e-03,
        1.26647167e-02, -2.04065405e-02, -6.34043664e-03, -9.33075882e-03,
        7.83965178e-03, -7.66061805e-03,  2.70886570e-02, -1.94057263e-02,
       -9.86714661e-03,  1.76868145e-03, -1.22007318e-02, -1.27434812e-03,
       -9.70755145e-03, -4.24927324e-02, -1.85534284e-02,  5.32229606e-04,
       -8.25025979e-03, -3.59333754e-02, -9.98385716e-03, -1.53422393e-02],
      dtype=float32), array([-6.20066328e-03, -2.82336194e-02,  4.25800048e-02,  1.05877593e-02,
        1.98271195e-03,  1.41599625e-02,  3.08143552e-02,  1.54157737e-02,
       -1.53251998e-02,  5.56191057e-02, -3.70310768e-02,  1.21477898e-02,
        9.67239402e-03,  4.49280301e-03, -5.60625456e-02, -2.02378742e-02,
        3.54578458e-02,  1.45712923e-02,  9.07855574e-03,  2.28851358e-03,
       -1.06183197e-02,  7.69784302e-02,  4.82262671e-02,  2.62960158e-02,
       -3.45010199e-02,  7.80263916e-03, -5.97493798e-02, -3.44293453e-02,
        2.71164048e-02,  4.11011763e-02, -4.05908423e-03,  2.28959918e-02,
       -3.09198312e-02,  1.81055721e-02, -4.73673530e-02,  4.82311547e-02,
        1.58964619e-02, -2.35782284e-02, -4.93029095e-02, -1.83357559e-02,
       -1.29582360e-02, -1.71595812e-02, -5.43578379e-02,  3.46795954e-02,
       -3.28189023e-02,  2.54488438e-02, -2.85873357e-02,  4.37824056e-02,
        1.06648710e-02, -3.30463275e-02, -3.16025056e-02, -4.40748483e-02,
        3.11428457e-02, -1.59350634e-02,  3.96539122e-02, -1.51949562e-02,
       -1.05924550e-02,  8.42968076e-02,  2.40516420e-02,  3.51880454e-02,
        6.65500620e-03,  5.40465452e-02, -3.47421947e-03, -3.46288681e-02,
       -4.96896058e-02,  4.95794080e-02,  7.45425671e-02,  5.94536103e-02,
       -9.13117640e-03,  2.03236248e-02,  6.63493760e-03, -7.80671835e-03,
       -4.61013913e-02, -2.55681295e-02, -4.88577709e-02,  2.49717161e-02,
       -4.68727238e-02,  3.39222960e-02, -1.05182016e-02,  3.70570552e-03,
       -2.38976832e-02,  2.80719586e-02,  8.52836203e-03,  3.27389617e-03,
       -3.58823054e-02, -1.33709721e-02,  7.14146672e-03, -3.19778398e-02,
       -3.91011275e-02,  1.81023516e-02,  5.71412034e-04,  2.30314434e-02,
        6.13592900e-02, -1.40972259e-02, -3.08436472e-02, -8.75847787e-03,
       -1.30245406e-02,  2.53714640e-02, -7.12931808e-03, -3.06497999e-02,
       -4.53358293e-02,  1.11750010e-02,  3.67624015e-02,  5.21682054e-02,
       -3.24299447e-02, -2.59999298e-02, -3.95365544e-02, -1.39700780e-02,
       -2.00676862e-02,  3.02086044e-02, -2.62820274e-02,  3.01014204e-02,
       -1.04022082e-02, -2.76257563e-02,  1.73751302e-02,  3.30911316e-02,
        2.39352155e-02,  5.05381748e-02, -4.92458865e-02, -1.96026471e-02,
        2.48382855e-02,  6.36137500e-02,  6.23695645e-03, -3.32885385e-02,
        2.41137333e-02, -2.49790344e-02,  8.11567646e-04, -5.26162423e-02,
        6.06404559e-04,  5.09248264e-02,  3.80767435e-02,  5.42862192e-02,
       -1.95434634e-02, -4.11114097e-02, -6.46439046e-02,  3.56014743e-02,
       -2.31690798e-02,  4.64327224e-02, -8.82666837e-03,  2.89429333e-02,
        2.24460885e-02, -2.10017134e-02, -3.50876935e-02,  4.43388568e-03,
        6.68725818e-02, -1.37309558e-04, -4.90462873e-03, -3.86806577e-02,
        8.38170126e-02,  9.81874391e-03, -2.26133261e-02,  2.75101941e-02,
        4.95725172e-03, -1.61621172e-03,  4.00634184e-02, -2.47346703e-02,
       -1.58230308e-02,  5.34579903e-02,  1.98066086e-02,  2.79381610e-02,
        5.99513762e-02,  3.90144140e-02,  3.27749550e-02,  6.70951977e-03,
       -1.02593973e-02,  3.21003720e-02, -3.19474377e-02,  2.27384083e-02,
       -2.10517831e-02,  3.87754589e-02,  2.10882872e-02,  2.44135298e-02,
       -4.31820415e-02, -3.90272886e-02,  3.18045951e-02,  2.92397626e-02,
       -2.36726063e-03, -4.20865268e-02, -2.67430339e-02, -1.04237057e-03,
       -3.75858247e-02,  2.63616275e-02,  3.97499613e-02,  5.81151955e-02,
        2.74146907e-02,  4.17469330e-02,  3.14361937e-02, -2.30892375e-02,
       -4.38692905e-02, -1.27578378e-02,  4.27794419e-02,  5.63287921e-03,
       -3.64159718e-02, -1.70111377e-02,  2.86567900e-02,  6.90717325e-02,
       -5.42945880e-03,  1.75845306e-02, -3.66721004e-02, -2.61496417e-02,
       -1.64448079e-02,  2.38137078e-02, -3.39147933e-02, -6.98489416e-03,
        2.82316338e-02,  7.55858840e-03, -4.97156717e-02, -3.11452243e-02,
        3.34946718e-03, -2.34060995e-02,  3.97399291e-02,  2.56597791e-02,
       -4.84538898e-02, -2.84954300e-03, -1.78138670e-02, -3.48481983e-02,
        2.39855777e-02, -3.23115215e-02, -3.95065062e-02, -3.88476029e-02,
        5.49182482e-02, -4.03974317e-02,  3.40399030e-03, -4.36742976e-02,
       -1.48042440e-02, -2.01264285e-02, -4.25135382e-02, -2.26286910e-02,
       -2.96347123e-02,  6.77140132e-02, -2.91329920e-02,  9.78520513e-03,
       -2.81625967e-02,  3.26859243e-02,  5.69730215e-02, -7.32932240e-02,
        4.51524416e-03,  1.21360049e-02,  6.38758987e-02, -1.20698218e-03,
       -1.42561253e-02, -5.05737513e-02, -2.70475131e-02, -1.13426875e-02,
       -3.65288556e-02,  6.60649016e-02, -6.76515326e-02,  5.01465648e-02,
        5.86273596e-02,  4.56058467e-03,  1.24802103e-03, -1.46625219e-02,
        5.90674952e-02,  8.41885991e-03,  5.35868816e-02, -1.26596047e-02,
        1.28063885e-02,  2.30402425e-02,  2.56426930e-02,  9.27335862e-03,
        3.73686175e-03, -8.84650741e-03, -5.34838904e-03,  3.50483395e-02,
        3.95486737e-03, -4.09462973e-02, -2.20269114e-02,  2.33536139e-02,
        8.84314347e-03, -5.30081801e-02, -5.54662943e-02,  3.67104746e-02,
        1.06833000e-02, -1.93115771e-02,  5.16777039e-02,  2.33472195e-02,
       -2.83554178e-02,  5.04815094e-02, -7.17627164e-03,  3.34230624e-02,
       -1.57103818e-02,  1.22983884e-02, -3.70274149e-02,  2.41256077e-02,
        2.79430579e-02,  1.77185852e-02,  2.51836069e-02, -1.54899620e-02,
       -1.28316293e-02,  3.58415470e-02,  1.03745507e-02, -4.03443836e-02,
        3.05933543e-02,  9.58743785e-03, -1.13293082e-02,  3.40934061e-02,
        9.82373394e-03, -2.66220216e-02,  2.73621175e-03, -8.05488676e-02,
        4.58616652e-02,  2.07710192e-02,  4.55257632e-02,  5.62268086e-02,
        1.15242787e-02, -1.05373338e-02, -7.94748403e-03,  3.23638134e-02,
       -1.99956074e-02, -1.12670856e-02,  3.53619270e-02, -2.69638915e-02,
        4.68343124e-03, -5.64962365e-02, -2.07128152e-02,  4.28777896e-02,
        5.20673059e-02,  4.14840803e-02, -4.98830639e-02,  4.58379202e-02,
       -5.82259102e-03,  1.50688421e-02,  2.79316325e-02,  3.25158685e-02,
       -2.55762096e-02,  4.72721923e-03, -9.69439838e-03,  3.51824313e-02,
        3.31120528e-02,  2.66518537e-02,  3.14486027e-02, -1.31023331e-02,
        2.16140877e-02,  2.78798807e-02,  6.32043928e-02,  4.13791053e-02,
        1.80568136e-02,  5.09037226e-02,  3.03819473e-03,  3.24943140e-02,
        1.53306155e-02,  4.21089754e-02,  1.63234137e-02, -1.38062155e-02,
       -1.24401497e-02,  1.36014994e-03, -1.72364917e-02, -1.15818921e-02,
       -3.43200117e-02,  2.20048483e-02,  2.20847744e-02, -2.86891367e-02,
       -6.37422176e-03, -3.14901732e-02, -5.03683230e-03,  1.12190489e-02,
       -2.63983547e-03,  3.18392995e-03, -9.04299784e-03,  7.31925759e-03,
        3.70233394e-02,  3.61950486e-03, -3.71458009e-02,  3.05280648e-02,
       -5.61281554e-02, -5.10968752e-02, -8.98927101e-04,  4.86040376e-02,
        1.21009406e-02,  1.76102500e-02,  7.08204135e-02,  3.50671485e-02,
       -1.58022512e-02,  5.86840808e-02,  3.28104310e-02, -1.19140567e-02,
       -1.91441160e-02,  7.08805770e-02,  7.40957540e-03, -1.04661705e-02,
       -8.65212549e-03, -5.55592170e-03,  5.64066740e-03, -2.53870003e-02,
        1.95147991e-02,  4.55700606e-02, -8.85086425e-04, -4.73667309e-02,
       -4.51791063e-02,  5.39720282e-02,  6.32903352e-02,  1.76039506e-02,
       -3.14190029e-03,  2.96237469e-02,  1.66600998e-02,  3.25218812e-02,
        3.47994529e-02,  4.28155400e-02, -1.23430239e-02, -2.29396415e-03,
       -8.52054078e-03, -6.11251686e-03, -1.89385619e-02, -2.63557322e-02,
        4.05394658e-02, -1.45348031e-02, -2.16436498e-02, -2.92707584e-03,
        2.45235171e-02, -7.87385833e-03,  3.99083756e-02,  1.95072312e-02,
       -5.10044657e-02,  4.11017798e-02,  2.52548121e-02,  5.95090501e-02,
        8.51552561e-03,  3.07192281e-02, -2.94467956e-02,  1.01833567e-02,
       -2.47564018e-02,  5.45695834e-02,  2.41867620e-02,  2.09446922e-02,
        2.02402496e-03,  3.45408022e-02,  6.32368773e-03,  1.96602996e-02,
        3.43343690e-02, -7.36059900e-03, -3.39219272e-02, -4.70620347e-03,
       -3.45310234e-02,  2.90122498e-02, -2.63866484e-02,  6.97899563e-03,
       -2.35515628e-02, -3.55860824e-03, -1.80820432e-02, -1.20294997e-02,
       -1.79745983e-02,  2.87006497e-02,  3.57007012e-02, -1.90572086e-04,
       -2.21242253e-02, -2.05824664e-03,  3.81457694e-02,  4.43963036e-02,
        6.59708530e-02,  3.53290364e-02,  3.89010645e-02,  3.57865021e-02,
       -4.77011018e-02,  3.09946444e-02, -1.65228266e-02,  4.07958850e-02,
        3.46231312e-02, -4.15130295e-02,  7.57526373e-03,  3.11737768e-02,
        4.85704131e-02,  3.06599513e-02, -1.44976247e-02,  4.55419384e-02,
        4.00108695e-02,  7.77585665e-03, -3.82260904e-02, -1.72180142e-02,
        1.64536759e-02, -2.32566684e-03,  4.34214771e-02,  4.39423397e-02,
        2.95072496e-02,  8.73146430e-02, -1.86399259e-02,  4.20750715e-02,
       -2.58592907e-02,  6.19663410e-02, -1.25224818e-03, -3.25294957e-02,
        3.77101786e-02,  5.28225116e-02, -1.50806587e-02, -4.45377417e-02,
       -7.43868500e-02,  3.15360911e-02,  3.72255966e-02,  1.80516969e-02,
       -4.48729135e-02,  1.50024844e-02, -4.19919714e-02, -9.86126368e-04,
        1.57443173e-02,  2.14568786e-02, -3.82919535e-02, -4.62992452e-02,
       -2.79937554e-02,  5.01681902e-02,  4.24101204e-02,  2.98888665e-02,
       -1.30333344e-03, -3.08004972e-02, -2.90320814e-03,  8.36649071e-03,
        5.02759637e-03,  5.41945035e-03, -4.02186252e-02, -8.80167633e-03,
        1.27946194e-02,  5.60139194e-02, -2.33876333e-02,  3.33018228e-02,
       -1.80558860e-02,  2.31829025e-02, -2.60203686e-02, -3.29831289e-03,
        4.40109186e-02, -1.56647544e-02,  1.61425192e-02,  5.56592084e-02,
       -3.14893648e-02,  1.65396612e-02,  2.22391691e-02, -3.15937214e-02,
        1.13400100e-02,  1.74458809e-02,  6.54337183e-02,  4.82842103e-02,
        4.55216728e-02, -4.55778725e-02,  1.12117939e-02, -3.27509046e-02,
        3.86610739e-02,  3.17252008e-03,  2.10512970e-02,  2.72854175e-02,
        1.09498957e-02,  2.01968253e-02,  5.03408462e-02,  2.05275193e-02,
       -1.05694518e-03,  3.29378657e-02, -2.92912945e-02, -2.22339686e-02,
       -3.20344344e-02, -6.66714162e-02, -3.71073522e-02,  2.53174547e-02,
        1.24175809e-02, -1.25820786e-02, -4.94953804e-02,  6.47236928e-02,
       -1.86157320e-02, -3.97187509e-02, -2.74337232e-02,  2.08655782e-02,
        2.84184329e-02,  1.16234422e-02,  3.30566950e-02,  3.10275946e-02,
       -2.47186003e-03, -5.33118919e-02,  3.87478396e-02, -3.93867828e-02,
       -9.42375045e-03,  4.25113961e-02, -4.46184836e-02, -3.32209542e-02,
       -4.09952253e-02,  3.53777129e-03,  2.21698768e-02,  3.80736217e-02,
        4.36842144e-02,  4.11686189e-02,  4.85646917e-04, -4.48260978e-02,
        4.13096584e-02,  2.65128203e-02,  4.36390936e-02,  4.14119028e-02,
        6.93823323e-02, -4.02413569e-02, -3.17003727e-02,  7.14220572e-03,
        1.98881831e-02,  1.25431819e-02, -3.26379165e-02, -6.05350360e-02,
       -3.03081842e-03, -3.29331830e-02, -3.66298370e-02, -1.00713712e-03,
        3.91887967e-03,  3.83470990e-02, -3.17258537e-02, -1.07382024e-02,
       -5.18840216e-02, -3.14528607e-02, -1.32990526e-02,  1.05041284e-02,
       -3.58694084e-02,  1.75286476e-02, -6.94257254e-03,  5.58227301e-03,
        2.65148431e-02, -3.26466560e-03, -4.07739766e-02,  3.40046659e-02,
        2.19636112e-02, -3.07684788e-03, -2.90892869e-02, -2.76413150e-02,
        4.77490686e-02, -1.19777443e-02, -2.57240422e-02, -2.28682021e-03,
        3.73124257e-02,  4.02446184e-03, -1.26759158e-02,  1.91709045e-02,
       -2.75764172e-03,  3.21750753e-02,  6.04085326e-02,  1.07014636e-02,
        1.01398919e-02,  1.30549874e-02,  3.34612019e-02, -1.41072283e-02,
        2.25928240e-02,  1.23305898e-02, -4.09716517e-02, -1.49425422e-03,
        5.90999275e-02,  4.63931428e-05, -1.89806409e-02, -5.09903841e-02,
        3.77883688e-02, -5.66757582e-02,  1.64565314e-02,  1.11529138e-03,
       -2.99717076e-02, -2.54368521e-02, -1.06704831e-02, -1.49029829e-02,
       -6.29705116e-02, -3.29912044e-02, -2.08227988e-02,  2.96171587e-02,
       -2.68778093e-02,  6.27792329e-02, -9.90098706e-05,  3.62255909e-02,
       -2.96624526e-02,  2.51167007e-02, -4.85652685e-02, -1.06044877e-02,
       -1.86001863e-02,  1.96208488e-02,  1.16079468e-02,  5.52626848e-02,
       -2.97791064e-02, -3.52468379e-02, -4.56434935e-02, -3.32978591e-02,
       -5.10356426e-02, -4.72140945e-02,  4.43945127e-03,  9.23705474e-03,
       -3.07732355e-02,  3.73311341e-02, -2.89251823e-02,  2.89247893e-02,
       -3.67533304e-02, -1.97121445e-02, -2.66464371e-02, -9.03489441e-03,
        1.13290511e-02,  5.20504750e-02,  5.62125854e-02, -4.09492012e-03,
       -9.80080198e-03, -2.32795998e-02, -2.72659101e-02, -2.35640407e-02,
        1.69088598e-02, -4.50804159e-02, -1.79846063e-02,  2.68087145e-02,
       -5.03292307e-02, -1.21148322e-02,  2.40812302e-02,  3.87535915e-02,
       -3.28882150e-02,  2.84913741e-02,  2.09984295e-02, -5.04626334e-03,
       -4.63194661e-02, -3.87470387e-02,  2.68737525e-02,  2.36693118e-02,
        3.12629044e-02,  5.32079302e-02,  9.96106584e-03,  2.66506076e-02,
       -3.63675617e-02, -3.87642942e-02,  6.09073862e-02, -2.72828750e-02,
       -3.17944363e-02, -6.90909252e-02, -5.51264957e-02, -4.91699167e-02,
       -6.70166640e-03,  2.04042848e-02, -2.87877619e-02, -2.19763117e-03,
       -1.11937732e-03, -3.02013736e-02,  4.32861969e-02, -3.06299720e-02,
        3.88743505e-02,  4.84987199e-02, -9.30265523e-03, -1.07396487e-02,
        4.16288786e-02,  6.30053040e-03,  9.63239465e-03, -5.72078396e-03],
      dtype=float32), array([0.09577794, 0.09571654, 0.10692906, 0.09326748, 0.09267489,
       0.0856851 , 0.10145631, 0.09763269, 0.0952527 , 0.10792975,
       0.10210511, 0.10955848, 0.09061045, 0.10272736, 0.11511692,
       0.09519041, 0.12236128, 0.08508969, 0.09125667, 0.09958141,
       0.09293946, 0.1379142 , 0.10500016, 0.09854998, 0.09202112,
       0.08712636, 0.11434379, 0.10684978, 0.09105752, 0.10373303,
       0.0958039 , 0.09314814, 0.0938696 , 0.09282045, 0.09479622,
       0.1115861 , 0.10175693, 0.09619961, 0.10790535, 0.09165558,
       0.08598933, 0.10367715, 0.10508305, 0.08885089, 0.09829654,
       0.10245074, 0.09561727, 0.09679888, 0.0954833 , 0.09646229,
       0.09242906, 0.11385342, 0.11364096, 0.10994154, 0.11211685,
       0.08454552, 0.09087195, 0.13689668, 0.08355194, 0.10747865,
       0.09529052, 0.09267224, 0.09345192, 0.10064742, 0.10123929,
       0.10556563, 0.15909769, 0.11875318, 0.09218957, 0.09681877,
       0.08438783, 0.08841729, 0.09076569, 0.08374833, 0.10824961,
       0.09490582, 0.10792481, 0.0860272 , 0.0980351 , 0.08925113,
       0.09219584, 0.09270883, 0.09930703, 0.08766282, 0.09771913,
       0.08818842, 0.10065788, 0.0917147 , 0.11271574, 0.09579422,
       0.08515069, 0.09324976, 0.13046114, 0.09274708, 0.11113076,
       0.08931214, 0.09685481, 0.0934309 , 0.08595373, 0.09528375,
       0.11086797, 0.0871489 , 0.10782011, 0.11736186, 0.10424048,
       0.09275665, 0.10924723, 0.09539638, 0.10993809, 0.09052312,
       0.10513262, 0.12530749, 0.08678156, 0.08831806, 0.09916358,
       0.09055306, 0.10597072, 0.11961997, 0.12769791, 0.09181671,
       0.08552822, 0.10979778, 0.08985693, 0.09173333, 0.11656275,
       0.08918539, 0.08275602, 0.10634374, 0.08828731, 0.11041746,
       0.09519261, 0.11088387, 0.09133936, 0.11323419, 0.1017262 ,
       0.09064341, 0.10061631, 0.1351007 , 0.10824899, 0.10594443,
       0.0874465 , 0.08769809, 0.12100942, 0.09955345, 0.13795626,
       0.09125246, 0.0998397 , 0.09383111, 0.1484699 , 0.08448541,
       0.09923533, 0.09575728, 0.09287076, 0.09471853, 0.1015095 ,
       0.09850573, 0.0999584 , 0.09747992, 0.1305019 , 0.10155492,
       0.09931213, 0.1021502 , 0.10220308, 0.09447978, 0.08497759,
       0.1108635 , 0.11144989, 0.09196897, 0.09284799, 0.0989471 ,
       0.10148434, 0.11908439, 0.10462233, 0.10263076, 0.11200233,
       0.0959694 , 0.08534865, 0.11499625, 0.09862719, 0.1011386 ,
       0.09437331, 0.09491216, 0.10699488, 0.12262545, 0.08303349,
       0.10780672, 0.09616596, 0.09552887, 0.11317362, 0.08590265,
       0.10098607, 0.1005747 , 0.09825246, 0.08891542, 0.0933352 ,
       0.12204715, 0.09775552, 0.09369265, 0.08639734, 0.09160315,
       0.0885081 , 0.08396501, 0.10494565, 0.09761619, 0.09858558,
       0.09605243, 0.12620959, 0.09251607, 0.0920342 , 0.09395235,
       0.09196315, 0.08910278, 0.10505113, 0.08445673, 0.09793559,
       0.10654736, 0.08885124, 0.09247341, 0.11599562, 0.09546924,
       0.10090566, 0.10657544, 0.09333757, 0.09462623, 0.09440316,
       0.09350616, 0.10875329, 0.10327499, 0.10406196, 0.12667784,
       0.10699095, 0.08656212, 0.10612366, 0.11152011, 0.10309886,
       0.13960852, 0.08609437, 0.10276603, 0.128256  , 0.08573759,
       0.08367814, 0.1096846 , 0.10543443, 0.0962336 , 0.10449601,
       0.12707046, 0.11463916, 0.10880189, 0.11164682, 0.08898477,
       0.08512886, 0.08630057, 0.11190203, 0.10236588, 0.12927192,
       0.09304942, 0.08835316, 0.09848818, 0.10364781, 0.09327821,
       0.0862285 , 0.09455261, 0.09553235, 0.10988415, 0.08342171,
       0.11999516, 0.08990075, 0.10047555, 0.09918206, 0.11024182,
       0.14013314, 0.10476971, 0.08929002, 0.09199112, 0.10744471,
       0.09227652, 0.10073216, 0.12235598, 0.09008581, 0.11979578,
       0.09008264, 0.08330397, 0.11714309, 0.09318693, 0.1178363 ,
       0.09119355, 0.0894604 , 0.09196889, 0.0896465 , 0.09136561,
       0.08404071, 0.09974936, 0.09426598, 0.08481248, 0.08682445,
       0.09869136, 0.08770286, 0.10761591, 0.08807525, 0.1279104 ,
       0.10317925, 0.08906229, 0.104943  , 0.12321085, 0.09448265,
       0.08504384, 0.08881638, 0.10903826, 0.09667708, 0.09237321,
       0.08863412, 0.10472035, 0.08384882, 0.11143039, 0.09707246,
       0.10521494, 0.10984552, 0.09215033, 0.11414043, 0.0989463 ,
       0.09573328, 0.08972263, 0.10092878, 0.09367161, 0.09530655,
       0.08576097, 0.09126551, 0.11401434, 0.10525025, 0.09140226,
       0.13045464, 0.08440183, 0.10297186, 0.09577616, 0.11345416,
       0.10177571, 0.09851022, 0.10792914, 0.09535749, 0.09858642,
       0.08980231, 0.09712704, 0.08993532, 0.0856179 , 0.09963865,
       0.09906689, 0.10794456, 0.0945422 , 0.09754755, 0.09208139,
       0.08872657, 0.10493116, 0.08985499, 0.09325697, 0.08515528,
       0.09934362, 0.0893494 , 0.0881494 , 0.08552731, 0.09495385,
       0.11152785, 0.09530058, 0.09732244, 0.09918829, 0.11903148,
       0.10247948, 0.09126067, 0.14584203, 0.08436998, 0.09162601,
       0.15291156, 0.12605202, 0.08747783, 0.11606514, 0.08839176,
       0.08373597, 0.09340174, 0.12806515, 0.09343927, 0.0855431 ,
       0.08722741, 0.08293419, 0.0919283 , 0.09513102, 0.09167144,
       0.14046219, 0.09002485, 0.10264318, 0.10424186, 0.1032332 ,
       0.12507187, 0.08927061, 0.08405083, 0.09027693, 0.08951695,
       0.13069442, 0.11351801, 0.12649062, 0.09192901, 0.08228902,
       0.09720594, 0.09480658, 0.08836138, 0.10440483, 0.12600154,
       0.08672428, 0.08568949, 0.09091417, 0.1315083 , 0.08392921,
       0.10626475, 0.09618965, 0.12997042, 0.11591908, 0.09288704,
       0.11552629, 0.08319145, 0.09816877, 0.0949726 , 0.09867222,
       0.091005  , 0.10373804, 0.09829156, 0.09120778, 0.09933434,
       0.09438318, 0.0888768 , 0.08928968, 0.09778745, 0.08446201,
       0.10771102, 0.09755959, 0.09937813, 0.12123542, 0.09105611,
       0.08817707, 0.09440528, 0.08774704, 0.0982637 , 0.0943175 ,
       0.09332094, 0.13465755, 0.09864978, 0.09311403, 0.08977011,
       0.09188318, 0.08923874, 0.1137248 , 0.12533265, 0.09224351,
       0.09719957, 0.10326785, 0.10037465, 0.09614325, 0.09430718,
       0.09835096, 0.1197333 , 0.09524295, 0.09082726, 0.10367995,
       0.11935162, 0.08587863, 0.09348051, 0.09322228, 0.11642047,
       0.08426601, 0.09557618, 0.09605059, 0.08465142, 0.09345621,
       0.10868308, 0.11538505, 0.09556806, 0.1765568 , 0.09492531,
       0.1087182 , 0.08470539, 0.11514419, 0.08571831, 0.10647028,
       0.12673382, 0.1312572 , 0.09272163, 0.1020496 , 0.12348776,
       0.12069608, 0.11344851, 0.0965122 , 0.12245958, 0.08932007,
       0.10955626, 0.09183589, 0.09102407, 0.08558387, 0.10825431,
       0.10390636, 0.0926147 , 0.09938689, 0.1048043 , 0.11168835,
       0.09039458, 0.08907874, 0.0888465 , 0.08495028, 0.08921809,
       0.09036989, 0.09365287, 0.09438056, 0.08721706, 0.13069932,
       0.09709393, 0.10310686, 0.08845215, 0.08782517, 0.10005177,
       0.08909635, 0.09454021, 0.0890814 , 0.093199  , 0.12964539,
       0.08744483, 0.08947257, 0.10149518, 0.09557396, 0.09735964,
       0.11380455, 0.10884795, 0.11920014, 0.11121361, 0.09343416,
       0.08482817, 0.08688254, 0.0926426 , 0.09025212, 0.08611593,
       0.09590021, 0.08788751, 0.08873238, 0.09625085, 0.09417012,
       0.0930749 , 0.09943435, 0.09269128, 0.0886749 , 0.10165669,
       0.14072055, 0.11206796, 0.09131792, 0.10757308, 0.10639562,
       0.10509069, 0.12702501, 0.08704964, 0.10102744, 0.08882068,
       0.09509569, 0.10804678, 0.09873781, 0.08379922, 0.09226861,
       0.08703001, 0.12868533, 0.09767218, 0.10578611, 0.09021331,
       0.11039678, 0.10635664, 0.1009981 , 0.09978109, 0.08592291,
       0.09122169, 0.10838398, 0.13745023, 0.08750485, 0.0879954 ,
       0.09684648, 0.11282632, 0.10431902, 0.11172322, 0.10779008,
       0.11796019, 0.10479515, 0.09563716, 0.09149146, 0.09627965,
       0.09412757, 0.09652522, 0.11395191, 0.08916304, 0.1055062 ,
       0.09801853, 0.08352242, 0.10075276, 0.1064602 , 0.09892874,
       0.0830815 , 0.10022418, 0.1109076 , 0.0905334 , 0.0840294 ,
       0.08872748, 0.0882493 , 0.08821709, 0.09292443, 0.09639204,
       0.08488441, 0.09381199, 0.10658604, 0.09438656, 0.09011762,
       0.0955555 , 0.1021803 , 0.15098327, 0.09646883, 0.09622858,
       0.08488229, 0.08549056, 0.09574535, 0.09096329, 0.08952536,
       0.08907093, 0.09265034, 0.13048205, 0.09588869, 0.08844927,
       0.11837137, 0.0976226 , 0.10378473, 0.09049167, 0.09757316,
       0.10439841, 0.08929899, 0.11690671, 0.08562014, 0.08738277,
       0.10084081, 0.08801331, 0.12913062, 0.0865211 , 0.09330153,
       0.10123374, 0.11268074, 0.09120247, 0.08572533, 0.10637325,
       0.12653938, 0.08637573, 0.08683307, 0.10759472, 0.09836834,
       0.0947716 , 0.11056454, 0.08551105, 0.08507852, 0.1171319 ,
       0.10355496, 0.08921453, 0.08894922, 0.09649101, 0.11327174,
       0.08485356, 0.08929783, 0.11700278, 0.08648725, 0.10174983,
       0.1044551 , 0.08820543, 0.08233711, 0.09217029, 0.10632282,
       0.11111455, 0.09168322, 0.11450093, 0.096979  , 0.0914662 ,
       0.09380014, 0.08554852, 0.1277511 , 0.1106738 , 0.08475053,
       0.09759064, 0.08497495, 0.11252996, 0.09084243, 0.09426965,
       0.102373  , 0.08819443, 0.09827191, 0.11548281, 0.09398589,
       0.09444352, 0.09392474, 0.09289042, 0.08981508, 0.10330092,
       0.0853815 , 0.11323074, 0.08560672, 0.11876135, 0.09146085,
       0.09294911, 0.11354423, 0.08490629, 0.09682094, 0.10142877,
       0.10413267, 0.12395612, 0.09028421, 0.09812771, 0.12570034,
       0.11002934, 0.10490932, 0.08404897, 0.08498911, 0.11723528,
       0.08458043, 0.08563037, 0.09614891, 0.09822969, 0.09325098,
       0.08997761, 0.11982616, 0.09721554, 0.08366364, 0.10558948,
       0.09280191, 0.09051292, 0.08546214], dtype=float32), array([[[[ 0.02420424],
         [-0.01960248],
         [ 0.01616875],
         ...,
         [-0.01424405],
         [ 0.016891  ],
         [ 0.00166204]],

        [[-0.00643004],
         [ 0.02079141],
         [ 0.00979111],
         ...,
         [-0.01014178],
         [-0.02448976],
         [-0.01730352]],

        [[ 0.02219252],
         [ 0.03218284],
         [-0.03190489],
         ...,
         [-0.00860386],
         [ 0.00986046],
         [-0.0083708 ]]],


       [[[-0.01182581],
         [-0.00605828],
         [-0.01982191],
         ...,
         [-0.02975314],
         [ 0.01255722],
         [ 0.02541171]],

        [[-0.01985672],
         [ 0.0084566 ],
         [-0.00040388],
         ...,
         [-0.01094817],
         [-0.01399977],
         [-0.01845469]],

        [[-0.00911854],
         [ 0.01119657],
         [-0.03459647],
         ...,
         [-0.00351811],
         [-0.00181023],
         [-0.00035198]]],


       [[[ 0.01651937],
         [ 0.00949989],
         [ 0.00653961],
         ...,
         [ 0.01282695],
         [-0.00379308],
         [ 0.02250511]],

        [[ 0.0221692 ],
         [-0.01143135],
         [ 0.01044311],
         ...,
         [-0.00464701],
         [-0.00167026],
         [-0.00101572]],

        [[-0.00804372],
         [ 0.0215235 ],
         [ 0.01340006],
         ...,
         [-0.01586572],
         [-0.00269877],
         [-0.00442728]]]], dtype=float32), array([[[[ 0.03953243, -0.06837729,  0.00566696, ...,  0.01261137,
          -0.07429045,  0.00574039],
         [ 0.0481285 ,  0.03306615, -0.05735042, ..., -0.05844409,
          -0.04971614, -0.0226668 ],
         [-0.06433535, -0.02107939,  0.05000868, ...,  0.00417729,
          -0.05405258, -0.008082  ],
         ...,
         [ 0.05447839,  0.03233107, -0.02392517, ..., -0.04276669,
           0.04010751,  0.02763246],
         [-0.02309275, -0.00097629,  0.03198195, ...,  0.04166341,
          -0.03280732,  0.06107331],
         [ 0.02241313, -0.0465268 , -0.04013161, ...,  0.02309621,
           0.03666284,  0.03244168]]]], dtype=float32), array([0.99348193, 0.9942743 , 1.0160264 , 1.0124164 , 1.0360919 ,
       0.99305815, 0.99201614, 0.9976588 , 1.0178859 , 1.0030252 ,
       0.9984926 , 0.99728304, 0.9916704 , 1.0097737 , 0.9972823 ,
       0.99836504, 1.0113033 , 1.0079093 , 0.9990215 , 0.9981877 ,
       0.98975295, 0.9940777 , 0.9942357 , 0.9973575 , 0.99490976,
       0.9984796 , 1.0025936 , 0.99622226, 0.99794847, 1.0037005 ,
       0.99968266, 0.9917958 , 1.0363638 , 1.0307015 , 0.9976812 ,
       1.0137028 , 0.99146026, 0.9927924 , 1.0003735 , 0.98423964,
       0.99953485, 0.9967753 , 1.0044016 , 1.0112276 , 1.0039991 ,
       1.0056212 , 1.0131936 , 0.9939238 , 0.988936  , 1.0011814 ,
       0.99214244, 0.9961782 , 1.0038229 , 0.9888653 , 0.99483746,
       0.99943477, 0.99386156, 1.0014228 , 0.98382473, 1.0103362 ,
       1.0097709 , 0.99891824, 0.99670726, 0.99415946, 0.9864836 ,
       0.98862606, 0.9976263 , 0.99311435, 0.99447906, 0.99935323,
       0.9917762 , 1.0110594 , 1.0173568 , 0.99150527, 0.9987424 ,
       0.9965192 , 0.9912751 , 0.9782637 , 1.0008051 , 0.99656075,
       0.9939692 , 0.99868536, 0.996364  , 0.9920832 , 1.0087594 ,
       0.9893214 , 0.99708056, 0.9962787 , 1.0000551 , 0.9957686 ,
       1.0105033 , 1.0021307 , 0.99882066, 1.0126016 , 1.0037678 ,
       1.000494  , 1.0167123 , 1.0057867 , 1.0035524 , 0.9972137 ,
       0.9971882 , 0.9979614 , 0.99155295, 1.0034834 , 0.99951464,
       0.99525064, 0.99509865, 1.0151259 , 0.99239236, 0.9933027 ,
       0.99678975, 0.9961529 , 0.9936267 , 0.99039596, 0.99364203,
       0.98927057, 0.9932104 , 0.9874086 , 0.9959403 , 1.0004557 ,
       0.9927118 , 0.9906736 , 0.99539673, 1.0108118 , 0.99527246,
       0.9891305 , 0.9978539 , 0.9890126 , 0.99843657, 0.99094504,
       0.99037695, 0.99400187, 0.9954035 , 0.9987873 , 1.0079399 ,
       1.0032101 , 1.0043914 , 0.9954802 , 0.99281114, 0.9910447 ,
       0.9925221 , 1.0174851 , 1.009543  , 0.98503095, 1.0019078 ,
       0.9954859 , 1.0018395 , 0.9931347 , 0.9923356 , 0.99233353,
       0.99982697, 1.0198977 , 0.99583644, 1.0140865 , 0.98884535,
       1.0013995 , 0.9977657 , 0.99283034, 1.0100778 , 0.98652065,
       0.99636865, 0.9962773 , 1.0368708 , 0.99802756, 0.9965009 ,
       0.9975192 , 1.0052137 , 1.0421317 , 1.0362034 , 0.99958414,
       1.0012034 , 1.0010258 , 0.99708295, 1.0039868 , 0.9981651 ,
       0.99883896, 0.9959096 , 0.9930938 , 0.9981643 , 1.0061477 ,
       0.98775685, 0.99799263, 0.98673755, 1.0031804 , 0.99600095,
       0.99439305, 1.0085174 , 1.0082163 , 0.99023235, 1.0016677 ,
       0.98476213, 0.99579614, 0.99705756, 1.0139366 , 0.9860953 ,
       0.99735886, 1.0112332 , 0.9951495 , 0.99061   , 0.9946392 ,
       0.99649554, 0.9972642 , 0.99607503, 0.99944896, 0.9966003 ,
       0.9937714 , 1.0204356 , 1.0444036 , 0.9837648 , 1.0238497 ,
       0.99631685, 0.99797523, 1.0028088 , 1.0105981 , 0.99983144,
       1.0190811 , 0.9989734 , 1.0146254 , 0.9843045 , 0.99424607,
       1.0027012 , 1.0150983 , 0.99517184, 0.9948177 , 0.99518174,
       1.0153954 , 0.97855204, 0.98528457, 0.99316204, 0.9946114 ,
       0.99165285, 0.9935899 , 0.9984555 , 0.9992684 , 0.9976375 ,
       0.99534583, 0.9925438 , 0.998503  , 0.99913347, 0.9947529 ,
       0.9995626 , 1.005508  , 1.0045556 , 1.0018476 , 0.99706465,
       1.0019523 , 0.99911135, 1.008505  , 0.99736995, 1.0014611 ,
       0.994555  , 0.98949355, 1.0067734 , 0.9901181 , 1.020055  ,
       1.0025011 , 1.003886  , 0.9955216 , 0.9883632 , 0.9952717 ,
       1.0221974 , 0.9964177 , 0.9963742 , 0.98563117, 1.0061013 ,
       0.9975057 , 0.99311316, 1.0061523 , 1.0009326 , 0.98952085,
       0.99558794, 0.9943865 , 1.0239524 , 1.0188972 , 1.0018185 ,
       0.99482805, 0.99420565, 0.9937455 , 0.9940537 , 0.9989693 ,
       1.0059544 , 0.9951236 , 0.99765825, 0.99210185, 1.0001583 ,
       0.98726654, 1.0027717 , 0.9927037 , 1.01946   , 0.9952202 ,
       1.0091547 , 1.0031023 , 0.99189276, 0.9947397 , 0.9994434 ,
       1.0019364 , 0.9990754 , 0.9975805 , 1.0201706 , 0.9997    ,
       1.0095968 , 0.9833631 , 0.98451877, 1.0025375 , 1.0020394 ,
       0.98897284, 0.9963755 , 0.9956556 , 1.0003986 , 1.002097  ,
       1.0132821 , 0.995506  , 0.98411745, 0.99777585, 0.99367577,
       0.9970693 , 1.0010458 , 0.99536955, 1.018266  , 1.0117916 ,
       0.98870003, 1.0040852 , 0.9949536 , 0.9985664 , 0.9943483 ,
       0.9918917 , 0.99292254, 0.99675304, 0.9950116 , 0.99557877,
       1.023691  , 0.99405867, 0.9971115 , 0.99048156, 0.99571055,
       1.005949  , 1.0047134 , 0.97625285, 0.9936018 , 0.9950894 ,
       0.9943222 , 0.9993847 , 1.0012023 , 0.99779344, 1.0041444 ,
       1.0234828 , 0.98886156, 0.99439687, 0.9945741 , 0.9919303 ,
       0.9982156 , 0.9932505 , 0.9954257 , 1.0103769 , 0.9900565 ,
       0.99157315, 1.0040092 , 0.99935025, 0.99098474, 1.011598  ,
       1.011823  , 1.0097425 , 1.0124079 , 0.9967327 , 0.997424  ,
       0.9942582 , 0.9888867 , 1.0353057 , 0.99914503, 0.9942857 ,
       0.99602956, 1.0011044 , 0.99225277, 0.9903681 , 0.99895626,
       1.0020893 , 1.0132154 , 0.9924638 , 0.990852  , 0.9895244 ,
       1.005697  , 0.9941817 , 0.98662   , 1.0006279 , 1.0120499 ,
       0.99241346, 0.9929316 , 0.9997807 , 0.99773914, 0.99692875,
       0.99899393, 1.0025564 , 1.0118715 , 1.0032543 , 1.0000618 ,
       1.0021572 , 0.9916037 , 0.9939305 , 1.0226895 , 0.9992012 ,
       0.9927704 , 0.9973615 , 0.9886709 , 1.0019419 , 0.9974343 ,
       1.0046322 , 0.9892035 , 0.9964777 , 1.0026813 , 0.98943096,
       1.0067748 , 1.0065423 , 0.9927589 , 1.0009319 , 0.9911163 ,
       1.0031998 , 1.0007222 , 0.99908   , 1.0040368 , 0.9969037 ,
       0.99352425, 0.98696077, 1.0153677 , 0.9847773 , 1.0141792 ,
       0.990878  , 0.9940646 , 0.9969702 , 0.99616253, 0.99576384,
       1.0002989 , 0.9952879 , 0.9914378 , 0.988177  , 0.99566376,
       1.0062343 , 1.0004387 , 1.0051976 , 0.99555063, 0.9951869 ,
       0.99997586, 0.9982229 , 0.99135005, 0.9858063 , 0.9937372 ,
       1.0178387 , 0.99350846, 1.0068485 , 0.99377835, 0.98752743,
       0.9893063 , 0.9886482 , 1.0120513 , 1.0020796 , 0.9900187 ,
       0.9967748 , 0.9942458 , 0.99723035, 1.0014026 , 0.98566866,
       0.99783254, 0.99552923, 0.9991955 , 0.99977845, 1.021397  ,
       0.99988216, 0.9821795 , 0.99928397, 1.0013593 , 1.001975  ,
       1.0007887 , 0.98834294, 1.0013382 , 1.0045775 , 1.0033275 ,
       0.9977086 , 0.9939843 , 0.9929611 , 1.008095  , 0.9974535 ,
       0.9915007 , 1.002325  , 0.997648  , 0.9909728 , 0.9983181 ,
       1.0055434 , 0.9984697 , 1.0002562 , 0.99160695, 1.0014892 ,
       0.98900056, 0.99602574, 0.9815337 , 0.99355274, 1.0011339 ,
       1.0000364 , 1.004275  , 0.99461627, 0.9845961 , 1.0161136 ,
       0.99166876, 1.0084379 , 0.9889104 , 0.99636996, 1.0026945 ,
       1.0034188 , 0.9932374 , 0.9957675 , 0.99047506, 0.99780345,
       0.9935795 , 1.014107  , 0.99092734, 1.0048708 , 1.0018013 ,
       1.0048962 , 1.0000724 , 0.99617684, 1.0063833 , 1.0218569 ,
       1.0029402 , 1.009384  , 1.0034703 , 0.9887919 , 1.0025439 ,
       0.993337  , 0.9947745 , 0.9856721 , 0.9976507 , 0.9905172 ,
       1.0238771 , 0.99905485, 1.0049018 , 0.9972149 , 1.0104358 ,
       0.9926301 , 1.0213917 , 0.99196947, 0.9956945 , 0.99554837,
       1.0169253 , 0.99926835, 0.9954854 , 1.0069278 , 0.9916295 ,
       0.9904331 , 0.9863293 , 0.9860003 , 0.9948068 , 1.009641  ,
       1.0068238 , 0.998323  , 0.99500525, 1.0132939 , 0.99575955,
       0.9861885 , 1.0351337 , 0.9968442 , 1.0031985 , 0.9965221 ,
       1.004512  , 0.9969647 , 0.99473315, 0.9876675 , 0.99359304,
       0.9982742 , 0.99488795, 1.0003873 , 1.0054407 , 0.992201  ,
       0.98050857, 1.0032585 , 0.998727  , 1.0249305 , 0.99712604,
       1.0140859 , 1.0201392 , 0.9965848 , 0.9999411 , 0.98441654,
       0.98400563, 0.992569  , 0.9955888 , 0.9953226 , 0.9972533 ,
       1.0001192 , 0.9851493 , 1.0062649 , 0.99843943, 0.99725574,
       1.0017443 , 0.9846126 , 0.99511427, 1.0089895 , 0.99986935,
       0.99439776, 0.9918384 , 1.0060624 , 1.0199721 , 0.998714  ,
       0.9959743 , 0.99659395, 0.9915193 , 0.99214745, 0.99450624,
       0.99594355, 1.002423  , 0.9917153 , 1.0016844 , 1.0079496 ,
       1.0090318 , 0.99686354, 0.998953  , 0.9988846 , 0.9877468 ,
       0.99683326, 1.000681  , 0.999851  , 0.99183077, 1.0315808 ,
       0.9945835 , 1.0131017 , 0.9964426 , 0.99750906, 0.9978025 ,
       1.004697  , 0.99447095, 1.0068673 , 0.9948572 , 0.99406433,
       0.99594355, 0.99585897, 1.0021508 , 0.9933673 , 0.9848538 ,
       0.9913889 , 1.0062537 , 1.0166854 , 1.0101523 , 0.99759096,
       0.9874824 , 0.98730046, 0.9911395 , 0.97905385, 1.0026866 ,
       0.99955237, 0.9965643 , 1.0186356 , 1.016991  , 0.99557173,
       0.993204  , 0.9931873 , 0.99995244, 0.9993359 , 0.9928889 ,
       0.9929182 , 0.9944484 , 0.99354786, 0.9844941 , 0.9967271 ,
       0.99380904, 1.0010604 , 0.99017256, 0.9973679 , 1.0078142 ,
       0.9910817 , 1.0178809 , 1.0005859 , 0.9986175 , 1.0205721 ,
       0.99430776, 0.98573124, 0.9858569 , 1.0091664 , 1.0179102 ,
       0.9957625 , 1.0081817 , 0.99988973, 1.0067452 , 1.0009046 ,
       0.99073905, 0.99745643, 0.9940542 , 0.98983884, 0.99142414,
       1.0073252 , 0.99400795, 1.0066825 , 0.99332654, 0.99833006,
       0.9920817 , 0.9938712 , 0.99380314, 1.0017141 , 0.9947325 ,
       1.000767  , 0.99785215, 0.9983153 , 1.0007429 , 1.0053222 ,
       1.0168664 , 0.9931661 , 0.9975415 , 0.99643475, 1.0200816 ,
       0.99465966, 1.013401  , 0.9948887 , 0.9962454 , 0.9976588 ,
       0.99981743, 0.9938958 , 1.0387092 , 0.9926208 , 1.0033764 ,
       1.0079253 , 0.99851614, 1.0002052 , 1.0036775 , 1.0223079 ,
       0.9961143 , 1.0157613 , 1.0092758 , 1.0232315 , 0.9988126 ,
       0.9993059 , 1.0165159 , 0.99904275], dtype=float32), array([-1.25147393e-02, -1.82148404e-02,  2.53869477e-03, -1.96580850e-02,
       -4.30188254e-02, -1.48730853e-03, -6.87218644e-03, -7.46727781e-03,
       -3.28757465e-02,  1.07802206e-03, -7.09635252e-03, -3.69983073e-03,
       -7.65128201e-03, -2.16992702e-02, -8.00658949e-03, -3.33928280e-02,
       -1.71675161e-02, -3.34268296e-03, -1.10906353e-02, -8.90242588e-03,
        6.23691780e-03, -6.90192962e-03, -1.91866118e-03, -2.87739243e-02,
       -5.73189650e-03, -1.08670127e-02, -4.69410745e-03, -2.58293911e-03,
       -8.79410375e-03,  4.51838877e-03, -4.18566056e-02, -2.66124867e-02,
       -3.44407149e-02, -3.24865021e-02, -1.03362789e-03, -2.73940135e-02,
        8.15832056e-03, -4.88099921e-03, -2.12922264e-02, -1.13829514e-02,
       -2.77849510e-02, -4.01603524e-03, -1.79490652e-02, -3.31801400e-02,
       -3.40554342e-02, -1.63511882e-04, -2.65650731e-02, -1.09344935e-02,
       -2.50327140e-02, -3.99661511e-02, -4.98904008e-03, -3.84177901e-02,
       -1.95907466e-02, -1.15800649e-02,  4.05965140e-03, -1.40519058e-02,
       -8.32597166e-03,  1.75291125e-03, -8.61408748e-03, -9.54172295e-03,
       -2.62691174e-02, -7.61157228e-03, -3.30397068e-03, -2.16165595e-02,
       -5.52768027e-03, -8.82149767e-03, -2.29232814e-02, -1.84512958e-02,
       -1.96869485e-03,  1.05023254e-02, -5.94136305e-03, -4.25545201e-02,
       -3.36617120e-02, -1.39171407e-02, -1.47465686e-03, -2.05176207e-03,
       -8.80202744e-03, -4.56297956e-03, -3.94722680e-04, -2.07230053e-03,
        1.43131698e-02, -2.17154846e-02, -8.22458882e-03,  1.40657574e-02,
       -1.61523297e-02, -8.36531632e-03,  1.07165277e-02,  5.88661106e-03,
       -6.34978013e-03, -2.71874759e-03, -4.54740133e-03, -2.89931297e-02,
        1.04202926e-02, -4.69416678e-02,  1.45073459e-02, -9.32635460e-03,
       -2.60201897e-02, -1.13262404e-02, -1.21217454e-02,  1.19195282e-02,
       -3.07468474e-02, -2.74906270e-02, -9.23226774e-03, -6.56680204e-03,
        7.77518516e-03, -2.46724989e-02, -3.71658499e-03,  1.71641577e-02,
       -5.40579762e-03,  6.52175630e-03, -2.98039848e-03,  1.29032591e-02,
        3.48805520e-03, -1.15127787e-02,  1.70024689e-02, -9.84770246e-03,
       -7.97899906e-03, -8.40055291e-03, -3.78933642e-03,  4.53031762e-03,
       -1.88001245e-03, -9.45348572e-03, -9.94972885e-03,  3.82968062e-03,
       -3.17641743e-03, -8.30444135e-03, -5.60061075e-03, -1.40379127e-02,
       -1.08185029e-02,  2.33001448e-02, -1.22502511e-02, -1.11004552e-02,
       -1.30010042e-02, -2.06103306e-02, -1.62233543e-02, -1.05205327e-02,
        7.48708844e-03,  3.66031518e-03, -1.03034880e-02, -5.49252797e-03,
       -6.48790877e-03, -1.96689088e-02, -3.84784751e-02, -1.06394738e-02,
        1.73074305e-02, -1.30806025e-02, -9.15999804e-03, -7.81532377e-03,
       -9.41174384e-03, -1.06159765e-02, -1.43881971e-02, -3.15513946e-02,
       -2.75701401e-03,  8.45547416e-04, -4.28829202e-03, -3.26571800e-02,
       -8.85185727e-04, -6.41539274e-03, -2.36970335e-02, -1.03708087e-02,
       -3.52168106e-03, -5.97073836e-03, -4.73911129e-02, -5.61489211e-03,
       -6.96590752e-04, -9.74660553e-03, -2.18534488e-02, -1.43428184e-02,
       -1.43334204e-02, -1.88252870e-02, -9.31303855e-03, -3.53635512e-02,
       -2.88953795e-03, -6.15772791e-03, -1.54486671e-03, -2.87761092e-02,
       -6.99107070e-04, -2.43895557e-02, -1.08533567e-02, -2.25768704e-02,
        2.05715583e-03,  6.74766069e-03, -4.96694585e-03, -2.30284203e-02,
       -1.78536754e-02, -3.68483947e-03, -2.95021366e-02,  2.33308356e-02,
        1.42491516e-02, -2.01153066e-02,  2.03179140e-02,  3.84855014e-03,
        1.90210133e-03, -1.34029249e-02, -7.38685485e-03,  5.02868090e-03,
        1.10111758e-02, -6.32121740e-03, -2.29258016e-02,  9.99581069e-04,
       -4.36544325e-03, -5.27229253e-03,  1.33713102e-03, -6.83305506e-03,
        7.46025471e-04, -9.34901647e-03, -4.00829725e-02, -2.69314628e-02,
       -3.63265909e-03,  1.63617180e-04, -1.45404339e-02,  3.34574073e-03,
        5.49356081e-03,  4.60108370e-03, -4.36576121e-02, -4.06091921e-02,
        1.39879342e-03,  1.87427998e-02, -2.70548593e-02, -3.18400376e-03,
       -1.59667917e-02, -3.90244350e-02, -7.25761056e-03, -4.06385213e-03,
       -8.21227767e-03, -3.41985226e-02, -4.78430791e-03, -9.30658914e-03,
       -2.84129940e-03,  6.83255680e-03, -1.12371356e-03, -1.14984727e-02,
       -3.67878098e-03, -1.98928230e-02, -3.10468189e-02, -1.80095993e-02,
       -8.13551713e-04, -3.19989445e-03, -3.47525030e-02, -1.44379248e-03,
       -2.36273836e-02, -3.89574617e-02, -2.36458704e-03, -6.97200792e-03,
       -1.77711120e-03,  8.47936422e-03,  1.79459958e-03, -2.39270348e-02,
       -9.49318055e-03, -5.86188817e-03, -3.24591808e-02, -5.19955717e-03,
       -3.20071056e-02, -1.26680853e-02, -2.72371471e-02,  1.83830243e-02,
       -2.62793042e-02, -3.55378073e-03, -2.03077570e-02, -1.56805459e-02,
       -1.23258745e-02, -3.40628885e-02, -3.59994126e-03, -3.43332696e-03,
        7.56527018e-03, -3.28640849e-03, -6.67095510e-03, -7.61557231e-03,
        2.75693624e-03,  1.42216054e-03, -2.94124847e-03, -2.00936478e-02,
       -2.42836140e-02, -2.17794664e-02, -1.40516032e-02, -6.65324414e-03,
       -6.91153202e-03, -8.90119839e-03, -3.58826923e-03,  2.38392479e-03,
       -7.09712086e-03, -1.60215318e-03, -8.96448921e-03, -9.71706118e-03,
        1.18236709e-03, -2.92991679e-02,  2.73923296e-03, -8.39445926e-03,
       -2.45566331e-02, -4.75445623e-03, -2.29770853e-03, -5.63000515e-03,
       -1.34787709e-02, -1.01012185e-04,  3.40952491e-03, -1.96472220e-02,
       -8.76254123e-03, -2.24944483e-02, -3.03143337e-02, -2.32752878e-03,
       -1.08188083e-02, -1.28978146e-02, -1.47920577e-02, -2.91942060e-02,
        1.24735432e-03, -4.11844254e-03, -2.52910377e-03, -6.54318044e-03,
       -6.84347586e-04, -4.84070508e-03, -1.77799053e-02, -5.65782003e-03,
       -1.69918761e-02, -3.55211180e-03, -8.76258314e-03, -1.97473653e-02,
       -6.22195052e-03, -5.50234457e-03, -1.95088554e-02,  1.02188461e-03,
       -8.35788250e-03,  2.06573773e-02, -9.58661828e-03, -2.33056839e-03,
       -8.61275382e-03, -1.84730031e-02,  7.22368620e-03, -2.62192264e-02,
       -3.47716510e-02, -4.40979563e-02,  3.74274999e-02, -3.75870173e-03,
       -1.38976108e-02, -8.78904946e-03,  3.09332623e-03,  1.10199712e-02,
        2.80218478e-02, -1.29317921e-02,  8.33114237e-03,  5.65142324e-03,
       -2.89340760e-03,  8.16996954e-03, -3.87654756e-03, -2.55964417e-02,
       -7.49732507e-03, -1.85834132e-02, -2.94339899e-02, -9.89146158e-03,
       -1.33559806e-02, -3.86597845e-03, -6.83023827e-03, -8.47237709e-04,
       -1.50719145e-02, -7.92844780e-03,  2.94741429e-03, -1.07472884e-02,
        5.21415146e-03, -1.80609077e-02,  5.04599651e-03, -2.62632016e-02,
        1.71356872e-02, -2.07724068e-02, -4.92316373e-02, -5.53610409e-03,
       -3.80993937e-03, -2.52294773e-03, -1.73814073e-02, -6.48778491e-03,
        2.54356191e-02, -8.63269065e-03,  4.34895931e-03, -2.32803468e-02,
       -2.57689878e-02, -2.39653904e-02,  1.40555119e-02, -1.17622139e-02,
       -1.63866598e-02, -8.74053128e-03, -6.96348539e-03, -6.84011728e-03,
        7.71131553e-03, -5.87096764e-03, -9.47981421e-03, -2.58574449e-02,
       -3.73729356e-02, -3.16634253e-02, -1.11044459e-02,  5.88099938e-04,
       -1.97934806e-02, -7.36364303e-03,  1.19985258e-02,  6.35760324e-03,
       -2.01647002e-02,  3.17088538e-03, -2.66932677e-02,  9.33191914e-04,
       -9.53750033e-03,  9.74084483e-04, -2.71659549e-02, -1.22407603e-03,
       -2.24630050e-02, -5.62376576e-04, -8.71932227e-03,  9.07646678e-03,
        1.37729163e-03,  9.58620862e-04, -2.13837549e-02,  8.65273364e-03,
       -1.43322144e-02, -8.42093024e-03, -2.80936584e-02, -3.34458016e-02,
       -1.93802314e-03,  1.26536656e-03, -1.07125249e-02, -1.47122396e-02,
        5.92868682e-03, -1.57155693e-02, -8.55340436e-03, -2.29481235e-02,
       -2.23651286e-02, -1.47623997e-02,  2.07717977e-02, -9.08659585e-03,
       -1.14044044e-02, -1.37159973e-02, -7.64095865e-04,  1.01240836e-02,
       -1.49300294e-02, -2.95574800e-03,  8.06442462e-03, -5.51109063e-03,
       -8.60967394e-03, -1.10110817e-02, -1.23999058e-03,  3.83214722e-03,
       -6.71235472e-03, -1.32845202e-02, -2.50254129e-03, -1.37495026e-02,
       -6.69802167e-03,  2.63160560e-03, -2.33860500e-02, -6.32601744e-03,
       -1.87910593e-03, -3.77144851e-02, -1.19115245e-02,  1.26931081e-02,
       -4.63458244e-03, -3.63666448e-03, -2.32534320e-03, -9.20100417e-03,
       -3.74022573e-02, -3.10037495e-03, -4.08951528e-02, -5.80515061e-03,
       -1.46688838e-02, -1.51191037e-02, -1.58202671e-03,  5.39867114e-03,
       -2.73169540e-02, -8.08523735e-04,  5.14671486e-03,  2.50989404e-02,
       -4.63891402e-02, -1.95444585e-03, -2.48006396e-02,  8.60136468e-03,
       -1.65350512e-02,  2.09093723e-03, -3.80137786e-02, -3.76556185e-03,
       -8.01829563e-04, -3.92252430e-02,  4.78196982e-03, -6.14482909e-04,
       -4.09065885e-03, -9.51061491e-03,  8.59755278e-03,  1.05647696e-02,
        3.19893286e-03, -1.28121516e-02, -8.65237229e-03, -5.95275639e-03,
        4.92337765e-03, -2.59315949e-02, -2.69686487e-02, -6.07323041e-03,
       -9.44245700e-03, -6.27774280e-03, -1.63414255e-02, -3.69363874e-02,
       -2.13141162e-02,  7.64488184e-04, -2.92537231e-02, -5.31103089e-03,
       -2.83100978e-02, -1.04357786e-02,  6.53279247e-03, -3.53615321e-02,
       -5.32893371e-03,  3.29859108e-02, -5.13870828e-03, -2.66967248e-03,
       -2.10765924e-04, -1.01485173e-03, -2.72591296e-03, -1.56314634e-02,
       -4.17921506e-02, -3.93490903e-02, -7.12931738e-04, -2.03416422e-02,
       -7.52774626e-03,  3.25000437e-04, -2.94381604e-02, -1.99917215e-03,
       -1.61470268e-02, -1.25268186e-02, -2.44498067e-03, -2.84869745e-02,
       -1.03439845e-03, -8.56011827e-03,  4.75640036e-03, -1.26869231e-02,
       -5.75695001e-03, -1.07319411e-02, -5.76609187e-03, -1.77965313e-02,
       -1.31851733e-02, -7.90081359e-03, -2.03338321e-02,  7.45820906e-03,
       -4.62586395e-02, -1.29438064e-03, -3.65812220e-02, -1.79103985e-02,
       -2.73303147e-02, -1.29536865e-03,  3.47874663e-03, -1.42951738e-02,
       -2.60632113e-02, -5.51152509e-03, -2.13719532e-02, -1.11008883e-02,
       -6.27595792e-03, -7.87111279e-03, -1.81400571e-02, -2.25091130e-02,
        2.28321389e-03, -8.01308267e-03,  1.68198720e-03, -3.90162729e-02,
        3.21361795e-03, -2.81254109e-02,  2.05603498e-03, -8.87658913e-03,
       -1.69650614e-02,  7.72919506e-03, -1.72432270e-02, -5.95761789e-03,
       -7.94743840e-03,  6.21010968e-03, -5.24620758e-03, -1.60394795e-02,
        9.19438526e-03,  1.77627092e-03, -1.42523926e-02, -3.02314777e-02,
       -5.57179525e-02, -1.56601667e-02,  1.14919776e-02,  8.93954188e-03,
       -4.55616554e-03, -5.37453219e-02, -1.35848895e-02, -2.79873814e-02,
       -3.10008004e-02, -5.88388368e-03,  1.59033854e-02, -2.87615247e-02,
       -1.47559745e-02, -1.84913035e-02, -6.90278178e-03,  8.66882619e-04,
       -3.61992009e-02, -6.43488951e-03, -1.02404505e-03,  3.77353630e-03,
       -2.73252651e-02, -6.20841794e-03,  7.42547167e-03, -3.94642204e-02,
       -4.98180743e-03, -4.62195352e-02, -2.71934140e-02, -4.45132842e-03,
       -7.64856860e-03,  1.12798102e-02, -2.53161080e-02, -2.47106552e-02,
       -1.02389243e-03, -1.81879476e-02, -6.67923409e-03, -1.69746485e-03,
       -7.51050794e-03, -3.11355032e-02,  1.43236537e-02, -1.18320370e-02,
        8.67669377e-03, -1.30585199e-02,  2.17240341e-02, -1.08480491e-02,
       -6.83405262e-04, -4.08486323e-03, -1.14293359e-02, -7.14744441e-03,
       -8.58733989e-03, -1.10899443e-02, -5.25721023e-03, -4.17420752e-02,
       -5.85009158e-03,  7.65396142e-03,  3.74767173e-04, -1.45035647e-02,
        3.84327082e-04, -3.45985517e-02, -3.32370680e-03,  1.97711885e-02,
        1.44784432e-02, -8.63251556e-03, -6.40395842e-03, -2.16708817e-02,
       -1.91096663e-02, -7.63925817e-03, -7.95528758e-03, -4.42176359e-03,
       -8.22451338e-03, -7.22707761e-03, -4.58841324e-02, -1.74955353e-02,
       -2.49317102e-03, -8.49777553e-03, -2.00983305e-02, -2.35206038e-02,
        3.10163223e-03,  1.03393458e-02, -3.11627500e-02, -2.51490343e-02,
        8.23261403e-03, -6.22956315e-03, -5.80310263e-03, -2.91228550e-03,
       -8.59141443e-03,  3.46287247e-03, -5.74346026e-03, -2.31082854e-03,
       -2.78447825e-03, -5.71426516e-03, -1.02521796e-02,  8.78285430e-03,
       -6.51809853e-03,  7.57779693e-03, -1.58002134e-02,  3.67638236e-03,
       -4.18691896e-04, -1.23342394e-03, -2.78654713e-02, -9.60175786e-03,
       -7.28470692e-03, -2.23979875e-02, -7.60575198e-03, -7.47557823e-03,
       -9.09241289e-03, -3.04823443e-02,  3.23590683e-03, -2.35594958e-02,
        4.08117703e-05, -1.61645317e-03, -2.68508960e-02,  6.81756297e-03,
       -7.22541567e-03,  3.81231704e-03, -1.66736003e-02,  4.12341300e-03,
       -1.27015903e-03, -5.45816310e-03, -8.82450771e-03,  1.39733246e-02,
       -1.36170872e-02, -1.01960320e-02, -4.52219043e-03, -1.55996357e-03,
       -1.25230169e-02, -3.02172024e-02, -1.42888809e-02, -3.52008939e-02,
       -1.81326326e-02, -1.25415474e-02, -3.45787406e-03, -5.08522941e-03,
       -4.87629250e-02, -7.81741645e-03, -8.44611693e-03,  1.44849271e-02,
       -2.03485955e-02, -3.86073883e-03, -2.85048373e-02, -6.85611414e-03,
        1.54526290e-02, -1.60056651e-02,  3.91244143e-03, -2.42348434e-03,
       -4.17285487e-02, -4.15527774e-03, -8.55962001e-03, -1.47822089e-02,
       -1.03013935e-02,  5.00159280e-04, -1.07592484e-02, -1.93667561e-02,
       -5.56149613e-03, -3.28448899e-02,  1.37327216e-03, -5.64633273e-02,
        3.22783622e-03,  7.11792940e-03, -2.78341752e-02, -7.53241638e-03],
      dtype=float32), array([-5.37415296e-02,  4.09162283e-01,  3.32035124e-01,  4.64084834e-01,
        7.54416287e-01,  3.96990657e-01, -8.37494731e-02, -2.55721748e-01,
        5.15819132e-01, -1.42359668e-02,  1.99010760e-01, -2.92175412e-01,
       -1.06139727e-01,  6.23447418e-01,  2.23687440e-01,  2.36819908e-01,
        2.73275822e-01,  1.26217261e-01, -1.97292387e-01,  3.90182525e-01,
       -4.05205011e-01, -8.49189162e-02, -3.54795516e-01, -1.44391865e-01,
        3.07764024e-01, -3.13281417e-02,  1.64486423e-01, -3.07325512e-01,
        1.06741309e-01, -1.86309561e-01, -1.92290261e-01,  1.09701879e-01,
        5.48824906e-01,  4.80875105e-01, -2.53150910e-01,  5.46951234e-01,
       -1.28269047e-01, -3.75052512e-01,  3.35053146e-01, -2.54517078e-01,
       -1.75907940e-01, -1.51154503e-01, -1.50887549e-01,  4.60281402e-01,
        2.68613130e-01,  4.08858687e-01,  4.02700335e-01, -1.88028857e-01,
        1.78484887e-01,  3.73238862e-01, -2.23278359e-01,  3.51554126e-01,
        2.25631878e-01, -1.98392868e-01, -1.65908128e-01, -4.62835729e-01,
        3.96035658e-03, -2.66239762e-01, -1.07802451e-01,  4.22774665e-02,
        6.33860752e-02,  3.01364273e-01, -7.26864580e-03, -6.13994263e-02,
       -1.08172903e-02, -2.55951494e-01,  1.88198850e-01,  1.31099522e-01,
       -1.02016002e-01, -2.49763474e-01,  1.32012054e-01,  5.21906376e-01,
        1.76669419e-01,  1.68886572e-01, -2.34068394e-01, -1.04747638e-01,
       -1.78673699e-01,  2.47901991e-01,  9.79595110e-02, -2.35874757e-01,
       -3.57397497e-01,  4.57098424e-01, -9.68090370e-02,  1.24682590e-01,
        3.09386611e-01, -1.99851245e-01, -2.23588899e-01, -1.24774553e-01,
       -2.88190603e-01,  2.17086777e-01, -1.47617102e-01,  6.40360042e-02,
       -2.25461915e-01,  4.44982260e-01, -2.53573596e-01, -1.15067452e-01,
        3.22559446e-01,  2.54714310e-01, -1.43308327e-01, -1.64182678e-01,
        3.21694940e-01,  3.84830892e-01, -1.76443592e-01,  2.72863507e-01,
       -1.36977866e-01, -1.45832747e-01,  3.33700478e-02, -2.56685078e-01,
        1.17569946e-01, -2.62750238e-01, -1.21755928e-01, -2.57538617e-01,
        2.24463835e-01, -2.24521816e-01, -1.03130266e-01, -1.55682206e-01,
       -1.76424444e-01, -2.71261424e-01, -3.36874038e-01, -2.71628916e-01,
       -2.50350893e-01,  3.13596606e-01,  2.50600815e-01,  1.77570924e-01,
       -3.99389237e-01, -1.69581488e-01,  1.30597427e-01,  1.87111288e-01,
        2.28807747e-01, -4.14711863e-01,  1.06456555e-01, -2.27133751e-01,
        2.47855857e-01,  2.72369832e-01,  2.90583581e-01,  2.98813254e-01,
       -2.29395255e-01, -1.79835141e-01,  1.72263950e-01,  1.13325536e-01,
        8.47153068e-02,  4.06593025e-01,  4.40133929e-01,  3.91717581e-03,
       -1.71203360e-01,  3.04447830e-01, -3.67052734e-01, -2.80911088e-01,
       -2.24505320e-01, -1.39521360e-01,  1.71950869e-02,  9.75017846e-02,
       -1.08203791e-01,  9.48922858e-02, -2.30735973e-01, -1.34386405e-01,
       -9.68275890e-02, -7.08531514e-02,  3.79683703e-01, -7.50238076e-02,
        2.79727168e-02, -1.73899472e-01,  3.47737074e-01, -2.33870447e-02,
       -3.04198444e-01, -2.34618559e-01,  3.04326087e-01,  4.69725400e-01,
        7.28770018e-01, -3.47021610e-01, -1.65990680e-01, -1.12337142e-01,
        1.06976934e-01,  8.61614123e-02, -8.65342319e-02, -8.51596594e-02,
       -3.54510322e-02, -4.99948598e-02,  2.96692014e-01,  1.66929871e-01,
       -2.98926890e-01, -2.31640071e-01, -2.66538382e-01, -2.27989733e-01,
        1.17197828e-02, -2.13832915e-01,  8.47495943e-02, -3.00570130e-01,
       -3.69533837e-01, -2.13134006e-01, -3.99196029e-01, -1.94072902e-01,
       -2.26071775e-01, -5.01038320e-02, -2.00411901e-01, -4.84537445e-02,
       -2.41779555e-02, -3.25297415e-01, -1.77962378e-01, -1.41537607e-01,
       -1.30980268e-01,  3.01121920e-01, -2.24371925e-01, -8.59280750e-02,
       -1.20612152e-01,  2.19664454e-01,  5.40065944e-01,  7.66175747e-01,
        2.32166171e-01,  1.14080660e-01, -2.67841280e-01, -2.15033650e-01,
       -1.40830278e-01, -2.34697297e-01,  3.30922157e-01,  3.94613862e-01,
       -1.71171293e-01, -1.25569686e-01, -1.63874149e-01, -1.13039553e-01,
        3.36682081e-01,  8.94441009e-01,  4.88535352e-02, -2.02773482e-01,
       -1.04448445e-01,  2.18179330e-01, -2.54859149e-01, -3.34955484e-01,
       -2.34655872e-01, -2.01033995e-01, -4.07235265e-01, -2.78336346e-01,
        8.50439593e-02, -1.52802169e-01,  5.61270416e-01, -8.43331665e-02,
       -5.09080350e-01,  1.74305011e-02, -1.13072626e-01, -2.41559416e-01,
        2.37982124e-01,  4.86734658e-01,  2.17222080e-01,  3.00025903e-02,
        6.31332025e-03, -1.83397204e-01, -2.87958920e-01,  3.84624511e-01,
        5.35830446e-02,  2.63142407e-01, -7.63470009e-02, -1.58990890e-01,
        1.80563480e-01,  2.56989986e-01,  3.66480321e-01, -2.62775362e-01,
        3.92061651e-01, -1.83593065e-01,  1.92145593e-02, -1.19382016e-01,
        4.74706978e-01, -1.10859938e-01, -2.70077199e-01, -3.38620007e-01,
        4.64011461e-01,  8.17178190e-02,  1.60294831e-01, -3.78799550e-02,
       -2.58511424e-01, -8.01205710e-02, -2.21479833e-02, -2.71806531e-02,
        2.27310643e-01,  3.32136244e-01,  3.06093246e-01,  2.68008560e-01,
        9.95544866e-02, -2.04196360e-04,  2.23965287e-01, -2.10434094e-01,
       -5.76921068e-02, -5.21214008e-02,  1.44314259e-01, -9.12423879e-02,
       -3.17172050e-01, -4.58529480e-02, -1.21976919e-01, -2.80391127e-01,
        1.45779327e-01,  1.70693561e-01,  1.03600360e-01, -2.56893277e-01,
       -2.87926644e-01, -1.80820629e-01, -1.54134274e-01, -9.58540738e-02,
       -2.31650352e-01,  9.63137373e-02,  7.75079370e-01,  3.90953161e-02,
        2.00795412e-01, -2.27634892e-01,  4.18883227e-02,  3.45869571e-01,
        1.79949790e-01,  2.16231316e-01, -2.75359094e-01, -1.61875322e-01,
       -3.71016145e-01,  2.70781159e-01,  3.12037230e-01, -1.40968058e-02,
       -2.73391664e-01, -3.72927397e-01, -1.53761730e-01, -1.09212257e-01,
        2.35821739e-01, -2.10642368e-01,  2.64290810e-01,  6.91192150e-01,
        1.73741505e-01, -2.30779588e-01,  2.34026518e-02,  2.44815171e-01,
       -7.85972774e-02, -1.03464864e-01, -2.54431248e-01, -1.47413775e-01,
       -4.81289513e-02,  3.22025418e-01, -2.78199643e-01, -2.83868223e-01,
        2.88159162e-01, -1.19834282e-01, -1.74953669e-01,  3.74886513e-01,
       -1.56102285e-01,  3.06570351e-01, -1.17719010e-01, -1.48028612e-01,
       -1.55717984e-01, -2.82625824e-01,  1.33580729e-01,  6.45383120e-01,
       -1.02543294e-01,  7.14769185e-01,  2.14198023e-01, -1.78352639e-01,
       -1.55738667e-01, -7.75557309e-02,  7.47722536e-02, -1.20512731e-01,
        2.59857953e-01,  3.01652312e-01, -2.28324190e-01,  2.32136920e-01,
       -2.12254226e-01,  2.16753021e-01, -1.81021854e-01,  3.93464029e-01,
       -1.18433438e-01,  3.19918752e-01,  4.96788383e-01, -1.19516946e-01,
       -3.27559263e-01, -1.57507472e-02,  1.93314970e-01,  4.50773239e-01,
       -2.69780308e-01, -9.89173874e-02, -1.44682795e-01,  2.97166437e-01,
        2.72670239e-01, -2.82905877e-01, -3.83317471e-01,  1.77187994e-01,
        4.97616023e-01, -4.35515732e-01, -2.18070015e-01,  4.01776209e-02,
       -5.54920137e-02, -2.21996501e-01, -3.22822273e-01, -1.45699069e-01,
        2.09398374e-01,  5.63620664e-02, -1.63174435e-01, -3.24093848e-01,
        3.82586449e-01, -1.88429415e-01, -2.53498644e-01, -2.80311376e-01,
        2.83865273e-01, -3.32636207e-01, -1.37021199e-01, -2.40778908e-01,
       -1.84718698e-01, -6.45467639e-02,  9.35312435e-02, -2.86363125e-01,
        2.84597665e-01,  2.72414535e-02, -1.45284295e-01, -1.34915575e-01,
       -9.70245376e-02, -5.11830635e-02, -2.25953907e-01, -1.95805594e-01,
       -1.35480776e-01, -1.99853331e-01,  4.53125983e-01,  5.64535677e-01,
       -1.26662999e-01, -1.07713133e-01,  1.79570168e-01,  2.82726109e-01,
       -2.93080043e-03, -1.47623252e-02, -7.09088072e-02, -2.34691780e-02,
        1.47287279e-01,  6.15999661e-02,  2.39075243e-01,  3.29754531e-01,
        1.53293639e-01,  1.13954566e-01, -4.54483740e-02, -2.75726408e-01,
       -1.47725299e-01, -5.00396565e-02, -8.42659548e-02,  2.27330402e-02,
       -2.39508554e-01, -2.31031477e-01, -2.25461617e-01, -2.28878319e-01,
       -2.14053586e-01,  2.17707261e-01, -1.56360090e-01, -3.72047462e-02,
        2.48279184e-01, -2.29020014e-01, -8.59523639e-02, -3.64747941e-01,
       -2.97016799e-01,  3.20525050e-01,  4.39601690e-02, -1.51250750e-01,
       -1.59588397e-01,  2.88790297e-02, -2.24572897e-01, -4.69853282e-01,
        7.37757802e-01,  2.21215367e-01,  2.73225486e-01, -3.28380823e-01,
        1.68373629e-01,  2.53751248e-01, -3.50990295e-01, -4.24775273e-01,
        6.93711787e-02, -2.88584441e-01, -2.80629843e-01, -3.84797841e-01,
        4.18835402e-01, -1.46926358e-01, -2.24211052e-01, -1.75167173e-01,
        8.63886252e-02, -2.64579147e-01,  2.16837108e-01, -2.99245983e-01,
       -2.20385686e-01, -9.14455578e-02,  3.61223429e-01,  1.75968871e-01,
       -1.62266269e-01,  1.13887504e-01,  2.19150390e-02, -8.40580463e-02,
       -2.90547550e-01,  2.40211934e-01, -2.97330208e-02, -1.34527534e-01,
       -1.45040438e-01, -1.97324470e-01, -1.99003015e-02,  2.71548773e-03,
        1.34215221e-01, -2.37027198e-01, -4.52196300e-02,  1.54173402e-02,
        4.34995182e-02, -2.61334509e-01, -2.31105134e-01, -1.24334618e-02,
        2.73866177e-01, -3.16829652e-01,  3.72928418e-02,  2.33495042e-01,
       -5.11590019e-02, -3.11687350e-01, -2.47985750e-01, -2.95593053e-01,
       -1.77349105e-01, -1.41871199e-01, -3.13141674e-01,  3.08326393e-01,
        4.14689071e-03,  8.77265856e-02, -9.37267542e-02,  1.03090741e-01,
        2.04950929e-01, -3.95127714e-01,  3.02716464e-01,  6.47637546e-01,
        3.17636937e-01,  9.55793411e-02,  1.66558191e-01,  6.23047233e-01,
       -1.62243247e-01,  1.51572213e-01, -2.81041116e-01,  1.03906880e-03,
       -2.09344879e-01,  9.75917503e-02, -1.17602952e-01, -3.16462725e-01,
        1.18227646e-01, -1.63100868e-01,  2.84295529e-01, -1.90099239e-01,
        3.26406211e-01, -2.18096942e-01,  2.58027226e-01,  1.06641121e-01,
        2.21204251e-01,  2.71280259e-01, -9.38325226e-02,  6.53478950e-02,
        3.02481592e-01, -2.39658073e-01,  2.89741069e-01,  3.05539906e-01,
       -9.56145376e-02, -2.45306805e-01,  1.46157831e-01, -6.76988363e-02,
       -3.64037663e-01, -3.66299897e-01, -2.06258982e-01,  4.33745533e-01,
       -4.27124426e-02,  3.48289311e-01, -1.26285687e-01,  2.33418450e-01,
        7.43299365e-01, -7.23467395e-02,  4.43345517e-01, -2.75959760e-01,
       -5.12587242e-02, -1.05561040e-01, -2.15983409e-02, -1.11548893e-01,
        2.17127800e-01, -1.51014686e-01, -5.31984307e-03,  2.88551658e-01,
        3.99434835e-01,  9.71282795e-02, -1.81974515e-01, -2.36925662e-01,
        1.11894630e-01,  4.86437947e-01,  4.62444834e-02,  3.85958135e-01,
        6.71809137e-01, -7.96927214e-02, -3.49613428e-02, -1.17014781e-01,
        1.40970424e-01, -1.95902288e-01, -1.42075168e-02,  4.46086138e-01,
        2.54524142e-01,  2.12534636e-01,  9.69505757e-02, -1.34986565e-01,
        3.10835838e-01, -1.13433644e-01, -2.50536621e-01, -3.32575440e-01,
       -2.01699227e-01,  3.94014597e-01, -2.80822158e-01, -2.89668709e-01,
       -2.31621966e-01, -2.40040779e-01,  2.49075294e-01,  2.88410932e-01,
       -2.58640885e-01,  2.72969097e-01, -3.10235292e-01, -1.71235427e-01,
       -2.24132195e-01,  1.26753189e-03,  2.30795875e-01, -7.22303391e-02,
       -2.53479391e-01, -1.95127964e-01, -2.01523185e-01,  1.85167566e-01,
       -1.11108810e-01,  2.30980128e-01, -2.27998406e-01,  1.91255540e-01,
        1.36845514e-01,  4.95429412e-02,  7.42993355e-02,  8.29983592e-01,
        2.89448529e-01, -3.49043995e-01,  2.11152032e-01,  2.49232709e-01,
       -2.27952003e-01,  3.43113452e-01, -2.26994276e-01, -2.60517895e-01,
       -2.78302819e-01,  1.37221232e-01,  2.43463129e-01,  2.37671703e-01,
       -7.30452240e-02,  1.26558140e-01, -2.63170954e-02,  1.63279369e-01,
        4.52109635e-01,  1.93145826e-01,  2.70277262e-01, -4.40733656e-02,
       -2.55962938e-01,  1.18173428e-01, -7.63784349e-02,  2.34776422e-01,
        1.23486564e-01, -7.26055726e-02,  8.49894583e-02,  2.67430693e-01,
       -3.74569803e-01, -8.94969255e-02, -1.35841757e-01, -2.04855874e-01,
       -2.34061666e-03, -2.24418372e-01, -2.11182922e-01, -2.16436118e-01,
       -2.37335429e-01, -2.29837239e-01, -2.25268155e-01, -1.93732709e-01,
       -1.68197691e-01,  1.36938440e-02, -2.40017235e-01, -2.56998569e-01,
       -4.43375826e-01, -1.98975116e-01,  5.00983596e-01,  1.58936158e-01,
        6.82108253e-02,  5.31181812e-01,  2.67419130e-01, -8.75318423e-02,
        2.87720948e-01,  6.71103597e-01, -2.25013956e-01,  1.49306700e-01,
       -1.23661838e-01, -1.45779699e-01,  3.92599523e-01, -2.69727081e-01,
       -2.05643132e-01, -2.03436494e-01, -2.22545847e-01,  1.59834549e-01,
       -7.86572769e-02,  2.17409194e-01, -3.57235044e-01, -3.30494404e-01,
        1.71097338e-01, -2.43829846e-01, -2.86633968e-01, -1.90689012e-01,
       -1.47455989e-03,  3.61773223e-01,  3.43407243e-01,  2.71769702e-01,
       -1.75277308e-01, -2.02912241e-01, -8.50546435e-02, -9.62264761e-02,
        3.81353796e-01, -1.70919105e-01,  6.13897070e-02, -1.88041821e-01,
        2.06051275e-01, -1.26695767e-01,  2.72346467e-01, -4.70153652e-02,
       -1.84116304e-01,  1.81194574e-01, -1.47917271e-01, -2.33559132e-01,
        7.27204561e-01, -1.40097365e-01, -2.31761828e-01,  4.70250607e-01,
        1.52980968e-01, -1.90758795e-01, -1.28500432e-01,  2.12745354e-01,
       -1.97809383e-01,  3.50294024e-01, -3.07307005e-01,  1.80899918e-01,
       -4.68186438e-01, -3.88006061e-01,  4.81588274e-01, -2.79904127e-01],
      dtype=float32), array([ 0.3327807 ,  3.0484803 ,  2.6421592 ,  2.4315922 ,  7.94694   ,
        0.80904627,  0.3690651 ,  1.1436298 ,  3.6293766 ,  0.4706364 ,
        0.6468805 ,  1.1958396 ,  0.6335388 ,  4.1756024 ,  0.82986486,
        1.3334575 ,  0.748397  ,  1.9193712 ,  0.7247514 ,  1.0351443 ,
        4.4563746 ,  0.45687985,  1.5463235 ,  2.365016  ,  1.1283125 ,
        0.7445019 ,  0.38156387,  1.7096375 ,  0.70196134,  0.2775233 ,
        1.7508241 ,  0.43664563,  3.1454763 ,  4.1959786 ,  0.63232   ,
        4.570507  ,  0.31861398,  2.25473   ,  1.8212999 ,  0.74816287,
        1.3643403 ,  0.6720832 ,  1.631557  ,  2.9894674 ,  1.7988075 ,
        2.6543474 ,  2.4652126 ,  0.3654989 ,  0.83404016,  2.4347775 ,
        1.8321921 ,  2.785221  ,  1.1024752 ,  0.8742391 ,  1.0616989 ,
        2.0043108 ,  0.28524107,  2.2329998 ,  0.6198032 ,  0.40894374,
        0.41303608,  1.1595674 ,  1.533299  ,  0.74289   ,  0.40487477,
        0.47248513,  0.7226366 ,  1.1216592 ,  0.48624924,  1.747796  ,
        0.91672516,  4.6968193 ,  1.566316  ,  0.23823068,  1.0086312 ,
        0.60521007,  0.2823171 ,  1.3552487 ,  0.719022  ,  0.8490156 ,
        2.946507  ,  3.0752885 ,  0.32087886,  0.54146296,  1.3902142 ,
        0.6774586 ,  1.8641411 ,  0.53441656,  1.3145821 ,  1.284216  ,
        0.792052  ,  0.7329519 ,  1.1798353 ,  2.180963  ,  0.73399854,
        1.4624456 ,  1.6819297 ,  1.0648497 ,  0.80091166,  1.3547364 ,
        1.8129408 ,  1.7907532 ,  0.23862346,  1.2609218 ,  0.52645385,
        1.7234592 ,  0.17794108,  1.2949748 ,  0.56174016,  0.99138224,
        0.95496446,  1.4905982 ,  1.9440807 ,  0.36851966,  0.42397282,
        0.535509  ,  0.9151884 ,  1.4468007 ,  1.5770404 ,  1.7716614 ,
        0.8090787 ,  1.4183993 ,  0.7554667 ,  0.3441105 ,  2.707974  ,
        0.92519605,  0.69006824,  1.0626112 ,  0.6943812 ,  3.673677  ,
        0.45876536,  3.2250452 ,  0.77421796,  0.89062166,  1.9171238 ,
        1.035832  ,  1.8431424 ,  0.696508  ,  0.7613561 ,  0.31593698,
        0.3688552 ,  2.5735674 ,  2.9485037 ,  0.25365877,  0.7059155 ,
        0.7488766 ,  3.3940852 ,  1.2870806 ,  0.7513505 ,  0.98609185,
        1.0997144 ,  0.96252114,  0.8054091 ,  1.073553  ,  0.6290288 ,
        2.2784414 ,  0.31472716,  0.2077946 ,  1.6948085 ,  0.58882713,
        0.70673186,  0.46413264,  1.2767429 ,  0.31806263,  1.1839118 ,
        2.1167107 ,  1.8725154 ,  2.591478  ,  5.434643  ,  1.4112777 ,
        0.7778101 ,  2.0962186 ,  0.7029923 ,  0.99846935,  0.28881285,
        0.54929185,  0.2683559 ,  0.4487631 ,  2.3735845 ,  0.9086546 ,
        1.5477039 ,  0.97787327,  1.3125908 ,  2.5213904 ,  0.4351329 ,
        2.023297  ,  0.6007772 ,  2.424951  ,  2.019726  ,  1.8739098 ,
        2.3864136 ,  0.8231542 ,  0.63021624,  1.834436  ,  0.3530587 ,
        0.76591164,  0.44339368,  1.6984135 ,  0.75214416,  0.27365637,
        0.81302667,  0.7958843 ,  0.72021216,  0.45264316,  0.5775851 ,
        0.59011763,  5.2486024 ,  8.25757   ,  0.5258191 ,  0.42118046,
        1.7789074 ,  0.6835812 ,  0.75583696,  1.5173001 ,  1.3586965 ,
        2.2691164 ,  1.3034235 ,  2.600733  ,  0.69152856,  0.33655033,
        1.1698012 , 11.585928  ,  0.21970846,  0.47043055,  0.7032084 ,
        1.8144968 ,  1.0755619 ,  2.6026316 ,  0.78836936,  0.9925994 ,
        2.1237645 ,  0.87889457,  0.13162668,  2.3606582 ,  3.2419662 ,
        0.33132347,  2.9483538 ,  0.5412175 ,  2.5315578 ,  1.1797233 ,
        1.1503285 ,  4.088352  ,  0.7671806 ,  0.4078809 ,  0.26530406,
        1.2048076 ,  1.1858493 ,  2.4823444 ,  0.4033143 ,  0.83318055,
        1.7560346 ,  0.4630091 ,  0.727661  ,  1.2651488 ,  2.0749292 ,
        1.0587393 ,  1.5540378 ,  0.8618593 ,  0.38752833,  1.1045064 ,
        3.187314  ,  1.3590499 ,  1.0282688 ,  2.6109083 ,  7.3709025 ,
        0.3275083 ,  0.21009922,  0.46961287,  0.8556241 ,  0.7612951 ,
        0.4009122 ,  0.27579942,  1.4929273 ,  1.6167594 ,  1.4042997 ,
        1.4428744 ,  0.20368145,  0.3540978 ,  0.59177   ,  0.8737276 ,
        0.856081  ,  0.13064131,  0.30474886,  0.34657672,  0.90546423,
        0.5408881 ,  0.6526507 ,  2.9056683 ,  0.6855725 ,  0.31103277,
        0.96972716,  0.9250662 ,  0.89284194,  0.96736073,  1.1748428 ,
        0.9332827 ,  1.265733  ,  0.6163517 ,  6.3426595 ,  0.26555997,
        1.4048547 ,  2.0176442 ,  0.33123454,  1.4700028 ,  0.7753293 ,
        0.7423796 ,  1.1326318 ,  0.8442639 ,  0.77769184,  0.74830246,
        2.820079  ,  0.18694758,  1.2301676 ,  1.7230759 ,  0.30250356,
        0.98684675,  1.6192127 ,  0.31347242,  0.8180512 ,  8.418096  ,
        0.37450096,  1.2388036 ,  0.9298734 ,  0.8056384 ,  0.3911149 ,
        0.22320864,  0.61267585,  1.7721871 ,  0.5893099 ,  1.9291937 ,
        2.178737  ,  1.3914102 ,  1.6655521 ,  0.94803977,  0.64925206,
        3.085864  ,  1.7906884 ,  0.8280285 ,  1.0434632 ,  1.2349094 ,
        0.49527854,  1.8895397 ,  0.85078007,  5.00793   ,  1.9766347 ,
        6.2204223 ,  1.1299037 ,  0.5109858 ,  0.27567267,  0.32210118,
        0.21159221,  0.46193892,  1.345735  ,  2.6107209 ,  1.5343499 ,
        1.1275944 ,  1.7179396 ,  1.1245542 ,  0.5135225 ,  4.2155027 ,
        2.208816  ,  1.8761652 ,  3.5366733 ,  0.98087025,  1.469063  ,
        0.73438287,  0.62119436,  4.7587304 ,  2.1603613 ,  0.5811175 ,
        0.35364652,  1.7059451 ,  1.526393  ,  1.209516  ,  1.4784884 ,
        0.6311215 ,  4.5016174 ,  1.7160075 ,  1.5263135 ,  0.24731654,
        2.2668045 ,  1.0084335 ,  2.0251398 ,  0.8102063 ,  1.7155768 ,
        0.33324006,  0.5417865 ,  2.5957074 ,  1.4889973 ,  1.7077848 ,
        1.2976012 ,  1.437189  ,  1.142127  ,  1.4936242 ,  2.3640203 ,
        0.74998504,  0.8682727 ,  0.49662048,  0.4551336 ,  1.179832  ,
        1.4663656 ,  0.21711573,  0.96224856,  0.529009  ,  0.54954714,
        0.24965157,  1.636216  ,  2.092971  ,  0.87939984,  0.29275912,
        1.834341  ,  3.3505335 ,  0.55126965,  0.8258679 ,  0.5012283 ,
        2.155066  ,  0.57766384,  0.9904036 ,  0.71012646,  0.46776527,
        0.95564985,  0.54532695,  0.7456248 ,  2.274319  ,  0.72404766,
        0.27030772,  0.96259564,  1.9117601 ,  1.4702115 ,  0.5330012 ,
        0.54519624,  0.34142768,  1.2516983 ,  1.4250386 ,  1.0740052 ,
        0.8788967 ,  1.3616326 ,  0.7662453 ,  0.6067788 ,  0.6324128 ,
        0.925911  ,  0.7969184 ,  1.4379632 ,  1.7467726 ,  1.6369776 ,
        1.8494514 ,  2.1001253 ,  1.2487385 ,  0.2260442 ,  0.5259316 ,
        1.1913291 ,  3.431142  ,  7.5960627 ,  1.0334336 ,  1.5685363 ,
        1.0977054 ,  0.83664066,  0.65307117,  1.4493341 ,  3.1171844 ,
        0.882399  ,  0.8800646 ,  0.5940699 ,  2.3470306 ,  2.3220813 ,
        1.4224865 ,  0.45045528,  0.47141147,  0.311692  ,  1.5464604 ,
        2.1081705 ,  1.2651185 ,  1.6752073 ,  1.4490392 ,  3.0436482 ,
        0.28323516,  0.5418939 ,  0.7829875 ,  0.24550916,  0.7981782 ,
        0.9984502 ,  0.8087183 ,  0.56665903,  0.740747  ,  0.9039161 ,
        2.3103266 ,  0.8975315 ,  0.9629609 ,  0.49479914,  1.8775623 ,
        0.3272666 ,  0.6604664 ,  0.72994685,  0.84278405,  1.9857284 ,
        0.5145732 ,  0.757428  ,  1.2980239 ,  0.51134   ,  1.1764424 ,
        0.32504138,  2.0528712 ,  1.2136894 ,  2.126948  ,  0.5567566 ,
        1.2640896 ,  2.7316663 ,  0.74655825,  0.6907353 ,  1.0118253 ,
        0.5909646 ,  0.909649  ,  0.8245113 ,  2.016478  ,  1.8534178 ,
        7.2733445 ,  1.5128669 ,  0.221509  ,  0.6823811 ,  5.475795  ,
        1.0249026 ,  0.3104704 ,  1.3591572 ,  0.304211  ,  1.6830308 ,
        0.47327572,  0.6607831 ,  1.5578157 ,  0.6655212 ,  1.3314404 ,
        1.2722604 ,  0.558535  ,  2.3777642 ,  1.416618  ,  1.3663205 ,
        0.30485928,  1.1612418 ,  1.0600567 ,  0.57231236,  0.35274836,
        1.3451186 ,  0.52182174,  1.2750292 ,  1.6884286 ,  0.43512103,
        0.63519996,  0.6288408 ,  0.5167308 ,  2.5751507 ,  2.0336962 ,
        0.67897767,  1.6322266 ,  0.43093443,  2.251974  ,  0.6277811 ,
        0.63833207, 10.015344  ,  0.4048283 ,  2.6749928 ,  1.1807203 ,
        0.28878796,  0.6063025 ,  0.42851365,  0.7746373 ,  1.1206728 ,
        0.53568643,  0.30717993,  0.8017356 ,  1.7336986 ,  0.35249949,
        1.2372011 ,  0.7637058 ,  0.27709487,  3.2783139 ,  0.6662963 ,
        2.2201145 ,  4.0965476 ,  0.48725304,  0.5615845 ,  0.3010648 ,
        0.7382601 ,  1.506264  ,  0.22608668,  3.7392492 ,  1.4685479 ,
        0.5758794 ,  0.44010037,  1.1664021 ,  1.7346168 ,  1.0123727 ,
        1.5866731 ,  1.7898791 ,  0.5520339 ,  1.9019343 ,  1.9970872 ,
        0.74526817,  0.7082817 ,  1.371391  ,  1.599217  ,  1.7740151 ,
        0.7960871 ,  0.9937907 ,  1.0730112 ,  0.5753022 ,  0.91832405,
        1.1477549 ,  1.2714049 ,  0.39284372,  1.3258419 ,  1.793764  ,
        0.9909072 ,  0.8266897 ,  0.4537314 ,  2.3327427 ,  0.8074966 ,
        0.54557526,  0.49821183,  0.34521168,  0.20609397,  9.651462  ,
        0.71522975,  4.0330195 ,  0.6121094 ,  2.1059313 ,  0.45365545,
        2.237866  ,  0.43786362,  1.5244043 ,  1.3272835 ,  0.5302248 ,
        0.50356454,  1.5100652 ,  1.2506409 ,  0.4675336 ,  0.5070625 ,
        0.43071464,  2.2483091 ,  3.104224  ,  1.4549228 ,  0.3761041 ,
        2.1306179 ,  0.35320863,  0.78291625,  0.4142009 ,  0.47314066,
        0.81824535,  1.0122626 ,  1.687347  ,  3.499749  ,  0.40184236,
        0.25093883,  1.3558279 ,  0.37313747,  0.66246784,  0.5176731 ,
        1.1728617 ,  1.5198612 ,  1.0351692 ,  0.8886603 ,  1.1463436 ,
        2.4676082 ,  0.3605686 ,  0.6334905 ,  1.3505685 ,  3.1742208 ,
        0.7855259 ,  2.679046  ,  0.67551625,  0.30331483,  4.1635194 ,
        1.5587968 ,  0.16479151,  1.0223833 ,  3.0386534 ,  0.31408226,
        1.3117827 ,  1.8106879 ,  0.9642483 ,  1.3670127 ,  2.2459483 ,
        0.82991606,  1.1357216 ,  2.7667668 ,  0.5538095 ,  0.44537732,
        0.5351512 ,  0.9381464 ,  1.9098284 ,  1.2133638 ,  0.58969253,
        0.9587108 ,  0.8409767 ,  0.3388582 ,  1.9246323 ,  1.4855689 ,
        1.3352565 ,  1.6246852 ,  0.7269184 ,  0.6303654 ,  0.5701842 ,
        1.8090249 ,  0.49835652,  0.44144872,  1.3843865 ,  1.3629478 ,
        0.48258495,  0.88504046,  0.5690598 ,  1.5644479 ,  0.6520301 ,
        0.5586196 ,  1.3649601 ,  7.811776  ,  0.29882607,  2.1570778 ,
        2.6693866 ,  0.5467647 ,  0.76717794,  1.9029132 ,  1.2048478 ,
        0.5772554 ,  3.0432565 ,  2.4228108 ,  0.9357555 ,  2.1936617 ,
        2.2771401 ,  3.8404026 ,  1.6681666 ], dtype=float32), array([[[[-0.00846947],
         [ 0.02071366],
         [ 0.04215192],
         ...,
         [-0.02796756],
         [-0.01682374],
         [-0.02901231]],

        [[-0.00545929],
         [ 0.01907332],
         [ 0.03330569],
         ...,
         [-0.02051617],
         [ 0.00422201],
         [ 0.00737644]],

        [[ 0.03535827],
         [-0.02042649],
         [ 0.01211351],
         ...,
         [ 0.01616188],
         [ 0.02813596],
         [-0.00880417]]],


       [[[-0.01976404],
         [-0.02613015],
         [ 0.02807442],
         ...,
         [-0.01502228],
         [-0.00300005],
         [ 0.0035536 ]],

        [[ 0.03449998],
         [-0.01674033],
         [-0.00377777],
         ...,
         [ 0.01519427],
         [-0.00440162],
         [ 0.02399995]],

        [[ 0.00569672],
         [-0.02495708],
         [ 0.00632454],
         ...,
         [-0.02516125],
         [ 0.03848636],
         [-0.00917755]]],


       [[[-0.00354768],
         [-0.01428194],
         [ 0.0344804 ],
         ...,
         [-0.02021332],
         [ 0.02000448],
         [ 0.0136679 ]],

        [[-0.0207687 ],
         [ 0.02013712],
         [ 0.04177075],
         ...,
         [-0.01779166],
         [ 0.04177635],
         [-0.02967148]],

        [[-0.01423532],
         [ 0.01737646],
         [ 0.01391108],
         ...,
         [ 0.00057693],
         [-0.01247881],
         [-0.00928404]]]], dtype=float32), array([[[[-0.00268587,  0.05668257, -0.06647342, ...,  0.0163044 ,
          -0.05243562,  0.0363462 ],
         [-0.02064316,  0.05593283,  0.01788726, ...,  0.03750442,
          -0.01999911,  0.04246533],
         [ 0.00509105,  0.02540975, -0.04487963, ..., -0.01154073,
          -0.0434742 ,  0.04866126],
         ...,
         [-0.03968961,  0.06165128,  0.03536097, ...,  0.02397677,
           0.01846254, -0.03138342],
         [-0.04752889,  0.02695373,  0.03849889, ...,  0.02636993,
           0.01642253,  0.040064  ],
         [ 0.0372522 , -0.05994442,  0.01342283, ..., -0.03179685,
           0.00306481, -0.03407331]]]], dtype=float32), array([0.9963482 , 1.0053481 , 0.9987953 , ..., 1.012825  , 0.97758794,
       0.99846274], dtype=float32), array([ 0.00156032, -0.0046209 ,  0.00434061, ..., -0.00369595,
        0.00488893, -0.00638942], dtype=float32), array([ 0.02693829,  0.03003328,  0.00329791, ..., -0.01823135,
       -0.00201856, -0.03141299], dtype=float32), array([0.11184163, 0.0964446 , 0.08320562, ..., 0.084604  , 0.08471532,
       0.09937594], dtype=float32), array([[[[ 0.01678915,  0.04988911, -0.03906552, ..., -0.05093925,
           0.02989499, -0.06033453],
         [ 0.04676599, -0.02974605, -0.05343994, ..., -0.03389833,
          -0.00339439, -0.045158  ],
         [ 0.06380095,  0.02118749, -0.02026658, ...,  0.00637925,
           0.05298078,  0.04134476],
         ...,
         [-0.04974977, -0.01985743, -0.0096459 , ...,  0.01039689,
           0.03294016, -0.00234116],
         [ 0.0030471 ,  0.03120682, -0.01281084, ..., -0.052246  ,
           0.00741949, -0.00906244],
         [-0.04846167,  0.01337624, -0.0027344 , ...,  0.03467157,
          -0.03337672,  0.05110787]]]], dtype=float32), array([1.002367  , 0.9967992 , 0.99515724, ..., 0.9903002 , 1.0016704 ,
       0.9914039 ], dtype=float32), array([ 0.00156031, -0.00462091,  0.0043406 , ..., -0.00369595,
        0.00488898, -0.00638943], dtype=float32), array([-0.10406606, -0.03382408, -0.0934854 , ..., -0.17254174,
        0.12055599, -0.19509478], dtype=float32), array([521.8526  , 261.07425 , 301.39163 , ..., 274.11557 , 116.805626,
        48.76265 ], dtype=float32), array([[[[-0.01199567],
         [ 0.0001537 ],
         [-0.00071806],
         ...,
         [ 0.03114023],
         [ 0.00893599],
         [ 0.01679154]],

        [[ 0.01614075],
         [-0.01560928],
         [ 0.00729902],
         ...,
         [-0.01193405],
         [ 0.0064779 ],
         [-0.01102761]],

        [[-0.02366626],
         [ 0.008982  ],
         [ 0.00447071],
         ...,
         [ 0.02475073],
         [ 0.0179691 ],
         [-0.02389519]]],


       [[[-0.00056529],
         [-0.01808408],
         [ 0.00269308],
         ...,
         [-0.01633359],
         [ 0.01192426],
         [-0.00770907]],

        [[-0.0193677 ],
         [-0.01609904],
         [-0.00627227],
         ...,
         [-0.00915193],
         [-0.00827292],
         [ 0.01502663]],

        [[-0.02083208],
         [ 0.01084299],
         [ 0.00360403],
         ...,
         [-0.0044065 ],
         [-0.0058985 ],
         [ 0.02031088]]],


       [[[-0.02054249],
         [-0.01738125],
         [-0.0110574 ],
         ...,
         [ 0.02600057],
         [ 0.00424885],
         [-0.01598213]],

        [[ 0.01771853],
         [ 0.01151179],
         [ 0.03742103],
         ...,
         [-0.01360591],
         [-0.01255468],
         [ 0.00871721]],

        [[-0.01698685],
         [ 0.00690453],
         [-0.00333192],
         ...,
         [ 0.02538497],
         [ 0.01157913],
         [-0.00539087]]]], dtype=float32), array([[[[-0.01313852, -0.01458488,  0.05423514, ...,  0.02604388,
          -0.02627349,  0.01166215],
         [ 0.05232007,  0.02199778, -0.04392969, ...,  0.00092844,
           0.00285879, -0.02931659],
         [-0.00527789,  0.02527986,  0.00126185, ...,  0.05183494,
          -0.02778224,  0.00449783],
         ...,
         [ 0.04911867,  0.02354748,  0.00878858, ...,  0.00292787,
          -0.02687027,  0.00375365],
         [ 0.00708507,  0.02031061, -0.02635811, ..., -0.02237274,
          -0.0499883 ,  0.00701427],
         [ 0.02388863,  0.01069184, -0.01437562, ..., -0.02717936,
          -0.01977962,  0.02027901]]]], dtype=float32), array([0.9874007 , 0.98744965, 0.99118453, ..., 0.9949352 , 0.99506664,
       0.99164057], dtype=float32), array([-0.01285974, -0.00826451, -0.00988848, ..., -0.01526792,
       -0.02953358, -0.00636288], dtype=float32), array([-0.01176116, -0.00801991, -0.00748461, ...,  0.01848655,
        0.01074886, -0.02908644], dtype=float32), array([0.16276635, 0.15146527, 0.17312248, ..., 0.22384788, 0.13662663,
       0.25068915], dtype=float32), array([[[[ 2.27481220e-02],
         [-1.21501610e-02],
         [ 5.16826892e-03],
         ...,
         [-1.65598765e-02],
         [-1.26126055e-02],
         [ 1.73551831e-02]],

        [[-1.68082118e-02],
         [-1.04260230e-02],
         [ 3.04495334e-03],
         ...,
         [ 8.21077079e-03],
         [-2.31798608e-02],
         [ 1.77853070e-02]],

        [[-1.08991163e-02],
         [-3.27828713e-03],
         [-1.54396407e-02],
         ...,
         [-2.95388629e-03],
         [ 5.41420979e-03],
         [ 6.86511490e-03]]],


       [[[-8.48367065e-03],
         [-7.01539393e-05],
         [ 6.01114193e-03],
         ...,
         [ 1.73342284e-02],
         [ 3.63934436e-03],
         [-8.16123933e-03]],

        [[-6.37989817e-03],
         [ 1.76328234e-02],
         [-2.70577613e-03],
         ...,
         [ 1.05803711e-02],
         [-1.79926921e-02],
         [-1.08706718e-02]],

        [[ 2.02493742e-02],
         [-6.14126306e-03],
         [ 6.06256130e-04],
         ...,
         [ 1.31826159e-02],
         [ 6.16102340e-03],
         [ 8.99396720e-04]]],


       [[[-6.09481381e-03],
         [ 7.18556531e-03],
         [ 4.49714158e-03],
         ...,
         [ 9.20587312e-03],
         [ 2.45839451e-02],
         [ 9.53135837e-04]],

        [[ 8.03775433e-03],
         [ 2.09222864e-02],
         [ 6.40477985e-03],
         ...,
         [-3.00125591e-03],
         [ 9.29269195e-03],
         [ 8.91726185e-03]],

        [[ 1.69255747e-03],
         [ 1.07965553e-02],
         [-2.10291129e-02],
         ...,
         [-1.71798212e-03],
         [-7.32997060e-03],
         [-1.93371605e-02]]]], dtype=float32), array([[[[-0.02126325, -0.01839781, -0.00148631, ...,  0.0426232 ,
          -0.02639965,  0.03690689],
         [ 0.01137651, -0.03785216,  0.00349071, ..., -0.04218185,
           0.01914377, -0.02868685],
         [ 0.02283519, -0.04042364, -0.04287462, ...,  0.0095065 ,
           0.02563447,  0.03183229],
         ...,
         [ 0.02879261, -0.03378972, -0.00112389, ...,  0.02507788,
          -0.00942094, -0.02096093],
         [-0.00952111,  0.04568452, -0.00818155, ..., -0.00079431,
           0.03456939,  0.01293302],
         [-0.03097643, -0.04198865, -0.02942837, ..., -0.02291824,
           0.03978715, -0.0109707 ]]]], dtype=float32), array([0.96457994, 0.9878153 , 0.9851746 , ..., 0.99050295, 0.9911839 ,
       0.98199993], dtype=float32), array([-0.03842989, -0.00630813, -0.00897148, ..., -0.01403379,
       -0.00974117, -0.0142447 ], dtype=float32), array([-0.04948959, -0.07145635, -0.06919954, ...,  0.05699107,
       -0.08087052,  0.05424311], dtype=float32), array([0.14546186, 0.15246259, 0.1376819 , ..., 0.12743892, 0.1844426 ,
       0.12030631], dtype=float32), array([[ 0.03299155,  0.0361734 ],
       [-0.01484185, -0.02089168],
       [-0.03914388, -0.04253298],
       ...,
       [-0.00106338,  0.04151799],
       [-0.01485984,  0.04629659],
       [ 0.01750458,  0.03223975]], dtype=float32), array([ 0.00783205, -0.00783205], dtype=float32)]

# # np.concatenate(weights_of_MobileNet,weights_of_Inception)
# # using naive method to concat
# for i in weights_of_Inception :
#     weights_of_MobileNet.append(i)
# # weights_of_MobileNet_and_Inception = weights_of_MobileNet.append(weights_of_Inception)
# print("weights_of_MobileNet_and_Inception: ")
# print(weights_of_MobileNet)

# # np.concatenate(weights_of_MobileNet,weights_of_Inception)
# # using naive method to concat
# for i in weights_of_Xception :
#     weights_of_MobileNet.append(i)
# # weights_of_MobileNet_and_Inception = weights_of_MobileNet.append(weights_of_Inception)
# print("weights_of_MobileNet_and_Inception: ")
# print(weights_of_MobileNet)

print(type(weights_of_MobileNet))

<class 'list'>

weights_of_MobileNet_and_Inception = np.concatenate((weights_of_MobileNet[0], weights_of_Inception[0]))
print(type(weights_of_MobileNet_and_Inception))

<class 'numpy.ndarray'>

print(weights_of_MobileNet_and_Inception.shape)

(6, 3, 3, 32)

weights_of_MobileNet_Inception_and_Xception = c = np.concatenate((weights_of_MobileNet_and_Inception, weights_of_Xception[0])) #np.stack((weights_of_MobileNet_and_Inception,b), axis=3) 
print(type(weights_of_MobileNet_Inception_and_Xception))
print(weights_of_MobileNet_Inception_and_Xception.shape)

<class 'numpy.ndarray'>
(9, 3, 3, 32)

# serialize model to JSON
model_weights_for_json = ensemble_model.to_json()
with open("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.json", "w") as json_file:
    json_file.write(model_weights_for_json)
# serialize weights to HDF5
ensemble_model.save_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5")
print("Saved model to disk")

Saved model to disk

# #create a model from the weights of multiple models
# def model_weight_ensemble(members, weights):
#     #determine how many layers need to be averaged
#     n_layers = len(members[0].get_weights())
#     print("No. of Layers which need to be averaged: ")
#     print(n_layers)
#     print("The weights of the Member 0 are: ")
#     print(members[0].get_weights())
#     # avg_model_weights = list()
#     # for weight in weights:
#     #     weight = float(weight)
#     # for layer in range(n_layers):
#     #     #collect this layer from each model
#     #     layer_weights = array([model.get_weights()[layer] for model in members])
#     #     # weighted average of weights for this layer
#     #     avg_layer_weights = average(layer_weights, axis = 0, weights=weights)
#     #     #store average layer weights
#     #     avg_model_weights.append(avg_layer_weights)
#     # # create a new model with the same structure
#     # model = clone_model(members[0])
#     # # set the weights in the new
#     # model.set_weights(avg_model_weights)
#     # model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
#     return model

# create a new model with the weighted average of all model weights
# new_model = model_weight_ensemble(members, weights)

# new_model

# # summarize the created model
# new_model.summary()

5.5 Evaluating ensemble model

# Compute test set predictions
NUMBER_TEST_SAMPLES_Ensemble = 150

y_true_Ensemble = valid_targets[:NUMBER_TEST_SAMPLES_Ensemble]
y_score_Ensemble = []
for index in range(NUMBER_TEST_SAMPLES_Ensemble): #compute one at a time due to memory constraints
    image_to_predict_Ensemble = path_to_tensor(validation_files[index]).astype("float32")/255.
    probs_Ensemble = ensemble_model.predict(image_to_predict_Ensemble,)
    if np.argmax(probs_Ensemble) == 0:
        y_score_Ensemble.append([1., 0.])
    elif np.argmax(probs_Ensemble) == 1:
        y_score_Ensemble.append([0., 1.])
    print("Predicted value {}... ".format(index+1) + " Melanoma : ", probs_Ensemble[0][0],  " | Other : ", probs_Ensemble[0][1])
    print("Real values {}...".format(index+1) + "      Melanoma : ", valid_targets[index][0], "      | Other : ", valid_targets[index][1])
    print("---------------------------------------------------------------------------")
    
    
correct_Ensemble = np.array(y_true_Ensemble) == np.array(y_score_Ensemble)

Predicted value 1...  Melanoma :  0.7946493  | Other :  0.20535073
Real values 1...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 2...  Melanoma :  0.79446805  | Other :  0.20553192
Real values 2...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 3...  Melanoma :  0.79421806  | Other :  0.20578192
Real values 3...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 4...  Melanoma :  0.7943096  | Other :  0.20569041
Real values 4...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 5...  Melanoma :  0.79384565  | Other :  0.20615439
Real values 5...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 6...  Melanoma :  0.7982955  | Other :  0.20170449
Real values 6...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 7...  Melanoma :  0.79406905  | Other :  0.20593093
Real values 7...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 8...  Melanoma :  0.7938037  | Other :  0.2061963
Real values 8...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 9...  Melanoma :  0.79388565  | Other :  0.20611438
Real values 9...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 10...  Melanoma :  0.7936238  | Other :  0.20637628
Real values 10...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 11...  Melanoma :  0.7934489  | Other :  0.20655107
Real values 11...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 12...  Melanoma :  0.79373074  | Other :  0.20626931
Real values 12...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 13...  Melanoma :  0.79341  | Other :  0.20659003
Real values 13...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 14...  Melanoma :  0.79339164  | Other :  0.20660836
Real values 14...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 15...  Melanoma :  0.7939805  | Other :  0.20601958
Real values 15...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 16...  Melanoma :  0.78891885  | Other :  0.21108115
Real values 16...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 17...  Melanoma :  0.7935034  | Other :  0.20649666
Real values 17...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 18...  Melanoma :  0.7938964  | Other :  0.20610368
Real values 18...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 19...  Melanoma :  0.7949728  | Other :  0.20502728
Real values 19...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 20...  Melanoma :  0.79034805  | Other :  0.20965193
Real values 20...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 21...  Melanoma :  0.7955109  | Other :  0.20448916
Real values 21...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 22...  Melanoma :  0.76713884  | Other :  0.2328612
Real values 22...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 23...  Melanoma :  0.7934717  | Other :  0.20652834
Real values 23...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 24...  Melanoma :  0.82934296  | Other :  0.17065704
Real values 24...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 25...  Melanoma :  0.7440462  | Other :  0.25595382
Real values 25...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 26...  Melanoma :  0.7931649  | Other :  0.20683515
Real values 26...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 27...  Melanoma :  0.7935525  | Other :  0.20644751
Real values 27...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 28...  Melanoma :  0.79016924  | Other :  0.20983073
Real values 28...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 29...  Melanoma :  0.7936482  | Other :  0.20635182
Real values 29...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 30...  Melanoma :  0.7932641  | Other :  0.20673595
Real values 30...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 31...  Melanoma :  0.7814226  | Other :  0.21857744
Real values 31...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 32...  Melanoma :  0.8295269  | Other :  0.17047307
Real values 32...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 33...  Melanoma :  0.8297872  | Other :  0.1702128
Real values 33...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 34...  Melanoma :  0.7931062  | Other :  0.20689383
Real values 34...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 35...  Melanoma :  0.77920246  | Other :  0.22079754
Real values 35...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 36...  Melanoma :  0.79415584  | Other :  0.20584413
Real values 36...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 37...  Melanoma :  0.79333943  | Other :  0.20666057
Real values 37...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 38...  Melanoma :  0.793751  | Other :  0.20624898
Real values 38...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 39...  Melanoma :  0.79395187  | Other :  0.20604818
Real values 39...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 40...  Melanoma :  0.7938254  | Other :  0.20617461
Real values 40...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 41...  Melanoma :  0.775681  | Other :  0.22431898
Real values 41...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 42...  Melanoma :  0.79402065  | Other :  0.20597939
Real values 42...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 43...  Melanoma :  0.79353607  | Other :  0.20646402
Real values 43...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 44...  Melanoma :  0.7828617  | Other :  0.21713826
Real values 44...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 45...  Melanoma :  0.7817323  | Other :  0.21826774
Real values 45...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 46...  Melanoma :  0.79423374  | Other :  0.20576625
Real values 46...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 47...  Melanoma :  0.79393816  | Other :  0.20606183
Real values 47...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 48...  Melanoma :  0.7936143  | Other :  0.2063857
Real values 48...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 49...  Melanoma :  0.7941241  | Other :  0.20587584
Real values 49...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 50...  Melanoma :  0.78242064  | Other :  0.21757933
Real values 50...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 51...  Melanoma :  0.7940129  | Other :  0.20598713
Real values 51...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 52...  Melanoma :  0.77770734  | Other :  0.22229266
Real values 52...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 53...  Melanoma :  0.7936019  | Other :  0.20639817
Real values 53...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 54...  Melanoma :  0.79331326  | Other :  0.20668676
Real values 54...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 55...  Melanoma :  0.79419124  | Other :  0.20580882
Real values 55...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 56...  Melanoma :  0.79330814  | Other :  0.2066919
Real values 56...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 57...  Melanoma :  0.7935462  | Other :  0.20645377
Real values 57...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 58...  Melanoma :  0.79437876  | Other :  0.20562124
Real values 58...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 59...  Melanoma :  0.77097934  | Other :  0.22902071
Real values 59...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 60...  Melanoma :  0.8296695  | Other :  0.17033057
Real values 60...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 61...  Melanoma :  0.7950589  | Other :  0.20494112
Real values 61...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 62...  Melanoma :  0.7878059  | Other :  0.21219413
Real values 62...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 63...  Melanoma :  0.8297818  | Other :  0.17021821
Real values 63...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 64...  Melanoma :  0.77977  | Other :  0.22023004
Real values 64...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 65...  Melanoma :  0.7932207  | Other :  0.2067793
Real values 65...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 66...  Melanoma :  0.7945665  | Other :  0.20543347
Real values 66...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 67...  Melanoma :  0.7930357  | Other :  0.20696437
Real values 67...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 68...  Melanoma :  0.793774  | Other :  0.20622599
Real values 68...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 69...  Melanoma :  0.7944595  | Other :  0.20554046
Real values 69...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 70...  Melanoma :  0.7926153  | Other :  0.20738468
Real values 70...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 71...  Melanoma :  0.79388654  | Other :  0.2061135
Real values 71...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 72...  Melanoma :  0.782694  | Other :  0.21730608
Real values 72...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 73...  Melanoma :  0.7939943  | Other :  0.20600578
Real values 73...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 74...  Melanoma :  0.79323673  | Other :  0.20676325
Real values 74...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 75...  Melanoma :  0.8066156  | Other :  0.19338445
Real values 75...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 76...  Melanoma :  0.7931875  | Other :  0.2068125
Real values 76...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 77...  Melanoma :  0.79409736  | Other :  0.20590267
Real values 77...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 78...  Melanoma :  0.7939528  | Other :  0.2060472
Real values 78...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 79...  Melanoma :  0.7939517  | Other :  0.2060484
Real values 79...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 80...  Melanoma :  0.79284567  | Other :  0.20715433
Real values 80...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 81...  Melanoma :  0.79494065  | Other :  0.20505938
Real values 81...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 82...  Melanoma :  0.7937161  | Other :  0.20628399
Real values 82...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 83...  Melanoma :  0.7932672  | Other :  0.20673287
Real values 83...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 84...  Melanoma :  0.7939741  | Other :  0.20602587
Real values 84...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 85...  Melanoma :  0.79367584  | Other :  0.20632416
Real values 85...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 86...  Melanoma :  0.7937097  | Other :  0.2062903
Real values 86...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 87...  Melanoma :  0.783745  | Other :  0.21625504
Real values 87...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 88...  Melanoma :  0.7722322  | Other :  0.22776791
Real values 88...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 89...  Melanoma :  0.7941396  | Other :  0.20586036
Real values 89...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 90...  Melanoma :  0.8297133  | Other :  0.17028676
Real values 90...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 91...  Melanoma :  0.79548407  | Other :  0.20451596
Real values 91...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 92...  Melanoma :  0.81564283  | Other :  0.18435723
Real values 92...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 93...  Melanoma :  0.794963  | Other :  0.20503698
Real values 93...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 94...  Melanoma :  0.82975984  | Other :  0.17024016
Real values 94...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 95...  Melanoma :  0.79429877  | Other :  0.20570128
Real values 95...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 96...  Melanoma :  0.75853723  | Other :  0.24146281
Real values 96...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 97...  Melanoma :  0.8297259  | Other :  0.17027408
Real values 97...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 98...  Melanoma :  0.79384613  | Other :  0.20615387
Real values 98...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 99...  Melanoma :  0.7933082  | Other :  0.20669179
Real values 99...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 100...  Melanoma :  0.7933488  | Other :  0.2066512
Real values 100...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 101...  Melanoma :  0.793672  | Other :  0.206328
Real values 101...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 102...  Melanoma :  0.79405963  | Other :  0.20594037
Real values 102...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 103...  Melanoma :  0.77064764  | Other :  0.22935241
Real values 103...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 104...  Melanoma :  0.8146641  | Other :  0.1853359
Real values 104...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 105...  Melanoma :  0.7939967  | Other :  0.2060033
Real values 105...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 106...  Melanoma :  0.79341835  | Other :  0.20658168
Real values 106...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 107...  Melanoma :  0.7954488  | Other :  0.2045512
Real values 107...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 108...  Melanoma :  0.75588673  | Other :  0.2441133
Real values 108...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 109...  Melanoma :  0.7926159  | Other :  0.20738408
Real values 109...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 110...  Melanoma :  0.7637703  | Other :  0.23622975
Real values 110...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 111...  Melanoma :  0.7849947  | Other :  0.21500532
Real values 111...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 112...  Melanoma :  0.7848618  | Other :  0.21513818
Real values 112...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 113...  Melanoma :  0.794598  | Other :  0.20540199
Real values 113...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 114...  Melanoma :  0.7946787  | Other :  0.20532136
Real values 114...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 115...  Melanoma :  0.795012  | Other :  0.20498799
Real values 115...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 116...  Melanoma :  0.7963065  | Other :  0.20369357
Real values 116...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 117...  Melanoma :  0.77428377  | Other :  0.2257163
Real values 117...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 118...  Melanoma :  0.790096  | Other :  0.20990402
Real values 118...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 119...  Melanoma :  0.79647654  | Other :  0.20352346
Real values 119...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 120...  Melanoma :  0.7847605  | Other :  0.21523951
Real values 120...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 121...  Melanoma :  0.79686016  | Other :  0.20313984
Real values 121...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 122...  Melanoma :  0.78795373  | Other :  0.21204633
Real values 122...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 123...  Melanoma :  0.77808875  | Other :  0.22191124
Real values 123...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 124...  Melanoma :  0.7940876  | Other :  0.2059124
Real values 124...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 125...  Melanoma :  0.79670763  | Other :  0.20329231
Real values 125...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 126...  Melanoma :  0.7795569  | Other :  0.22044319
Real values 126...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 127...  Melanoma :  0.7960228  | Other :  0.20397723
Real values 127...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 128...  Melanoma :  0.8094191  | Other :  0.19058095
Real values 128...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 129...  Melanoma :  0.7946817  | Other :  0.20531833
Real values 129...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 130...  Melanoma :  0.7952275  | Other :  0.20477252
Real values 130...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 131...  Melanoma :  0.7913198  | Other :  0.20868024
Real values 131...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 132...  Melanoma :  0.77038074  | Other :  0.22961926
Real values 132...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 133...  Melanoma :  0.7936033  | Other :  0.20639674
Real values 133...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 134...  Melanoma :  0.7937984  | Other :  0.20620164
Real values 134...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 135...  Melanoma :  0.8228366  | Other :  0.17716348
Real values 135...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 136...  Melanoma :  0.7932342  | Other :  0.20676583
Real values 136...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 137...  Melanoma :  0.79396814  | Other :  0.2060319
Real values 137...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 138...  Melanoma :  0.7947593  | Other :  0.20524071
Real values 138...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 139...  Melanoma :  0.7710347  | Other :  0.22896531
Real values 139...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 140...  Melanoma :  0.7929396  | Other :  0.20706044
Real values 140...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 141...  Melanoma :  0.7936098  | Other :  0.2063902
Real values 141...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 142...  Melanoma :  0.7951159  | Other :  0.20488411
Real values 142...      Melanoma :  0.0       | Other :  1.0
---------------------------------------------------------------------------
Predicted value 143...  Melanoma :  0.79334015  | Other :  0.2066599
Real values 143...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 144...  Melanoma :  0.79386103  | Other :  0.20613906
Real values 144...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 145...  Melanoma :  0.7939822  | Other :  0.20601782
Real values 145...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 146...  Melanoma :  0.7945866  | Other :  0.20541345
Real values 146...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 147...  Melanoma :  0.79402375  | Other :  0.20597628
Real values 147...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 148...  Melanoma :  0.79495686  | Other :  0.20504317
Real values 148...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 149...  Melanoma :  0.79328007  | Other :  0.20671998
Real values 149...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------
Predicted value 150...  Melanoma :  0.7937859  | Other :  0.2062141
Real values 150...      Melanoma :  1.0       | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Ensemble)*100))

Accuracy = 80.00%

image_to_predict_Ensemble = path_to_tensor("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Output_melanoma/ISIC_0000000_180_angle_flipped.jpg").astype('float32')/255.
ensemble_model.predict(image_to_predict_Ensemble)

array([[0.7931409 , 0.20685914]], dtype=float32)

5.5.1 Compute Test Set Predictions

def predict_ensemble(img_path,
            model_architecture = model_architecture, 
            path_model_weight = weight_path):
    # Printing the information passed to the Predict Function
    print("Image Path: ")
    print(img_path)
    print("Arhitecture Used:")
    print(model_architecture)
    print("Path for Model Weights: ")
    print(path_model_weight)
    # Getting the tensor of image
    image_to_predict = path_to_tensor(img_path).astype('float32')/255
    # Getting the model's architecture
    model = model_architecture
    # Loading the weights
    model.load_weights(path_model_weight)
    # printing the weights
    print("Model Weights: ")
    print(model.load_weights(path_model_weight))
    # Predicting
    pred = model.predict(image_to_predict)
    print("Prediction..." + " Melanoma : ", pred[0][0], " | Other : ", pred[0][1])
    predict_0_0 = pred[0][0]
    predict_0_1 = pred[0][1]
    if np.argmax(pred) == 0:
        return [1., 0.]
    elif np.argmax(pred) == 1:
        return [0., 1.]

# Compute test set predictions
#model_architecture,path_model_weight
NUMBER_TEST_SAMPLES_Ensemble = 150

all_weights_combined_as_list = weights_of_MobileNet_Inception_and_Xception

y_true_Ensemble = valid_targets[:NUMBER_TEST_SAMPLES_Ensemble]
y_score_Ensemble = []
for index in range(NUMBER_TEST_SAMPLES_Ensemble): #compute one at a time due to memory constraints
    probs_Ensemble = predict_ensemble(img_path = validation_files[index], model_architecture = ensemble_model, path_model_weight = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5")
    print("Real values {}...".format(index+1) + "Melanoma : ", valid_targets[index][0], " | Other : ", valid_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Ensemble.append(probs_Ensemble)
    
correct_Ensemble = np.array(y_true_Ensemble) == np.array(y_score_Ensemble)

Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0004337.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946493  | Other :  0.20535073
Real values 1...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001769.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79446805  | Other :  0.20553192
Real values 2...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79421806  | Other :  0.20578192
Real values 3...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003539.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943096  | Other :  0.20569041
Real values 4...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003805.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79384565  | Other :  0.20615439
Real values 5...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7982955  | Other :  0.20170449
Real values 6...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001852.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79406905  | Other :  0.20593093
Real values 7...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003657.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938037  | Other :  0.2061963
Real values 8...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0003462.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79388565  | Other :  0.20611438
Real values 9...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0001871.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936238  | Other :  0.20637628
Real values 10...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934489  | Other :  0.20655107
Real values 11...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79373074  | Other :  0.20626931
Real values 12...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006914.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79341  | Other :  0.20659003
Real values 13...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007141.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339164  | Other :  0.20660836
Real values 14...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007344.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939805  | Other :  0.20601958
Real values 15...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007235.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78891885  | Other :  0.21108115
Real values 16...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935034  | Other :  0.20649666
Real values 17...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938964  | Other :  0.20610368
Real values 18...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0008524.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7949728  | Other :  0.20502728
Real values 19...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007528.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79034805  | Other :  0.20965193
Real values 20...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955109  | Other :  0.20448916
Real values 21...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0007332.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76713884  | Other :  0.2328612
Real values 22...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0006671.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934717  | Other :  0.20652834
Real values 23...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0010459.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82934296  | Other :  0.17065704
Real values 24...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012099.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7440462  | Other :  0.25595382
Real values 25...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012126.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931649  | Other :  0.20683515
Real values 26...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935525  | Other :  0.20644751
Real values 27...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0009995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79016924  | Other :  0.20983073
Real values 28...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936482  | Other :  0.20635182
Real values 29...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012151.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932641  | Other :  0.20673595
Real values 30...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012204.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7814226  | Other :  0.21857744
Real values 31...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012143.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8295269  | Other :  0.17047307
Real values 32...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012191.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297872  | Other :  0.1702128
Real values 33...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012109.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931062  | Other :  0.20689383
Real values 34...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012159.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77920246  | Other :  0.22079754
Real values 35...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79415584  | Other :  0.20584413
Real values 36...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012316.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79333943  | Other :  0.20666057
Real values 37...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012306.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793751  | Other :  0.20624898
Real values 38...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79395187  | Other :  0.20604818
Real values 39...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938254  | Other :  0.20617461
Real values 40...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012380.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.775681  | Other :  0.22431898
Real values 41...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79402065  | Other :  0.20597939
Real values 42...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012222.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79353607  | Other :  0.20646402
Real values 43...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012335.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7828617  | Other :  0.21713826
Real values 44...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7817323  | Other :  0.21826774
Real values 45...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79423374  | Other :  0.20576625
Real values 46...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393816  | Other :  0.20606183
Real values 47...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936143  | Other :  0.2063857
Real values 48...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012210.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941241  | Other :  0.20587584
Real values 49...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78242064  | Other :  0.21757933
Real values 50...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940129  | Other :  0.20598713
Real values 51...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77770734  | Other :  0.22229266
Real values 52...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012538.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936019  | Other :  0.20639817
Real values 53...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012684.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79331326  | Other :  0.20668676
Real values 54...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79419124  | Other :  0.20580882
Real values 55...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79330814  | Other :  0.2066919
Real values 56...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012400.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935462  | Other :  0.20645377
Real values 57...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012547.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79437876  | Other :  0.20562124
Real values 58...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77097934  | Other :  0.22902071
Real values 59...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012492.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8296695  | Other :  0.17033057
Real values 60...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012660.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950589  | Other :  0.20494112
Real values 61...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013082.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7878059  | Other :  0.21219413
Real values 62...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297818  | Other :  0.17021821
Real values 63...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77977  | Other :  0.22023004
Real values 64...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013188.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932207  | Other :  0.2067793
Real values 65...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945665  | Other :  0.20543347
Real values 66...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930357  | Other :  0.20696437
Real values 67...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793774  | Other :  0.20622599
Real values 68...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944595  | Other :  0.20554046
Real values 69...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013104.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7926153  | Other :  0.20738468
Real values 70...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013128.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79388654  | Other :  0.2061135
Real values 71...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0012959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.782694  | Other :  0.21730608
Real values 72...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013010.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939943  | Other :  0.20600578
Real values 73...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013491.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79323673  | Other :  0.20676325
Real values 74...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013549.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8066156  | Other :  0.19338445
Real values 75...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013562.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931875  | Other :  0.2068125
Real values 76...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013501.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79409736  | Other :  0.20590267
Real values 77...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939528  | Other :  0.2060472
Real values 78...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939517  | Other :  0.2060484
Real values 79...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013632.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79284567  | Other :  0.20715433
Real values 80...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013561.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79494065  | Other :  0.20505938
Real values 81...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013518.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937161  | Other :  0.20628399
Real values 82...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013527.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932672  | Other :  0.20673287
Real values 83...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013421.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939741  | Other :  0.20602587
Real values 84...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79367584  | Other :  0.20632416
Real values 85...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013898.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937097  | Other :  0.2062903
Real values 86...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013828.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.783745  | Other :  0.21625504
Real values 87...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7722322  | Other :  0.22776791
Real values 88...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941396  | Other :  0.20586036
Real values 89...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013702.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297133  | Other :  0.17028676
Real values 90...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79548407  | Other :  0.20451596
Real values 91...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013736.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.81564283  | Other :  0.18435723
Real values 92...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013651.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794963  | Other :  0.20503698
Real values 93...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82975984  | Other :  0.17024016
Real values 94...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79429877  | Other :  0.20570128
Real values 95...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0013793.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.75853723  | Other :  0.24146281
Real values 96...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297259  | Other :  0.17027408
Real values 97...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79384613  | Other :  0.20615387
Real values 98...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014428.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933082  | Other :  0.20669179
Real values 99...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014178.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933488  | Other :  0.2066512
Real values 100...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014382.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793672  | Other :  0.206328
Real values 101...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405963  | Other :  0.20594037
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77064764  | Other :  0.22935241
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014302.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8146641  | Other :  0.1853359
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939967  | Other :  0.2060033
Real values 105...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79341835  | Other :  0.20658168
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014162.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7954488  | Other :  0.2045512
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014618.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.75588673  | Other :  0.2441133
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014610.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7926159  | Other :  0.20738408
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014601.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7637703  | Other :  0.23622975
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014620.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7849947  | Other :  0.21500532
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014616.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7848618  | Other :  0.21513818
Real values 112...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014623.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794598  | Other :  0.20540199
Real values 113...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014572.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946787  | Other :  0.20532136
Real values 114...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014558.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795012  | Other :  0.20498799
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014624.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7963065  | Other :  0.20369357
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014633.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77428377  | Other :  0.2257163
Real values 117...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014597.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.790096  | Other :  0.20990402
Real values 118...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014608.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79647654  | Other :  0.20352346
Real values 119...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014611.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7847605  | Other :  0.21523951
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79686016  | Other :  0.20313984
Real values 121...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014829.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78795373  | Other :  0.21204633
Real values 122...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014635.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77808875  | Other :  0.22191124
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014857.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940876  | Other :  0.2059124
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014931.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79670763  | Other :  0.20329231
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7795569  | Other :  0.22044319
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014637.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7960228  | Other :  0.20397723
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014712.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8094191  | Other :  0.19058095
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014688.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946817  | Other :  0.20531833
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952275  | Other :  0.20477252
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7913198  | Other :  0.20868024
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77038074  | Other :  0.22961926
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936033  | Other :  0.20639674
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937984  | Other :  0.20620164
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0014979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8228366  | Other :  0.17716348
Real values 135...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015124.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932342  | Other :  0.20676583
Real values 136...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015243.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79396814  | Other :  0.2060319
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015144.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947593  | Other :  0.20524071
Real values 138...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7710347  | Other :  0.22896531
Real values 139...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015313.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7929396  | Other :  0.20706044
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936098  | Other :  0.2063902
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015256.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951159  | Other :  0.20488411
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015211.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79334015  | Other :  0.2066599
Real values 143...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015443.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79386103  | Other :  0.20613906
Real values 144...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015372.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939822  | Other :  0.20601782
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945866  | Other :  0.20541345
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015445.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79402375  | Other :  0.20597628
Real values 147...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015401.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79495686  | Other :  0.20504317
Real values 148...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015496.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79328007  | Other :  0.20671998
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Validation_Data/Data Image JPG/ISIC_0015483.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb26a05cfd0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937859  | Other :  0.2062141
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Ensemble)*100))

Accuracy = 80.00%

5.5.2 Evaluating the Model

5.5.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Ensemble = []
for i in range(len(y_true_Ensemble)):
    y_true_2_Ensemble.append(y_true_Ensemble[i][0])

5.5.2.2 Re-ordering the Predict y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Ensemble = []
for i in range(len(y_score_Ensemble)):
    y_score_2_Ensemble.append(y_score_Ensemble[i][0])

5.5.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Ensemble, y_score_2_Ensemble)

5.5.2.4 Confusion Matrix

5.5.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_Ensemble, FALSE_POSITIVE_Ensemble, TRUE_NEGATIVE_Ensemble, FALSE_NEGATIVE_Ensemble = positive_negative_measurement(y_true_2_Ensemble, y_score_2_Ensemble)
postives_negatives_Ensemble = [[TRUE_POSITIVE_Ensemble, FALSE_POSITIVE_Ensemble], 
                                [FALSE_NEGATIVE_Ensemble, TRUE_NEGATIVE_Ensemble]]

5.5.2.4.2 Obtaining the Labels

sns.set()
labels_Ensemble =  np.array([['True positive: ' + str(TRUE_POSITIVE_Ensemble),
                     'False positive: ' + str(FALSE_POSITIVE_Ensemble)],
                    ['False negative: ' + str(FALSE_NEGATIVE_Ensemble),
                     'True negative: ' + str(TRUE_POSITIVE_Ensemble)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Ensemble, annot = labels_Ensemble, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb268567210>

5.5.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Ensemble = TRUE_POSITIVE_Ensemble / (TRUE_POSITIVE_Ensemble + FALSE_NEGATIVE_Ensemble)
print("Sensitivity: ", sensitivity_Ensemble)

Sensitivity:  1.0

5.5.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Ensemble = TRUE_NEGATIVE_Ensemble / (TRUE_NEGATIVE_Ensemble + FALSE_NEGATIVE_Ensemble)
    print("Specifity: ", specifity_Ensemble)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

5.5.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Ensemble = TRUE_POSITIVE_Ensemble / (TRUE_POSITIVE_Ensemble + FALSE_POSITIVE_Ensemble)
print("Precision: ", predcision_Ensemble)

Precision:  0.8

5.5.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Ensemble = TRUE_NEGATIVE_Ensemble / (TRUE_NEGATIVE_Ensemble + FALSE_NEGATIVE_Ensemble)
    print("Negative predictive value: ", npv_Ensemble)
except:
    print("0 Negative Predictions")

0 Negative Predictions

5.5.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Ensemble = (TRUE_POSITIVE_Ensemble + TRUE_NEGATIVE_Ensemble) / (TRUE_POSITIVE_Ensemble + FALSE_POSITIVE_Ensemble + TRUE_NEGATIVE_Ensemble + FALSE_NEGATIVE_Ensemble)
print("Accuracy: ", accuracy_Ensemble)

Accuracy:  0.8

6. Evaluating the Models Individually on Testing Data

Working Flowchart:

Defining Function to calculatae Receiving Operating Characteristic curve

def compute_roc(y_true, y_score):
    """ 
    Computing the "Receiving Operating Characteristic curve" and area
    """
    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_true, y_score) 
    auroc = auc(false_positive_rate, true_positive_rate) 
    return false_positive_rate, true_positive_rate, auroc

Defining Function for Plotting the Receiving Operating Characteristic curve

def plot_roc(y_true, y_score):
    """ 
    Ploting the Receiving Operating Characteristic curve
    """
    false_positive_rate, true_positive_rate, auroc = compute_roc(y_true, y_score)
    plt.figure(figsize=(10,6))
    plt.grid()
    plt.plot(false_positive_rate, 
             true_positive_rate, 
             color='darkorange',
             lw=2, 
             label='ROC curve (area = {:.2f})'.format(auroc))
    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')
    plt.xlim([0.0, 1.0])
    plt.ylim([0.0, 1.05])
    plt.xlabel('False Positive Rate', fontsize=12)
    plt.ylabel('True Positive Rate', fontsize=12)
    plt.title('Receiver operating characteristic example', fontsize=15)
    plt.legend(loc="lower right", fontsize=14)
    plt.show()

plt.style.available

['Solarize_Light2',
 '_classic_test_patch',
 'bmh',
 'classic',
 'dark_background',
 'fast',
 'fivethirtyeight',
 'ggplot',
 'grayscale',
 'seaborn',
 'seaborn-bright',
 'seaborn-colorblind',
 'seaborn-dark',
 'seaborn-dark-palette',
 'seaborn-darkgrid',
 'seaborn-deep',
 'seaborn-muted',
 'seaborn-notebook',
 'seaborn-paper',
 'seaborn-pastel',
 'seaborn-poster',
 'seaborn-talk',
 'seaborn-ticks',
 'seaborn-white',
 'seaborn-whitegrid',
 'tableau-colorblind10']

plt.style.use("seaborn-white")

6.1 MobileNet Architecture

6.1.1 Computing Test Set Predictions

print("No. of Files in Test Data")
print(len(test_files))
print("No. of Target Values in Test Data")
print(len(test_targets))

No. of Files in Test Data
600
No. of Target Values in Test Data
600

# Compute test set predictions
NUMBER_TEST_SAMPLES_MobileNet_Test = 600

mobilenet_architecture_function = mobilenet_architecture()
mobilenet_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5"

y_true_MobileNet_Test = test_targets[:NUMBER_TEST_SAMPLES_MobileNet_Test]
print(y_true_MobileNet_Test)

Model: "model_12"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_10 (InputLayer)        [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d_12  (None, 1024)              0         
_________________________________________________________________
dense_12 (Dense)             (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________
[[1. 0.]
 [1. 0.]
 [1. 0.]
 ...
 [1. 0.]
 [1. 0.]
 [1. 0.]]

y_score_MobileNet_Test = []
count = 0
for index in range(NUMBER_TEST_SAMPLES_MobileNet_Test): #compute one at a time due to memory constraints
    count = count+1
    print(count)
    probs_MobileNet_Test = predict(img_path = test_files[index], model_architecture = mobilenet_architecture_function, path_model_weight = mobilenet_architecture_weight_path)
    print("Real values..." + "Melanoma : ", test_targets[index][0], " | Other : ", test_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_MobileNet_Test.append(probs_MobileNet_Test)
    
correct_MobileNet_Test = np.array(y_true_MobileNet_Test) == np.array(y_score_MobileNet_Test)

Streaming output truncated to the last 5000 lines.
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862681  | Other :  0.113731936
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
147
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866708  | Other :  0.11332922
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
148
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866504  | Other :  0.11334962
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
149
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862066  | Other :  0.11379336
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
150
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871077  | Other :  0.1128923
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
151
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8865779  | Other :  0.11342211
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
152
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876123  | Other :  0.11238773
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
153
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88729656  | Other :  0.11270348
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
154
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88714623  | Other :  0.11285377
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
155
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872706  | Other :  0.1127293
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
156
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88814247  | Other :  0.11185749
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
157
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8877825  | Other :  0.11221748
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
158
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876268  | Other :  0.11237317
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
159
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868117  | Other :  0.11318829
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
160
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872636  | Other :  0.11273641
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
161
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861549  | Other :  0.11384507
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
162
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88624376  | Other :  0.113756225
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
163
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88511235  | Other :  0.11488769
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
164
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872869  | Other :  0.11271315
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
165
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88744944  | Other :  0.11255056
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
166
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88601166  | Other :  0.11398834
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
167
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870349  | Other :  0.11296516
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
168
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88821083  | Other :  0.11178918
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
169
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881027  | Other :  0.11189724
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
170
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88744056  | Other :  0.11255941
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
171
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855346  | Other :  0.11446539
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
172
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867607  | Other :  0.1132393
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
173
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867696  | Other :  0.11323039
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
174
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873662  | Other :  0.11263384
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
175
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88704985  | Other :  0.1129501
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
176
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8877353  | Other :  0.11226465
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
177
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8878744  | Other :  0.112125605
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
178
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88776135  | Other :  0.112238586
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
179
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860978  | Other :  0.11390226
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
180
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857848  | Other :  0.11421518
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
181
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859886  | Other :  0.114011414
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
182
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88616633  | Other :  0.11383373
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
183
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881777  | Other :  0.1118223
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
184
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88780993  | Other :  0.11219009
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
185
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860413  | Other :  0.11395878
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
186
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88758796  | Other :  0.11241208
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
187
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887066  | Other :  0.112933956
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
188
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88680613  | Other :  0.113193795
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
189
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88814247  | Other :  0.11185755
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
190
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8877258  | Other :  0.11227422
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
191
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867642  | Other :  0.11323574
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
192
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859858  | Other :  0.1140142
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
193
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88661486  | Other :  0.11338511
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
194
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88741225  | Other :  0.112587705
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
195
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88707584  | Other :  0.112924196
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
196
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88575804  | Other :  0.114241906
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
197
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871088  | Other :  0.11289123
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
198
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853432  | Other :  0.11465682
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
199
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88641286  | Other :  0.113587126
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
200
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88570344  | Other :  0.114296585
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
201
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88734365  | Other :  0.11265639
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
202
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860617  | Other :  0.11393822
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
203
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88674784  | Other :  0.113252185
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
204
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879729  | Other :  0.11202713
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
205
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88798463  | Other :  0.11201531
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
206
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862062  | Other :  0.11379378
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
207
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88648057  | Other :  0.11351942
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
208
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.885918  | Other :  0.11408197
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
209
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8851271  | Other :  0.11487295
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
210
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88585573  | Other :  0.11414425
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
211
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.885293  | Other :  0.11470705
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
212
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88576275  | Other :  0.11423728
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
213
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88564456  | Other :  0.11435548
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
214
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861741  | Other :  0.11382591
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
215
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862289  | Other :  0.11377109
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
216
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88704497  | Other :  0.112955034
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
217
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860064  | Other :  0.11399352
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
218
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8865064  | Other :  0.113493614
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
219
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88661194  | Other :  0.11338807
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
220
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870738  | Other :  0.11292617
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
221
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88619626  | Other :  0.11380379
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
222
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88725394  | Other :  0.11274605
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
223
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852123  | Other :  0.11478774
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
224
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88731897  | Other :  0.112681024
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
225
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88589996  | Other :  0.114100024
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
226
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88714427  | Other :  0.11285579
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
227
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88595855  | Other :  0.11404152
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
228
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858007  | Other :  0.11419925
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
229
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88722163  | Other :  0.11277834
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
230
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88611466  | Other :  0.11388538
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
231
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886062  | Other :  0.113938004
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
232
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870116  | Other :  0.112988435
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
233
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855555  | Other :  0.11444449
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
234
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88684636  | Other :  0.11315359
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
235
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856582  | Other :  0.11434182
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
236
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88584983  | Other :  0.11415023
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
237
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88736945  | Other :  0.11263055
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
238
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88583475  | Other :  0.114165254
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
239
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.885749  | Other :  0.11425097
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
240
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874978  | Other :  0.11250224
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
241
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88696444  | Other :  0.11303556
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
242
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866458  | Other :  0.11335422
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
243
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863525  | Other :  0.113647535
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
244
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887058  | Other :  0.11294193
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
245
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869316  | Other :  0.11306838
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
246
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868382  | Other :  0.11316184
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
247
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875305  | Other :  0.11246954
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
248
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88718957  | Other :  0.11281046
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
249
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861103  | Other :  0.11388971
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
250
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862367  | Other :  0.11376325
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
251
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88623524  | Other :  0.11376475
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
252
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88753164  | Other :  0.11246838
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
253
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867874  | Other :  0.1132126
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
254
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855785  | Other :  0.11442144
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
255
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853261  | Other :  0.114673935
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
256
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88668203  | Other :  0.11331793
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
257
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.884858  | Other :  0.11514194
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
258
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88733923  | Other :  0.11266079
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
259
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869711  | Other :  0.113028914
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
260
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868545  | Other :  0.11314552
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
261
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88618356  | Other :  0.113816455
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
262
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875029  | Other :  0.112497136
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
263
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853594  | Other :  0.11464061
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
264
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855813  | Other :  0.114418685
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
265
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867142  | Other :  0.11328583
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
266
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852175  | Other :  0.11478248
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
267
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866381  | Other :  0.11336188
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
268
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88561386  | Other :  0.1143861
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
269
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868406  | Other :  0.11315947
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
270
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88602346  | Other :  0.113976575
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
271
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856233  | Other :  0.11437668
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
272
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863545  | Other :  0.11364553
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
273
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88737905  | Other :  0.11262094
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
274
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88494015  | Other :  0.115059786
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
275
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88639665  | Other :  0.1136033
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
276
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88576686  | Other :  0.114233114
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
277
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876475  | Other :  0.11235255
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
278
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857347  | Other :  0.11426535
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
279
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8851875  | Other :  0.11481251
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
280
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871739  | Other :  0.112826146
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
281
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869434  | Other :  0.11305654
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
282
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88464916  | Other :  0.11535085
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
283
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875241  | Other :  0.11247586
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
284
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8851157  | Other :  0.11488424
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
285
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852332  | Other :  0.11476676
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
286
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858221  | Other :  0.11417783
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
287
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855558  | Other :  0.114444196
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
288
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88678974  | Other :  0.11321027
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
289
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8854227  | Other :  0.11457734
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
290
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858934  | Other :  0.11410657
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
291
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88520575  | Other :  0.1147942
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
292
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866804  | Other :  0.11331959
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
293
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88592225  | Other :  0.114077784
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
294
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859758  | Other :  0.114024274
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
295
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853549  | Other :  0.11464513
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
296
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867769  | Other :  0.113223046
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
297
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886334  | Other :  0.11366598
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
298
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88477004  | Other :  0.11522997
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
299
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88571024  | Other :  0.11428978
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
300
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88526833  | Other :  0.1147317
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
301
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864904  | Other :  0.11350959
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
302
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8851323  | Other :  0.11486764
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
303
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856484  | Other :  0.114351586
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
304
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860303  | Other :  0.113969706
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
305
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88491243  | Other :  0.115087576
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
306
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88615716  | Other :  0.11384284
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
307
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855904  | Other :  0.11440958
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
308
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869211  | Other :  0.11307887
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
309
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886755  | Other :  0.113245
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
310
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88715637  | Other :  0.11284364
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
311
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870258  | Other :  0.112974234
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
312
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857574  | Other :  0.11424257
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
313
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88728756  | Other :  0.1127125
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
314
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866429  | Other :  0.11335713
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
315
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88631666  | Other :  0.113683335
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
316
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867794  | Other :  0.113220565
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
317
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88700026  | Other :  0.11299973
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
318
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88661075  | Other :  0.11338931
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
319
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868915  | Other :  0.11310853
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
320
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8854405  | Other :  0.114559434
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
321
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855371  | Other :  0.11446295
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
322
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870333  | Other :  0.11296668
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
323
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866977  | Other :  0.113302305
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
324
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8865112  | Other :  0.11348879
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
325
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867276  | Other :  0.11327241
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
326
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858427  | Other :  0.114157334
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
327
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88520163  | Other :  0.11479839
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
328
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873261  | Other :  0.11267385
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
329
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88607943  | Other :  0.113920614
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
330
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88672704  | Other :  0.113273
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
331
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88641924  | Other :  0.11358079
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
332
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856954  | Other :  0.1143046
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
333
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88692683  | Other :  0.11307319
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
334
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88686454  | Other :  0.11313541
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
335
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88667303  | Other :  0.11332698
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
336
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853325  | Other :  0.11466749
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
337
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871722  | Other :  0.11282778
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
338
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864817  | Other :  0.11351825
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
339
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88732356  | Other :  0.112676375
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
340
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863238  | Other :  0.11367617
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
341
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88478297  | Other :  0.115217
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
342
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861062  | Other :  0.11389378
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
343
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88596314  | Other :  0.11403686
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
344
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88738734  | Other :  0.11261273
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
345
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88738215  | Other :  0.112617865
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
346
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88596237  | Other :  0.11403767
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
347
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88515323  | Other :  0.11484672
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
348
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88575196  | Other :  0.114248045
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
349
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867259  | Other :  0.11327409
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
350
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88487643  | Other :  0.115123555
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
351
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88458556  | Other :  0.1154144
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
352
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88646543  | Other :  0.11353454
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
353
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88563144  | Other :  0.11436852
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
354
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88554037  | Other :  0.11445962
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
355
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855302  | Other :  0.11446985
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
356
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853612  | Other :  0.11463879
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
357
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88572174  | Other :  0.11427822
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
358
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88645476  | Other :  0.11354529
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
359
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860072  | Other :  0.113992766
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
360
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88698244  | Other :  0.11301755
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
361
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88675106  | Other :  0.11324896
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
362
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88553923  | Other :  0.11446078
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
363
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88732505  | Other :  0.11267492
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
364
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870434  | Other :  0.11295661
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
365
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8851144  | Other :  0.114885546
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
366
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88695395  | Other :  0.113046125
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
367
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88513786  | Other :  0.114862196
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
368
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861221  | Other :  0.11387785
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
369
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88567454  | Other :  0.11432551
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
370
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857896  | Other :  0.11421048
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
371
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857565  | Other :  0.11424352
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
372
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863145  | Other :  0.1136855
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
373
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88726616  | Other :  0.112733915
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
374
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868221  | Other :  0.11317788
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
375
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88664603  | Other :  0.11335395
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
376
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862699  | Other :  0.113730036
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
377
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88558954  | Other :  0.11441041
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
378
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88568854  | Other :  0.114311375
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
379
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88708055  | Other :  0.112919465
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
380
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863437  | Other :  0.11365628
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
381
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871708  | Other :  0.11282924
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
382
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88660467  | Other :  0.11339535
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
383
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872381  | Other :  0.11276194
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
384
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88682556  | Other :  0.11317447
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
385
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88575304  | Other :  0.114246994
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
386
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8837953  | Other :  0.1162047
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
387
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88556534  | Other :  0.11443461
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
388
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855789  | Other :  0.11442113
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
389
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864091  | Other :  0.113590896
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
390
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862887  | Other :  0.11371135
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
391
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873798  | Other :  0.11262021
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
392
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874845  | Other :  0.112515524
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
393
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88579315  | Other :  0.11420691
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
394
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868313  | Other :  0.113168776
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
395
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887066  | Other :  0.11293401
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
396
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88733387  | Other :  0.11266608
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
397
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868251  | Other :  0.113174856
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
398
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864825  | Other :  0.11351752
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
399
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88652384  | Other :  0.11347619
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
400
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88624626  | Other :  0.113753766
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
401
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871275  | Other :  0.11287247
Real values...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
402
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864635  | Other :  0.11353644
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
403
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88712645  | Other :  0.11287354
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
404
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88590556  | Other :  0.114094436
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
405
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856826  | Other :  0.11431744
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
406
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853826  | Other :  0.11461736
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
407
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856867  | Other :  0.11431328
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
408
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871297  | Other :  0.11287035
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
409
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88653785  | Other :  0.11346214
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
410
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88755906  | Other :  0.112441
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
411
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870693  | Other :  0.11293074
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
412
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88625616  | Other :  0.11374383
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
413
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852937  | Other :  0.11470625
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
414
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856478  | Other :  0.1143522
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
415
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88741976  | Other :  0.11258024
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
416
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88578016  | Other :  0.11421983
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
417
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868043  | Other :  0.11319574
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
418
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88600034  | Other :  0.113999665
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
419
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869691  | Other :  0.113030866
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
420
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88595515  | Other :  0.11404485
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
421
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88717586  | Other :  0.112824164
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
422
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8842227  | Other :  0.11577731
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
423
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8850405  | Other :  0.11495951
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
424
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88551027  | Other :  0.114489764
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
425
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88709956  | Other :  0.11290042
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
426
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88726634  | Other :  0.11273368
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
427
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88586813  | Other :  0.11413183
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
428
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88540894  | Other :  0.11459108
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
429
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864066  | Other :  0.11359345
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
430
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88556236  | Other :  0.1144376
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
431
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88420916  | Other :  0.11579083
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
432
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867559  | Other :  0.11324404
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
433
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852369  | Other :  0.11476304
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
434
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88541454  | Other :  0.114585415
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
435
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88615304  | Other :  0.113847025
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
436
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88524497  | Other :  0.11475499
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
437
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88589376  | Other :  0.11410622
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
438
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855769  | Other :  0.114423044
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
439
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88551927  | Other :  0.11448071
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
440
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88520277  | Other :  0.11479727
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
441
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855444  | Other :  0.11445564
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
442
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88727033  | Other :  0.11272967
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
443
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88711977  | Other :  0.11288025
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
444
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88746345  | Other :  0.11253653
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
445
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88761127  | Other :  0.11238875
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
446
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864933  | Other :  0.11350663
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
447
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861867  | Other :  0.11381326
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
448
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857705  | Other :  0.11422945
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
449
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8850631  | Other :  0.11493684
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
450
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88717633  | Other :  0.112823695
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
451
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88735974  | Other :  0.11264029
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
452
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88674796  | Other :  0.1132521
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
453
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874892  | Other :  0.112510785
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
454
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88567036  | Other :  0.11432962
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
455
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88615817  | Other :  0.11384184
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
456
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8853547  | Other :  0.11464532
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
457
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88707644  | Other :  0.11292354
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
458
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88582754  | Other :  0.114172444
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
459
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871348  | Other :  0.11286524
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
460
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88615555  | Other :  0.11384447
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
461
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859039  | Other :  0.11409607
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
462
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859546  | Other :  0.114045344
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
463
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8850437  | Other :  0.11495632
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
464
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88570035  | Other :  0.11429967
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
465
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88684785  | Other :  0.11315214
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
466
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8877825  | Other :  0.11221753
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
467
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862238  | Other :  0.113776185
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
468
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869344  | Other :  0.11306558
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
469
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8864257  | Other :  0.11357425
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
470
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866231  | Other :  0.113376915
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
471
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858653  | Other :  0.11413471
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
472
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8856928  | Other :  0.11430722
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
473
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861428  | Other :  0.11385723
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
474
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870019  | Other :  0.11299815
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
475
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8878794  | Other :  0.11212062
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
476
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88664645  | Other :  0.11335358
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
477
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88793904  | Other :  0.11206097
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
478
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870243  | Other :  0.11297568
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
479
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88775414  | Other :  0.11224589
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
480
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859939  | Other :  0.114006124
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
481
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887835  | Other :  0.11216502
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
482
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861004  | Other :  0.11389959
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
483
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88653773  | Other :  0.11346224
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
484
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8880682  | Other :  0.1119318
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
485
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861887  | Other :  0.11381133
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
486
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873977  | Other :  0.1126023
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
487
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886834  | Other :  0.11316602
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
488
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88626426  | Other :  0.11373582
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
489
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.888069  | Other :  0.111931
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
490
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88648075  | Other :  0.113519266
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
491
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88674587  | Other :  0.11325415
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
492
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862753  | Other :  0.1137247
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
493
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886549  | Other :  0.11345107
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
494
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875348  | Other :  0.11246518
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
495
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88622475  | Other :  0.11377533
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
496
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8861111  | Other :  0.11388891
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
497
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870111  | Other :  0.11298882
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
498
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866286  | Other :  0.113371335
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
499
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88647026  | Other :  0.11352977
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
500
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88639104  | Other :  0.11360895
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
501
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869828  | Other :  0.1130172
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
502
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88635385  | Other :  0.11364614
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
503
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868354  | Other :  0.11316458
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
504
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866397  | Other :  0.113360316
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
505
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870089  | Other :  0.112991154
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
506
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8852937  | Other :  0.114706196
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
507
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876104  | Other :  0.11238963
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
508
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858518  | Other :  0.11414826
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
509
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88535917  | Other :  0.11464087
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
510
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866642  | Other :  0.1133358
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
511
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863197  | Other :  0.1136803
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
512
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886125  | Other :  0.11387495
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
513
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866614  | Other :  0.11333859
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
514
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858153  | Other :  0.114184685
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
515
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875668  | Other :  0.11243316
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
516
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8863825  | Other :  0.11361744
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
517
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88570315  | Other :  0.114296876
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
518
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88585573  | Other :  0.11414427
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
519
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88648987  | Other :  0.113510154
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
520
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88685024  | Other :  0.11314982
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
521
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88608843  | Other :  0.11391155
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
522
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88643616  | Other :  0.11356376
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
523
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8874881  | Other :  0.112511836
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
524
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88752365  | Other :  0.11247637
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
525
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868459  | Other :  0.113154136
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
526
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870194  | Other :  0.112980664
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
527
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88717717  | Other :  0.112822846
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
528
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88825524  | Other :  0.111744694
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
529
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88713175  | Other :  0.11286824
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
530
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88803214  | Other :  0.11196792
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
531
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88696104  | Other :  0.113039
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
532
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88736415  | Other :  0.11263588
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
533
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873443  | Other :  0.11265572
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
534
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860279  | Other :  0.11397211
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
535
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879771  | Other :  0.112022825
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
536
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876418  | Other :  0.11235821
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
537
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873818  | Other :  0.11261825
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
538
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871316  | Other :  0.11286844
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
539
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88626856  | Other :  0.11373151
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
540
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8862274  | Other :  0.113772556
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
541
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876335  | Other :  0.112366505
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
542
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871236  | Other :  0.112876356
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
543
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875297  | Other :  0.11247032
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
544
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88650024  | Other :  0.11349972
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
545
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872605  | Other :  0.11273955
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
546
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860319  | Other :  0.113968104
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
547
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8854133  | Other :  0.114586726
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
548
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8873482  | Other :  0.11265178
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
549
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8869227  | Other :  0.113077305
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
550
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8879888  | Other :  0.11201118
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
551
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88743085  | Other :  0.11256913
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
552
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88687974  | Other :  0.11312022
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
553
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870544  | Other :  0.11294564
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
554
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88758695  | Other :  0.112413116
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
555
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870938  | Other :  0.112906255
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
556
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866262  | Other :  0.11337385
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
557
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88767165  | Other :  0.11232834
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
558
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8859836  | Other :  0.11401635
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
559
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868285  | Other :  0.11317158
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
560
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881249  | Other :  0.11187512
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
561
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88701236  | Other :  0.11298762
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
562
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8880651  | Other :  0.11193487
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
563
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8876783  | Other :  0.11232163
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
564
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.886619  | Other :  0.11338098
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
565
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871737  | Other :  0.11282628
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
566
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868133  | Other :  0.11318676
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
567
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88623136  | Other :  0.11376864
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
568
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88631827  | Other :  0.11368177
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
569
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88726586  | Other :  0.11273412
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
570
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88571477  | Other :  0.114285216
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
571
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871188  | Other :  0.11288116
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
572
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88675845  | Other :  0.113241576
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
573
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8877499  | Other :  0.11225014
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
574
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8857613  | Other :  0.114238724
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
575
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88826877  | Other :  0.11173122
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
576
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871098  | Other :  0.112890154
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
577
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870188  | Other :  0.11298116
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
578
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871802  | Other :  0.11281982
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
579
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88725847  | Other :  0.11274153
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
580
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867815  | Other :  0.1132185
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
581
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872198  | Other :  0.1127802
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
582
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8855639  | Other :  0.11443604
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
583
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8858832  | Other :  0.114116795
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
584
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88777786  | Other :  0.112222135
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
585
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8872196  | Other :  0.11278039
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
586
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8866637  | Other :  0.11333627
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
587
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8881971  | Other :  0.111802906
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
588
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88745433  | Other :  0.1125457
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
589
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88611597  | Other :  0.113884054
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
590
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8868724  | Other :  0.113127574
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
591
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88670415  | Other :  0.11329581
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
592
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88714886  | Other :  0.11285116
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
593
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88785297  | Other :  0.11214702
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
594
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88830304  | Other :  0.111697
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
595
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88702786  | Other :  0.112972155
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
596
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8871511  | Other :  0.11284893
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
597
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8870941  | Other :  0.11290597
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
598
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875579  | Other :  0.112442054
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
599
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8860789  | Other :  0.113921136
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
600
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268214710>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88707143  | Other :  0.112928525
Real values...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_MobileNet_Test)*100))

Accuracy = 80.50%

6.1.2 Re-ordering Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_MobileNet_Test = []
for i in range(len(y_true_MobileNet_Test)):
    y_true_2_MobileNet_Test.append(y_true_MobileNet_Test[i][0])

6.1.3 Re-ordering Predicte y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_MobileNet_Test = []
for i in range(len(y_score_MobileNet_Test)):
    y_score_2_MobileNet_Test.append(y_score_MobileNet_Test[i][0])

6.1.4 Plotting the Re-ordered ROC

plot_roc(y_true_2_MobileNet_Test, y_score_2_MobileNet_Test)

6.1.5 Confusion Matrix

6.1.5.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_MobileNet_Test, FALSE_POSITIVE_MobileNet_Test, TRUE_NEGATIVE_MobileNet_Test, FALSE_NEGATIVE_MobileNet_Test = positive_negative_measurement(y_true_2_MobileNet_Test, y_score_2_MobileNet_Test)
postives_negatives_MobileNet_Test = [[TRUE_POSITIVE_MobileNet_Test, FALSE_POSITIVE_MobileNet_Test], 
                                     [FALSE_NEGATIVE_MobileNet_Test, TRUE_NEGATIVE_MobileNet_Test]]

postives_negatives_MobileNet_Test

[[483, 117], [0, 0]]

6.1.5.2 Obtaining Labels

sns.set()
labels_MobileNet_Test =  np.array([['True positive: ' + str(TRUE_POSITIVE_MobileNet_Test),
                                    'False positive: ' + str(FALSE_POSITIVE_MobileNet_Test)],
                                    ['False negative: ' + str(FALSE_NEGATIVE_MobileNet_Test),
                                    'True negative: ' + str(TRUE_NEGATIVE_MobileNet_Test)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_MobileNet_Test, annot = labels_MobileNet_Test, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb267881c50>

labels_MobileNet_Test

array([['True positive: 483', 'False positive: 117'],
       ['False negative: 0', 'True negative: 0']], dtype='<U19')

6.1.5.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_MobileNet_Test = TRUE_POSITIVE_MobileNet_Test / (TRUE_POSITIVE_MobileNet_Test + FALSE_NEGATIVE_MobileNet_Test)
print("Sensitivity: ", sensitivity_MobileNet_Test)

Sensitivity:  1.0

6.1.5.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_MobileNet_Test = TRUE_NEGATIVE_MobileNet_Test / (TRUE_NEGATIVE_MobileNet_Test + FALSE_NEGATIVE_MobileNet_Test)
    print("Specifity: ", specifity_MobileNet_Test)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

6.1.5.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_MobileNet_Test = TRUE_POSITIVE_MobileNet_Test / (TRUE_POSITIVE_MobileNet_Test + FALSE_POSITIVE_MobileNet_Test)
print("Precision: ", predcision_MobileNet_Test)

Precision:  0.805

6.1.5.6 Calculating Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_MobileNet_Test = TRUE_NEGATIVE_MobileNet_Test / (TRUE_NEGATIVE_MobileNet_Test + FALSE_NEGATIVE_MobileNet_Test)
    print("Negative predictive value: ", npv_MobileNet_Test)
except:
    print("0 Negative Predictions")

0 Negative Predictions

6.1.5.7 Calculating Accuracy

# Accuracy 
accuracy_MobileNet_Test = (TRUE_POSITIVE_MobileNet_Test + TRUE_NEGATIVE_MobileNet_Test) / (TRUE_POSITIVE_MobileNet_Test + FALSE_POSITIVE_MobileNet_Test + TRUE_NEGATIVE_MobileNet_Test + FALSE_NEGATIVE_MobileNet_Test)
print("Accuracy: ", accuracy_MobileNet_Test)

Accuracy:  0.805

6.2 Inception Architecture

6.2.1 Compute Test Set Predictions

# Compute test set predictions
NUMBER_TEST_SAMPLES_Inception_Test = 600

inception_architecture_function = inception_architecture()
inception_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5"

y_true_Inception_Test = test_targets[:NUMBER_TEST_SAMPLES_Inception_Test]
y_score_Inception_Test = []
for index in range(NUMBER_TEST_SAMPLES_Inception_Test): #compute one at a time due to memory constraints
    probs_Inception_Test = predict(img_path = test_files[index], model_architecture = inception_architecture_function, path_model_weight = inception_architecture_weight_path)
    print("Real values {}...".format(index+1) + "Melanoma : ", test_targets[index][0], " | Other : ", test_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Inception_Test.append(probs_Inception_Test)
    
correct_Inception_Test = np.array(y_true_Inception_Test) == np.array(y_score_Inception_Test)

Streaming output truncated to the last 5000 lines.
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013414.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89559543  | Other :  0.1044046
Real values 101...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013325.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89259046  | Other :  0.10740949
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.79319865  | Other :  0.20680134
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013321.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8829239  | Other :  0.117076114
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911784  | Other :  0.108821556
Real values 105...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013374.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8258183  | Other :  0.17418167
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.94756806  | Other :  0.052431874
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013465.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8634936  | Other :  0.13650642
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013678.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9744975  | Other :  0.025502462
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013696.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9104786  | Other :  0.089521386
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013511.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9994173  | Other :  0.0005826936
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013615.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.77316654  | Other :  0.22683343
Real values 112...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8954151  | Other :  0.10458492
Real values 113...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8875364  | Other :  0.112463586
Real values 114...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013529.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.3584186e-13
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013577.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.890742  | Other :  0.109258026
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8930557  | Other :  0.10694429
Real values 117...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013602.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90080374  | Other :  0.09919622
Real values 118...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013673.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8923487  | Other :  0.10765125
Real values 119...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013512.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.2831847e-09
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9140022  | Other :  0.08599776
Real values 121...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013565.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89162844  | Other :  0.108371556
Real values 122...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013813.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.999826  | Other :  0.00017397424
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013733.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8914953  | Other :  0.10850469
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8906192  | Other :  0.10938076
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013764.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8772025  | Other :  0.12279745
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013767.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911754  | Other :  0.10882464
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013739.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.75352937  | Other :  0.24647063
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013794.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7655264  | Other :  0.23447357
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013708.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90787214  | Other :  0.09212779
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8813221  | Other :  0.11867787
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013738.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.0837043e-19
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85541517  | Other :  0.14458482
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.893059  | Other :  0.10694094
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013842.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8867537  | Other :  0.11324629
Real values 135...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89138544  | Other :  0.108614564
Real values 136...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013908.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8974459  | Other :  0.10255416
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013897.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8924706  | Other :  0.10752935
Real values 138...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013911.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949018  | Other :  0.10509818
Real values 139...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89083725  | Other :  0.10916277
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013917.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89265317  | Other :  0.10734681
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8937707  | Other :  0.10622928
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919604  | Other :  0.10803961
Real values 143...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99998987  | Other :  1.0114748e-05
Real values 144...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90370506  | Other :  0.09629496
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89125925  | Other :  0.108740754
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89775765  | Other :  0.10224237
Real values 147...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.4407122e-14
Real values 148...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89130795  | Other :  0.10869205
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910034  | Other :  0.10899657
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9216875  | Other :  0.07831249
Real values 151...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87286437  | Other :  0.12713568
Real values 152...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8957181  | Other :  0.10428188
Real values 153...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.96046543  | Other :  0.039534524
Real values 154...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89630353  | Other :  0.103696406
Real values 155...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8936427  | Other :  0.10635729
Real values 156...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8924932  | Other :  0.10750683
Real values 157...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910481  | Other :  0.10895189
Real values 158...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8913211  | Other :  0.10867889
Real values 159...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89085084  | Other :  0.109149136
Real values 160...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89139575  | Other :  0.10860427
Real values 161...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  3.642063e-09
Real values 162...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8921067  | Other :  0.10789332
Real values 163...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.999713  | Other :  0.00028697716
Real values 164...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89251  | Other :  0.10748993
Real values 165...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.890861  | Other :  0.10913902
Real values 166...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908744  | Other :  0.10912554
Real values 167...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925565  | Other :  0.10744351
Real values 168...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8927156  | Other :  0.107284434
Real values 169...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8931447  | Other :  0.106855266
Real values 170...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8943284  | Other :  0.10567162
Real values 171...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89128315  | Other :  0.10871689
Real values 172...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.890948  | Other :  0.10905197
Real values 173...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89192235  | Other :  0.10807772
Real values 174...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89078087  | Other :  0.10921913
Real values 175...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8912493  | Other :  0.10875064
Real values 176...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86127234  | Other :  0.13872771
Real values 177...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89068705  | Other :  0.10931302
Real values 178...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7712451  | Other :  0.22875488
Real values 179...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.93917996  | Other :  0.06082
Real values 180...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8994939  | Other :  0.10050612
Real values 181...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911146  | Other :  0.10888544
Real values 182...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89106965  | Other :  0.10893032
Real values 183...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89300454  | Other :  0.10699549
Real values 184...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.96386224  | Other :  0.03613779
Real values 185...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89068806  | Other :  0.10931189
Real values 186...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99831843  | Other :  0.0016815844
Real values 187...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8907153  | Other :  0.10928474
Real values 188...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89165676  | Other :  0.10834319
Real values 189...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892954  | Other :  0.10704606
Real values 190...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.2473849e-13
Real values 191...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.850961  | Other :  0.14903893
Real values 192...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8575185  | Other :  0.14248154
Real values 193...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.96844965  | Other :  0.031550378
Real values 194...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949734  | Other :  0.1050266
Real values 195...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9082024  | Other :  0.091797605
Real values 196...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89908856  | Other :  0.100911364
Real values 197...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8462224  | Other :  0.15377755
Real values 198...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.900522  | Other :  0.09947803
Real values 199...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7834356  | Other :  0.21656442
Real values 200...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89146453  | Other :  0.10853551
Real values 201...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.80958116  | Other :  0.19041882
Real values 202...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8990332  | Other :  0.100966826
Real values 203...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.97053605  | Other :  0.029463926
Real values 204...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88607025  | Other :  0.11392974
Real values 205...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8089514  | Other :  0.1910486
Real values 206...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87931895  | Other :  0.12068098
Real values 207...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89718556  | Other :  0.1028144
Real values 208...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90436465  | Other :  0.095635355
Real values 209...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88180524  | Other :  0.118194744
Real values 210...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89140093  | Other :  0.10859903
Real values 211...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.894167  | Other :  0.10583303
Real values 212...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8886756  | Other :  0.111324385
Real values 213...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89405215  | Other :  0.10594786
Real values 214...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8678242  | Other :  0.13217582
Real values 215...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.93351614  | Other :  0.06648383
Real values 216...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8986698  | Other :  0.10133022
Real values 217...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9064339  | Other :  0.09356608
Real values 218...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.83833385  | Other :  0.16166621
Real values 219...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90288454  | Other :  0.097115524
Real values 220...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89710706  | Other :  0.10289296
Real values 221...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8990479  | Other :  0.10095204
Real values 222...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89934045  | Other :  0.10065959
Real values 223...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8712395  | Other :  0.1287605
Real values 224...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925623  | Other :  0.10743761
Real values 225...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8568379  | Other :  0.143162
Real values 226...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89569306  | Other :  0.10430698
Real values 227...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85708123  | Other :  0.14291881
Real values 228...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88998616  | Other :  0.11001383
Real values 229...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8931468  | Other :  0.106853224
Real values 230...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.898175  | Other :  0.101825
Real values 231...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89396584  | Other :  0.10603418
Real values 232...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8570295  | Other :  0.14297056
Real values 233...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949392  | Other :  0.105060786
Real values 234...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89253074  | Other :  0.10746931
Real values 235...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892182  | Other :  0.10781806
Real values 236...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932706  | Other :  0.106729366
Real values 237...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925368  | Other :  0.10746318
Real values 238...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8978674  | Other :  0.10213263
Real values 239...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89370966  | Other :  0.1062904
Real values 240...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90071577  | Other :  0.09928429
Real values 241...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89311075  | Other :  0.106889196
Real values 242...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89258456  | Other :  0.107415415
Real values 243...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8936366  | Other :  0.10636336
Real values 244...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8978465  | Other :  0.10215342
Real values 245...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89345264  | Other :  0.10654739
Real values 246...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8935426  | Other :  0.10645743
Real values 247...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915409  | Other :  0.10845912
Real values 248...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89914495  | Other :  0.10085503
Real values 249...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89295924  | Other :  0.107040755
Real values 250...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89568543  | Other :  0.10431459
Real values 251...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.899445  | Other :  0.10055499
Real values 252...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89318323  | Other :  0.10681683
Real values 253...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89229953  | Other :  0.10770041
Real values 254...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89710987  | Other :  0.10289011
Real values 255...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89212483  | Other :  0.107875176
Real values 256...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8917338  | Other :  0.10826612
Real values 257...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8729765  | Other :  0.1270235
Real values 258...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933846  | Other :  0.10661537
Real values 259...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8941179  | Other :  0.10588206
Real values 260...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89849997  | Other :  0.10150005
Real values 261...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8775134  | Other :  0.12248659
Real values 262...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8945821  | Other :  0.10541791
Real values 263...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89684266  | Other :  0.10315738
Real values 264...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85224307  | Other :  0.14775693
Real values 265...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929921  | Other :  0.10700788
Real values 266...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926317  | Other :  0.107368335
Real values 267...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8920888  | Other :  0.1079112
Real values 268...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89613  | Other :  0.10386993
Real values 269...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.899996  | Other :  0.10000403
Real values 270...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89265114  | Other :  0.10734888
Real values 271...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8928522  | Other :  0.107147776
Real values 272...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8927472  | Other :  0.10725282
Real values 273...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8914657  | Other :  0.10853426
Real values 274...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8556552  | Other :  0.14434479
Real values 275...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89574575  | Other :  0.104254216
Real values 276...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.81005335  | Other :  0.18994668
Real values 277...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88375205  | Other :  0.116247915
Real values 278...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892561  | Other :  0.10743896
Real values 279...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.893275  | Other :  0.106724955
Real values 280...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8931857  | Other :  0.106814265
Real values 281...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916622  | Other :  0.10833785
Real values 282...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9012352  | Other :  0.09876483
Real values 283...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8948155  | Other :  0.10518448
Real values 284...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89401186  | Other :  0.105988175
Real values 285...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86466455  | Other :  0.13533542
Real values 286...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88549894  | Other :  0.11450102
Real values 287...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933745  | Other :  0.10662548
Real values 288...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8917966  | Other :  0.108203374
Real values 289...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89530534  | Other :  0.10469466
Real values 290...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89195853  | Other :  0.10804145
Real values 291...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8962482  | Other :  0.10375177
Real values 292...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89258647  | Other :  0.10741354
Real values 293...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8523262  | Other :  0.1476738
Real values 294...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89678186  | Other :  0.103218146
Real values 295...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8538671  | Other :  0.14613293
Real values 296...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89687854  | Other :  0.1031215
Real values 297...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89216137  | Other :  0.10783866
Real values 298...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89306426  | Other :  0.1069357
Real values 299...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892259  | Other :  0.10774102
Real values 300...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8934633  | Other :  0.10653667
Real values 301...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919774  | Other :  0.10802256
Real values 302...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926327  | Other :  0.107367285
Real values 303...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933007  | Other :  0.106699295
Real values 304...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8970814  | Other :  0.102918565
Real values 305...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8821324  | Other :  0.117867656
Real values 306...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8921718  | Other :  0.10782813
Real values 307...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8980875  | Other :  0.10191252
Real values 308...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8958438  | Other :  0.10415618
Real values 309...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8951022  | Other :  0.104897775
Real values 310...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8923887  | Other :  0.107611336
Real values 311...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926653  | Other :  0.10733468
Real values 312...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89405805  | Other :  0.105941944
Real values 313...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89268297  | Other :  0.10731702
Real values 314...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89219195  | Other :  0.10780803
Real values 315...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89703435  | Other :  0.10296566
Real values 316...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99147147  | Other :  0.008528515
Real values 317...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929043  | Other :  0.10709574
Real values 318...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.893878  | Other :  0.10612204
Real values 319...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.92264277  | Other :  0.077357225
Real values 320...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8945972  | Other :  0.10540284
Real values 321...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87776345  | Other :  0.12223651
Real values 322...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89641094  | Other :  0.10358905
Real values 323...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8936483  | Other :  0.1063517
Real values 324...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8944974  | Other :  0.10550258
Real values 325...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9026299  | Other :  0.097370066
Real values 326...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89187604  | Other :  0.108123995
Real values 327...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9282176  | Other :  0.07178235
Real values 328...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89274424  | Other :  0.10725579
Real values 329...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8753426  | Other :  0.12465733
Real values 330...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.81012917  | Other :  0.1898708
Real values 331...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8983193  | Other :  0.101680696
Real values 332...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89313805  | Other :  0.106861986
Real values 333...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89776534  | Other :  0.10223469
Real values 334...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89703065  | Other :  0.102969356
Real values 335...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8935079  | Other :  0.106492035
Real values 336...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89712965  | Other :  0.10287033
Real values 337...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89677614  | Other :  0.10322388
Real values 338...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89641243  | Other :  0.10358759
Real values 339...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99660623  | Other :  0.0033937758
Real values 340...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89221525  | Other :  0.1077847
Real values 341...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8650813  | Other :  0.13491866
Real values 342...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8967684  | Other :  0.10323167
Real values 343...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8468472  | Other :  0.15315284
Real values 344...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8943884  | Other :  0.105611674
Real values 345...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89294165  | Other :  0.10705833
Real values 346...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916172  | Other :  0.108382866
Real values 347...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8731434  | Other :  0.12685667
Real values 348...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85572594  | Other :  0.144274
Real values 349...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89259225  | Other :  0.10740769
Real values 350...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919375  | Other :  0.10806247
Real values 351...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926791  | Other :  0.107320935
Real values 352...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8891921  | Other :  0.110807896
Real values 353...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8928894  | Other :  0.107110605
Real values 354...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89303344  | Other :  0.10696657
Real values 355...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8966684  | Other :  0.10333161
Real values 356...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932344  | Other :  0.106765606
Real values 357...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8941928  | Other :  0.10580715
Real values 358...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918269  | Other :  0.10817308
Real values 359...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86204076  | Other :  0.13795924
Real values 360...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8933898  | Other :  0.1066102
Real values 361...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9076082  | Other :  0.09239178
Real values 362...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89627224  | Other :  0.10372774
Real values 363...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929391  | Other :  0.10706091
Real values 364...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918516  | Other :  0.10814838
Real values 365...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.887975  | Other :  0.112025015
Real values 366...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89719516  | Other :  0.10280484
Real values 367...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8934555  | Other :  0.106544554
Real values 368...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8985262  | Other :  0.1014738
Real values 369...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89705145  | Other :  0.1029486
Real values 370...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8945961  | Other :  0.1054039
Real values 371...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949035  | Other :  0.10509653
Real values 372...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.967224  | Other :  0.03277599
Real values 373...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8935582  | Other :  0.106441855
Real values 374...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88127166  | Other :  0.118728384
Real values 375...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8927932  | Other :  0.1072068
Real values 376...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89835924  | Other :  0.10164081
Real values 377...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8975645  | Other :  0.10243553
Real values 378...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9884688  | Other :  0.011531198
Real values 379...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89367926  | Other :  0.106320776
Real values 380...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89991874  | Other :  0.10008124
Real values 381...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89798933  | Other :  0.10201067
Real values 382...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8928343  | Other :  0.10716569
Real values 383...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8937178  | Other :  0.10628213
Real values 384...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89468217  | Other :  0.10531778
Real values 385...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926852  | Other :  0.10731481
Real values 386...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89258915  | Other :  0.10741092
Real values 387...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87817043  | Other :  0.12182959
Real values 388...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.79527134  | Other :  0.20472868
Real values 389...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90135354  | Other :  0.09864647
Real values 390...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90135616  | Other :  0.09864383
Real values 391...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8934725  | Other :  0.10652751
Real values 392...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89477175  | Other :  0.10522818
Real values 393...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8981932  | Other :  0.10180677
Real values 394...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89815855  | Other :  0.10184142
Real values 395...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.999997  | Other :  3.0248564e-06
Real values 396...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90056014  | Other :  0.09943979
Real values 397...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932626  | Other :  0.10673737
Real values 398...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916384  | Other :  0.108361624
Real values 399...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89187235  | Other :  0.10812769
Real values 400...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89448756  | Other :  0.1055125
Real values 401...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89740336  | Other :  0.10259662
Real values 402...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8914955  | Other :  0.10850446
Real values 403...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8923485  | Other :  0.1076515
Real values 404...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9009299  | Other :  0.09907009
Real values 405...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89552295  | Other :  0.10447703
Real values 406...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.87283033  | Other :  0.12716964
Real values 407...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9227221  | Other :  0.07727792
Real values 408...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9017779  | Other :  0.098222025
Real values 409...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90329957  | Other :  0.09670042
Real values 410...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89588207  | Other :  0.10411788
Real values 411...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7691117  | Other :  0.23088835
Real values 412...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8067234  | Other :  0.19327657
Real values 413...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8947669  | Other :  0.10523307
Real values 414...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.860366  | Other :  0.139634
Real values 415...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89843696  | Other :  0.10156301
Real values 416...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9742854  | Other :  0.025714623
Real values 417...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89288205  | Other :  0.107118
Real values 418...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.830122  | Other :  0.16987795
Real values 419...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8964711  | Other :  0.10352894
Real values 420...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9026088  | Other :  0.09739124
Real values 421...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8956858  | Other :  0.104314215
Real values 422...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89865774  | Other :  0.10134223
Real values 423...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8930187  | Other :  0.106981285
Real values 424...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9339098  | Other :  0.06609021
Real values 425...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88772935  | Other :  0.11227064
Real values 426...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8996464  | Other :  0.10035361
Real values 427...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915622  | Other :  0.10843783
Real values 428...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.830287  | Other :  0.16971304
Real values 429...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925815  | Other :  0.10741846
Real values 430...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918123  | Other :  0.10818769
Real values 431...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8932918  | Other :  0.10670828
Real values 432...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8923963  | Other :  0.107603736
Real values 433...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915931  | Other :  0.108406946
Real values 434...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7964039  | Other :  0.20359609
Real values 435...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89626545  | Other :  0.103734575
Real values 436...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89575243  | Other :  0.10424753
Real values 437...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8701785  | Other :  0.12982151
Real values 438...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8632145  | Other :  0.13678546
Real values 439...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9036912  | Other :  0.09630886
Real values 440...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926298  | Other :  0.10737021
Real values 441...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89695495  | Other :  0.10304501
Real values 442...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9024755  | Other :  0.09752454
Real values 443...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99999905  | Other :  9.529833e-07
Real values 444...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89425087  | Other :  0.10574915
Real values 445...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88632303  | Other :  0.11367696
Real values 446...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7915233  | Other :  0.20847668
Real values 447...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.88571906  | Other :  0.11428092
Real values 448...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916249  | Other :  0.10837508
Real values 449...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8934611  | Other :  0.10653892
Real values 450...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8956746  | Other :  0.1043254
Real values 451...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89642185  | Other :  0.103578135
Real values 452...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9040539  | Other :  0.09594609
Real values 453...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8599242  | Other :  0.14007576
Real values 454...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90536124  | Other :  0.094638795
Real values 455...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.895581  | Other :  0.10441901
Real values 456...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8949418  | Other :  0.10505824
Real values 457...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892969  | Other :  0.107030965
Real values 458...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8609782  | Other :  0.13902181
Real values 459...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89455897  | Other :  0.10544103
Real values 460...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8928066  | Other :  0.1071934
Real values 461...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8922224  | Other :  0.1077776
Real values 462...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8920704  | Other :  0.107929565
Real values 463...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929292  | Other :  0.1070708
Real values 464...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8931256  | Other :  0.10687443
Real values 465...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8849541  | Other :  0.115045965
Real values 466...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8962366  | Other :  0.10376335
Real values 467...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89309233  | Other :  0.10690765
Real values 468...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89851165  | Other :  0.10148832
Real values 469...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86161625  | Other :  0.1383837
Real values 470...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8922287  | Other :  0.10777125
Real values 471...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8961248  | Other :  0.10387517
Real values 472...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926733  | Other :  0.10732674
Real values 473...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8918741  | Other :  0.10812591
Real values 474...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8974109  | Other :  0.102589026
Real values 475...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90434116  | Other :  0.095658876
Real values 476...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89232326  | Other :  0.10767672
Real values 477...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  4.2831705e-10
Real values 478...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89404064  | Other :  0.105959326
Real values 479...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.83946437  | Other :  0.16053565
Real values 480...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89242625  | Other :  0.107573755
Real values 481...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86188066  | Other :  0.13811933
Real values 482...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89104354  | Other :  0.10895652
Real values 483...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8916127  | Other :  0.10838724
Real values 484...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8943469  | Other :  0.10565309
Real values 485...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89241856  | Other :  0.10758136
Real values 486...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89094615  | Other :  0.109053895
Real values 487...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9896902  | Other :  0.010309779
Real values 488...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89296216  | Other :  0.10703779
Real values 489...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8929003  | Other :  0.107099704
Real values 490...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8959082  | Other :  0.10409178
Real values 491...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909856  | Other :  0.109014414
Real values 492...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85683495  | Other :  0.14316504
Real values 493...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  2.7914476e-14
Real values 494...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7110036  | Other :  0.28899643
Real values 495...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9017567  | Other :  0.098243296
Real values 496...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8596729  | Other :  0.14032714
Real values 497...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.891209  | Other :  0.108791016
Real values 498...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89092606  | Other :  0.10907389
Real values 499...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909565  | Other :  0.10904345
Real values 500...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89119357  | Other :  0.10880641
Real values 501...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.99533254  | Other :  0.0046674106
Real values 502...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9986411  | Other :  0.0013589141
Real values 503...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910243  | Other :  0.10897569
Real values 504...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.890929  | Other :  0.10907102
Real values 505...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8925378  | Other :  0.107462294
Real values 506...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8920055  | Other :  0.1079945
Real values 507...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.81742775  | Other :  0.1825722
Real values 508...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8922729  | Other :  0.1077271
Real values 509...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8063038  | Other :  0.19369625
Real values 510...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89085966  | Other :  0.10914031
Real values 511...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8912196  | Other :  0.108780384
Real values 512...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89096695  | Other :  0.10903308
Real values 513...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89373076  | Other :  0.106269196
Real values 514...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8907501  | Other :  0.109249905
Real values 515...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909795  | Other :  0.10902051
Real values 516...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8637411  | Other :  0.13625887
Real values 517...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8950471  | Other :  0.104952924
Real values 518...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.77381206  | Other :  0.22618793
Real values 519...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908658  | Other :  0.10913415
Real values 520...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908523  | Other :  0.10914773
Real values 521...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908247  | Other :  0.10917537
Real values 522...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.5247598e-15
Real values 523...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89069015  | Other :  0.10930983
Real values 524...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909937  | Other :  0.109006226
Real values 525...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909259  | Other :  0.1090741
Real values 526...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89080507  | Other :  0.109194875
Real values 527...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89177173  | Other :  0.10822825
Real values 528...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89247245  | Other :  0.10752759
Real values 529...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908734  | Other :  0.109126635
Real values 530...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89084506  | Other :  0.10915494
Real values 531...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8906437  | Other :  0.10935629
Real values 532...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89089686  | Other :  0.10910313
Real values 533...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8919606  | Other :  0.10803941
Real values 534...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89321744  | Other :  0.10678254
Real values 535...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89286995  | Other :  0.10712998
Real values 536...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9890142  | Other :  0.010985808
Real values 537...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911428  | Other :  0.10885718
Real values 538...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89093536  | Other :  0.109064646
Real values 539...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89194834  | Other :  0.10805167
Real values 540...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8913085  | Other :  0.1086915
Real values 541...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89127576  | Other :  0.10872426
Real values 542...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.9680998e-08
Real values 543...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  2.7745373e-13
Real values 544...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8810678  | Other :  0.118932135
Real values 545...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8907558  | Other :  0.10924425
Real values 546...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.81148046  | Other :  0.18851955
Real values 547...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89738166  | Other :  0.10261836
Real values 548...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89107627  | Other :  0.108923785
Real values 549...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90195197  | Other :  0.09804799
Real values 550...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9999447  | Other :  5.5298016e-05
Real values 551...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.85330015  | Other :  0.14669983
Real values 552...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908792  | Other :  0.10912071
Real values 553...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8906422  | Other :  0.109357744
Real values 554...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8911835  | Other :  0.108816445
Real values 555...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.7962318  | Other :  0.20376818
Real values 556...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8906859  | Other :  0.1093141
Real values 557...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89319617  | Other :  0.10680386
Real values 558...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8907246  | Other :  0.10927546
Real values 559...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8917826  | Other :  0.10821743
Real values 560...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8910454  | Other :  0.10895458
Real values 561...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.90079623  | Other :  0.099203736
Real values 562...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.86684966  | Other :  0.13315034
Real values 563...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89087677  | Other :  0.1091232
Real values 564...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908023  | Other :  0.10919769
Real values 565...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8913982  | Other :  0.10860179
Real values 566...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89239484  | Other :  0.10760518
Real values 567...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89614356  | Other :  0.10385649
Real values 568...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89295274  | Other :  0.10704728
Real values 569...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8945095  | Other :  0.105490476
Real values 570...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8975024  | Other :  0.1024976
Real values 571...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908659  | Other :  0.10913413
Real values 572...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89101076  | Other :  0.10898922
Real values 573...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8926046  | Other :  0.10739534
Real values 574...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8912589  | Other :  0.10874107
Real values 575...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.892586  | Other :  0.10741405
Real values 576...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.890625  | Other :  0.10937498
Real values 577...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89114046  | Other :  0.10885956
Real values 578...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8952136  | Other :  0.10478636
Real values 579...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8913192  | Other :  0.10868078
Real values 580...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89095813  | Other :  0.10904188
Real values 581...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8912481  | Other :  0.10875186
Real values 582...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  4.066025e-08
Real values 583...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8908763  | Other :  0.10912366
Real values 584...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89110494  | Other :  0.10889509
Real values 585...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  4.766386e-11
Real values 586...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8931405  | Other :  0.106859505
Real values 587...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  6.057905e-13
Real values 588...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.9453498  | Other :  0.0546502
Real values 589...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8909454  | Other :  0.10905462
Real values 590...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  9.7019784e-14
Real values 591...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89283264  | Other :  0.10716742
Real values 592...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8915536  | Other :  0.10844645
Real values 593...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8967103  | Other :  0.10328978
Real values 594...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  2.9969718e-12
Real values 595...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89351773  | Other :  0.10648231
Real values 596...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.893008  | Other :  0.10699205
Real values 597...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.89165187  | Other :  0.10834817
Real values 598...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.8948846  | Other :  0.105115436
Real values 599...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb267492e90>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5
Model Weights: 
None
Prediction... Melanoma :  1.0  | Other :  1.4443084e-10
Real values 600...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Inception_Test)*100))

Accuracy = 80.50%

6.2.2 Evaluating the Model

6.2.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Inception_Test = []
for i in range(len(y_true_Inception_Test)):
    y_true_2_Inception_Test.append(y_true_Inception_Test[i][0])

6.2.2.2 Re-ordering the Predicte y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Inception_Test = []
for i in range(len(y_score_Inception_Test)):
    y_score_2_Inception_Test.append(y_score_Inception_Test[i][0])

6.2.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Inception_Test, y_score_2_Inception_Test)

6.2.2.4 Confusion Matrix

6.2.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

6.2.2.4.2 Obtaining Labels

TRUE_POSITIVE_Inception_Test, FALSE_POSITIVE_Inception_Test, TRUE_NEGATIVE_Inception_Test, FALSE_NEGATIVE_Inception_Test = positive_negative_measurement(y_true_2_Inception_Test, y_score_2_Inception_Test)
postives_negatives_Inception_Test = [[TRUE_POSITIVE_Inception_Test, FALSE_POSITIVE_Inception_Test], 
                                     [FALSE_NEGATIVE_Inception_Test, TRUE_NEGATIVE_Inception_Test]]

sns.set()
labels_Inception_Test =  np.array([['True positive: ' + str(TRUE_POSITIVE_Inception_Test),
                                    'False positive: ' + str(FALSE_POSITIVE_Inception_Test)],
                                    ['False negative: ' + str(FALSE_NEGATIVE_Inception_Test),
                                    'True negative: ' + str(TRUE_POSITIVE_Inception_Test)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Inception_Test, annot = labels_Inception_Test, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb26692e810>

6.2.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Inception_Test = TRUE_POSITIVE_Inception_Test / (TRUE_POSITIVE_Inception_Test + FALSE_NEGATIVE_Inception_Test)
print("Sensitivity: ", sensitivity_Inception_Test)

Sensitivity:  1.0

6.2.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Inception_Test = TRUE_NEGATIVE_Inception_Test / (TRUE_NEGATIVE_Inception_Test + FALSE_NEGATIVE_Inception_Test)
    print("Specifity: ", specifity_Inception_Test)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

6.2.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Inception_Test = TRUE_POSITIVE_Inception_Test / (TRUE_POSITIVE_Inception_Test + FALSE_POSITIVE_Inception_Test)
print("Precision: ", predcision_Inception_Test)

Precision:  0.805

6.2.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Inception_Test = TRUE_NEGATIVE_Inception_Test / (TRUE_NEGATIVE_Inception_Test + FALSE_NEGATIVE_Inception_Test)
    print("Negative predictive value: ", npv_Inception_Test)
except:
    print("0 Negative Predictions")

0 Negative Predictions

6.2.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Inception_Test = (TRUE_POSITIVE_Inception_Test + TRUE_NEGATIVE_Inception_Test) / (TRUE_POSITIVE_Inception_Test + FALSE_POSITIVE_Inception_Test + TRUE_NEGATIVE_Inception_Test + FALSE_NEGATIVE_Inception_Test)
print("Accuracy: ", accuracy_Inception_Test)

Accuracy:  0.805

6.3 Xception Architecture

6.3.1 Compute Test Set Predictions

# Compute test set predictions
NUMBER_TEST_SAMPLES_Xception_Test = 600

xception_architecture_function = xception_architecture()
xception_architecture_weight_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5"


y_true_Xception_Test = test_targets[:NUMBER_TEST_SAMPLES_Xception_Test]
y_score_Xception_Test = []
for index in range(NUMBER_TEST_SAMPLES_Xception_Test): #compute one at a time due to memory constraints
    probs_Xception_Test = predict(img_path = test_files[index], model_architecture = xception_architecture_function, path_model_weight = xception_architecture_weight_path)
    print("Real values {}...".format(index+1) + "Melanoma : ", test_targets[index][0], " | Other : ", test_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Xception_Test.append(probs_Xception_Test)
    
correct_Xception_Test = np.array(y_true_Xception_Test) == np.array(y_score_Xception_Test)

Streaming output truncated to the last 5000 lines.
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013414.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022198  | Other :  0.3977802
Real values 101...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013325.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225385  | Other :  0.39774615
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235906  | Other :  0.3976409
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013321.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023053  | Other :  0.39769477
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225856  | Other :  0.39774138
Real values 105...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013374.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023496  | Other :  0.39765048
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241616  | Other :  0.39758384
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013465.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222065  | Other :  0.39777935
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013678.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024244  | Other :  0.3975756
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013696.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237026  | Other :  0.3976297
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013511.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023272  | Other :  0.39767274
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013615.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022811  | Other :  0.39771897
Real values 112...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225356  | Other :  0.39774644
Real values 113...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022831  | Other :  0.39771682
Real values 114...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013529.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226506  | Other :  0.3977349
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013577.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022078  | Other :  0.39779222
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022461  | Other :  0.39775386
Real values 117...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013602.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60243547  | Other :  0.39756453
Real values 118...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013673.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226613  | Other :  0.39773387
Real values 119...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013512.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228246  | Other :  0.39771757
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60253936  | Other :  0.39746064
Real values 121...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013565.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022557  | Other :  0.39774427
Real values 122...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013813.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022641  | Other :  0.3977359
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013733.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022512  | Other :  0.39774883
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022067  | Other :  0.39779326
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013764.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023411  | Other :  0.39765894
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013767.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022756  | Other :  0.39772442
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013739.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023313  | Other :  0.39766872
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013794.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234654  | Other :  0.39765346
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013708.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022044  | Other :  0.39779565
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023809  | Other :  0.39761913
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013738.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022552  | Other :  0.3977448
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022335  | Other :  0.3977665
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60217786  | Other :  0.39782214
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013842.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240436  | Other :  0.39759564
Real values 135...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022524  | Other :  0.39774755
Real values 136...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013908.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222876  | Other :  0.3977712
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013897.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60219866  | Other :  0.3978013
Real values 138...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013911.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222715  | Other :  0.39777285
Real values 139...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022329  | Other :  0.3977671
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013917.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021927  | Other :  0.39780727
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227317  | Other :  0.39772683
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022576  | Other :  0.39774236
Real values 143...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227233  | Other :  0.39772767
Real values 144...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024925  | Other :  0.39750752
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227513  | Other :  0.39772487
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234  | Other :  0.39766008
Real values 147...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022516  | Other :  0.39774838
Real values 148...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022898  | Other :  0.39771017
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021923  | Other :  0.39780778
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227615  | Other :  0.39772385
Real values 151...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60229146  | Other :  0.3977086
Real values 152...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022186  | Other :  0.39778134
Real values 153...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022088  | Other :  0.39779118
Real values 154...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221213  | Other :  0.39778787
Real values 155...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222614  | Other :  0.39777386
Real values 156...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021697  | Other :  0.39783034
Real values 157...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021871  | Other :  0.3978129
Real values 158...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220385  | Other :  0.39779612
Real values 159...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022225  | Other :  0.39777747
Real values 160...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022453  | Other :  0.3977548
Real values 161...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022935  | Other :  0.39770648
Real values 162...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026999  | Other :  0.3973001
Real values 163...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602257  | Other :  0.397743
Real values 164...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220283  | Other :  0.39779717
Real values 165...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602225  | Other :  0.39777496
Real values 166...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022269  | Other :  0.39777312
Real values 167...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60223645  | Other :  0.39776355
Real values 168...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022442  | Other :  0.39775574
Real values 169...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221845  | Other :  0.39778155
Real values 170...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222703  | Other :  0.397773
Real values 171...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218114  | Other :  0.39781886
Real values 172...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602217  | Other :  0.39778298
Real values 173...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022038  | Other :  0.3977962
Real values 174...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221416  | Other :  0.39778587
Real values 175...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022278  | Other :  0.39777225
Real values 176...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023124  | Other :  0.39768767
Real values 177...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021915  | Other :  0.39780855
Real values 178...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238266  | Other :  0.39761734
Real values 179...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602456  | Other :  0.39754397
Real values 180...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023356  | Other :  0.39766446
Real values 181...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022806  | Other :  0.3977194
Real values 182...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021995  | Other :  0.39780048
Real values 183...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602218  | Other :  0.39778203
Real values 184...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023415  | Other :  0.39765853
Real values 185...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021816  | Other :  0.39781842
Real values 186...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022271  | Other :  0.39777294
Real values 187...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220134  | Other :  0.39779863
Real values 188...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602233  | Other :  0.397767
Real values 189...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226583  | Other :  0.3977342
Real values 190...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022328  | Other :  0.39776722
Real values 191...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023649  | Other :  0.39763507
Real values 192...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023003  | Other :  0.3976997
Real values 193...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602217  | Other :  0.39778298
Real values 194...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218376  | Other :  0.39781624
Real values 195...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024733  | Other :  0.39752668
Real values 196...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024369  | Other :  0.3975631
Real values 197...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023738  | Other :  0.39762625
Real values 198...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023282  | Other :  0.3976718
Real values 199...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023603  | Other :  0.39763966
Real values 200...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022185  | Other :  0.3977815
Real values 201...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023128  | Other :  0.39768723
Real values 202...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022979  | Other :  0.39770213
Real values 203...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022103  | Other :  0.39778972
Real values 204...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220724  | Other :  0.39779276
Real values 205...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023636  | Other :  0.39763644
Real values 206...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023714  | Other :  0.3976286
Real values 207...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024936  | Other :  0.39750642
Real values 208...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237956  | Other :  0.39762044
Real values 209...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023124  | Other :  0.3976876
Real values 210...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024151  | Other :  0.39758497
Real values 211...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024152  | Other :  0.39758483
Real values 212...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023181  | Other :  0.39768186
Real values 213...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60242534  | Other :  0.39757463
Real values 214...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023166  | Other :  0.39768335
Real values 215...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602359  | Other :  0.39764103
Real values 216...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023147  | Other :  0.39768532
Real values 217...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234725  | Other :  0.3976528
Real values 218...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023728  | Other :  0.39762717
Real values 219...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60248023  | Other :  0.39751983
Real values 220...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238004  | Other :  0.39762
Real values 221...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025814  | Other :  0.39741865
Real values 222...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024236  | Other :  0.39757642
Real values 223...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254407  | Other :  0.39745596
Real values 224...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024848  | Other :  0.3975152
Real values 225...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240126  | Other :  0.39759874
Real values 226...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023385  | Other :  0.39766148
Real values 227...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023644  | Other :  0.3976356
Real values 228...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250884  | Other :  0.39749113
Real values 229...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025397  | Other :  0.39746028
Real values 230...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023978  | Other :  0.3976022
Real values 231...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602515  | Other :  0.397485
Real values 232...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60232925  | Other :  0.39767075
Real values 233...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024356  | Other :  0.39756444
Real values 234...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023451  | Other :  0.3976549
Real values 235...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025013  | Other :  0.3974988
Real values 236...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60264415  | Other :  0.3973558
Real values 237...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024228  | Other :  0.3975772
Real values 238...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023818  | Other :  0.39761811
Real values 239...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025442  | Other :  0.3974558
Real values 240...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024945  | Other :  0.3975055
Real values 241...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025528  | Other :  0.3974472
Real values 242...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241914  | Other :  0.39758092
Real values 243...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6027536  | Other :  0.39724648
Real values 244...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024479  | Other :  0.397552
Real values 245...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249156  | Other :  0.39750844
Real values 246...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025629  | Other :  0.3974371
Real values 247...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60231936  | Other :  0.39768067
Real values 248...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023709  | Other :  0.3976291
Real values 249...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241383  | Other :  0.3975861
Real values 250...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024023  | Other :  0.3975977
Real values 251...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60245824  | Other :  0.39754173
Real values 252...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024937  | Other :  0.39750633
Real values 253...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023567  | Other :  0.3976434
Real values 254...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023799  | Other :  0.39762002
Real values 255...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022729  | Other :  0.3977271
Real values 256...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026711  | Other :  0.39732894
Real values 257...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023873  | Other :  0.39761272
Real values 258...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249805  | Other :  0.39750195
Real values 259...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025268  | Other :  0.39747322
Real values 260...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238546  | Other :  0.3976145
Real values 261...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024757  | Other :  0.39752433
Real values 262...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024861  | Other :  0.39751396
Real values 263...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023621  | Other :  0.3976379
Real values 264...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024063  | Other :  0.39759368
Real values 265...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60260564  | Other :  0.39739436
Real values 266...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023263  | Other :  0.39767376
Real values 267...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249084  | Other :  0.3975092
Real values 268...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024521  | Other :  0.39754793
Real values 269...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024247  | Other :  0.3975753
Real values 270...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024148  | Other :  0.39758524
Real values 271...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60245466  | Other :  0.3975453
Real values 272...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024019  | Other :  0.39759806
Real values 273...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602726  | Other :  0.39727405
Real values 274...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022677  | Other :  0.3977323
Real values 275...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60243624  | Other :  0.39756376
Real values 276...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240096  | Other :  0.397599
Real values 277...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023979  | Other :  0.39760205
Real values 278...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025226  | Other :  0.39747733
Real values 279...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025472  | Other :  0.3974528
Real values 280...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025536  | Other :  0.39744642
Real values 281...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602628  | Other :  0.397372
Real values 282...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024554  | Other :  0.3975446
Real values 283...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60253876  | Other :  0.39746124
Real values 284...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024574  | Other :  0.3975426
Real values 285...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237837  | Other :  0.39762166
Real values 286...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024255  | Other :  0.39757448
Real values 287...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025406  | Other :  0.39745942
Real values 288...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025276  | Other :  0.39747235
Real values 289...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602402  | Other :  0.39759803
Real values 290...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249305  | Other :  0.39750692
Real values 291...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250324  | Other :  0.39749673
Real values 292...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024427  | Other :  0.39755732
Real values 293...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024051  | Other :  0.39759493
Real values 294...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025231  | Other :  0.3974769
Real values 295...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60243845  | Other :  0.39756158
Real values 296...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60246885  | Other :  0.39753115
Real values 297...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024655  | Other :  0.39753452
Real values 298...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60247916  | Other :  0.3975208
Real values 299...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602488  | Other :  0.39751202
Real values 300...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60255086  | Other :  0.3974492
Real values 301...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024265  | Other :  0.39757347
Real values 302...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60247475  | Other :  0.39752528
Real values 303...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244197  | Other :  0.39755803
Real values 304...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024638  | Other :  0.39753625
Real values 305...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023717  | Other :  0.39762834
Real values 306...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024646  | Other :  0.39753535
Real values 307...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024898  | Other :  0.39751017
Real values 308...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024646  | Other :  0.39753538
Real values 309...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60252225  | Other :  0.39747775
Real values 310...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60242796  | Other :  0.397572
Real values 311...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239327  | Other :  0.39760673
Real values 312...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025213  | Other :  0.39747867
Real values 313...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60247815  | Other :  0.39752182
Real values 314...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023814  | Other :  0.39761856
Real values 315...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60272074  | Other :  0.39727923
Real values 316...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250634  | Other :  0.3974936
Real values 317...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024914  | Other :  0.39750862
Real values 318...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025889  | Other :  0.3974111
Real values 319...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60230905  | Other :  0.39769095
Real values 320...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602369  | Other :  0.39763093
Real values 321...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60256475  | Other :  0.39743525
Real values 322...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254693  | Other :  0.397453
Real values 323...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024261  | Other :  0.39757386
Real values 324...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249937  | Other :  0.3975006
Real values 325...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241544  | Other :  0.39758456
Real values 326...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60236114  | Other :  0.3976389
Real values 327...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60259414  | Other :  0.39740592
Real values 328...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024366  | Other :  0.39756337
Real values 329...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239273  | Other :  0.39760727
Real values 330...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023816  | Other :  0.3976184
Real values 331...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024726  | Other :  0.39752737
Real values 332...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60255474  | Other :  0.39744526
Real values 333...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024682  | Other :  0.39753184
Real values 334...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023803  | Other :  0.3976197
Real values 335...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239583  | Other :  0.39760414
Real values 336...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024705  | Other :  0.3975295
Real values 337...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024863  | Other :  0.3975137
Real values 338...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024535  | Other :  0.3975465
Real values 339...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60262835  | Other :  0.39737168
Real values 340...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025079  | Other :  0.39749214
Real values 341...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60232204  | Other :  0.39767793
Real values 342...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244244  | Other :  0.39755756
Real values 343...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244083  | Other :  0.3975592
Real values 344...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025562  | Other :  0.39744374
Real values 345...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024709  | Other :  0.39752913
Real values 346...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024477  | Other :  0.3975523
Real values 347...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024078  | Other :  0.3975922
Real values 348...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244143  | Other :  0.3975586
Real values 349...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60258186  | Other :  0.39741817
Real values 350...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254943  | Other :  0.3974505
Real values 351...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025492  | Other :  0.39745083
Real values 352...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024133  | Other :  0.3975867
Real values 353...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60248405  | Other :  0.39751592
Real values 354...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249037  | Other :  0.3975097
Real values 355...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025371  | Other :  0.39746293
Real values 356...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024256  | Other :  0.39757442
Real values 357...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025077  | Other :  0.39749223
Real values 358...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60251784  | Other :  0.3974822
Real values 359...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024914  | Other :  0.39750862
Real values 360...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023759  | Other :  0.39762405
Real values 361...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023564  | Other :  0.39764363
Real values 362...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602461  | Other :  0.397539
Real values 363...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60248864  | Other :  0.3975114
Real values 364...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602378  | Other :  0.39762202
Real values 365...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240716  | Other :  0.3975928
Real values 366...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023827  | Other :  0.39761725
Real values 367...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024179  | Other :  0.39758205
Real values 368...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023744  | Other :  0.39762565
Real values 369...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240316  | Other :  0.39759684
Real values 370...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024113  | Other :  0.39758867
Real values 371...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023924  | Other :  0.39760765
Real values 372...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025535  | Other :  0.3974465
Real values 373...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025033  | Other :  0.39749667
Real values 374...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237765  | Other :  0.39762235
Real values 375...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025459  | Other :  0.39745408
Real values 376...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60246384  | Other :  0.3975362
Real values 377...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602369  | Other :  0.39763093
Real values 378...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023557  | Other :  0.39764434
Real values 379...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254735  | Other :  0.39745265
Real values 380...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024359  | Other :  0.39756408
Real values 381...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024462  | Other :  0.39755374
Real values 382...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025158  | Other :  0.39748424
Real values 383...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024387  | Other :  0.39756128
Real values 384...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60249543  | Other :  0.39750454
Real values 385...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60255384  | Other :  0.3974461
Real values 386...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023759  | Other :  0.39762408
Real values 387...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241127  | Other :  0.3975888
Real values 388...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024152  | Other :  0.39758483
Real values 389...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024599  | Other :  0.39754006
Real values 390...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024196  | Other :  0.39758036
Real values 391...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025232  | Other :  0.39747676
Real values 392...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024052  | Other :  0.39759478
Real values 393...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602488  | Other :  0.39751202
Real values 394...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60258645  | Other :  0.39741358
Real values 395...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60267466  | Other :  0.3973253
Real values 396...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023572  | Other :  0.3976428
Real values 397...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238624  | Other :  0.3976137
Real values 398...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60243195  | Other :  0.39756805
Real values 399...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60233057  | Other :  0.39766946
Real values 400...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250807  | Other :  0.3974919
Real values 401...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602488  | Other :  0.39751196
Real values 402...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228616  | Other :  0.3977138
Real values 403...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024646  | Other :  0.3975354
Real values 404...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023729  | Other :  0.39762712
Real values 405...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60246146  | Other :  0.3975385
Real values 406...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239285  | Other :  0.39760718
Real values 407...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60263073  | Other :  0.39736924
Real values 408...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60260653  | Other :  0.39739352
Real values 409...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602401  | Other :  0.39759892
Real values 410...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024894  | Other :  0.39751056
Real values 411...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023878  | Other :  0.39761224
Real values 412...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023527  | Other :  0.3976473
Real values 413...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60241246  | Other :  0.3975875
Real values 414...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60258186  | Other :  0.3974181
Real values 415...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60245854  | Other :  0.39754146
Real values 416...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023586  | Other :  0.3976414
Real values 417...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60245866  | Other :  0.39754134
Real values 418...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239255  | Other :  0.39760745
Real values 419...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60242355  | Other :  0.39757642
Real values 420...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024372  | Other :  0.39756274
Real values 421...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025918  | Other :  0.39740816
Real values 422...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024779  | Other :  0.39752212
Real values 423...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024782  | Other :  0.39752176
Real values 424...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025327  | Other :  0.39746734
Real values 425...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025629  | Other :  0.39743716
Real values 426...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024663  | Other :  0.3975337
Real values 427...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602388  | Other :  0.39761198
Real values 428...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60256493  | Other :  0.3974351
Real values 429...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238534  | Other :  0.39761466
Real values 430...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025674  | Other :  0.3974326
Real values 431...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024636  | Other :  0.39753637
Real values 432...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024201  | Other :  0.39757988
Real values 433...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023329  | Other :  0.39766714
Real values 434...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60236716  | Other :  0.39763284
Real values 435...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023734  | Other :  0.3976266
Real values 436...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023826  | Other :  0.3976174
Real values 437...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60238147  | Other :  0.39761856
Real values 438...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60242987  | Other :  0.3975702
Real values 439...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023552  | Other :  0.39764485
Real values 440...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024135  | Other :  0.3975865
Real values 441...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60245323  | Other :  0.39754674
Real values 442...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244083  | Other :  0.39755917
Real values 443...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60259086  | Other :  0.39740914
Real values 444...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025208  | Other :  0.39747915
Real values 445...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024187  | Other :  0.39758134
Real values 446...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023508  | Other :  0.3976492
Real values 447...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234857  | Other :  0.39765143
Real values 448...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60246414  | Other :  0.39753583
Real values 449...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60250455  | Other :  0.39749542
Real values 450...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244995  | Other :  0.39755008
Real values 451...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60262096  | Other :  0.39737907
Real values 452...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024144  | Other :  0.39758554
Real values 453...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023878  | Other :  0.39761224
Real values 454...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023979  | Other :  0.39760208
Real values 455...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60244024  | Other :  0.3975598
Real values 456...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6027154  | Other :  0.3972846
Real values 457...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026052  | Other :  0.39739475
Real values 458...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025354  | Other :  0.3974646
Real values 459...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026583  | Other :  0.39734173
Real values 460...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6026263  | Other :  0.39737368
Real values 461...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60232896  | Other :  0.39767107
Real values 462...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024044  | Other :  0.3975956
Real values 463...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60254025  | Other :  0.39745972
Real values 464...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024898  | Other :  0.39751017
Real values 465...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60258615  | Other :  0.39741385
Real values 466...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239756  | Other :  0.3976024
Real values 467...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60253936  | Other :  0.39746067
Real values 468...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239035  | Other :  0.39760965
Real values 469...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6025746  | Other :  0.39742547
Real values 470...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60247445  | Other :  0.39752555
Real values 471...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024078  | Other :  0.39759216
Real values 472...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60234904  | Other :  0.39765096
Real values 473...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022832  | Other :  0.39771682
Real values 474...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023389  | Other :  0.39766103
Real values 475...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024257  | Other :  0.39757434
Real values 476...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022979  | Other :  0.39770213
Real values 477...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226166  | Other :  0.39773834
Real values 478...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602199  | Other :  0.39780104
Real values 479...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237306  | Other :  0.39762694
Real values 480...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022736  | Other :  0.39772642
Real values 481...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024797  | Other :  0.39752027
Real values 482...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228306  | Other :  0.3977169
Real values 483...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225564  | Other :  0.3977444
Real values 484...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023525  | Other :  0.3976475
Real values 485...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218424  | Other :  0.3978158
Real values 486...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60223144  | Other :  0.39776853
Real values 487...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602499  | Other :  0.397501
Real values 488...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602225  | Other :  0.39777496
Real values 489...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235566  | Other :  0.39764434
Real values 490...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227215  | Other :  0.39772788
Real values 491...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022971  | Other :  0.39770287
Real values 492...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023791  | Other :  0.3976209
Real values 493...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022832  | Other :  0.39771682
Real values 494...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023496  | Other :  0.3976504
Real values 495...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023379  | Other :  0.3976621
Real values 496...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022136  | Other :  0.39778635
Real values 497...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226065  | Other :  0.39773932
Real values 498...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222024  | Other :  0.39777976
Real values 499...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022632  | Other :  0.3977368
Real values 500...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022016  | Other :  0.39779842
Real values 501...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60251456  | Other :  0.39748544
Real values 502...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023151  | Other :  0.39768487
Real values 503...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227734  | Other :  0.39772266
Real values 504...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022578  | Other :  0.39774224
Real values 505...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60235536  | Other :  0.39764467
Real values 506...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021967  | Other :  0.39780328
Real values 507...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023833  | Other :  0.39761668
Real values 508...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022891  | Other :  0.3977109
Real values 509...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023522  | Other :  0.3976478
Real values 510...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022863  | Other :  0.3977137
Real values 511...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023272  | Other :  0.3976728
Real values 512...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225874  | Other :  0.39774126
Real values 513...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60240114  | Other :  0.39759883
Real values 514...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022163  | Other :  0.39778367
Real values 515...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227597  | Other :  0.39772406
Real values 516...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60232586  | Other :  0.39767417
Real values 517...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6024784  | Other :  0.39752164
Real values 518...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023509  | Other :  0.39764908
Real values 519...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60229146  | Other :  0.39770854
Real values 520...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022865  | Other :  0.3977135
Real values 521...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226434  | Other :  0.3977356
Real values 522...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60227096  | Other :  0.3977291
Real values 523...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222936  | Other :  0.39777064
Real values 524...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022638  | Other :  0.3977362
Real values 525...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021827  | Other :  0.3978173
Real values 526...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022198  | Other :  0.39778015
Real values 527...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60226434  | Other :  0.3977356
Real values 528...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220575  | Other :  0.39779425
Real values 529...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021907  | Other :  0.39780927
Real values 530...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023162  | Other :  0.39768383
Real values 531...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60219795  | Other :  0.39780208
Real values 532...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021734  | Other :  0.3978266
Real values 533...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022063  | Other :  0.39779368
Real values 534...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60219437  | Other :  0.39780563
Real values 535...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021894  | Other :  0.39781055
Real values 536...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60237765  | Other :  0.39762232
Real values 537...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220945  | Other :  0.39779058
Real values 538...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602304  | Other :  0.39769605
Real values 539...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022951  | Other :  0.39770493
Real values 540...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225713  | Other :  0.39774293
Real values 541...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602276  | Other :  0.397724
Real values 542...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022366  | Other :  0.39776337
Real values 543...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225475  | Other :  0.39774525
Real values 544...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221654  | Other :  0.3977834
Real values 545...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220194  | Other :  0.39779803
Real values 546...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60224056  | Other :  0.39775944
Real values 547...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60222423  | Other :  0.39777574
Real values 548...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022984  | Other :  0.39770168
Real values 549...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022775  | Other :  0.39772248
Real values 550...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023388  | Other :  0.3976612
Real values 551...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022223  | Other :  0.3977777
Real values 552...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220397  | Other :  0.39779603
Real values 553...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022139  | Other :  0.39778608
Real values 554...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022021  | Other :  0.39779788
Real values 555...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602311  | Other :  0.39768898
Real values 556...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218906  | Other :  0.39781097
Real values 557...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023132  | Other :  0.39768675
Real values 558...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602177  | Other :  0.39782292
Real values 559...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022578  | Other :  0.39774224
Real values 560...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022301  | Other :  0.39776996
Real values 561...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60224605  | Other :  0.39775392
Real values 562...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60221267  | Other :  0.39778736
Real values 563...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022144  | Other :  0.3977856
Real values 564...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60216165  | Other :  0.39783835
Real values 565...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60216886  | Other :  0.39783114
Real values 566...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60219467  | Other :  0.39780536
Real values 567...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60239273  | Other :  0.3976073
Real values 568...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218847  | Other :  0.39781153
Real values 569...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60217446  | Other :  0.39782554
Real values 570...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022852  | Other :  0.39771473
Real values 571...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021675  | Other :  0.3978325
Real values 572...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60223913  | Other :  0.39776087
Real values 573...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021975  | Other :  0.39780244
Real values 574...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022437  | Other :  0.39775634
Real values 575...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60217565  | Other :  0.39782435
Real values 576...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021691  | Other :  0.3978309
Real values 577...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021575  | Other :  0.39784253
Real values 578...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021859  | Other :  0.3978141
Real values 579...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021945  | Other :  0.39780545
Real values 580...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60216737  | Other :  0.3978326
Real values 581...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60231745  | Other :  0.39768255
Real values 582...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60225934  | Other :  0.3977406
Real values 583...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022303  | Other :  0.3977697
Real values 584...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021912  | Other :  0.39780873
Real values 585...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60223126  | Other :  0.3977688
Real values 586...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218716  | Other :  0.39781287
Real values 587...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6023138  | Other :  0.39768618
Real values 588...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60224324  | Other :  0.3977567
Real values 589...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60220945  | Other :  0.3977905
Real values 590...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60224843  | Other :  0.39775157
Real values 591...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60218126  | Other :  0.39781874
Real values 592...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.602174  | Other :  0.39782602
Real values 593...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022252  | Other :  0.39777485
Real values 594...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022437  | Other :  0.39775625
Real values 595...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60228693  | Other :  0.397713
Real values 596...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6021771  | Other :  0.39782292
Real values 597...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022486  | Other :  0.39775142
Real values 598...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.60229963  | Other :  0.3977003
Real values 599...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb268458810>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5
Model Weights: 
None
Prediction... Melanoma :  0.6022443  | Other :  0.39775565
Real values 600...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Xception_Test)*100))

Accuracy = 80.50%

6.3.2 Evaluating the Model

6.3.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Xception_Test = []
for i in range(len(y_true_Xception_Test)):
    y_true_2_Xception_Test.append(y_true_Xception_Test[i][0])

6.3.2.2 Re-ordering the Predict y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Xception_Test = []
for i in range(len(y_score_Xception_Test)):
    y_score_2_Xception_Test.append(y_score_Xception_Test[i][0])

6.3.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Xception_Test, y_score_2_Xception_Test)

6.3.2.4 Confusion Matrix

6.3.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_Xception_Test, FALSE_POSITIVE_Xception_Test, TRUE_NEGATIVE_Xception_Test, FALSE_NEGATIVE_Xception_Test = positive_negative_measurement(y_true_2_Xception_Test, y_score_2_Xception_Test)
postives_negatives_Xception_Test = [[TRUE_POSITIVE_Xception_Test, FALSE_POSITIVE_Xception_Test], 
                                    [FALSE_NEGATIVE_Xception_Test, TRUE_NEGATIVE_Xception_Test]]

6.3.2.4.2 Obtaining the Labels

sns.set()
labels_Xception_Test =  np.array([['True positive: ' + str(TRUE_POSITIVE_Xception_Test),
                                    'False positive: ' + str(FALSE_POSITIVE_Xception_Test)],
                                    ['False negative: ' + str(FALSE_NEGATIVE_Xception_Test),
                                    'True negative: ' + str(TRUE_POSITIVE_Xception_Test)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Xception_Test, annot = labels_Xception_Test, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb267857b10>

6.3.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Xception_Test = TRUE_POSITIVE_Xception_Test / (TRUE_POSITIVE_Xception_Test + FALSE_NEGATIVE_Xception_Test)
print("Sensitivity: ", sensitivity_Xception_Test)

Sensitivity:  1.0

6.3.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Xception_Test = TRUE_NEGATIVE_Xception_Test / (TRUE_NEGATIVE_Xception_Test + FALSE_NEGATIVE_Xception_Test)
    print("Specifity: ", specifity_Xception_Test)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

6.3.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Xception_Test = TRUE_POSITIVE_Xception_Test / (TRUE_POSITIVE_Xception_Test + FALSE_POSITIVE_Xception_Test)
print("Precision: ", predcision_Xception_Test)

Precision:  0.805

6.3.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Xception_Test = TRUE_NEGATIVE_Xception_Test / (TRUE_NEGATIVE_Xception_Test + FALSE_NEGATIVE_Xception_Test)
    print("Negative predictive value: ", npv_Xception_Test)
except:
    print("0 Negative Predictions")

0 Negative Predictions

6.3.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Xception_Test = (TRUE_POSITIVE_Xception_Test + TRUE_NEGATIVE_Xception_Test) / (TRUE_POSITIVE_Xception_Test + FALSE_POSITIVE_Xception_Test + TRUE_NEGATIVE_Xception_Test + FALSE_NEGATIVE_Xception_Test)
print("Accuracy: ", accuracy_Xception_Test)

Accuracy:  0.805

7. Evaluating the Models Together on Testing Data - Ensembling the models

Working Flowchart:

7.1 Defining the Input Shape

# Single input for multiple models
model_input = Input(shape=(512, 512, 3))

7.2 Defining all the Models

def mobilenet_architecture():
    """
    Pre-build architecture of mobilenet for our dataset.
    """
    # Imprting the model
    from keras.applications.mobilenet import MobileNet

    # Pre-build model
    base_model = MobileNet(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    mobilenet_model = Model(base_model.input, output)
    
    # Getting the summary of architecture
    mobilenet_model.summary()
    
    # Compiling the model
    mobilenet_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])

    return mobilenet_model

# Model 1
mobilenet_model = mobilenet_architecture()
mobilenet_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5")

Model: "model_15"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_11 (InputLayer)        [(None, 512, 512, 3)]     0         
_________________________________________________________________
conv1 (Conv2D)               (None, 256, 256, 32)      864       
_________________________________________________________________
conv1_bn (BatchNormalization (None, 256, 256, 32)      128       
_________________________________________________________________
conv1_relu (ReLU)            (None, 256, 256, 32)      0         
_________________________________________________________________
conv_dw_1 (DepthwiseConv2D)  (None, 256, 256, 32)      288       
_________________________________________________________________
conv_dw_1_bn (BatchNormaliza (None, 256, 256, 32)      128       
_________________________________________________________________
conv_dw_1_relu (ReLU)        (None, 256, 256, 32)      0         
_________________________________________________________________
conv_pw_1 (Conv2D)           (None, 256, 256, 64)      2048      
_________________________________________________________________
conv_pw_1_bn (BatchNormaliza (None, 256, 256, 64)      256       
_________________________________________________________________
conv_pw_1_relu (ReLU)        (None, 256, 256, 64)      0         
_________________________________________________________________
conv_pad_2 (ZeroPadding2D)   (None, 257, 257, 64)      0         
_________________________________________________________________
conv_dw_2 (DepthwiseConv2D)  (None, 128, 128, 64)      576       
_________________________________________________________________
conv_dw_2_bn (BatchNormaliza (None, 128, 128, 64)      256       
_________________________________________________________________
conv_dw_2_relu (ReLU)        (None, 128, 128, 64)      0         
_________________________________________________________________
conv_pw_2 (Conv2D)           (None, 128, 128, 128)     8192      
_________________________________________________________________
conv_pw_2_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_2_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_dw_3 (DepthwiseConv2D)  (None, 128, 128, 128)     1152      
_________________________________________________________________
conv_dw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_dw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pw_3 (Conv2D)           (None, 128, 128, 128)     16384     
_________________________________________________________________
conv_pw_3_bn (BatchNormaliza (None, 128, 128, 128)     512       
_________________________________________________________________
conv_pw_3_relu (ReLU)        (None, 128, 128, 128)     0         
_________________________________________________________________
conv_pad_4 (ZeroPadding2D)   (None, 129, 129, 128)     0         
_________________________________________________________________
conv_dw_4 (DepthwiseConv2D)  (None, 64, 64, 128)       1152      
_________________________________________________________________
conv_dw_4_bn (BatchNormaliza (None, 64, 64, 128)       512       
_________________________________________________________________
conv_dw_4_relu (ReLU)        (None, 64, 64, 128)       0         
_________________________________________________________________
conv_pw_4 (Conv2D)           (None, 64, 64, 256)       32768     
_________________________________________________________________
conv_pw_4_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_4_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_dw_5 (DepthwiseConv2D)  (None, 64, 64, 256)       2304      
_________________________________________________________________
conv_dw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_dw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pw_5 (Conv2D)           (None, 64, 64, 256)       65536     
_________________________________________________________________
conv_pw_5_bn (BatchNormaliza (None, 64, 64, 256)       1024      
_________________________________________________________________
conv_pw_5_relu (ReLU)        (None, 64, 64, 256)       0         
_________________________________________________________________
conv_pad_6 (ZeroPadding2D)   (None, 65, 65, 256)       0         
_________________________________________________________________
conv_dw_6 (DepthwiseConv2D)  (None, 32, 32, 256)       2304      
_________________________________________________________________
conv_dw_6_bn (BatchNormaliza (None, 32, 32, 256)       1024      
_________________________________________________________________
conv_dw_6_relu (ReLU)        (None, 32, 32, 256)       0         
_________________________________________________________________
conv_pw_6 (Conv2D)           (None, 32, 32, 512)       131072    
_________________________________________________________________
conv_pw_6_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_6_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_7 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_7 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_7_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_7_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_8 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_8 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_8_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_8_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_9 (DepthwiseConv2D)  (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_9 (Conv2D)           (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_9_bn (BatchNormaliza (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_9_relu (ReLU)        (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_10 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_10 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_10_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_10_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_dw_11 (DepthwiseConv2D) (None, 32, 32, 512)       4608      
_________________________________________________________________
conv_dw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_dw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pw_11 (Conv2D)          (None, 32, 32, 512)       262144    
_________________________________________________________________
conv_pw_11_bn (BatchNormaliz (None, 32, 32, 512)       2048      
_________________________________________________________________
conv_pw_11_relu (ReLU)       (None, 32, 32, 512)       0         
_________________________________________________________________
conv_pad_12 (ZeroPadding2D)  (None, 33, 33, 512)       0         
_________________________________________________________________
conv_dw_12 (DepthwiseConv2D) (None, 16, 16, 512)       4608      
_________________________________________________________________
conv_dw_12_bn (BatchNormaliz (None, 16, 16, 512)       2048      
_________________________________________________________________
conv_dw_12_relu (ReLU)       (None, 16, 16, 512)       0         
_________________________________________________________________
conv_pw_12 (Conv2D)          (None, 16, 16, 1024)      524288    
_________________________________________________________________
conv_pw_12_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_12_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_dw_13 (DepthwiseConv2D) (None, 16, 16, 1024)      9216      
_________________________________________________________________
conv_dw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_dw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
conv_pw_13 (Conv2D)          (None, 16, 16, 1024)      1048576   
_________________________________________________________________
conv_pw_13_bn (BatchNormaliz (None, 16, 16, 1024)      4096      
_________________________________________________________________
conv_pw_13_relu (ReLU)       (None, 16, 16, 1024)      0         
_________________________________________________________________
global_average_pooling2d_15  (None, 1024)              0         
_________________________________________________________________
dense_15 (Dense)             (None, 2)                 2050      
=================================================================
Total params: 3,230,914
Trainable params: 3,209,026
Non-trainable params: 21,888
_________________________________________________________________

def inception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model 
    from keras.applications.inception_v3 import InceptionV3

    # Pre-build model
    base_model = InceptionV3(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    inception_model = Model(base_model.input, output)
    
    # Summary of the model
    inception_model.summary()
    
    # Compiling the model
    inception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                            loss = 'categorical_crossentropy', 
                            metrics = ['accuracy'])
    
    return inception_model

# Model 2
inception_model = inception_architecture()
inception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.InceptionV3.hdf5")

Model: "model_16"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_11 (InputLayer)           [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_490 (Conv2D)             (None, 255, 255, 32) 864         input_11[0][0]                   
__________________________________________________________________________________________________
batch_normalization_490 (BatchN (None, 255, 255, 32) 96          conv2d_490[0][0]                 
__________________________________________________________________________________________________
activation_470 (Activation)     (None, 255, 255, 32) 0           batch_normalization_490[0][0]    
__________________________________________________________________________________________________
conv2d_491 (Conv2D)             (None, 253, 253, 32) 9216        activation_470[0][0]             
__________________________________________________________________________________________________
batch_normalization_491 (BatchN (None, 253, 253, 32) 96          conv2d_491[0][0]                 
__________________________________________________________________________________________________
activation_471 (Activation)     (None, 253, 253, 32) 0           batch_normalization_491[0][0]    
__________________________________________________________________________________________________
conv2d_492 (Conv2D)             (None, 253, 253, 64) 18432       activation_471[0][0]             
__________________________________________________________________________________________________
batch_normalization_492 (BatchN (None, 253, 253, 64) 192         conv2d_492[0][0]                 
__________________________________________________________________________________________________
activation_472 (Activation)     (None, 253, 253, 64) 0           batch_normalization_492[0][0]    
__________________________________________________________________________________________________
max_pooling2d_20 (MaxPooling2D) (None, 126, 126, 64) 0           activation_472[0][0]             
__________________________________________________________________________________________________
conv2d_493 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_20[0][0]           
__________________________________________________________________________________________________
batch_normalization_493 (BatchN (None, 126, 126, 80) 240         conv2d_493[0][0]                 
__________________________________________________________________________________________________
activation_473 (Activation)     (None, 126, 126, 80) 0           batch_normalization_493[0][0]    
__________________________________________________________________________________________________
conv2d_494 (Conv2D)             (None, 124, 124, 192 138240      activation_473[0][0]             
__________________________________________________________________________________________________
batch_normalization_494 (BatchN (None, 124, 124, 192 576         conv2d_494[0][0]                 
__________________________________________________________________________________________________
activation_474 (Activation)     (None, 124, 124, 192 0           batch_normalization_494[0][0]    
__________________________________________________________________________________________________
max_pooling2d_21 (MaxPooling2D) (None, 61, 61, 192)  0           activation_474[0][0]             
__________________________________________________________________________________________________
conv2d_498 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
batch_normalization_498 (BatchN (None, 61, 61, 64)   192         conv2d_498[0][0]                 
__________________________________________________________________________________________________
activation_478 (Activation)     (None, 61, 61, 64)   0           batch_normalization_498[0][0]    
__________________________________________________________________________________________________
conv2d_496 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_499 (Conv2D)             (None, 61, 61, 96)   55296       activation_478[0][0]             
__________________________________________________________________________________________________
batch_normalization_496 (BatchN (None, 61, 61, 48)   144         conv2d_496[0][0]                 
__________________________________________________________________________________________________
batch_normalization_499 (BatchN (None, 61, 61, 96)   288         conv2d_499[0][0]                 
__________________________________________________________________________________________________
activation_476 (Activation)     (None, 61, 61, 48)   0           batch_normalization_496[0][0]    
__________________________________________________________________________________________________
activation_479 (Activation)     (None, 61, 61, 96)   0           batch_normalization_499[0][0]    
__________________________________________________________________________________________________
average_pooling2d_45 (AveragePo (None, 61, 61, 192)  0           max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_495 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_497 (Conv2D)             (None, 61, 61, 64)   76800       activation_476[0][0]             
__________________________________________________________________________________________________
conv2d_500 (Conv2D)             (None, 61, 61, 96)   82944       activation_479[0][0]             
__________________________________________________________________________________________________
conv2d_501 (Conv2D)             (None, 61, 61, 32)   6144        average_pooling2d_45[0][0]       
__________________________________________________________________________________________________
batch_normalization_495 (BatchN (None, 61, 61, 64)   192         conv2d_495[0][0]                 
__________________________________________________________________________________________________
batch_normalization_497 (BatchN (None, 61, 61, 64)   192         conv2d_497[0][0]                 
__________________________________________________________________________________________________
batch_normalization_500 (BatchN (None, 61, 61, 96)   288         conv2d_500[0][0]                 
__________________________________________________________________________________________________
batch_normalization_501 (BatchN (None, 61, 61, 32)   96          conv2d_501[0][0]                 
__________________________________________________________________________________________________
activation_475 (Activation)     (None, 61, 61, 64)   0           batch_normalization_495[0][0]    
__________________________________________________________________________________________________
activation_477 (Activation)     (None, 61, 61, 64)   0           batch_normalization_497[0][0]    
__________________________________________________________________________________________________
activation_480 (Activation)     (None, 61, 61, 96)   0           batch_normalization_500[0][0]    
__________________________________________________________________________________________________
activation_481 (Activation)     (None, 61, 61, 32)   0           batch_normalization_501[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_475[0][0]             
                                                                 activation_477[0][0]             
                                                                 activation_480[0][0]             
                                                                 activation_481[0][0]             
__________________________________________________________________________________________________
conv2d_505 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_505 (BatchN (None, 61, 61, 64)   192         conv2d_505[0][0]                 
__________________________________________________________________________________________________
activation_485 (Activation)     (None, 61, 61, 64)   0           batch_normalization_505[0][0]    
__________________________________________________________________________________________________
conv2d_503 (Conv2D)             (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_506 (Conv2D)             (None, 61, 61, 96)   55296       activation_485[0][0]             
__________________________________________________________________________________________________
batch_normalization_503 (BatchN (None, 61, 61, 48)   144         conv2d_503[0][0]                 
__________________________________________________________________________________________________
batch_normalization_506 (BatchN (None, 61, 61, 96)   288         conv2d_506[0][0]                 
__________________________________________________________________________________________________
activation_483 (Activation)     (None, 61, 61, 48)   0           batch_normalization_503[0][0]    
__________________________________________________________________________________________________
activation_486 (Activation)     (None, 61, 61, 96)   0           batch_normalization_506[0][0]    
__________________________________________________________________________________________________
average_pooling2d_46 (AveragePo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_502 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_504 (Conv2D)             (None, 61, 61, 64)   76800       activation_483[0][0]             
__________________________________________________________________________________________________
conv2d_507 (Conv2D)             (None, 61, 61, 96)   82944       activation_486[0][0]             
__________________________________________________________________________________________________
conv2d_508 (Conv2D)             (None, 61, 61, 64)   16384       average_pooling2d_46[0][0]       
__________________________________________________________________________________________________
batch_normalization_502 (BatchN (None, 61, 61, 64)   192         conv2d_502[0][0]                 
__________________________________________________________________________________________________
batch_normalization_504 (BatchN (None, 61, 61, 64)   192         conv2d_504[0][0]                 
__________________________________________________________________________________________________
batch_normalization_507 (BatchN (None, 61, 61, 96)   288         conv2d_507[0][0]                 
__________________________________________________________________________________________________
batch_normalization_508 (BatchN (None, 61, 61, 64)   192         conv2d_508[0][0]                 
__________________________________________________________________________________________________
activation_482 (Activation)     (None, 61, 61, 64)   0           batch_normalization_502[0][0]    
__________________________________________________________________________________________________
activation_484 (Activation)     (None, 61, 61, 64)   0           batch_normalization_504[0][0]    
__________________________________________________________________________________________________
activation_487 (Activation)     (None, 61, 61, 96)   0           batch_normalization_507[0][0]    
__________________________________________________________________________________________________
activation_488 (Activation)     (None, 61, 61, 64)   0           batch_normalization_508[0][0]    
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_482[0][0]             
                                                                 activation_484[0][0]             
                                                                 activation_487[0][0]             
                                                                 activation_488[0][0]             
__________________________________________________________________________________________________
conv2d_512 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_512 (BatchN (None, 61, 61, 64)   192         conv2d_512[0][0]                 
__________________________________________________________________________________________________
activation_492 (Activation)     (None, 61, 61, 64)   0           batch_normalization_512[0][0]    
__________________________________________________________________________________________________
conv2d_510 (Conv2D)             (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_513 (Conv2D)             (None, 61, 61, 96)   55296       activation_492[0][0]             
__________________________________________________________________________________________________
batch_normalization_510 (BatchN (None, 61, 61, 48)   144         conv2d_510[0][0]                 
__________________________________________________________________________________________________
batch_normalization_513 (BatchN (None, 61, 61, 96)   288         conv2d_513[0][0]                 
__________________________________________________________________________________________________
activation_490 (Activation)     (None, 61, 61, 48)   0           batch_normalization_510[0][0]    
__________________________________________________________________________________________________
activation_493 (Activation)     (None, 61, 61, 96)   0           batch_normalization_513[0][0]    
__________________________________________________________________________________________________
average_pooling2d_47 (AveragePo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_509 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_511 (Conv2D)             (None, 61, 61, 64)   76800       activation_490[0][0]             
__________________________________________________________________________________________________
conv2d_514 (Conv2D)             (None, 61, 61, 96)   82944       activation_493[0][0]             
__________________________________________________________________________________________________
conv2d_515 (Conv2D)             (None, 61, 61, 64)   18432       average_pooling2d_47[0][0]       
__________________________________________________________________________________________________
batch_normalization_509 (BatchN (None, 61, 61, 64)   192         conv2d_509[0][0]                 
__________________________________________________________________________________________________
batch_normalization_511 (BatchN (None, 61, 61, 64)   192         conv2d_511[0][0]                 
__________________________________________________________________________________________________
batch_normalization_514 (BatchN (None, 61, 61, 96)   288         conv2d_514[0][0]                 
__________________________________________________________________________________________________
batch_normalization_515 (BatchN (None, 61, 61, 64)   192         conv2d_515[0][0]                 
__________________________________________________________________________________________________
activation_489 (Activation)     (None, 61, 61, 64)   0           batch_normalization_509[0][0]    
__________________________________________________________________________________________________
activation_491 (Activation)     (None, 61, 61, 64)   0           batch_normalization_511[0][0]    
__________________________________________________________________________________________________
activation_494 (Activation)     (None, 61, 61, 96)   0           batch_normalization_514[0][0]    
__________________________________________________________________________________________________
activation_495 (Activation)     (None, 61, 61, 64)   0           batch_normalization_515[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_489[0][0]             
                                                                 activation_491[0][0]             
                                                                 activation_494[0][0]             
                                                                 activation_495[0][0]             
__________________________________________________________________________________________________
conv2d_517 (Conv2D)             (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_517 (BatchN (None, 61, 61, 64)   192         conv2d_517[0][0]                 
__________________________________________________________________________________________________
activation_497 (Activation)     (None, 61, 61, 64)   0           batch_normalization_517[0][0]    
__________________________________________________________________________________________________
conv2d_518 (Conv2D)             (None, 61, 61, 96)   55296       activation_497[0][0]             
__________________________________________________________________________________________________
batch_normalization_518 (BatchN (None, 61, 61, 96)   288         conv2d_518[0][0]                 
__________________________________________________________________________________________________
activation_498 (Activation)     (None, 61, 61, 96)   0           batch_normalization_518[0][0]    
__________________________________________________________________________________________________
conv2d_516 (Conv2D)             (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_519 (Conv2D)             (None, 30, 30, 96)   82944       activation_498[0][0]             
__________________________________________________________________________________________________
batch_normalization_516 (BatchN (None, 30, 30, 384)  1152        conv2d_516[0][0]                 
__________________________________________________________________________________________________
batch_normalization_519 (BatchN (None, 30, 30, 96)   288         conv2d_519[0][0]                 
__________________________________________________________________________________________________
activation_496 (Activation)     (None, 30, 30, 384)  0           batch_normalization_516[0][0]    
__________________________________________________________________________________________________
activation_499 (Activation)     (None, 30, 30, 96)   0           batch_normalization_519[0][0]    
__________________________________________________________________________________________________
max_pooling2d_22 (MaxPooling2D) (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_496[0][0]             
                                                                 activation_499[0][0]             
                                                                 max_pooling2d_22[0][0]           
__________________________________________________________________________________________________
conv2d_524 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_524 (BatchN (None, 30, 30, 128)  384         conv2d_524[0][0]                 
__________________________________________________________________________________________________
activation_504 (Activation)     (None, 30, 30, 128)  0           batch_normalization_524[0][0]    
__________________________________________________________________________________________________
conv2d_525 (Conv2D)             (None, 30, 30, 128)  114688      activation_504[0][0]             
__________________________________________________________________________________________________
batch_normalization_525 (BatchN (None, 30, 30, 128)  384         conv2d_525[0][0]                 
__________________________________________________________________________________________________
activation_505 (Activation)     (None, 30, 30, 128)  0           batch_normalization_525[0][0]    
__________________________________________________________________________________________________
conv2d_521 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_526 (Conv2D)             (None, 30, 30, 128)  114688      activation_505[0][0]             
__________________________________________________________________________________________________
batch_normalization_521 (BatchN (None, 30, 30, 128)  384         conv2d_521[0][0]                 
__________________________________________________________________________________________________
batch_normalization_526 (BatchN (None, 30, 30, 128)  384         conv2d_526[0][0]                 
__________________________________________________________________________________________________
activation_501 (Activation)     (None, 30, 30, 128)  0           batch_normalization_521[0][0]    
__________________________________________________________________________________________________
activation_506 (Activation)     (None, 30, 30, 128)  0           batch_normalization_526[0][0]    
__________________________________________________________________________________________________
conv2d_522 (Conv2D)             (None, 30, 30, 128)  114688      activation_501[0][0]             
__________________________________________________________________________________________________
conv2d_527 (Conv2D)             (None, 30, 30, 128)  114688      activation_506[0][0]             
__________________________________________________________________________________________________
batch_normalization_522 (BatchN (None, 30, 30, 128)  384         conv2d_522[0][0]                 
__________________________________________________________________________________________________
batch_normalization_527 (BatchN (None, 30, 30, 128)  384         conv2d_527[0][0]                 
__________________________________________________________________________________________________
activation_502 (Activation)     (None, 30, 30, 128)  0           batch_normalization_522[0][0]    
__________________________________________________________________________________________________
activation_507 (Activation)     (None, 30, 30, 128)  0           batch_normalization_527[0][0]    
__________________________________________________________________________________________________
average_pooling2d_48 (AveragePo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_520 (Conv2D)             (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_523 (Conv2D)             (None, 30, 30, 192)  172032      activation_502[0][0]             
__________________________________________________________________________________________________
conv2d_528 (Conv2D)             (None, 30, 30, 192)  172032      activation_507[0][0]             
__________________________________________________________________________________________________
conv2d_529 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_48[0][0]       
__________________________________________________________________________________________________
batch_normalization_520 (BatchN (None, 30, 30, 192)  576         conv2d_520[0][0]                 
__________________________________________________________________________________________________
batch_normalization_523 (BatchN (None, 30, 30, 192)  576         conv2d_523[0][0]                 
__________________________________________________________________________________________________
batch_normalization_528 (BatchN (None, 30, 30, 192)  576         conv2d_528[0][0]                 
__________________________________________________________________________________________________
batch_normalization_529 (BatchN (None, 30, 30, 192)  576         conv2d_529[0][0]                 
__________________________________________________________________________________________________
activation_500 (Activation)     (None, 30, 30, 192)  0           batch_normalization_520[0][0]    
__________________________________________________________________________________________________
activation_503 (Activation)     (None, 30, 30, 192)  0           batch_normalization_523[0][0]    
__________________________________________________________________________________________________
activation_508 (Activation)     (None, 30, 30, 192)  0           batch_normalization_528[0][0]    
__________________________________________________________________________________________________
activation_509 (Activation)     (None, 30, 30, 192)  0           batch_normalization_529[0][0]    
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_500[0][0]             
                                                                 activation_503[0][0]             
                                                                 activation_508[0][0]             
                                                                 activation_509[0][0]             
__________________________________________________________________________________________________
conv2d_534 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_534 (BatchN (None, 30, 30, 160)  480         conv2d_534[0][0]                 
__________________________________________________________________________________________________
activation_514 (Activation)     (None, 30, 30, 160)  0           batch_normalization_534[0][0]    
__________________________________________________________________________________________________
conv2d_535 (Conv2D)             (None, 30, 30, 160)  179200      activation_514[0][0]             
__________________________________________________________________________________________________
batch_normalization_535 (BatchN (None, 30, 30, 160)  480         conv2d_535[0][0]                 
__________________________________________________________________________________________________
activation_515 (Activation)     (None, 30, 30, 160)  0           batch_normalization_535[0][0]    
__________________________________________________________________________________________________
conv2d_531 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_536 (Conv2D)             (None, 30, 30, 160)  179200      activation_515[0][0]             
__________________________________________________________________________________________________
batch_normalization_531 (BatchN (None, 30, 30, 160)  480         conv2d_531[0][0]                 
__________________________________________________________________________________________________
batch_normalization_536 (BatchN (None, 30, 30, 160)  480         conv2d_536[0][0]                 
__________________________________________________________________________________________________
activation_511 (Activation)     (None, 30, 30, 160)  0           batch_normalization_531[0][0]    
__________________________________________________________________________________________________
activation_516 (Activation)     (None, 30, 30, 160)  0           batch_normalization_536[0][0]    
__________________________________________________________________________________________________
conv2d_532 (Conv2D)             (None, 30, 30, 160)  179200      activation_511[0][0]             
__________________________________________________________________________________________________
conv2d_537 (Conv2D)             (None, 30, 30, 160)  179200      activation_516[0][0]             
__________________________________________________________________________________________________
batch_normalization_532 (BatchN (None, 30, 30, 160)  480         conv2d_532[0][0]                 
__________________________________________________________________________________________________
batch_normalization_537 (BatchN (None, 30, 30, 160)  480         conv2d_537[0][0]                 
__________________________________________________________________________________________________
activation_512 (Activation)     (None, 30, 30, 160)  0           batch_normalization_532[0][0]    
__________________________________________________________________________________________________
activation_517 (Activation)     (None, 30, 30, 160)  0           batch_normalization_537[0][0]    
__________________________________________________________________________________________________
average_pooling2d_49 (AveragePo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_530 (Conv2D)             (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_533 (Conv2D)             (None, 30, 30, 192)  215040      activation_512[0][0]             
__________________________________________________________________________________________________
conv2d_538 (Conv2D)             (None, 30, 30, 192)  215040      activation_517[0][0]             
__________________________________________________________________________________________________
conv2d_539 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_49[0][0]       
__________________________________________________________________________________________________
batch_normalization_530 (BatchN (None, 30, 30, 192)  576         conv2d_530[0][0]                 
__________________________________________________________________________________________________
batch_normalization_533 (BatchN (None, 30, 30, 192)  576         conv2d_533[0][0]                 
__________________________________________________________________________________________________
batch_normalization_538 (BatchN (None, 30, 30, 192)  576         conv2d_538[0][0]                 
__________________________________________________________________________________________________
batch_normalization_539 (BatchN (None, 30, 30, 192)  576         conv2d_539[0][0]                 
__________________________________________________________________________________________________
activation_510 (Activation)     (None, 30, 30, 192)  0           batch_normalization_530[0][0]    
__________________________________________________________________________________________________
activation_513 (Activation)     (None, 30, 30, 192)  0           batch_normalization_533[0][0]    
__________________________________________________________________________________________________
activation_518 (Activation)     (None, 30, 30, 192)  0           batch_normalization_538[0][0]    
__________________________________________________________________________________________________
activation_519 (Activation)     (None, 30, 30, 192)  0           batch_normalization_539[0][0]    
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_510[0][0]             
                                                                 activation_513[0][0]             
                                                                 activation_518[0][0]             
                                                                 activation_519[0][0]             
__________________________________________________________________________________________________
conv2d_544 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_544 (BatchN (None, 30, 30, 160)  480         conv2d_544[0][0]                 
__________________________________________________________________________________________________
activation_524 (Activation)     (None, 30, 30, 160)  0           batch_normalization_544[0][0]    
__________________________________________________________________________________________________
conv2d_545 (Conv2D)             (None, 30, 30, 160)  179200      activation_524[0][0]             
__________________________________________________________________________________________________
batch_normalization_545 (BatchN (None, 30, 30, 160)  480         conv2d_545[0][0]                 
__________________________________________________________________________________________________
activation_525 (Activation)     (None, 30, 30, 160)  0           batch_normalization_545[0][0]    
__________________________________________________________________________________________________
conv2d_541 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_546 (Conv2D)             (None, 30, 30, 160)  179200      activation_525[0][0]             
__________________________________________________________________________________________________
batch_normalization_541 (BatchN (None, 30, 30, 160)  480         conv2d_541[0][0]                 
__________________________________________________________________________________________________
batch_normalization_546 (BatchN (None, 30, 30, 160)  480         conv2d_546[0][0]                 
__________________________________________________________________________________________________
activation_521 (Activation)     (None, 30, 30, 160)  0           batch_normalization_541[0][0]    
__________________________________________________________________________________________________
activation_526 (Activation)     (None, 30, 30, 160)  0           batch_normalization_546[0][0]    
__________________________________________________________________________________________________
conv2d_542 (Conv2D)             (None, 30, 30, 160)  179200      activation_521[0][0]             
__________________________________________________________________________________________________
conv2d_547 (Conv2D)             (None, 30, 30, 160)  179200      activation_526[0][0]             
__________________________________________________________________________________________________
batch_normalization_542 (BatchN (None, 30, 30, 160)  480         conv2d_542[0][0]                 
__________________________________________________________________________________________________
batch_normalization_547 (BatchN (None, 30, 30, 160)  480         conv2d_547[0][0]                 
__________________________________________________________________________________________________
activation_522 (Activation)     (None, 30, 30, 160)  0           batch_normalization_542[0][0]    
__________________________________________________________________________________________________
activation_527 (Activation)     (None, 30, 30, 160)  0           batch_normalization_547[0][0]    
__________________________________________________________________________________________________
average_pooling2d_50 (AveragePo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_540 (Conv2D)             (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_543 (Conv2D)             (None, 30, 30, 192)  215040      activation_522[0][0]             
__________________________________________________________________________________________________
conv2d_548 (Conv2D)             (None, 30, 30, 192)  215040      activation_527[0][0]             
__________________________________________________________________________________________________
conv2d_549 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_50[0][0]       
__________________________________________________________________________________________________
batch_normalization_540 (BatchN (None, 30, 30, 192)  576         conv2d_540[0][0]                 
__________________________________________________________________________________________________
batch_normalization_543 (BatchN (None, 30, 30, 192)  576         conv2d_543[0][0]                 
__________________________________________________________________________________________________
batch_normalization_548 (BatchN (None, 30, 30, 192)  576         conv2d_548[0][0]                 
__________________________________________________________________________________________________
batch_normalization_549 (BatchN (None, 30, 30, 192)  576         conv2d_549[0][0]                 
__________________________________________________________________________________________________
activation_520 (Activation)     (None, 30, 30, 192)  0           batch_normalization_540[0][0]    
__________________________________________________________________________________________________
activation_523 (Activation)     (None, 30, 30, 192)  0           batch_normalization_543[0][0]    
__________________________________________________________________________________________________
activation_528 (Activation)     (None, 30, 30, 192)  0           batch_normalization_548[0][0]    
__________________________________________________________________________________________________
activation_529 (Activation)     (None, 30, 30, 192)  0           batch_normalization_549[0][0]    
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_520[0][0]             
                                                                 activation_523[0][0]             
                                                                 activation_528[0][0]             
                                                                 activation_529[0][0]             
__________________________________________________________________________________________________
conv2d_554 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_554 (BatchN (None, 30, 30, 192)  576         conv2d_554[0][0]                 
__________________________________________________________________________________________________
activation_534 (Activation)     (None, 30, 30, 192)  0           batch_normalization_554[0][0]    
__________________________________________________________________________________________________
conv2d_555 (Conv2D)             (None, 30, 30, 192)  258048      activation_534[0][0]             
__________________________________________________________________________________________________
batch_normalization_555 (BatchN (None, 30, 30, 192)  576         conv2d_555[0][0]                 
__________________________________________________________________________________________________
activation_535 (Activation)     (None, 30, 30, 192)  0           batch_normalization_555[0][0]    
__________________________________________________________________________________________________
conv2d_551 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_556 (Conv2D)             (None, 30, 30, 192)  258048      activation_535[0][0]             
__________________________________________________________________________________________________
batch_normalization_551 (BatchN (None, 30, 30, 192)  576         conv2d_551[0][0]                 
__________________________________________________________________________________________________
batch_normalization_556 (BatchN (None, 30, 30, 192)  576         conv2d_556[0][0]                 
__________________________________________________________________________________________________
activation_531 (Activation)     (None, 30, 30, 192)  0           batch_normalization_551[0][0]    
__________________________________________________________________________________________________
activation_536 (Activation)     (None, 30, 30, 192)  0           batch_normalization_556[0][0]    
__________________________________________________________________________________________________
conv2d_552 (Conv2D)             (None, 30, 30, 192)  258048      activation_531[0][0]             
__________________________________________________________________________________________________
conv2d_557 (Conv2D)             (None, 30, 30, 192)  258048      activation_536[0][0]             
__________________________________________________________________________________________________
batch_normalization_552 (BatchN (None, 30, 30, 192)  576         conv2d_552[0][0]                 
__________________________________________________________________________________________________
batch_normalization_557 (BatchN (None, 30, 30, 192)  576         conv2d_557[0][0]                 
__________________________________________________________________________________________________
activation_532 (Activation)     (None, 30, 30, 192)  0           batch_normalization_552[0][0]    
__________________________________________________________________________________________________
activation_537 (Activation)     (None, 30, 30, 192)  0           batch_normalization_557[0][0]    
__________________________________________________________________________________________________
average_pooling2d_51 (AveragePo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_550 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_553 (Conv2D)             (None, 30, 30, 192)  258048      activation_532[0][0]             
__________________________________________________________________________________________________
conv2d_558 (Conv2D)             (None, 30, 30, 192)  258048      activation_537[0][0]             
__________________________________________________________________________________________________
conv2d_559 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_51[0][0]       
__________________________________________________________________________________________________
batch_normalization_550 (BatchN (None, 30, 30, 192)  576         conv2d_550[0][0]                 
__________________________________________________________________________________________________
batch_normalization_553 (BatchN (None, 30, 30, 192)  576         conv2d_553[0][0]                 
__________________________________________________________________________________________________
batch_normalization_558 (BatchN (None, 30, 30, 192)  576         conv2d_558[0][0]                 
__________________________________________________________________________________________________
batch_normalization_559 (BatchN (None, 30, 30, 192)  576         conv2d_559[0][0]                 
__________________________________________________________________________________________________
activation_530 (Activation)     (None, 30, 30, 192)  0           batch_normalization_550[0][0]    
__________________________________________________________________________________________________
activation_533 (Activation)     (None, 30, 30, 192)  0           batch_normalization_553[0][0]    
__________________________________________________________________________________________________
activation_538 (Activation)     (None, 30, 30, 192)  0           batch_normalization_558[0][0]    
__________________________________________________________________________________________________
activation_539 (Activation)     (None, 30, 30, 192)  0           batch_normalization_559[0][0]    
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_530[0][0]             
                                                                 activation_533[0][0]             
                                                                 activation_538[0][0]             
                                                                 activation_539[0][0]             
__________________________________________________________________________________________________
conv2d_562 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_562 (BatchN (None, 30, 30, 192)  576         conv2d_562[0][0]                 
__________________________________________________________________________________________________
activation_542 (Activation)     (None, 30, 30, 192)  0           batch_normalization_562[0][0]    
__________________________________________________________________________________________________
conv2d_563 (Conv2D)             (None, 30, 30, 192)  258048      activation_542[0][0]             
__________________________________________________________________________________________________
batch_normalization_563 (BatchN (None, 30, 30, 192)  576         conv2d_563[0][0]                 
__________________________________________________________________________________________________
activation_543 (Activation)     (None, 30, 30, 192)  0           batch_normalization_563[0][0]    
__________________________________________________________________________________________________
conv2d_560 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_564 (Conv2D)             (None, 30, 30, 192)  258048      activation_543[0][0]             
__________________________________________________________________________________________________
batch_normalization_560 (BatchN (None, 30, 30, 192)  576         conv2d_560[0][0]                 
__________________________________________________________________________________________________
batch_normalization_564 (BatchN (None, 30, 30, 192)  576         conv2d_564[0][0]                 
__________________________________________________________________________________________________
activation_540 (Activation)     (None, 30, 30, 192)  0           batch_normalization_560[0][0]    
__________________________________________________________________________________________________
activation_544 (Activation)     (None, 30, 30, 192)  0           batch_normalization_564[0][0]    
__________________________________________________________________________________________________
conv2d_561 (Conv2D)             (None, 14, 14, 320)  552960      activation_540[0][0]             
__________________________________________________________________________________________________
conv2d_565 (Conv2D)             (None, 14, 14, 192)  331776      activation_544[0][0]             
__________________________________________________________________________________________________
batch_normalization_561 (BatchN (None, 14, 14, 320)  960         conv2d_561[0][0]                 
__________________________________________________________________________________________________
batch_normalization_565 (BatchN (None, 14, 14, 192)  576         conv2d_565[0][0]                 
__________________________________________________________________________________________________
activation_541 (Activation)     (None, 14, 14, 320)  0           batch_normalization_561[0][0]    
__________________________________________________________________________________________________
activation_545 (Activation)     (None, 14, 14, 192)  0           batch_normalization_565[0][0]    
__________________________________________________________________________________________________
max_pooling2d_23 (MaxPooling2D) (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_541[0][0]             
                                                                 activation_545[0][0]             
                                                                 max_pooling2d_23[0][0]           
__________________________________________________________________________________________________
conv2d_570 (Conv2D)             (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_570 (BatchN (None, 14, 14, 448)  1344        conv2d_570[0][0]                 
__________________________________________________________________________________________________
activation_550 (Activation)     (None, 14, 14, 448)  0           batch_normalization_570[0][0]    
__________________________________________________________________________________________________
conv2d_567 (Conv2D)             (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_571 (Conv2D)             (None, 14, 14, 384)  1548288     activation_550[0][0]             
__________________________________________________________________________________________________
batch_normalization_567 (BatchN (None, 14, 14, 384)  1152        conv2d_567[0][0]                 
__________________________________________________________________________________________________
batch_normalization_571 (BatchN (None, 14, 14, 384)  1152        conv2d_571[0][0]                 
__________________________________________________________________________________________________
activation_547 (Activation)     (None, 14, 14, 384)  0           batch_normalization_567[0][0]    
__________________________________________________________________________________________________
activation_551 (Activation)     (None, 14, 14, 384)  0           batch_normalization_571[0][0]    
__________________________________________________________________________________________________
conv2d_568 (Conv2D)             (None, 14, 14, 384)  442368      activation_547[0][0]             
__________________________________________________________________________________________________
conv2d_569 (Conv2D)             (None, 14, 14, 384)  442368      activation_547[0][0]             
__________________________________________________________________________________________________
conv2d_572 (Conv2D)             (None, 14, 14, 384)  442368      activation_551[0][0]             
__________________________________________________________________________________________________
conv2d_573 (Conv2D)             (None, 14, 14, 384)  442368      activation_551[0][0]             
__________________________________________________________________________________________________
average_pooling2d_52 (AveragePo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_566 (Conv2D)             (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_568 (BatchN (None, 14, 14, 384)  1152        conv2d_568[0][0]                 
__________________________________________________________________________________________________
batch_normalization_569 (BatchN (None, 14, 14, 384)  1152        conv2d_569[0][0]                 
__________________________________________________________________________________________________
batch_normalization_572 (BatchN (None, 14, 14, 384)  1152        conv2d_572[0][0]                 
__________________________________________________________________________________________________
batch_normalization_573 (BatchN (None, 14, 14, 384)  1152        conv2d_573[0][0]                 
__________________________________________________________________________________________________
conv2d_574 (Conv2D)             (None, 14, 14, 192)  245760      average_pooling2d_52[0][0]       
__________________________________________________________________________________________________
batch_normalization_566 (BatchN (None, 14, 14, 320)  960         conv2d_566[0][0]                 
__________________________________________________________________________________________________
activation_548 (Activation)     (None, 14, 14, 384)  0           batch_normalization_568[0][0]    
__________________________________________________________________________________________________
activation_549 (Activation)     (None, 14, 14, 384)  0           batch_normalization_569[0][0]    
__________________________________________________________________________________________________
activation_552 (Activation)     (None, 14, 14, 384)  0           batch_normalization_572[0][0]    
__________________________________________________________________________________________________
activation_553 (Activation)     (None, 14, 14, 384)  0           batch_normalization_573[0][0]    
__________________________________________________________________________________________________
batch_normalization_574 (BatchN (None, 14, 14, 192)  576         conv2d_574[0][0]                 
__________________________________________________________________________________________________
activation_546 (Activation)     (None, 14, 14, 320)  0           batch_normalization_566[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_548[0][0]             
                                                                 activation_549[0][0]             
__________________________________________________________________________________________________
concatenate_10 (Concatenate)    (None, 14, 14, 768)  0           activation_552[0][0]             
                                                                 activation_553[0][0]             
__________________________________________________________________________________________________
activation_554 (Activation)     (None, 14, 14, 192)  0           batch_normalization_574[0][0]    
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_546[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_10[0][0]             
                                                                 activation_554[0][0]             
__________________________________________________________________________________________________
conv2d_579 (Conv2D)             (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_579 (BatchN (None, 14, 14, 448)  1344        conv2d_579[0][0]                 
__________________________________________________________________________________________________
activation_559 (Activation)     (None, 14, 14, 448)  0           batch_normalization_579[0][0]    
__________________________________________________________________________________________________
conv2d_576 (Conv2D)             (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_580 (Conv2D)             (None, 14, 14, 384)  1548288     activation_559[0][0]             
__________________________________________________________________________________________________
batch_normalization_576 (BatchN (None, 14, 14, 384)  1152        conv2d_576[0][0]                 
__________________________________________________________________________________________________
batch_normalization_580 (BatchN (None, 14, 14, 384)  1152        conv2d_580[0][0]                 
__________________________________________________________________________________________________
activation_556 (Activation)     (None, 14, 14, 384)  0           batch_normalization_576[0][0]    
__________________________________________________________________________________________________
activation_560 (Activation)     (None, 14, 14, 384)  0           batch_normalization_580[0][0]    
__________________________________________________________________________________________________
conv2d_577 (Conv2D)             (None, 14, 14, 384)  442368      activation_556[0][0]             
__________________________________________________________________________________________________
conv2d_578 (Conv2D)             (None, 14, 14, 384)  442368      activation_556[0][0]             
__________________________________________________________________________________________________
conv2d_581 (Conv2D)             (None, 14, 14, 384)  442368      activation_560[0][0]             
__________________________________________________________________________________________________
conv2d_582 (Conv2D)             (None, 14, 14, 384)  442368      activation_560[0][0]             
__________________________________________________________________________________________________
average_pooling2d_53 (AveragePo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_575 (Conv2D)             (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_577 (BatchN (None, 14, 14, 384)  1152        conv2d_577[0][0]                 
__________________________________________________________________________________________________
batch_normalization_578 (BatchN (None, 14, 14, 384)  1152        conv2d_578[0][0]                 
__________________________________________________________________________________________________
batch_normalization_581 (BatchN (None, 14, 14, 384)  1152        conv2d_581[0][0]                 
__________________________________________________________________________________________________
batch_normalization_582 (BatchN (None, 14, 14, 384)  1152        conv2d_582[0][0]                 
__________________________________________________________________________________________________
conv2d_583 (Conv2D)             (None, 14, 14, 192)  393216      average_pooling2d_53[0][0]       
__________________________________________________________________________________________________
batch_normalization_575 (BatchN (None, 14, 14, 320)  960         conv2d_575[0][0]                 
__________________________________________________________________________________________________
activation_557 (Activation)     (None, 14, 14, 384)  0           batch_normalization_577[0][0]    
__________________________________________________________________________________________________
activation_558 (Activation)     (None, 14, 14, 384)  0           batch_normalization_578[0][0]    
__________________________________________________________________________________________________
activation_561 (Activation)     (None, 14, 14, 384)  0           batch_normalization_581[0][0]    
__________________________________________________________________________________________________
activation_562 (Activation)     (None, 14, 14, 384)  0           batch_normalization_582[0][0]    
__________________________________________________________________________________________________
batch_normalization_583 (BatchN (None, 14, 14, 192)  576         conv2d_583[0][0]                 
__________________________________________________________________________________________________
activation_555 (Activation)     (None, 14, 14, 320)  0           batch_normalization_575[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_557[0][0]             
                                                                 activation_558[0][0]             
__________________________________________________________________________________________________
concatenate_11 (Concatenate)    (None, 14, 14, 768)  0           activation_561[0][0]             
                                                                 activation_562[0][0]             
__________________________________________________________________________________________________
activation_563 (Activation)     (None, 14, 14, 192)  0           batch_normalization_583[0][0]    
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_555[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_11[0][0]             
                                                                 activation_563[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_16 (Gl (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dense_16 (Dense)                (None, 2)            4098        global_average_pooling2d_16[0][0]
==================================================================================================
Total params: 21,806,882
Trainable params: 21,772,450
Non-trainable params: 34,432
__________________________________________________________________________________________________

def xception_architecture():
    """
    Pre-build architecture of inception for our dataset.
    """
    # Imprting the model
    from keras.applications.xception import Xception

    # Pre-build model
    base_model = Xception(include_top = False, weights = None, input_tensor = model_input)

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    xception_model = Model(base_model.input, output)

    # Summary of the model
    xception_model.summary()
    
    # Compiling the model
    xception_model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                           loss = 'categorical_crossentropy', 
                           metrics = ['accuracy'])

    return xception_model

# Model 3
xception_model = xception_architecture()
xception_model.load_weights("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/xception_weights.hdf5")

Model: "model_17"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_11 (InputLayer)           [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_11[0][0]                   
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_584 (Conv2D)             (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_584 (BatchN (None, 127, 127, 128 512         conv2d_584[0][0]                 
__________________________________________________________________________________________________
add_60 (Add)                    (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_584[0][0]    
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add_60[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_585 (Conv2D)             (None, 64, 64, 256)  32768       add_60[0][0]                     
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_585 (BatchN (None, 64, 64, 256)  1024        conv2d_585[0][0]                 
__________________________________________________________________________________________________
add_61 (Add)                    (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_585[0][0]    
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_61[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_586 (Conv2D)             (None, 32, 32, 728)  186368      add_61[0][0]                     
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_586 (BatchN (None, 32, 32, 728)  2912        conv2d_586[0][0]                 
__________________________________________________________________________________________________
add_62 (Add)                    (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_586[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_62[0][0]                     
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_63 (Add)                    (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_62[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_63[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_64 (Add)                    (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_63[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_64[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_65 (Add)                    (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_64[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_65[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_66 (Add)                    (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_65[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_66[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_67 (Add)                    (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_66[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_67[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_68 (Add)                    (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_67[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_68[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_69 (Add)                    (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_68[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_69[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_70 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_69[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_70[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_587 (Conv2D)             (None, 16, 16, 1024) 745472      add_70[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_587 (BatchN (None, 16, 16, 1024) 4096        conv2d_587[0][0]                 
__________________________________________________________________________________________________
add_71 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_587[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_71[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_17 (Gl (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_17 (Dense)                (None, 2)            4098        global_average_pooling2d_17[0][0]
==================================================================================================
Total params: 20,865,578
Trainable params: 20,811,050
Non-trainable params: 54,528
__________________________________________________________________________________________________

7.3 Appending All the Models

# Appending all models
models = [mobilenet_model, inception_model, xception_model]

7.4 Defining the Ensembling Function

def ensemble(models, model_input):
    outputs = [model.outputs[0] for model in models]
    y = keras.layers.Average()(outputs)
    model = Model(model_input, y, name='ensemble')
    return model

# Getting ensemble model
ensemble_model = ensemble(models, model_input)

7.5 Evaluating ensemble model

# Compute test set predictions
#model_architecture,path_model_weight
NUMBER_TEST_SAMPLES_Ensemble_Test = 600

all_weights_combined_as_list = weights_of_MobileNet_Inception_and_Xception

y_true_Ensemble_Test = test_targets[:NUMBER_TEST_SAMPLES_Ensemble_Test]
y_score_Ensemble_Test = []
for index in range(NUMBER_TEST_SAMPLES_Ensemble_Test): #compute one at a time due to memory constraints
    probs_Ensemble_Test = predict_ensemble(img_path = test_files[index], model_architecture = ensemble_model, path_model_weight = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5")
    print("Real values {}...".format(index+1) + "Melanoma : ", test_targets[index][0], " | Other : ", test_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Ensemble_Test.append(probs_Ensemble_Test)
    
correct_Ensemble_Test = np.array(y_true_Ensemble_Test) == np.array(y_score_Ensemble_Test)

Streaming output truncated to the last 5000 lines.
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932675  | Other :  0.20673251
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79558945  | Other :  0.20441055
Real values 147...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82963395  | Other :  0.17036602
Real values 148...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79326814  | Other :  0.20673186
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934345  | Other :  0.20656554
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8035139  | Other :  0.19648616
Real values 151...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78758943  | Other :  0.21241067
Real values 152...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950778  | Other :  0.20492224
Real values 153...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8166069  | Other :  0.18339317
Real values 154...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952621  | Other :  0.20473787
Real values 155...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79467046  | Other :  0.20532954
Real values 156...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79414845  | Other :  0.20585155
Real values 157...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936207  | Other :  0.20637934
Real values 158...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934456  | Other :  0.20655444
Real values 159...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934457  | Other :  0.20655434
Real values 160...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79326534  | Other :  0.2067347
Real values 161...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8295125  | Other :  0.17048757
Real values 162...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79330635  | Other :  0.2066937
Real values 163...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297523  | Other :  0.17024772
Real values 164...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405415  | Other :  0.2059459
Real values 165...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930326  | Other :  0.20696744
Real values 166...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933788  | Other :  0.20662127
Real values 167...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943346  | Other :  0.20566541
Real values 168...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79435414  | Other :  0.2056458
Real values 169...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942679  | Other :  0.20573208
Real values 170...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940301  | Other :  0.20597002
Real values 171...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79340833  | Other :  0.2065917
Real values 172...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79331154  | Other :  0.20668845
Real values 173...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938308  | Other :  0.20616925
Real values 174...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933483  | Other :  0.20665169
Real values 175...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937374  | Other :  0.20626251
Real values 176...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7838197  | Other :  0.21618032
Real values 177...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935466  | Other :  0.20645338
Real values 178...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7532419  | Other :  0.24675816
Real values 179...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8091402  | Other :  0.19085972
Real values 180...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7959393  | Other :  0.20406067
Real values 181...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79318714  | Other :  0.20681286
Real values 182...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938156  | Other :  0.20618437
Real values 183...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943441  | Other :  0.20565587
Real values 184...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.817415  | Other :  0.18258505
Real values 185...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934859  | Other :  0.20651412
Real values 186...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82920384  | Other :  0.17079616
Real values 187...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932409  | Other :  0.20675907
Real values 188...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79401076  | Other :  0.20598924
Real values 189...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943152  | Other :  0.20568483
Real values 190...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82966566  | Other :  0.17033432
Real values 191...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77977055  | Other :  0.22022939
Real values 192...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78214455  | Other :  0.21785545
Real values 193...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.81935966  | Other :  0.18064037
Real values 194...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947444  | Other :  0.20525567
Real values 195...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7988113  | Other :  0.20118873
Real values 196...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7962114  | Other :  0.20378856
Real values 197...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7779798  | Other :  0.22202021
Real values 198...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79642105  | Other :  0.203579
Real values 199...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7571665  | Other :  0.24283355
Real values 200...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936756  | Other :  0.20632446
Real values 201...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76598525  | Other :  0.23401475
Real values 202...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79602635  | Other :  0.20397371
Real values 203...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8202397  | Other :  0.17976026
Real values 204...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79208744  | Other :  0.20791261
Real values 205...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7658404  | Other :  0.23415962
Real values 206...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7893903  | Other :  0.21060967
Real values 207...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951991  | Other :  0.20480093
Real values 208...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7972905  | Other :  0.20270959
Real values 209...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78999114  | Other :  0.21000886
Real values 210...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79303634  | Other :  0.2069637
Real values 211...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794115  | Other :  0.20588505
Real values 212...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7922127  | Other :  0.20778725
Real values 213...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942172  | Other :  0.20578282
Real values 214...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7854566  | Other :  0.21454343
Real values 215...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8076401  | Other :  0.19235997
Real values 216...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956637  | Other :  0.20433637
Real values 217...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7984292  | Other :  0.20157084
Real values 218...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7757729  | Other :  0.22422716
Real values 219...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79747957  | Other :  0.20252052
Real values 220...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79522777  | Other :  0.20477223
Real values 221...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7962944  | Other :  0.2037056
Real values 222...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956588  | Other :  0.20434126
Real values 223...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7870342  | Other :  0.21296583
Real values 224...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936491  | Other :  0.20635095
Real values 225...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78212786  | Other :  0.21787219
Real values 226...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79466337  | Other :  0.20533666
Real values 227...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7817488  | Other :  0.21825123
Real values 228...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932389  | Other :  0.2067611
Real values 229...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393375  | Other :  0.2060663
Real values 230...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795545  | Other :  0.20445506
Real values 231...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944975  | Other :  0.20550254
Real values 232...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7816381  | Other :  0.21836194
Real values 233...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947404  | Other :  0.2052596
Real values 234...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935114  | Other :  0.20648867
Real values 235...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935111  | Other :  0.20648903
Real values 236...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944281  | Other :  0.20557192
Real values 237...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935981  | Other :  0.20640187
Real values 238...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953328  | Other :  0.20466726
Real values 239...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945839  | Other :  0.20541617
Real values 240...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967249  | Other :  0.20327513
Real values 241...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79410315  | Other :  0.20589688
Real values 242...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79378545  | Other :  0.20621464
Real values 243...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944827  | Other :  0.20551726
Real values 244...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79574203  | Other :  0.20425794
Real values 245...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79426086  | Other :  0.20573923
Real values 246...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79454535  | Other :  0.20545469
Real values 247...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79368323  | Other :  0.20631675
Real values 248...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79587543  | Other :  0.20412461
Real values 249...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79387  | Other :  0.20613003
Real values 250...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947744  | Other :  0.20522568
Real values 251...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7964783  | Other :  0.2035217
Real values 252...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941548  | Other :  0.20584527
Real values 253...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934116  | Other :  0.20658842
Real values 254...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79493856  | Other :  0.20506136
Real values 255...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936933  | Other :  0.20630674
Real values 256...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79308766  | Other :  0.20691234
Real values 257...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7875676  | Other :  0.21243235
Real values 258...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942846  | Other :  0.20571542
Real values 259...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79449975  | Other :  0.20550027
Real values 260...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956897  | Other :  0.20431034
Real values 261...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.789164  | Other :  0.21083602
Real values 262...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941426  | Other :  0.2058575
Real values 263...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7949287  | Other :  0.20507133
Real values 264...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7804546  | Other :  0.21954548
Real values 265...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936051  | Other :  0.20639491
Real values 266...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938654  | Other :  0.20613466
Real values 267...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339784  | Other :  0.20660216
Real values 268...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951409  | Other :  0.20485911
Real values 269...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79614806  | Other :  0.20385198
Real values 270...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79356307  | Other :  0.20643693
Real values 271...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79388714  | Other :  0.20611286
Real values 272...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941761  | Other :  0.20582394
Real values 273...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793044  | Other :  0.20695603
Real values 274...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7814399  | Other :  0.21856014
Real values 275...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946496  | Other :  0.20535037
Real values 276...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7667006  | Other :  0.23329942
Real values 277...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7906282  | Other :  0.20937178
Real values 278...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934238  | Other :  0.20657627
Real values 279...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794332  | Other :  0.20566797
Real values 280...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942276  | Other :  0.2057724
Real values 281...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79297984  | Other :  0.20702025
Real values 282...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79707164  | Other :  0.20292842
Real values 283...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941567  | Other :  0.20584333
Real values 284...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79390085  | Other :  0.20609918
Real values 285...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78428835  | Other :  0.21571164
Real values 286...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7911601  | Other :  0.2088399
Real values 287...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79423493  | Other :  0.20576505
Real values 288...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793249  | Other :  0.20675103
Real values 289...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945336  | Other :  0.20546643
Real values 290...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932191  | Other :  0.20678088
Real values 291...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795144  | Other :  0.20485604
Real values 292...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936505  | Other :  0.20634955
Real values 293...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7802357  | Other :  0.21976434
Real values 294...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7948866  | Other :  0.2051134
Real values 295...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7810275  | Other :  0.21897253
Real values 296...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79522717  | Other :  0.20477287
Real values 297...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931323  | Other :  0.20686772
Real values 298...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79375124  | Other :  0.20624876
Real values 299...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933385  | Other :  0.20666158
Real values 300...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941682  | Other :  0.20583181
Real values 301...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79317874  | Other :  0.20682123
Real values 302...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935853  | Other :  0.20641473
Real values 303...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79392433  | Other :  0.20607567
Real values 304...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79481924  | Other :  0.20518081
Real values 305...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79022044  | Other :  0.20977962
Real values 306...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793409  | Other :  0.20659101
Real values 307...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958328  | Other :  0.20416719
Real values 308...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950212  | Other :  0.20497887
Real values 309...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794927  | Other :  0.20507306
Real values 310...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79394746  | Other :  0.20605253
Real values 311...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936053  | Other :  0.20639467
Real values 312...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946223  | Other :  0.2053777
Real values 313...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939347  | Other :  0.20606534
Real values 314...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79363006  | Other :  0.20636998
Real values 315...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955115  | Other :  0.20448849
Real values 316...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8269927  | Other :  0.1730073
Real values 317...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940022  | Other :  0.20599791
Real values 318...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79445285  | Other :  0.20554721
Real values 319...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8034641  | Other :  0.19653587
Real values 320...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79416776  | Other :  0.20583224
Real values 321...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78912055  | Other :  0.21087949
Real values 322...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952186  | Other :  0.20478146
Real values 323...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941952  | Other :  0.2058048
Real values 324...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79457474  | Other :  0.2054252
Real values 325...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79696274  | Other :  0.20303732
Real values 326...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931463  | Other :  0.20685375
Real values 327...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.80604595  | Other :  0.19395404
Real values 328...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937534  | Other :  0.2062466
Real values 329...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7881541  | Other :  0.21184587
Real values 330...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7663101  | Other :  0.23369001
Real values 331...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79549575  | Other :  0.20450422
Real values 332...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79420656  | Other :  0.20579349
Real values 333...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79569936  | Other :  0.20430064
Real values 334...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953614  | Other :  0.20463869
Real values 335...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79374546  | Other :  0.20625457
Real values 336...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955908  | Other :  0.20440921
Real values 337...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79524803  | Other :  0.20475194
Real values 338...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953965  | Other :  0.2046035
Real values 339...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8285195  | Other :  0.17148054
Real values 340...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931687  | Other :  0.20683128
Real values 341...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7845032  | Other :  0.21549678
Real values 342...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795058  | Other :  0.20494203
Real values 343...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7788918  | Other :  0.22110826
Real values 344...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947756  | Other :  0.20522444
Real values 345...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79379165  | Other :  0.2062084
Real values 346...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930727  | Other :  0.2069273
Real values 347...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78710115  | Other :  0.21289897
Real values 348...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7816312  | Other :  0.21836889
Real values 349...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933502  | Other :  0.20664981
Real values 350...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79302424  | Other :  0.2069758
Real values 351...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793898  | Other :  0.2061021
Real values 352...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7924123  | Other :  0.20758772
Real values 353...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79363793  | Other :  0.20636205
Real values 354...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79368466  | Other :  0.20631537
Real values 355...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7948556  | Other :  0.20514445
Real values 356...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937939  | Other :  0.20620608
Real values 357...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79438514  | Other :  0.2056149
Real values 358...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934507  | Other :  0.20654935
Real values 359...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7838382  | Other :  0.21616182
Real values 360...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941723  | Other :  0.20582774
Real values 361...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79850125  | Other :  0.20149873
Real values 362...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953528  | Other :  0.20464723
Real values 363...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794157  | Other :  0.20584297
Real values 364...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79311466  | Other :  0.20688532
Real values 365...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79244536  | Other :  0.20755467
Real values 366...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7949053  | Other :  0.20509478
Real values 367...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939985  | Other :  0.20600149
Real values 368...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795525  | Other :  0.20447499
Real values 369...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950814  | Other :  0.20491865
Real values 370...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79425466  | Other :  0.20574537
Real values 371...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945368  | Other :  0.20546323
Real values 372...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.81901455  | Other :  0.18098548
Real values 373...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79429454  | Other :  0.20570546
Real values 374...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7900984  | Other :  0.20990157
Real values 375...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938697  | Other :  0.20613031
Real values 376...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7954709  | Other :  0.20452914
Real values 377...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952074  | Other :  0.20479262
Real values 378...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8259684  | Other :  0.17403167
Real values 379...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941901  | Other :  0.20580992
Real values 380...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7965085  | Other :  0.20349154
Real values 381...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79568005  | Other :  0.20431992
Real values 382...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941961  | Other :  0.20580396
Real values 383...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943274  | Other :  0.20567262
Real values 384...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943103  | Other :  0.20568977
Real values 385...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930114  | Other :  0.20698854
Real values 386...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79351014  | Other :  0.20648989
Real values 387...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78872025  | Other :  0.21127984
Real values 388...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7613653  | Other :  0.2386348
Real values 389...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967007  | Other :  0.20329928
Real values 390...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970519  | Other :  0.20294814
Real values 391...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944934  | Other :  0.20550661
Real values 392...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943234  | Other :  0.20567665
Real values 393...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958375  | Other :  0.20416252
Real values 394...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795937  | Other :  0.204063
Real values 395...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.83000183  | Other :  0.16999814
Real values 396...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7965808  | Other :  0.20341915
Real values 397...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940438  | Other :  0.2059562
Real values 398...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935314  | Other :  0.20646863
Real values 399...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348314  | Other :  0.20651698
Real values 400...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947077  | Other :  0.20529228
Real values 401...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79545164  | Other :  0.20454834
Real values 402...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793636  | Other :  0.20636395
Real values 403...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935729  | Other :  0.20642713
Real values 404...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7963285  | Other :  0.20367154
Real values 405...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944557  | Other :  0.20554432
Real values 406...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78697  | Other :  0.21303003
Real values 407...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.80416095  | Other :  0.19583917
Real values 408...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7969741  | Other :  0.2030259
Real values 409...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7977532  | Other :  0.20224679
Real values 410...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79514694  | Other :  0.20485306
Real values 411...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7525853  | Other :  0.24741481
Real values 412...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76478994  | Other :  0.23521003
Real values 413...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79427576  | Other :  0.20572427
Real values 414...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78345585  | Other :  0.21654412
Real values 415...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955586  | Other :  0.20444143
Real values 416...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82114947  | Other :  0.17885059
Real values 417...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937803  | Other :  0.20621967
Real values 418...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7731613  | Other :  0.22683875
Real values 419...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79494995  | Other :  0.20505008
Real values 420...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7974073  | Other :  0.20259272
Real values 421...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79416674  | Other :  0.20583324
Real values 422...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79539204  | Other :  0.20460796
Real values 423...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936691  | Other :  0.20633094
Real values 424...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8078474  | Other :  0.19215266
Real values 425...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79251957  | Other :  0.20748049
Real values 426...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7959937  | Other :  0.2040064
Real values 427...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931198  | Other :  0.2068803
Real values 428...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77308625  | Other :  0.22691385
Real values 429...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935097  | Other :  0.20649025
Real values 430...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.792863  | Other :  0.20713703
Real values 431...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941704  | Other :  0.20582956
Real values 432...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933511  | Other :  0.20664889
Real values 433...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79311347  | Other :  0.2068865
Real values 434...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7616414  | Other :  0.23835866
Real values 435...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946279  | Other :  0.20537207
Real values 436...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946763  | Other :  0.20532373
Real values 437...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7860457  | Other :  0.21395437
Real values 438...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7837212  | Other :  0.21627879
Real values 439...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970831  | Other :  0.20291698
Real values 440...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935292  | Other :  0.20647079
Real values 441...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955595  | Other :  0.20444047
Real values 442...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79734534  | Other :  0.20265464
Real values 443...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8300178  | Other :  0.16998222
Real values 444...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947943  | Other :  0.20520568
Real values 445...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79174507  | Other :  0.20825498
Real values 446...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76002026  | Other :  0.23997971
Real values 447...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79127944  | Other :  0.20872061
Real values 448...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79305077  | Other :  0.20694926
Real values 449...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79438066  | Other :  0.20561934
Real values 450...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951614  | Other :  0.2048386
Real values 451...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79526365  | Other :  0.20473644
Real values 452...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7979859  | Other :  0.20201413
Real values 453...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78266084  | Other :  0.2173392
Real values 454...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79797244  | Other :  0.20202756
Real values 455...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79445875  | Other :  0.20554137
Real values 456...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79491127  | Other :  0.2050888
Real values 457...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938006  | Other :  0.2061994
Real values 458...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7835495  | Other :  0.21645056
Real values 459...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944576  | Other :  0.20554242
Real values 460...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937789  | Other :  0.20622104
Real values 461...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79350203  | Other :  0.20649801
Real values 462...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79317284  | Other :  0.20682716
Real values 463...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937233  | Other :  0.20627674
Real values 464...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941545  | Other :  0.20584558
Real values 465...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7917743  | Other :  0.20822579
Real values 466...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79495275  | Other :  0.20504731
Real values 467...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941887  | Other :  0.2058113
Real values 468...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7957759  | Other :  0.20422408
Real values 469...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7836046  | Other :  0.21639536
Real values 470...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79352283  | Other :  0.20647717
Real values 471...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947418  | Other :  0.20525818
Real values 472...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937217  | Other :  0.20627831
Real values 473...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937197  | Other :  0.20628029
Real values 474...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958764  | Other :  0.20412356
Real values 475...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7978045  | Other :  0.20219561
Real values 476...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941868  | Other :  0.20581327
Real values 477...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.829762  | Other :  0.170238
Real values 478...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946646  | Other :  0.20533542
Real values 479...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77594376  | Other :  0.22405624
Real values 480...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79417837  | Other :  0.20582174
Real values 481...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78348696  | Other :  0.21651308
Real values 482...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932881  | Other :  0.20671189
Real values 483...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79397887  | Other :  0.20602116
Real values 484...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794296  | Other :  0.20570397
Real values 485...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79400015  | Other :  0.20599982
Real values 486...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933372  | Other :  0.20666282
Real values 487...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82615113  | Other :  0.17384887
Real values 488...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79441875  | Other :  0.20558125
Real values 489...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939123  | Other :  0.20608777
Real values 490...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79497546  | Other :  0.2050246
Real values 491...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79318607  | Other :  0.20681399
Real values 492...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.781921  | Other :  0.21807902
Real values 493...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82993937  | Other :  0.17006068
Real values 494...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7331926  | Other :  0.2668074
Real values 495...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967352  | Other :  0.20326477
Real values 496...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7829659  | Other :  0.2170341
Real values 497...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79336613  | Other :  0.2066339
Real values 498...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932055  | Other :  0.20679449
Real values 499...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932036  | Other :  0.20679641
Real values 500...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934593  | Other :  0.20654067
Real values 501...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.828067  | Other :  0.171933
Real values 502...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82926387  | Other :  0.17073612
Real values 503...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79331374  | Other :  0.20668623
Real values 504...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339856  | Other :  0.20660147
Real values 505...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933957  | Other :  0.20660439
Real values 506...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393756  | Other :  0.20606248
Real values 507...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76855433  | Other :  0.23144571
Real values 508...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793307  | Other :  0.20669296
Real values 509...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7651068  | Other :  0.23489329
Real values 510...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931552  | Other :  0.20684478
Real values 511...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79322404  | Other :  0.20677605
Real values 512...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79329574  | Other :  0.2067043
Real values 513...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939824  | Other :  0.20601758
Real values 514...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935111  | Other :  0.2064889
Real values 515...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932128  | Other :  0.20678735
Real values 516...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7839234  | Other :  0.21607666
Real values 517...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944605  | Other :  0.20553963
Real values 518...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7542176  | Other :  0.24578238
Real values 519...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79333586  | Other :  0.20666417
Real values 520...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79307574  | Other :  0.20692426
Real values 521...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931751  | Other :  0.2068249
Real values 522...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299197  | Other :  0.1700803
Real values 523...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348105  | Other :  0.20651895
Real values 524...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79336786  | Other :  0.20663218
Real values 525...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337597  | Other :  0.20662403
Real values 526...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934007  | Other :  0.2065993
Real values 527...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940971  | Other :  0.20590286
Real values 528...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393667  | Other :  0.20606336
Real values 529...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936987  | Other :  0.20630127
Real values 530...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337406  | Other :  0.20662592
Real values 531...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79340196  | Other :  0.20659809
Real values 532...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934715  | Other :  0.20652848
Real values 533...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339826  | Other :  0.20660174
Real values 534...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79446304  | Other :  0.205537
Real values 535...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79423374  | Other :  0.20576625
Real values 536...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8262579  | Other :  0.17374215
Real values 537...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934946  | Other :  0.2065054
Real values 538...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931694  | Other :  0.20683074
Real values 539...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349035  | Other :  0.20650971
Real values 540...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79373306  | Other :  0.20626698
Real values 541...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935585  | Other :  0.20644155
Real values 542...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299221  | Other :  0.1700779
Real values 543...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.829585  | Other :  0.17041498
Real values 544...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79018164  | Other :  0.20981836
Real values 545...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7929966  | Other :  0.20700347
Real values 546...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7663781  | Other :  0.23362193
Real values 547...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956514  | Other :  0.20434862
Real values 548...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934324  | Other :  0.20656759
Real values 549...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79740614  | Other :  0.2025939
Real values 550...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299048  | Other :  0.1700952
Real values 551...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78080076  | Other :  0.21919927
Real values 552...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933792  | Other :  0.2066208
Real values 553...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348105  | Other :  0.20651898
Real values 554...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349315  | Other :  0.20650685
Real values 555...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76172304  | Other :  0.238277
Real values 556...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79351556  | Other :  0.20648448
Real values 557...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79383105  | Other :  0.206169
Real values 558...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932434  | Other :  0.20675665
Real values 559...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940551  | Other :  0.20594494
Real values 560...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934293  | Other :  0.20657073
Real values 561...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970358  | Other :  0.20296419
Real values 562...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7855803  | Other :  0.21441978
Real values 563...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79323673  | Other :  0.20676327
Real values 564...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337925  | Other :  0.20662078
Real values 565...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79346013  | Other :  0.20653991
Real values 566...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79360694  | Other :  0.20639306
Real values 567...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79495156  | Other :  0.20504853
Real values 568...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79413575  | Other :  0.20586431
Real values 569...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79413295  | Other :  0.20586708
Real values 570...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79563546  | Other :  0.20436451
Real values 571...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932639  | Other :  0.20673607
Real values 572...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936666  | Other :  0.2063334
Real values 573...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935211  | Other :  0.20647883
Real values 574...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939238  | Other :  0.2060762
Real values 575...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939572  | Other :  0.20604286
Real values 576...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793271  | Other :  0.20672902
Real values 577...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349273  | Other :  0.20650731
Real values 578...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79488605  | Other :  0.205114
Real values 579...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79343176  | Other :  0.20656824
Real values 580...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79344845  | Other :  0.20655155
Real values 581...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79304314  | Other :  0.20695683
Real values 582...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82938087  | Other :  0.17061916
Real values 583...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79362816  | Other :  0.20637183
Real values 584...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935053  | Other :  0.20649473
Real values 585...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8296317  | Other :  0.17036836
Real values 586...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79450834  | Other :  0.20549177
Real values 587...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299227  | Other :  0.1700773
Real values 588...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8112363  | Other :  0.18876366
Real values 589...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933425  | Other :  0.20665757
Real values 590...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8296509  | Other :  0.17034912
Real values 591...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405427  | Other :  0.20594577
Real values 592...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938602  | Other :  0.20613983
Real values 593...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7957462  | Other :  0.20425388
Real values 594...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297572  | Other :  0.17024282
Real values 595...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943186  | Other :  0.20568141
Real values 596...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940931  | Other :  0.20590699
Real values 597...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79381955  | Other :  0.20618056
Real values 598...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944211  | Other :  0.20557897
Real values 599...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82977194  | Other :  0.17022806
Real values 600...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Ensemble_Test)*100))

Accuracy = 80.50%

image_to_predict_Ensemble_Test = path_to_tensor("/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Output_melanoma/ISIC_0000000_180_angle_flipped.jpg").astype('float32')/255.
ensemble_model.predict(image_to_predict_Ensemble_Test)

array([[0.7931409 , 0.20685914]], dtype=float32)

7.5.1 Compute Test Set Predictions

# Compute test set predictions
NUMBER_TEST_SAMPLES_Ensemble_Test = 600

all_weights_combined_as_list = weights_of_MobileNet_Inception_and_Xception

y_true_Ensemble_Test = test_targets[:NUMBER_TEST_SAMPLES_Ensemble_Test]
y_score_Ensemble_Test = []
for index in range(NUMBER_TEST_SAMPLES_Ensemble_Test): #compute one at a time due to memory constraints
    probs_Ensemble_Test = predict(img_path = test_files[index], model_architecture = ensemble_model, path_model_weight = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5")
    print("Real values {}...".format(index+1) + "Melanoma : ", test_targets[index][0], " | Other : ", test_targets[index][1])
    print("---------------------------------------------------------------------------")
    y_score_Ensemble_Test.append(probs_Ensemble_Test)
    
correct_Ensemble_Test = np.array(y_true_Ensemble_Test) == np.array(y_score_Ensemble_Test)

Streaming output truncated to the last 5000 lines.
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013414.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946235  | Other :  0.20537655
Real values 101...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013325.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942421  | Other :  0.2057579
Real values 102...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76050615  | Other :  0.23949385
Real values 103...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013321.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7908087  | Other :  0.20919132
Real values 104...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79335105  | Other :  0.20664898
Real values 105...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013374.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7714226  | Other :  0.22857738
Real values 106...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8122859  | Other :  0.1877141
Real values 107...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013465.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7842564  | Other :  0.21574366
Real values 108...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013678.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82117003  | Other :  0.17882994
Real values 109...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013696.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7993757  | Other :  0.20062433
Real values 110...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013511.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8295554  | Other :  0.17044467
Real values 111...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013615.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.75424147  | Other :  0.24575858
Real values 112...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952156  | Other :  0.2047844
Real values 113...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7921771  | Other :  0.20782289
Real values 114...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013529.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297748  | Other :  0.17022519
Real values 115...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013577.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79346156  | Other :  0.20653847
Real values 116...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79398465  | Other :  0.20601532
Real values 117...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013602.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.796272  | Other :  0.20372805
Real values 118...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013673.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934686  | Other :  0.20653145
Real values 119...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013512.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82971716  | Other :  0.17028284
Real values 120...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.80081296  | Other :  0.19918703
Real values 121...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013565.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79366493  | Other :  0.20633501
Real values 122...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013813.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82970345  | Other :  0.17029658
Real values 123...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013733.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79359424  | Other :  0.20640576
Real values 124...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934558  | Other :  0.20654425
Real values 125...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013764.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7884182  | Other :  0.21158187
Real values 126...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013767.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931811  | Other :  0.20681891
Real values 127...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013739.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.74737215  | Other :  0.25262782
Real values 128...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013794.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.75150096  | Other :  0.24849908
Real values 129...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013708.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79884696  | Other :  0.20115301
Real values 130...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7904147  | Other :  0.20958535
Real values 131...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013738.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.829765  | Other :  0.17023496
Real values 132...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7818512  | Other :  0.21814883
Real values 133...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013809.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794105  | Other :  0.20589499
Real values 134...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013842.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7919416  | Other :  0.20805845
Real values 135...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938804  | Other :  0.2061196
Real values 136...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013908.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79575765  | Other :  0.20424235
Real values 137...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013897.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941587  | Other :  0.20584124
Real values 138...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013911.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947595  | Other :  0.20524049
Real values 139...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932331  | Other :  0.20676689
Real values 140...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013917.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405665  | Other :  0.20594332
Real values 141...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79447293  | Other :  0.2055271
Real values 142...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939609  | Other :  0.2060391
Real values 143...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82963467  | Other :  0.17036533
Real values 144...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.797457  | Other :  0.20254302
Real values 145...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932675  | Other :  0.20673251
Real values 146...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013891.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79558945  | Other :  0.20441055
Real values 147...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82963395  | Other :  0.17036602
Real values 148...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0013925.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79326814  | Other :  0.20673186
Real values 149...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014103.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934345  | Other :  0.20656554
Real values 150...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8035139  | Other :  0.19648616
Real values 151...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014177.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78758943  | Other :  0.21241067
Real values 152...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014148.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950778  | Other :  0.20492224
Real values 153...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8166069  | Other :  0.18339317
Real values 154...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952621  | Other :  0.20473787
Real values 155...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014117.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79467046  | Other :  0.20532954
Real values 156...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014090.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79414845  | Other :  0.20585155
Real values 157...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014186.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936207  | Other :  0.20637934
Real values 158...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014110.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934456  | Other :  0.20655444
Real values 159...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014181.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934457  | Other :  0.20655434
Real values 160...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014077.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79326534  | Other :  0.2067347
Real values 161...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8295125  | Other :  0.17048757
Real values 162...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79330635  | Other :  0.2066937
Real values 163...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014336.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297523  | Other :  0.17024772
Real values 164...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014319.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405415  | Other :  0.2059459
Real values 165...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930326  | Other :  0.20696744
Real values 166...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933788  | Other :  0.20662127
Real values 167...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943346  | Other :  0.20566541
Real values 168...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014349.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79435414  | Other :  0.2056458
Real values 169...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942679  | Other :  0.20573208
Real values 170...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014221.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940301  | Other :  0.20597002
Real values 171...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014278.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79340833  | Other :  0.2065917
Real values 172...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014288.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79331154  | Other :  0.20668845
Real values 173...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014233.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938308  | Other :  0.20616925
Real values 174...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014219.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933483  | Other :  0.20665169
Real values 175...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014284.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937374  | Other :  0.20626251
Real values 176...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7838197  | Other :  0.21618032
Real values 177...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014423.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935466  | Other :  0.20645338
Real values 178...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014470.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7532419  | Other :  0.24675816
Real values 179...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014489.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8091402  | Other :  0.19085972
Real values 180...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014392.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7959393  | Other :  0.20406067
Real values 181...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014503.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79318714  | Other :  0.20681286
Real values 182...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014500.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938156  | Other :  0.20618437
Real values 183...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943441  | Other :  0.20565587
Real values 184...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014454.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.817415  | Other :  0.18258505
Real values 185...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014457.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934859  | Other :  0.20651412
Real values 186...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014434.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82920384  | Other :  0.17079616
Real values 187...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014474.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932409  | Other :  0.20675907
Real values 188...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014506.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79401076  | Other :  0.20598924
Real values 189...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014478.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943152  | Other :  0.20568483
Real values 190...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014409.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82966566  | Other :  0.17033432
Real values 191...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014567.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77977055  | Other :  0.22022939
Real values 192...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014574.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78214455  | Other :  0.21785545
Real values 193...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014541.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.81935966  | Other :  0.18064037
Real values 194...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014513.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947444  | Other :  0.20525567
Real values 195...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014600.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7988113  | Other :  0.20118873
Real values 196...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014586.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7962114  | Other :  0.20378856
Real values 197...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014587.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7779798  | Other :  0.22202021
Real values 198...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014542.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79642105  | Other :  0.203579
Real values 199...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014588.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7571665  | Other :  0.24283355
Real values 200...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936756  | Other :  0.20632446
Real values 201...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014619.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76598525  | Other :  0.23401475
Real values 202...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014575.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79602635  | Other :  0.20397371
Real values 203...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014546.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8202397  | Other :  0.17976026
Real values 204...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014548.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79208744  | Other :  0.20791261
Real values 205...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014590.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7658404  | Other :  0.23415962
Real values 206...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014634.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7893903  | Other :  0.21060967
Real values 207...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014644.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951991  | Other :  0.20480093
Real values 208...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014647.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7972905  | Other :  0.20270959
Real values 209...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014643.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78999114  | Other :  0.21000886
Real values 210...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014652.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79303634  | Other :  0.2069637
Real values 211...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014653.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794115  | Other :  0.20588505
Real values 212...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014629.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7922127  | Other :  0.20778725
Real values 213...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014648.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942172  | Other :  0.20578282
Real values 214...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014626.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7854566  | Other :  0.21454343
Real values 215...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8076401  | Other :  0.19235997
Real values 216...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014627.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956637  | Other :  0.20433637
Real values 217...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014649.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7984292  | Other :  0.20157084
Real values 218...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7757729  | Other :  0.22422716
Real values 219...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014675.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79747957  | Other :  0.20252052
Real values 220...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014666.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79522777  | Other :  0.20477223
Real values 221...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014663.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7962944  | Other :  0.2037056
Real values 222...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014687.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956588  | Other :  0.20434126
Real values 223...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014677.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7870342  | Other :  0.21296583
Real values 224...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014698.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936491  | Other :  0.20635095
Real values 225...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014703.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78212786  | Other :  0.21787219
Real values 226...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014697.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79466337  | Other :  0.20533666
Real values 227...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014695.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7817488  | Other :  0.21825123
Real values 228...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014693.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932389  | Other :  0.2067611
Real values 229...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014740.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393375  | Other :  0.2060663
Real values 230...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014725.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795545  | Other :  0.20445506
Real values 231...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014720.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944975  | Other :  0.20550254
Real values 232...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014729.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7816381  | Other :  0.21836194
Real values 233...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014743.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947404  | Other :  0.2052596
Real values 234...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014727.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935114  | Other :  0.20648867
Real values 235...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014728.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935111  | Other :  0.20648903
Real values 236...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014746.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944281  | Other :  0.20557192
Real values 237...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014749.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935981  | Other :  0.20640187
Real values 238...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014766.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953328  | Other :  0.20466726
Real values 239...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014768.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945839  | Other :  0.20541617
Real values 240...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014765.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967249  | Other :  0.20327513
Real values 241...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014753.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79410315  | Other :  0.20589688
Real values 242...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014755.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79378545  | Other :  0.20621464
Real values 243...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014790.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944827  | Other :  0.20551726
Real values 244...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014772.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79574203  | Other :  0.20425794
Real values 245...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014786.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79426086  | Other :  0.20573923
Real values 246...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014784.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79454535  | Other :  0.20545469
Real values 247...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014773.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79368323  | Other :  0.20631675
Real values 248...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014780.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79587543  | Other :  0.20412461
Real values 249...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014787.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79387  | Other :  0.20613003
Real values 250...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014814.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947744  | Other :  0.20522568
Real values 251...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014800.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7964783  | Other :  0.2035217
Real values 252...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014796.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941548  | Other :  0.20584527
Real values 253...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014798.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934116  | Other :  0.20658842
Real values 254...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014807.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79493856  | Other :  0.20506136
Real values 255...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014792.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936933  | Other :  0.20630674
Real values 256...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014826.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79308766  | Other :  0.20691234
Real values 257...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014815.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7875676  | Other :  0.21243235
Real values 258...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014835.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942846  | Other :  0.20571542
Real values 259...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014844.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79449975  | Other :  0.20550027
Real values 260...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014820.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956897  | Other :  0.20431034
Real values 261...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014833.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.789164  | Other :  0.21083602
Real values 262...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014822.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941426  | Other :  0.2058575
Real values 263...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014862.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7949287  | Other :  0.20507133
Real values 264...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014867.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7804546  | Other :  0.21954548
Real values 265...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014853.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936051  | Other :  0.20639491
Real values 266...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014868.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938654  | Other :  0.20613466
Real values 267...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014854.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339784  | Other :  0.20660216
Real values 268...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014863.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951409  | Other :  0.20485911
Real values 269...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014879.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79614806  | Other :  0.20385198
Real values 270...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014876.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79356307  | Other :  0.20643693
Real values 271...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014907.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79388714  | Other :  0.20611286
Real values 272...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014901.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941761  | Other :  0.20582394
Real values 273...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014883.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793044  | Other :  0.20695603
Real values 274...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014872.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7814399  | Other :  0.21856014
Real values 275...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014921.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946496  | Other :  0.20535037
Real values 276...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014928.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7667006  | Other :  0.23329942
Real values 277...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014932.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7906282  | Other :  0.20937178
Real values 278...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014927.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934238  | Other :  0.20657627
Real values 279...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014912.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794332  | Other :  0.20566797
Real values 280...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014910.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7942276  | Other :  0.2057724
Real values 281...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79297984  | Other :  0.20702025
Real values 282...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79707164  | Other :  0.20292842
Real values 283...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941567  | Other :  0.20584333
Real values 284...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79390085  | Other :  0.20609918
Real values 285...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78428835  | Other :  0.21571164
Real values 286...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7911601  | Other :  0.2088399
Real values 287...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79423493  | Other :  0.20576505
Real values 288...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793249  | Other :  0.20675103
Real values 289...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945336  | Other :  0.20546643
Real values 290...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932191  | Other :  0.20678088
Real values 291...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795144  | Other :  0.20485604
Real values 292...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936505  | Other :  0.20634955
Real values 293...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7802357  | Other :  0.21976434
Real values 294...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7948866  | Other :  0.2051134
Real values 295...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7810275  | Other :  0.21897253
Real values 296...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79522717  | Other :  0.20477287
Real values 297...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931323  | Other :  0.20686772
Real values 298...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79375124  | Other :  0.20624876
Real values 299...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933385  | Other :  0.20666158
Real values 300...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941682  | Other :  0.20583181
Real values 301...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79317874  | Other :  0.20682123
Real values 302...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935853  | Other :  0.20641473
Real values 303...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79392433  | Other :  0.20607567
Real values 304...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79481924  | Other :  0.20518081
Real values 305...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79022044  | Other :  0.20977962
Real values 306...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793409  | Other :  0.20659101
Real values 307...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014977.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958328  | Other :  0.20416719
Real values 308...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950212  | Other :  0.20497887
Real values 309...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794927  | Other :  0.20507306
Real values 310...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0014998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79394746  | Other :  0.20605253
Real values 311...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936053  | Other :  0.20639467
Real values 312...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946223  | Other :  0.2053777
Real values 313...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939347  | Other :  0.20606534
Real values 314...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79363006  | Other :  0.20636998
Real values 315...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955115  | Other :  0.20448849
Real values 316...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8269927  | Other :  0.1730073
Real values 317...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940022  | Other :  0.20599791
Real values 318...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79445285  | Other :  0.20554721
Real values 319...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8034641  | Other :  0.19653587
Real values 320...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015020.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79416776  | Other :  0.20583224
Real values 321...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78912055  | Other :  0.21087949
Real values 322...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952186  | Other :  0.20478146
Real values 323...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941952  | Other :  0.2058048
Real values 324...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79457474  | Other :  0.2054252
Real values 325...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79696274  | Other :  0.20303732
Real values 326...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931463  | Other :  0.20685375
Real values 327...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015021.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.80604595  | Other :  0.19395404
Real values 328...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937534  | Other :  0.2062466
Real values 329...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7881541  | Other :  0.21184587
Real values 330...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7663101  | Other :  0.23369001
Real values 331...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79549575  | Other :  0.20450422
Real values 332...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79420656  | Other :  0.20579349
Real values 333...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79569936  | Other :  0.20430064
Real values 334...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953614  | Other :  0.20463869
Real values 335...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79374546  | Other :  0.20625457
Real values 336...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955908  | Other :  0.20440921
Real values 337...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79524803  | Other :  0.20475194
Real values 338...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953965  | Other :  0.2046035
Real values 339...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8285195  | Other :  0.17148054
Real values 340...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015089.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931687  | Other :  0.20683128
Real values 341...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015078.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7845032  | Other :  0.21549678
Real values 342...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015102.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795058  | Other :  0.20494203
Real values 343...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7788918  | Other :  0.22110826
Real values 344...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015115.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947756  | Other :  0.20522444
Real values 345...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015118.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79379165  | Other :  0.2062084
Real values 346...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930727  | Other :  0.2069273
Real values 347...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015129.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78710115  | Other :  0.21289897
Real values 348...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015127.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7816312  | Other :  0.21836889
Real values 349...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015125.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933502  | Other :  0.20664981
Real values 350...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015130.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79302424  | Other :  0.2069758
Real values 351...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015132.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793898  | Other :  0.2061021
Real values 352...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015119.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7924123  | Other :  0.20758772
Real values 353...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015142.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79363793  | Other :  0.20636205
Real values 354...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015146.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79368466  | Other :  0.20631537
Real values 355...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015139.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7948556  | Other :  0.20514445
Real values 356...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015140.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937939  | Other :  0.20620608
Real values 357...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015136.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79438514  | Other :  0.2056149
Real values 358...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015133.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934507  | Other :  0.20654935
Real values 359...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015156.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7838382  | Other :  0.21616182
Real values 360...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015150.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941723  | Other :  0.20582774
Real values 361...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015160.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79850125  | Other :  0.20149873
Real values 362...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015157.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7953528  | Other :  0.20464723
Real values 363...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015149.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794157  | Other :  0.20584297
Real values 364...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015152.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79311466  | Other :  0.20688532
Real values 365...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015155.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79244536  | Other :  0.20755467
Real values 366...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015175.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7949053  | Other :  0.20509478
Real values 367...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015167.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939985  | Other :  0.20600149
Real values 368...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015163.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795525  | Other :  0.20447499
Real values 369...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015174.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7950814  | Other :  0.20491865
Real values 370...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015173.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79425466  | Other :  0.20574537
Real values 371...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015161.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7945368  | Other :  0.20546323
Real values 372...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015171.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.81901455  | Other :  0.18098548
Real values 373...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015176.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79429454  | Other :  0.20570546
Real values 374...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015185.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7900984  | Other :  0.20990157
Real values 375...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015193.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938697  | Other :  0.20613031
Real values 376...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015184.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7954709  | Other :  0.20452914
Real values 377...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015179.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7952074  | Other :  0.20479262
Real values 378...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015180.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8259684  | Other :  0.17403167
Real values 379...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015208.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941901  | Other :  0.20580992
Real values 380...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015212.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7965085  | Other :  0.20349154
Real values 381...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015206.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79568005  | Other :  0.20431992
Real values 382...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015203.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941961  | Other :  0.20580396
Real values 383...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015207.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943274  | Other :  0.20567262
Real values 384...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015201.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943103  | Other :  0.20568977
Real values 385...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015202.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7930114  | Other :  0.20698854
Real values 386...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015224.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79351014  | Other :  0.20648989
Real values 387...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015217.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78872025  | Other :  0.21127984
Real values 388...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015223.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7613653  | Other :  0.2386348
Real values 389...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015218.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967007  | Other :  0.20329928
Real values 390...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015226.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970519  | Other :  0.20294814
Real values 391...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015216.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944934  | Other :  0.20550661
Real values 392...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015215.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943234  | Other :  0.20567665
Real values 393...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015244.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958375  | Other :  0.20416252
Real values 394...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015229.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.795937  | Other :  0.204063
Real values 395...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015245.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.83000183  | Other :  0.16999814
Real values 396...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015232.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7965808  | Other :  0.20341915
Real values 397...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015237.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940438  | Other :  0.2059562
Real values 398...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015241.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935314  | Other :  0.20646863
Real values 399...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015254.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348314  | Other :  0.20651698
Real values 400...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015251.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947077  | Other :  0.20529228
Real values 401...Melanoma :  0.0  | Other :  1.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015255.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79545164  | Other :  0.20454834
Real values 402...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015250.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793636  | Other :  0.20636395
Real values 403...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015258.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935729  | Other :  0.20642713
Real values 404...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015264.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7963285  | Other :  0.20367154
Real values 405...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015283.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944557  | Other :  0.20554432
Real values 406...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015270.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78697  | Other :  0.21303003
Real values 407...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015274.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.80416095  | Other :  0.19583917
Real values 408...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015279.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7969741  | Other :  0.2030259
Real values 409...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015276.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7977532  | Other :  0.20224679
Real values 410...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015291.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79514694  | Other :  0.20485306
Real values 411...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015273.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7525853  | Other :  0.24741481
Real values 412...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015293.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76478994  | Other :  0.23521003
Real values 413...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015311.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79427576  | Other :  0.20572427
Real values 414...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015310.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78345585  | Other :  0.21654412
Real values 415...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015298.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955586  | Other :  0.20444143
Real values 416...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015309.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82114947  | Other :  0.17885059
Real values 417...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015312.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937803  | Other :  0.20621967
Real values 418...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015357.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7731613  | Other :  0.22683875
Real values 419...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015353.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79494995  | Other :  0.20505008
Real values 420...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015331.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7974073  | Other :  0.20259272
Real values 421...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015347.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79416674  | Other :  0.20583324
Real values 422...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015330.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79539204  | Other :  0.20460796
Real values 423...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015355.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936691  | Other :  0.20633094
Real values 424...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015369.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8078474  | Other :  0.19215266
Real values 425...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015368.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79251957  | Other :  0.20748049
Real values 426...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015383.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7959937  | Other :  0.2040064
Real values 427...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015386.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931198  | Other :  0.2068803
Real values 428...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015363.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77308625  | Other :  0.22691385
Real values 429...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015364.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935097  | Other :  0.20649025
Real values 430...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015360.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.792863  | Other :  0.20713703
Real values 431...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015403.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941704  | Other :  0.20582956
Real values 432...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015395.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933511  | Other :  0.20664889
Real values 433...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015412.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79311347  | Other :  0.2068865
Real values 434...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015411.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7616414  | Other :  0.23835866
Real values 435...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015390.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946279  | Other :  0.20537207
Real values 436...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015404.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946763  | Other :  0.20532373
Real values 437...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015416.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7860457  | Other :  0.21395437
Real values 438...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015419.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7837212  | Other :  0.21627879
Real values 439...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015436.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970831  | Other :  0.20291698
Real values 440...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015418.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935292  | Other :  0.20647079
Real values 441...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015440.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7955595  | Other :  0.20444047
Real values 442...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015417.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79734534  | Other :  0.20265464
Real values 443...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015447.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8300178  | Other :  0.16998222
Real values 444...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015481.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947943  | Other :  0.20520568
Real values 445...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015464.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79174507  | Other :  0.20825498
Real values 446...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015468.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76002026  | Other :  0.23997971
Real values 447...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015455.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79127944  | Other :  0.20872061
Real values 448...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015476.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79305077  | Other :  0.20694926
Real values 449...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015466.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79438066  | Other :  0.20561934
Real values 450...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015482.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7951614  | Other :  0.2048386
Real values 451...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015544.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79526365  | Other :  0.20473644
Real values 452...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015510.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7979859  | Other :  0.20201413
Real values 453...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015563.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78266084  | Other :  0.2173392
Real values 454...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015526.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79797244  | Other :  0.20202756
Real values 455...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015485.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79445875  | Other :  0.20554137
Real values 456...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015537.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79491127  | Other :  0.2050888
Real values 457...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015559.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938006  | Other :  0.2061994
Real values 458...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015603.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7835495  | Other :  0.21645056
Real values 459...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015568.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944576  | Other :  0.20554242
Real values 460...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015566.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937789  | Other :  0.20622104
Real values 461...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015614.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79350203  | Other :  0.20649801
Real values 462...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015593.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79317284  | Other :  0.20682716
Real values 463...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015582.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937233  | Other :  0.20627674
Real values 464...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015607.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941545  | Other :  0.20584558
Real values 465...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015636.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7917743  | Other :  0.20822579
Real values 466...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015625.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79495275  | Other :  0.20504731
Real values 467...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015617.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941887  | Other :  0.2058113
Real values 468...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015645.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7957759  | Other :  0.20422408
Real values 469...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015638.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7836046  | Other :  0.21639536
Real values 470...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015641.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79352283  | Other :  0.20647717
Real values 471...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015631.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7947418  | Other :  0.20525818
Real values 472...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015939.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937217  | Other :  0.20627831
Real values 473...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015938.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7937197  | Other :  0.20628029
Real values 474...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015936.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7958764  | Other :  0.20412356
Real values 475...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015941.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7978045  | Other :  0.20219561
Real values 476...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015947.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7941868  | Other :  0.20581327
Real values 477...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015944.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.829762  | Other :  0.170238
Real values 478...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015943.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7946646  | Other :  0.20533542
Real values 479...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015940.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.77594376  | Other :  0.22405624
Real values 480...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015945.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79417837  | Other :  0.20582174
Real values 481...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015937.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78348696  | Other :  0.21651308
Real values 482...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015942.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932881  | Other :  0.20671189
Real values 483...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015946.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79397887  | Other :  0.20602116
Real values 484...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015956.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.794296  | Other :  0.20570397
Real values 485...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015950.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79400015  | Other :  0.20599982
Real values 486...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015955.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933372  | Other :  0.20666282
Real values 487...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015949.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82615113  | Other :  0.17384887
Real values 488...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015951.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79441875  | Other :  0.20558125
Real values 489...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015954.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939123  | Other :  0.20608777
Real values 490...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015953.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79497546  | Other :  0.2050246
Real values 491...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015959.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79318607  | Other :  0.20681399
Real values 492...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015958.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.781921  | Other :  0.21807902
Real values 493...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015952.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82993937  | Other :  0.17006068
Real values 494...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015960.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7331926  | Other :  0.2668074
Real values 495...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015948.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7967352  | Other :  0.20326477
Real values 496...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015957.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7829659  | Other :  0.2170341
Real values 497...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015962.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79336613  | Other :  0.2066339
Real values 498...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015965.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932055  | Other :  0.20679449
Real values 499...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015961.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932036  | Other :  0.20679641
Real values 500...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015972.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934593  | Other :  0.20654067
Real values 501...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015963.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.828067  | Other :  0.171933
Real values 502...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015968.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82926387  | Other :  0.17073612
Real values 503...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015969.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79331374  | Other :  0.20668623
Real values 504...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015971.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339856  | Other :  0.20660147
Real values 505...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015973.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933957  | Other :  0.20660439
Real values 506...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015964.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393756  | Other :  0.20606248
Real values 507...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015966.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76855433  | Other :  0.23144571
Real values 508...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015967.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793307  | Other :  0.20669296
Real values 509...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015986.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7651068  | Other :  0.23489329
Real values 510...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015981.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931552  | Other :  0.20684478
Real values 511...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015982.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79322404  | Other :  0.20677605
Real values 512...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015980.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79329574  | Other :  0.2067043
Real values 513...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015974.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939824  | Other :  0.20601758
Real values 514...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015985.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935111  | Other :  0.2064889
Real values 515...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015976.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932128  | Other :  0.20678735
Real values 516...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015979.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7839234  | Other :  0.21607666
Real values 517...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015978.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944605  | Other :  0.20553963
Real values 518...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015987.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7542176  | Other :  0.24578238
Real values 519...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015975.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79333586  | Other :  0.20666417
Real values 520...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015984.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79307574  | Other :  0.20692426
Real values 521...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015983.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931751  | Other :  0.2068249
Real values 522...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015998.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299197  | Other :  0.1700803
Real values 523...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015988.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348105  | Other :  0.20651895
Real values 524...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015992.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79336786  | Other :  0.20663218
Real values 525...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015991.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337597  | Other :  0.20662403
Real values 526...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015993.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934007  | Other :  0.2065993
Real values 527...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015995.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940971  | Other :  0.20590286
Real values 528...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015990.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79393667  | Other :  0.20606336
Real values 529...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015997.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936987  | Other :  0.20630127
Real values 530...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015994.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337406  | Other :  0.20662592
Real values 531...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015989.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79340196  | Other :  0.20659809
Real values 532...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015996.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934715  | Other :  0.20652848
Real values 533...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016006.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79339826  | Other :  0.20660174
Real values 534...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016004.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79446304  | Other :  0.205537
Real values 535...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016002.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79423374  | Other :  0.20576625
Real values 536...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016003.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8262579  | Other :  0.17374215
Real values 537...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016011.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934946  | Other :  0.2065054
Real values 538...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016009.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7931694  | Other :  0.20683074
Real values 539...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016005.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349035  | Other :  0.20650971
Real values 540...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016008.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79373306  | Other :  0.20626698
Real values 541...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016000.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935585  | Other :  0.20644155
Real values 542...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0015999.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299221  | Other :  0.1700779
Real values 543...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016007.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.829585  | Other :  0.17041498
Real values 544...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016001.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79018164  | Other :  0.20981836
Real values 545...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016015.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7929966  | Other :  0.20700347
Real values 546...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016019.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7663781  | Other :  0.23362193
Real values 547...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016022.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7956514  | Other :  0.20434862
Real values 548...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016014.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934324  | Other :  0.20656759
Real values 549...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016012.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79740614  | Other :  0.2025939
Real values 550...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016016.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299048  | Other :  0.1700952
Real values 551...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016018.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.78080076  | Other :  0.21919927
Real values 552...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016024.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933792  | Other :  0.2066208
Real values 553...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016017.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79348105  | Other :  0.20651898
Real values 554...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016023.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349315  | Other :  0.20650685
Real values 555...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016013.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.76172304  | Other :  0.238277
Real values 556...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016030.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79351556  | Other :  0.20648448
Real values 557...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016033.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79383105  | Other :  0.206169
Real values 558...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016034.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932434  | Other :  0.20675665
Real values 559...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016025.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940551  | Other :  0.20594494
Real values 560...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016028.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7934293  | Other :  0.20657073
Real values 561...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016027.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7970358  | Other :  0.20296419
Real values 562...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016026.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7855803  | Other :  0.21441978
Real values 563...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016029.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79323673  | Other :  0.20676327
Real values 564...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016031.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79337925  | Other :  0.20662078
Real values 565...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016035.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79346013  | Other :  0.20653991
Real values 566...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016041.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79360694  | Other :  0.20639306
Real values 567...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016038.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79495156  | Other :  0.20504853
Real values 568...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016036.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79413575  | Other :  0.20586431
Real values 569...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016043.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79413295  | Other :  0.20586708
Real values 570...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016046.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79563546  | Other :  0.20436451
Real values 571...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016037.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7932639  | Other :  0.20673607
Real values 572...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016045.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7936666  | Other :  0.2063334
Real values 573...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016044.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935211  | Other :  0.20647883
Real values 574...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016040.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939238  | Other :  0.2060762
Real values 575...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016042.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7939572  | Other :  0.20604286
Real values 576...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016048.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.793271  | Other :  0.20672902
Real values 577...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016059.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79349273  | Other :  0.20650731
Real values 578...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016054.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79488605  | Other :  0.205114
Real values 579...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016057.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79343176  | Other :  0.20656824
Real values 580...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016052.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79344845  | Other :  0.20655155
Real values 581...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016055.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79304314  | Other :  0.20695683
Real values 582...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016058.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82938087  | Other :  0.17061916
Real values 583...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016051.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79362816  | Other :  0.20637183
Real values 584...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016049.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7935053  | Other :  0.20649473
Real values 585...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016053.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8296317  | Other :  0.17036836
Real values 586...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016050.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79450834  | Other :  0.20549177
Real values 587...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016056.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8299227  | Other :  0.1700773
Real values 588...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016070.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8112363  | Other :  0.18876366
Real values 589...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016063.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7933425  | Other :  0.20665757
Real values 590...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016065.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8296509  | Other :  0.17034912
Real values 591...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016062.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79405427  | Other :  0.20594577
Real values 592...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016069.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7938602  | Other :  0.20613983
Real values 593...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016072.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7957462  | Other :  0.20425388
Real values 594...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016064.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.8297572  | Other :  0.17024282
Real values 595...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016060.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7943186  | Other :  0.20568141
Real values 596...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016061.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7940931  | Other :  0.20590699
Real values 597...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016071.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.79381955  | Other :  0.20618056
Real values 598...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016068.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.7944211  | Other :  0.20557897
Real values 599...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------
Image Path: /content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0016066.jpg
Arhitecture Used:
<tensorflow.python.keras.engine.functional.Functional object at 0x7fb276a267d0>
Path for Model Weights: 
/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/Ensemble Model/ensemble_model.h5
Model Weights: 
None
Prediction... Melanoma :  0.82977194  | Other :  0.17022806
Real values 600...Melanoma :  1.0  | Other :  0.0
---------------------------------------------------------------------------

print("Accuracy = %2.2f%%" % (np.mean(correct_Ensemble_Test)*100))

Accuracy = 80.50%

7.5.2 Evaluating the Model

7.5.2.1 Re-ordering the Actual y for ROC

# Re-ordering the actual y (for ROC)
y_true_2_Ensemble_Test = []
for i in range(len(y_true_Ensemble_Test)):
    y_true_2_Ensemble_Test.append(y_true_Ensemble_Test[i][0])

7.5.2.2 Re-ordering the Predict y for ROC

# Re-ordering the predicte y (for ROC)
y_score_2_Ensemble_Test = []
for i in range(len(y_score_Ensemble_Test)):
    y_score_2_Ensemble_Test.append(y_score_Ensemble_Test[i][0])

7.5.2.3 Plotting the Re-ordered ROC

plot_roc(y_true_2_Ensemble_Test, y_score_2_Ensemble_Test)

7.5.2.4 Confusion Matrix

7.5.2.4.1 Defining the Confusion Matrix Function

def positive_negative_measurement(y_true, y_score):
    # Initialization
    TRUE_POSITIVE = 0
    FALSE_POSITIVE = 0
    TRUE_NEGATIVE = 0
    FALSE_NEGATIVE = 0
    
    # Calculating the model
    for i in range(len(y_score)):
        if y_true[i] == y_score[i] == 1:
            TRUE_POSITIVE += 1
        if (y_score[i] == 1) and (y_true[i] != y_score[i]):
            FALSE_POSITIVE += 1
        if y_true[i] == y_score[i] == 0:
            TRUE_NEGATIVE += 1
        if (y_score[i] == 0) and (y_true[i] != y_score[i]):
            FALSE_NEGATIVE += 1

    return(TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, FALSE_NEGATIVE)

TRUE_POSITIVE_Ensemble_Test, FALSE_POSITIVE_Ensemble_Test, TRUE_NEGATIVE_Ensemble_Test, FALSE_NEGATIVE_Ensemble_Test = positive_negative_measurement(y_true_2_Ensemble_Test, y_score_2_Ensemble_Test)
postives_negatives_Ensemble_Test = [[TRUE_POSITIVE_Ensemble_Test, FALSE_POSITIVE_Ensemble_Test], 
                                    [FALSE_NEGATIVE_Ensemble_Test, TRUE_NEGATIVE_Ensemble_Test]]

7.5.2.4.2 Obtaining the Labels

sns.set()
labels_Ensemble_Test =  np.array([['True positive: ' + str(TRUE_POSITIVE_Ensemble_Test),
                                    'False positive: ' + str(FALSE_POSITIVE_Ensemble_Test)],
                                    ['False negative: ' + str(FALSE_NEGATIVE_Ensemble_Test),
                                    'True negative: ' + str(TRUE_POSITIVE_Ensemble_Test)]])
plt.figure(figsize = (13, 10))
sns.heatmap(postives_negatives_Ensemble_Test, annot = labels_Ensemble_Test, linewidths = 0.1, fmt="", cmap = 'RdYlGn')

<matplotlib.axes._subplots.AxesSubplot at 0x7fb269306910>

7.5.2.4.3 Calculating Sensitivity/Recall/Hit Rate/True Positive Rate

# Sensitivity | Recall | hit rate | true positive rate (TPR)
sensitivity_Ensemble_Test = TRUE_POSITIVE_Ensemble_Test / (TRUE_POSITIVE_Ensemble_Test + FALSE_NEGATIVE_Ensemble_Test)
print("Sensitivity: ", sensitivity_Ensemble_Test)

Sensitivity:  1.0

7.5.2.4.4 Calculating Specificity/Selectivity/True Negative Rate

# Specificity | selectivity | true negative rate (TNR)
try:
    specifity_Ensemble_Test = TRUE_NEGATIVE_Ensemble_Test / (TRUE_NEGATIVE_Ensemble_Test + FALSE_NEGATIVE_Ensemble_Test)
    print("Specifity: ", specifity_Ensemble_Test)
except:
    print("No Specificity due to NO NEGATIVE results.")

No Specificity due to NO NEGATIVE results.

7.5.2.4.5 Calculating Precision/Positive Predictive Value

# Precision | positive predictive value (PPV)
predcision_Ensemble_Test = TRUE_POSITIVE_Ensemble_Test / (TRUE_POSITIVE_Ensemble_Test + FALSE_POSITIVE_Ensemble_Test)
print("Precision: ", predcision_Ensemble_Test)

Precision:  0.805

7.5.2.4.6 Negative Predictive Value

# Negative predictive value (NPV)
try:
    npv_Ensemble_Test = TRUE_NEGATIVE_Ensemble_Test / (TRUE_NEGATIVE_Ensemble_Test + FALSE_NEGATIVE_Ensemble_Test)
    print("Negative predictive value: ", npv_Ensemble_Test)
except:
    print("0 Negative Predictions")

0 Negative Predictions

7.5.2.4.7 Calculating Accuracy

# Accuracy 
accuracy_Ensemble_Test = (TRUE_POSITIVE_Ensemble_Test + TRUE_NEGATIVE_Ensemble_Test) / (TRUE_POSITIVE_Ensemble_Test + FALSE_POSITIVE_Ensemble_Test + TRUE_NEGATIVE_Ensemble_Test + FALSE_NEGATIVE_Ensemble_Test)
print("Accuracy: ", accuracy_Ensemble_Test)

Accuracy:  0.805

8. Localization

Working Flowchart:

8.1 Obtaining the Path for the MobileNet Architecture Models

# Importing the libraries
from keras.applications.mobilenet import preprocess_input
import scipy
import cv2

path_to_model_weight = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/Saved Models/weights.best.mobilenet.hdf5"

8.2 Sample Image Path

img_path = "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/ISIC-2017_Test_v2_Data/Data Image JPG/ISIC_0012240.jpg"

8.3 Defining the function for the Layer Weights for MobileNet

def getting_two_layer_weights(path_model_weight = path_to_model_weight):
    # The model

    # Imprting the model
    from keras.applications.mobilenet import MobileNet

    # Pre-build model
    base_model = MobileNet(include_top = False, weights = None, input_shape = (512, 512, 3))

    # Adding output layers
    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    output = Dense(units = 2, activation = 'softmax')(x)

    # Creating the whole model
    model = Model(base_model.input, output)
    #model.summary()

    # Compiling the model
    model.compile(optimizer = keras.optimizers.Adam(lr = 0.001), 
                  loss = 'categorical_crossentropy', 
                  metrics = ['accuracy'])
    
    # loading the weights
    model.load_weights(path_model_weight)
    
    # Getting the AMP layer weight
    all_amp_layer_weights = model.layers[-1].get_weights()[0]
    
    # Extracting the wanted output
    mobilenet_model = Model(inputs = model.input, outputs = (model.layers[-3].output, model.layers[-1].output))
    
    return mobilenet_model, all_amp_layer_weights

mobilenet_model, all_amp_layer_weights = getting_two_layer_weights(path_to_model_weight)

8.4 Defining Class Activation Map Function

def mobilenet_CAM(img_path, model, all_amp_layer_weights):
    # Getting filtered images from last convolutional layer + model prediction output
    last_conv_output, predictions = model.predict(path_to_tensor(img_path)) # last_conv_output.shape = (1, 16, 16, 1024)
    
    # Converting the dimension of last convolutional layer to 16 x 16 x 1024     
    last_conv_output = np.squeeze(last_conv_output)
    
    # Model's prediction
    predicted_class = np.argmax(predictions)
    
    # Bilinear upsampling (resize each image to size of original image)
    mat_for_mult = scipy.ndimage.zoom(last_conv_output, (32, 32, 1), order = 1)  # dim from (16, 16, 1024) to (512, 512, 1024)
    
    # Getting the AMP layer weights
    amp_layer_weights = all_amp_layer_weights[:, predicted_class] # dim: (1024,)    
    
    # CAM for object class that is predicted to be in the image
    final_output = np.dot(mat_for_mult, amp_layer_weights) # dim: 512 x 512

    # Return class activation map (CAM)
    return final_output, predicted_class

final_output, predicted_class = mobilenet_CAM(img_path, mobilenet_model, all_amp_layer_weights)

8.5 Plotting the Class Activation Function for MobileNet

def plot_CAM(img_path, ax, model, all_amp_layer_weights):
    # Loading the image / resizing to 512x512 / Converting BGR to RGB
    #im = cv2.resize(cv2.cvtColor(cv2.imread(img_path), cv2.COLOR_BGR2RGB), (512, 512))
    im = path_to_tensor(img_path).astype("float32")/255.
    
    # Plotting the image
    ax.imshow(im.squeeze(), vmin=0, vmax=255)
    
    # Getting the class activation map
    CAM, pred = mobilenet_CAM(img_path, model, all_amp_layer_weights)
    
    CAM = (CAM - CAM.min()) / (CAM.max() - CAM.min())
    
    # Plotting the class activation map
    ax.imshow(CAM, cmap = "jet", alpha = 0.5, interpolation='nearest', vmin=0, vmax=1)

8.6 Visualizing the Images

# Visualizing images with and without localization
# Canvas
fig, ax = plt.subplots(nrows=1, ncols=2, figsize = (10, 10))
# Image without localization
ax[0].imshow((path_to_tensor(img_path).astype('float32')/255).squeeze())
# Image with localization
CAM = plot_CAM(img_path, ax[1], mobilenet_model, all_amp_layer_weights)
plt.show()

# Getting the image tensor
image_to_predict = path_to_tensor(img_path).astype('float32')/255
print(image_to_predict)

[[[[0.08627451 0.07843138 0.09019608]
   [0.08627451 0.07843138 0.09019608]
   [0.08627451 0.08235294 0.07450981]
   ...
   [0.39215687 0.23137255 0.14509805]
   [0.36862746 0.20784314 0.12156863]
   [0.14901961 0.08235294 0.05490196]]

  [[0.08235294 0.07450981 0.08627451]
   [0.08627451 0.07843138 0.09019608]
   [0.09411765 0.09019608 0.08235294]
   ...
   [0.3764706  0.22745098 0.15294118]
   [0.37254903 0.22352941 0.13333334]
   [0.36862746 0.23921569 0.16470589]]

  [[0.08627451 0.08627451 0.09411765]
   [0.08627451 0.07843138 0.09019608]
   [0.08627451 0.07843138 0.08235294]
   ...
   [0.38431373 0.23529412 0.14509805]
   [0.3764706  0.22745098 0.15294118]
   [0.3882353  0.23921569 0.15686275]]

  ...

  [[0.07843138 0.07058824 0.08235294]
   [0.06666667 0.05882353 0.07058824]
   [0.06666667 0.06666667 0.06666667]
   ...
   [0.43529412 0.33333334 0.27450982]
   [0.4117647  0.29803923 0.24313726]
   [0.4862745  0.4        0.35686275]]

  [[0.07450981 0.06666667 0.07058824]
   [0.07058824 0.07058824 0.07058824]
   [0.06666667 0.06666667 0.06666667]
   ...
   [0.49019608 0.3882353  0.3372549 ]
   [0.45882353 0.35686275 0.29803923]
   [0.49019608 0.39607844 0.35686275]]

  [[0.07450981 0.07058824 0.05490196]
   [0.07843138 0.07058824 0.07450981]
   [0.07450981 0.07450981 0.08235294]
   ...
   [0.5294118  0.44313726 0.3882353 ]
   [0.49411765 0.40784314 0.3529412 ]
   [0.45882353 0.34901962 0.3019608 ]]]]

# Predicting the image
prediction = ensemble_model.predict(image_to_predict)
print(prediction)

[[0.78165424 0.21834576]]

prediction_final = "Melanoma: " + str(np.round(prediction[0][0]*100, decimals = 4)) + "%" + \
                   " | Other illness: " + str(np.round(prediction[0][1]*100, decimals = 4)) + "%"

# Canvas initialization
fig = plt.figure(figsize = (10, 10))

# First image
ax = fig.add_subplot(121)
ax.imshow(image_to_predict.squeeze())
ax.text(0.3, 1.6, prediction_final)

# Second image
ax = fig.add_subplot(122)
CAM = plot_CAM(img_path, ax, mobilenet_model, all_amp_layer_weights)

plt.show()

9. Saving the Complete Model for the Python Interface Application

Working Flowchart:

%cd "/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/FINAL SAVED OUTPUTS/"
ensemble_model.save('FINAL_FILE_for_Soft_Computing_Project_Skin_Cancer.h5')
h5_saved_ensemble_model = load_model('FINAL_FILE_for_Soft_Computing_Project_Skin_Cancer.h5')
h5_saved_ensemble_model.summary()

/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/FINAL SAVED OUTPUTS
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
Model: "ensemble"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_11 (InputLayer)           [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_490 (Conv2D)             (None, 255, 255, 32) 864         input_11[0][0]                   
__________________________________________________________________________________________________
batch_normalization_490 (BatchN (None, 255, 255, 32) 96          conv2d_490[0][0]                 
__________________________________________________________________________________________________
activation_470 (Activation)     (None, 255, 255, 32) 0           batch_normalization_490[0][0]    
__________________________________________________________________________________________________
conv2d_491 (Conv2D)             (None, 253, 253, 32) 9216        activation_470[0][0]             
__________________________________________________________________________________________________
batch_normalization_491 (BatchN (None, 253, 253, 32) 96          conv2d_491[0][0]                 
__________________________________________________________________________________________________
activation_471 (Activation)     (None, 253, 253, 32) 0           batch_normalization_491[0][0]    
__________________________________________________________________________________________________
conv2d_492 (Conv2D)             (None, 253, 253, 64) 18432       activation_471[0][0]             
__________________________________________________________________________________________________
batch_normalization_492 (BatchN (None, 253, 253, 64) 192         conv2d_492[0][0]                 
__________________________________________________________________________________________________
activation_472 (Activation)     (None, 253, 253, 64) 0           batch_normalization_492[0][0]    
__________________________________________________________________________________________________
max_pooling2d_20 (MaxPooling2D) (None, 126, 126, 64) 0           activation_472[0][0]             
__________________________________________________________________________________________________
conv2d_493 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_20[0][0]           
__________________________________________________________________________________________________
batch_normalization_493 (BatchN (None, 126, 126, 80) 240         conv2d_493[0][0]                 
__________________________________________________________________________________________________
activation_473 (Activation)     (None, 126, 126, 80) 0           batch_normalization_493[0][0]    
__________________________________________________________________________________________________
conv2d_494 (Conv2D)             (None, 124, 124, 192 138240      activation_473[0][0]             
__________________________________________________________________________________________________
batch_normalization_494 (BatchN (None, 124, 124, 192 576         conv2d_494[0][0]                 
__________________________________________________________________________________________________
activation_474 (Activation)     (None, 124, 124, 192 0           batch_normalization_494[0][0]    
__________________________________________________________________________________________________
max_pooling2d_21 (MaxPooling2D) (None, 61, 61, 192)  0           activation_474[0][0]             
__________________________________________________________________________________________________
conv2d_498 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
batch_normalization_498 (BatchN (None, 61, 61, 64)   192         conv2d_498[0][0]                 
__________________________________________________________________________________________________
activation_478 (Activation)     (None, 61, 61, 64)   0           batch_normalization_498[0][0]    
__________________________________________________________________________________________________
conv2d_496 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_499 (Conv2D)             (None, 61, 61, 96)   55296       activation_478[0][0]             
__________________________________________________________________________________________________
batch_normalization_496 (BatchN (None, 61, 61, 48)   144         conv2d_496[0][0]                 
__________________________________________________________________________________________________
batch_normalization_499 (BatchN (None, 61, 61, 96)   288         conv2d_499[0][0]                 
__________________________________________________________________________________________________
activation_476 (Activation)     (None, 61, 61, 48)   0           batch_normalization_496[0][0]    
__________________________________________________________________________________________________
activation_479 (Activation)     (None, 61, 61, 96)   0           batch_normalization_499[0][0]    
__________________________________________________________________________________________________
average_pooling2d_45 (AveragePo (None, 61, 61, 192)  0           max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_495 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_21[0][0]           
__________________________________________________________________________________________________
conv2d_497 (Conv2D)             (None, 61, 61, 64)   76800       activation_476[0][0]             
__________________________________________________________________________________________________
conv2d_500 (Conv2D)             (None, 61, 61, 96)   82944       activation_479[0][0]             
__________________________________________________________________________________________________
conv2d_501 (Conv2D)             (None, 61, 61, 32)   6144        average_pooling2d_45[0][0]       
__________________________________________________________________________________________________
batch_normalization_495 (BatchN (None, 61, 61, 64)   192         conv2d_495[0][0]                 
__________________________________________________________________________________________________
batch_normalization_497 (BatchN (None, 61, 61, 64)   192         conv2d_497[0][0]                 
__________________________________________________________________________________________________
batch_normalization_500 (BatchN (None, 61, 61, 96)   288         conv2d_500[0][0]                 
__________________________________________________________________________________________________
batch_normalization_501 (BatchN (None, 61, 61, 32)   96          conv2d_501[0][0]                 
__________________________________________________________________________________________________
activation_475 (Activation)     (None, 61, 61, 64)   0           batch_normalization_495[0][0]    
__________________________________________________________________________________________________
activation_477 (Activation)     (None, 61, 61, 64)   0           batch_normalization_497[0][0]    
__________________________________________________________________________________________________
activation_480 (Activation)     (None, 61, 61, 96)   0           batch_normalization_500[0][0]    
__________________________________________________________________________________________________
activation_481 (Activation)     (None, 61, 61, 32)   0           batch_normalization_501[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 61, 61, 256)  0           activation_475[0][0]             
                                                                 activation_477[0][0]             
                                                                 activation_480[0][0]             
                                                                 activation_481[0][0]             
__________________________________________________________________________________________________
conv2d_505 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_505 (BatchN (None, 61, 61, 64)   192         conv2d_505[0][0]                 
__________________________________________________________________________________________________
activation_485 (Activation)     (None, 61, 61, 64)   0           batch_normalization_505[0][0]    
__________________________________________________________________________________________________
conv2d_503 (Conv2D)             (None, 61, 61, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_506 (Conv2D)             (None, 61, 61, 96)   55296       activation_485[0][0]             
__________________________________________________________________________________________________
batch_normalization_503 (BatchN (None, 61, 61, 48)   144         conv2d_503[0][0]                 
__________________________________________________________________________________________________
batch_normalization_506 (BatchN (None, 61, 61, 96)   288         conv2d_506[0][0]                 
__________________________________________________________________________________________________
activation_483 (Activation)     (None, 61, 61, 48)   0           batch_normalization_503[0][0]    
__________________________________________________________________________________________________
activation_486 (Activation)     (None, 61, 61, 96)   0           batch_normalization_506[0][0]    
__________________________________________________________________________________________________
average_pooling2d_46 (AveragePo (None, 61, 61, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_502 (Conv2D)             (None, 61, 61, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_504 (Conv2D)             (None, 61, 61, 64)   76800       activation_483[0][0]             
__________________________________________________________________________________________________
conv2d_507 (Conv2D)             (None, 61, 61, 96)   82944       activation_486[0][0]             
__________________________________________________________________________________________________
conv2d_508 (Conv2D)             (None, 61, 61, 64)   16384       average_pooling2d_46[0][0]       
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 255, 255, 32) 864         input_11[0][0]                   
__________________________________________________________________________________________________
batch_normalization_502 (BatchN (None, 61, 61, 64)   192         conv2d_502[0][0]                 
__________________________________________________________________________________________________
batch_normalization_504 (BatchN (None, 61, 61, 64)   192         conv2d_504[0][0]                 
__________________________________________________________________________________________________
batch_normalization_507 (BatchN (None, 61, 61, 96)   288         conv2d_507[0][0]                 
__________________________________________________________________________________________________
batch_normalization_508 (BatchN (None, 61, 61, 64)   192         conv2d_508[0][0]                 
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 255, 255, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
activation_482 (Activation)     (None, 61, 61, 64)   0           batch_normalization_502[0][0]    
__________________________________________________________________________________________________
activation_484 (Activation)     (None, 61, 61, 64)   0           batch_normalization_504[0][0]    
__________________________________________________________________________________________________
activation_487 (Activation)     (None, 61, 61, 96)   0           batch_normalization_507[0][0]    
__________________________________________________________________________________________________
activation_488 (Activation)     (None, 61, 61, 64)   0           batch_normalization_508[0][0]    
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 255, 255, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 61, 61, 288)  0           activation_482[0][0]             
                                                                 activation_484[0][0]             
                                                                 activation_487[0][0]             
                                                                 activation_488[0][0]             
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 253, 253, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
conv2d_512 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 253, 253, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
batch_normalization_512 (BatchN (None, 61, 61, 64)   192         conv2d_512[0][0]                 
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 253, 253, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
activation_492 (Activation)     (None, 61, 61, 64)   0           batch_normalization_512[0][0]    
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 253, 253, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
conv2d_510 (Conv2D)             (None, 61, 61, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_513 (Conv2D)             (None, 61, 61, 96)   55296       activation_492[0][0]             
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
batch_normalization_510 (BatchN (None, 61, 61, 48)   144         conv2d_510[0][0]                 
__________________________________________________________________________________________________
batch_normalization_513 (BatchN (None, 61, 61, 96)   288         conv2d_513[0][0]                 
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 253, 253, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
activation_490 (Activation)     (None, 61, 61, 48)   0           batch_normalization_510[0][0]    
__________________________________________________________________________________________________
activation_493 (Activation)     (None, 61, 61, 96)   0           batch_normalization_513[0][0]    
__________________________________________________________________________________________________
average_pooling2d_47 (AveragePo (None, 61, 61, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 253, 253, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
conv2d_509 (Conv2D)             (None, 61, 61, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_511 (Conv2D)             (None, 61, 61, 64)   76800       activation_490[0][0]             
__________________________________________________________________________________________________
conv2d_514 (Conv2D)             (None, 61, 61, 96)   82944       activation_493[0][0]             
__________________________________________________________________________________________________
conv2d_515 (Conv2D)             (None, 61, 61, 64)   18432       average_pooling2d_47[0][0]       
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 253, 253, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_584 (Conv2D)             (None, 127, 127, 128 8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
batch_normalization_509 (BatchN (None, 61, 61, 64)   192         conv2d_509[0][0]                 
__________________________________________________________________________________________________
batch_normalization_511 (BatchN (None, 61, 61, 64)   192         conv2d_511[0][0]                 
__________________________________________________________________________________________________
batch_normalization_514 (BatchN (None, 61, 61, 96)   288         conv2d_514[0][0]                 
__________________________________________________________________________________________________
batch_normalization_515 (BatchN (None, 61, 61, 64)   192         conv2d_515[0][0]                 
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 127, 127, 128 0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_584 (BatchN (None, 127, 127, 128 512         conv2d_584[0][0]                 
__________________________________________________________________________________________________
activation_489 (Activation)     (None, 61, 61, 64)   0           batch_normalization_509[0][0]    
__________________________________________________________________________________________________
activation_491 (Activation)     (None, 61, 61, 64)   0           batch_normalization_511[0][0]    
__________________________________________________________________________________________________
activation_494 (Activation)     (None, 61, 61, 96)   0           batch_normalization_514[0][0]    
__________________________________________________________________________________________________
activation_495 (Activation)     (None, 61, 61, 64)   0           batch_normalization_515[0][0]    
__________________________________________________________________________________________________
add_60 (Add)                    (None, 127, 127, 128 0           block2_pool[0][0]                
                                                                 batch_normalization_584[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 61, 61, 288)  0           activation_489[0][0]             
                                                                 activation_491[0][0]             
                                                                 activation_494[0][0]             
                                                                 activation_495[0][0]             
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 127, 127, 128 0           add_60[0][0]                     
__________________________________________________________________________________________________
conv2d_517 (Conv2D)             (None, 61, 61, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 127, 127, 256 33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
batch_normalization_517 (BatchN (None, 61, 61, 64)   192         conv2d_517[0][0]                 
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
activation_497 (Activation)     (None, 61, 61, 64)   0           batch_normalization_517[0][0]    
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 127, 127, 256 0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv2d_518 (Conv2D)             (None, 61, 61, 96)   55296       activation_497[0][0]             
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 127, 127, 256 67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
batch_normalization_518 (BatchN (None, 61, 61, 96)   288         conv2d_518[0][0]                 
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 127, 127, 256 1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_585 (Conv2D)             (None, 64, 64, 256)  32768       add_60[0][0]                     
__________________________________________________________________________________________________
activation_498 (Activation)     (None, 61, 61, 96)   0           batch_normalization_518[0][0]    
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 64, 64, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_585 (BatchN (None, 64, 64, 256)  1024        conv2d_585[0][0]                 
__________________________________________________________________________________________________
conv2d_516 (Conv2D)             (None, 30, 30, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_519 (Conv2D)             (None, 30, 30, 96)   82944       activation_498[0][0]             
__________________________________________________________________________________________________
add_61 (Add)                    (None, 64, 64, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_585[0][0]    
__________________________________________________________________________________________________
batch_normalization_516 (BatchN (None, 30, 30, 384)  1152        conv2d_516[0][0]                 
__________________________________________________________________________________________________
batch_normalization_519 (BatchN (None, 30, 30, 96)   288         conv2d_519[0][0]                 
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 64, 64, 256)  0           add_61[0][0]                     
__________________________________________________________________________________________________
activation_496 (Activation)     (None, 30, 30, 384)  0           batch_normalization_516[0][0]    
__________________________________________________________________________________________________
activation_499 (Activation)     (None, 30, 30, 96)   0           batch_normalization_519[0][0]    
__________________________________________________________________________________________________
max_pooling2d_22 (MaxPooling2D) (None, 30, 30, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 64, 64, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 30, 30, 768)  0           activation_496[0][0]             
                                                                 activation_499[0][0]             
                                                                 max_pooling2d_22[0][0]           
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
conv2d_524 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 64, 64, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_524 (BatchN (None, 30, 30, 128)  384         conv2d_524[0][0]                 
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 64, 64, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
activation_504 (Activation)     (None, 30, 30, 128)  0           batch_normalization_524[0][0]    
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 64, 64, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_586 (Conv2D)             (None, 32, 32, 728)  186368      add_61[0][0]                     
__________________________________________________________________________________________________
conv2d_525 (Conv2D)             (None, 30, 30, 128)  114688      activation_504[0][0]             
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 32, 32, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_586 (BatchN (None, 32, 32, 728)  2912        conv2d_586[0][0]                 
__________________________________________________________________________________________________
batch_normalization_525 (BatchN (None, 30, 30, 128)  384         conv2d_525[0][0]                 
__________________________________________________________________________________________________
add_62 (Add)                    (None, 32, 32, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_586[0][0]    
__________________________________________________________________________________________________
activation_505 (Activation)     (None, 30, 30, 128)  0           batch_normalization_525[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 32, 32, 728)  0           add_62[0][0]                     
__________________________________________________________________________________________________
conv2d_521 (Conv2D)             (None, 30, 30, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_526 (Conv2D)             (None, 30, 30, 128)  114688      activation_505[0][0]             
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
batch_normalization_521 (BatchN (None, 30, 30, 128)  384         conv2d_521[0][0]                 
__________________________________________________________________________________________________
batch_normalization_526 (BatchN (None, 30, 30, 128)  384         conv2d_526[0][0]                 
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
activation_501 (Activation)     (None, 30, 30, 128)  0           batch_normalization_521[0][0]    
__________________________________________________________________________________________________
activation_506 (Activation)     (None, 30, 30, 128)  0           batch_normalization_526[0][0]    
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 32, 32, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv2d_522 (Conv2D)             (None, 30, 30, 128)  114688      activation_501[0][0]             
__________________________________________________________________________________________________
conv2d_527 (Conv2D)             (None, 30, 30, 128)  114688      activation_506[0][0]             
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
batch_normalization_522 (BatchN (None, 30, 30, 128)  384         conv2d_522[0][0]                 
__________________________________________________________________________________________________
batch_normalization_527 (BatchN (None, 30, 30, 128)  384         conv2d_527[0][0]                 
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
activation_502 (Activation)     (None, 30, 30, 128)  0           batch_normalization_522[0][0]    
__________________________________________________________________________________________________
activation_507 (Activation)     (None, 30, 30, 128)  0           batch_normalization_527[0][0]    
__________________________________________________________________________________________________
average_pooling2d_48 (AveragePo (None, 30, 30, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 32, 32, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
conv2d_520 (Conv2D)             (None, 30, 30, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_523 (Conv2D)             (None, 30, 30, 192)  172032      activation_502[0][0]             
__________________________________________________________________________________________________
conv2d_528 (Conv2D)             (None, 30, 30, 192)  172032      activation_507[0][0]             
__________________________________________________________________________________________________
conv2d_529 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_48[0][0]       
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
batch_normalization_520 (BatchN (None, 30, 30, 192)  576         conv2d_520[0][0]                 
__________________________________________________________________________________________________
batch_normalization_523 (BatchN (None, 30, 30, 192)  576         conv2d_523[0][0]                 
__________________________________________________________________________________________________
batch_normalization_528 (BatchN (None, 30, 30, 192)  576         conv2d_528[0][0]                 
__________________________________________________________________________________________________
batch_normalization_529 (BatchN (None, 30, 30, 192)  576         conv2d_529[0][0]                 
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
conv1 (Conv2D)                  (None, 256, 256, 32) 864         input_11[0][0]                   
__________________________________________________________________________________________________
activation_500 (Activation)     (None, 30, 30, 192)  0           batch_normalization_520[0][0]    
__________________________________________________________________________________________________
activation_503 (Activation)     (None, 30, 30, 192)  0           batch_normalization_523[0][0]    
__________________________________________________________________________________________________
activation_508 (Activation)     (None, 30, 30, 192)  0           batch_normalization_528[0][0]    
__________________________________________________________________________________________________
activation_509 (Activation)     (None, 30, 30, 192)  0           batch_normalization_529[0][0]    
__________________________________________________________________________________________________
add_63 (Add)                    (None, 32, 32, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_62[0][0]                     
__________________________________________________________________________________________________
conv1_bn (BatchNormalization)   (None, 256, 256, 32) 128         conv1[0][0]                      
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 30, 30, 768)  0           activation_500[0][0]             
                                                                 activation_503[0][0]             
                                                                 activation_508[0][0]             
                                                                 activation_509[0][0]             
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 32, 32, 728)  0           add_63[0][0]                     
__________________________________________________________________________________________________
conv1_relu (ReLU)               (None, 256, 256, 32) 0           conv1_bn[0][0]                   
__________________________________________________________________________________________________
conv2d_534 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
conv_dw_1 (DepthwiseConv2D)     (None, 256, 256, 32) 288         conv1_relu[0][0]                 
__________________________________________________________________________________________________
batch_normalization_534 (BatchN (None, 30, 30, 160)  480         conv2d_534[0][0]                 
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
conv_dw_1_bn (BatchNormalizatio (None, 256, 256, 32) 128         conv_dw_1[0][0]                  
__________________________________________________________________________________________________
activation_514 (Activation)     (None, 30, 30, 160)  0           batch_normalization_534[0][0]    
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 32, 32, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv_dw_1_relu (ReLU)           (None, 256, 256, 32) 0           conv_dw_1_bn[0][0]               
__________________________________________________________________________________________________
conv2d_535 (Conv2D)             (None, 30, 30, 160)  179200      activation_514[0][0]             
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
conv_pw_1 (Conv2D)              (None, 256, 256, 64) 2048        conv_dw_1_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_535 (BatchN (None, 30, 30, 160)  480         conv2d_535[0][0]                 
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
conv_pw_1_bn (BatchNormalizatio (None, 256, 256, 64) 256         conv_pw_1[0][0]                  
__________________________________________________________________________________________________
activation_515 (Activation)     (None, 30, 30, 160)  0           batch_normalization_535[0][0]    
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 32, 32, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
conv_pw_1_relu (ReLU)           (None, 256, 256, 64) 0           conv_pw_1_bn[0][0]               
__________________________________________________________________________________________________
conv2d_531 (Conv2D)             (None, 30, 30, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_536 (Conv2D)             (None, 30, 30, 160)  179200      activation_515[0][0]             
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
conv_pad_2 (ZeroPadding2D)      (None, 257, 257, 64) 0           conv_pw_1_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_531 (BatchN (None, 30, 30, 160)  480         conv2d_531[0][0]                 
__________________________________________________________________________________________________
batch_normalization_536 (BatchN (None, 30, 30, 160)  480         conv2d_536[0][0]                 
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
conv_dw_2 (DepthwiseConv2D)     (None, 128, 128, 64) 576         conv_pad_2[0][0]                 
__________________________________________________________________________________________________
activation_511 (Activation)     (None, 30, 30, 160)  0           batch_normalization_531[0][0]    
__________________________________________________________________________________________________
activation_516 (Activation)     (None, 30, 30, 160)  0           batch_normalization_536[0][0]    
__________________________________________________________________________________________________
add_64 (Add)                    (None, 32, 32, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_63[0][0]                     
__________________________________________________________________________________________________
conv_dw_2_bn (BatchNormalizatio (None, 128, 128, 64) 256         conv_dw_2[0][0]                  
__________________________________________________________________________________________________
conv2d_532 (Conv2D)             (None, 30, 30, 160)  179200      activation_511[0][0]             
__________________________________________________________________________________________________
conv2d_537 (Conv2D)             (None, 30, 30, 160)  179200      activation_516[0][0]             
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 32, 32, 728)  0           add_64[0][0]                     
__________________________________________________________________________________________________
conv_dw_2_relu (ReLU)           (None, 128, 128, 64) 0           conv_dw_2_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_532 (BatchN (None, 30, 30, 160)  480         conv2d_532[0][0]                 
__________________________________________________________________________________________________
batch_normalization_537 (BatchN (None, 30, 30, 160)  480         conv2d_537[0][0]                 
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
conv_pw_2 (Conv2D)              (None, 128, 128, 128 8192        conv_dw_2_relu[0][0]             
__________________________________________________________________________________________________
activation_512 (Activation)     (None, 30, 30, 160)  0           batch_normalization_532[0][0]    
__________________________________________________________________________________________________
activation_517 (Activation)     (None, 30, 30, 160)  0           batch_normalization_537[0][0]    
__________________________________________________________________________________________________
average_pooling2d_49 (AveragePo (None, 30, 30, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
conv_pw_2_bn (BatchNormalizatio (None, 128, 128, 128 512         conv_pw_2[0][0]                  
__________________________________________________________________________________________________
conv2d_530 (Conv2D)             (None, 30, 30, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_533 (Conv2D)             (None, 30, 30, 192)  215040      activation_512[0][0]             
__________________________________________________________________________________________________
conv2d_538 (Conv2D)             (None, 30, 30, 192)  215040      activation_517[0][0]             
__________________________________________________________________________________________________
conv2d_539 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_49[0][0]       
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 32, 32, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv_pw_2_relu (ReLU)           (None, 128, 128, 128 0           conv_pw_2_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_530 (BatchN (None, 30, 30, 192)  576         conv2d_530[0][0]                 
__________________________________________________________________________________________________
batch_normalization_533 (BatchN (None, 30, 30, 192)  576         conv2d_533[0][0]                 
__________________________________________________________________________________________________
batch_normalization_538 (BatchN (None, 30, 30, 192)  576         conv2d_538[0][0]                 
__________________________________________________________________________________________________
batch_normalization_539 (BatchN (None, 30, 30, 192)  576         conv2d_539[0][0]                 
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
conv_dw_3 (DepthwiseConv2D)     (None, 128, 128, 128 1152        conv_pw_2_relu[0][0]             
__________________________________________________________________________________________________
activation_510 (Activation)     (None, 30, 30, 192)  0           batch_normalization_530[0][0]    
__________________________________________________________________________________________________
activation_513 (Activation)     (None, 30, 30, 192)  0           batch_normalization_533[0][0]    
__________________________________________________________________________________________________
activation_518 (Activation)     (None, 30, 30, 192)  0           batch_normalization_538[0][0]    
__________________________________________________________________________________________________
activation_519 (Activation)     (None, 30, 30, 192)  0           batch_normalization_539[0][0]    
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
conv_dw_3_bn (BatchNormalizatio (None, 128, 128, 128 512         conv_dw_3[0][0]                  
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 30, 30, 768)  0           activation_510[0][0]             
                                                                 activation_513[0][0]             
                                                                 activation_518[0][0]             
                                                                 activation_519[0][0]             
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 32, 32, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
conv_dw_3_relu (ReLU)           (None, 128, 128, 128 0           conv_dw_3_bn[0][0]               
__________________________________________________________________________________________________
conv2d_544 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
conv_pw_3 (Conv2D)              (None, 128, 128, 128 16384       conv_dw_3_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_544 (BatchN (None, 30, 30, 160)  480         conv2d_544[0][0]                 
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
conv_pw_3_bn (BatchNormalizatio (None, 128, 128, 128 512         conv_pw_3[0][0]                  
__________________________________________________________________________________________________
activation_524 (Activation)     (None, 30, 30, 160)  0           batch_normalization_544[0][0]    
__________________________________________________________________________________________________
add_65 (Add)                    (None, 32, 32, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_64[0][0]                     
__________________________________________________________________________________________________
conv_pw_3_relu (ReLU)           (None, 128, 128, 128 0           conv_pw_3_bn[0][0]               
__________________________________________________________________________________________________
conv2d_545 (Conv2D)             (None, 30, 30, 160)  179200      activation_524[0][0]             
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 32, 32, 728)  0           add_65[0][0]                     
__________________________________________________________________________________________________
conv_pad_4 (ZeroPadding2D)      (None, 129, 129, 128 0           conv_pw_3_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_545 (BatchN (None, 30, 30, 160)  480         conv2d_545[0][0]                 
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
conv_dw_4 (DepthwiseConv2D)     (None, 64, 64, 128)  1152        conv_pad_4[0][0]                 
__________________________________________________________________________________________________
activation_525 (Activation)     (None, 30, 30, 160)  0           batch_normalization_545[0][0]    
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
conv_dw_4_bn (BatchNormalizatio (None, 64, 64, 128)  512         conv_dw_4[0][0]                  
__________________________________________________________________________________________________
conv2d_541 (Conv2D)             (None, 30, 30, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_546 (Conv2D)             (None, 30, 30, 160)  179200      activation_525[0][0]             
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 32, 32, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv_dw_4_relu (ReLU)           (None, 64, 64, 128)  0           conv_dw_4_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_541 (BatchN (None, 30, 30, 160)  480         conv2d_541[0][0]                 
__________________________________________________________________________________________________
batch_normalization_546 (BatchN (None, 30, 30, 160)  480         conv2d_546[0][0]                 
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
conv_pw_4 (Conv2D)              (None, 64, 64, 256)  32768       conv_dw_4_relu[0][0]             
__________________________________________________________________________________________________
activation_521 (Activation)     (None, 30, 30, 160)  0           batch_normalization_541[0][0]    
__________________________________________________________________________________________________
activation_526 (Activation)     (None, 30, 30, 160)  0           batch_normalization_546[0][0]    
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
conv_pw_4_bn (BatchNormalizatio (None, 64, 64, 256)  1024        conv_pw_4[0][0]                  
__________________________________________________________________________________________________
conv2d_542 (Conv2D)             (None, 30, 30, 160)  179200      activation_521[0][0]             
__________________________________________________________________________________________________
conv2d_547 (Conv2D)             (None, 30, 30, 160)  179200      activation_526[0][0]             
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 32, 32, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
conv_pw_4_relu (ReLU)           (None, 64, 64, 256)  0           conv_pw_4_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_542 (BatchN (None, 30, 30, 160)  480         conv2d_542[0][0]                 
__________________________________________________________________________________________________
batch_normalization_547 (BatchN (None, 30, 30, 160)  480         conv2d_547[0][0]                 
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
conv_dw_5 (DepthwiseConv2D)     (None, 64, 64, 256)  2304        conv_pw_4_relu[0][0]             
__________________________________________________________________________________________________
activation_522 (Activation)     (None, 30, 30, 160)  0           batch_normalization_542[0][0]    
__________________________________________________________________________________________________
activation_527 (Activation)     (None, 30, 30, 160)  0           batch_normalization_547[0][0]    
__________________________________________________________________________________________________
average_pooling2d_50 (AveragePo (None, 30, 30, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
conv_dw_5_bn (BatchNormalizatio (None, 64, 64, 256)  1024        conv_dw_5[0][0]                  
__________________________________________________________________________________________________
conv2d_540 (Conv2D)             (None, 30, 30, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_543 (Conv2D)             (None, 30, 30, 192)  215040      activation_522[0][0]             
__________________________________________________________________________________________________
conv2d_548 (Conv2D)             (None, 30, 30, 192)  215040      activation_527[0][0]             
__________________________________________________________________________________________________
conv2d_549 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_50[0][0]       
__________________________________________________________________________________________________
add_66 (Add)                    (None, 32, 32, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_65[0][0]                     
__________________________________________________________________________________________________
conv_dw_5_relu (ReLU)           (None, 64, 64, 256)  0           conv_dw_5_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_540 (BatchN (None, 30, 30, 192)  576         conv2d_540[0][0]                 
__________________________________________________________________________________________________
batch_normalization_543 (BatchN (None, 30, 30, 192)  576         conv2d_543[0][0]                 
__________________________________________________________________________________________________
batch_normalization_548 (BatchN (None, 30, 30, 192)  576         conv2d_548[0][0]                 
__________________________________________________________________________________________________
batch_normalization_549 (BatchN (None, 30, 30, 192)  576         conv2d_549[0][0]                 
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 32, 32, 728)  0           add_66[0][0]                     
__________________________________________________________________________________________________
conv_pw_5 (Conv2D)              (None, 64, 64, 256)  65536       conv_dw_5_relu[0][0]             
__________________________________________________________________________________________________
activation_520 (Activation)     (None, 30, 30, 192)  0           batch_normalization_540[0][0]    
__________________________________________________________________________________________________
activation_523 (Activation)     (None, 30, 30, 192)  0           batch_normalization_543[0][0]    
__________________________________________________________________________________________________
activation_528 (Activation)     (None, 30, 30, 192)  0           batch_normalization_548[0][0]    
__________________________________________________________________________________________________
activation_529 (Activation)     (None, 30, 30, 192)  0           batch_normalization_549[0][0]    
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
conv_pw_5_bn (BatchNormalizatio (None, 64, 64, 256)  1024        conv_pw_5[0][0]                  
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 30, 30, 768)  0           activation_520[0][0]             
                                                                 activation_523[0][0]             
                                                                 activation_528[0][0]             
                                                                 activation_529[0][0]             
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
conv_pw_5_relu (ReLU)           (None, 64, 64, 256)  0           conv_pw_5_bn[0][0]               
__________________________________________________________________________________________________
conv2d_554 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 32, 32, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
conv_pad_6 (ZeroPadding2D)      (None, 65, 65, 256)  0           conv_pw_5_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_554 (BatchN (None, 30, 30, 192)  576         conv2d_554[0][0]                 
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
conv_dw_6 (DepthwiseConv2D)     (None, 32, 32, 256)  2304        conv_pad_6[0][0]                 
__________________________________________________________________________________________________
activation_534 (Activation)     (None, 30, 30, 192)  0           batch_normalization_554[0][0]    
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
conv_dw_6_bn (BatchNormalizatio (None, 32, 32, 256)  1024        conv_dw_6[0][0]                  
__________________________________________________________________________________________________
conv2d_555 (Conv2D)             (None, 30, 30, 192)  258048      activation_534[0][0]             
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 32, 32, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
conv_dw_6_relu (ReLU)           (None, 32, 32, 256)  0           conv_dw_6_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_555 (BatchN (None, 30, 30, 192)  576         conv2d_555[0][0]                 
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 32, 32, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
conv_pw_6 (Conv2D)              (None, 32, 32, 512)  131072      conv_dw_6_relu[0][0]             
__________________________________________________________________________________________________
activation_535 (Activation)     (None, 30, 30, 192)  0           batch_normalization_555[0][0]    
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 32, 32, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
conv_pw_6_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_pw_6[0][0]                  
__________________________________________________________________________________________________
conv2d_551 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_556 (Conv2D)             (None, 30, 30, 192)  258048      activation_535[0][0]             
__________________________________________________________________________________________________
add_67 (Add)                    (None, 32, 32, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_66[0][0]                     
__________________________________________________________________________________________________
conv_pw_6_relu (ReLU)           (None, 32, 32, 512)  0           conv_pw_6_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_551 (BatchN (None, 30, 30, 192)  576         conv2d_551[0][0]                 
__________________________________________________________________________________________________
batch_normalization_556 (BatchN (None, 30, 30, 192)  576         conv2d_556[0][0]                 
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_67[0][0]                     
__________________________________________________________________________________________________
conv_dw_7 (DepthwiseConv2D)     (None, 32, 32, 512)  4608        conv_pw_6_relu[0][0]             
__________________________________________________________________________________________________
activation_531 (Activation)     (None, 30, 30, 192)  0           batch_normalization_551[0][0]    
__________________________________________________________________________________________________
activation_536 (Activation)     (None, 30, 30, 192)  0           batch_normalization_556[0][0]    
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
conv_dw_7_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_dw_7[0][0]                  
__________________________________________________________________________________________________
conv2d_552 (Conv2D)             (None, 30, 30, 192)  258048      activation_531[0][0]             
__________________________________________________________________________________________________
conv2d_557 (Conv2D)             (None, 30, 30, 192)  258048      activation_536[0][0]             
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
conv_dw_7_relu (ReLU)           (None, 32, 32, 512)  0           conv_dw_7_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_552 (BatchN (None, 30, 30, 192)  576         conv2d_552[0][0]                 
__________________________________________________________________________________________________
batch_normalization_557 (BatchN (None, 30, 30, 192)  576         conv2d_557[0][0]                 
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 32, 32, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
conv_pw_7 (Conv2D)              (None, 32, 32, 512)  262144      conv_dw_7_relu[0][0]             
__________________________________________________________________________________________________
activation_532 (Activation)     (None, 30, 30, 192)  0           batch_normalization_552[0][0]    
__________________________________________________________________________________________________
activation_537 (Activation)     (None, 30, 30, 192)  0           batch_normalization_557[0][0]    
__________________________________________________________________________________________________
average_pooling2d_51 (AveragePo (None, 30, 30, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
conv_pw_7_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_pw_7[0][0]                  
__________________________________________________________________________________________________
conv2d_550 (Conv2D)             (None, 30, 30, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_553 (Conv2D)             (None, 30, 30, 192)  258048      activation_532[0][0]             
__________________________________________________________________________________________________
conv2d_558 (Conv2D)             (None, 30, 30, 192)  258048      activation_537[0][0]             
__________________________________________________________________________________________________
conv2d_559 (Conv2D)             (None, 30, 30, 192)  147456      average_pooling2d_51[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
conv_pw_7_relu (ReLU)           (None, 32, 32, 512)  0           conv_pw_7_bn[0][0]               
__________________________________________________________________________________________________
batch_normalization_550 (BatchN (None, 30, 30, 192)  576         conv2d_550[0][0]                 
__________________________________________________________________________________________________
batch_normalization_553 (BatchN (None, 30, 30, 192)  576         conv2d_553[0][0]                 
__________________________________________________________________________________________________
batch_normalization_558 (BatchN (None, 30, 30, 192)  576         conv2d_558[0][0]                 
__________________________________________________________________________________________________
batch_normalization_559 (BatchN (None, 30, 30, 192)  576         conv2d_559[0][0]                 
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 32, 32, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
conv_dw_8 (DepthwiseConv2D)     (None, 32, 32, 512)  4608        conv_pw_7_relu[0][0]             
__________________________________________________________________________________________________
activation_530 (Activation)     (None, 30, 30, 192)  0           batch_normalization_550[0][0]    
__________________________________________________________________________________________________
activation_533 (Activation)     (None, 30, 30, 192)  0           batch_normalization_553[0][0]    
__________________________________________________________________________________________________
activation_538 (Activation)     (None, 30, 30, 192)  0           batch_normalization_558[0][0]    
__________________________________________________________________________________________________
activation_539 (Activation)     (None, 30, 30, 192)  0           batch_normalization_559[0][0]    
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
conv_dw_8_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_dw_8[0][0]                  
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 30, 30, 768)  0           activation_530[0][0]             
                                                                 activation_533[0][0]             
                                                                 activation_538[0][0]             
                                                                 activation_539[0][0]             
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
conv_dw_8_relu (ReLU)           (None, 32, 32, 512)  0           conv_dw_8_bn[0][0]               
__________________________________________________________________________________________________
conv2d_562 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
add_68 (Add)                    (None, 32, 32, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_67[0][0]                     
__________________________________________________________________________________________________
conv_pw_8 (Conv2D)              (None, 32, 32, 512)  262144      conv_dw_8_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_562 (BatchN (None, 30, 30, 192)  576         conv2d_562[0][0]                 
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_68[0][0]                     
__________________________________________________________________________________________________
conv_pw_8_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_pw_8[0][0]                  
__________________________________________________________________________________________________
activation_542 (Activation)     (None, 30, 30, 192)  0           batch_normalization_562[0][0]    
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
conv_pw_8_relu (ReLU)           (None, 32, 32, 512)  0           conv_pw_8_bn[0][0]               
__________________________________________________________________________________________________
conv2d_563 (Conv2D)             (None, 30, 30, 192)  258048      activation_542[0][0]             
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
conv_dw_9 (DepthwiseConv2D)     (None, 32, 32, 512)  4608        conv_pw_8_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_563 (BatchN (None, 30, 30, 192)  576         conv2d_563[0][0]                 
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 32, 32, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
conv_dw_9_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_dw_9[0][0]                  
__________________________________________________________________________________________________
activation_543 (Activation)     (None, 30, 30, 192)  0           batch_normalization_563[0][0]    
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
conv_dw_9_relu (ReLU)           (None, 32, 32, 512)  0           conv_dw_9_bn[0][0]               
__________________________________________________________________________________________________
conv2d_560 (Conv2D)             (None, 30, 30, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_564 (Conv2D)             (None, 30, 30, 192)  258048      activation_543[0][0]             
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
conv_pw_9 (Conv2D)              (None, 32, 32, 512)  262144      conv_dw_9_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_560 (BatchN (None, 30, 30, 192)  576         conv2d_560[0][0]                 
__________________________________________________________________________________________________
batch_normalization_564 (BatchN (None, 30, 30, 192)  576         conv2d_564[0][0]                 
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 32, 32, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
conv_pw_9_bn (BatchNormalizatio (None, 32, 32, 512)  2048        conv_pw_9[0][0]                  
__________________________________________________________________________________________________
activation_540 (Activation)     (None, 30, 30, 192)  0           batch_normalization_560[0][0]    
__________________________________________________________________________________________________
activation_544 (Activation)     (None, 30, 30, 192)  0           batch_normalization_564[0][0]    
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
conv_pw_9_relu (ReLU)           (None, 32, 32, 512)  0           conv_pw_9_bn[0][0]               
__________________________________________________________________________________________________
conv2d_561 (Conv2D)             (None, 14, 14, 320)  552960      activation_540[0][0]             
__________________________________________________________________________________________________
conv2d_565 (Conv2D)             (None, 14, 14, 192)  331776      activation_544[0][0]             
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
conv_dw_10 (DepthwiseConv2D)    (None, 32, 32, 512)  4608        conv_pw_9_relu[0][0]             
__________________________________________________________________________________________________
batch_normalization_561 (BatchN (None, 14, 14, 320)  960         conv2d_561[0][0]                 
__________________________________________________________________________________________________
batch_normalization_565 (BatchN (None, 14, 14, 192)  576         conv2d_565[0][0]                 
__________________________________________________________________________________________________
add_69 (Add)                    (None, 32, 32, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_68[0][0]                     
__________________________________________________________________________________________________
conv_dw_10_bn (BatchNormalizati (None, 32, 32, 512)  2048        conv_dw_10[0][0]                 
__________________________________________________________________________________________________
activation_541 (Activation)     (None, 14, 14, 320)  0           batch_normalization_561[0][0]    
__________________________________________________________________________________________________
activation_545 (Activation)     (None, 14, 14, 192)  0           batch_normalization_565[0][0]    
__________________________________________________________________________________________________
max_pooling2d_23 (MaxPooling2D) (None, 14, 14, 768)  0           mixed7[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_69[0][0]                     
__________________________________________________________________________________________________
conv_dw_10_relu (ReLU)          (None, 32, 32, 512)  0           conv_dw_10_bn[0][0]              
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 14, 14, 1280) 0           activation_541[0][0]             
                                                                 activation_545[0][0]             
                                                                 max_pooling2d_23[0][0]           
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
conv_pw_10 (Conv2D)             (None, 32, 32, 512)  262144      conv_dw_10_relu[0][0]            
__________________________________________________________________________________________________
conv2d_570 (Conv2D)             (None, 14, 14, 448)  573440      mixed8[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
conv_pw_10_bn (BatchNormalizati (None, 32, 32, 512)  2048        conv_pw_10[0][0]                 
__________________________________________________________________________________________________
batch_normalization_570 (BatchN (None, 14, 14, 448)  1344        conv2d_570[0][0]                 
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 32, 32, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
conv_pw_10_relu (ReLU)          (None, 32, 32, 512)  0           conv_pw_10_bn[0][0]              
__________________________________________________________________________________________________
activation_550 (Activation)     (None, 14, 14, 448)  0           batch_normalization_570[0][0]    
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
conv_dw_11 (DepthwiseConv2D)    (None, 32, 32, 512)  4608        conv_pw_10_relu[0][0]            
__________________________________________________________________________________________________
conv2d_567 (Conv2D)             (None, 14, 14, 384)  491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_571 (Conv2D)             (None, 14, 14, 384)  1548288     activation_550[0][0]             
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
conv_dw_11_bn (BatchNormalizati (None, 32, 32, 512)  2048        conv_dw_11[0][0]                 
__________________________________________________________________________________________________
batch_normalization_567 (BatchN (None, 14, 14, 384)  1152        conv2d_567[0][0]                 
__________________________________________________________________________________________________
batch_normalization_571 (BatchN (None, 14, 14, 384)  1152        conv2d_571[0][0]                 
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 32, 32, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
conv_dw_11_relu (ReLU)          (None, 32, 32, 512)  0           conv_dw_11_bn[0][0]              
__________________________________________________________________________________________________
activation_547 (Activation)     (None, 14, 14, 384)  0           batch_normalization_567[0][0]    
__________________________________________________________________________________________________
activation_551 (Activation)     (None, 14, 14, 384)  0           batch_normalization_571[0][0]    
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 32, 32, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
conv_pw_11 (Conv2D)             (None, 32, 32, 512)  262144      conv_dw_11_relu[0][0]            
__________________________________________________________________________________________________
conv2d_568 (Conv2D)             (None, 14, 14, 384)  442368      activation_547[0][0]             
__________________________________________________________________________________________________
conv2d_569 (Conv2D)             (None, 14, 14, 384)  442368      activation_547[0][0]             
__________________________________________________________________________________________________
conv2d_572 (Conv2D)             (None, 14, 14, 384)  442368      activation_551[0][0]             
__________________________________________________________________________________________________
conv2d_573 (Conv2D)             (None, 14, 14, 384)  442368      activation_551[0][0]             
__________________________________________________________________________________________________
average_pooling2d_52 (AveragePo (None, 14, 14, 1280) 0           mixed8[0][0]                     
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 32, 32, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
conv_pw_11_bn (BatchNormalizati (None, 32, 32, 512)  2048        conv_pw_11[0][0]                 
__________________________________________________________________________________________________
conv2d_566 (Conv2D)             (None, 14, 14, 320)  409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_568 (BatchN (None, 14, 14, 384)  1152        conv2d_568[0][0]                 
__________________________________________________________________________________________________
batch_normalization_569 (BatchN (None, 14, 14, 384)  1152        conv2d_569[0][0]                 
__________________________________________________________________________________________________
batch_normalization_572 (BatchN (None, 14, 14, 384)  1152        conv2d_572[0][0]                 
__________________________________________________________________________________________________
batch_normalization_573 (BatchN (None, 14, 14, 384)  1152        conv2d_573[0][0]                 
__________________________________________________________________________________________________
conv2d_574 (Conv2D)             (None, 14, 14, 192)  245760      average_pooling2d_52[0][0]       
__________________________________________________________________________________________________
add_70 (Add)                    (None, 32, 32, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_69[0][0]                     
__________________________________________________________________________________________________
conv_pw_11_relu (ReLU)          (None, 32, 32, 512)  0           conv_pw_11_bn[0][0]              
__________________________________________________________________________________________________
batch_normalization_566 (BatchN (None, 14, 14, 320)  960         conv2d_566[0][0]                 
__________________________________________________________________________________________________
activation_548 (Activation)     (None, 14, 14, 384)  0           batch_normalization_568[0][0]    
__________________________________________________________________________________________________
activation_549 (Activation)     (None, 14, 14, 384)  0           batch_normalization_569[0][0]    
__________________________________________________________________________________________________
activation_552 (Activation)     (None, 14, 14, 384)  0           batch_normalization_572[0][0]    
__________________________________________________________________________________________________
activation_553 (Activation)     (None, 14, 14, 384)  0           batch_normalization_573[0][0]    
__________________________________________________________________________________________________
batch_normalization_574 (BatchN (None, 14, 14, 192)  576         conv2d_574[0][0]                 
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 32, 32, 728)  0           add_70[0][0]                     
__________________________________________________________________________________________________
conv_pad_12 (ZeroPadding2D)     (None, 33, 33, 512)  0           conv_pw_11_relu[0][0]            
__________________________________________________________________________________________________
activation_546 (Activation)     (None, 14, 14, 320)  0           batch_normalization_566[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 14, 14, 768)  0           activation_548[0][0]             
                                                                 activation_549[0][0]             
__________________________________________________________________________________________________
concatenate_10 (Concatenate)    (None, 14, 14, 768)  0           activation_552[0][0]             
                                                                 activation_553[0][0]             
__________________________________________________________________________________________________
activation_554 (Activation)     (None, 14, 14, 192)  0           batch_normalization_574[0][0]    
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 32, 32, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
conv_dw_12 (DepthwiseConv2D)    (None, 16, 16, 512)  4608        conv_pad_12[0][0]                
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 14, 14, 2048) 0           activation_546[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_10[0][0]             
                                                                 activation_554[0][0]             
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 32, 32, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
conv_dw_12_bn (BatchNormalizati (None, 16, 16, 512)  2048        conv_dw_12[0][0]                 
__________________________________________________________________________________________________
conv2d_579 (Conv2D)             (None, 14, 14, 448)  917504      mixed9[0][0]                     
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 32, 32, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
conv_dw_12_relu (ReLU)          (None, 16, 16, 512)  0           conv_dw_12_bn[0][0]              
__________________________________________________________________________________________________
batch_normalization_579 (BatchN (None, 14, 14, 448)  1344        conv2d_579[0][0]                 
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 32, 32, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
conv_pw_12 (Conv2D)             (None, 16, 16, 1024) 524288      conv_dw_12_relu[0][0]            
__________________________________________________________________________________________________
activation_559 (Activation)     (None, 14, 14, 448)  0           batch_normalization_579[0][0]    
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 32, 32, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_587 (Conv2D)             (None, 16, 16, 1024) 745472      add_70[0][0]                     
__________________________________________________________________________________________________
conv_pw_12_bn (BatchNormalizati (None, 16, 16, 1024) 4096        conv_pw_12[0][0]                 
__________________________________________________________________________________________________
conv2d_576 (Conv2D)             (None, 14, 14, 384)  786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_580 (Conv2D)             (None, 14, 14, 384)  1548288     activation_559[0][0]             
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 16, 16, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_587 (BatchN (None, 16, 16, 1024) 4096        conv2d_587[0][0]                 
__________________________________________________________________________________________________
conv_pw_12_relu (ReLU)          (None, 16, 16, 1024) 0           conv_pw_12_bn[0][0]              
__________________________________________________________________________________________________
batch_normalization_576 (BatchN (None, 14, 14, 384)  1152        conv2d_576[0][0]                 
__________________________________________________________________________________________________
batch_normalization_580 (BatchN (None, 14, 14, 384)  1152        conv2d_580[0][0]                 
__________________________________________________________________________________________________
add_71 (Add)                    (None, 16, 16, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_587[0][0]    
__________________________________________________________________________________________________
conv_dw_13 (DepthwiseConv2D)    (None, 16, 16, 1024) 9216        conv_pw_12_relu[0][0]            
__________________________________________________________________________________________________
activation_556 (Activation)     (None, 14, 14, 384)  0           batch_normalization_576[0][0]    
__________________________________________________________________________________________________
activation_560 (Activation)     (None, 14, 14, 384)  0           batch_normalization_580[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 16, 16, 1536) 1582080     add_71[0][0]                     
__________________________________________________________________________________________________
conv_dw_13_bn (BatchNormalizati (None, 16, 16, 1024) 4096        conv_dw_13[0][0]                 
__________________________________________________________________________________________________
conv2d_577 (Conv2D)             (None, 14, 14, 384)  442368      activation_556[0][0]             
__________________________________________________________________________________________________
conv2d_578 (Conv2D)             (None, 14, 14, 384)  442368      activation_556[0][0]             
__________________________________________________________________________________________________
conv2d_581 (Conv2D)             (None, 14, 14, 384)  442368      activation_560[0][0]             
__________________________________________________________________________________________________
conv2d_582 (Conv2D)             (None, 14, 14, 384)  442368      activation_560[0][0]             
__________________________________________________________________________________________________
average_pooling2d_53 (AveragePo (None, 14, 14, 2048) 0           mixed9[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 16, 16, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
conv_dw_13_relu (ReLU)          (None, 16, 16, 1024) 0           conv_dw_13_bn[0][0]              
__________________________________________________________________________________________________
conv2d_575 (Conv2D)             (None, 14, 14, 320)  655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_577 (BatchN (None, 14, 14, 384)  1152        conv2d_577[0][0]                 
__________________________________________________________________________________________________
batch_normalization_578 (BatchN (None, 14, 14, 384)  1152        conv2d_578[0][0]                 
__________________________________________________________________________________________________
batch_normalization_581 (BatchN (None, 14, 14, 384)  1152        conv2d_581[0][0]                 
__________________________________________________________________________________________________
batch_normalization_582 (BatchN (None, 14, 14, 384)  1152        conv2d_582[0][0]                 
__________________________________________________________________________________________________
conv2d_583 (Conv2D)             (None, 14, 14, 192)  393216      average_pooling2d_53[0][0]       
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 16, 16, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
conv_pw_13 (Conv2D)             (None, 16, 16, 1024) 1048576     conv_dw_13_relu[0][0]            
__________________________________________________________________________________________________
batch_normalization_575 (BatchN (None, 14, 14, 320)  960         conv2d_575[0][0]                 
__________________________________________________________________________________________________
activation_557 (Activation)     (None, 14, 14, 384)  0           batch_normalization_577[0][0]    
__________________________________________________________________________________________________
activation_558 (Activation)     (None, 14, 14, 384)  0           batch_normalization_578[0][0]    
__________________________________________________________________________________________________
activation_561 (Activation)     (None, 14, 14, 384)  0           batch_normalization_581[0][0]    
__________________________________________________________________________________________________
activation_562 (Activation)     (None, 14, 14, 384)  0           batch_normalization_582[0][0]    
__________________________________________________________________________________________________
batch_normalization_583 (BatchN (None, 14, 14, 192)  576         conv2d_583[0][0]                 
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 16, 16, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
conv_pw_13_bn (BatchNormalizati (None, 16, 16, 1024) 4096        conv_pw_13[0][0]                 
__________________________________________________________________________________________________
activation_555 (Activation)     (None, 14, 14, 320)  0           batch_normalization_575[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 14, 14, 768)  0           activation_557[0][0]             
                                                                 activation_558[0][0]             
__________________________________________________________________________________________________
concatenate_11 (Concatenate)    (None, 14, 14, 768)  0           activation_561[0][0]             
                                                                 activation_562[0][0]             
__________________________________________________________________________________________________
activation_563 (Activation)     (None, 14, 14, 192)  0           batch_normalization_583[0][0]    
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 16, 16, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
conv_pw_13_relu (ReLU)          (None, 16, 16, 1024) 0           conv_pw_13_bn[0][0]              
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 14, 14, 2048) 0           activation_555[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_11[0][0]             
                                                                 activation_563[0][0]             
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 16, 16, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_15 (Gl (None, 1024)         0           conv_pw_13_relu[0][0]            
__________________________________________________________________________________________________
global_average_pooling2d_16 (Gl (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
global_average_pooling2d_17 (Gl (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dense_15 (Dense)                (None, 2)            2050        global_average_pooling2d_15[0][0]
__________________________________________________________________________________________________
dense_16 (Dense)                (None, 2)            4098        global_average_pooling2d_16[0][0]
__________________________________________________________________________________________________
dense_17 (Dense)                (None, 2)            4098        global_average_pooling2d_17[0][0]
__________________________________________________________________________________________________
average_1 (Average)             (None, 2)            0           dense_15[0][0]                   
                                                                 dense_16[0][0]                   
                                                                 dense_17[0][0]                   
==================================================================================================
Total params: 45,903,374
Trainable params: 45,792,526
Non-trainable params: 110,848
__________________________________________________________________________________________________

10. Converting the .h5 File to .tflite File for the Python Interface Application

Working Flowchart:

import tensorflow as tf

saved_ensemble_model = tf.keras.models.load_model('/content/drive/MyDrive/dataset/ISIC Challenge 2017 Organized/FINAL SAVED OUTPUTS/FINAL_FILE_for_Soft_Computing_Project_Skin_Cancer.h5')
converter = tf.lite.TFLiteConverter.from_keras_model(saved_ensemble_model)
tflite_model = converter.convert()
open("FINAL_FILE_for_Interface_Soft_Computing_Project_Skin_Cancer.tflite", "wb").write(tflite_model)

WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
INFO:tensorflow:Assets written to: /tmp/tmpjins5vum/assets

183140620